Julie Schnipper
email: julie_schnipper@hotmail.com

Isabelle Dhennin-Duthille

Ahmed Ahidouch
email: ahidouch@gmail.com

Halima Ouadid-Ahidouch

Shu-Sang Nelson

Yee

Elena Lastraioli

Alessandra Fiorio Pla

Sa Kouba
email: sana.kouba@hotmail.com

Frédéric Hague

Alban Girault
email: alban.girault@u-picardie.fr

Pierre Rybarczyk
email: rybarczyk.pierre@chu-amiens.fr

Marie-Sophie Tellie

Stéphanie Guénin

Riad Tebbakha
email: tebbakha.riad@chu-amiens.fr

Henri Sevestre
email: henrisevestre@gmail.com

Stine Falsig Pedersen
email: sfpedersen@bio.ku.dk

Alban Giraul

Marie-Sophie Telliez
email: marie-sophie.telliez@u-picardie.fr

Jiayi Yao
email: jiayi.yao@bio.ku.dk

Dominika Czaplinska
email: dominika.czaplinska@bio.ku.dk

Renata Ialchina
email: renata.ialchina@bio.ku.dk

Bin Liu
email: liu@cancer.dk

Albin Sandelin

Stine Falsig Pedersen

5-phosphatase A 5hmC 5-hydroxymethylcytosine ACh Acetylcholine ADEX Aberrantly differentiated endocrine exocrine AKT Protein kinase B

Keywords: ion channels, exocrine pancreas, pancreatic ductal adenocarcinoma, signaling pathways, biomarkers pancreatic ductal adenocarcinoma, TRPC1, cell proliferation, spheroid growth, cell cycle progression, PI3K, calmodulin pancreatic ductal adenocarcinoma, tumor microenvironment, acid adaptation, Ca 2+ signaling, TRPC1, cell migration, cell proliferation, spheroid growth, cell cycle progression, PI3K, calmodulin

2-ABP 2-aminoethoxydiphenyl borate 5PTase

Polyphosphate-

profoundly grateful and who should be acknowledged for their invaluable contributions to this thesis work.

First, I would like to thank Prof. Laurent Counillon, Prof. Fabien Van Coppenolle, Prof. Luis Pardo, Dr. Sébastien Roger, Prof. Loic Garçon, and Prof. Henri Sevestre for agreeing to take part in my jury. Thank you in advance for showing interest in my research and for taking the time to evaluate and discuss my thesis and my following thesis defense.

I would like to thank my supervisor Prof. Halima Ouadid-Ahidouch for giving me the opportunity to carry out this thesis project in her laboratory. Thank you for challenging me and guiding me and for our many inspiring scientific discussions throughout the last three years. Your door has always been open to me, and even during my bad times, you have encouraged and supported me to work on. I am exceptionally thankful that you have welcomed and included me in your group as an international student, even though the French have challenged me. Again, thank you for taking good care of me during the lockdown and for our many travels we, after all, have had the opportunity to accomplish. I owe a special thank you to Prof. Stine Falsig Pedersen for welcoming me into her laboratory for my secondments during my Ph.D. I started my very early scientific career in your laboratory, and you inspired me to take this opportunity to go abroad, and you keep inspiring me. Thank you for always helping and caring for me, both scientifically and personally. Thanks to everyone in your group who always included me, no matter how long I had to stay. I wish to thank everyone in the AnaPath Department at CHU Amiens-Picardie. Especially thanks to Prof. Henri Sevestre for welcoming me with open arms and including me in the department and your family. It has been such a pleasure to work with you. Thank you for teaching me and encouraging me to work in pathology. Thank you for all our good times, even during the lockdown.

Thanks to Dr. Pierre Rybarczyk for taking the time to analyze many IHC slides with me during the years and for some great moments meanwhile. Thanks to Dr. Riad Tebbakha for taking care of all administration related to ethical procedures during this project, and thank you for warmly welcoming me to the AnaPath. Here, I would also like to thank Marie-Pierre Mabille for carrying out the experimental procedures during this Ph.D., and for being brave to try to work with me in English.

I would like to thank everyone in LPCM for welcoming me and making an effort to work with me in English.

Especially thanks to Marie-Sophie Telliez, who helped me with all experimental procedures during my Ph.D.

Thank you for some good moments. It has been a pleasure and challenging (I think for both of us), but at least we have tried to collaborate in English and French. Thanks to Lucille Dubuisson for taking very good care of me and installing me in Amiens, when I arrived back in 2019, I could not have integrated so well without your help all along. Also, thanks to Nathalie Guingand for the administrative help the last year. Thanks to Dr. Alban Girault for helping me out experimentally with biotinylation assays and scientific discussions and personally for cheering on me during the ups and downs. Thanks to Dr. Frédéric Hague for helping me with calcium imaging and scientific debates, where you have always made great perspectives of my work, encouraging me to think of further experiments to do, and personally, thanks for joking and cheering in the early mornings.

Thanks to Dr. Sana Kouba for helping me with many experimental procedures, such as co-IP and PLA. No matter what, you have always been a great friend, smiling, laughing, and encouraging. Thanks to Prof. Mathieu Gautier, Dr. Isabelle Dhennin-Duthille, and Dr. Lise Rodat-Despoix for welcoming me and for scientific and personal encouragement during the years. I would also like to thank all the current and previous students, Mohamed, Julie, Melanie, Sarah, Riadh, Hiba, and Sylvie, for their support, help, and great time during the last three years.

Thanks to everyone at the CRRBM for help and collaboration the last three years. I owe a special thanks to Dr. Stéphanie Guénin for helping me with everything I needed during my daily laboratory work and for your friendship.

Moreover, I wish to thank all members, fellows, and PIs of the Marie Curie international training network pHioniC for their great friendship, collaborations, and all the memorable moments.

Thereby I would like to thank my family and friends who have been a part of my life for the last three years.

Especially thanks to my little sister, who cheered on me and helped me with whatever I needed help with, even with this distance between us. You have always been patient with me, made me brave, and stood by me all along. Thanks to my dear friend Ida, who has always supported me, taking her time to talk, discuss and listen to whatever I say. Thank you for still being as close, and even closer to me, as we have ever been.

I would like to dedicate this thesis and the last three years of work to my angel-Mom who raised me and gave me the strength and courage to take this path in my life. You have made me who I am.

Finally, my deepest thankfulness and appreciation to my better half, Mohamed. I am beyond grateful for everything you have done and still do for me, which words cannot describe. I am forever indebted to you. The pancreas is a transversally retroperitoneal organ in the abdomen, located posterior to the stomach. It weighs about 100 grams and is 14-23 cm long. It is divided into the head, neck, body, and tail. The head of the pancreas is located in the loop of the duodenum where it exits the stomach (Figure 1A). The neck and body lie posterior to the distal portion of the stomach, and the tail lies near the hilum of the spleen. The blood supply of the pancreatic head departs from the superior pancreatic duodenal artery (branches from the hepatic artery) and the inferior pancreatic duodenal artery (branches from the superior mesenteric artery). The tail of the pancreas is supplied through branches from the splenic artery. The venous blood from the head is drained into the superior mesenteric vein, and the blood from the body and tail is drained into the splenic veins, which both end up in the portal vein. The pancreatic ducts extend through the whole organ, from the tail to the head, where the principal duct (duct of Wirsung) and the accessory duct (duct of Santorini) merge with the distal common bile duct. These end up in the central pancreatic draining duct (papilla of Vater), which terminates in the second part of the duodenum. On the cellular level, the pancreas originates from the endodermal germ layer and is made up of two major types of tissue; the endocrine and the exocrine part (Figure 1D) [START_REF] Longnecker | Anatomy and Histology of the Pancreas. The Pancreapedia: Exocrine Pancreas Knowledge Base[END_REF][START_REF] Talathi | Anatomy, Abdomen and Pelvis[END_REF]).

The endocrine pancreas

The endocrine tissue of the pancreas is composed of the islets of Langerhans and looks like small islets under the microscope. More than a million islets of Langerhans are distributed all over the adult human pancreas, but these islets comprise only 1-2% of the pancreatic mass [START_REF] Longnecker | Anatomy and Histology of the Pancreas. The Pancreapedia: Exocrine Pancreas Knowledge Base[END_REF]. The islets of Langerhans consist of four cell types; the alpha, beta, and delta cells and pancreatic polypeptide cells (PP cells), which all secrete metabolic regulatory hormones into the bloodstream (Figure 1D). The alpha cells produce and secrete glucagon, the beta cells insulin, the delta cells somatostatin, and the PP cells pancreatic polypeptide (Figure 1D). The main deficiencies of the endocrine pancreas are type I or II diabetes mellitus, and the endocrine cells are also the source of pancreatic neuroendocrine tumors [START_REF] Bardeesy | Pancreatic cancer biology and genetics[END_REF][START_REF] Longnecker | Anatomy and Histology of the Pancreas. The Pancreapedia: Exocrine Pancreas Knowledge Base[END_REF][START_REF] Talathi | Anatomy, Abdomen and Pelvis[END_REF]).

The exocrine pancreas

The exocrine pancreas comprises more than 95% of the pancreatic volume and is responsible for producing and secreting pancreatic juices containing essential digestive enzymes and fluids to the intestine. The exocrine tissue contains mainly two cell types necessary for its function; acinar cells (make up >80% of the pancreatic mass) that produce the digestive enzymes and the duct cells, which add mucus and bicarbonate to the enzyme mixture (Figure 1B,C). The acini are arranged in an anastomosing tubular network, consisting of acinar and centroacinar cells forming a central lumen, which is the beginning of the branching duct system. The acinar cells are polarized in a basolateral and apical axis, and the secretory zymogen granules are stored in the apical domain. The zymogen granules contain precursors of pancreatic digestive enzymes, including lipases, alphaamylases, carboxypolypeptidase, trypsin, and chymotrypsin. In addition, the granules contain trypsin inhibitors preventing enzyme activation. The zymogen granules are continuously secreted, with the highest rate after a meal [START_REF] Bardeesy | Pancreatic cancer biology and genetics[END_REF][START_REF] Longnecker | Anatomy and Histology of the Pancreas. The Pancreapedia: Exocrine Pancreas Knowledge Base[END_REF][START_REF] Talathi | Anatomy, Abdomen and Pelvis[END_REF].

The lobules formed by the acinar cells are connected to the ductules, which are constructed of duct cells, transporting the secreted pancreatic enzymes to the major pancreatic duct ending in the duodenum. The acinar lobule ends, and the duct system begins with the centroacinar cells marking the transition between acinar and duct cells. The duct cells have several segments based on size and location, and the ducts have several cell types, including secretory, mucosal, and ciliated cells. The secretory duct cells start the branch of the ductal tree with small intercalated duct cells that join together and are sequentially followed by the intralobular, interlobular and interlobar duct segments. In humans, the interlobar ducts unite and form the principal duct (duct of Wirsung). The intercalated and intralobular ducts are the major sites of HCO3 -secretion. These cells contain a high number of mitochondria to meet the high energy demand of the transcellular HCO3 -and fluid secretion. In contrast, they have a relatively small amount of organelles required for protein secretion [START_REF] Bardeesy | Pancreatic cancer biology and genetics[END_REF][START_REF] Longnecker | Anatomy and Histology of the Pancreas. The Pancreapedia: Exocrine Pancreas Knowledge Base[END_REF][START_REF] Talathi | Anatomy, Abdomen and Pelvis[END_REF].

Additionally, the pancreas contains a third and minor cell type; the pancreatic stellate cells (PSCs). They are located both at the periacinar and periductal space or surrounding the islets of Langerhans, thus participating in the maintenance of the pancreatic tissue architecture [START_REF] Bachem | Identification, culture, and characterization of pancreatic stellate cells in rats and humans[END_REF][START_REF] Apte | Pancreatic stellate cells: a starring role in normal and diseased pancreas[END_REF], Zhou et al. 2019). [START_REF] Bardeesy | Pancreatic cancer biology and genetics[END_REF].

Figure 1. Graphical overview of the anatomy of the pancreas. A) Overview of the anatomy of the pancreas and the main ducts. B) Anatomy of the exocrine pancreas consisting of acini and ductal branches. C) A single acinus containing several acinar cells and centroacinar cells assembles into a duct. D) Overview of endocrine cells and how they are organized between acini (Modified from

Pancreatic fluid secretion and pH regulation

The functional unit formed by acinar and ductal cells secretes 1-2 L/day of pancreatic juice, an alkaline isotonic fluid containing several digestive enzymes, as described above (Lee et al. 2012). The high bicarbonate (HCO3 - ) concentration provides an optimal pH for the digestive enzymes and neutralizes the acidic chyme entering the duodenum from the stomach [START_REF] Hegyi | Pancreatic ductal bicarbonate secretion: challenge of the acinar Acid load[END_REF]. The pancreatic exocrine secretion is controlled by multiple neurohormonal inputs (Lee et al. 2012). The activation of acinar cells is regulated by Ca 2+ -mobilizing agents, whereas duct cells are primarily regulated by cyclic adenosine monophosphate (cAMP) generating receptors. The main stimulation of acinar cells is through receptors responding to the hormone cholecystokinin (CKK) and the neurotransmitter acetylcholine (ACh). In comparison, duct cells respond to a cholinergic vagal output and the hormone secretin. Both secretin and CCK are secreted by the duodenum and enter the pancreas from the bloodstream. The secretion of these hormones is due to the digestive phase the human body enters, during the intake of a meal, enhancing the pancreatic fluid secretion (Lee et al. 2012).

During the secretion of the pancreatic fluids, the acini and ductal cells performing net acid-base transport are exposed to very different extracellular pH values on the apical and basolateral membranes, respectively (Novak et al. 2013). At the luminal site of the pancreatic duct system, the acinar cells secrete an isotonic sodium chloride (NaCl) and proton (H + ) -rich fluid containing different digestive enzymes, which can decrease the luminal pH to 6.8 [START_REF] Hegyi | Pancreatic ductal bicarbonate secretion: challenge of the acinar Acid load[END_REF], Hegyi and Petersen 2013, Pallagi et al. 2015). In the duct cells, chloride Cl -stimulate the excretion of HCO3 -to produce an alkaline fluid that can contain up to 140 mM HCO3 -and increase the luminal pH to 8 (Ishiguro et al. 2012, Hegyi and Petersen 2013, Pallagi et al. 2015).

This HCO3 -secretion is regulated by ion channels and transporters along the pancreatic ducts.

Acini and ductal cells absorb ions in a periodic pattern, alternating between the resting and digestive phases. When the digestive phase is initiated, CCK or ACh can stimulate receptors (e.g., G-protein coupled receptors GPCRs) at the apical pole of acinar cells, which evokes a rise in the intracellular Ca 2+ concentration (Lee et al. 2012). The calcium (Ca 2+ ) signal activates a Cl -uptake across the basolateral membrane through sodium (Na + )-potassium (K + )-2Cl -cotransporters, which cooperate with the Ca 2+ -activated K + channels and the Na + /K + pump. The increased Ca 2+ concentration stimulates Ca 2+ -activated Cl -channels at the apical pole, producing Cl -and zymogen granules into the acinar lumen (Hegyi and Petersen 2013). Along with the Cl - transport is the Na + and water movement from the interstitial fluid to the acinar lumen through the leaky tight junctions. On the luminal side of the proximal duct cells, secretin stimulated rises of intracellular cAMP and high Cl -concentrations will activate the SLC26A6 Cl -/HCO3 -exchanger, secreting HCO3 -to the ductal lumen and absorb Cl -. As the Cl -concentrations fall and the HCO3 -concentration rises in the distal part of the ducts, the SL26A6 approaches equilibrium, and the HCO3 -secretion will mainly be mediated by the cystic fibrosis transmembrane conductance regulator (CFTR) (Ishiguro et al. 2012). Indeed, a high load of HCO3 -from the basolateral side is required to satisfy the high demand for HCO3 -excretion. The HCO3 -are transported directly across the basolateral membrane into the duct cells through Na + /HCO3 cotransporters (NBCs) or indirectly by passive diffusion of carbon dioxide (CO2) through the cell membrane. CO2 is converted to HCO3 -and H + by carbonic anhydrases (CAs) and HCO3 -. Thus, HCO3 -can be transported into the lumen, and a backward transport of H + to the basolateral membrane is maintained by Na + /H + exchangers (NHEs) and H + -ATPases (Figure 2) (Pallagi et al. 2015) (transporters are described in detail in the section 'pH regulatory transport proteins'). (Ishiguro et al. 2012).

Thus, under normal conditions, the production of H + and HCO3 -along the pancreatic duct system results in changing pH values of the pancreatic juices. The varying extracellular pH (pHo) challenges the buffer capacity of the cells in the pancreatic ducts and can result in a variable intracellular pH (pHi) landscape (Pedersen et al. 2017). The regulation of the pHi in pancreatic duct cells is maintained by ion transporters that contribute to cellular pH homeostasis. The major pH regulator is the NHEs. It is reported that NHEs contribute to pHi regulation of pancreatic ducts of different species, including rats, mice, guinea pigs, pigs, and human duct cell lines [START_REF] Novak | Fundamentals of Bicarbonate Secretion in Epithelia[END_REF]. One of the nine members of the NHE family, NHE1, is ubiquitously expressed and is often regarded as the central cellular acid extruder. Several studies indicate that NHE1 is localized on the basolateral membrane of pancreatic duct cells, contributing to normal duct function by regulating pHi [START_REF] Novak | Fundamentals of Bicarbonate Secretion in Epithelia[END_REF]. As described above, NBCs translocate HCO3 -into the cell, which alkalinizes the cytosol [START_REF] Bardeesy | Pancreatic cancer biology and genetics[END_REF]. One family of NBCs was cloned from the pancreas; pNBC (NBCe1B). This isoform was found in the basolateral membrane of human pancreatic duct cells. The isoform NBCn1 is also expressed in the pancreatic ductal cells of mice, but rather in the luminal membrane, where it probably regulates HCO3 -salvage [START_REF] Novak | Fundamentals of Bicarbonate Secretion in Epithelia[END_REF].

Additional pH regulators of pancreatic duct cells are the anion exchangers, which are expressed on the basolateral membrane. Not surprisingly have, other H + pumps (the V-ATPases and H + /K + -ATPases) shown to be involved in the regulation of pHi, however, with a relatively small contribution, compared to NHE1 (Novak and Praetorius 2020). As described above, the HCO3 -secretion creates alkaline apical conditions, where the pH 6.8 pH 8

H + Zymogen Granule

Interstitial pH pH 7. 36 7.31 extrusion of H + and CO2 across the basolateral membrane will create acidity. This phenomenon is proposed as the acid tide, reflecting pancreatic interstitial acidosis [START_REF] Rune | Diurnal variations in the acid-base balance of blood[END_REF][START_REF] Ashley | Pancreatic interstitial pH regulation: effects of secretory stimulation[END_REF], Novak et al. 2013).

Hallmarks of cancer

In a multicellular organism, cancer is defined as the abnormal growth of a (multi)clonal cell population, which can invade and degrade surrounding and distant tissue within the host to form secondary tumors [START_REF] Greaves | Clonal evolution in cancer[END_REF]. For this to occur, a cell displays six characteristics called the Hallmarks of cancer during its transformation from normal to malignant. These characteristics were described and classified by Hanahan and Weinberg in 2000 as (1) an unlimited potential to replicate; (2) resisting apoptosis; (3) sustaining proliferative signaling; (4) evasion of growth suppressors (5) inducing angiogenesis; and ( 6) activation of invading and metastatic processes. These six characteristics are now divided in two 14 subcategories (Figure 3) [START_REF] Hanahan | Hallmarks of Cancer: New Dimensions[END_REF]Weinberg 2011, Hanahan 2022).

Pancreatic carcinogenesis

On gross inspection, pancreatic ductal adenocarcinomas (PDAC) are a firm white-yellow mass with poorly detectable demarcates. The tumor is surrounded by a non-malignant pancreas showing fibrosis, atrophy, and dilated ducts due to obstructive effects during carcinoma expansion [START_REF] Ying | Genetics and biology of pancreatic ductal adenocarcinoma[END_REF]. On the microscopic level, PDAC presents a heterogeneous growth pattern with atypical tubular glands resembling small or medium-sized pancreatic ducts. The irregular tubular glands are embedded in a desmoplastic stroma consisting of stromal and inflammatory cells and extracellular matrix proteins, which all contribute to the aggressive behavior of these neoplasms (Figure 4) [START_REF] Haeberle | Pathology of pancreatic cancer[END_REF]. They are classified by well-, moderately-, or poorly differentiated PDAC. PDAC evolves from well-characterized precursor lesions, where the most widely described are the microscopic pancreatic intraepithelial neoplasia (PanIN), followed by the macroscopic cysts called the intraductal papillary mucinous neoplasm (IPMN) and the mucinous cystic neoplasm (MCN) [START_REF] Ying | Genetics and biology of pancreatic ductal adenocarcinoma[END_REF]. Precursor lesions are usually described as bearing the characteristics of ductal epithelial cells.

However, several studies support the notion that various cell types of the pancreas exhibiting the malignant potential of duct cells. For instance, acinar cells can, through a reprogramming process called acinar-toductal metaplasia, give rise to pancreatic cancer, which is often associated with the cell damage and inflammation that occurs during acute or chronic pancreatitis [START_REF] Ying | Genetics and biology of pancreatic ductal adenocarcinoma[END_REF].

The [START_REF] Morris | KRAS, Hedgehog, Wnt and the twisted developmental biology of pancreatic ductal adenocarcinoma[END_REF]).

The three steps of PDAC development and progression

• Initiation

A single cell can undergo genetic alterations of either intrinsic (DNA repair defects, inherited genetic mutations, reactive oxygen species) or extrinsic (environmental factors, such as radiation or chemical exposure) origin that the cell cannot repair. In most instances, this initiating mutation will lead to cell apoptosis or senescence or be lost owing to immune surveillance. If these mechanisms fail and the initiating mutation causes the cell to escape from senescence and immunosuppression or rather apoptosis, the cell will transform and continuously promotes its growth and survival advantages (Makohon-Moore and Iacobuzio-Donahue 2016). During cell transformation, two types of genes can be altered: (1) proto-oncogenes: gain-of-function mutation. Several oncogenes are known to code for growth factor receptors, transcription factors, and genes that initiate cell proliferation. (2) tumor-suppressor genes: loss of function mutation, meaning that the gene cannot exert its inhibitory effect [START_REF] Lee | Oncogenes and tumor suppressor genes[END_REF]. A well-known tumor suppressor gene is the TP53 gene, which is found in more than 50% of cancers, making it impossible for cells to repair DNA, undergo cell cycle arrest, and activate apoptosis [START_REF] Muller | p53 mutations in cancer[END_REF].

The oncogenic KRAS mutations are the best known to initiate PDAC development, as described for PanINs.

However, studies have shown that the mutation needs to be subsequently combined with the inactivation of the other tumor suppressor genes (TP53, CDK2NA, and SMAD4) to promote and maintain PDAC progression (Figure 7A) [START_REF] Grant | Molecular Pathogenesis of Pancreatic Cancer[END_REF]).

• Clonal expansion

The cell possessing the initiating mutation that selected it to survive and grow creates a clonal population defined by the presence of the driver gene mutation, which in PDAC will be an oncogenic KRAS mutation. As the cell population progressively grows in number and geographical space, the descendants gradually acquire additional driver and passenger mutations (as seen for PanINs) to increase the clonal heterogeneity of the neoplasm. This phase is known as the phase between the precancerous lesions (PanIN3) and the development of full-blown PDAC (Figure 7B) (Makohon-Moore and Iacobuzio-Donahue 2016).

• Progression

The ongoing clonal expansion can promote a population of neoplastic cells to escape through the basement membrane into the surrounding stroma. Degradation of the dense extracellular matrix (ECM) and immune infiltrates provide selective and adaptive forces that shape these cells into subclonal populations with high fitness advantages. The dissemination process from where a cell population breaks free from the primary neoplasm might be an ongoing process during tumor development. However, these cells possessing a high fitness may have the most excellent chance of migrating to and surviving in a new microenvironment, such as in the liver, lung, or peritoneum, all common metastatic sites of PDAC (Figure 7C) (Makohon-Moore and Iacobuzio-Donahue 2016).

Cell cycle regulation in PDAC

Eukaryotic cells reproduce themselves through a highly regulated series of events, collectively known as the eukaryotic cell cycle. These events include cell growth, replication of genetic material and organelles, and segregation of the genetic material and organelles to separate them into two different daughter cells. Every event in the cell cycle comprises a corresponding phase: the G1, S, G2, and M phases. The G1 phase prepares the cell for DNA synthesis; the chromosomes are replicated during the S phase. The G2 phase prepares for mitosis, which occurs during the M phase, where chromosomes are separated into two individual cells. The G phases have been referred to as Gap-phases, where visually, nothing is happening. However, the G phases are now known as Growth-phases as it was recognized that the cell uses this time to grow. Under favorable conditions, a somatic cell can remain in the G1 phase for half of the cell cycle time. Under stress conditions, this time is even longer, and some cells will remain outside the active division events, entering the so-called G0 phase. The length of the cell cycle is highly variable between cell types. Yet, in rapidly growing cells, such as cancer cells in culture, the cycle length is approximately 24 h (Lewis 2010).

Positive or negative regulating proteins control the cell cycle. Positive regulating proteins are the four cyclins and their belonging cyclin-dependent kinases (CDKs), which must undergo phosphorylation to be activated. The proteins form complexes responsible for the progress through the cell cycle, and the levels of the CDKs remain relatively stable while it is the concentration of the cyclins that fluctuates (Figure 8B). The levels of the cyclins are induced through transcriptional activation upon a receipt of the appropriate signal to move through the cell cycle, allowing the formation of the suitable cyclin/CDK complex. The different complexes are formed at specific points in the cell cycle, thus regulating individual checkpoints [START_REF] Lewis | Cell Cycle Control in Pancreatic Cancer Pathogenesis[END_REF].

The progression through the G1 phase of the cell cycle is regulated by the cyclin D/CDK4 and D/CDK6 complexes. Three types of cyclin D exist (D1, 2, and 3). Initially, cyclin D expression levels respond to external stimuli such as mitogens, inducing the transport of CDK4 and CDK6 into the nucleus. Cyclin D forms an active complex with CDK4 or CDK6, which can phosphorylate members of the retinoblastoma (Rb)

protein family [START_REF] Malumbres | Mammalian cyclin-dependent kinases[END_REF]. Rb proteins exert a negative regulation to repress transcription of cyclins by binding and modulating the activity of transcription factors of the E2F family. Once phosphorylated, Rb loses its affinity for E2F, and E2F-mediated transcription of cyclin E (E1 and 2), cyclin A (A1 and 2), and E2F itself is initiated. When cyclin E binds to CDK2, it provides a positive feedback loop by phosphorylating Rb [START_REF] Bertoli | Control of cell cycle transcription during G1 and S phases[END_REF]. The activity of the cyclin E/CDK2 complex is required for S phase progression. During the S phase, cyclin A levels rise, and cyclin E dissociates from CDK2, allowing cyclin A to bind, which is required for proper completion and exit from the S phase [START_REF] Malumbres | Mammalian cyclin-dependent kinases[END_REF].

During the G2 phase, cyclin A is degraded by ubiquitin-mediated proteolysis, whereas cyclin B (B1 and 2) are actively synthesized. When cyclin A is degraded, CDK1 forms a complex with cyclin B. This complex is thought to regulate several events during both the G2-M transition and through mitosis (Figure 8A) [START_REF] Malumbres | Mammalian cyclin-dependent kinases[END_REF].

• CDK inhibitors

The cyclin/CDKs complexes are regulated by inhibitory proteins, the so-called repressor proteins or CDK inhibitors (CDKIs). CDKIs act as allosteric inhibitors of the CDKs and block their kinase activity [START_REF] Kahl | Regulation of cell cycle progression by calcium/calmodulin-dependent pathways[END_REF]. The two groups of CKIs are; the (1) INK4 protein family (p15, p16, p18, and p19), which arrest cells in the G1 phase by binding to cyclin D/CDK complexes, and (2) the Cip/Kip (p21 and p27) protein family, which inhibit cyclin/CDK2 complexes, inducing both G1 and G2 cell cycle arrest. Another inhibitor of the G1/S transitions checkpoint is the TP53, which suppresses the transcriptional activation of the CDKI proteins Cip/Kip (p21 and p27). Cip/Kip proteins bind and inhibit the activity of cyclin E/CDK2 and cyclin A/CDK2 complexes, preventing the progression through the G1/S transition. In the M phase, the function of the cyclin B/CDK1 is activated upon the removal of inhibitory phosphates by the Cdc25 phosphatase, allowing cells to enter the M phase (Figure 8A) [START_REF] Lewis | Cell Cycle Control in Pancreatic Cancer Pathogenesis[END_REF]. downstream Raf, mitogen-activated protein kinase-activated protein kinases (MEK), and extracellular signalregulated kinase 1/2 (ERK1/2) (Figure 9). The activated kinases phosphorylate their targets to regulate cellular functions. Among them are transcription factors and other regulators implicated in the expression of cyclin/CDK and CDKIs [START_REF] Lewis | Cell Cycle Control in Pancreatic Cancer Pathogenesis[END_REF].

The second pathway activated by the Kras protein is the PI3K/AKT signaling pathway. The PI3K protein is overexpressed in 70% of PDAC cases [START_REF] Edling | Key role of phosphoinositide 3-kinase class IB in pancreatic cancer[END_REF], where the kinase AKT is consistently activated in 40% of all PDAC cell lines [START_REF] Bondar | Inhibition of the phosphatidylinositol 3'kinase-AKT pathway induces apoptosis in pancreatic carcinoma cells in vitro and in vivo[END_REF]. The constitutively active Ras can phosphorylate PI3K, which binds and phosphorylate phosphatidylinositol (4,5)-biphosphate (PIP2) to phosphatidylinositol (3,4,5)-trisphosphate (PIP3), activating AKT. One of the downstream targets of AKT is the mammalian target of rapamycin (mTOR) kinase, an essential regulator of several translation proteins involved in proliferation and survival (Figure 9). In addition, Kras can activate an anti-apoptotic signal, thus reducing the cell's ability to undergo cell death.

Figure 9. Schematic overview of the common genetic alterations that affect cell cycle progression and proliferation in PDAC [START_REF] Mizrahi | Pancreatic cancer[END_REF].

The INK4A (also mentioned as CDK2A) protein p16 inhibits CDK complexes and is frequently mutated in PDAC as early as in PanIN2 lesions, resulting in loss of function. p16 binds to cyclin D/CDK complexes and inhibits the Rb proteins at the G1/S checkpoint. Loss of p16 will eliminate its inhibitory function and allow the cells to continuously pass through this checkpoint, underscoring the relevance of the INK4A mutation in PDAC development [START_REF] Lewis | Cell Cycle Control in Pancreatic Cancer Pathogenesis[END_REF].

The tumor suppressor TP53, also frequently mutated in PDAC, is a target of p21. TP53 is a key proapoptotic regulator of apoptosis. When a cell becomes insensitive to apoptotic signals, it fails to undergo cell death. Thus, the evasion of apoptosis results in cell survival and the continued proliferation of cells. TP53 deficiency impairs cell death in response to apoptotic stimuli, blocks the senescence induced by oncogenes, and enhances the transformation of cells activated by oncogenes as KRAS. Emphasizing the relevance of TP53 in cell cycle progression, it has been found that TP53-deficient mice are more likely to develop spontaneous carcinogen-induced tumors and accelerate the development and metastatic potential of PDAC [START_REF] Hingorani | Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice[END_REF].

The canonical transforming growth factor β (TGFβ)/SMAD4 pathway plays a tumor suppressive role in the early stages of cancer by inducing cell cycle arrest and apoptosis. The activation of SMAD4 through

TGFβ serves its functions in the G1/S phase transition, as it promotes the transcription of the inhibitors p15 and p21. An early study reported that TGFβ failed to induce the expression of p21 in pancreatic cancer cell lines in the absence of SMAD4, resulting in enhanced cell growth [START_REF] Grau | Induction of p21waf1 expression and growth inhibition by transforming growth factor beta involve the tumor suppressor gene DPC4 in human pancreatic adenocarcinoma cells[END_REF].

Taken together, all the mutations appearing during PDAC development lead to uncontrolled cell cycle progression, hence PDAC growth and progression.

Metastatic properties of PDAC

During cancer progression, cells acquire aggressive properties to invade and spread to surrounding and distant tissues, where they can form secondary tumors, namely metastases [START_REF] Pantel | Dissecting the metastatic cascade[END_REF]Brakenhoff 2004, Quail and[START_REF] Quail | Microenvironmental regulation of tumor progression and metastasis[END_REF]. The steps of tumor metastasis concerning epithelial-derived carcinomas include loss of epithelial polarity, migration, and invasion of the ECM and surrounding tissue, intravasation into the blood and/or lymphatic vessels, survival here, and the extravasation and colonization at different organ sites [START_REF] Yilmaz | Mechanisms of motility in metastasizing cells[END_REF]Christofori 2010, Fares et al. 2020). The migratory and invasive abilities of cancer cells present essential parameters in the metastatic cascade. Several molecular pathways define distinct types of migration and invasion in a cancer cell-autonomous fashion, including single-cell amoeboid and mesenchymal migration and collective cell migration. For these processes to succeed, cancer cells lose their polarity and function to adhere to the ECM, allowing them to move (Figure 10) [START_REF] Bravo-Cordero | Directed cell invasion and migration during metastasis[END_REF]. In general, cancer cells acquire a migratory phenotype by undergoing epithelial-mesenchymal transition (EMT), which is a process associated with a profound reorganization of the cytoskeleton and focal adhesions in order to diminish cell-cell attachment and strengthen cell-matrix adhesions [START_REF] Bravo-Cordero | Directed cell invasion and migration during metastasis[END_REF][START_REF] Leggett | The epithelial-mesenchymal transition and the cytoskeleton in bioengineered systems[END_REF]. Here, the EMT process is described with respect to cancer cell migration. However, all epithelial cells can undergo EMT, which occurs during embryonic development, wound healing, and other diseases. The EMT process is initiated by inflammatory stimuli in the tumor microenvironment, such as growth factors, hypoxia, or acidosis, which act through developmental transcription factors (e.g., SNAIL, TWIST, and ZEB) to repress the expression of epithelial markers (e.g., E-cadherin and claudin) and induce the expression of mesenchymal markers (e.g., Ncadherin and vimentin) [START_REF] Yilmaz | Mechanisms of motility in metastasizing cells[END_REF]. A complete EMT occurs when the cancer cells undergo cytoskeletal reorganization, with a loss of apicobasal polarity and a gain of front-back polarity. In particular, the cells weaken their cell-cell junctions and form actin-rich protrusions at the leading edge [START_REF] Leggett | The epithelial-mesenchymal transition and the cytoskeleton in bioengineered systems[END_REF]. The formation of these protrusions is driven by localized actin polymerization and often occurs in response to chemotactic signals. Carcinoma cells in primary tumors will form protrusions called pseudopods and lamellipodia at the migrating front, allowing them to attach and crawl on the ECM fibers [START_REF] Yamaguchi | Cell migration in tumors[END_REF]. To migrate through the physical barrier of the dense ECM, cancer cells protrude invadopodia and podosomes. Invadopodia and podosomes are remarkably similar structures [START_REF] Yamaguchi | Cell migration in tumors[END_REF]). However, invadopodia formation is only observed in highly invasive cancer cells, thus implicated in tumor cell metastasis (Chen et al. 1994[START_REF] Yamaguchi | Cell migration in tumors[END_REF][START_REF] Bravo-Cordero | Directed cell invasion and migration during metastasis[END_REF], while podosomes are formed by monocyte-derived cells. Both can produce or exhibit matrix metalloproteases (MMPs) and plasminogen, which are responsible for ECM degradation, the intravasation to the vessels, and the extravasation, from where they locate to other organs [START_REF] Yamaguchi | Cell migration in tumors[END_REF][START_REF] Bravo-Cordero | Directed cell invasion and migration during metastasis[END_REF]. The Rho-family guanosine triphosphate (GTP)-ases are among many regulating proteins linked to motility and protrusion formation as they can activate signaling targets that direct upstream actin cytoskeleton-altering proteins. The most studied Rho-GTPases include RhoA, Rac1, and Cdc42 [START_REF] Bravo-Cordero | Directed cell invasion and migration during metastasis[END_REF]). 4) they extravade to a local or distant organ where they can (5) colonize and form metastasis (Generated with Biorender).

Genetic alterations and signaling causing PDAC metastasis

The metastatic potential of PDAC is one of the main reasons for the poor outcome of patients. Indeed, driver and passenger gene mutations are involved in these metastatic processes. Comparative analysis of primary PDAC tumors with matched metastatic tissue revealed that 90% of tissues had concordant driver gene mutations between the primary and metastatic material [START_REF] Yachida | Distant metastasis occurs late during the genetic evolution of pancreatic cancer[END_REF][START_REF] Yachida | Clinical significance of the genetic landscape of pancreatic cancer and implications for identification of potential long-term survivors[END_REF]. The number of mutational driver genes in a tumor correlated to the metastatic burden of the patients and disease-free survival [START_REF] Yachida | Clinical significance of the genetic landscape of pancreatic cancer and implications for identification of potential long-term survivors[END_REF]. Notably, TP53 and SMAD4 [START_REF] Iacobuzio-Donahue | DPC4 gene status of the primary carcinoma correlates with patterns of failure in patients with pancreatic cancer[END_REF][START_REF] Whatcott | Desmoplasia in Primary Tumors and Metastatic Lesions of Pancreatic Cancer[END_REF][START_REF] Grant | Molecular Pathogenesis of Pancreatic Cancer[END_REF]) mutations were associated with a higher metastatic burden and poor prognosis of PDAC patients, compared to KRAS and CDKN2A, which were related to oligometastases [START_REF] Yachida | Clinical significance of the genetic landscape of pancreatic cancer and implications for identification of potential long-term survivors[END_REF].

The KRAS mutations affect numerous downstream signaling pathways. One of them, as described before, is the PI3K/AKT/mTOR pathway, most often involved in cell proliferation and survival and less in migration and invasion. However, several studies have found that the PI3K pathway is involved in forming PDAC metastasis. In an orthotopic mouse model, the treatment with the PI3K inhibitor LY294002 decreased metastasis and tumor growth and increased tumor cell death [START_REF] Bondar | Inhibition of the phosphatidylinositol 3'kinase-AKT pathway induces apoptosis in pancreatic carcinoma cells in vitro and in vivo[END_REF]. Tumor intrinsic activation of PI3K signaling, in particular PI3Kα, has been associated with an inflammatory metastatic phenotype, which led to enhanced accumulation of protumorigenic-like macrophages in PDAC [START_REF] Thibault | Pancreatic cancer intrinsic PI3Kalpha activity accelerates metastasis and rewires macrophage component[END_REF]). In addition, inhibition of the PI3Kγ isoform in a mouse model with PDAC resulted in the reprogramming of immunosuppressive tumor-associated macrophages to promote T-cell-mediated anti-tumor immune response, which reduced PDAC metastasis and desmoplasia [START_REF] Kaneda | Macrophage PI3Kgamma Drives Pancreatic Ductal Adenocarcinoma Progression[END_REF]. Targeting PI3K/AKT and mTOR has proven more effective than targeting one alone [START_REF] Mehra | Targeting PI3K Pathway in Pancreatic Ductal Adenocarcinoma: Rationale and Progress[END_REF]. Treatment of PDAC cell lines with Urolithin A, a natural compound inhibiting PI3K/AKT and mTOR simultaneously, resulted in reduced migration, tumor growth, and proliferation in vitro, along with improving overall survival in a mouse model with highly aggressive PDAC [START_REF] Totiger | Urolithin A, a Novel Natural Compound to Target PI3K/AKT/mTOR Pathway in Pancreatic Cancer[END_REF]. These results suggest that PI3K signaling is also involved in migration, besides being involved in proliferation and survival.

ERK signaling is primarily associated with tumor growth. However, evidence has revealed that ERK signaling is a critical regulator of cell motility [START_REF] Tanimura | ERK signalling as a regulator of cell motility[END_REF], also in PDAC. Indeed, one study has shown that the MAPK signaling pathway was involved in PDAC migration upstream from several receptors, including the TGFβ-activated kinase 1 (Huang et al. 2017) and several isoforms of the β-Adrenergic receptor [START_REF] Huang | Norepinephrine stimulates pancreatic cancer cell proliferation, migration and invasion via beta-adrenergic receptor-dependent activation of P38/MAPK pathway[END_REF]. Yang et al. demonstrated that overexpression of KRAS decreased the expression of the tumor suppressor Raf kinase inhibitory protein (RKIP) and, through ERK activation, regulated EMT and migration of PANC-1 and SW1990 PDAC cell lines [START_REF] Yang | KRAS promotes tumor metastasis and chemoresistance by repressing RKIP via the MAPK-ERK pathway in pancreatic cancer[END_REF]. Furthermore, ERK has been shown

to regulate EMT and hence migration through the non-canonical SMAD4 pathway, indicating that the function of ERK can be controlled through other pathways than KRAS [START_REF] Derynck | Smad-dependent and Smad-independent pathways in TGF-beta family signalling[END_REF]Zhang 2003, Javadrashid et al. 2021).

Epidemiology of pancreatic cancer

PDAC accounts for more than 90% of pancreatic cancer cases. Other subtypes of pancreatic cancer include neuroendocrine tumors, acinar carcinoma, and pancreatic blastoma (Park et al. 2021). According to cancer statistics, it was estimated that in the 27 countries of the European Union (EU), approximately 111500 people (55000 males and 56500 females) will die from PDAC by 2025 [START_REF] Ferlay | More deaths from pancreatic cancer than breast cancer in the EU by 2017[END_REF]. In 2020, there were 14461 new cases and 13793 PDAC-related deaths in France (source; GLOBOCAN 2020). In 2020, the global number of incidences was 495773, and the number of deaths was 466003, indicating almost as many deaths as new cases. A systematic analysis showed that the incidences and deaths increased 2.3-fold from 1990 to 2017, reflecting that the number of incidences increased and the overall survival rate remains low. The 5-year survival rate of PDAC varies globally in different countries and regions but does not exceed 10%. PDAC is thought to be the second cause of cancer-related deaths in 2030, only surpassed by lung cancer (Figure 11) [START_REF] Rahib | Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States[END_REF]. The cause of PDAC is relatively unknown. Yet, many non-modifiable and modifiable risk factors are associated with the development of PDAC.

Non-modifiable risk factors -Age: the risk of developing PDAC increases with age, and new cases are most frequently diagnosed in patients between 65-74 years of age -Gender: the worldwide incidence and mortality of PDAC are higher among males than females -ABO blood group: different studies have found a significantly higher risk of developing PDAC in patients with A or AB blood types than those with type O.

-Genetic susceptibility and family history: hereditary PDACs include inherited cancer syndromes with a known germline mutation associated with an increased risk of PDAC and familial PDAC, with two or more cases within a family [START_REF] Chang | Screening and early detection of pancreatic cancer in high risk population[END_REF]. PDAC related to hereditary syndromes or familial PDAC occurrence accounts for about 10% of cases. The most known genetic mutations associated with an increased risk of PDAC development include CDKN2A (associated with familial atypical multiple mole melanoma), BRCA1/2) (associated with hereditary breast cancer ovarian cancer syndrome), and MLH1/MSH6/MSH2/PMS2 (associated with hereditary nonpolyposis colorectal carcinoma syndrome) and CFTR (associated with hereditary cystic fibrosis) (McWilliams et al. 2010[START_REF] Ghiorzo | Genetic predisposition to pancreatic cancer[END_REF], Cazacu et al. 2018[START_REF] Rawla | Epidemiology of Pancreatic Cancer: Global Trends, Etiology and Risk Factors[END_REF] -Diabetes mellitus and obesity: compared to patients without any form of diabetes (based on hyperglycemia), those who were recently diagnosed with diabetes had an almost 7-fold increased risk of developing PDAC (Huang et al. 2020). Furthermore, relevant studies have shown that obese patients have an increased risk of developing PDAC with a potentially worse outcome Modifiable risk-factors -Smoking: Cigarette smoking has the strongest positive association with the risk of developing cancer. A recent European case-control study showed that current smokers have a 72% higher risk of developing PDAC than never-smokers. Furthermore, 16% of all PDAC diagnoses could be avoided through tobacco preventive measures [START_REF] Molina-Montes | Pancreatic Cancer Risk in Relation to Lifetime Smoking Patterns, Tobacco Type, and Dose-Response Relationships[END_REF]. Tobacco smoking also increases the risk of developing PDAC in individuals with a family history of cancer [START_REF] Molina-Montes | Risk of pancreatic cancer associated with family history of cancer and other medical conditions by accounting for smoking among relatives[END_REF] -Alcohol: In general, there is no doubt that high alcohol consumption (more than three drinks per day) is associated with the risk of developing PDAC [START_REF] Rawla | Epidemiology of Pancreatic Cancer: Global Trends, Etiology and Risk Factors[END_REF] -Dietary factors: As a whole, consuming diets high in vegetables, fruits, and other plant-based foods can reduce the risk of developing PDAC, while a diet rich in meat and animal products can increase the risk of PDAC development [START_REF] Tsai | Environmental Risk Factors of Pancreatic Cancer[END_REF] -Pancreatitis: It has been reported that acute pancreatitis, an inflammatory disease of the exocrine pancreas, is associated with damage and necrosis of tissue [START_REF] Habtezion | Acute Pancreatitis: A Multifaceted Set of Organelle and Cellular Interactions[END_REF]. Furthermore, when acute pancreatitis progress to chronic pancreatitis, the risk of developing PDAC increases 9-fold, compared to patients with the first incidence of acute pancreatitis [START_REF] Rijkers | Risk of Pancreatic Cancer After a Primary Episode of Acute Pancreatitis[END_REF] 2. TNM Classification PDAC classification is based on the international cancer classification system developed by the American Joint Committee of Cancer (AJCC) [START_REF] Gress | Principles of Cancer Staging[END_REF]. It is defined as the tumor (T), node (N), metastasis (M) (TNM) staging system (Table 1):

-T; primary tumor is classified by existence, size, or extent of the tumor by a coefficient ranging from 0-4, where 0 assigns no evidence of a primary tumor -N; regional lymph nodes are classified by their existence and extent, ranging from 0-3 (0-2 in PDAC diagnosis), where 0 assigns no regional lymph node involvement with cancer -M; distant metastases specifies whether distant metastases are present and is classified by either 0 or 1, where the M1 category may be specified further, according to the location of metastases

Category Definition

T1

Tumor ≤2 cm in greatest dimension T1a Tumor ≤0.5 cm in greatest dimension T1b Tumor ≥0.5 cm and <1 in greatest dimension T1c Tumor 1-2 cm in greatest dimension T2 Tumor >2 and ≤4 cm in greatest dimension T3 Tumor >4 cm in greatest dimension T4 Tumor involves CA, SMA, and/or CHA regardless of size N1 Metastasis in 1-3 regional lymph nodes N2 Metastasis in ≥ 4 regional lymph nodes

M0

No metastasis in distant organ

M1 Metastasis in distant organ

Table 1 TNM Classification of PDAC. CA: celiac axis, SMA: superior mesenteric artery, CHA: common hepatic artery [START_REF] Gress | Principles of Cancer Staging[END_REF]).

Grade classification of PDAC

The grade of PDAC is classified by a qualitative assessment of histological material and describes the degree of tumor differentiation. It can reflect to which extent the tumor resembles the normal tissue and may provide important information on the risk of metastasis and prognosis. The grades range from 0-3 (Makohon-Moore and Iacobuzio-Donahue 2016).

- 'basal-like' or 'classical' type by RNA transcriptional analysis. The classical subtype is characterized by a higher level of differentiation, fibrosis, and inflammation. In contrast, the basal-like subtype is associated with loss of differentiation and a poorer clinical outcome [START_REF] Moffitt | Virtual microdissection identifies distinct tumor-and stroma-specific subtypes of pancreatic ductal adenocarcinoma[END_REF]. In 2016, another categorization of PDAC subtypes, based on genomic analysis, classified tumors into four distinct subtypes: the squamous, pancreatic progenitor, immunogenic, and aberrantly differentiated endocrine exocrine (ADEX) [START_REF] Bailey | Genomic analyses identify molecular subtypes of pancreatic cancer[END_REF].

Cross-study analysis suggested that the squamous, basal-like, and quasi-mesenchymal subtypes displayed similar molecular profiles and likely represented the same subset of PDAC tumors. Tumors categorized within these three subtypes were also similar in their clinical outcomes, possessing a poor prognosis and response to chemotherapy compared to the pancreatic progenitor or classical subtypes [START_REF] Mizrahi | Pancreatic cancer[END_REF]). The latest study, which has been categorizing PDAC subtypes, was made in 2018 [START_REF] Puleo | Stratification of Pancreatic Ductal Adenocarcinomas Based on Tumor and Microenvironment Features[END_REF]. Here, they confirmed the presence of the pancreatic progenitor, basal-like, squamous, and quasi-mesenchymal subtypes.

Further, they characterized the pancreatic tumor microenvironment and classified three additional subtypes: desmoplastic, immune classical, and stroma-activated [START_REF] Puleo | Stratification of Pancreatic Ductal Adenocarcinomas Based on Tumor and Microenvironment Features[END_REF]). However, the latter three are not yet evaluated for clinical implications.

Diagnosis and treatment

PDAC is often diagnosed at a late onset, and about 50% of patients present with distant metastasis at the time of diagnosis [START_REF] Mizrahi | Pancreatic cancer[END_REF]. There are no cardinal symptoms for PDAC, and to date, no recommendation exists for screening in asymptomatic adults. Many patients develop few if any, symptoms before the disease are advanced. Unfortunately, the symptoms of PDAC overlap with other benign or malignant conditions [START_REF] Loveday | Pancreatic cancer: An update on diagnosis and management[END_REF]. The patients often have non-specific complaints such as epigastric or back pain, nausea, bloating, abdominal fullness, or change in stool consistency. All symptoms are more frequently related to alternative benign causes than PDAC, which may delay the time of diagnosis. At the time of diagnosis, more specific symptoms occur, including abdominal and back pain, abnormal liver function herein, jaundice, newonset diabetes, dyspepsia, vomiting, nausea, and weight loss [START_REF] Loveday | Pancreatic cancer: An update on diagnosis and management[END_REF][START_REF] Mizrahi | Pancreatic cancer[END_REF]). The presentation of symptoms is often correlated with the location of the tumor within the pancreas. As 60-70% of PDACs arise from the pancreatic head or the body, these patients are more likely to develop painless jaundice caused by biliary obstruction [START_REF] Schmidt-Hansen | Symptoms of Pancreatic Cancer in Primary Care: A Systematic Review[END_REF]. However, the positive predictive value of jaundice for diagnosing PDAC is only 4-13% (Schmidt- [START_REF] Schmidt-Hansen | Symptoms of Pancreatic Cancer in Primary Care: A Systematic Review[END_REF]. Patients with tumors in the body of the pancreas tend to invade vascular structures such as the celiac, hepatic, and superior mesenteric vessels and the portal vein, which can all cause back pain. Tumors in the pancreatic tail often grow unrestricted due to fewer anatomical neighbors, thus presenting in an advanced stage at the time of diagnosis (Figure 12) [START_REF] Walter | Symptoms and patient factors associated with diagnostic intervals for pancreatic cancer (SYMPTOM pancreatic study): a prospective cohort study[END_REF].

The diagnosis of PDAC requires cross-sectional imaging, preferably computed tomography (CT), using a pancreas protocol, which carries a sensitivity of at least 90% [START_REF] Valls | Dual-phase helical CT of pancreatic adenocarcinoma: assessment of resectability before surgery[END_REF][START_REF] Al-Hawary | Pancreatic ductal adenocarcinoma radiology reporting template: consensus statement of the society of abdominal radiology and the american pancreatic association[END_REF].

Magnetic resonance imaging (MRI) can provide a detailed assessment of the biliary tract and has a high sensitivity in detecting liver sections [START_REF] Vachiranubhap | Magnetic resonance imaging of adenocarcinoma of the pancreas[END_REF]. Endoscopic ultrasound is a supplemental tool for identifying local lymph nodes and tumors in nearby vascular structures [START_REF] Dewitt | Comparison of endoscopic ultrasonography and multidetector computed tomography for detecting and staging pancreatic cancer[END_REF]). Positron emission tomography (PET)-CT scans are not routinely used in the diagnosis of PDAC but are considered when patients display a high risk for metastasis, which is detected by the serum marker carbohydrate antigen 19-19. The concentration of this antigen in the blood is proportional to the suspected high disease stage [START_REF] Mizrahi | Pancreatic cancer[END_REF].

At present, surgical resection remains the only treatment that offers curative potential. Local tumors can be defined as resectable, whereas borderline resectable and locally advanced PDAC are usually categorized as inoperable. Tumors arising in the pancreatic head are typically resected with a pancreaticoduodenectomy (Whipple procedure). This includes the resection of the pancreatic head, duodenum, proximal jejunum, a segment of the stomach, the common bile duct, and gall bladder. Tumors in the tail and body are usually resected with distal pancreatectomy combined with splenectomy (Park et al. 2021). FOLFIRINOX is given for individuals with a high functional status according to the Eastern Cooperative Oncology Group (ECOG) classifications, where performance status is ranged from 0-5, where 0 is fully active, and 5 is dead. Gemcitabine and capecitabine or gemcitabine alone are given to individuals with poor functional status, according to the ECOG. The main components of these chemotherapies are DNA-damaging agents directly affecting DNA synthesis and repair (oxaliplatin, irinotecan) and antimetabolites (gemcitabine and fluorouracil) (Park et al. 2021). Most clinical trials represent a modest prolongation of survival for PDAC patients treated with these chemotherapeutic agents. However, a recent clinical trial presenting 493 patients with resected PDAC, a low carbohydrate antigen 19-9 concentration, and a 0 or 1 in ECOG functional status, were randomized to receive six months of adjuvant FOLFIRINOX or gemcitabine [START_REF] Conroy | FOLFIRINOX or Gemcitabine as Adjuvant Therapy for Pancreatic Cancer[END_REF]. Here, patients receiving FOLFIRINOX had an overall survival of 54.4 months compared to 35 months in patients only treated with gemcitabine [START_REF] Conroy | FOLFIRINOX or Gemcitabine as Adjuvant Therapy for Pancreatic Cancer[END_REF].

Recently, novel therapies for PDAC patients started to evolve, and several clinical trials are ongoing to test immunotherapeutic combinations (Park et al. 2021). For instance, single-agent PD1-blockade (monoclonal antibody) has been approved for mismatch repair deficiency in any tumor by US Food and Drug Administration. Mismatch repair deficiencies occur in around 1% of patients with PDAC and are defined by either germline or somatic alterations or loss in mismatch repair deficiency genes such as MLH1 and MSH2.

Additionally, targeting immunosuppressive metabolite adenosine of the tumor microenvironment, using small molecule targeting agents (e.g., AB680) or antibody therapy (e.g., oleclumab) displays a novel metabolismdirected approach for targeting PDAC, and a Phase I study is ongoing [START_REF] Bendell | A phase I study to evaluate the safety and tolerability of AB680 combination therapy in participants with gastrointestinal malignancies[END_REF].

CHAPTER 2: The pancreatic tumor microenvironment and the involvement of pH in cancer progression

The pancreatic tumor microenvironment PDACs are solid tumors and constitute two major components: the pancreatic cancer cells and the tumor stroma. The desmoplastic stroma is heterogeneous and comprises both cellular and acellular components.

Among cellular components are the pancreatic PSCs, cancer-associated fibroblasts (CAFs), immune cells, endothelial cells, and cancer stem cells. The acellular characteristics include poor vascularization, low nutrient concentrations, increased inflammatory stress, high interstitial fluid pressure, stiffness of the ECM, hypoxia, and extracellular acidosis that in general are known to occur together [START_REF] Feig | The pancreas cancer microenvironment[END_REF], Pedersen et al. 2017[START_REF] Li | The Metabolism Symbiosis Between Pancreatic Cancer and Tumor Microenvironment[END_REF][START_REF] Truong | Pancreatic Cancer Microenvironment and Cellular Composition: Current Understandings and Therapeutic Approaches[END_REF][START_REF] Elingaard-Larsen | How Reciprocal Interactions Between the Tumor Microenvironment and Ion Transport Proteins Drive Cancer Progression[END_REF]. However, several studies demonstrate that H + accumulation occurs outside of regions with dioxygen (O2) depletion, for instance, in highly proliferative areas of the tumor-stroma border (Figure 13) (Helmlinger et al. 1997[START_REF] Fukumura | Hypoxia and acidosis independently up-regulate vascular endothelial growth factor transcription in brain tumors in vivo[END_REF], Rohani et al. 2019). Thus, the PDAC tumor microenvironment forms hostile conditions, and only adapted cells can survive, proliferate and exert other malignant effects (Boedtkjer and Pedersen 2020). The following section will focus on the importance of microenvironmental pH in cancer cell development and progression.

pH regulation in cancer progression

The cytosol of normal cells is usually slightly acidic (~7.0-7.2) due to the production of acid as a byproduct of metabolism and to the inward negative membrane potential that drives the influx of H + and efflux of negatively charged ions [START_REF] Casey | Sensors and regulators of intracellular pH[END_REF]. The pHi is determined by the combined effects of pH buffering capacity and ion carriers [START_REF] Casey | Sensors and regulators of intracellular pH[END_REF]) (see pH regulatory transport proteins). Precise and tight regulation of pHi is necessary as numerous essential processes are regulated by pH, including cell cycle progression, cell signaling, cell motility, cell volume, and cancer development and progression [START_REF] Casey | Sensors and regulators of intracellular pH[END_REF], Webb et al. 2011, Corbet and Feron 2017, Flinck et al. 2018, Boedtkjer and Pedersen 2020). Indeed, pH directly influences the activity of all proteins that undergo protonation [START_REF] Srivastava | Intracellular pH sensors: design principles and functional significance[END_REF][START_REF] Schonichen | Considering protonation as a posttranslational modification regulating protein structure and function[END_REF], White et al. 2017[START_REF] Swietach | What is pH regulation, and why do cancer cells need it?[END_REF], and these proteins appear to operate optimally near pH 7.3. Thus, it should be of interest to maintain a stable cytosolic pH near this level [START_REF] Swietach | What is pH regulation, and why do cancer cells need it?[END_REF].

In general, normal cells exhibit a pHi lower than the extracellular pH of ~7.4. However, in cancer cells, the pH gradient is reversed with a pHi of 7.1-7.6 (when measured at physiological pH) and a pHo in the range of 6.2-6.9 (Vaupel et al. 1989, Helmlinger et al. 1997, Swietach et al. 2014, Rohani et al. 2019, Boedtkjer and Pedersen 2020). The decline of pHo can promote a decrease of pHi to a similar extent as for normal cells. Thus, tumor cells in acidic areas will experience a very low pHo and are expected to exhibit a relatively low pHi (although higher than non-transformed cells in the same conditions). Whilst other cancer cells in areas with a neutral pH are expected to have a relatively high pHi (Boedtkjer and Pedersen 2020). The increase of pHi is a hallmark of transformed cells and is permissive for growth factor-induced proliferation, cell cycle progression, and differentiation [START_REF] Cardone | The role of disturbed pH dynamics and the Na+/H+ exchanger in metastasis[END_REF], Webb et al. 2011, Corbet and Feron 2017). The decreased pHo is known to promote ECM degradation leading to invasion and migration (Riemann et al. 2014[START_REF] Riemann | Acidosis Promotes Metastasis Formation by Enhancing Tumor Cell Motility[END_REF], Riemann et al. 2019[START_REF] Thews | Tumor pH and metastasis: a malignant process beyond hypoxia[END_REF]. The alkaline pHi of cancer cells can seem paradoxical, as high proliferative and glycolytic rates, caused by metabolic reprogramming, generate acid production as described below (Webb et al. 2011).

Metabolic reprogramming

Most normal cells generate the energy necessary for cellular processes primarily through oxidative phosphorylation. On the contrary, many cancer cells reprogram their energy production by limiting their energy metabolism mainly to glycolysis, even in the presence of oxygen, a state termed 'aerobic glycolysis' or 'the Warburg Effect' [START_REF] Warburg | On the origin of cancer cells[END_REF]) (Figure 14). Poor vascularization in desmoplastic solid tumors, such as PDAC, leads to inadequate O2 delivery and, subsequently, hypoxia, which limits oxidative phosphorylation (Hanahan and Weinberg 2011). The hypoxic response in cancer cells works pleiotropically by upregulating glucose transporters and enzymes of the glycolytic pathways, leading to increased glycolysis (Semenza 2010, Wicks and[START_REF] Wicks | Hypoxia-inducible factors: cancer progression and clinical translation[END_REF]. In addition, hypoxia increases levels of the transcription factors hypoxia-inducible factors (HIF1α and HIF2α), which, in turn, upregulates glycolysis [START_REF] Kroemer | Tumor cell metabolism: cancer's Achilles' heel[END_REF]Pouyssegur 2008, Semenza 2010). The increased glucose uptake and utilization in tumors are used in the diagnostic imaging technique PET, which uses the glucose analog tracer 18 fluorodeoxyglucose (FdG) to visualize primary and metastatic lesions by their glucose uptake, which depends on the rate of glycolysis [START_REF] Gatenby | Why do cancers have high aerobic glycolysis?[END_REF].

Even though aerobic glycolysis is far less efficient than oxidative phosphorylation given the relatively poor adenosine triphosphate (ATP) generation by glycolysis, glycolysis supplies highly proliferative cancer cells with biosynthetic precursors of nucleotides, proteins, and lipids which are needed to sustain tumor growth.

In fact, cancer cells can consume at least ten times more glucose than normal cells [START_REF] Icard | A global view of the biochemical pathways involved in the regulation of the metabolism of cancer cells[END_REF]Lincet 2012, Andersen et al. 2014). As mentioned above, several oncogenes and their related pathways favor the switch to aerobic glycolysis, including PI3K, mTOR, Myc, TP53, and the regulation of HIF. In addition, oncogenes can promote glycolysis. This is, for instance, true for KRAS, which upregulates glucose transporters and glycolytic enzymes [START_REF] Chen | Anticancer strategies based on the metabolic profile of tumor cells: therapeutic targeting of the Warburg effect[END_REF], Andersen et al. 2021). Concerning PDAC, a metabolic and transcriptional profiling study of 38 pancreatic cancer cell lines revealed that they belonged to a glycolytic subtype, defined by displaying high levels of gene expression and metabolites from the glycolytic, serine and pentose phosphate pathways [START_REF] Daemen | Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors[END_REF]. Another study showed an upregulation of glycolytic pathway genes in clinical resectable and metastatic PDAC samples. The samples classified as a glycolytic subtype showed amplification of the KRAS and Myc oncogenes, which further correlated with the basal, squamous, and quasi-mesenchymal molecular subtypes, associated with poor clinical outcomes [START_REF] Karasinska | Altered Gene Expression along the Glycolysis-Cholesterol Synthesis Axis Is Associated with Outcome in Pancreatic Cancer[END_REF], Andersen et al. 2021).

The increased proliferation combined with the glycolytic shift leads to large metabolic acid production.

The glucose metabolism through aerobic glycolysis will result in only 2 ATP per glucose molecule and a high amount of lactate and H + . In contrast, the metabolism of glucose to ATP from oxidative phosphorylation generates up to 36 ATPs per molecule of glucose and acid in the form of CO2 [START_REF] Andersen | Interactions of ion transporters and channels with cancer cell metabolism and the tumour microenvironment[END_REF]) (Figure 14). Adapted from [START_REF] Vander Heiden | Understanding the Warburg effect: the metabolic requirements of cell proliferation[END_REF] Thus, the metabolic acid production can be substantial in both hypoxic and oxidative parts of the tumor (Helmlinger et al. 1997, Rohani et al. 2019). The lack of blood supply in many tumor areas limits acid venting.

It causes an acid accumulation inside the cells, decreasing cell proliferation and cell death [START_REF] L'allemain | Growth factor action and intracellular pH regulation in fibroblasts. Evidence for a major role of the Na+/H+ antiport[END_REF][START_REF] Yamagata | The contribution of lactic acid to acidification of tumours: studies of variant cells lacking lactate dehydrogenase[END_REF][START_REF] Gatenby | Why do cancers have high aerobic glycolysis?[END_REF]. Hence, cancer cells need a robust pH regulatory system to overcome intracellular acidosis and to maintain an alkaline pHi permissive growth. To overcome this acidic burden, the pH-regulatory system facilitates CO2, HCO3 -and H + diffusion and transport across the plasma membrane (Damaghi et al. 2013[START_REF] Swietach | What is pH regulation, and why do cancer cells need it?[END_REF]).

pH regulatory transport proteins

The regulatory pH system of cancer cells is highly regulated by plasma membrane-localized acid-base transporters and the pH regulatory enzymes CAs (Figure 15).

• NHEs

The mammalian Na + /H + exchangers (NHEs) mediate the electroneutral exchange of extracellular Na + with intracellular H + in a 1:1 stoichiometry (Aronson 1985, Montrose and[START_REF] Montrose | Kinetics of Na+/H+ Exchange[END_REF]. It is a secondary active transporter driven by the inward-directed chemical Na + gradient maintained by the Na + /K + ATPase [START_REF] Skou | The Na,K-ATPase[END_REF][START_REF] Keener | Mathematical Physiology I: Cellular Physiology[END_REF][START_REF] Counillon | Na(+)/H(+) antiporter (NHE1) and lactate/H(+) symporters (MCTs) in pH homeostasis and cancer metabolism[END_REF][START_REF] Pedersen | The SLC9A-C Mammalian Na(+)/H(+) Exchanger Family: Molecules, Mechanisms, and Physiology[END_REF]. The NHE1 is a member of the Solute Carrier 9A (SLC9A) gene family and is expressed in essential all types of tissue and localizes to the basolateral membrane of epithelial cells. Other NHE isoforms are more tissue-specific, and their subcellular location differs [START_REF] Coupaye-Gerard | Biosynthesis and cell surface delivery of the NHE1 isoform of Na+/H+ exchanger in A6 cells[END_REF][START_REF] Peti-Peterdi | Macula densa Na(+)/H(+) exchange activities mediated by apical NHE2 and basolateral NHE4 isoforms[END_REF], Park et al. 2001[START_REF] Orlowski | Na+/H+ exchangers[END_REF][START_REF] Pedersen | The SLC9A-C Mammalian Na(+)/H(+) Exchanger Family: Molecules, Mechanisms, and Physiology[END_REF].

NHE1 remains the most widely studied among NHEs, both in the context of pH regulation and disease.

NHE1 is active when pHi acidifies and is nearly quiescent at physiological pH (unless activated by other stimuli such as mitogens and growth factors), keeping the pH in a narrow range (Stock andPedersen 2017, Pedersen and[START_REF] Pedersen | The SLC9A-C Mammalian Na(+)/H(+) Exchanger Family: Molecules, Mechanisms, and Physiology[END_REF]. This homeostatic pH regulation connects NHE1 to several physiological and pathophysiological functions. NHE1 has been linked to cancer progression, and upregulation of its expression and activity is often correlated with tumor malignancy [START_REF] Stock | Roles of pH and the Na(+)/H(+) exchanger NHE1 in cancer: From cell biology and animal models to an emerging translational perspective?[END_REF] through the roles of NHE1 in cell cycle progression (Flinck et al. 2018), proliferation [START_REF] Amith | The Na(+)/H(+) exchanger (NHE1) as a novel coadjuvant target in paclitaxel therapy of triple-negative breast cancer cells[END_REF], Andersen et al. 2016), invasion [START_REF] Cardone | A novel NHE1-centered signaling cassette drives epidermal growth factor receptor-dependent pancreatic tumor metastasis and is a target for combination therapy[END_REF], migration [START_REF] Stuwe | pH dependence of melanoma cell migration: protons extruded by NHE1 dominate protons of the bulk solution[END_REF][START_REF] Martin | Intracellular pH gradients in migrating cells[END_REF]), and apoptosis (Rich et al. 2000).

• NBCs

The electroneutral Na + /HCO3 --cotransporter NBCn1, moving 1 Na + and 1 HCO3 -from the extracellular space to the cytosol, is often co-expressed with NHE1 [START_REF] Boedtkjer | Physiology, pharmacology and pathophysiology of the pH regulatory transport proteins NHE1 and NBCn1: similarities, differences, and implications for cancer therapy[END_REF]). NBCn1 has a broad expression profile and belongs to the Solute Carrier 4A gene family, which consists of nine other members. However, NBCn1 is the isoform most widely studied concerning pHi regulation. NBCn1 extrudes acid secondarily by the uptake of HCO3 -which neutralizes cytosolic H + and converts it into H2O and CO2 with help from intracellular carbonic anhydrases (CA) [START_REF] Boedtkjer | Physiology, pharmacology and pathophysiology of the pH regulatory transport proteins NHE1 and NBCn1: similarities, differences, and implications for cancer therapy[END_REF]. When CO2 diffuses across the plasma membrane, it is then converted back to HCO3 -by membrane-bound extracellular facing CA and can be reutilized by NBCn1. NBCn1 is less studied than NHE1 in relation to cancer. However, NBCn1 protein is two-to threefold upregulated during breast cancer carcinogenesis and is the dominant mechanism of net acid extrusion in both murine and human breast cancer tissue [START_REF] Boedtkjer | Contribution of Na+,HCO3(-)-cotransport to cellular pH control in human breast cancer: a role for the breast cancer susceptibility locus NBCn1 (SLC4A7)[END_REF][START_REF] Gorbatenko | Regulation and roles of bicarbonate transporters in cancer[END_REF], Lee et al. 2015, Andersen et al. 2018). In addition, extracellular acidification (pH ≤ 6.8) upregulates the expression of NBCn1 in cultured rat hippocampal neurons, suggesting that NBCn1 not only regulates but also is a sensor of the tumor microenvironment [START_REF] Cooper | Sodium/bicarbonate cotransporter NBCn1/slc4a7 increases cytotoxicity in magnesium depletion in primary cultures of hippocampal neurons[END_REF]).

• MCTs

The consequence of high glycolytic activity is an increased production of lactate and H + . The monocarboxylate transporters (MCT) of the SLC16 family, where two isoforms (MCT1 and MCT4) contribute to acid extrusion by mediating electroneutral transport of 1 monocarboxylate and 1 H + [START_REF] Halestrap | The monocarboxylate transporter family--role and regulation[END_REF]. Both MCT1 and MCT4 mediate the co-transport of H + and monocarboxylates, such as lactate, pyruvate, and ketone bodies, across the plasma membrane, thus eliminating the acid load associated with increased glycolysis [START_REF] Halestrap | The monocarboxylate transporter family--role and regulation[END_REF]. The lactate concentration in the cytosol of tumor cells can reach levels as high as 40 mM [START_REF] Walenta | Lactate: mirror and motor of tumor malignancy[END_REF]. It has been proposed that both transporters are essential for tumor growth by mediating a continuous lactic efflux, thereby securing a sustained high glycolytic flow [START_REF] Halestrap | The monocarboxylate transporter family--role and regulation[END_REF]. MCT1 and MCT4 are upregulated in several cancers and have been linked to poor prognosis [START_REF] Felmlee | Monocarboxylate Transporters (SLC16): Function, Regulation, and Role in Health and Disease[END_REF]. Interestingly, the elevated lactate levels in the extracellular space can be a nutrient source for stroma cells or other cancer cells as long as they have access to oxygen. MCT1 in neighboring cells can take up and utilize lactate for energy production through oxidative metabolism [START_REF] Perez-Escuredo | Monocarboxylate transporters in the brain and in cancer[END_REF]).

• Vacuolar-type ATPase

The vacuolar-type (V)-ATPase, a member of the VATP6 family, is mainly located in lysosomes or late endosomes, where it ensures the H + flux into the lumen of these organelles to maintain an acidic pH, which is essential for their function [START_REF] Nishi | The vacuolar (H+)-ATPases--nature's most versatile proton pumps[END_REF]. However, the V-ATPase pump has been found in the plasma membrane of different cell types, including tumor cells [START_REF] Martinez-Zaguilan | Vacuolar-type H(+)-ATPases are functionally expressed in plasma membranes of human tumor cells[END_REF]). Here, it acidifies the extracellular space by extruding protons. It has been shown that the plasma membrane localization of this pump contributes to cell migration and invasion by facilitating a local acidic extracellular microenvironment (Sennoune et al. 2004, Sennoune et al. 2004[START_REF] Rojas | Vacuolar-type H+-ATPases at the plasma membrane regulate pH and cell migration in microvascular endothelial cells[END_REF][START_REF] Mcguire | Regulation of V-ATPase assembly and function of V-ATPases in tumor cell invasiveness[END_REF]).

Changes in pH shape PDAC development

As described above, metabolic reprogramming and poor vascularization lead to the acidic microenvironment, a hallmark of cancer carcinogenesis. Pedersen et al. hypothesized that the acid-base challenges that the epithelial cells in the normal pancreas are exposed to can facilitate cancer development (Pedersen et al. 2017) (Figure 16). The so-called acidic tide occurring in the interstitium when HCO3 -is secreted to neutralize the acidic pancreatic juice extruded by the acini (see section Pancreatic fluid secretion and pH regulation) could cause an acid preconditioning, which could increase the survival potential of cancer cells in the acidic tumor microenvironment (Pedersen, 2017). The alternating digestion phases that stimulate pancreatic HCO3 - secretion affect the interstitial pHo in a cyclic manner. At the onset of PDAC, either (1) decreased extracellular acidosis develops due to reduced transepithelial HCO3 -secretion along with reduced epithelial integrity; or (2) an inflammatory state is induced, such as chronic pancreatitis, where the epithelial environment is exposed to moderately increased and sustained acidity. Thus, the epithelial cells are constantly exposed to unstable pH conditions, which can contribute to the dormancy of premalignant stages of PDAC and favor proliferation, invasion, migration, metastasis, and resistance to chemotherapy (Pedersen et al. 2017).

Cellular adaptation to extracellular acidosis in carcinogenesis

It is now well established that the pHo of cancer cells is acidic and that this property is associated with aggressive behaviors of solid tumors. Early studies by Thomlinson and Gray reported that human tumors surrounded blood vessels as cords. As the tumor grew, the blood supply decreased, and the central region of the tumor became hypoxic, even though the diffusion distance of glucose remained [START_REF] Thomlinson | The histological structure of some human lung cancers and the possible implications for radiotherapy[END_REF]. As already described above, hypoxia upregulates glycolysis, thus acid extrusion is required to maintain the pHi, leading to the acidic pHo, which in turn can provide an evolutionary selection pressure and initiate adaptive responses in cancer cells, enhancing malignant and invasive phenotypes (Damaghi et al. 2015, Pillai et al. 2019[START_REF] Elingaard-Larsen | How Reciprocal Interactions Between the Tumor Microenvironment and Ion Transport Proteins Drive Cancer Progression[END_REF]. There is evidence that the acid-adapted phenotype may be particularly aggressive when the cancer cells encounter a less acidic environment (Robey et al. 2009, Riemann et al. 2014[START_REF] Riemann | Acidosis Promotes Metastasis Formation by Enhancing Tumor Cell Motility[END_REF], Boedtkjer and Pedersen 2020, de Bem Prunes et al. 2022). As described below, the mechanisms of adaptation to the acidic microenvironment are pleiotropic.

The adaptation and selection to the acidic environment will initially slow the growth of cancer cells.

Early studies have shown that strongly acidic pHo can cause double-stranded DNA breaks [START_REF] Morita | Clastogenicity of low pH to various cultured mammalian cells[END_REF], and recovery from DNA damage from other stressors is inhibited at acidic pHo, leading to the accumulation of chromosomal aberrations [START_REF] Jayanth | Effects of extracellular and intracellular pH on repair of potentially lethal damage, chromosome aberrations and DNA double-strand breaks in irradiated plateau-phase A549 cells[END_REF]. Furthermore, acidosis favors epigenetic changes and oncogenic mutations (Rohani et al. 2019, Boedtkjer andPedersen 2020). Thus, acidic stress may cause genetic instability and a risk of malignant transition. Acidic stress occurs in several precancerous inflammatory states, such as chronic pancreatitis, a known risk factor for PDAC development (Kirkegard et al. 2017). The dual roles of the acidic environment, inhibiting growth and increasing oncogenic mutations could explain why the PanINs can be dormant for years and subsequently turn into full-blown PDAC, suggesting that the preneoplastic cells adapt to the microenvironment and hence turn into a malignant state (Pedersen et al. 2017, Boedtkjer andPedersen 2020).

The genetic instability and accumulation of oncogenes caused by acid adaptation can lead to metabolic changes. Acidosis reduces the glycolytic rate, for instance, by inhibiting the rate-limiting enzyme phosphofructokinase [START_REF] Trivedi | Effect of pH on the kinetics of frog muscle phosphofructokinase[END_REF]Danforth 1966, Blaszczak andSwietach 2021), which can force cancer cells to rely more on oxidative phosphorylation and a shift towards glutamine and fatty acid metabolism. This shift can supply the cancer cells with the energy necessary for the high proliferative rate (Lamonte et al. 2013[START_REF] Corbet | Acidosis Drives the Reprogramming of Fatty Acid Metabolism in Cancer Cells through Changes in Mitochondrial and Histone Acetylation[END_REF], Wu et al. 2016, Boedtkjer and Pedersen 2020[START_REF] Dierge | Peroxidation of n-3 and n-6 polyunsaturated fatty acids in the acidic tumor environment leads to ferroptosis-mediated anticancer effects[END_REF][START_REF] Michl | CRISPR-Cas9 screen identifies oxidative phosphorylation as essential for cancer cell survival at low extracellular pH[END_REF].

The acidic microenvironment also facilitates cancer cells' invasion and migration properties. To initiate the invasive process and spread through blood and lymphatic vessels and subsequently infiltrate the surrounding tissue, cancer cells have to penetrate the ECM [START_REF] Riemann | Extracellular Acidosis Modulates the Expression of Epithelial-Mesenchymal Transition (EMT) Markers and Adhesion of Epithelial and Tumor Cells[END_REF]). This process is initiated by the aid of the acidic pHo, which activates (MMPs and cathepsins secreted from the cancer cells to the extracellular space to catalyze the degradation of the ECM [START_REF] Martin | Intracellular pH gradients in migrating cells[END_REF][START_REF] Kato | Acidic extracellular microenvironment and cancer[END_REF][START_REF] Stock | Roles of pH and the Na(+)/H(+) exchanger NHE1 in cancer: From cell biology and animal models to an emerging translational perspective?[END_REF], Sutoo et al. 2020). Additionally, the translocation of lysosomes to the plasma membrane where they fuse and release their acidic content is proposed to contribute to ECM remodeling and local invasion.

Here, it has been found that the lysosomal-associated membrane protein 2 (LAMP2) protects the plasma membrane from acid hydrolysis (Damaghi et al. 2015). Interestingly, local acidification is of more importance than total acidification, as it is the leading edge of the migrating cells that contribute to the ECM degradation process. Indeed, it has been shown that NHE1 alone or in a complex with NBCn1 and CAIX are located in invadopodia [START_REF] Busco | NHE1 promotes invadopodial ECM proteolysis through acidification of the peri-invadopodial space[END_REF], Boedtkjer et al. 2016). This acid-exporting machinery can establish an acidic pHo at the leading edge of the cell, which facilitates directional migration and, thereby, degradation of the ECM [START_REF] Busco | NHE1 promotes invadopodial ECM proteolysis through acidification of the peri-invadopodial space[END_REF], Boedtkjer et al. 2016).

Cells can undergo EMT that initiate invading and migratory processes. Acidosis stimulates epithelial cells to lose their apicobasal polarity and cell-cell adhesion, whereas they become mesenchymal-like and gain invasive and migratory properties [START_REF] Riemann | Extracellular Acidosis Modulates the Expression of Epithelial-Mesenchymal Transition (EMT) Markers and Adhesion of Epithelial and Tumor Cells[END_REF]. However, the underlying mechanisms are not fully understood. Indeed, it has been found that acidic pHo reduces the expression of E-cadherin and upregulates vimentin, N-cadherin, twist, and other EMT markers in breast cancer, lung cancer, prostate cancer, PDAC, and melanoma cells [START_REF] Suzuki | Acidic extracellular pH promotes epithelial mesenchymal transition in Lewis lung carcinoma model[END_REF][START_REF] Peppicelli | Extracellular acidity strengthens mesenchymal stem cells to promote melanoma progression[END_REF], Riemann et al. 2019[START_REF] Sadeghi | Integrative Analysis of Breast Cancer Cells Reveals an Epithelial-Mesenchymal Transition Role in Adaptation to Acidic Microenvironment[END_REF], Shin et al. 2020, Wu et al. 2022). Recently, several markers of EMT and invasion have been found dysregulated in PDAC cell lines, and their expression depended on the time of acidosis duration. The expression of E-cadherin was decreased after three weeks and completely abolished after 4-5 and 10-12 months of acid adaptation. The opposite effect was found on the expression of N-cadherin, SNAIL, fibronectin1, vimentin, and laminin (Wu et al. 2022).

Not surprisingly, the low pHo favors invasion in various cell types (Martinez-Zaguilan et al. 1996, Moellering et al. 2008, Estrella et al. 2013, Riemann et al. 2014). The effect can be ascribed to long-term acidosis as exposure to low pHo for as short as 24 h selects for invasive phenotypes in colorectal cancer and melanoma cells (Martinez-Zaguilan et al. 1996, Zhou et al. 2017). The hypothesis that acidic pH promotes invasion by H + diffusing from the proximal tumor and remodeling the adjacent tissue has been tested in vivo [START_REF] Rofstad | Acidic extracellular pH promotes experimental metastasis of human melanoma cells in athymic nude mice[END_REF], Estrella et al. 2013). Intravital microscopy of HCT116 tumors found that areas with low acidic pHo of peritumoral tissues corresponded to regions with the highest tumor invasion. In addition, tumors did not invade regions with normal pHo. Immunohistochemical (IHC) analysis revealed that the tumor edge showed an increased expression of NHE1 and the glucose transporter (GLUT1), both of which were associated with peritumoral acidosis (Estrella et al. 2013).

The invading process is accompanied by migration and may result in near or distant metastases.

Numerous studies have shown that acidic pH increases cell migration. In vitro, this was demonstrated by scratch and transwell assays or by time-lapse microscopy [START_REF] Chen | An acidic extracellular pH induces Src kinase-dependent loss of beta-catenin from the adherens junction[END_REF][START_REF] Parks | The Na(+)/HCO3(-) Co-Transporter SLC4A4 Plays a Role in Growth and Migration of Colon and Breast Cancer Cells[END_REF][START_REF] Peppicelli | Extracellular acidity strengthens mesenchymal stem cells to promote melanoma progression[END_REF], Peppicelli et al. 2017[START_REF] Wu | Acid-sensing ion channels contribute to the effect of extracellular acidosis on proliferation and migration of A549 cells[END_REF]. Enhanced migration was found in cells treated upon acute acidification, and long-term acidosis, including in PDAC cell lines [START_REF] Riemann | Acidosis Promotes Metastasis Formation by Enhancing Tumor Cell Motility[END_REF], Wu et al. 2022), suggesting enhanced migration is a long-lasting feature of tumor cells. Early and recent studies have shown that oxygen deficiency and hypoxia lead to a higher rate of distant metastases [START_REF] Ishikawa | Expression of hypoxic-inducible factor 1alpha predicts metastasis-free survival after radiation therapy alone in stage IIIB cervical squamous cell carcinoma[END_REF][START_REF] Chang | Hypoxia predicts aggressive growth and spontaneous metastasis formation from orthotopically grown primary xenografts of human pancreatic cancer[END_REF][START_REF] Schito | Hypoxic pathobiology of breast cancer metastasis[END_REF]. As described in the 'Metabolic reprogramming' section, hypoxia intensifies glycolytic metabolism, enhancing lactic acid and H + production. Lactate concentration can be measured using bioluminescence assays of cervical cancer. In this way, it was shown that primary tumors with a high level of intratumoral lactate exhibit a significantly higher rate of metastases [START_REF] Walenta | High lactate levels predict likelihood of metastases, tumor recurrence, and restricted patient survival in human cervical cancers[END_REF][START_REF] Ellingsen | The Microenvironment of Cervical Carcinoma Xenografts: Associations with Lymph Node Metastasis and Its Assessment by DCE-MRI[END_REF][START_REF] Walenta | Lactate-An Integrative Mirror of Cancer Metabolism[END_REF]. Regarding acidification, different outcomes have been found. In two studies on melanoma and prostate cancer cells, respectively, it was found that acid-primed tumor cells injected into a xenograft mouse model immediately after incubation increased the metastatic rate [START_REF] Rofstad | Acidic extracellular pH promotes experimental metastasis of human melanoma cells in athymic nude mice[END_REF], Riemann et al. 2014). In contrast, another study of sarcoma and melanoma cell mouse models found that cells incubated at pH 6.5 did not increase the number of lung metastases, except if they were re-cultured in physiological pH conditions for at least 24 h [START_REF] Schlappack | Glucose starvation and acidosis: effect on experimental metastatic potential, DNA content and MTX resistance of murine tumour cells[END_REF]). Furthermore, it has been found that primary tumors with low metastatic potential exhibit a homogeneous pH distribution, whereas primary tumors with a high metastatic potential exhibit low pH values in the tumor periphery [START_REF] Wang | Evaluating tumor metastatic potential by imaging intratumoral acidosis via pH-activatable near-infrared fluorescent probe[END_REF].

Even though the features of the increased glycolytic activity and upregulation of H + pumps lead to enhanced proliferation of cancer cells, it is well known that extracellular acidosis decreases pHi, which inhibits cell cycle progression and hence proliferation (Flinck et al. 2018, Boedtkjer andPedersen 2020). Thus, tight regulation and a transient increase in pHi are essential for progression through cell cycle-specific checkpoints [START_REF] Putney | Na-H exchange-dependent increase in intracellular pH times G2/M entry and transition[END_REF]Barber 2003, Flinck M et al. 2018). However, long-term acidosis will eventually select and adapt cancer cells to grow in an acidic environment (Pillai et al. 2019). For instance, PDAC cells lines grown in acidic pH (6.7) for 2-3 weeks accumulate in the G1 phase, whereas the number of cells in the S-phase is reduced, along with a reduced expression of CDK4, CDK6, Cyclin D1, Cyclin E, and an increase in p21 Kip1 .

When the same cells are cultured for a period of 4-5 months or 10-12 months, the expression of cell cycle regulating proteins and the number of cells in different cell cycle phases return to similar as for cells grown in pH 7.4 (Wu et al. 2022), indicating that cells can adapt their growth to the hostile acidic microenvironment.

Interestingly, dual roles can be attributed to the acidic pHo (Boedtkjer and Pedersen 2020). An acidic pHo can acidify pHi, thus limiting proliferation, but acidic pHo can also act directly on extracellular H + sensors such as GPCRs or acid-sensing ion channels (ASIC), which facilitate increased intracellular Ca 2+ levels that may conversely promote proliferation and growth (Zhu et al. 2017).

Taken together, these reports indicate that the reciprocal interactions between the tumor microenvironment and tumor cells affect cancer development and their ability to grow and metastasize to other organs (Figure 17). and other characteristics contributing to a malignant phenotype. Cancer cells can perform local invasion epithelial to mesenchymal transition (EMT), extracellular matrix (ECM) degradation, migration, and metastasis to distant organs, where they escape the immune system and exhibit enhanced survival potentials. Adapted from (Boedtkjer and Pedersen 2020).

To target cancer cells and kill them without side effects on normal cells, it is favorable to target characteristics of cancer cells that differ from normal cells [START_REF] Jin | The updated landscape of tumor microenvironment and drug repurposing[END_REF]. Increased glycolytic metabolism and the subsequent upregulation of acid extrusion, leading to acidic pHo, are shared features of most solid tumors [START_REF] Andersen | Interactions of ion transporters and channels with cancer cell metabolism and the tumour microenvironment[END_REF]. Thus, inhibition of cancer cell metabolism or direct targeting of the acidity has been proposed as promising strategies to selectively kill tumor cells [START_REF] Neri | Interfering with pH regulation in tumours as a therapeutic strategy[END_REF][START_REF] Porporato | Anticancer targets in the glycolytic metabolism of tumors: a comprehensive review[END_REF][START_REF] Parks | Disrupting proton dynamics and energy metabolism for cancer therapy[END_REF][START_REF] Margetis | Metabolic targeting of malignant tumors: a need for systemic approach[END_REF]). Hence, tumor acidosis is a relevant therapeutic target and can be approached by; 1) targeting acidity directly or indirectly by inhibiting acid-extruding transporters; 2) inhibiting the metabolic processes responsible for producing acids in the first place (Pillai et al. 2019). Several challenges exist for drug delivery to cancer cells due to the acidic, hypoxic, and poorly vascularized tumor microenvironment. Most of the commonly used chemotherapeutics are weak bases, and they become protonated in the acidic pHo of the tumor, which prevents the drugs from passively diffusing across the plasma membrane of the tumor and reaching the intracellular target [START_REF] Raghunand | Enhancement of chemotherapy by manipulation of tumour pH[END_REF][START_REF] Gerweck | Tumor pH controls the in vivo efficacy of weak acid and base chemotherapeutics[END_REF], Webb et al. 2011). This challenge could be circumvented by raising the pHo of solid tumors (Webb et al. 2011).

Oral buffers, such as NaHCO3, have been shown to increase the pHo of xenograft tumors without affecting the systemic pH balance. The increased tumor pHo reduced the formation of spontaneous metastases but did not decrease primary tumor growth (Robey et al. 2009). However, the issue with this so-called systemic buffer therapy where oral supplementation of NaHCO3 is given in humans is the required dose, which is too high for agreeable administration [START_REF] Yang | Does Baking Soda Function as a Magic Bullet for Patients With Cancer? A Mini Review[END_REF]. The systemic treatment could potentially be replaced by local delivery of bicarbonate [START_REF] Chao | A nonrandomized cohort and a randomized study of local control of large hepatocarcinoma by targeting intratumoral lactic acidosis[END_REF] as NaHCO3 treatment can increase the uptake of other conventional chemotherapies, such as doxorubicin and oxaliplatin [START_REF] Yang | Does Baking Soda Function as a Magic Bullet for Patients With Cancer? A Mini Review[END_REF].

The tumor acidity can also be targeted by inhibiting acid extruders, such as NHE1, NBCn1, MCTs, and the V-ATPase. This inhibition would lead to dual effects, as it would raise the pHo of tumors, allowing for more optimal conditions to distribute chemotherapeutic drugs, and the intracellular acid accumulation could enforce cancer cell death [START_REF] Reshkin | Paclitaxel induces apoptosis via protein kinase Aand p38 mitogen-activated protein-dependent inhibition of the Na+/H+ exchanger (NHE) NHE isoform 1 in human breast cancer cells[END_REF][START_REF] Lauritzen | NBCn1 and NHE1 expression and activity in DeltaNErbB2 receptor-expressing MCF-7 breast cancer cells: contributions to pHi regulation and chemotherapy resistance[END_REF][START_REF] Floch | CD147 subunit of lactate/H+ symporters MCT1 and hypoxia-inducible MCT4 is critical for energetics and growth of glycolytic tumors[END_REF][START_REF] Amith | The Na(+)/H(+) exchanger (NHE1) as a novel coadjuvant target in paclitaxel therapy of triple-negative breast cancer cells[END_REF].

Targeting the glycolytic pathway can be done by inhibiting enzymes involved in glycolysis, such as glyceraldehyde phosphate dehydrogenase (GAPDH) or glucose-6-phosphate dehydrogenase (G6PDH), or by inhibiting the glucose uptake (Pillai et al. 2019).

Collectively, tumor acidosis offers the prospect that treatments interfering with pH as a target have great potential, both directly and to optimize the conditions for conventional chemotherapy.

CHAPTER 3: Ion channels and calcium homeostasis in the pancreatic tumor microenvironment

Ion channels in the pancreas and PDAC Ion channels are transmembrane proteins that form aqueous pores across the plasma membrane. Open pores provide a low resistance pathway for ion movement down a concentration gradient. Ion channels are, in general, classified by their ion permeability (e.g., Ca 2+ , K + , Na + , Cl -, or non-selective) [START_REF] Niemeyer | Ion channels in health and disease. 83rd Boehringer Ingelheim Fonds International Titisee Conference[END_REF].

Accordingly, ion channels provide signaling and modulation of transmembrane solutes and water, and each cell expresses hundreds to thousands of channels that differ according to the cell and tissue requirements (Niemeyer et al. 2001, Gouaux andMackinnon 2005). On a cellular level, the redistribution of ions changes electrical and chemical properties, which regulates numerous cellular processes, including; cell volume, transcription, and intracellular signaling and trafficking. These processes are tightly regulated to ensure normal tissue homeostasis through cell cycle progression, proliferation, invasion, migration, and apoptosis (Chen et al. 1994, Stock andSchwab 2015).

In the exocrine pancreas, ion channels, in cooperation with transporters, mainly contribute to the secretion of enzymes and bicarbonate (as described in 'Pancreatic fluid secretion and pH regulation'). Thus, a correct ion channel and transporter distribution are needed to maintain accurate fluid secretion. An aberrant expression, distribution, and/or activity of ion channels are associated with several diseases, and the term 'channelopathies' has been widely used to describe these disorders [START_REF] Niemeyer | Ion channels in health and disease. 83rd Boehringer Ingelheim Fonds International Titisee Conference[END_REF], Kim 2014). While many channelopathies are associated with neuromuscular and cardiac diseases, many also affect epithelial cell and organ function. Classical channelopathies result from mutations in a gene coding for ion channel proteins (Kim 2014). These mutations result in under-or overexpression, non-function, or dysfunctional regulation of the corresponding ion channel protein. In the pancreas, an often occurring channelopathy is cystic fibrosis.

Mutations in the CFTR gene leads to altered Cl -and HCO3 -secretion, clotting of the ducts, pancreatic dysfunction, and eventually pancreatic insufficiency (McWilliams et al. 2010).

The abnormal regulation of ion channel expression and/or activity is also classified as a 'hallmark of cancer' (Hanahan and Weinberg 2011, Kim 2014, Prevarskaya et al. 2018[START_REF] Hanahan | Hallmarks of Cancer: New Dimensions[END_REF]). Thus, changes in the pancreas ion channel distribution, expression, and function can result in the malignant transformation from normal epithelial cells to full-blown PDAC (Pedersen et al. 2017, Schnipper et al. 2020). Several studies have found that ion channel dysregulation is involved in cellular processes driving PDAC progression. However, the comparison between the role of ion channels in the healthy pancreas and PDAC has never been synthesized.

Hence, we made a comprehensive review describing the localization and function of K + , Ca 2+ , Cl -, Aquaporin, and Na + channels in the healthy exocrine pancreas. Furthermore, we summarized the role of these ion channels in PDAC development and progression and how they can function as novel biomarkers of PDAC (Schnipper et al. 2020). In this thesis manuscript, we will be focusing on the role of Ca 2+ channels.

Calcium homeostasis

Ca 2+ is an essential element in the human body, and maintaining a constant free ionized Ca 2+ concentration is biologically necessary for the function of excitable and non-excitable tissues. Normal Ca 2+ concentrations in the body are tightly regulated by ion transport in the intestinal tract, kidneys, and bone. 99% of Ca 2+ in the human body is stored in the bones. Ca 2+ in the blood constitutes 50% in its free ionized form, and it is available for all tissues. The remaining 10% is combined with various anions, and 40% is bound to serum proteins, mainly albumin [START_REF] Maalouf | Calcium Homeostasis. Textbook of Endocrine Physiology[END_REF].

In its ionized form, Ca 2+ has a vital role in intracellular signaling processes, where it can regulate fertilization, differentiation, transcription, proliferation, cell death, protein phosphorylation, and migration (Berridge et al. 2000). In the exocrine pancreas, intracellular Ca 2+ plays a central role in regulating enzyme, HCO3 -, and fluid secretion (Petersen 2014). Fine-tuning of Ca 2+ levels is essential to avoid uncontrolled Ca 2+ release, Ca 2+ overload, and toxicity, which can lead to the development of several pathologies. A high concentration of Ca 2+ leads to subsequent harmful events, such as lipid and membrane damage or nucleic acid and protein aggregation [START_REF] Case | Evolution of calcium homeostasis: from birth of the first cell to an omnipresent signalling system[END_REF]). Thus, the precise intracellular Ca 2+ concentration is tightly regulated by various Ca 2+ transport proteins (ion channels, exchangers, and ATPases) and buffer proteins. Due to membrane impermeability, extracellular Ca 2+ concentrations are higher (1-2 mM) than intracellular Ca 2+ concentrations, which are maintained close to 100 nM but can reach 1 or 2 µM after stimulation [START_REF] Berridge | Calcium signalling: dynamics, homeostasis and remodelling[END_REF]. This increased intracellular Ca 2+ concentration is responsible for multiple Ca 2+ -dependent cellular processes. Two main pathways permit the increase of intracellular Ca 2+ ; (1) entry of extracellular Ca 2+ through channels permeable to Ca 2+ or exchangers, and (2) the release of Ca 2+ through the endoplasmic reticulum (ER)

or sarcoplasmic reticulum (SR), which are the central intracellular Ca 2+ reserves. The release from ER or SR occurs via stimulation of channel receptors, such as inositol triphosphate (IP3) receptors (IP3R) or ryanodine receptors (RyR). These two pathways are responsible for activating downstream Ca 2+ -dependent signaling and permit a spatiotemporal regulation of cellular processes (Berridge et al. 2000[START_REF] Berridge | Calcium signalling: dynamics, homeostasis and remodelling[END_REF]).

Calcium signaling in the pancreas

In pancreatic acinar and ductal cells, the intracellular increase of Ca 2+ is mainly evoked by ACh and CCK, respectively (Petersen 2014). This increase of intracellular Ca 2+ activates epithelial Ca 2+ -dependent K + and Cl - ion channels, which are required for the enzyme, HCO3 -, and fluid secretion (described in section Pancreatic fluid secretion and pH regulation). The binding of ACh or CCK to specific receptors activates phospholipase C β (PLCβ), which binds and hydrolyzes PIP2 in the plasma membrane, and releases IP3 and diacylglycerol.

IP3 binds to the IP3R in the membrane of ER, located in the apical pole of acinar cells, mediating a Ca 2+ wave to the basal pole. The IP3R stimulation promotes a Ca 2+ ER store depletion leading to clustering of the ER Ca 2+

sensor, the stromal interaction molecule 1 (STIM1), which activates store-operated channels (SOCs) and transient receptor potential (TRP) channels, leading to the Ca 2+ influx known as SOC entry (SOCE) Figure 18. Since the sustained elevation of intracellular Ca 2+ concentrations can be toxic, it is necessary to extrude Ca 2+ from the cytoplasm. In addition, also intracellular buffer proteins and organelles, such as the mitochondria, are involved in maintaining intracellular Ca 2+ homeostasis (Berridge et al. 2000).

This Ca 2+ homeostasis is general for most epithelial cells and is maintained by transmembrane ion channels, intracellular ion channels, pumps, and transporters, briefly described below and summarized in Figure 19.

Transmembrane calcium channels

The primary source of intracellular Ca 2+ is extracellular Ca 2+ , which is transported across the plasma membrane through activated ion channels. The electrochemical gradient allows the Ca 2+ influx from the extracellular space through different types of ion channels, classified according to the genes that encode their components and their functional properties:

Voltage-gated calcium channels (VGCCs) are present in the membrane of all excitable cells. VGCC are key signal transducers of electrical excitability, as they convert the electrical signal of the action potential in the cell membrane to intracellular Ca 2+ signals. Hence, regulated changes in the membrane potential and membrane depolarization will activate them, leading to the Ca 2+ entry regulating essential functions for excitable cells, such as contraction, transmitter release, hormone secretion, and gene transcription [START_REF] Zamponi | The Physiology, Pathology, and Pharmacology of Voltage-Gated Calcium Channels and Their Future Therapeutic Potential[END_REF]. These channels are classified into six subtypes: the L-, N-, P-, Q, R, and T-type. They are assembled by complexes of α1, β, γ, and α2-δ subunits, where the α1 is the pore-forming subunit, but confer more gating properties when co-expressed with α2δ subunit and especially the β-subunit [START_REF] Catterall | Voltage-gated calcium channels[END_REF].

VGCCs are mainly expressed in excitable cells, such as neurons and muscle cells, and endocrine cells.

However, they are found to be expressed in epithelial cells. Specifically, VGCCs are overexpressed in different epithelial-derived cancers (Tajada and Villalobos 2020).

Receptor-operated channels (ROCs) are directly gated by extracellular stimuli such as ligands. They are found in excitable cells responding to neurotransmitters and non-excitable cells responding to agonists such as ATP. They are provided with a cation-permeable pore that allows the influx of Ca 2+ [START_REF] Penner | Calcium influx and its control by calcium release[END_REF]. One type of ubiquitously expressed ROCs is the purinergic receptors which are ATP-gated; their activation is associated with increased intracellular Ca 2+ and cyclic AMP levels [START_REF] North | Molecular physiology of P2X receptors[END_REF]. Indeed, TRP channels can be activated as ROCs [START_REF] Pedersen | Transient receptor potential channels in mechanosensing and cell volume regulation[END_REF].

Second-messenger-operated channels (SMOCs) share many properties with ROC. The main difference is that SMOCs are gated by intracellular second messengers binding to G-proteins or messengers secondary to receptor stimulation [START_REF] Penner | Calcium influx and its control by calcium release[END_REF], leading to the entry of extracellular Ca 2+ . For instance, some TRP channels are activated by second messengers, such as diacylglycerol, which is the case for TRPC3, TRPC6, and TRPC7. In addition is the Arachidonate-Regulated Ca 2+ channel, in association with ORAI1, ORAI3, and STIM1, which are activated by arachidonic acid allowing Ca 2+ entry [START_REF] Penner | Calcium influx and its control by calcium release[END_REF].

SOCs are the main pathway for Ca 2+ entry in non-excitable cells, such as epithelial cells. As described above, these channels generate SOCE. Upon ER Ca 2+ store depletion from 700 µM to 200 µM (Alvarez andMontero 2002, Tajada andVillalobos 2020), cytoplasmic Ca 2+ concentration increases. This partial depletion of ER stores activates STIM1, which oligomerizes and interacts with plasma membrane-localized SOCs such as ORAI or TRP channels, allowing Ca 2+ influx. ORAI channels appear in three isoforms (ORAI1, ORAI2, and ORAI3) and are mainly involved in the inwardly Ca 2+ release-activated Ca 2+ (ICRAC) current [START_REF] Prakriya | Store-Operated Calcium Channels[END_REF]. STIM1 (and STIM2) are distributed in the ER-and plasma membrane and contain an EF-hand Ca 2+ binding domain, which binds free Ca 2+ ions, thus sensing the changes in Ca 2+ concentrations of the ER upon store depletion [START_REF] Grabmayr | STIM Proteins: An Ever-Expanding Family[END_REF].

TRP channels represent a large family of non-selective ion channels mainly expressed in the plasma membrane. They can form homo-and hetero-tetramers and are activated upon different stimuli. The mammalian TRP channels are grouped into seven subfamilies: The ankyrin (TRPA), canonical (TRPC), melastatin (TRPM), mucolipin (TRPML), polycystin (TRPP), vanilloid (TRPV), and NO-mechano-potential C (TRPN) [START_REF] Samanta | Transient Receptor Potential (TRP) Channels[END_REF]). The latter is only found in invertebrates and fish [START_REF] Nilius | The transient receptor potential family of ion channels[END_REF].

The role of TRP channels in mediating SOCE is a controversial issue. Certain members of the TRP family display properties similar to the operation of other SOCs. At least, TRPC1, TRPC3, TRPC6, and TRPV6 act as SOCs by interacting with STIM1 [START_REF] Trebak | The TRPC3/6/7 subfamily of cation channels[END_REF][START_REF] Vanden Abeele | Store-operated Ca2+ channels in prostate cancer epithelial cells: function, regulation, and role in carcinogenesis[END_REF]. However, the relationship of TRP channels to SOC is likely cell-specific and influenced by factors such as endogenous expression and their capability to form heteromultimeric structures [START_REF] Ong | Role of TRPC Channels in Store-Operated Calcium Entry[END_REF]).

Intracellular calcium channels

Intracellular organelles can function as Ca 2+ stores as they rapidly respond to the need for intracellular Ca 2+ . The main store of intracellular Ca 2+ is the ER. The release of Ca 2+ from the ER occurs mainly through the activation of the IP3R and RyR [START_REF] Mikoshiba | The IP3 receptor/Ca2+ channel and its cellular function[END_REF][START_REF] Van Petegem | Ryanodine receptors: structure and function[END_REF]. Even though the two receptors share sequence homology, their activation of them is distinct. The three IP3R isoforms (IP3R1, IP3R2, IP3R3) are mainly activated by IP3 as a product of the hydrolysis of PIP2 into IP3 and diacylglycerol, as described above.

In contrast, RyR, which also appears in three isoforms (RyR1, RyR2, and RyR3), is activated by low concentrations of Ca 2+ (in the µM range) or ryanodine (an alkaloid inhibitor only found in plants) [START_REF] Van Petegem | Ryanodine receptors: structure and function[END_REF]. The mitochondrial calcium uniporter (MCU) is responsible for the passage of Ca 2+ from the cytosol into mitochondria. MCUs are activated upon increased cytosolic Ca 2+ concentrations and a depolarization of the mitochondrial membrane (Marchi and Pinton 2014).

Calcium pumps and transporters

Besides, Ca 2+ channels, pumps, and transporters are essential to maintain the intracellular Ca 2+ concentration.

Indeed, Ca 2+ channels allow the influx of Ca 2+ , where transporters and pumps remove Ca 2+ from the cytosol by the extrusion across the plasma membrane or into organellar Ca 2+ stores. Together, these mechanisms restore basal Ca 2+ levels and prevent intracellular Ca 2+ overload. The removal of Ca 2+ requires energy in the form of ATP hydrolysis for Ca 2+ pumps or in the electrochemical gradient of other cations for transporters.

Both types of Ca 2+ removers have been characterized:

In the plasma membrane are two critical players in Ca 2+ removal described. The Na + /Ca 2+ exchange transporter (NCX) is a bi-directional transporter and removes Ca 2+ from the cytosol in exchange for three Na + into the cell. However, the transporter can, in specific modes, provide Ca 2+ entry [START_REF] Jeffs | The role of the Na(+)/Ca(2+) exchanger (NCX) in neurons following ischaemia[END_REF]). In addition, the plasma membrane Ca 2+ -ATPase (PMCA) pumps Ca 2+ /ATP in a 1:1 stoichiometry, which provides a high affinity but low capacity for Ca 2+ extrusion, compared to NCX [START_REF] Khananshvili | Sodium-calcium exchangers (NCX): molecular hallmarks underlying the tissuespecific and systemic functions[END_REF][START_REF] Krebs | The Plasma Membrane Calcium Pump (PMCA): Regulation of Cytosolic Ca(2+), Genetic Diversities and Its Role in Sub-plasma Membrane Microdomains[END_REF]. The two transporters cooperate in such a way as the PMCA ensures a cytosolic Ca 2+ concentration around the basal level, where the NCX eliminates significant rises of intracellular Ca 2+ [START_REF] Brini | The plasma membrane Ca(2)+ ATPase and the plasma membrane sodium calcium exchanger cooperate in the regulation of cell calcium[END_REF].

The ER and mitochondria, recognized as Ca 2+ stores, hold their own Ca 2+ transporters. Ca 2+ is constantly leaking from channels in the ER membrane. Still, the Ca 2+ concentration remains high due to the continuous activity of the ER/SR Ca 2+ -ATPases (SERCA) that recharge Ca 2+ stores by pumping two Ca 2+ for every hydrolyzed ATP molecule [START_REF] Periasamy | SERCA pump isoforms: their role in calcium transport and disease[END_REF]. In the mitochondria, the Ca 2+ uptake is provided by MCU and the Na + /Ca 2+ (NCLX) and Ca 2+ /H + (HCX) exchangers, respectively. The Golgiassociated secretory Ca 2+ ATPases (SPCAs) are responsible for loading the Golgi apparatus with Ca 2+ [START_REF] Vandecaetsbeek | The Ca2+ pumps of the endoplasmic reticulum and Golgi apparatus[END_REF].

Other calcium-binding proteins and processes

Besides ion channels, transporters, and pumps, other proteins maintain Ca 2+ homeostasis. Intracellular changes in Ca 2+ concentrations promote the binding of Ca 2+ to specific Ca 2+ binding proteins, modulating Ca 2+ signaling and the transduction of cellular signaling pathways [START_REF] Lewit-Bentley | EF-hand calcium-binding proteins[END_REF]. A common characteristic between all Ca 2+ binding proteins is the expression of the EF-hand Ca 2+ -binding domain, which forms a highaffinity binding site for Ca 2+ . Most EF-hand-containing proteins belong to a group of 'Ca 2+ sensors'; that is, binding Ca 2+ induces a conformational change, allowing them to interact with specific targets, such as downstream signaling pathways, in a Ca 2+ -dependent manner [START_REF] Kretsinger | Carp muscle calcium-binding protein. II. Structure determination and general description[END_REF]Nockolds 1973, Ikura 1996).

The Ca 2+ binding proteins can be divided into two families; buffer proteins and effector proteins. Buffer proteins do not work as Ca 2+ sensors. Depending on their affinity and kinetics, they function as 'Ca 2+ chelators' as they reduce the quantity of free Ca 2+ available in the cytosol, thus contributing to regulating the spatiotemporal aspects of Ca 2+ signaling [START_REF] Schwaller | Cytosolic Ca2+ buffers[END_REF]. Some intracellular buffer proteins are expressed in the cytosol (e.g., calretinin and calbindin), and others at the reticular level (e.g., calnexin and calreticulin).

Unlike buffer proteins, effector proteins work as Ca 2+ sensors and lead to conformational changes. Indeed, the binding of Ca 2+ to effector proteins as calmodulin (CaM) modifies the conformational architecture of the latter and transduces changes in Ca 2+ concentrations into cellular signals by binding to a range of target proteins [START_REF] Ikura | Calcium binding and conformational response in EF-hand proteins[END_REF][START_REF] Halling | Conserved properties of individual Ca2+-binding sites in calmodulin[END_REF]. S100 proteins are also essential Ca 2+ sensors. The activity of S100 proteins depends on Ca 2+ binding followed by conformational shifts. Interestingly, the expression of the subfamily S100P protein has been found to increase during the progression from PanIN to invasive adenocarcinoma, and it is used as a specific diagnostic marker of PDAC [START_REF] Deng | Usefulness of S100P in diagnosis of adenocarcinoma of pancreas on fine-needle aspiration biopsy specimens[END_REF][START_REF] Ezzat | The role of S100P and IMP3 in the cytologic diagnosis of pancreatic adenocarcinoma[END_REF].

Calcium in cellular processes

Focus on calcium and calcium channels in proliferation and migration

Ca 2+ is a universal second messenger that regulates numerous cellular processes, including cell proliferation and motility. The mechanism by which Ca 2+ regulates cell division and proliferation is by ( 1) acting directly on target proteins involved in cell cycle progression or (2) its effect can be mediated by Ca 2+ binding proteins, such as CaM [START_REF] Kahl | Regulation of cell cycle progression by calcium/calmodulin-dependent pathways[END_REF].

Early studies have demonstrated that the cell's ability to proliferate depends on its sensitivity to external Ca 2+ concentrations. Non-transformed cells are highly dependent, and neoplastic cells are less dependent on external Ca 2+ . Proliferating human or mouse non-transformed cells, incubated in a medium containing low extracellular Ca 2+ levels (10-60 µM) ceased cellular division and accumulated in the G1 phase [START_REF] Boynton | The different roles of serum and calcium in the control of proliferation of BALB/c 3T3 mouse cells[END_REF][START_REF] Hazelton | Calcium, magnesium, and growth control in the WI-38 human fibroblast cell[END_REF][START_REF] Whitfield | The regulation of cell proliferation by calcium and cyclic AMP[END_REF]). This G1 arrest was reversible in mouse fibroblasts, and returning to a medium with normal extracellular Ca 2+ levels (1.25 and 1.80 mM Ca 2+ ) enabled cells to undergo DNA synthesis within hours [START_REF] Boynton | The different roles of serum and calcium in the control of proliferation of BALB/c 3T3 mouse cells[END_REF]. Indeed, the cells were susceptible to Ca 2+ depletion at two points during the cell cycle: (1) in the early G1 phase and (2) near the G1/S boundary [START_REF] Boynton | The control of human WI-38 cell proliferation by extracellular calcium and its elimination by SV-40 virus-induced proliferative transformation[END_REF]. When human endothelial cells were stimulated with growth factors, the chelation of Ca 2+ (0.03 mM extracellular Ca 2+ ) would, at any time during the first eight hours after stimulation, result in inhibited DNA synthesis [START_REF] Takuwa | Ca2+/calmodulin is involved in growth factor-induced retinoblastoma gene product phosphorylation in human vascular endothelial cells[END_REF]. At any other time, after these eight hours, the depletion of Ca 2+ did not affect the ability of the cells to pass into the S-phase. Beyond these two critical time points, no further influx of extracellular Ca 2+ signal is required [START_REF] Reddy | Cell cycle: regulatory events in G1-->S transition of mammalian cells[END_REF], Capiod 2013). It was demonstrated 30 years ago that the Ca 2+ influx decreased during cell division, probably through uncoupling store depletion from SOCE [START_REF] Volpi | Intracellular elevations of free calcium induced by activation of histamine H1 receptors in interphase and mitotic HeLa cells: hormone signal transduction is altered during mitosis[END_REF]Berlin 1988, Preston et al. 1991), ORAI1 internalization during cell division [START_REF] Yu | Orai1 internalization and STIM1 clustering inhibition modulate SOCE inactivation during meiosis[END_REF], or STIM1 phosphorylation [START_REF] Smyth | Phosphorylation of STIM1 underlies suppression of store-operated calcium entry during mitosis[END_REF]). Since has it been confirmed, in several cell lines, that SOCE decreases during mitosis [START_REF] Tani | Cell cycle-dependent regulation of store-operated I(CRAC) and Mg2+-nucleotide-regulated MagNuM (TRPM7) currents[END_REF][START_REF] Russa | Microtubule remodeling mediates the inhibition of storeoperated calcium entry (SOCE) during mitosis in COS-7 cells[END_REF][START_REF] El Boustany | Differential roles of STIM1, STIM2 and Orai1 in the control of cell proliferation and SOCE amplitude in HEK293 cells[END_REF]. However, Ca 2+ transients released from intracellular stores are required for a cell to progress through the M-phase. Studies performed in sea urchin eggs and mammalian cells revealed that single Ca 2+ transients and sustained increases occur during pronuclear migration, envelope break-down, and the meta-and anaphase transition of mitosis and cytokinesis [START_REF] Kao | Active involvement of Ca2+ in mitotic progression of Swiss 3T3 fibroblasts[END_REF]). The cyclic increases in IP3 and IP3R generate this Ca 2+ release from internal stores [START_REF] Poenie | Changes of free calcium levels with stages of the cell division cycle[END_REF][START_REF] Kahl | Regulation of cell cycle progression by calcium/calmodulin-dependent pathways[END_REF], Hodeify et al. 2018). In general, cells need extracellular Ca 2+ levels, thus the influx of Ca 2+ , to control G1 and S-phase transitions, but it is not necessary during late S-phase and G2/M transitions. Here, cell division depends on the release of intracellular Ca 2+ (Hodeify et al. 2018).

Once intracellular Ca 2+ levels increase, Ca 2+ binding proteins such as CaM can propagate the signal [START_REF] Chin | Calmodulin: a prototypical calcium sensor[END_REF]. When CaM is activated, it binds to other proteins bearing CaM domains, including the family of Ca 2+ /CaM-kinases (CaMK). CaMK turns on different cellular downstream pathways mediated by transcription factors, such as nuclear factor of activated T-cells (NFAT) and nuclear factor kappa-lightchain-enhancer of activated B cells (NFκB), among others, which regulate gene expression of Cyclin/CDK complexes and other cell cycle relevant inhibitors (Figure 20A) (Berridge et al. 2000[START_REF] Humeau | Calcium signaling and cell cycle: Progression or death[END_REF].

Ca 2+ channels are needed for the influx of Ca 2+ to regulate the cell cycle. The link between Ca 2+ channel expression and proliferation was demonstrated in knockdown (KD) experiments, where many cases showed that the KD of several TRP channels and ORAI/STIM reduced Ca 2+ entry and hence cell cycle progression and proliferation (Borowiec et al. 2014) (Figure 20B). However, several exceptions are now found where reducing the expression of the channel has no effect on Ca 2+ entry, which provides evidence for additional channel functions, except for mediating Ca 2+ influx. The Ca 2+ -independent role of ion channels can, to some extent, explain the fact that untransformed cells exceed proliferative capacity in the presence of as little as 50-100 µM free Ca 2+ . Yet, transformed cells can proliferate even in the presence of only 20 µM Ca 2+ (Borowiec et al. 2014[START_REF] Humeau | Calcium signaling and cell cycle: Progression or death[END_REF]. ) and its consequence on cell cycle distribution (Modified from [START_REF] Kahl | Regulation of cell cycle progression by calcium/calmodulin-dependent pathways[END_REF] and (Borowiec et al. 2014).

A B

As for proliferation, Ca 2+ signaling is essential for regulating cell migration. Early and recent studies have shown that migrating eosinophils and embryonic lung fibroblasts display a front-to-rear end-increasing gradient of Ca 2+ concentrations [START_REF] Brundage | Calcium gradients underlying polarization and chemotaxis of eosinophils[END_REF][START_REF] Brundage | Chemotaxis of newt eosinophils: calcium regulation of chemotactic response[END_REF][START_REF] Wei | Calcium flickers steer cell migration[END_REF]. When chemoattractants are present or during cell turning, the Ca 2+ signals are enhanced, and the resting Ca 2+ concentration is elevated [START_REF] Brundage | Calcium gradients underlying polarization and chemotaxis of eosinophils[END_REF][START_REF] Brundage | Chemotaxis of newt eosinophils: calcium regulation of chemotactic response[END_REF][START_REF] Wei | Calcium flickers steer cell migration[END_REF]). The spatially and temporally patterned activation of local Ca 2+ concentrations affects cell migration in the form of Ca 2+dependent processes in the leading lamella (Figure 21) [START_REF] Wei | Calcium gradients underlying cell migration[END_REF]). Among many signaling pathways, Ca 2+ regulates actin-myosin-based cytoskeletal networks and integrin-based focal adhesion complexes. Ca 2+ can activate protein kinase C (PKC) and CaMK, which interact with actin, thus affecting its dynamics [START_REF] Ohta | Type II Ca2+/calmodulin-dependent protein kinase binds to actin filaments in a calmodulin-sensitive manner[END_REF][START_REF] Larsson | Protein kinase C and the regulation of the actin cytoskeleton[END_REF][START_REF] Hoffman | Calcium-calmodulin-dependent protein kinase II isoforms differentially impact the dynamics and structure of the actin cytoskeleton[END_REF]). In addition, Ca 2+ can regulate Rho GTPases and PI3K, which are essential for actin polymerization, and involved in cytoskeletal remodeling and adhesion formation (Holinstat et al. 2003, Evans and[START_REF] Evans | Ca2+ influx is an essential component of the positive-feedback loop that maintains leading-edge structure and activity in macrophages[END_REF]. Indeed, several TRP channels have been reported as contributors to cell migration and cancer metastasis (Canales Coutino and Mayor 2021).

Calcium in cancer

A focus on pancreatic cancer

It is well-established that Ca 2+ is one of the essential intracellular regulators of physiological and pathophysiological conditions, including cancer (Tajada and Villalobos 2020). Ca 2+ is involved in all tumor processes, from malignant transformation to the formation of metastases. The Ca 2+ signaling mechanism in terms of speed, amplitude, and spatio-temporal patterning results in interactions and crosstalk with other signaling pathways in cancer progression (Berridge et al. 2000). There is often a significant remodeling in the expression and function of the proteins directly involved in Ca 2+ signaling, for instance, ion channels [START_REF] Monteith | The calcium-cancer signalling nexus[END_REF]. Several ion channels, including Ca 2+ permeable, are associated with cell cycle progression, proliferation, apoptosis, invasion, and migration (Prevarskaya et al. 2018, Schnipper et al. 2020). However, the dysregulation of Ca 2+ channels in PDAC is less explored compared to other types of cancer, such as breastcervical-, and colorectal cancer (Chen et al. 2019) TRPV1 regulates the Epidermal growth factor receptor (EGFR) in PANC-1 cells, where a high expression of TRPV1 is associated with a decrease in EGFR expression and vice versa. The overexpression of TRPV1 leads to decrease proliferation through the MAPK signaling pathway. In contrast, another study has demonstrated that low expressions of TRPV1 reduce cell proliferation and induce cell proliferation (Hartel et al. 2006).

TRPV6 is overexpressed in human pancreatic cancer tissues and two PDAC cell lines, Capan2 and SW1990. Here, TRPV6 promotes cell cycle progression, proliferation, migration, invasion, and reduced apoptosis (Song et al. 2018). On the contrary, two other studies have found downregulation of TRPV6 in human PDAC samples and a PDAC cell line A818-6 grown in a highly malignant undifferentiated monolayer (Zaccagnino et al. 2016, Tawfik et al. 2020).

TRPM2, TRPM7, and TRPM8 are overexpressed in human PDAC samples and several cell lines, which drives cell cycle progression, proliferation, migration, and invasion (Yee et al. 2010, Rybarczyk et al. 2012, Cucu et al. 2014, Yee et al. 2014, Rybarczyk et al. 2017, Ulareanu et al. 2017). For TRPM7, are these processes usually regulated through Mg 2+ entry (Rybarczyk et al. 2012, Rybarczyk et al. 2017).

The VGCCs CaV2.1 and CaV3.1 are upregulated and downregulated, respectively, in human PDAC tissue; however, there is no evidence of how these channels are involved in PDAC progression (Zaccagnino et al. 2016).

Ca 2+ pumps and transporters are also known to be dysregulated in PDAC. MCU, SERCA, and several isoforms of PMCA and NCX are involved in PDAC progression [START_REF] Bettaieb | Ca(2+) Signaling and Its Potential Targeting in Pancreatic Ductal Carcinoma[END_REF]. Ca 2+ signaling affects the activity of other ion channels in the pancreas (described in Calcium signaling in the pancreas), Thus, Ca 2+activated channels or different types of ion channel families such as K + , Cl -, and Na + channels are dysregulated in PDAC, summarized in (Schnipper et al. 2020). In addition, it has been proposed that ion channels are a good target in cancer therapy, found in ovarian-, breast-, prostate-, and esophageal cancers (Prevarskaya et al. 2018).

Calcium channels in the tumor microenvironment TRPC6 is proposed to regulate autocrine stimulation of PSCs in hypoxic conditions [START_REF] Nielsen | TRPC6 channels modulate the response of pancreatic stellate cells to hypoxia[END_REF]. Ca 2+ entry through TRPC3 activates neighboring KCa3.1channels, which results in increased PDGFstimulated PSC migration [START_REF] Storck | Ion channels in control of pancreatic stellate cell migration[END_REF]. Furthermore, TRPV4 expression decreases in PSC when cultured under elevated ambient pressure, mimicking the conditions found in PDAC [START_REF] Sharma | TRPV4 regulates matrix stiffness and TGFbeta1-induced epithelial-mesenchymal transition[END_REF].

Several Ca 2+ channels have been found expressed in different cell types of the immune system, such as neutrophils, macrophages, T-cells, and B-lymphocytes. In these cell types, Ca 2+ channels also contribute to controlling cellular responses, which have been associated with PDAC progression and development [START_REF] Hofschroer | Ion Channels Orchestrate Pancreatic Ductal Adenocarcinoma Progression and Therapy[END_REF].

Taken together, Ca 2+ signaling through ion channels is essential for neighboring cells in the tumor microenvironment. Ca 2+ transients in the crosstalk between cells in the tumor microenvironment and PDAC cells could be vital for PDAC development and progression. As described before, the challenged pH gradient is a prominent factor in the tumor microenvironment.

Calcium and pH

Separately, pH and Ca 2+ regulate the same physiological processes equally, and disrupted homeostasis of both is involved in tumor progression. In addition, Ca 2+ and pH are linked together, and crosstalk between pHi and intracellular Ca 2+ exists [START_REF] Molinari | Role of protons in calcium signaling[END_REF]. In aqueous solutions, the solubility of calcium salts in water is pH-dependent since the H + competes with calcium for the same binding sites and can easily replace it [START_REF] Mccudden | pH-adjusted ionized calcium[END_REF]. The replacement of calcium to H + increases ionized Ca 2+ in the solution. Thus, in solution, H + reduces the binding affinity of ligands and promotes Ca 2+ release. This indicates a direct chemical interdependence between H + and Ca 2+ ions and that an increase in pH (alkalization) promotes the storage of bound calcium, decreasing the concentration of free Ca 2+ . In contrast, a decrease in pH (acidification) fosters the breaking/solubilization of bound calcium, hence increasing Ca 2+ concentrations [START_REF] Mccudden | pH-adjusted ionized calcium[END_REF]). An example of the relationship between ionized and bound calcium and changes in pH is illustrated in the blood (Figure 22). However, the interdependence of H + and Ca 2+ inside a cell should be considered part of the cell's overall metabolic system in the cytoplasm [START_REF] Molinari | Role of protons in calcium signaling[END_REF]. One could expect that acidification of the cytosol would increase intracellular Ca 2+ concentrations and that, on the other hand, alkalization would promote decreased intracellular Ca 2+ concentrations. However, the structure of the cell is highly complex, and due to various biological systems and processes, which control H + and Ca 2+ concentrations, they are modified according to the physiological needs of the cell. Hence, experimental studies do not demonstrate consistent results, and some studies show that increased Ca 2+ concentrations are produced by acidification in different cell systems [START_REF] Orchard | Acidosis facilitates spontaneous sarcoplasmic reticulum Ca2+ release in rat myocardium[END_REF][START_REF] Kim | Cellular mechanisms underlying calcium-proton interactions in cultured chick ventricular cells[END_REF][START_REF] Cairns | Changes in myoplasmic pH and calcium concentration during exposure to lactate in isolated rat ventricular myocytes[END_REF][START_REF] Daugirdas | Intracellular acidification associated with changes in free cytosolic calcium. Evidence for Ca2+/H+ exchange via a plasma membrane Ca(2+)-ATPase in vascular smooth muscle cells[END_REF][START_REF] Donoso | Luminal pH regulated calcium release kinetics in sarcoplasmic reticulum vesicles[END_REF][START_REF] Nishiguchi | Changes in intracellular Ca2+ concentration produced by the alteration of intracellular pH in rat parotid acinar cells[END_REF][START_REF] Gonzalez | Effect of intracellular pH on acetylcholine-induced Ca2+ waves in mouse pancreatic acinar cells[END_REF], Chen et al. 2001[START_REF] Thomas | The effects of HCl and CaCl(2) injections on intracellular calcium and pH in voltageclamped snail (Helix aspersa) neurons[END_REF][START_REF] Marin | Calcium dynamics during physiological acidification in Xenopus oocyte[END_REF][START_REF] Krizaj | Intracellular pH modulates inner segment calcium homeostasis in vertebrate photoreceptors[END_REF][START_REF] Swietach | Coupled Ca2+/H+ transport by cytoplasmic buffers regulates local Ca2+ and H+ ion signaling[END_REF][START_REF] Paillamanque | Effects of Fatty Acids on Intracellular [Ca2+], Mitochondrial Uncoupling and Apoptosis in Rat Pachytene Spermatocytes and Round Spermatids[END_REF], Hu et al. 2017[START_REF] Berra-Romani | Arachidonic Acid Evokes an Increase in Intracellular Ca(2+) Concentration and Nitric Oxide Production in Endothelial Cells from Human Brain Microcirculation[END_REF], Sun et al. 2021). Whilst other have shown that alkalization produces increased Ca 2+ concentrations [START_REF] Kiang | Effect of intracellular pH on cytosolic free [Ca2+] in human epidermoid A-431 cells[END_REF][START_REF] Guse | Ca2+ release and Ca2+ entry induced by rapid cytosolic alkalinization in Jurkat T-lymphocytes[END_REF][START_REF] Alfonso | Calcium-pH crosstalks in rat mast cells: cytosolic alkalinization, but not intracellular calcium release, is a sufficient signal for degranulation[END_REF][START_REF] Minelli | Ammonium triggers calcium elevation in cultured mouse microglial cells by initiating Ca(2+) release from thapsigargin-sensitive intracellular stores[END_REF][START_REF] Li | Intracellular alkalinization induces cytosolic Ca2+ increases by inhibiting sarco/endoplasmic reticulum Ca2+-ATPase (SERCA)[END_REF][START_REF] Chowdhury | Effects of differentiation on purinergic and neurotensin-mediated calcium signaling in human HT-29 colon cancer cells[END_REF]. Ionized

Ca 2+ indirectly has a role in the cytosolic pH [START_REF] Molinari | Role of protons in calcium signaling[END_REF]. When Ca 2+ influx is activated, PLC is hydrolyzed. PLCs are acidifying enzymes because when PLC hydrolyzes PIP2, it produces diacylglycerol, an alcohol, and IP3, an acid. IP3 is protonated and must completely dissociate to bring itself into balance with the pH of the cytosol (pH 7.2) and, therefore quickly release an H + . The same occurs when IP3 is further degraded to inositol 1,4 biphosphate by polyphosphate-5-phosphatase A (5PTase). The two hydrolysis events are likely interrelated and are a part of the mechanisms that control the influx of Ca 2+ through SOCs [START_REF] Molinari | Role of protons in calcium signaling[END_REF]. Thus, it can be hypothesized that Ca 2+ oscillations, in combination with other processes, originate from the diffusion of H + in the cytoplasm and the activation of Ca 2+ -dependent enzymes.

Early studies have been carried out regarding pancreatic cells, showing how pH affects Ca 2+ fluctuations.

These studies on isolated rat pancreatic acinar cells [START_REF] Speake | Modulation of calcium signals by intracellular pH in isolated rat pancreatic acinar cells[END_REF] showed that changing pH affected Ca 2+ signals. Indeed, cytosolic alkalization of non-stimulated acinar cells increased Ca 2+ release from intracellular stores, where acidification had no effect. On the contrary, when the acinar cells were agonist stimulated with either ACh or CCK, acidification enhanced Ca 2+ signals, whereas alkalization had an inhibitory effect [START_REF] Speake | Modulation of calcium signals by intracellular pH in isolated rat pancreatic acinar cells[END_REF]. In other studies, performed on rat pancreatic acinar cells, the authors found the opposite result, where extracellular acidification and intracellular alkalization had an inhibitory effect on Ca 2+ entry upon CCK stimulation. In contrast, extracellular alkalization and intracellular acidification enhanced the Ca 2+ entry [START_REF] Muallem | Modulation of agonist-activated calcium influx by extracellular pH in rat pancreatic acini[END_REF][START_REF] Tsunoda | Cytosolic free calcium spiking affected by intracellular pH change[END_REF]), leading to amylase secretion [START_REF] Tsunoda | Characterization of sustained [Ca2+]i increase in pancreatic acinar cells and its relation to amylase secretion[END_REF]). In mouse pancreatic acinar cells, acidification of the cytosol decreased Ca 2+ wave propagations upon ACh stimulation [START_REF] Gonzalez | Effect of intracellular pH on acetylcholine-induced Ca2+ waves in mouse pancreatic acinar cells[END_REF].

The interdependency between pH and Ca 2+ signaling in cancer models is less studied. In a colon carcinoma cell line, alkaline pHi release Ca 2+ from intracellular Ca 2+ stores via an IP3-independent mechanism, leading to activation of Ca 2+ influx. Acidic pHi could induce small and slow intracellular Ca 2+ changes. Furthermore, thapsigargin or carbachol stimulated Ca 2+ influxes were decreased upon acidification but enhanced by alkaline pHi changes [START_REF] Nitschke | The effect of intracellular pH on cytosolic Ca2+ in HT29 cells[END_REF]. In androgen-independent prostate cancer cells, ATP induced growth arrest by increasing Ca 2+ entry, leading to a rapid and sustained decrease of pHi. On the other hand, intracellular acidification reduces Ca 2+ release from ER and thus cell proliferation [START_REF] Humez | The role of intracellular pH in cell growth arrest induced by ATP[END_REF] (Petho et al. 2020). The same considerations have been made for Ca 2+ channels, which have been shown to be pH sensitive (Audero et al. 2022). As this thesis is mainly focused on TRP isoforms, these channels and their cooperative partners (ORAI/STIM) (Figure 23), as acid sensors will be briefly described here:

• TRPM Among different stimuli, some TRPM are sensitive to low pH. TRPM2 channel currents are completely inhibited by a pHi of 6 due to ion competition [START_REF] Starkus | Regulation of TRPM2 by extra-and intracellular calcium[END_REF] or conformational changes induced by H + binding [START_REF] Du | Modulation of TRPM2 by acidic pH and the underlying mechanisms for pH sensitivity[END_REF][START_REF] Yang | State-dependent inhibition of TRPM2 channel by acidic pH[END_REF]. TRPM6 and TRPM7 channel currents are also sensitive to acidosis.

However, the effect seems controversial as some studies have shown that both TRPM6 and TRPM7 are inhibited by acidic pHo, and others have shown that they are activated [START_REF] Jiang | Potentiation of TRPM7 inward currents by protons[END_REF][START_REF] Li | Molecular determinants of Mg2+ and Ca2+ permeability and pH sensitivity in TRPM6 and TRPM7[END_REF]).

• TRPC

In contrast to TRPM channels, some TRPC channels can be activated by acidic pH. Both TRPC4 and TRPC5 are activated by acidic pHo (6.5) but inhibited when pHo decreases below 6 and 5.5, respectively (Semtner et al. 2007, Holzer 2009). Activation of TRPC4 currents by acidosis is mediated by GPCRs and requires an increase in intracellular Ca 2+ concentrations (Thakur et al. 2020). On the contrary, TRPC5 can be activated directly by protonation and through GPCR activation (Semtner et al. 2007). Conversely to TRPC5 and TRPC4, TRPC6 currents are slightly inhibited by acidic pH. This modest inhibition could be explained by the lack of glutamate residues which are present in both TRPC4 and TRPC5 (Semtner et al. 2007).

• TRPV TRPV1 was the first TRP channel demonstrated to be activated by protonation. A direct effect of protons on channel opening occurs at pH ≤ 5.9. This proton-induced activation depends on glutamic acid and phenylalanine, and the negatively charged form of Glu is crucial for proton sensing [START_REF] Jordt | Acid potentiation of the capsaicin receptor determined by a key extracellular site[END_REF][START_REF] Aneiros | The biophysical and molecular basis of TRPV1 proton gating[END_REF], as seen for TRPC4 and TRPC5. Similar to TRPV1, TRPV4 is activated by an extracellular pH below 6 [START_REF] Suzuki | Impaired pressure sensation in mice lacking TRPV4[END_REF]).

• TRPA Less studied is the TRPA subfamily, which is activated by acidic pH in a concentration-dependent manner.

TRPA1 currents were induced until pH 5.4, and Ca 2+ influx was around 50% enhanced at pH 6.0 and 5.0 compared to pH 6.4, indicating that TRPA1 induces Ca 2+ entry upon acidification (de la Roche et al. 2013).

• ORAI/STIM complexes

In contrast to TRP channels, which show paradoxical results whether they are activated or inactivated by acidification, then it is well accepted that all three ORAI isoforms and at least STIM1 are inhibited by acidic pH's around 6 [START_REF] Yu | Regulation of Orai/STIM Channels by pH. Calcium Entry Channels in Non-Excitable Cells[END_REF], Audero et al. 2022). In addition, they are activated upon alkalization at a pH of about 8. Both effects have been studied in a wide range of cell lines and show that SOCE is decreased upon acidosis while enhanced by alkalization [START_REF] Scrimgeour | Glu(1)(0)(6) in the Orai1 pore contributes to fast Ca(2)(+)-dependent inactivation and pH dependence of Ca(2)(+) release-activated Ca(2)(+) (CRAC) current[END_REF][START_REF] Beck | Regulation of endogenous and heterologous Ca(2)(+) releaseactivated Ca(2)(+) currents by pH[END_REF]. Conserved intracellular and extracellular glutamate and histidine residues have been described as the pH sensitivity among all three ORAI isoforms [START_REF] Tsujikawa | Identification of key amino acid residues responsible for internal and external pH sensitivity of Orai1/STIM1 channels[END_REF]. In addition, negatively charged amino acid residues of STIM1 also seem responsible for the pHi-dependent inactivity of STIM1 [START_REF] Tsujikawa | Identification of key amino acid residues responsible for internal and external pH sensitivity of Orai1/STIM1 channels[END_REF]. Interestingly, a recent study has shown that ORAI1 and ORAI2 ICRAC amplitudes depend on pHi in the same manner, where ORAI3

ICRAC amplitude does not depend on pHi, suggesting that the pH sensitivity is different among the three ORAI isoforms [START_REF] Rychkov | Orai1-and Orai2-, but not Orai3-mediated ICRAC is regulated by intracellular pH[END_REF]. CHAPTER 4: The TRPC1 channel Classification of TRP channels TRP genes were first described in Drosophila melanogaster in 1969. Studies of this fruit fly's visual system identified a visually impaired mutant fly with a transient response to steady light instead of a sustained electroretinogram, which was recorded in the wild-type fly. Thus, the mutant was named transient receptor potential [START_REF] Cosens | Abnormal electroretinogram from a Drosophila mutant[END_REF]. However, it was not until 1989 that the trp gene was identified by [START_REF] Montell | Molecular characterization of the Drosophila trp locus: a putative integral membrane protein required for phototransduction[END_REF]. To date, more than 100 trp genes have been identified across species, including 28 mammalian TRP genes. This superfamily is divided into seven subfamilies (mentioned in Transmembrane calcium channels), where the number of channels within one subfamily varies. They are distinguished from one another based on differences in their primary amino acid sequence rather than ligand affinity or selectivity [START_REF] Nilius | The transient receptor potential family of ion channels[END_REF]. All TRP channels comprise six putative transmembrane spanning domains and a cation-permeable pore formed by a short hydrophobic region between transmembrane domains 5 and 6. TRP channels are widely expressed across tissues, including epithelial cells. They are activated by environmental stresses, such as; changes in temperature, pressure, pH, and osmolarity, as well as chemicals, hormones, and cytokines. In general, their activation is potentiated by PLC activation mediated by GPCRs. This activation leads to an inward current of Ca 2+ and Na + ions, defining that TRP channels are nonselective cation channels [START_REF] Nilius | The transient receptor potential family of ion channels[END_REF]. However, some channels are more selective for Ca 2+ than others [START_REF] Vangeel | Transient Receptor Potential Channels and Calcium Signaling[END_REF].

The first subfamily of mammalian TRP channels studied is the TRPC subfamily canonical TRP channels. TRPC channels can form homo or hetero-tetramers with other families of the TRP channel family.

Like most other TRP channels, they function as Ca 2+ permeable plasma membrane channels and display varying Ca 2+ selectivity [START_REF] Vangeel | Transient Receptor Potential Channels and Calcium Signaling[END_REF]Voets 2019, Wang et al. 2020). The following section will focus on the first identified TRPC member, TRPC1.

TRPC1; Expression and structure

The TRPC family comprises seven members, and this TRP subfamily shares 30%-47% amino acid homology (Wang et al. 2020). The first identified member out of the seven in the TRPC subfamily is TRPC1. The DNA, an amino acid sequence, and the expression pattern of TRPC1 were published in 1995 [START_REF] Wes | TRPC1, a human homolog of a Drosophila store-operated channel[END_REF][START_REF] Zhu | Molecular cloning of a widely expressed human homologue for the Drosophila trp gene[END_REF], followed by the first functional data in 1996 [START_REF] Zitt | Cloning and functional expression of a human Ca2+permeable cation channel activated by calcium store depletion[END_REF]. The human gene coding for TRPC1 is localized on chromosome 3, while the murine homolog is on chromosome 9. TRPC1 protein expression pattern is ubiquitously expressed across tissue types, with a low expression in the pancreas, compared to high expression in the retina and ovaries (Figure 24). The TRPC1 mRNA is expressed in five splice variants, but only three (α, β, and ε) seem to be translated and form functional proteins [START_REF] Sakura | Identification of four trp1 gene variants murine pancreatic beta-cells[END_REF]Ashcroft 1997, Ong et al. 2013). The predicted size of TRPC1 is around 90 KDa. However, in native tissues, the actual size was more remarkable than first anticipated and can be explained by its glycosylation between the transmembrane domain 5 and the pore region (Rychkov and Barritt 2007). TRPC1 shows structural similarities with the other members of the TRPC subfamily [START_REF] Nesin | Trpc1[END_REF].

The putative transmembrane structure of TRPC1 consists of the following (Figure 25):

-Coiled-coil domains in intracellular N-and C-termini, where the C-terminus is a proline-rich region -Six membrane-spanning helices (S1-S6)

-A hydrophobic pore-forming loop (P), with negatively charged aspartic acid (D) and glutamic acid (E) residues, and a putative selectivity filter (SYGEE) between S5 and S6

-A TRP box/motif (EWKKFAR)

-A CaM-binding domain that partially overlaps with an IP3R-binding domain -Four ankyrin repeats that may be important for binding and interactions with other proteins

The localization of TRPC1 in native tissues has been questioned. Indeed, in HEK and CHO cell models, TRPC1 localized in ER and intracellular vesicles [START_REF] Alfonso | Regulation of the cellular localization and function of human transient receptor potential channel 1 by other members of the TRPC family[END_REF], Cheng et al. 2011), whereas in tsA 201 cells, TRPC1 was localized in the plasma membrane [START_REF] Barrera | AFM imaging reveals the tetrameric structure of the TRPC1 channel[END_REF]). TRPC1 has also been shown to localize in lipid raft domains [START_REF] Lockwich | Assembly of Trp1 in a signaling complex associated with caveolin-scaffolding lipid raft domains[END_REF]. Besides, TRPC1 can form functional channels with other TRP family members. TRPC1 has been shown to form heterotetrameric channel complexes in the plasma membrane with TRPC3, -4, -5, 6-and -7 (Dietrich et al. 2014). Additionally, TRPC1 physically interacts with TRPP1 channels, which are mutated in patients with polycystic kidney disease [START_REF] Bai | Formation of a new receptor-operated channel by heteromeric assembly of TRPP2 and TRPC1 subunits[END_REF]. TRPC1 also interacts with the highly Ca 2+ selective channels TRPV6 and TRPV4. Apart from TRP channels, TRPC1 can also form a complex with ORAI1 and STIM1, which are implicated in SOCE [START_REF] Ong | Role of TRPC Channels in Store-Operated Calcium Entry[END_REF]). These findings clearly demonstrate that TRPC1 is functional, at least in heteromeric channel complexes.

TRPC1; Activation and regulation

Various TRP channels are mechanosensitive, gated directly by physical forces like membrane stretch or temperature, biochemically by ligands, or downstream signaling cascades. TRP channels are involved in several cellular processes, including Ca 2+ homeostasis, nociception, inflammation, and cell motility (Wang et al. 2020). In general terms, TRPC1 is a member of ion channels called 'cellular sensors' (Pedersen andNilius 2007, Eijkelkamp et al. 2013). TRPC1 has shown to be activated via:

-Stretch; leading to TRPC1-dependent Ca 2+ entry in several cell types, such as frog oocytes, cells from cerebral arteries, and skeletal and smooth muscle cells [START_REF] Maroto | TRPC1 forms the stretch-activated cation channel in vertebrate cells[END_REF], Dietrich et al. 2007[START_REF] Formigli | Regulation of transient receptor potential canonical channel 1 (TRPC1) by sphingosine 1-phosphate in C2C12 myoblasts and its relevance for a role of mechanotransduction in skeletal muscle differentiation[END_REF] -Light; TRPC1-deficient mice exhibited nearly a 50% decrease in behavioral responses to both the light-stroke and light punctate mechanical assays [START_REF] Garrison | TRPC1 contributes to light-touch sensation and mechanical responses in low-threshold cutaneous sensory neurons[END_REF] -Ambient pressure; TRPC1-mediated Ca 2+ influx rises when PSCs are kept under elevated pressure [START_REF] Staaf | Down regulation of TRPC1 by shRNA reduces mechanosensitivity in mouse dorsal root ganglion neurons in vitro[END_REF], Fels et al. 2016, Radoslavova et al. 2022) -Hypoxia; TRPC1 expression is induced and mediates Ca 2+ entry in non-cancerous and cancerous cell lines [START_REF] Sukumaran | TRPC1-mediated Ca(2)(+) entry is essential for the regulation of hypoxia and nutrient depletion-dependent autophagy[END_REF], Azimi et al. 2017) -Growth factors; EGF, TGFβ, Platelet-derived growth factor (PDGF), and vascular endothelial growth factor (VEGF), lead to the regulation of different cellular processes involved in cancer progression through TRPC1 and Ca 2+ entry (Tajeddine and Gailly 2012, Asghar et al. 2015, Schaar et al. 2016, Azimi et al. 2017) -Interaction with other proteins, such as GPCRs, other channels, and classical channel activations, such as store-depletion (Nesin andTsiokas 2014, Ong et al. 2016). For instance, by forming a complex with the GTPase RhoA in intestinal epithelial cells (Chung et al. 2015) 3. The contribution of TRPC1 in the SOCE scenario

With the discovery of TRPC channels, none of these Ca 2+ permeable channels seemed to generate currents that resembled ICRAC. Thus, identifying the role of these channels and other regulatory components of SOCE led to the identification of the CRAC channel component ORAI1. This four-transmembrane domain protein assembles into a hexamer to form the pore of a CRAC channel [START_REF] Ong | Role of TRPC Channels in Store-Operated Calcium Entry[END_REF]). ORAI1 and two other isoforms (ORAI 2 and ORAI3) display store-dependent activation [START_REF] Feske | A mutation in Orai1 causes immune deficiency by abrogating CRAC channel function[END_REF][START_REF] Vig | CRACM1 is a plasma membrane protein essential for storeoperated Ca2+ entry[END_REF].

Furthermore, were the STIM1 and STIM2 proteins identified as Ca 2+ sensing proteins localized in the ER membrane, from where they sense intracellular Ca 2+ levels and regulate SOCE [START_REF] Cahalan | STIMulating store-operated Ca(2+) entry[END_REF]. It is now known that at least STIM1 can activate both ORAI1 and TRPC1 (Ambudkar et al. 2017). TRPC1 is reported to have a role in SOCE in various cell types. However, the contribution of TRPC1 in SOCE has not been consistent since several reports found that exogenous TRPC1 expression did not increase SOCE, while the KD of endogenous TRPC1 expression significantly decreased SOCE [START_REF] Dehaven | TRPC channels function independently of STIM1 and Orai1[END_REF][START_REF] Ong | Role of TRPC Channels in Store-Operated Calcium Entry[END_REF]). The latter was found in different cell types, such as smooth muscle and endothelial cells, but interestingly also in human salivary glands and pancreatic acinar cells (Liu et al. 2007, Hong et al. 2011, Sun et al. 2015). Several studies in TRPC1 deficient mice (TRPC1 -/-) displayed low SOCE, which decreased the Ca 2+ dependent activation of Ca 2+ -activated K + channels (KCa) and Cl -channel activity, inhibiting fluid and protein secretion (Liu et al. 2007, Hong et al. 2011, Sun et al. 2015). Notably, the expression of ORAI1 did not change in the salivary gland or pancreatic acinar cells from the TRPC1 -/-mice, meaning that this channel does not compensate for the lack of TRPC1 or support the Ca 2+ signaling on its own. In these secretory glands, the decreased secretion is primarily a result of the loss of TRPC1-mediated SOCE (Hong et al. 2011).

Albeit from these results, other reports show that ORAI1 is required for TRPC1 function, as silencing of ORAI1 abolished TRPC1 channel activation, despite the presence of STIM1. Here, it was shown that the Ca 2+ influx through ORAI1 triggered the insertion of TRPC1 in the plasma membrane. Furthermore, is STIM1 required for TRPC1 channel activation, as a KD of STIM1 reduced endogenous TRPC1-mediated SOCE and Ca 2+ current, whereas co-expression of both TRPC1 and STIM1 enhanced SOCE [START_REF] Ong | Dynamic assembly of TRPC1-STIM1-Orai1 ternary complex is involved in store-operated calcium influx. Evidence for similarities in store-operated and calcium release-activated calcium channel components[END_REF]). ORAI1

and STIM1 form a complex with TRPC1 in response to ER Ca 2+ store depletion in several cell types, including salivary gland and pancreatic acinar cells [START_REF] Ong | Dynamic assembly of TRPC1-STIM1-Orai1 ternary complex is involved in store-operated calcium influx. Evidence for similarities in store-operated and calcium release-activated calcium channel components[END_REF][START_REF] Lu | Expression and association of TRPC subtypes with Orai1 and STIM1 in human parathyroid[END_REF][START_REF] Zhang | Functional interactions among STIM1, Orai1 and TRPC1 on the activation of SOCs in HL-7702 cells[END_REF][START_REF] Almirza | Role of Trpc channels, Stim1 and Orai1 in PGF(2alpha)-induced calcium signaling in NRK fibroblasts[END_REF][START_REF] Ng | TRPC1 and Orai1 interact with STIM1 and mediate capacitative Ca(2+) entry caused by acute hypoxia in mouse pulmonary arterial smooth muscle cells[END_REF][START_REF] Pani | Impairment of TRPC1-STIM1 channel assembly and AQP5 translocation compromise agonist-stimulated fluid secretion in mice lacking caveolin1[END_REF]. Co-localization experiments revealed that TRPC1 localized in the same ER-plasma membrane junctions where the ORAI1/STIM1 complex was localized. This localization allows for Ca 2+ entry through TRPC1 by assembling with STIM1 [START_REF] Ong | Dynamic assembly of TRPC1-STIM1-Orai1 ternary complex is involved in store-operated calcium influx. Evidence for similarities in store-operated and calcium release-activated calcium channel components[END_REF], Cheng et al. 2008, Kim et al. 2009, Cheng et al. 2011).

Additionally, the lipid raft domain caveolae-residing protein, caveolin-1 (Cav-1), is an essential modifier of TRPC1 activity and plasma membrane localization depends on this protein. When Cav-1 is lacking, TRPC1 displays abnormal localization and is not able to interact with STIM1, which is essential for the TRPC1 activation and SOCE [START_REF] Pani | Activation of TRPC1 by STIM1 in ER-PM microdomains involves release of the channel from its scaffold caveolin-1[END_REF][START_REF] Pani | Impairment of TRPC1-STIM1 channel assembly and AQP5 translocation compromise agonist-stimulated fluid secretion in mice lacking caveolin1[END_REF][START_REF] Lee | Molecular determinants mediating gating of Transient Receptor Potential Canonical (TRPC) channels by stromal interaction molecule 1 (STIM1)[END_REF]. TRPC1 localization and trafficking can also be modulated by several cytoskeletal and microtubule proteins. It has been shown that the monomeric GTPase, RhoA, promotes TRPC1 translocalization to the plasma membrane in pulmonary artery endothelial cells and intestinal epithelial cells (Mehta et al. 2003, Chung et al. 2015). Whilst in retinal epithelial cells, βtubulin determines the plasma membrane expression of TRPC1 (Bollimuntha et al. 2005). The inhibition of TRPC1 of either RhoA or β-tubulin abolished SOCE (Mehta et al. 2003, Bollimuntha et al. 2005, Chung et al. 2015).

Taken together, TRPC1 can interact with STIM1 and form a SOC that generates an ISOC current. When TRPC1 interacts with ORAI1 and STIM1, it can participate in the generation of the ICRAC or ISOC current (Figure 26). Furthermore, its interaction with other proteins is required for TRPC1 plasma membrane localization where SOCE is regulated.

Pharmacological inhibition of TRPC1

To date, no pharmacological inhibitors have proven to be specific and selective for TRPC1. It is typically genetically encoded approaches used to decrease the expression and function of TRPC1, such as smallinterfering RNA (siRNA) or short-hairpin RNA (shRNA) strategies [START_REF] Zhong | The regulatory and modulatory roles of TRP family channels in malignant tumors and relevant therapeutic strategies[END_REF]. TRP channels can be inhibited by the lanthanides La 3+ and Gd 3+ , which are widely used in electrophysiological experiments [START_REF] Bouron | Permeation, regulation and control of expression of TRP channels by trace metal ions[END_REF].

Some pharmacological inhibitors often utilized are SOC inhibitors 2-APB, SKF96365, and MRS1845. 2aminoethoxydiphenyl borate (2-ABP) is frequently used as a reasonably non-selected SOC inhibitor but was initially discovered as an IP3R inhibitor. Similarly, SKF96365 was developed to inhibit receptor-mediated Ca 2+

entry, but the compounds showed pleiotropic effects, as it inhibits SOCE via STIM1 and several TRPC channels, as well as voltage-gated Ca 2+ and K + channels. Furthermore, the dihydropyridine MRS1845 has been reported to inhibit the SOCE pathway [START_REF] Gautier | New insights into pharmacological tools to TR(i)P cancer up[END_REF]). However, its potential effect on TRPC1 has now been proven in electrophysiological studies. Interestingly, compounds including AM12, AC1903, Clemizole, Galangin, M084, and PICO 145 have been described as more specific antagonists of TRPC1 in combination with TRPC4 and TRPC5 (Elzamzamy et al. 2020).

TRPC1 in pathologies

A focus on cancer The biological role of TRPC1 has been studied in genetically engineered TRPC1 -/-mouse models. Although the mice survived TRPC1 depletion, they showed defects in several organs and tissues, and this loss of TRPC1 leads to the decreased fluid secretion of exocrine glands such as salivary glands and pancreatic acinar cells [START_REF] Nesin | Trpc1[END_REF]. Furthermore, the TRPC1 deficiency showed; reduced response to hemodynamic stress in terms of developing cardiac hypertrophy; slow regeneration of skeletal muscle cells; dysfunctional development and growth of bones; reduced production of cytokines and chemokines; increased development of lung edemas; reduced vascular remodeling after chronic hypoxia; epilepsy-induced neurodegeneration, and increased unfolded protein response and a reduced number of dopaminergic neurons concerning Parkinson's disease (Dietrich et al. 2014, Nesin and[START_REF] Nesin | Trpc1[END_REF].

Widely studied is the implication of TRPC1 in cancer progression. Numerous studies have shown that dysregulation of TRPC1, both beside and through Ca 2+ entry, and as a biomarker of several types of cancer (Elzamzamy et al. 2020). The following section will summarize the role of TRPC1 in different kinds of cancer.

• Breast cancer TRPC1 has been widely studied in breast cancer (Elzamzamy et al. 2020). Azimi et al. found that TRPC1 was overexpressed in MDA-MB-468, MDA-MB-231, and HCC1569 breast cancer cell lines under hypoxic conditions, which increased expression of Snail, Vimentin, and Twist, leading to EMT. This effect was regulated through an AKT/HIF1α pathway. Furthermore, it was found that reducing TRPC1 expression under hypoxic conditions decreased basal Ca 2+ entry (Azimi et al. 2017). However, silencing of TRPC1 slightly increased SOCE activity, indicating that the TRPC1/AKT/HIF1α pathway regulating EMT is SOCEindependent AKT/TRPC1 dependency was shown in another study where downregulation of TRPC1 reduced the activation of AKT (Kaemmerer et al. 2018). Schaar et al. found that TTRPC1-mediated SOCE in TGFβ stimulated breast cell lines and breast cancer cell lines, which resulted in increased calpain activity and, thus, EMT and cell migration (Schaar et al. 2016). Davis et al. showed that silencing of TRPC1 inhibited constitutively active ERK1/2 and led to S-phase reduction and, thus, attenuation of cell proliferation. However, this seemed to be in a SOCE-independent manner as the downregulation of TRPC1 also slightly increased SOCE (Davis et al. 2012). In a phenotypic distant breast cancer cell line, MCF-7, the silencing of TRPC1 attenuated ERK1/2 phosphorylation mediated by the activation of the Ca 2+ -sensing receptor (CaR), thus arresting cells in the G1 phase and decreasing cell proliferation [START_REF] El Hiani | Calcium-sensing receptor stimulation induces nonselective cation channel activation in breast cancer cells[END_REF], El Hiani et al. 2009).

Furthermore, a feed-forward loop was described where TRPC1 expression required activation of EGFR and ERK activity (El Hiani et al. 2009, El Hiani et al. 2009). In the same cell line was, cell cycle progression dependent on TRPC1 expression mediating the activity of KCa3.1 (Faouzi et al. 2016). The role of TRPC1 was MCF7 cells is dependent on Ca 2+ entry (El Hiani et al. 2009, El Hiani et al. 2009, Faouzi et al. 2016).

Several studies have found that TRPC1 is upregulated in human breast cancer tissue, which correlates with TNM stage, clinical stage, and lymph node metastasis [START_REF] Dhennin-Duthille | High expression of transient receptor potential channels in human breast cancer epithelial cells and tissues: correlation with pathological parameters[END_REF], Mandavilli et al. 2012, Zhang et al. 2020). However, a recent study has shown a high TRPC1 expression in different breast cancer compared to a corresponding normal-like cell line. Here, they found that the increased expression of TRPC1 inhibited the expression of AKT and EMT markers leading to subsequent inhibition of cell proliferation, migration, and invasion. Furthermore, they found that upregulation of TRPC1 in breast tumor tissue correlated with a better prognosis in estrogen receptor + patients (Zhang et al. 2020). These contradictory results indicate that TRPC1, in some breast cancer patient populations, seems to have a protective effect while showing a more aggressive role in others.

• Lung cancer

In the lung cancer cell line A549, exposure to high nicotine levels resulted in increased HIF1α levels, leading to an upregulation of the SOC components, ORAI1, TRPC6, and TRPC1, as found in breast cancer (Azimi et al. 2017, Wang et al. 2018). On the other hand, the downregulation of HIF1α was associated with low levels of ORAI1, TRPC6, and TRPC1, decreasing cell proliferation. Interestingly, high nicotine levels were related to enhanced basal intracellular Ca 2+ concentrations. Downregulation of TRPC1 decreased hypoxia-induced autophagy, which is known to promote survival in hypoxic environments (Wang et al. 2018). Another report demonstrated in the same cell line that silencing of TRPC1 decreased the expression of cyclins D1 and D3 along with induced G0/G1 cell cycle arrest, resulting in reduced cell growth. This TRPC1 silencing was associated with a decreased phosphorylation and activation of EGFR and subsequent disruption of AKT and ERK pathways. The stimulation of EGFR led to induced TRPC1-mediated SOCE (Tajeddine and Gailly 2012).

Moreover, another study showed that inhibition with 2-ABP or a specific TRPC1 inhibiting antibody (T1E3) repressed cell proliferation [START_REF] Jiang | Involvement of TRPC channels in lung cancer cell differentiation and the correlation analysis in human non-small cell lung cancer[END_REF]. Several studies have demonstrated that a high expression of TRPC1 in non-small cell lung cancer (NSCLC) human specimens correlated with well-differentiated tumors, advanced TNM stage, and low disease-free survival (Jiang et al. 2013, Ke andLong 2022).

• Colorectal cancer TRPC1 has been shown to be overexpressed in several colorectal cancer (CRC) cell lines (HT29, HCT116, SW620, SW480, and CaCo2, compared to a corresponding normal-like cell line (Sobradillo et al. 2014, Sun et al. 2021). Even though SOCE is highly upregulated in several of these cell lines, TRPC1 silencing has until now only been shown to significantly decrease SOCE levels in SW620 and HCT116 cells [START_REF] Gueguinou | SK3/TRPC1/Orai1 complex regulates SOCE-dependent colon cancer cell migration: a novel opportunity to modulate anti-EGFR mAb action by the alkyl-lipid Ohmline[END_REF], Sun et al. 2021). However, TRPC1 seems to have a role in CRC progression. It was demonstrated that reducing TRPC1 expression levels and disrupting a complex consisting of TRPC1, ORAI1, and the Ca 2+activated K + channel (SK3) in the lipid rafts led to decreased cell migration. It was shown that this mechanism was regulating migration via AKT and EGFR activation in a Ca 2+ -dependent manner [START_REF] Gueguinou | SK3/TRPC1/Orai1 complex regulates SOCE-dependent colon cancer cell migration: a novel opportunity to modulate anti-EGFR mAb action by the alkyl-lipid Ohmline[END_REF].

In a recent study, it was demonstrated that TRPC1 regulated CRC cell and tumor growth and metastasis by forming a complex with CaM and PI3K (Sun et al. 2021). In vitro, silencing of TRPC1 inhibited cell migration, EMT, and invasion, decreased expression levels of Cyclin B1 and CDK1, and accumulated cells in G2/M phases, leading to reduced cell proliferation. In vivo, TRPC1 silencing decreased tumor growth and metastasis, and tumorigenesis was attenuated in TRPC1 -/-mice. In contrast, the upregulation of TRPC1 promoted cell growth and migration, both in vitro and in vivo. TRPC1 interacted and co-localized with both PI3K and CaM.

In addition, AKT activation induced by an overexpression of TRPC1 was decreased upon inhibition of the PI3K with LY294002 (Sun et al. 2021). Furthermore, TRPC1 was upregulated in human CRC tissue samples, which correlated with a poor prognosis in the form of low survival (Ibrahim et al. 2019, Sun et al. 2021).

• Prostate

It has been shown that TRPC1 is a SOC component in LNCaP and ATP-stimulated primary human prostate cancer epithelial cells, and the silencing of TRPC1 decreases SOCE levels [START_REF] Vanden Abeele | Store-operated Ca2+ channels in prostate cancer epithelial cells: function, regulation, and role in carcinogenesis[END_REF][START_REF] Pigozzi | Calcium store contents control the expression of TRPC1, TRPC3 and TRPV6 proteins in LNCaP prostate cancer cell line[END_REF][START_REF] Thebault | Differential role of transient receptor potential channels in Ca2+ entry and proliferation of prostate cancer epithelial cells[END_REF]. However, the expression levels of TRPC1 are known to decrease with the progression of prostate cancer from androgen-dependent to androgen-independent (Shapovalov et al. 2016).

In addition, one study has demonstrated that TRPC1 expression was increased in the early stages of prostate cancer compared to late stages and that the high expression was associated with lower proliferation and more prolonged recurrence-free survival (Perrouin Verbe et al. 2016, Perrouin-Verbe et al. 2019). These results suggest that TRPC1 could have a protective role in prostate cancer.

• Glioblastoma and neuroblastoma

In a glioma/glioblastoma multiforme (GBM) cell model, D54MG cells, the inhibition of SOCE inhibitors 2-APB, SKF96365, and MRS1845, significantly decreased both Ca 2+ influx and proliferation, as well as the formation of multinucleated cells, a known characteristic of GBM (Bomben and Sontheimer 2010). Specific inhibition of TRPC1 with either a polyclonal-TRPC1 antibody or shRNA targeting decreased Ca 2+ entry significantly (Bomben and Sontheimer 2010). This inhibition led to reduced proliferation and enlargement of multinucleated cells (Bomben and Sontheimer 2010). The role of TRPC1 in GBM was assessed in vivo by injecting mice with glioma cells that ectopically expressed a doxycycline-inducible shRNA targeting TRPC1.

Mice with this inducible TRPC1 KD exhibited a smaller tumor size than mice with a wild-type TRPC1 expression (Bomben and Sontheimer 2010). Another study demonstrated that TRPC1 co-localized with Cav-1 in the lipid rafts of the leading edge of D54MG cells (Bomben et al. 2011). This localization involved chemotaxis and directional migration of cells towards EGF, as the mechanism was attenuated upon TRPC1 silencing (Bomben et al. 2011). The use of SOCE inhibitors MRS1845 and SKF96365 inhibited glioma cell migration, suggesting that Ca 2+ signaling is involved in this migration process (Bomben et al. 2011).

The role of TRPC1 has been studied in SH-SY5Y neuroblastoma cells. It was shown that SH-SY5Y cells treated with an exogenous neurotoxin, 1-methyl-4-phenylpyridinium ion (MPP + ), exhibited low TRPC1 protein and mRNA expression (Bollimuntha et al. 2005). The inhibition with MPP + induced translocation of TRPC1 from the plasma membrane to the cytosol. They found that overexpression of TRPC1 maintained the plasma membrane localization, even upon MPP + treatment. In addition, they demonstrated that TRPC1 overexpression protected SH-SY5Y cells from cell death upon MPP + treatment. On the contrary, TRPC1 silencing could not protect cells from cell death. This protection partially depended on a Ca 2+ influx (Bollimuntha et al. 2005).

• Hepatocellular carcinoma

In the hepatocellular carcinoma cell line Huh7, the KD of TRPC1 increased SOCE levels and suppressed cell proliferation (Selli et al. 2015). The same authors found that silencing of TRPC1 in Huh7 cells changed the SOC and proliferation gene expression pattern (Selli et al. 2016). Different genes of the MAPK signaling pathway were upregulated upon TRPC1 silencing. The same was found for the cell cycle progression regulating genes CDK11A/B and URGCP (Up-regulator of Cell Proliferation). Interestingly, STIM1 was reciprocally upregulated, suggesting a compensatory role of STIM1 in TRPC1-deficient Huh7 cells (Selli et al. 2016).

• Nasopharyngeal carcinoma and thyroid cancer

In a study in a nasopharyngeal carcinoma cell line, CNE2, it was demonstrated that both shRNA silencing of TRPC1 and 2-ABP treatment decreased the expression levels of TRPC1. Both types of TRPC1 abolishment decreased expression of MMP2 and 9, resulting in reduced CNE2 cell migration and invasion. It was not further investigated if the inhibition of TRPC1 affected Ca 2+ entry [START_REF] He | Silencing TRPC1 expression inhibits invasion of CNE2 nasopharyngeal tumor cells[END_REF]).

In the endocrine follicular thyroid cancer cell line ML-1, the silencing of TRPC1 resulted in the attenuation of sphingosine-1 (SP-1) induced proliferation, invasion, and migration (Asghar et al. 2015). TRPC1 KD decreased SOCE upon SP-1 stimulation but failed to inhibit both basal Ca 2+ entry and SOCE. Furthermore, the SP1 receptor, VGFR, HIF1α, MMP2, and 9 decreased upon TRPC1 silencing and CaM inhibition. Along was a decrease in the expression of PKC isoforms, ERK1/2, cyclin D2, and D3 CDK6, and an upregulation of p21 and p27, which resulted in a significant increase in cell population in the G0/G1 phase, and a substantial decrease in S and G2 phases (Asghar et al. 2015). These results suggest that TRPC1 regulates thyroid cell proliferation, invasion, and downstream migration mechanisms.

• Ovarian and endometrial cancer

The role of TRPC1 in ovarian cancer was investigated in a cell line called SKOV-3. First, the two SOCE inhibitors, 2-ABP and SKF96365, decreased cell proliferation in a concentration-dependent manner. Next, cell proliferation was enhanced by stimulation with trypsin. Both antibody inhibition of TRPC1 and siRNA transfection reduced the proliferation rate of SKOV-3 cells, whereas overexpression of TRPC1promoted cell proliferation and colony formation (Zeng et al. 2013). The inhibition of SKOV-3 cell proliferation could result from the decreased number in the G2/M cell cycle phases upon the inhibition of SK96365 or TRPC1 silencing.

Furthermore, the expression of TRPC1 was investigated in human tissue samples where the mRNA TRPC1 expression was significantly lower in undifferentiated ovarian cancer than in normal ovarian tissue (Zeng et al. 2013). Similar results were found upon IHC analysis where the expression of TRPC1 was significantly lower in undifferentiated tissue (Grade 3) compared to well-differentiated tissue (Grade 1-2) (Zeng et al. 2013).

Microarray analysis showed that TRPC1 was downregulated in human ovarian cancer samples, compared to adjacent tissue samples, and in drug-resistant ovarian cancer cell lines, compared to sensitive cell lines (Liu et al. 2016). mRNA-microRNA analysis showed that TRPC1 was interacting with several genes involved in the drug resistance of ovarian cancer. Additionally, the authors made a TCGA investigation which revealed that TRPC1 expressions were lower the higher the histological grade (Liu et al. 2016).

The role of TRPC1 in endometrial carcinoma is poorly understood among many other cancers.

However, one study made a TCGA and micro-array-based investigation. Here, they found that a high expression of TRPC1 in samples from endometrial cancer patients was correlated with low overall survival, even though the expression of TRPC1 was downregulated between endometrial cancer and adjacent tissue samples (Wang et al. 2021).

• Tongue-, esophageal-, and gastric cancer TRPC1 is overexpressed in tongue squamous cell carcinoma (TSCC) cell lines and tissue, compared to a normal control cell line and adjacent tissue (Xu et al. 2017). The high protein expression of TRPC1 in TSCC specimens was significantly correlated with EphA2, ephrinA1, e-NOS, VEGF-A expression, and microvessel density, indicative markers of angiogenesis upregulation. In terms of prognosis, high TPRC1 expression was positively correlated with clinical stage, lymph node metastasis, and tumor differentiation of TSCC (Xu et al. 2017). In a recent study, it was demonstrated by IHC analysis and mRNA expression that TRPC1 was a good value for differentiating TSCC tissue from adjacent tissue. The high expression of TRPC1 positively correlated with pathological grade and lymph node metastasis. However, a high TRPC1 expression negatively correlated with overall survival, especially in patients who received adjuvant radiotherapy [START_REF] Shi | TRPC1 correlates with poor tumor features, radiotherapy efficacy and survival in tongue squamous cell carcinoma[END_REF].

The role of TRPC1 in esophageal cancer cell lines is, to some extent, a little complicated. EC9706 cells, which natively have a high expression of TRPC1, were transfected with siRNA targeting TRPC1, resulting in increased cell proliferation, migration, and invasion rates (Zeng et al. 2021). Intriguingly, the KD of TRPC1 induced the activation of AKT and the levels of p27. In the KYSE150 cells, natively expressing low levels of TRPC1, overexpression resulted in decreased proliferation, migration, and invasion rates, along with reduced activation of AKT and p27 (Zeng et al. 2021). The authors performed IHC analysis on human esophageal cancer samples, where they found a low expression compared to adjacent tissue. The low expression correlated with high proliferation, lymph node metastasis, and low survival (Zeng et al. 2021).

TRPC1 was involved in TGFβ induced EMT in a gastric cancer cell line, SGC-7901 cells. Specific TRPC1 silencing and inhibition with SKF96365 and 2-APB increased mRNA and protein levels of E-cadherin and decreased the levels of vimentin and α-SMA. The inhibition with SKF96365 and 2-APB significantly reduced protein levels of TRPC1 along with Ras and Raf1 and the phosphorylation of ERK1/2, suggesting that the MAPK signaling pathway is involved in EMT of gastric cancer cells [START_REF] Ge | TRPC1/3/6 inhibition attenuates the TGF-beta1-induced epithelialmesenchymal transition in gastric cancer via the Ras/Raf1/ERK signaling pathway[END_REF] Zhiyong et al. developed two stable gastric cancer cell lines; BGC-823 cells with a low expression of TRPC1 and MKN-45 cells with a high expression of TRPC1 (Zhang et al. 2020). While BGC-823, with low TRPC1, exhibited decreased cell migration, MKN-45, with a high TRPC1 expression, displayed enhanced cell migration. The authors speculated if miRNA involved in the pathogenesis of gastric cancer could regulate TRPC1 expression. By a database prediction, they found that miR-135a-5p could be a possible TRPC1 target. This mechanism was further analyzed and confirmed by luciferase, qRT-PCR, and protein expression assays demonstrating that co-transfection with miR-135a-5p decreased and increased TRPC1 levels in BGC-823 and MKN-45 cells, respectively (Zhang et al. 2020). Furthermore, they found that a circulating RNA (ciRS-7) acted as a sponge of miR-135a-5p and reversed miR-135a-5p-mediated downregulation of TRPC1. In addition, they demonstrated that both TRPC1 and ciRS-7 were upregulated in human gastric cancer tissue, which correlated with low survival (Zhang et al. 2020).

• Renal Cell Carcinoma

It has recently been shown that TRPC1 is overexpressed in renal cell carcinoma (Chen et al. 2022). IHC analysis and qRT-PCR demonstrated that TRPC1 levels were elevated in human tissue samples from renal cell carcinoma patients. Here, the high TRPC1 expression did not correlate with tumor properties. However, an increased expression of TRPC1 protein, but not mRNA, was associated with a low overall survival (Chen et al. 2022).

TRPC1 in the pancreatic tumor microenvironment

A high expression of TRPC1 and TRPC4 and TRPC6 has been found in the PDAC cell line BxPC-3. Here, TRPC1 increased intracellular Ca 2+ levels upon TGFβ stimulation, followed by PKC-α activation, initiating cell motility and migration (Chow et al. 2008, Dong et al. 2010). The authors proved this with three approaches; (1) Pharmacological inhibition of SOCE with 2-ABP and La 3+ , which abolished the TGFβ-mediated Ca 2+ entry. ( 2) Blocking of PKC-α with selective inhibitors inhibited the TGFβ-induced Ca 2+ entry, and (3) KD of TRPC1, but not the KD of TRPC4 or TRPC6, reversed the TGFβ-induced motility and migration (Dong et al. 2010).

TRPC1 has been associated with pressure-induced activation of PSC (Fels et al. 2016, Radoslavova et al. 2022). In both murine and human PSCs, TRPC1 partially mediate PSC activation under high pressure by promoting αSMA expression. Elevated pressure increased the stiffness and the emitted traction forces of PSCs in a TRPC1-dependent manner. Furthermore, TRPC1 cooperated with the phosphorylated form of SMAD2 and regulated cell cycle progression and interleukin-6 (IL-6) secretion through an ERK1/2 and SMAD2dependent pathway (Radoslavova et al. 2022). In addition, pressure-induced activation of PSCs leads to TRPC1-dependent stimulation of migration and Ca 2+ influx (Fels et al. 2016).

Taken together, there is sparse evidence about the role of TRPC1 in the pancreatic tumor microenvironment.

The TRPC1 interactome

Besides interacting with other ion channels (especially TRPCs), TRPC1 interacts with other regulatory and scaffolding proteins to regulate downstream processes. Indeed, TRPC1 forms a complex with ORAI1 and STIM1 in the lipid rafts to allow the activation of SOCE. Additionally, the plasma membrane localization of TRPC1 is promoted by the monomeric GTPase, RhoA, as described in 'The contribution of TRPC1 in the SOCE scenario'. Upon thrombin activation, RhoA interacts with IP3R and TRPC1 in the plasma membrane of pulmonary artery endothelial cells, which is required for Ca 2+ entry. This Rho-activated Ca 2+ entry through TRPC1 enhances endothelial permeability (Mehta et al. 2003). In intestinal epithelial cells, the physical interaction between RhoA and TRPC1 mediates SOCE and stimulates cell migration after wounding (Chung et al. 2015). Besides RhoA, the Rho GTPase Rac1 and TRPC1 are associated with colon cancer cell migration by being involved in a complex positive feedback loop. SOCE induced by EGF activates Rac1 and STIM1 through the AKT pathway, which in turn promotes the translocalization of a TRPC1/SK3/ORAI1 complex into the lipid rafts, which triggers SOCE. Simultaneously, AKT-mediated Rac1 activation promotes SOCEdependent cell migration through the AKT pathway, leading to lamellipodia formation and calpain activation [START_REF] Gueguinou | SK3/TRPC1/Orai1 complex regulates SOCE-dependent colon cancer cell migration: a novel opportunity to modulate anti-EGFR mAb action by the alkyl-lipid Ohmline[END_REF]).

TRPC1 interacts with other membrane-bound proteins, such as metabotropic glutamate receptors, tumor necrosis factor receptors, and growth factor receptors [START_REF] Nesin | Trpc1[END_REF]. For instance, in isolated rat embryonic neural stem cells, TRPC1 physically interacts with the fibroblast growth factor receptor (FGFR-1). The silencing of TRPC1 suppresses Ca 2+ entry, cation conductance, and cell proliferation of these cells [START_REF] Fiorio Pla | Canonical transient receptor potential 1 plays a role in basic fibroblast growth factor (bFGF)/FGF receptor-1-induced Ca2+ entry and embryonic rat neural stem cell proliferation[END_REF].

Furthermore, TRPC1 interacts with cytosolic proteins, such as Homer protein, caveolins, and CaM (Ong andAmbudkar 2011, Nesin and[START_REF] Nesin | Trpc1[END_REF]. Deleting the second CaM binding domain in the Cterminal tail of TRPC1 resulted in a Ca 2+ -dependent inactivation of SOC currents in human salivary gland cells, suggesting that TRPC1 displays Ca 2+ -dependent inactivation [START_REF] Singh | Calmodulin regulates Ca(2+)-dependent feedback inhibition of store-operated Ca(2+) influx by interaction with a site in the C terminus of TrpC1[END_REF]. Additionally, as described above (in TRPC1 in the pancreatic tumor microenvironment), our group has recently shown that TRPC1 forms a complex αSMA and phosphorylated SMAD2 in PSCs (Radoslavova et al. 2022). Interestingly, TRPC1 interacts with PI3K and CaM in colorectal cancer cells, regulating tumor growth and metastasis (as described in TRPC1 in pathologies; colon cancer).

Taken together, several reports suggest that TRPC1 channel activity can rely on the interaction with different partner proteins, such as other ion channels, GTPases, other cytosolic proteins, and membrane-bound proteins. The interaction of TRPC1 with various proteins involved in up-and downstream mechanisms of several signaling cascades emphasizes the importance of a TRPC1 interactome (Figure 27). interacts with β-tubulin, which promotes plasma membrane localization and Ca 2+ entry. D) Agonist-stimulation promotes TRPC1 to form a complex with Cav-1 in the plasma membrane. This complex is needed for TRPC1 to interact with STIM1 and allow Ca 2+ entry. G) TRPC1 forms a complex with PI3K and CaM (Generated with Biorender).

INTRODUCTION

Ion channels are plasma membrane spanning proteins found in all human tissues, allowing rapid transport of ions and fluids between the extracellular and intracellular milieu [START_REF] Niemeyer | Ion channels in health and disease. 83rd Boehringer Ingelheim Fonds International Titisee Conference[END_REF]Gouaux and Mackinnon, 2005). Opening of ion channels can result in redistribution of different ions, which changes the electrical and chemical properties of the cell leading to several cellular processes [START_REF] Roux | Ion channels and ion selectivity[END_REF]. These include multiple signal transduction and downstream signaling events, including regulation of gene expression, secretion of enzymes and hormones, and intracellular communication between compartments (Chen et al., 1994;[START_REF] Tolon | Regulation of somatostatin gene expression by veratridine-induced depolarization in cultured fetal cerebrocortical cells[END_REF]Stock and Schwab, 2015). A stable regulation of these processes maintains normal tissue homeostasis, such as cell cycle progression, migration, and apoptosis [START_REF] Kunzelmann | Ion channels and cancer[END_REF][START_REF] Kunzelmann | Ion channels in regulated cell death[END_REF]Prevarskaya et al., 2018;[START_REF] Anderson | Role of ion channels in gastrointestinal cancer[END_REF]. Accordingly, dysregulated expression as well as altered function of ion channels are related to a great number of diseases (Kim, 2014), and can drive the transformation from normal to malignant cell behavior [START_REF] Litan | Cancer as a channelopathy: ion channels and pumps in tumor development and progression[END_REF]. Over the past decades, aberrant and even cancer-specific expression of numerous ion channels have been demonstrated in various types of cancers [START_REF] Pedersen | Ion channels and transporters in cancer: pathophysiology, regulation, and clinical potential[END_REF][START_REF] Djamgoz | Ion transport and cancer: from initiation to metastasis[END_REF]. Together, the abnormal expression and activity of ion channels can be categorized as "hallmarks of cancer" (Hanahan and Weinberg, 2011).

The pancreas is a complex organ, which has two main functions exerted by an exocrine and endocrine compartment [START_REF] Pandiri | Overview of exocrine pancreatic pathobiology[END_REF]. Dysregulation of exocrine pancreatic fluid secretion can contribute to pathologies such as pancreatitis and neoplasms such as pancreatic ductal adenocarcinoma (PDAC), whereas a well-known disorder related to dysfunction of the endocrine pancreas is diabetes mellitus (Pallagi et al., 2015;Kirkegard et al., 2017). The exocrine pancreas ensures enzymatic secretion for digesting fats and proteins in the intestines and, in parallel, the secretion of abundant fluid rich in bicarbonate ions, which serves to neutralize the acidic chime in the duodenum (Ishiguro et al., 2012;Lee et al., 2012;Pallagi et al., 2015). The bicarbonate secretion involves a tightly coordinated network of ion channels and transporters (Novak et al., 2013). The ductal epithelial cells comprising the exocrine pancreas are, as other types of epithelia, well-organized and exhibit epithelial features such as a polarized morphology and specialized cell-to-cell contact with tight junctions (Rodriguez-Boulan and [START_REF] Rodriguez-Boulan | Morphogenesis of the polarized epithelial cell phenotype[END_REF]. The ductal cells are equipped with a highly polarized set of ion channels and transporters, enabling the net bicarbonate excretion at the apical membrane, balanced by the net efflux of acid via the basolateral membrane to maintain their intracellular pH [START_REF] Steward | Mechanisms of bicarbonate secretion in the pancreatic duct[END_REF]. Therefore, a correct distribution of ion channels and transporters is important to maintain the secreting function of exocrine pancreas (Lee et al., 2012). Moreover, expression, function, and localization of ion channels in the plasma membrane are involved in the development and progression of PDAC (Pedersen et al., 2017). PDAC can arise from ductal cells [START_REF] Schneider | Pancreatic cancer: basic and clinical aspects[END_REF] or from acinar cells transforming to ductal cells by acinar-to-ductal-metaplasia, resulting in these cells possessing a ductal phenotype [START_REF] Aichler | Origin of pancreatic ductal adenocarcinoma from atypical flat lesions: a comparative study in transgenic mice and human tissues[END_REF]. The transformation-associated loss of cell polarity and cell-cell adhesions of the epithelial cell layer will result in an altered localization of ion channels (Coradini et al., 2011;[START_REF] Pedersen | Ion channels and transporters in cancer: pathophysiology, regulation, and clinical potential[END_REF].

Several reports and reviews about the role of transporters in bicarbonate, pancreatic fluid secretion and PDAC have been published [START_REF] Novak | Keeping up with bicarbonate[END_REF][START_REF] Lee | Coordination of pancreatic HCO3-secretion by protein-protein interaction between membrane transporters[END_REF][START_REF] Novak | Pancreatic bicarbonate secretion involves two proton pumps[END_REF]Ishiguro et al., 2012;Lee et al., 2012;[START_REF] Kong | Acid-base transport in pancreatic cancer: molecular mechanisms and clinical potential[END_REF][START_REF] Lemstrova | Role of solute carrier transporters in pancreatic cancer: a review[END_REF]Pedersen et al., 2017;[START_REF] Yamaguchi | Bicarbonate-rich fluid secretion predicted by a computational model of guinea-pig pancreatic duct epithelium[END_REF]. However, the role of ion channels in exocrine pancreas and in PDAC is not well understood. In this review, we aim to make a synthesis of the important role of ion channels and their localization and function in fluid secretion in healthy exocrine pancreatic tissue (see Table 1 andFigure 1). Next, we summarize the sparse knowledge of the involvement of ion channels in PDAC progression and development via effects on proliferation, apoptosis, invasion and migration (see Table 2 andFigure 2). Finally, we describe how ion channels are important novel biomarkers in PDAC (see Table 2 andFigure 3).

EXPRESSION, LOCALIZATION, AND ROLE OF ION CHANNELS IN HEALTHY PANCREATIC EPITHELIAL CELLS Potassium Channels

The relevance of K + channels in the exocrine pancreas received great attention in the 1970s-1980s, notably by Petersen's team, thanks to electrophysiological studies of ion channels on acinar pancreatic epithelial cells dissociated from the pancreas of different animal species. While several studies have shown the expression of different families of K + channels on both acinar and duct pancreatic cells [START_REF] Petersen | Electrophysiology of the pancreas[END_REF][START_REF] Bleich | The very small-conductance K+ channel KvLQT1 and epithelial function[END_REF][START_REF] Thevenod | Ion channels in secretory granules of the pancreas and their role in exocytosis and release of secretory proteins[END_REF][START_REF] Hayashi | Molecular basis of potassium channels in pancreatic duct epithelial cells[END_REF][START_REF] Venglovecz | Potassium channels in pancreatic duct epithelial cells: their role, function and pathophysiological relevance[END_REF], few studies have shown their physiological role in exocrine secretion.

Two excellent reviews have summarized the role of these channels in physiological process of ductal fluid secretion, likely by contributing to maintain the membrane potential and thereby providing driving forces for anion transport [START_REF] Hayashi | Molecular basis of potassium channels in pancreatic duct epithelial cells[END_REF][START_REF] Venglovecz | Potassium channels in pancreatic duct epithelial cells: their role, function and pathophysiological relevance[END_REF]. Among these channels the voltage-and Ca 2+ -activated K + , big conductance (BK, maxi-K), and the intermediate (IK, KCa3.1) Ca 2+ -activated K + channels have been intensely studied in pancreatic ductal cells. The BK which is activated by cAMP and PKA is found on the basolateral membrane of rat pancreatic duct cells (Gray et al., 1990a). The authors suggest its role in pancreatic bicarbonate secretion. BK is also found mainly expressed in the apical membrane of guinea-pig non-transformed pancreatic duct epithelial cells (PDEC) [START_REF] Venglovecz | Pathophysiological relevance of apical large-conductance Ca(2)+activated potassium channels in pancreatic duct epithelial cells[END_REF] where it regulates the bicarbonate secretion stimulated by the bile acid chenodeoxycholate likely through changes of the membrane potential. KCa3.1 was first characterized in cultured PDEC where it is expressed on the basolateral membrane of duct epithelial cells [START_REF] Nguyen | Calcium-activated potassium conductances on cultured nontransformed dog pancreatic duct epithelial cells[END_REF]. Activation of P2Y2R induced an increase of free intracellular calcium ([Ca 2+ ] i ) that activates KCa3.1, which in turn hyperpolarized the membrane potential, leading to a Cl -dependent bicarbonate secretion [START_REF] Jung | Pattern of Ca2+ increase determines the type of secretory mechanism activated in dog pancreatic duct epithelial cells[END_REF]. KCa3.1 was also found located on the basolateral and luminal membrane of pancreatic mouse and human duct cells [START_REF] Hayashi | An intermediateconductance Ca2+-activated K+ channel is important for secretion in pancreatic duct cells[END_REF]. The same authors demonstrated that both luminal and basolateral KCa3.1 channels were involved in the regulation of membrane potential.

In acinar cells, the membrane potential created by K + channels, and waves of [Ca 2+ ] i provide the necessary driving force for Cl -efflux through the luminal membrane, which is a key et al., 1994;[START_REF] Waldmann | Molecular cloning and functional expression of a novel amiloridesensitive Na+ channel[END_REF][START_REF] Zeiher | A mouse model for the delta F508 allele of cystic fibrosis[END_REF][START_REF] Novak | Where have all the Na+ channels gone? In search of functional ENaC in exocrine pancreas[END_REF][START_REF] Pascua | Ducts isolated from the pancreas of CFTR-null mice secrete fluid[END_REF]) [START_REF] Waldmann | Molecular cloning and functional expression of a novel amiloridesensitive Na+ channel[END_REF] ] i , from a Ca 2+ influx through SOCs in the basolateral membrane, where Cl -channels, Ca 2+ activated Cl - channels (CaCC) and different types of K + channels are activated to provide the efflux of their respected ions. K + channels also create a driving force by maintaining a negative membrane potential. The negative charge mediated by a high concentration of Cl -ions results in transport of Na + through tight junctions to the luminal space. NaCl makes the driving force for water to efflux through aquaporins and a cell shrinkage. This cell shrinkage reduces [Ca 2+ ] i , which inhibits Cl -and K + efflux through their channels and in parallel activates basolateral transporters and pumps to restore both Cl -and K + . The digestive enzymes are transported in the NaCl isotonic fluid to the ducts, which is low in HCO 3 -concentration in the proximal ducts, but this concentration increases through the transport to the distal duct cells.

The ductal fluid becomes rich in HCO 3 -, by a two-step process. The first step takes place in the proximal ducts, where Cl -/HCO 3 -exchangers secretes HCO 3 -and absorb Cl -and Cl -channels recycle Cl -. As in the acinar cells an osmotic reaction happens, where efflux of negative HCO 3 -and Na + drives water flow through aquaporins. This results in high concentration of HCO 3 -(~100 mM), a low concentration of Cl -(~25 mM) and a high fraction of water in the pancreatic juice. The second step takes place in the distal part of the ducts, where the specific Cl -channel CFTR changes selectivity to HCO 3 -and function as a HCO 3 -efflux channel to determine the final concentration of the HCO 3 -rich fluid (~140 mM). K + channels may, as in acini, take part in the secretion of K + and regulation of anion transport by maintaining the membrane potential in both the basolateral and luminal membrane. SOCs ensure the influx of Ca 2+ which takes part in regulation of ion channels through [Ca 2+ ] i as in acini. Activation or inhibition of P2 receptors by Ca 2+ signaling also regulate anion secretion through K + and Cl -channels. step in initiating fluid and electrolyte secretion (Lee et al., 2012). The activation of K + channels located on the basolateral membrane hyperpolarizes the resting membrane potential, promoting the driving force for luminal Cl -efflux through Cl - channels [START_REF] Petersen | Ca2+ signalling and Ca2+-activated ion channels in exocrine acinar cells[END_REF]. A Ca 2+ -dependent maxi-K + channel (200 pS) has been characterized upon stimulation with acetylcholine (ACh), cholecystokinin (CCK), and bombesin in pancreatic acinar cells [START_REF] Maruyama | Quantification of Ca2+-activated K+ channels under hormonal control in pig pancreas acinar cells[END_REF]Iwatsuki and Petersen, 1985a;[START_REF] Iwatsuki | Inhibition of Ca2+-activated K+ channels in pig pancreatic acinar cells by Ba2+, Ca2+, quinine and quinidine[END_REF][START_REF] Petersen | Human pancreatic acinar cells: studies of stimulus-secretion coupling[END_REF]Suzuki et al., 1985;[START_REF] Petersen | Electrophysiology of the pancreas[END_REF]. Moreover, [START_REF] Pearson | Neural and hormonal control of membrane conductance in the pig pancreatic acinar cell[END_REF] showed, on isolated pancreas acinar pig cells, that neural and hormonal (ACh, bombesin and pentagastrin) stimulation evokes a Ca 2+ -dependent cell hyperpolarization by causing an increase in membrane K + conductance [START_REF] Pearson | Neural and hormonal control of membrane conductance in the pig pancreatic acinar cell[END_REF]. An intermediate Ca 2+ -activated K + channel is also expressed in both the basolateral and the apical membranes of acinar cells [START_REF] Thompson-Vest | The distribution of intermediate-conductance, calcium-activated, potassium (IK) channels in epithelial cells[END_REF], but its role has not been studied. KCNQ1 (KVLQT1, Kv7.1) and KCNE1 (IsK, minK) have been found in abundance in pancreatic acinar cells [START_REF] Kottgen | Carbachol activates a K+ channel of very small conductance in the basolateral membrane of rat pancreatic acinar cells[END_REF][START_REF] Bleich | The very small-conductance K+ channel KvLQT1 and epithelial function[END_REF][START_REF] Demolombe | Differential expression of KvLQT1 and its regulator IsK in mouse epithelia[END_REF][START_REF] Warth | The multifaceted phenotype of the knockout mouse for the KCNE1 potassium channel gene[END_REF]Warth et al., 2002;[START_REF] Hayashi | An intermediateconductance Ca2+-activated K+ channel is important for secretion in pancreatic duct cells[END_REF]. By using mouse models associated with electrophysiological studies, Warth et al. (2002) showed that KCNQ1 was predominantly located at the basolateral membrane and its co-assemblage with KCNE1 leads to a voltage-dependent K + current that was increased by cholinergic stimulation and inhibited by the KCNQ1 blocker [START_REF] Kim | Voltage-dependent, slowly activating K+ current (I(Ks)) and its augmentation by carbachol in rat pancreatic acini[END_REF][START_REF] Kottgen | Carbachol activates a K+ channel of very small conductance in the basolateral membrane of rat pancreatic acinar cells[END_REF]Warth et al., 2002). The fact that inhibition of KCNQ1 channels diminishes intestinal Cl - secretion, made the authors suggest its involvement in pancreatic electrolyte secretion process.

K + inwardly rectifying channels (Kir) channels are expressed in exocrine pancreas. Kir 2.1,Kir2.3,Kir7.1,Kir5.1,and Kir4.2 were detected in rat pancreatic acini [START_REF] Kim | Inwardly rectifying K+ channels in the basolateral membrane of rat pancreatic acini[END_REF][START_REF] Pessia | Differential pH sensitivity of Kir4.1 and Kir4.2 potassium channels and their modulation by heteropolymerisation with Kir5.1[END_REF]. In-situ hybridization analysis confirmed the expression of Kir5.1 in human pancreatic acinar and ductal 2. The channels shown to be expressed in PDAC, but where the role is unknown are also shown in Table 2. Some ion channels have shown to be to have a low expression in PDAC, which correlates with other clinical factors. The ion channels are grouped as progression and aggressiveness markers, diagnostic markers or therapeutic targets. Among all ion channels, their expression (except CFTR) have been shown to be correlated with a low overall survival.

cells [START_REF] Liu | The human inward rectifier K(+) channel subunit kir5.1 (KCNJ16) maps to chromosome 17q25 and is expressed in kidney and pancreas[END_REF]. Moreover, it has been suggested that Kir5.1 forms heteromeric channels with Kir4.2 in rat pancreas and is involved in the pH-dependent regulation of K + flux [START_REF] Pessia | Differential pH sensitivity of Kir4.1 and Kir4.2 potassium channels and their modulation by heteropolymerisation with Kir5.1[END_REF]. Kir1.3 was also detected by northern blot analysis, in human pancreas [START_REF] Shuck | Cloning and characterization of two K+ inward rectifier (Kir) 1.1 potassium channel homologs from human kidney (Kir1.2 and Kir1.3)[END_REF]. The 2-Pore K + channel (K 2 P) family has also been found in human exocrine pancreas; however, their localization and function are still unknown. For example, TALK-1 and TALK-2 are very specifically expressed in exocrine pancreas where they are activated by NOS and ROS [START_REF] Girard | Genomic and functional characteristics of novel human pancreatic 2P domain K(+) channels[END_REF][START_REF] Duprat | Pancreatic two P domain K+ channels TALK-1 and TALK-2 are activated by nitric oxide and reactive oxygen species[END_REF], while TASK-2 is expressed in both exocrine and endocrine pancreas [START_REF] Duprat | TASK, a human background K+ channel to sense external pH variations near physiological pH[END_REF][START_REF] Duprat | Pancreatic two P domain K+ channels TALK-1 and TALK-2 are activated by nitric oxide and reactive oxygen species[END_REF].

Calcium Channels

As Petersen and co-workers showed the relevance of K + channels in exocrine pancreas, they have also described the role of Ca 2+ signaling, in pancreatic acinar cells (Petersen, 2014). In the early 70's they showed that movements of Ca 2+ was evoked upon ACh stimulation released Ca 2+ from intracellular stores and that only a small part of Ca 2+ was taken up from the extracellular solution [START_REF] Case | The relationship between calcium exchange and enzyme secretion in the isolated rat pancreas[END_REF][START_REF] Matthews | Pancreatic acinar cells: acetylcholine-induced membrane depolarization, calcium efflux and amylase release[END_REF]. This Ca 2+ signaling is involved in exocrine pancreatic fluid secretion as both acinar and duct cells in pancreas are regulated by receptors that change [Ca 2+ ] i , which activates epithelial Ca 2+ -dependent K + and Cl -ion channels, thereby enzyme and fluid secretion (Petersen, 2014). The Ca 2+ signal is initiated by ACh or CCK, binding to specific receptors [START_REF] Case | The relationship between calcium exchange and enzyme secretion in the isolated rat pancreas[END_REF][START_REF] Matthews | Pancreatic acinar cells: acetylcholine-induced membrane depolarization, calcium efflux and amylase release[END_REF][START_REF] Petersen | Pancreatic acinar cells: the role of calcium in stimulus-secretion coupling[END_REF], which generates specific Ca 2+ signals. These signals start by Ca 2+ activating phospholipase C, which hydrolyzes PIP 2 , hence generating IP 3 and diacylglycerol. IP 3 binds to IP 3 receptors located in the ER at the apical pole of the acinar cells mediating a Ca 2+ wave to the basal pole [START_REF] Mogami | Ca2+ flow via tunnels in polarized cells: recharging of apical Ca2+ stores by focal Ca2+ entry through basal membrane patch[END_REF]Hong et al., 2011). This evokes a Ca 2+ ER store depletion that results in clustering of the ER Ca 2+ sensor STIM1, which activates store-operated channels (SOCs) and transient receptor potential (TRP) channels, leading to Ca 2+ influx [START_REF] Petersen | Polarized calcium signaling in exocrine gland cells[END_REF]. Members and regulators of SOCs are the SOC channel pore-forming ORAI proteins (ORAI1-3) and their regulators STIM (STIM1-2) [START_REF] Hoth | The neglected CRAC proteins: Orai2, Orai3, and STIM2[END_REF]. ORAI1 is the best described among these and are found to be expressed at the apical membrane of pancreatic acinar cells where it colocalizes with IP 3 R (Hong et al., 2011;[START_REF] Lur | InsP(3)receptors and Orai channels in pancreatic acinar cells: co-localization and its consequences[END_REF] and at the basolateral membrane where it colocalizes with STIM1 [START_REF] Lur | InsP(3)receptors and Orai channels in pancreatic acinar cells: co-localization and its consequences[END_REF]. Recently, it has been shown that inhibition of ORAI1 in pancreatic acinar cells abolished SOC entry upon stimulation with thapsigargin, CCK, and the bile acid taurolithocholic acid 3-sulfate, indicating that ORAI1 mediates SOC entry in pancreatic acinar cells [START_REF] Gerasimenko | Ca2+ release-activated Ca2+ channel blockade as a potential tool in antipancreatitis therapy[END_REF][START_REF] Wen | Inhibitors of ORAI1 Prevent Cytosolic Calcium-Associated Injury of Human Pancreatic Acinar Cells and Acute Pancreatitis in 3 Mouse Models[END_REF]. TRPC channels have also been found to participate or influence store-dependent Ca 2+ influx in pancreatic acinar cells. TRPC1 was found to localize both at the apical and lateral regions of the basolateral membrane, and pancreatic acinar cells isolated from TRPC1 -/ -mice showed reduced Ca 2+ influx and Ca 2+ oscillation frequency (Hong et al., 2011). The role of TRPC1 in pancreatic acinar cells is not yet known, but it is suggested to have a similar role as in salivary glands, where they regulate fluid secretion and Ca 2+ activated K + channels (Liu et al., 2007). TRPC3 was found in the junctional site of the apical pole and the basolateral membrane of pancreatic acini cells and in TRPC3 -/ -mice a reduction of Ca 2+ influx was seen [START_REF] Kim | Homer 1 mediates store-and inositol 1,4,5-trisphosphate receptor-dependent translocation and retrieval of TRPC3 to the plasma membrane[END_REF]. Furthermore, TRPC6 seemed to be expressed in the pancreatic acini cells, but its localization and role are unknown [START_REF] Kim | Homer 1 mediates store-and inositol 1,4,5-trisphosphate receptor-dependent translocation and retrieval of TRPC3 to the plasma membrane[END_REF]. These data suggest that TRPC channels are involved in the SOC entry of pancreatic acini cells and could contribute to fluid secretion. Other TRP channels have been found to be expressed in exocrine pancreas; TRPV6 (Kim et al., 2013), TRPM7 [START_REF] Yee | Transient receptor potential ion channel Trpm7 regulates exocrine pancreatic epithelial proliferation by Mg2+sensitive Socs3a signaling in development and cancer[END_REF] and TRPM8 (Yee et al., 2010). However, only the role of TRPM7 is described. In a zebra fish model, it has been found that TRPM7 is involved in the developmental processes of exocrine pancreas, which was linked to Mg 2+ signaling [START_REF] Yee | Transient receptor potential ion channel Trpm7 regulates exocrine pancreatic epithelial proliferation by Mg2+sensitive Socs3a signaling in development and cancer[END_REF]. Diminish of cell cycle progression and cell growth in TRPM7-mutated zebra fish models attenuated proliferation of exocrine pancreatic epithelia. This was partially rescued by adding extra Mg 2+ to the embryo medium [START_REF] Yee | Transient receptor potential ion channel Trpm7 regulates exocrine pancreatic epithelial proliferation by Mg2+sensitive Socs3a signaling in development and cancer[END_REF]. Furthermore, the proliferation was also regulated by suppressor of cytokine signaling 3a (socs3a), indicating that TRPM7 plays a role in the development of exocrine pancreas [START_REF] Yee | Transient receptor potential ion channel Trpm7 regulates exocrine pancreatic epithelial proliferation by Mg2+sensitive Socs3a signaling in development and cancer[END_REF], but the physiological role in fluid secretion is yet to be determined.

In duct cells, HCO 3 -secretion is mediated by cAMP/Ca 2+ signaling systems. Through specific Ca 2+ channels and Ca 2+ activated ion channels (Ca 2+ -activated K + and Cl -channels), Ca 2+ can act as key player in regulation and secretion of pancreatic juices (Lee M. G. et al., 2012). The localization of SOCs in duct cells, due to HCO 3 -fluid secretion, is not well studied. However, it has been found that SOC-mediated Ca 2+ influx can be a driving force for exocytosis, evoked by trypsin [START_REF] Kim | Protease-activated receptor-2 increases exocytosis via multiple signal transduction pathways in pancreatic duct epithelial cells[END_REF] in dog PDEC. The same authors have shown the function of SOCs in dog PDEC where the typical inward rectifying current was found, as for other types of epithelial cells (Kim et al., 2013). Furthermore, it was found that STIM1, STIM2, ORAI1, ORAI2, and ORAI3 as well as TRPC1 and TRPV6 are all expressed in dog PDEC, where ORAI3 was shown to be the dominant expressing type (Kim et al., 2013). Moreover, STIM1 and ORAI3 are colocalized in both single cell PDEC and polarized monolayers upon thapsigargin treatment (Kim et al., 2013). Using thapsigargin, the same authors showed an increased [Ca 2+ ] i only at the basolateral membrane, indicating that SOCs are mainly located at this site of the plasma membrane (Kim et al., 2013). It might be hypothesized that the localization of SOCs and Ca 2+ -activated ion channels are the same in pancreatic duct cells as in acinar cells, and that they play a role in HCO 3 -secretion, as they play a role in enzyme and fluid secretion in acinar cells [START_REF] Maleth | Calcium signaling in pancreatic ductal epithelial cells: an old friend and a nasty enemy[END_REF].

Aquaporin Channels

Aquaporins (AQPs) are activated by Ca 2+ and mediate a water flow through the luminal membrane. The role of some AQP types in physiological and pathophysiological processes of exocrine pancreas has already been reviewed [START_REF] Burghardt | The role of aquaporin water channels in fluid secretion by the exocrine pancreas[END_REF][START_REF] Delporte | Aquaporins in salivary glands and pancreas[END_REF][START_REF] Arsenijevic | Aquaporins Involvement in Pancreas Physiology and in Pancreatic Diseases[END_REF]. AQP1 is expressed at the apical and basolateral membrane of centro-acinar cells and intercalated ductal cells [START_REF] Burghardt | Distribution of aquaporin water channels AQP1 and AQP5 in the ductal system of the human pancreas[END_REF][START_REF] Burghardt | The role of aquaporin water channels in fluid secretion by the exocrine pancreas[END_REF] and is also expressed in capillary endothelial cells and at the pancreatic zymogen granule membrane [START_REF] Cho | Aquaporin 1 regulates GTP-induced rapid gating of water in secretory vesicles[END_REF][START_REF] Burghardt | Distribution of aquaporin water channels AQP1 and AQP5 in the ductal system of the human pancreas[END_REF]. AQP5 has been found to be co-localized with AQP1 in the apical membrane of centro-acinar cells and intercalated ductal cells [START_REF] Burghardt | Distribution of aquaporin water channels AQP1 and AQP5 in the ductal system of the human pancreas[END_REF]. Otherwise, AQP8 is expressed only in acinar cells in the apical membrane [START_REF] Isokpehi | Integrative sequence and tissue expression profiling of chicken and mammalian aquaporins[END_REF]. In the two-step process of pancreatic fluid secretion, AQP8 in the pancreatic acinar cells ensures the water flow across the plasma membrane, where NaCl makes the driving force. In the pancreatic ductal cells the driving force is maintained by HCO3 -and Na + through AQP1 and AQP5 [START_REF] Burghardt | The role of aquaporin water channels in fluid secretion by the exocrine pancreas[END_REF]. However, this theory is not well explained, since pancreatic fluid secretion was not found to be altered in AQP1, AQP5, AQP8, or AQP12 knockout mice [START_REF] Ma | Defective dietary fat processing in transgenic mice lacking aquaporin-1 water channels[END_REF][START_REF] Yang | Phenotype analysis of aquaporin-8 null mice[END_REF][START_REF] Ohta | Pancreas-specific aquaporin 12 null mice showed increased susceptibility to caerulein-induced acute pancreatitis[END_REF]. Recently, the role of AQP1 has been confirmed to be involved in pancreatic fluid and bicarbonate secretion in an AQP1-knockout mouse model [START_REF] Venglovecz | The Importance of Aquaporin 1 in Pancreatitis and Its Relation to the CFTR Cl(-) Channel[END_REF].

Chloride Channels

In the early 80's the evidence for Ca 2+ activated Cl -channels (CaCC) were presented by whole-cell patch clamp and singlechannel currents in rat lacrimal acinar. Marty and co-workers showed that Cl -currents were evoked by muscarinic receptor activation and Ca 2+ , as previously demonstrated for the K + current [START_REF] Marty | Three types of calciumdependent channel in rat lacrimal glands[END_REF][START_REF] Petersen | Stimulus-secretion coupling: cytoplasmic calcium signals and the control of ion channels in exocrine acinar cells[END_REF]. Shortly after, following investigations confirmed this Ca 2+ activated Cl - current in rat pancreatic acinar cells [START_REF] Randriamampita | Calcium and secretagogues-induced conductances in rat exocrine pancreas[END_REF]. The localization of these Ca 2+ -dependent channels was proposed to be both on the basolateral and the luminal site, but speculations and further studies revealed that the localization of CaCC was found in the luminal membrane of pancreatic acinar cells, where an early activation of Cl -currents was seen upon ACh stimulation [START_REF] Kasai | Cytosolic Ca2+ gradients triggering unidirectional fluid secretion from exocrine pancreas[END_REF][START_REF] Zdebik | Chloride channels in the luminal membrane of rat pancreatic acini[END_REF]. A small delayed current was found after Ca 2+ has spread to the basal pole of the cell, suggesting that CaCC are highly located at the luminal membrane and to some extent in the basolateral of pancreatic acinar cells [START_REF] Kasai | Cytosolic Ca2+ gradients triggering unidirectional fluid secretion from exocrine pancreas[END_REF]. New evidence shows clearly that CaCC are exclusively localized to the apical membrane and regulate pancreatic fluid secretion [START_REF] Marty | Three types of calciumdependent channel in rat lacrimal glands[END_REF][START_REF] Kasai | Cytosolic Ca2+ gradients triggering unidirectional fluid secretion from exocrine pancreas[END_REF]Park et al., 2001).

Gray and his team have investigated the properties and roles of Cl -channels in pancreatic duct epithelial cells. They and others, found two types of Cl -channels in pancreatic ducts cells; cystic fibrosis transmembrane conductance regulator (CFTR), regulated by rises in [cAMP] I and CaCC, regulated by an increase in [Ca 2+ ] i [START_REF] Gray | Two types of chloride channel on duct cells cultured from human fetal pancreas[END_REF][START_REF] Riordan | Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA[END_REF]Gray et al., 1990b;[START_REF] Gray | cAMP-regulated whole cell chloride currents in pancreatic duct cells[END_REF][START_REF] Al-Nakkash | Bovine pancreatic duct cells express cAMP-and Ca(2+)-activated apical membrane Cl-conductances[END_REF][START_REF] Nguyen | Characterization of two distinct chloride channels in cultured dog pancreatic duct epithelial cells[END_REF]. Both types of channels have been found in several species and to be localized in the apical membrane of duct cells (Gray et al., 1990b;[START_REF] Marino | Localization of the cystic fibrosis transmembrane conductance regulator in pancreas[END_REF][START_REF] Ashton | Regulation of fluid secretion and intracellular messengers in isolated rat pancreatic ducts by acetylcholine[END_REF][START_REF] Evans | Interactions between secretin and acetylcholine in the regulation of fluid secretion by isolated rat pancreatic ducts[END_REF][START_REF] Al-Nakkash | Bovine pancreatic duct cells express cAMP-and Ca(2+)-activated apical membrane Cl-conductances[END_REF][START_REF] Zeng | Immuno and functional characterization of CFTR in submandibular and pancreatic acinar and duct cells[END_REF]Ishiguro et al., 2002;Wang and Novak, 2013;[START_REF] Yokoyama | Different immunohistochemical localization for TMEM16A and CFTR in acinar and ductal cells of rat major salivary glands and exocrine pancreas[END_REF]. CaCC have been found in rodent pancreatic ducts. Here, it was shown that increases in [Ca 2+ ]i, evoked by either ionomycin or ACh activated the Cl -channels (Gray et al., 1990b;[START_REF] Gray | Chloride channels and cystic fibrosis of the pancreas[END_REF]. Furthermore, Cl -currents were detected in mouse pancreatic ducts with no detectable function of CFTR, which indicates that these currents are carried by an ion channel that is distinct from CFTR [START_REF] Gray | CFTR and calcium-activated chloride currents in pancreatic duct cells of a transgenic CF mouse[END_REF][START_REF] Winpenny | Calcium-activated chloride conductance is not increased in pancreatic duct cells of CF mice[END_REF].

Until now, it has been shown that mammalian TMEM16 proteins have different physiological functions. TMEM16A and B are suggested to be CaCC, where both of TMEM16E and F are suggested to have scramblase and channel activities. TMEM16D, G, and J are suggested to only have a scramblase activity. Therefore, the channel nature of all TMEM16 proteins is still not clearly identified [Reviewed in [START_REF] Falzone | Known structures and unknown mechanisms of TMEM16 scramblases and channels[END_REF]]. Recently, it has been suggested that TMEM16A, of the TMEM16/Anoctamin family, is the CaCC gene candidate for Cl -secretion [START_REF] Caputo | TMEM16A, a membrane protein associated with calcium-dependent chloride channel activity[END_REF][START_REF] Schroeder | Expression cloning of TMEM16A as a calcium-activated chloride channel subunit[END_REF][START_REF] Yang | TMEM16A confers receptor-activated calcium-dependent chloride conductance[END_REF]. In rodent pancreatic acinar cells and intercalated ducts, expression of TMEM16A was found by immunostaining and RT-PCR [START_REF] Huang | Studies on expression and function of the TMEM16A calcium-activated chloride channel[END_REF][START_REF] Yokoyama | Different immunohistochemical localization for TMEM16A and CFTR in acinar and ductal cells of rat major salivary glands and exocrine pancreas[END_REF]. The biophysical properties of the channel agreed with Ca 2+dependent Cl -currents, described elsewhere [START_REF] Yang | TMEM16A confers receptor-activated calcium-dependent chloride conductance[END_REF]. Another study demonstrated that Ca 2+ -dependent Cl -secretion was defective in acinar cells from TMEM16A-null mice, indicating that TMEM16A has a physiological role in pancreatic fluid secretion [START_REF] Ousingsawat | Loss of TMEM16A causes a defect in epithelial Ca2+dependent chloride transport[END_REF].

The model of how Cl -is secreted through channels in exocrine pancreas is described as a two-step process, starting by the activation by ACh or CCK, which trigger an IP 3mediated rise of cytosolic Ca 2+ [START_REF] Iwatsuki | Pancreatic acinar cells: localization of acetylcholine receptors and the importance of chloride and calcium for acetylcholine-evoked depolarization[END_REF][START_REF] Reubi | Distribution of CCK1 and CCK2 receptors in normal and diseased human pancreatic tissue[END_REF][START_REF] Gautam | Cholinergic stimulation of amylase secretion from pancreatic acinar cells studied with muscarinic acetylcholine receptor mutant mice[END_REF][START_REF] Wang | How does cholecystokinin stimulate exocrine pancreatic secretion? From birds, rodents, to humans[END_REF]. In response to this stimulation, the NaCl rich fluid starts to be produced (Hegyi and Petersen, 2013). At the basolateral membrane the Na + -K + -2Cl -cotransporters (NKCC), Cl -/ HCO3 -exchangers and Na + /K + pumps are activated, to function together to establish the Cl -uptake mechanism. The increased [Ca 2+ ] i enhances the Cl -conductance of the luminal membrane and a K + channel-mediated hyperpolarization of the basolateral membrane creates the driving force for Cl -efflux to the luminal space. At the apical membrane, Cl -ions pass through the Cl -channels. This hormonal stimulation by ACh and CCK, leading to increased [Ca 2+ ] i, plays the central role in activating enzyme release and electrogenic Cl -secretion [START_REF] Petersen | Electrophysiology of pancreatic and salivary acinar cells[END_REF][START_REF] Mogami | Ca2+ flow via tunnels in polarized cells: recharging of apical Ca2+ stores by focal Ca2+ entry through basal membrane patch[END_REF][START_REF] Giovannucci | Cytosolic Ca(2+) and Ca(2+)-activated Cl(-) current dynamics: insights from two functionally distinct mouse exocrine cells[END_REF][START_REF] Petersen | Ca2+ signalling and Ca2+-activated ion channels in exocrine acinar cells[END_REF]. While Cl -passes through the acinar cells a negative charge in the luminal space arises, which moves Na + from the interstitial space to the acinar lumen via the paracellular pathway through leaky tight junctions, resulting in NaCl secretion. In physiological circumstances the acinar luminal Cl -concentration contains 135 mM Cl and 25 mM HCO3- [START_REF] Park | Dynamic regulation of CFTR bicarbonate permeability by [Cl-]i and its role in pancreatic bicarbonate secretion[END_REF]. The second step in pancreatic fluid secretion occurs in the duct cells and depends on the high concentration of luminal Cl -as it activates HCO 3 -efflux through Cl -/HCO 3 -exchangers, which elevates the luminal HCO 3 concentration and thereby activates CFTR functioning to secrete Cl -and to some extend HCO 3 - [START_REF] Ishiguro | CFTR functions as a bicarbonate channel in pancreatic duct cells[END_REF][START_REF] Wilschanski | The cystic fibrosis of exocrine pancreas[END_REF]. The HCO 3 -concentration in the fluid increases along the ducts, while the Cl -concentration reciprocally decreases. By the time the pancreatic fluid leaves the ducts the ratio is inverse, with the HCO 3 -concentration around 140 mM and the Cl - concentration around 20 mM [START_REF] Park | Dynamic regulation of CFTR bicarbonate permeability by [Cl-]i and its role in pancreatic bicarbonate secretion[END_REF]. These specific concentrations will inhibit CFTR and Cl -/HCO 3 -exchangers to prevent HCO 3 -reabsorption [START_REF] Wright | Novel regulation of cystic fibrosis transmembrane conductance regulator (CFTR) channel gating by external chloride[END_REF].

Sodium Channels

The efflux of Na + through tight junctions in both the acinar and ductal cells is a part of regulating the HCO 3 -rich fluid to be isotonic and to keep the cell osmolarity (Lee M. G. et al., 2012). The expression and function of Na + channels in normal pancreatic tissue are controversial. Some studies have shown functional expression of amiloride sensitive epithelial sodium channels (ENaC) in interlobular ducts from mice [START_REF] Zeiher | A mouse model for the delta F508 allele of cystic fibrosis[END_REF][START_REF] Pascua | Ducts isolated from the pancreas of CFTR-null mice secrete fluid[END_REF]. Moreover, transcripts of different subunits of ENaC have been also detected in human pancreas [START_REF] Mcdonald | Cloning, expression, and tissue distribution of a human amiloride-sensitive Na+ channel[END_REF][START_REF] Waldmann | Molecular cloning and functional expression of a novel amiloridesensitive Na+ channel[END_REF][START_REF] Novak | Where have all the Na+ channels gone? In search of functional ENaC in exocrine pancreas[END_REF]. Other studies have shown no functional activity of ENaC in isolated small ducts from rats or in PDAC cell lines Capan-1 and HPAF [START_REF] Novak | Where have all the Na+ channels gone? In search of functional ENaC in exocrine pancreas[END_REF][START_REF] Fong | Characterization of vectorial chloride transport pathways in the human pancreatic duct adenocarcinoma cell line HPAF[END_REF]Wang and Novak, 2013), which is in accordance with the secretory nature of pancreatic ducts.

EXPRESSION OF ION CHANNELS IN PDAC CELLS AND HUMAN TISSUES, FUNCTION, AND ASSOCIATED SIGNALING PATHWAYS IN CELL LINES Potassium Channels in PDAC

Kv Channels

It is widely accepted that Kv channels participate in cancer development and progression and their expression has shown to be aberrant in several types of tumor tissue, also in PDAC [START_REF] Serrano-Novillo | Implication of Voltage-Gated Potassium Channels in Neoplastic Cell Proliferation[END_REF][START_REF] Teisseyre | Voltage-Gated Potassium Channel Kv1.3 as a Target in Therapy of Cancer[END_REF]. It has been shown that Kv1.3 is expressed in different human PDAC cell lines, harboring mutation in p53 [START_REF] Zaccagnino | Tumor-reducing effect of the clinically used drug clofazimine in a SCID mouse model of pancreatic ductal adenocarcinoma[END_REF]. The authors demonstrate that the inhibition of Kv1.3 by clofazimine, induces apoptosis in-vitro and reduces tumor weight in-vivo [START_REF] Zaccagnino | Tumor-reducing effect of the clinically used drug clofazimine in a SCID mouse model of pancreatic ductal adenocarcinoma[END_REF]. Another study has reported a remodeling of Kv1.3 and Kv1.5 on a large cohort of human tissue samples [START_REF] Bielanska | Voltage-dependent potassium channels Kv1.3 and Kv1.5 in human cancer[END_REF]. In fact, they showed that protein expression of Kv1.3 was lower in PDAC tissue, while Kv1.5 had a higher protein expression in PDAC tissue compared to healthy tissue [START_REF] Bielanska | Voltage-dependent potassium channels Kv1.3 and Kv1.5 in human cancer[END_REF][START_REF] Comes | The voltage-dependent K(+) channels Kv1.3 and Kv1.5 in human cancer[END_REF]. The low expression of Kv1.3 in PDAC can be explained by a hypermethylation of the KCNA3 gene promoter (Brevet et al., 2009). Similar to Kv1.3 the expression of Kv7.1 has recently been shown to be down-regulated in PDAC (Zaccagnino et al., 2016;Tawfik et al., 2020). KCNQ1 (gene coding for Kv7.1) was downregulated in PDAC tissue, compared to normal tissue. In addition, downregulation of KCNQ1 was found in a system comparing PDAC A818-6 cells grown as a highly malignant undifferentiated monolayer (ML) or as threedimensional (3D) single layer hollow spheres (HS). Database analysis showed that KCNQ1 was involved in the enrichment of pancreatic secretion in normal pancreatic epithelium and HS, suggesting that a downregulation of KCNQ1 might impair fluid secretion in PDAC and ML cells, while being maintained in normal pancreas and HS cells (Tawfik et al., 2020). Another comprehensive study has been investigating the gene-expression levels of the transportome in PDAC and normal specimens (Zaccagnino et al., 2016). The authors showed the downregulation of five different K + channels, including the K + voltage-gated channels; KCNQ1 and KCNE1. Moreover, their results showed a downregulation of genes coding for the Kir4.2 (KCNJ15), Kir5.1 (KCNJ16), and the K 2 P channel TWIK-3 (KCNK7). In addition, the expression of KCNJ15 and KCNK7 was associated with the expression of EMT transcription factors (Zaccagnino et al., 2016). The authors also suggested that the higher expression of K + channels in normal pancreatic epithelium takes part in setting the resting membrane potential, which generates the driving force of fluid and ion secretion in the pancreatic ducts (Zaccagnino et al., 2016).

Kv10.1 is another Kv channel that has been reported in pancreatic cancer. The expression of Kv10.1 in peripheral tissues is very restricted [START_REF] Hemmerlein | Overexpression of Eag1 potassium channels in clinical tumours[END_REF], including pancreatic tissue [START_REF] Pardo | Oncogenic potential of EAG K(+) channels[END_REF]. A xenograft mouse model of pancreatic cancer showed that monoclonal antibodies blocking the Kv10.1 current exerts antitumor activity [START_REF] Gomez-Varela | Monoclonal antibody blockade of the human Eag1 potassium channel function exerts antitumor activity[END_REF]. Because Kv10.1 is nearly absent in normal tissue, there is a certain tumor selectivity for Kv10.1 expression, which gives rise to the possibility that Kv10.1 can be used as a targeting channel for the delivery of cytotoxic compounds [START_REF] Pardo | The roles of K(+) channels in cancer[END_REF]. However, the expression and function of Kv10.1 in PDAC must be further investigated.

Interestingly, another Kv channel, Kv11.1 has been implicated as an oncogene in various cancers, including PDAC [START_REF] Arcangeli | Interaction of tumour cells with their microenvironment: ion channels and cell adhesion molecules. A focus on pancreatic cancer[END_REF]Lastraioli et al., 2015a). In contrast, to the Kv10.1 expression, Kv11.1 is ubiquitously expressed in normal human tissues including heart where it is mainly expressed [START_REF] Sanguinetti | A mechanistic link between an inherited and an acquired cardiac arrhythmia: HERG encodes the IKr potassium channel[END_REF][START_REF] Mcdonald | A minK-HERG complex regulates the cardiac potassium current I(Kr)[END_REF][START_REF] Pond | Expression of distinct ERG proteins in rat, mouse, and human heart. Relation to functional I(Kr) channels[END_REF][START_REF] Camacho | Ether a go-go potassium channels and cancer[END_REF][START_REF] Comes | Involvement of potassium channels in the progression of cancer to a more malignant phenotype[END_REF]. KCNH2 (gene coding for Kv11.1) was identified as a gene with somatic mutations that could drive the metastatic process of PDAC [START_REF] Zhou | Exome sequencing and digital PCR analyses reveal novel mutated genes related to the metastasis of pancreatic ductal adenocarcinoma[END_REF]. Here, exome sequencing analysis showed that KCNH2 clustered into a single network related to cancer development. To investigate the involvement of KCNH2 in PDAC progression, the authors showed that knockdown of Kv11.1 reduced proliferation, colony formation and migration in PDAC cell lines. Immunohistochemical analysis of Kv11.1 expression showed expression in 8 out of 38 (21%) PDAC tissues, versus one out of 37 (2.7%) in normal tissues [START_REF] Zhou | Exome sequencing and digital PCR analyses reveal novel mutated genes related to the metastasis of pancreatic ductal adenocarcinoma[END_REF]. Another study further investigated the expression and role of Kv11.1 in PDAC [START_REF] Feng | HERG1 functions as an oncogene in pancreatic cancer and is downregulated by miR-96[END_REF]. Here, immunohistochemical analysis confirmed a strong expression in PDAC tissues, with highest expression in the cytoplasm and membrane. In contrary, normal tissue showed only weak expression. The expression was confirmed in PDAC cell lines [START_REF] Feng | HERG1 functions as an oncogene in pancreatic cancer and is downregulated by miR-96[END_REF]. Knockdown of Kv11.1 showed a significant decreased proliferation rate, higher number of cells undergoing apoptosis, cell cycle arrest in G1 phase and a reduction of migration and invasion, suggesting that Kv11.1 has a role in different aspects of PDAC progression [START_REF] Feng | HERG1 functions as an oncogene in pancreatic cancer and is downregulated by miR-96[END_REF]. This was confirmed in a xenograft mouse model, were a knockdown of Kv11.1 in CFPAC-1 cells showed reduced tumor growth and fewer metastatic nodules, compared to tumors in mice injected with control cells [START_REF] Feng | HERG1 functions as an oncogene in pancreatic cancer and is downregulated by miR-96[END_REF]. Furthermore, it was found that miR-96 was downregulated in tumor tissue and PDAC cells. The overexpression of miR-96 reduced cell proliferation, migration, and invasion in-vitro and reduced the Kv11.1 expression, tumor growth, and formation of metastasis in-vivo [START_REF] Feng | HERG1 functions as an oncogene in pancreatic cancer and is downregulated by miR-96[END_REF]. This indicates that Kv11.1 could function as an oncogene in PDAC and be a potential target of miR-96 [START_REF] Feng | HERG1 functions as an oncogene in pancreatic cancer and is downregulated by miR-96[END_REF]. Further investigations showed that Kv11.1 promotes pancreatic cancer cell migration, by modulation of F-actin organization and dynamics (Lastraioli et al., 2015b) suggesting its involvement in cancer metastasis [START_REF] Arcangeli | Interaction of tumour cells with their microenvironment: ion channels and cell adhesion molecules. A focus on pancreatic cancer[END_REF][START_REF] Manoli | The Activity of Kv 11.1 Potassium Channel Modulates F-Actin Organization During Cell Migration of Pancreatic Ductal Adenocarcinoma Cells[END_REF].

KCa Channels/KCa3.1/IK IK (KCa3.1) channels are the K + channels most frequently studied among this family in PDAC. Even though, transcripts of KCa4.1 and KCa4.2 also have been shown in some cell lines [START_REF] Hayashi | An intermediateconductance Ca2+-activated K+ channel is important for secretion in pancreatic duct cells[END_REF]. Investigation of the KCa3.1 mRNA expression in primary pancreatic cancer tumors show that 8 of 9 tumors (89%) contain a 6-to 66-fold higher expression, compared to normal pancreatic tissue [START_REF] Jager | Blockage of intermediate-conductance Ca2+-activated K+ channels inhibit human pancreatic cancer cell growth in vitro[END_REF]. KCa3.1 is also found overexpressed in several PDAC cell lines [START_REF] Jager | Blockage of intermediate-conductance Ca2+-activated K+ channels inhibit human pancreatic cancer cell growth in vitro[END_REF]. The over-expression of KCa3.1 was associated with an increased Ca 2+ -activated K + -current. Pharmacological inhibition (by TRAM-34, Clotrimazole) of KCa3.1 completely suppressed cell proliferation of MiaPaCa-2 and BxPC-3 cells but not PANC-1 cells [START_REF] Jager | Blockage of intermediate-conductance Ca2+-activated K+ channels inhibit human pancreatic cancer cell growth in vitro[END_REF]. Moreover, application of [Ca 2+ ] o while inhibiting with TRAM-34 or Clotrimazole rescued the MiaPaCa-2 and BxPC-3 cell proliferation but did not affect this of PANC-1 suggesting that PANC-1 cell line grows independently of functional KCa3.1 channels [START_REF] Jager | Blockage of intermediate-conductance Ca2+-activated K+ channels inhibit human pancreatic cancer cell growth in vitro[END_REF]. Bonito and co-workers have also reported the role of KCa3.1 in PDAC cell proliferation and migration [START_REF] Bonito | KCa3.1 (IK) modulates pancreatic cancer cell migration, invasion and proliferation: anomalous effects on TRAM-34[END_REF]. They showed a significant mRNA upregulation of KCa3.1 in MiaPaCa-2 and BxPC-3, but not in Capan-1 and PANC-1 cells. In addition, Patch clamp measurements revealed a Ca 2+activated K + current, which was reduced by TRAM-34 and clotrimazole. Interestingly, a transient gene silencing of KCa3.1 in MiaPaCa-2 cells completely abolished the Ca 2+ current [START_REF] Bonito | KCa3.1 (IK) modulates pancreatic cancer cell migration, invasion and proliferation: anomalous effects on TRAM-34[END_REF]. MiaPaca-2 cell proliferation was inhibited with TRAM-34 and 1% FBS, whereas no effect was found by application of TRAM-34 and 10% FBS in the culture media, as shown before [START_REF] Jager | Blockage of intermediate-conductance Ca2+-activated K+ channels inhibit human pancreatic cancer cell growth in vitro[END_REF]. Silencing of KCa3.1 removed the ability of MiaPaCa-2 cells to proliferate, and attenuated their cell invasion and migration. Surprisingly treatment upon TRAM-34 or clotrimazole increased cell migration. It was hypothesized that this could be due to Ca 2+ homeostasis, which was investigated by Ca 2+ imaging that confirmed that TRAM-34 evoked an increase of [Ca 2+ ] i [START_REF] Bonito | KCa3.1 (IK) modulates pancreatic cancer cell migration, invasion and proliferation: anomalous effects on TRAM-34[END_REF] possibly leading to promotion of cell migration [START_REF] Lotz | K+ channel inhibition accelerates intestinal epithelial cell wound healing[END_REF]. This indicates that KCa3.1 expression and function are important for cell proliferation, migration and invasion [START_REF] Bonito | KCa3.1 (IK) modulates pancreatic cancer cell migration, invasion and proliferation: anomalous effects on TRAM-34[END_REF]. Another study has identified KCa3.1 as a regulator of oxidative phosphorylation in MiaPaCa-2 cells as silencing and inhibition of KCa3.1 determined the effect of channel dependent-oxidative phosphorylation in proliferation and ATP generation [START_REF] Kovalenko | Identification of KCa3.1 Channel as a Novel Regulator of Oxidative Phosphorylation in a Subset of Pancreatic Carcinoma Cell Lines[END_REF]. In addition, MiaPaCa-2 cells showed mRNA and protein levels in mitochondria, suggesting that KCa3.1 is involved in proliferation through metabolic processes [START_REF] Kovalenko | Identification of KCa3.1 Channel as a Novel Regulator of Oxidative Phosphorylation in a Subset of Pancreatic Carcinoma Cell Lines[END_REF]. Three other studies have identified KCNN4 (gene coding for KCa3.1) as a gene related to PDAC as its transcripts and gene-level were upregulated compared to normal pancreatic tissue (Zaccagnino et al., 2016;[START_REF] Jiang | Integrated expression profiling of potassium channels identifys KCNN4 as a prognostic biomarker of pancreatic cancer[END_REF][START_REF] Shen | Identification of molecular biomarkers for pancreatic cancer with mRMR shortest path method[END_REF]. The upregulation of KCNN4 was associated with the gene expression of different EMT transcription factors (Zaccagnino et al., 2016).

Two-Pore K + Channels (K 2 P)
The outward conducting, pH and membrane potential activated K 2 P channels have an impact on physiological processes. They can regulate the cell volume, the membrane potential in form of being pH sensitive, modulate ion transport and Ca 2+ homeostasis. They are involved in cancer progression due to their impact on cell growth survival and migration, as it has been shown in different types of cancer [START_REF] Mu | Genomic amplification and oncogenic properties of the KCNK9 potassium channel gene[END_REF][START_REF] Kim | Altered expression of KCNK9 in colorectal cancers[END_REF][START_REF] Voloshyna | TREK-1 is a novel molecular target in prostate cancer[END_REF][START_REF] Alvarez-Baron | The two-pore domain potassium channel KCNK5: induction by estrogen receptor alpha and role in proliferation of breast cancer cells[END_REF]Lee G. W. et al., 2012;[START_REF] Nagy | Silencing the KCNK9 potassium channel (TASK-3) gene disturbs mitochondrial function, causes mitochondrial depolarization, and induces apoptosis of human melanoma cells[END_REF][START_REF] Sauter | pH-sensitive K(+) channel TREK-1 is a novel target in pancreatic cancer[END_REF]. A broad data base analysis of K 2 P expression in different cancers revealed an aberrant expression of different K 2 P in PDAC [START_REF] Williams | Altered expression of two-pore domain potassium (K2P) channels in cancer[END_REF]. mRNA expression of KCNK1 (gene coding for TWIK-1) was upregulated in PDAC compared to normal tissue, and KCNK3 (gene coding for TASK-1) were downregulated [START_REF] Williams | Altered expression of two-pore domain potassium (K2P) channels in cancer[END_REF]. One study has found the functional mRNA and protein expression of KCNK5 (gene coding for TASK-2) in PDAC cell lines HPAF, but the role in cancer progression was not further studied [START_REF] Fong | Characterization of vectorial chloride transport pathways in the human pancreatic duct adenocarcinoma cell line HPAF[END_REF]. In another study a pH sensitive K + current was identified in BxPC-3 cells and was probably mediated by TREK-1 [START_REF] Sauter | pH-sensitive K(+) channel TREK-1 is a novel target in pancreatic cancer[END_REF]. TREK-1 protein expression was shown in PDAC cell lines where it was shown that TREK-1 was involved in proliferation [START_REF] Sauter | pH-sensitive K(+) channel TREK-1 is a novel target in pancreatic cancer[END_REF]. A similar pattern was shown in a scratch wound healing assay were activation of TREK-1 lead to decreased migration. These results indicate that TREK-1 has a potential inhibiting role in PDAC proliferation and migration [START_REF] Sauter | pH-sensitive K(+) channel TREK-1 is a novel target in pancreatic cancer[END_REF]. Very few studies have been done on the role of K 2 P channels in PDAC. However, it can be suggested from other types of cancer that these channels can be related to cancer progression [START_REF] Comes | Involvement of potassium channels in the progression of cancer to a more malignant phenotype[END_REF].

Calcium Channels in PDAC

ORAI and STIM

It is well known that physiological Ca 2+ signaling has many effects in the exocrine pancreas, and takes part in stimulating secretion of HCO 3

-and other ions (Hegyi and Petersen, 2013;[START_REF] Maleth | Calcium signaling in pancreatic ductal epithelial cells: an old friend and a nasty enemy[END_REF]. In non-excitable cells, such as cancer cells, Ca 2+ entry occurs mainly through SOCs [START_REF] Mo | The store-operated calcium channels in cancer metastasis: from cell migration, invasion to metastatic colonization[END_REF] but also through transient receptor potential channels (TRP), which are selective for both Ca 2+ and Na + [START_REF] Worley | TRPC channels as STIM1-regulated store-operated channels[END_REF].

There is increasing evidence of dysregulated Ca 2+ signaling in cancer. This evidence is based on the implication of SOCs and TRP in key hallmarks of cancer progression and as prognostic markers in several types of cancers (Prevarskaya et al., 2007;Shapovalov et al., 2016;Chen et al., 2019). Some members of SOCs and TRP have been studied in PDAC, even though knowledge is less pronounced compared to other types of cancer, such as breast-, cervical-, and colorectal cancer (Chen et al., 2019).

The complex of ORAI1 and STIM1 has been shown to play a role in carcinogenesis and to be involved in regulation of proliferation, migration, invasion and apoptosis in different types of cancer (Chen et al., 2019). Only two studies have been performed on PDAC showing that ORAI1 and STIM1 mediate SOC entry and that they are involved in proliferation, survival and apoptosis (Kondratska et al., 2014;Khan et al., 2020). It has been shown that both ORAI1 and STIM1 were expressed in several PDAC cell lines at mRNA and protein levels, with PANC-1 showing the highest levels of both. Knockdown of ORAI1 and STIM1 with siRNA showed a significant reduction of Ca 2+ entry. This was confirmed in PANC-1, AsPC-1, MiaPaCa-2, and Capan-1 cells, indicating that SOC entry is mediated by ORAI1 and STIM1 in different PDAC cell lines. A recent study has revealed the involvement of Calcium Release-Activated calcium (CRAC) channel (ORAI1) in proliferation of PDAC (Khan et al., 2020). An inhibition with CRAC channel inhibitor, RP4010, showed a significant reduction of cell proliferation and colony formation in MiaPaCa-2 cells and in L3.6pl (a pancreatic adenosquamous carcinoma derivated cell line). The influx of calcium was also inhibited upon treatment with RP4010, suggesting that cell proliferation is mediated by regulation of Ca 2+ entry through CRAC channel (Khan et al., 2020). It was proposed that cell proliferation was calcium-regulated through the AKT/mTOR signaling pathway as RP4010 inhibition decreased the mRNA levels and protein expression of phosphorylated AKT, modulated the expression of proteins important for downstream AKT/mTOR signaling. Furthermore, RP4010 or ORAI1 knockdown showed a decrease in mRNA levels and in nuclear translocation of NFAT1, suggesting that CRAC channel takes part in modulating calcium signaling associated with NFAT translocation and that PDAC proliferation is regulated through the calcium-activated AKT/ mTOR/NFAT signaling (Khan et al., 2020). To test if RP4010 could enhance anticancer activity of standard used treatments gemcitabine and Nab-Paclitaxel, a combination of the three drugs were used to treat PDAC cell lines. The results showed a decrease in proliferation. A synergistic effect of certain dose combinations of RP4010 with gemcitabine/Nab-Paclitaxel was found to inhibit cell growth. In addition, this synergistic treatment downregulated the expression of NFATC1 and mTOR mRNA and NFAT1, NF-kB, and phosphorylated S6K proteins, suggesting that inhibition of cell proliferation through CRAC channel are mediated by a downregulation of mTOR, NFAT and NF-kB signaling (Khan et al., 2020). The anticancer activity and the synergistic effect of RP4010/Gemcitabine/Nab-Paclitaxel were tested in-vivo. In a patient-derived xenograft mouse model, it was shown that Ki-67 expression decreased with the treatment of RP4010 or by the triple combination treatment (Khan et al., 2020). The overexpression found by Kondratska and co-workers can explain increased [Ca 2+ ] i levels in PDAC cell lines, and that this is a mechanism for survival (Kondratska et al., 2014). In contrast, another study has found decreased gene expression levels of ORAI1 (Zaccagnino et al., 2016).

A recent study has been investigating the role of STIM1 in PDAC progression [START_REF] Wang | STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression[END_REF]. shRNA knockdown of STIM1 showed decreased proliferation, invasion, and upregulation of E-cadherin protein levels and downregulation of vimentin levels, suggesting that STIM1 is involved in carcinogenesis of PDAC and in some way involved in Epithelial-Mesenchymal transition (EMT). Even though, Ecadherin levels have shown to be upregulated, in contrary to what is usually seen in cells undergoing EMT where E-cadherin decrease in favor of N-cadherin [START_REF] Gheldof | Cadherins and epithelial-to-mesenchymal transition[END_REF]. Furthermore, tissue microarray analysis showed that the STIM1 expression positively correlated with HIF-1a [START_REF] Wang | STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression[END_REF]. It was further shown that similar protein expression levels of STIM1 and HIF-1a were expressed in different PDAC cell lines. STIM1 and HIF-1a protein levels were also upregulated in some PDAC tumor samples compared to non-tumor samples. Knockdown of HIF-1a in PANC-1 cells revealed a significantly lower mRNA and protein expression of STIM1. The co-upregulation of both proteins and the downregulation of STIM1 upon knockdown of HIF-1a indicate that STIM1 is regulated by HIF-1a on the transcriptional level. STIM1 promoter activity was tested in PANC-1 cells upon normoxia or hypoxia, where HIF-1a binding sites, under hypoxic conditions reduced STIM1 promoter activity [START_REF] Wang | STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression[END_REF]. These results indicate that HIF-1a probably regulates STIM1 transcription and that STIM1 overexpression, in a hypoxic environment, can promote PDAC progression and invasion [START_REF] Wang | STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression[END_REF].

The EMT process is stimulated upon loss of cell-cell contact and occurs in migrating cancer cells [START_REF] Gheldof | Cadherins and epithelial-to-mesenchymal transition[END_REF]. It has been shown in disconnected individual PANC-1 cells that ER/Plasma membrane junctions containing STIM1, together with the IP 3 Rs, redistribute to the leading edge of focal adhesions (Okeke et al., 2016). An inhibition of IP 3 Rs and SOC entry reduced the migrating capacity of PANC-1 cells. This mechanism indicates the importance of Ca 2+ signaling in migration through SOC entry and intracellular calcium channels (Okeke et al., 2016).

TRP Channels

TRP form an adaptable family of ion channel proteins where the majority are calcium permeable and show regulatory patterns that are sensitive to different environmental factors (Shapovalov et al., 2016). The role of TRP has been reported in different types of cancer (Prevarskaya et al., 2007). It has been proposed that TRPC1 can regulate PDAC cell proliferation through TGF-b signaling, as TGF-b has been shown to be one of the key modulators of EMT in mammary epithelial cells [START_REF] Radisky | Epithelial-mesenchymal transition and the stem cell phenotype[END_REF]. In PDAC cell line BxPC-3, TGF-b has shown to induce [Ca 2+ ] i increase leading to activation of the Ca 2+dependent protein kinase Ca (PKC-a) and its translocation to the plasma membrane. PKC-a activation by TGF-b initiates the motility and migration by inhibiting tumor suppressor PTEN (Chow et al., 2008). Further on, it has been shown that there is a high expression of TRPC1, TRPC4 and TRPC6 in BxPC-3 cells (Dong et al., 2010). Here, it was confirmed that TGF-b induces cytosolic Ca 2+ concentrations through TRPC1, followed by a PKC-a activation, thus initiating motility and migration. This was shown by a pharmacological inhibition of SOC entry pathways with 2-APB and La 3+ , which abolishes the TGF-b induced cytosolic Ca 2+ increase. Furthermore, blocking of PKCa with selective PKC-a inhibitors inhibited the TGF-b mediated Ca 2+ entry. In addition, knockdown of TRPC1 with siRNA reversed the effect of TGF-b on cell motility, although, knockdown of TRPC4 and TRPC6 did not have an effect on motility of TGF-b mediated BxPC-3 cell motility (Dong et al., 2010). These observations suggest that dysregulated Ca 2+ entry through TRPC1 could be involved in EMT, and thereby invasion and metastasis of PDAC.

TRPV channels function as sensors in the central and peripheral nervous system where the majority is sensitive to voltage and temperature [START_REF] Premkumar | TRP channels and analgesia[END_REF]. TRPV1 has shown to be related to oncogenesis and is expressed in different types of cancer [START_REF] Domotor | Immunohistochemical distribution of vanilloid receptor, calcitoningene related peptide and substance P in gastrointestinal mucosa of patients with different gastrointestinal disorders[END_REF][START_REF] Lazzeri | Transient receptor potential vanilloid type 1 (TRPV1) expression changes from normal urothelium to transitional cell carcinoma of human bladder[END_REF][START_REF] Sanchez | Expression of the transient receptor potential vanilloid 1 (TRPV1) in LNCaP and PC-3 prostate cancer cells and in human prostate tissue[END_REF][START_REF] Miao | High expression of vanilloid receptor-1 is associated with better prognosis of patients with hepatocellular carcinoma[END_REF][START_REF] Morelli | Cross-talk between alpha1D-adrenoceptors and transient receptor potential vanilloid type 1 triggers prostate cancer cell proliferation[END_REF][START_REF] Vercelli | Transient receptor potential vanilloid 1 expression and functionality in mcf-7 cells: a preliminary investigation[END_REF]. TRPV1 can be activated by multiple pathways, which can promote pancreatic inflammation and pain, but also pancreatic cancer (Hartel et al., 2006;Huang et al., 2020). TRPV1 was shown to be upregulated at the mRNA and protein level in PDAC tissue compared to normal pancreatic tissue (Hartel et al., 2006). TRPV1 staining has been shown in both normal acini and ducts but with highest intensity in nerves of inflamed tissue surrounding the cancer. The elevated TRPV1 expression in infiltrating nerves was associated with pain in patients with PDAC. The same authors showed that inhibition of TRPV1 with resiniferatoxin induces apoptosis by targeting mitochondrial respiration and decreases cell growth in some PDAC cell lines (Hartel et al., 2006).

Recently, it has been shown that TRPV1 regulates the Epidermal Growth Factor Receptor (EGFR) in PANC-1 cell line (Huang et al., 2020). In this study, an overexpression of TRPV1 has been associated with a decrease in protein expression of EGFR in PANC-1. Vice versa, the downregulation and inhibition of TRPV1 increases the protein expression of EGFR. In addition, an overexpression of TRPV1 showed increased levels of ubiquitinated EGFR. The membranous fractions of EGFR were reduced, while the cytoplasmic were increased compared to the control (Huang et al., 2020). This indicates that TRPV1 promotes EGFR ubiquitination and thereby a downregulation of EGFR activity, resulting in EGFR cytoplasmic translocation and degradation, which was found to be mainly through the lysosomal pathway (Huang et al., 2020). Furthermore, it was shown that TRPV1 overexpression inhibited proliferation, probably through the MAPK signaling pathway. Overexpression of TRPV1 resulted in decreased mRNA levels of KRAS and AKT2 and a treatment with EGF reduced the protein expression of ERK, JNK, and CREB, suggesting that a TRPV1 overexpression decreases EGFR/MAPK dependent proliferation in PANC-1 cells (Huang et al., 2020). The two above mentioned studies show contrary results in form of how the expression of TRPV1 is related to proliferation. Hartel et al., demonstrated that inhibition of TRPV1 terminate cell growth and induced apoptosis, where Huang et al., found that an overexpression of TRPV1 leads to a reduced proliferation rate (Hartel et al., 2006;Huang et al., 2020).

Another member of the TRPV family, TRPV6, was also found to be overexpressed in the primary pancreatic cancer tissues at both protein and mRNA levels. Moreover, by immunohistochemical analysis, it was found that TRPV6 is mainly localized in the cytoplasm in both tumor and normal tissue (Song et al., 2018). In-vitro, the highest level of TRPV6 was found in two pancreatic cell lines, Capan-2 and SW1990. The knockdown of TRPV6, by siRNA, resulted in reduced proliferation, cell cycle arrest in G0/G1 phase, promotion of apoptosis, and suppression of cell migration and invasion (Song et al., 2018). Furthermore, the silencing of TRPV6 resulted in a significant increase of sensitivity to the chemotherapeutic reagent oxaliplatin (Song et al., 2018). In contrast to this finding, Zaccagnino et al., 2016 showed a downregulation of TRPV6 in PDAC tissue, compared to normal pancreatic epithelium. Moreover, Tawfik et al., 2020 found also a downregulation of TRPV6 expression in a PDAC cell line A818-6 grown in a highly malignant undifferentiated monolayer. The authors suggest that a lower expression of TRPV6 could contribute to an inhibited epithelial fluid secretion in PDAC (Tawfik et al., 2020).

The TRPM family is also constituted with several members, which have been found to be implicated in carcinogenesis. One of the most studied in PDAC is TRPM7, which is a particular channel having an intrinsic kinase, together with its closest homolog TRPM6 (Yee et al., 2012a). TRMP7 is ubiquitously expressed and controls cellular homeostasis of ions, especially Mg 2+ and Ca 2+ . Interpreting that the developmental role of TRPM7 in zebrafish could be the same in humans, the role of TRPM7 has been studied in the development and progression of PDAC. Here, it has been shown that there was an overexpression of TRPM7 protein in PDAC tissue compared to normal tissue, and that TRPM7 is required for Mg 2+ -regulated proliferation. Knockdown of TRPM7 with siRNA showed that this channel is necessary to prevent cell cycle arrest in G0/G1 phases. Furthermore, the proliferation of TRPM7-deficient PDAC cells was rescued by adding Mg 2+ to the cell culture medium [START_REF] Yee | Transient receptor potential ion channel Trpm7 regulates exocrine pancreatic epithelial proliferation by Mg2+sensitive Socs3a signaling in development and cancer[END_REF]. Another study confirmed the overexpression of TRPM7 both at mRNA and protein levels in PDAC tissue (Rybarczyk et al., 2012). Furthermore, it was shown that TRPM7 silenced BxPC-3 cells decreased [Mg 2+ ] i , suggesting that TRPM7 takes part in regulating Mg 2+ uptake in PDAC cells. In contrary to previous findings, these authors demonstrated that the silencing of TRPM7 had no effect on cell viability or proliferation, but a significant decrease of BxPC-3 cell migration (Rybarczyk et al., 2012). TRPM7 has also been found to be involved in cell invasion in both MiaPaCa2-and PANC-1 cells. In the two last cell lines, TRPM7 regulates constitutive cation currents, the influx and homeostasis of Mg 2+ , and cell invasion through the Hsp90a/uPA/ MMP-2 proteolytic pathway (Rybarczyk et al., 2017).

Besides TRPM7, also other TRPM channels are found to be expressed in pancreatic cancer (Yee et al., 2010;Yee et al., 2014). TRPM8 is expressed in different types of adult human tissue and has also been found to be expressed in PDAC. In a panel of PDAC cell lines, mRNA TRPM8 was consistently overexpressed compared to the control cell line (H6c7) (Yee et al., 2010). This pattern has further been confirmed by immunohistochemistry in human PDAC tumors, compared to normal pancreatic tissue (Yee et al., 2010;Yee et al., 2014). Here, it was found that TRPM8 has a role in carcinogenesis in form of proliferation, migration and senescence. TRPM8 is required for proliferation by promoting cell cycle progression in PANC-1 and BxPC-3 cells, as a knockdown of TRPM8 showed a significant decrease in proliferation rate and a cell cycle arrest in G0/G1 phase (Yee et al., 2010). In another study, the knockdown of TRPM8 showed the opposite effect on proliferation. Here, the proliferation increased by 30% in PANC-1 cells and in contrary the proliferation was suppressed in HEK/M8 cells. It was found that TRPM8 is expressed in a non-glycosylated form in different PDAC cell lines, and that the channel in this form might have a protective role in PDAC (Ulareanu et al., 2017). Concerning the involvement of TRPM8 in migration and invasion, two studies show opposite results. One study demonstrated that TRPM8 also is required for cell migration, as a knockdown of the channel impaired migration of BxPC-3 and MiaPaCa-2 by 60% and 45%, respectively (Yee et al., 2014). Where another study found that it enhanced the motility of PANC-1 cells (Cucu et al., 2014).

Recently, it has been shown that a third member of the TRPM family, also plays a role in PDAC progression [START_REF] Lin | TRPM2 promotes the proliferation and invasion of pancreatic ductal adenocarcinoma[END_REF]. An overexpression of TRPM2 enhanced the proliferative, migrative and invasive abilities of PANC-1 cells, compared to the control cells and the results were inversed when TRPM2 was silenced in PANC-1 cells. It should be noted, that the study does not mention the application of a proliferation inhibitor during the Scratch wound-healing assay, which investigates the migratory role of TRPM2. Therefore, one can speculate if the wound-healing could be caused by proliferation, and not migration. Nevertheless, these results suggest that TRPM2 is involved at least in cell growth and invasion [START_REF] Lin | TRPM2 promotes the proliferation and invasion of pancreatic ductal adenocarcinoma[END_REF].

Voltage-Dependent Calcium Channels

The expression of two voltage dependent Ca 2+ channels have been found to be dysregulated in PDAC, namely, CaV2.1 (CACNA1A) and CaV3.1 (CACNA1G) are upregulated and downregulated, respectively (Zaccagnino et al., 2016). These sparse data indicate that voltage-dependent Ca 2+ channels might have a role in PDAC progression.

Chloride Channels in PDAC

Ca 2+ -Activated Chloride Channel (CaCC) and TMEM Proteins Aberrant expression and dysregulated function of Cl -channels have shown to be involved in carcinogenesis, especially their role in cell volume regulation has shown to be important for cancer cell migration and infiltration [START_REF] Duran | Chloride channels: often enigmatic, rarely predictable[END_REF][START_REF] Prevarskaya | Ion channels and the hallmarks of cancer[END_REF][START_REF] Anderson | Role of ion channels in gastrointestinal cancer[END_REF]. In Capan-1 cells, CaCC are expressed at the apical membrane, as shown for normal pancreatic acinar and ductal cells (Park et al., 2001;Wang et al., 2013;Wang and Novak, 2013).

The functional role of TMEM16A has been found to vary between different types of cancer [START_REF] Ayoub | ANO1 amplification and expression in HNSCC with a high propensity for future distant metastasis and its functions in HNSCC cell lines[END_REF][START_REF] Liu | Inhibition of Ca(2+)activated Cl(-) channel ANO1/TMEM16A expression suppresses tumor growth and invasiveness in human prostate carcinoma[END_REF][START_REF] Ruiz | Enhanced expression of ANO1 in head and neck squamous cell carcinoma causes cell migration and correlates with poor prognosis[END_REF][START_REF] Britschgi | Calcium-activated chloride channel ANO1 promotes breast cancer progression by activating EGFR and CAMK signaling[END_REF]. While a proproliferative role was found in breast and prostate cancer, the role in pancreatic cancer has been found to be contradictory. An anti-proliferative effect was found by a knockdown and overexpression strategy in CFPAC-1 cells [START_REF] Ruiz | Enhanced expression of ANO1 in head and neck squamous cell carcinoma causes cell migration and correlates with poor prognosis[END_REF], where another study found that inhibition with the TMEM16A specific inhibitor T16A inh -A01 decreased the proliferation rate in CFPAC-1 cells [START_REF] Mazzone | Inhibition of cell proliferation by a selective inhibitor of the Ca(2+)activated Cl(-) channel, Ano1[END_REF]. Both studies lack the comparison of PDAC cell lines with a normal pancreatic epithelial control cell line. This was considered in a recent study, where the role of TMEM16A was investigated in PDAC cell lines and compared to a normal pancreatic epithelial control cell line [START_REF] Sauter | ANO1 (TMEM16A) in pancreatic ductal adenocarcinoma (PDAC)[END_REF]. The mRNA expression of TMEM16A was upregulated, with a 1,450-fold, in AsPC-1, BxPC-3, and especially in Capan-1 cells [START_REF] Sauter | ANO1 (TMEM16A) in pancreatic ductal adenocarcinoma (PDAC)[END_REF]. The upregulation was confirmed by an increase in TMEM16A protein expression for all three cell lines. Furthermore, it was shown that TMEM16A carries the major component of CaCC current in these cell lines [START_REF] Sauter | ANO1 (TMEM16A) in pancreatic ductal adenocarcinoma (PDAC)[END_REF]. Moreover, the authors found that knockdown of TMEM16A had no effect on proliferation. Inhibition, by T16A inh -A01 or other CaCC inhibitors, failed to affect PDAC cell lines proliferation, while T16A inh -A01 had a significant effect on the control cell line cell proliferation, which almost completely lack the expression of TMEM16A. These results suggest that the inhibition by T16A inh -A01 is unspecific for TMEM16A, and that this channel has no implication in proliferation, at least in these three PDAC cell lines [START_REF] Sauter | ANO1 (TMEM16A) in pancreatic ductal adenocarcinoma (PDAC)[END_REF]. According to the role of TMEM16A in migration, gene silencing reduced the migratory capability of AsPC-1 and BxPC-3 cells, where the inhibition with T16A inh -A01 was ineffective [START_REF] Sauter | ANO1 (TMEM16A) in pancreatic ductal adenocarcinoma (PDAC)[END_REF]. Other CaCC inhibitors caused a decrease in migration of BxPC-3 cells. Nevertheless, Capan-1 cells showed the highest expression of TMEM16A, the migration was very slow, suggesting that TMEM16A is not implicated in the role of migration in Capan-1 cells and supporting that TMEM16A has different roles in carcinogenesis of PDAC cells [START_REF] Sauter | ANO1 (TMEM16A) in pancreatic ductal adenocarcinoma (PDAC)[END_REF].

Another recent study has performed a database investigation on the expression of TMEM16A and found that mRNA TMEM16A expression is upregulated in pancreatic cancer [START_REF] Crottes | TMEM16A controls EGF-induced calcium signaling implicated in pancreatic cancer prognosis[END_REF]. The authors found that extracellular application of EGF increased [Ca 2+ ] i and the outwardrectifying Cl -current, which were both inhibited by different TMEM16A inhibitors. The regulation of Cl -currents and the Ca 2+ response were probably due to SOC entry. Furthermore, silencing of TMEM16A in AsPC-1 cells reduced migration even under EGF treatments, while EGF induced migration in the control cell line. This indicates that TMEM16A is involved in EGF-induced PDAC migration and progression, probably through Ca 2+ signaling. In addition, this study investigated the possible role of TMEM16A to classify PDAC patients [START_REF] Crottes | TMEM16A controls EGF-induced calcium signaling implicated in pancreatic cancer prognosis[END_REF]. They found 10 genes involved in EGF-induced TMEM16A-dependent Ca 2+ signaling, which could distinguish neuro-endocrine tumors from other pancreatic cancers. In PDAC, these genes formed three clusters with different genetic profiles that could reflect different molecular characterizations [START_REF] Crottes | TMEM16A controls EGF-induced calcium signaling implicated in pancreatic cancer prognosis[END_REF].

Another TMEM16 protein expressed in pancreatic cancer is the TMEM16J protein, which also has been found to be overexpressed [START_REF] Jun | ANO9/ TMEM16J promotes tumourigenesis via EGFR and is a novel therapeutic target for pancreatic cancer[END_REF]. TMEM16J is not a well characterized protein, but it is proposed that it might function as a cation channel activated by the cAMP/PKA signaling pathway [START_REF] Falzone | Known structures and unknown mechanisms of TMEM16 scramblases and channels[END_REF][START_REF] Kim | Anoctamin 9/ TMEM16J is a cation channel activated by cAMP/PKA signal[END_REF]. An upregulation of TMEM16J gene-, mRNA-, and protein overexpression were found in AsPC-1, BxPC-3, and Capan-2 cell lines and a small overexpression in PANC-1 cells. An overexpression of TMEM16J in PANC-1 cells resulted in phosphorylated ERK1/2 levels, but not total ERK1/2 levels. Furthermore, both EGFR and phosphorylated EGFR levels were upregulated in PANC-1 cells overexpressing TMEM16J and an immunoprecipitation assay revealed that both TMEM16A and TMEM16J formed protein complexes with EGFR, but the binding affinity for TMEM16J was 132% higher, than for the one of TMEM16A [START_REF] Jun | ANO9/ TMEM16J promotes tumourigenesis via EGFR and is a novel therapeutic target for pancreatic cancer[END_REF], suggesting that TMEM16J are involved in upregulation and activation of EGFR. In contrary, a knockdown of TMEM16J in AsPC-1 cells resulted in inhibition of phosphorylated ERK1/2, EGFR and phosphorylated EGFR and a decreased proliferation rate. These results were confirmed in-vivo, were a xenograft mouse model was made by implanting PANC-1 cells stably overexpressing TMEM16J. It was shown that tumor growth was significantly increased and immunohistochemistry of these tumors confirmed the TMEM16J overexpression [START_REF] Jun | ANO9/ TMEM16J promotes tumourigenesis via EGFR and is a novel therapeutic target for pancreatic cancer[END_REF]. These results indicate that TMEM16J is implicated in cell proliferation and tumor growth. Another member of the TMEM16 family, TMEM16E, has been shown to be implicated in PDAC. It is not yet clear whether the TMEM16E protein function as an ion channel or scramblase [START_REF] Falzone | Known structures and unknown mechanisms of TMEM16 scramblases and channels[END_REF]. It has been shown, by immunohistochemical analysis, that TMEM16E is entirely expressed in PDAC but not in normal pancreatic tissue [START_REF] Song | Anoctamin 5 regulates cell proliferation and migration in pancreatic cancer[END_REF]. The highest expression of both mRNA and protein of TMEM16E was found in PANC-1 cells. The impact of TMEM16E on migration was investigated by a wound-scratch assay and a siRNA knockdown of TMEM16E showed a significant decrease in PANC-1 cell migration [START_REF] Song | Anoctamin 5 regulates cell proliferation and migration in pancreatic cancer[END_REF]. Even though, it should be mentioned that the authors do not account for the possible effect of proliferation in this assay. The migration was in some ways confirmed by the downregulation of vimentin protein expression, compared to the control, which showed a higher expression of vimentin, suggesting that TMEM16E is implicated in migration of PANC-1 cells. In addition, the proliferation of PANC-1 cells was significantly decreased upon knockdown of TMEM16E suggesting its role in proliferation [START_REF] Song | Anoctamin 5 regulates cell proliferation and migration in pancreatic cancer[END_REF]. This assay supports the speculation on the TMEM16E role in migration.

Besides being activated by Ca 2+ , CaCC can also be activated and regulated by specific proteins, namely Calcium-activated Chloride channel regulators (CLCAs) also called Calcium Chloride channel accessory proteins. CLCAs are expressed in different types of cancer and have been implicated in regulation of proliferation, migration and metastasis [START_REF] Yurtsever | Self-cleavage of human CLCA1 protein by a novel internal metalloprotease domain controls calcium-activated chloride channel activation[END_REF][START_REF] Lang | Ion channels in cancer: future perspectives and clinical potential[END_REF]Stock and Schwab, 2015). CLCA1 has been shown to be overexpressed in pancreatic cancer (Hu et al., 2018a;[START_REF] Hu | Calcium-activated chloride channel regulator 1 as a prognostic biomarker in pancreatic ductal adenocarcinoma[END_REF]. However, the expression pattern and underlying molecular mechanism of its role in PDAC is less known. Finally, low gene expression of Chloride Channel Kb (CLCNKB) and Chloride Voltage-Gated Channel 1 (CLCN1) have been reported in human PDAC tissue compared to normal pancreatic epithelium (Zaccagnino et al., 2016).

CFTR

It has been shown that CFTR is expressed in some PDAC cell lines. An early study showed that CFTR only was expressed in Capan-1 cells among nine different pancreatic cell lines and that the expression varied as a function of confluence [START_REF] Chambers | Expression of the cystic fibrosis gene and the major pancreatic mucin gene, MUC1, in human ductal epithelial cells[END_REF]. Singh et al., confirmed the almost non-existent expression of CFTR in PDAC cell lines. Indeed, mRNA levels were detectable in normal pancreatic tissue and three (Capan-1, Suit2 and SW1990) out of 16 pancreatic cell lines [START_REF] Singh | MUC4 expression is regulated by cystic fibrosis transmembrane conductance regulator in pancreatic adenocarcinoma cells via transcriptional and post-translational mechanisms[END_REF]. Furthermore, Zaccagnino et al., reported the downregulation of CFTR, at gene-level, in human PDAC tissue compared to normal pancreatic epithelium. This downregulation was associated with gene expression of EMT transcription factors (Zaccagnino et al., 2016). Furthermore, Singh et al., showed that wild type CFTR negatively regulated MUC4 expression while silencing of CFTR upregulated MUC4 expression. As MUC4 is a protein involved in tumor migration and metastasis, the negative regulation by CFTR indicates a protective role and a tumor suppressing function by inhibiting MUC4 and hence pancreatic cancer progression [START_REF] Singh | MUC4 expression is regulated by cystic fibrosis transmembrane conductance regulator in pancreatic adenocarcinoma cells via transcriptional and post-translational mechanisms[END_REF].

A recent study has investigated CFTR expression in patient derivated PDAC organoids, in order to enable routine organoid subtyping for personalized treatment [START_REF] Hennig | CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids[END_REF]. It has been suggested that subtyping could be based on the expression of cytokeratin 81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A). As the antibody for HNF1A was no longer available, the authors permitted CFTR to replace it as a potential marker instead of HNF1A [START_REF] Hennig | CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids[END_REF]. Organoids can be categorized into the established quasi-mesenchymal, exocrinelike, and classical subtypes. Immunofluorescence staining showed a mutual expression pattern where exocrine-like organoids were CFTR + /KRT81 -and quasi-mesenchymal CFTR -/KRT81 + . The protein expression revealed by IF was compared to mRNA levels of CFTR, which matched in 8 out of 10 cases [START_REF] Hennig | CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids[END_REF]. In addition, it was confirmed, by immunohistochemical analysis, that both CFTR and KRT81 were preserved in 6 out of 7 tumors, indicating that the organoids had the same subtype as their primary tumor [START_REF] Hennig | CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids[END_REF]. These results suggest that CFTR could be a supplement marker for HFN1A and that CFTR/KRT81 together might be a suitable way to evaluate subtype organoids for personal treatments [START_REF] Hennig | CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids[END_REF].

Cl -Intracellular Channel Proteins (CLICs)

CLICs are ubiquitously expressed and have been identified in several types of cancer, where they are either overexpressed or downregulated compared to the normal tissue [START_REF] Peretti | Chloride channels in cancer: Focus on chloride intracellular channel 1 and 4 (CLIC1 AND CLIC4) proteins in tumor development and as novel therapeutic targets[END_REF]. In PDAC, CLICs are mostly found upregulated, even though their specific role in PDAC progression and development is not yet understood. CLIC2, CLIC3, and CLIC5 have been shown to be expressed at mRNA and protein levels in a HPAF cell line. By an electrophysiological study, the authors revealed that there was no single channel/conductance for apical Cl - secretion, but that these CLICs rather contributed to provide a constant net conductance across the plasma membrane [START_REF] Fong | Characterization of vectorial chloride transport pathways in the human pancreatic duct adenocarcinoma cell line HPAF[END_REF]. Another study has shown the importance of CLIC3 in PDAC, as immunohistochemical analysis and mRNA levels showed an overexpression of CLIC3 in PDAC tissue compared to normal pancreatic tissue [START_REF] Dozynkiewicz | Rab25 and CLIC3 collaborate to promote integrin recycling from late endosomes/lysosomes and drive cancer progression[END_REF]. It was also found that CLIC3 in collaboration with Rab25 promoted cancer cell invasion and migration by integrin recycling from late endosomes/lysosomes [START_REF] Dozynkiewicz | Rab25 and CLIC3 collaborate to promote integrin recycling from late endosomes/lysosomes and drive cancer progression[END_REF]. CLIC1 was overexpressed in primary tumors compared to normal pancreatic tissue, and strongly expressed in MiaPaCa-2 and PANC-1 cells [START_REF] Lu | Chloride intracellular channel 1 (CLIC1) is activated and functions as an oncogene in pancreatic cancer[END_REF]. Silencing of CLIC1 showed a significant decrease in the proliferation rate, colony formation and the invasive abilities of both MiaPaCa-2 and PANC-1 cells, suggesting that CLIC1 contributes to the aggressive role of these PDAC cells [START_REF] Lu | Chloride intracellular channel 1 (CLIC1) is activated and functions as an oncogene in pancreatic cancer[END_REF]. In addition, gene expression levels of CLIC5 has been found to be downregulated in PDAC tissue, compared to normal pancreatic epithelium and to be associated with gene expression of transcription factors related to cell differentiation (Zaccagnino et al., 2016).

Aquaporins (AQPs) in PDAC

AQPs are expressed in various types of cancers and are predicted to be key regulators in tumor development and progression [START_REF] Papadopoulos | Key roles of aquaporins in tumor biology[END_REF]. The expression and role of AQPs in PDAC is poorly studied, yet few studies have described their involvement in PDAC progression [START_REF] Burghardt | Distribution of aquaporin water channels AQP1 and AQP5 in the ductal system of the human pancreas[END_REF][START_REF] Direito | Differential expression of aquaporin-3 and aquaporin-5 in pancreatic ductal adenocarcinoma[END_REF]Huang et al., 2017;[START_REF] Zou | AQP1 and AQP3 Expression are Associated With Severe Symptoms and Poor-prognosis of the Pancreatic Ductal Adenocarcinoma[END_REF]. Burghardt and co-workers have found mRNA expression of AQP1, AQP3, AQP4, AQP5, and AQP8 in PDAC. All subtypes were expressed in solid tumors, where only AQP3, AQP4, and AQP5 were expressed in PDAC cell lines [START_REF] Burghardt | Distribution of aquaporin water channels AQP1 and AQP5 in the ductal system of the human pancreas[END_REF]. Further studies have found an upregulation of AQP1 and AQP3 in PDAC tissue compared to normal pancreatic tissue [START_REF] Zou | AQP1 and AQP3 Expression are Associated With Severe Symptoms and Poor-prognosis of the Pancreatic Ductal Adenocarcinoma[END_REF]. The expression of AQP1 correlated with the expression of AQP3, suggesting that these two channels cooperate during PDAC development. Another study has shown the overexpression of AQP3 and AQP5 in PDAC tissue [START_REF] Direito | Differential expression of aquaporin-3 and aquaporin-5 in pancreatic ductal adenocarcinoma[END_REF]. AQP5 localization in PDAC was found to be in the entire plasma membrane and in the cytoplasm of ducts cells, where in normal pancreas the localization is in the apical membrane. Furthermore, AQP5 and AQP3 were suggested to be involved in proliferation and tumor transformation as a simultaneous overexpression was found to be correlated with an increased expression of EGFR, Ki-67, CK7, and a decrease of E-cadherin and increase of Vimentin [START_REF] Direito | Differential expression of aquaporin-3 and aquaporin-5 in pancreatic ductal adenocarcinoma[END_REF]. Another study investigating AQP has, through TCGA analysis, revealed that AQP3 shows the highest expression among AQPs in PDAC (Huang et al., 2017). The authors investigated the role of AQP3 further, with a focus on how microRNA (miR-874) regulates gene expression and post-translational events in PDAC. In a panel of eight pancreatic cell lines, they detected that cell lines with high AQP3 mRNA levels had lower miR-874 levels, where cell lines with high miR-874 had lower AQP3 levels suggesting that AQP3 expression is regulated by miR-874 (Huang et al., 2017). It was found that both modulation of AQP3 and miR-874 altered the expression and activity of mTOR and its downstream target S6, suggesting that an overexpression of AQP3 is associated with proliferation and cell survival by mTOR signaling in PDAC. In contrast to other studies, Zaccagnino et al. (2016) showed a downregulation of AQP3 and AQP8 expression in PDAC tissue compared to normal pancreatic one. Furthermore, they showed that AQP3 expression was associated with several cell differentiation related transcription factors.

Sodium Channels in PDAC

ASIC

It has recently been shown that acid-sensing ion channels (ASICs), an H + -gated subgroup of ENaC, are expressed in PDAC cell lines and tissue (Zhu et al., 2017). ASIC1 and ASIC3 were found functionally expressed and mRNA and protein expression were also found in PDAC cell lines. In all cases, the expression was upregulated compared to the normal control cell line. These results were confirmed in PDAC tissue where immunohistochemical analysis and qPCR revealed the overexpression compared to non-cancerous pancreatic tissue, suggesting that ASIC1 and ASIC3 have a pathophysiological role in PDAC (Zhu et al., 2017). Separate inhibition or knockdown of ASIC1 and ASIC3 decreased the acidity-promoted invasion and migration capacity of PDAC cell lines, but did not decrease the proliferation rate, suggesting that ASIC1 and ASIC3 are involved in the metastatic process of PDAC, but not tumor cell growth (Zhu et al., 2017). Furthermore, it was shown that ASIC1 and ASIC3 are involved in acidity-promoted EMT, as silencing or inhibition of ASIC1 or ASIC3 in PDAC cells showed decreased protein expression of mesenchymal markers Vimentin, Ncadherin, Snail, and ZEB1, while the epithelial marker Ecadherin showed increased protein expression. In contrary, PDAC cells overexpressing ASIC1 and ASIC3 showed an increase in mesenchymal markers and a decrease in epithelial markers, under acidic conditions. This was confirmed in human PDAC tissue samples by IF analysis. It was further investigated whether this mechanism was regulated by [Ca 2+ ] i , where it was found that inhibition of ASIC1 or ASIC3 resulted in a decrease of [Ca 2+ ] i upon acidification. In addition, the removal of [Ca 2+ ] i upon acidic conditions decreased mesenchymal markers and increased the epithelial ones. It was determined that the RhoA pathway, which is involved in cytoskeleton re-arrangement and cell migration, was a major effector of EMT induced by ASIC1/3-[Ca 2+ ] i activation in acidic conditions (Zhu et al., 2017). The role of ASIC1 and ASIC3 was further confirmed in-vivo, where a xenograft mouse model injected with BxPC-3 cells with a stable knockdown of ASIC1 and ASIC3 showed a significant decrease in lung and liver metastasis, but no obvious effect on tumor growth (Zhu et al., 2017).

VGSCs

Another subfamily of Na + channels, namely voltage gated sodium channels (VGSCs), has shown to be implicated in cancer progression [START_REF] Angus | Voltage gated sodium channels in cancer and their potential mechanisms of action[END_REF]). An early study has shown that Ca 2+ blockers Phenytoin and Verapamil inhibited the growth of pancreatic cancer cell lines MiaPaCa-2 and CAV, both in-vitro and in-vivo [START_REF] Sato | Inhibitory effect of calcium channel blockers on growth of pancreatic cancer cells[END_REF]. Phenytoin and Verapamil were chosen because they appeared to be blocking different Ca 2+ channels; Ttype and L-type voltage dependent Ca 2+ channels, respectively [START_REF] Sato | Inhibitory effect of calcium channel blockers on growth of pancreatic cancer cells[END_REF]. It has been suggested that this growth-inhibition of pancreatic cancer cell was rather due to the block of VGSC than the block of Ca 2+ channels, as both Phenytoin and Verapamil show high affinity for VGSC in the inactivated state of the channel [START_REF] Ragsdale | Frequency and voltagedependent inhibition of type IIA Na+ channels, expressed in a mammalian cell line, by local anesthetic, antiarrhythmic, and anticonvulsant drugs[END_REF][START_REF] Koltai | Voltage-gated sodium channel as a target for metastatic risk reduction with re-purposed drugs[END_REF]. In addition, the expression of VGSC (SCN9A and SCN3A) was downregulated in PDAC (Zaccagnino et al., 2016).

IONOTROPIC RECEPTORS IN PDAC Purinergic Receptors (P2XR) and N-Methyl-D-Aspartate Receptors (NMDAR)

Different types of ionotropic receptors including P2XR and NMDAR have been reported to be expressed in PDAC [START_REF] Kunzli | Upregulation of CD39/NTPDases and P2 receptors in human pancreatic disease[END_REF][START_REF] Hansen | Purinergic receptors and calcium signalling in human pancreatic duct cell lines[END_REF][START_REF] Burnstock | Purinergic signalling in the pancreas in health and disease[END_REF][START_REF] Li | Hijacking the neuronal NMDAR signaling circuit to promote tumor growth and invasion[END_REF][START_REF] North | NMDA receptors are important regulators of pancreatic cancer and are potential targets for treatment[END_REF]. Among P2XR, P2X7R is the most well described [START_REF] Kunzli | Upregulation of CD39/NTPDases and P2 receptors in human pancreatic disease[END_REF][START_REF] Hansen | Purinergic receptors and calcium signalling in human pancreatic duct cell lines[END_REF][START_REF] Burnstock | Purinergic signalling in the pancreas in health and disease[END_REF].This ionotropic receptor has shown to be overexpressed in PDAC cell lines and tissue [START_REF] Kunzli | Upregulation of CD39/NTPDases and P2 receptors in human pancreatic disease[END_REF][START_REF] Giannuzzo | The P2X7 receptor regulates cell survival, migration and invasion of pancreatic ductal adenocarcinoma cells[END_REF], and to be implicated in the proliferating, apoptotic, migrating, and invading processes of PDAC [START_REF] Kunzli | Upregulation of CD39/NTPDases and P2 receptors in human pancreatic disease[END_REF][START_REF] Hansen | Purinergic receptors and calcium signalling in human pancreatic duct cell lines[END_REF][START_REF] Giannuzzo | The P2X7 receptor regulates cell survival, migration and invasion of pancreatic ductal adenocarcinoma cells[END_REF][START_REF] Giannuzzo | Targeting of the P2X7 receptor in pancreatic cancer and stellate cells[END_REF][START_REF] Choi | Activating P2X7 Receptors Increases Proliferation of Human Pancreatic Cancer Cells via ERK1/2 and JNK[END_REF]. In addition, the expression of NMDAR was found in both PDAC cell lines and PDAC tumors, and their inhibition and blocking resulted in reduced different PDAC cell lines viability and survival [START_REF] Li | Hijacking the neuronal NMDAR signaling circuit to promote tumor growth and invasion[END_REF][START_REF] North | NMDA receptors are important regulators of pancreatic cancer and are potential targets for treatment[END_REF]. Furthermore, an inhibition of NMDAR prevented growth of tumor xenografts [START_REF] Li | Hijacking the neuronal NMDAR signaling circuit to promote tumor growth and invasion[END_REF][START_REF] North | NMDA receptors are important regulators of pancreatic cancer and are potential targets for treatment[END_REF].

ION CHANNELS AS PDAC BIOMARKERS

A growing number of studies have investigated ion channel expression in pancreatic cell lines and human tissues, showing modulation of mRNA and/or protein expression between normal and cancer cells. Among all the studied channels, only CFTR has lower expression in cancer cell lines compared to normal cells [START_REF] Singh | MUC4 expression is regulated by cystic fibrosis transmembrane conductance regulator in pancreatic adenocarcinoma cells via transcriptional and post-translational mechanisms[END_REF], while Kv1.3, Kv7.1, and TASK-1 were downregulated in PDAC tissue compared to healthy tissue (Brevet et al., 2009;[START_REF] Williams | Altered expression of two-pore domain potassium (K2P) channels in cancer[END_REF]Tawfik et al., 2020), suggesting a protective role and tumor suppressive function for these channels. Although most of the ion channels are overexpressed in PDAC, studies on ion channel expression patterns in correlation with clinical parameters are more limited.

Diagnostic Markers

Some attention has been given to the connection between pancreatic cancer risk and CFTR deficiency. Mutations in the CFTR gene cause the hereditary life shortening disease cystic fibrosis (CF). Severe clinical manifestations occur upon CF in secretory epithelial tissues and in pancreas, mutations causing loss of function lead to pancreatic insufficiency [START_REF] Wilschanski | The cystic fibrosis of exocrine pancreas[END_REF][START_REF] Castellani | Cystic fibrosis: a clinical view[END_REF]. Different cohort studies have investigated how different variants of CFTR affect the risk of pancreatic cancer [START_REF] Sheldon | A cohort study of cystic fibrosis and malignancy[END_REF][START_REF] Neglia | The risk of cancer among patients with cystic fibrosis. Cystic Fibrosis and Cancer Study Group[END_REF]. It has been shown that CF patients present an elevated risk to develop pancreatic cancer, even though the overall risk of developing cancer is the same as for the general population [START_REF] Sheldon | A cohort study of cystic fibrosis and malignancy[END_REF][START_REF] Neglia | The risk of cancer among patients with cystic fibrosis. Cystic Fibrosis and Cancer Study Group[END_REF]. Furthermore, studies also indicate that patients who are CFTR mutant carriers develop pancreatic cancer in a younger age, compared to patients carrying a wildtype form of CFTR (McWilliams et al., 2010;[START_REF] Hamoir | Clinical and morphological characteristics of sporadic genetically determined pancreatitis as compared to idiopathic pancreatitis: higher risk of pancreatic cancer in CFTR variants[END_REF], and patients carrying a germline mutation to some degree have an increased risk of developing PDAC (Cazacu et al., 2018). One mechanism of which a CFTR mutation could cause pancreatic cancer is by the defect of CFTR and ion transport leading to dysregulated mucus secretion and obstruction of the pancreatic ducts, which all are events that could result in pancreatitis (McWilliams et al., 2010). Patients with chronic pancreatitis have a 26-fold higher risk for developing pancreatic cancer compared to the general population [START_REF] Lowenfels | Pancreatitis and the risk of pancreatic cancer. International Pancreatitis Study Group[END_REF]Kirkegard et al., 2017), suggesting that CFTR mutation could be considered as a new risk factor for developing PDAC.

In order to discriminate pancreatic premalignant/malignant lesions from benign lesions, an explorative proteomic approach was performed on a cohort of 24 patients using targeting mass spectrometry analysis of different biomarkers [START_REF] Jabbar | Highly Accurate Identification of Cystic Precursor Lesions of Pancreatic Cancer Through Targeted Mass Spectrometry: A Phase IIc Diagnostic Study[END_REF]. This study proposed CLCA1 to be a supportive marker, which together with mucin-5AC (MUC5AC) and prostate stemcell antigen (PSCA) could distinguish cystic precursor lesions from PDAC, suggesting that CLCA1 is a potential biomarker in PDAC diagnosis.

Prognostic Markers of Cancer Progression and Aggressiveness

Different studies have investigated ion channels as potential biomarkers of PDAC development and progression. Using immunohistochemical analysis, high KCa3.1 expression in PDAC tissue was correlated with TNM stages III and IV [START_REF] Jiang | Integrated expression profiling of potassium channels identifys KCNN4 as a prognostic biomarker of pancreatic cancer[END_REF], and high expression of STIM1 was correlated with tumor grade [START_REF] Wang | STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression[END_REF]. Upregulation of Kv11.1 expression was associated with advanced tumor grade and high expression of Ki67 proliferative marker (Lastraioli et al., 2015b), whereas TRPV6, TRPM8 and AQP1/AQP3 channels were positively correlated with tumor stages III and IV and large tumor size (Yee et al., 2014;[START_REF] Du | Elevated Transient Receptor Potential Melastatin 8 (TRPM8) Expression Is Correlated with Poor Prognosis in Pancreatic Cancer[END_REF][START_REF] Liu | Silencing of TRPM8 inhibits aggressive tumor phenotypes and enhances gemcitabine sensitivity in pancreatic cancer[END_REF]Song et al., 2018;[START_REF] Zou | AQP1 and AQP3 Expression are Associated With Severe Symptoms and Poor-prognosis of the Pancreatic Ductal Adenocarcinoma[END_REF]. Finally, TRPM7 and Cl -intracellular channel proteins (CLIC1-3). CLIC1 overexpression was shown to be correlated with the three clinical parameters: advanced tumor grade, advanced tumor stage and large tumor size (Rybarczyk et al., 2012;[START_REF] Lu | Chloride intracellular channel 1 (CLIC1) is activated and functions as an oncogene in pancreatic cancer[END_REF][START_REF] Yee | Aberrant over-expression of TRPM7 ion channels in pancreatic cancer: required for cancer cell invasion and implicated in tumor growth and metastasis[END_REF][START_REF] Jia | CLIC1 overexpression is associated with poor prognosis in pancreatic ductal adenocarcinomas[END_REF]. These results suggest that all the ion channels cited above are associated with pancreatic tumor growth.

Regarding the metastatic status, immunohistochemistry experiments showed that TRPV6 expression was higher in cases where PDAC was infiltrating (Song et al., 2018). The same results were observed at mRNA and protein levels for CLIC3, with a highly detectable expression in regions where the tumor was invading normal pancreatic tissue [START_REF] Dozynkiewicz | Rab25 and CLIC3 collaborate to promote integrin recycling from late endosomes/lysosomes and drive cancer progression[END_REF]. Other studies revealed higher TRPM7 and TRPM8 staining in metastatic tumors than in non-metastatic tumors [START_REF] Yee | Aberrant over-expression of TRPM7 ion channels in pancreatic cancer: required for cancer cell invasion and implicated in tumor growth and metastasis[END_REF][START_REF] Liu | Silencing of TRPM8 inhibits aggressive tumor phenotypes and enhances gemcitabine sensitivity in pancreatic cancer[END_REF], which was confirmed by qPCR for TRPM8 [START_REF] Du | Elevated Transient Receptor Potential Melastatin 8 (TRPM8) Expression Is Correlated with Poor Prognosis in Pancreatic Cancer[END_REF]. AQP1 and AQP3 were also more expressed in PDAC patients with lymph node metastasis and invasion, than in non-invasive cancers [START_REF] Zou | AQP1 and AQP3 Expression are Associated With Severe Symptoms and Poor-prognosis of the Pancreatic Ductal Adenocarcinoma[END_REF], whereas overexpression of Kir3.1 potassium channel (GIRK1) was not found to be correlated with metastatic status (Brevet et al., 2009).

Gene expression correlation analysis demonstrated that TRPM2 is strongly correlated with different genes including toll-like receptor 7 (TLR7) [START_REF] Lin | TRPM2 promotes the proliferation and invasion of pancreatic ductal adenocarcinoma[END_REF], which has already been associated with PDAC progression [START_REF] Ochi | Toll-like receptor 7 regulates pancreatic carcinogenesis in mice and humans[END_REF][START_REF] Grimmig | TLR7 and TLR8 expression increases tumor cell proliferation and promotes chemoresistance in human pancreatic cancer[END_REF][START_REF] Wang | Activation of Toll-like receptor 7 regulates the expression of IFN-lambda1, p53, PTEN, VEGF, TIMP-1 and MMP-9 in pancreatic cancer cells[END_REF]. Moreover, AQP1 and AQP3 protein expression was highest in poorly differentiated tumors [START_REF] Direito | Differential expression of aquaporin-3 and aquaporin-5 in pancreatic ductal adenocarcinoma[END_REF][START_REF] Zou | AQP1 and AQP3 Expression are Associated With Severe Symptoms and Poor-prognosis of the Pancreatic Ductal Adenocarcinoma[END_REF], whereas AQP5 is more expressed in moderately differentiated tumors [START_REF] Direito | Differential expression of aquaporin-3 and aquaporin-5 in pancreatic ductal adenocarcinoma[END_REF], suggesting that AQPs are associated with tumor aggressiveness.

Finally, most of the studied ion channels in PDAC tissue were associated with overall survival of the patients. The authors usually used immunohistochemical staining on large cohorts and Kaplan-Meier survival analysis, to observe a correlation between high channel expression and short patient survival. This is the case for KCa3.1 [START_REF] Jiang | Integrated expression profiling of potassium channels identifys KCNN4 as a prognostic biomarker of pancreatic cancer[END_REF], STIM1 [START_REF] Wang | STIM1 overexpression in hypoxia microenvironment contributes to pancreatic carcinoma progression[END_REF], TRPM8 [START_REF] Liu | Silencing of TRPM8 inhibits aggressive tumor phenotypes and enhances gemcitabine sensitivity in pancreatic cancer[END_REF], TRPV6 (Song et al., 2018), TMEM16J [START_REF] Jun | ANO9/ TMEM16J promotes tumourigenesis via EGFR and is a novel therapeutic target for pancreatic cancer[END_REF], CLIC1 [START_REF] Lu | Chloride intracellular channel 1 (CLIC1) is activated and functions as an oncogene in pancreatic cancer[END_REF][START_REF] Jia | CLIC1 overexpression is associated with poor prognosis in pancreatic ductal adenocarcinomas[END_REF], and AQP1/AQP3 [START_REF] Zou | AQP1 and AQP3 Expression are Associated With Severe Symptoms and Poor-prognosis of the Pancreatic Ductal Adenocarcinoma[END_REF]. The same correlation was obtained on gene expression using qPCR for TRPM8 [START_REF] Du | Elevated Transient Receptor Potential Melastatin 8 (TRPM8) Expression Is Correlated with Poor Prognosis in Pancreatic Cancer[END_REF] or TCGA for TRPM2 [START_REF] Lin | TRPM2 promotes the proliferation and invasion of pancreatic ductal adenocarcinoma[END_REF] and TMEM16A [START_REF] Crottes | TMEM16A controls EGF-induced calcium signaling implicated in pancreatic cancer prognosis[END_REF]. Furthermore, the mutation status of TRPM2 was also analyzed using Kaplan-Meier in 10 patients out of 159, and the mutated TRPM2 gene revealed a negative correlation with patient survival, compared to patients expressing wildtype TRPM2 [START_REF] Lin | TRPM2 promotes the proliferation and invasion of pancreatic ductal adenocarcinoma[END_REF]. Studies on shorter cohorts also revealed that high protein expression of Kv11.1 and TRPM7 channels are inversely correlated with overall survival using Pearson correlation on 18 patients, and multivariate overall survival analysis on 44 samples, respectively (Rybarczyk et al., 2012;Lastraioli et al., 2015a) Comparison of ion channels expression level in 9 patients with short survival (<12 months) and 10 patients with long survival (>45 months) showed that short survival was correlated with high expression of CLIC3 and low expression of CLCA1 [START_REF] Hu | Calcium-activated chloride channel regulator 1 as a prognostic biomarker in pancreatic ductal adenocarcinoma[END_REF]. This low CLCA1 expression correlated with shorter disease-free survival was confirmed using tissue microarrays, immunohistochemistry and Kaplan-Meier analysis in 140 patients (Hu et al., 2018a). Except for CLCA1 which could be proposed as a good prognostic marker, all the other studied ion channels could be proposed as poor prognostic markers.

These studies on human tissues highlighted the major clinical relevance of ion channels expression in pancreatic cancer development (Table 2 andFigure 3). Indeed, the expression of potassium, calcium, chloride channels, and aquaporins is mainly associated with aggressiveness and invasiveness and inversely correlated to patient survival, suggesting that they may be potential markers of poor prognosis.

Therapeutic Targets

In general, PDAC cells are resistant to pro-apoptotic reagents, and overexpression of ion channels was shown to be involved in this resistance. Knockdown of TRPM7 in combination with gemcitabine treatment enhanced cytotoxicity in PANC-1 cells even though the precise mechanisms are not yet determined [START_REF] Yee | Targeted silencing of TRPM7 ion channel induces replicative senescence and produces enhanced cytotoxicity with gemcitabine in pancreatic adenocarcinoma[END_REF], whereas the silencing of TRPV6 in Capan-2 PDAC cells resulted in a significant increase of sensitivity to the chemotherapeutic reagent oxaliplatin, but had little effect on gemcitabine and cisplatin treatments (Song et al., 2018). Another study has shown that silencing of TRPM8 in combination with gemcitabine suppressed the proliferation and invasion properties of PANC-1 and BxPC-3 cells. In addition, gemcitabinesensitivity depended on TRPM8 silencing in these cell lines, where mRNA level of multi-drug related proteins was decreased, and expression of apoptosis-related proteins was also affected, suggesting that TRPM8 is involved in multi-drug resistance and apoptosis of PDAC cells [START_REF] Liu | Silencing of TRPM8 inhibits aggressive tumor phenotypes and enhances gemcitabine sensitivity in pancreatic cancer[END_REF]. PANC-1 cells apoptosis was also increased after treatment with chemotherapeutic reagents 5-fluorouracil or gemcitabine in combination with a knockdown of ORAI1, STIM1, or both (Kondratska et al., 2014). Furthermore, it was shown that cells treated with either 5-fluorouracil or gemcitabine increased ORAI1 and STIM1 expression as well as SOC entry suggesting that ORAI1 and STIM1 confer resistance to chemotherapy, probably through the increase of SOC entry (Kondratska et al., 2014). More recently, STIM1 was found to be involved in gemcitabine resistance in PDAC [START_REF] Zhou | Identification of chemoresistance-related mRNAs based on gemcitabineresistant pancreatic cancer cell lines[END_REF]. The transcriptome sequencing analysis in established gemcitabine resistant PDAC cell lines, showed that STIM1 was significantly upregulated in the gemcitabine resistant cell lines, compared to the parental cell line [START_REF] Zhou | Identification of chemoresistance-related mRNAs based on gemcitabineresistant pancreatic cancer cell lines[END_REF]. Among the chloride channels, knockdown of TMEM16J provided an additive effect on inhibiting proliferation upon treatment with gemcitabine and erlotinib, suggesting that a TMEM16J inhibitor can help to prevent gemcitabine resistance associated with the prolonged use of gemcitabine [START_REF] Jun | ANO9/ TMEM16J promotes tumourigenesis via EGFR and is a novel therapeutic target for pancreatic cancer[END_REF]. The team of Arcangeli has been investigating another therapeutic perspective with the development of a novel anti-Kv11.1 antibody-conjugated PEG-TiO 2 nanoparticles for targeting PDAC cells [START_REF] Sette | Development of novel anti-Kv 11.1 antibody-conjugated PEG-TiO2 nanoparticles for targeting pancreatic ductal adenocarcinoma cells[END_REF].

CONCLUSION

Increasing evidence indicates that ion channels are involved in the regulation of cancer proliferation, apoptosis, chemoresistance, migration, and invasion. The field of ion channels in PDAC still constitutes a novel area of research and even studies conclude their involvement in the malignancy and aggressiveness of PDAC, only relatively few studies provide the complete signaling pathways. Moreover, the majority of the studies cited in this review were carried out on 2D cultured cell lines. It appears thus necessary to develop and/or increase better approaches (organoids, 3D culture, and/or animal models) to investigate the candidate channel(s) as well as its (their) function and associated signaling pathways in PDAC. However, recently, an increasing number of publications on signaling in pancreatic cancer take the tumor microenvironment into-account. This reflects the interest in ionic channels and their potential promising use as therapeutic targets in the fight against pancreatic cancer.

73

OBJECTIVES 74 PDAC remains one of the deadliest cancers (Park et al. 2021). The dismal prognostic of PDAC is mainly due to the late manifestation of symptoms, its high metastatic potential, and strong chemoresistance [START_REF] Mizrahi | Pancreatic cancer[END_REF]. A prominent hallmark of PDAC tumors is their unique tumor microenvironment characterized by excessive fibrosis, acidity, and depletion of oxygen and nutrients due to poor vascularity (Pedersen et al. 2017).

Strong evidence shows the impact of the acidic tumor microenvironment on PDAC aggressiveness in proliferation, migration, invasion, and apoptosis [START_REF] Orth | Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches[END_REF]. However, the underlying mechanisms are poorly understood.

The dysregulation of ion channels modulates cancerous processes to such an extent that this phenomenon is characterized as 'onco-channelopathies' (Prevarskaya et al. 2018). More specifically is, the role of Ca 2+ channels and signaling known to be implicated in carcinogenesis (Prevarskaya et al. 2007, Shapovalov et al. 2016, Chen et al. 2019). However, the interplay between ion channel dysregulation and the acidic tumor microenvironment is not well studied.

Among ion channel families implicated in Ca 2+ entry is the TRP channel family. The canonical TRPC subfamily of the TRP channel family is characterized as 'pH sensing ion channels' (Wang et al. 2020). The first member of the TRPC family is TRPC1, which is particularly known to be involved in cancer carcinogenesis both through Ca 2+ entry and independently of Ca 2+ entry (Elzamzamy et al. 2020).

TRPC1 is involved in the carcinogenesis of several types of cancer, including PDAC, but how it is affected by the tumor microenvironment is not well understood. Our group and others have recently shown that TRPC1 is activated by ambient pressure, a feature of the tumor microenvironment in PSCs. This activation of TRPC1 promotes the proliferation and migration of PSCs in a Ca 2+ -dependent manner (Fels et al. 2016, Radoslavova et al. 2022). Furthermore, TRPC1 promotes Ca 2+ entry in breast cancer carcinogenesis in a hypoxic tumor microenvironment (Azimi et al. 2017).

Several studies have shown the role of the acidic environment and TRPC1 in cancer progression, but until now, the link between them remains unknown. Thus, our objectives of this study were to determine the interplay between TRPC1 and the tumor microenvironment.

The specific aims of the present research were as follows.:

1. To make a comprehensive screen of Ca 2+ ion channels in human PDAC tissue and cell lines 2. To elucidate the role of TRPC1 in PDAC progression in the form of proliferation 3. To characterize the effect of the acidic tumor microenvironment on Ca 2+ channel expression 4. To evaluate the implication of the acidic tumor microenvironment and TRPC1 in PDAC proliferation and migration Finally, we aimed to investigate if the acidic microenvironment could affect the DNA methylation of specific ion channels and their expression.

Cell culturing 1. Cell lines

The cell lines employed in this study are one control cell line and several PDAC cell lines, where our primary focus has been PANC-1 cells. All cell lines, including their characteristics, are summarized in Table 2.

• HPNE

The control used in this study is the normal-like duct cell line, Human Pancreatic Nestin-Expressing cells (HPNE), which was obtained from the pancreas of a 52-year-old man after his accidental death. The cells were immortalized by transduction with a retroviral expression vector containing human telomerase (hTERT) cDNA. The cells do not exhibit mutations in three common genes of pancreatic ductal adenocarcinoma; KRAS, TP53, and p16.

• Colo357

Colo357 cells are collected from a lymph node metastasis of a 77-year-old female. After a period of 2 months, she demonstrated weight loss, anemia, anorexia, and progressive jaundice, and it was found that she had a tumor in the head of the pancreas. The tumor cells were well-differentiated, and later genotyping of Colo357 cells revealed that they exhibit a KRAS mutation but wildtype (WT) in the three other genes. However, a homozygous deletion in SMAD4 has been observed.

• BxPC-3 BxPC-3 cells were cultured from a 61-year-old female with a tumor in the body of the pancreas. There was no evidence of metastasis found. These cells are moderate to poorly differentiated and are the only cells in this study with no mutation in the KRAS gene. They exhibit mutations in p53 and CDKN2A.

• AsPC-1 AsPC-1 cells are derived from a 62-year-old female with adenocarcinoma in the head of the pancreas. The cell line was obtained and established from ascitic cell components. The cells are poorly differentiated and displays mutations in all driver genes.

• MiaPaCa-2

The undifferentiated MiaPaCa-2 cells were derived from a 65-year-old man with 6 months of recurrent abdominal pain. The tumor was removed from the body and tail of the pancreas, where it infiltrated the periaortic area. No metastasis was detected upon tumor removal. MiaPaCa-2 cells display mutations in all four genes except SMAD4.

• PANC-1 PANC-1 cells were obtained from a specimen removed from the head of the pancreas of a 56-year-old man who demonstrated a history of jaundice. The tumor had a size of 1.5 cm and was invading the duodenal wall.

Tumor cells were malignant undifferentiated cells, showing perineural invasion and metastases to one peripancreatic lymph node. Later investigations have shown that PANC-1 cells exhibit genetic alterations in KRAS, TP53 and CDKN2A.

All cell lines can be obtained at the American Type Culture Collection (ATCC). We kindly received our PDAC cell lines from Prof. Anna Trauzold from the Institute of Experimental Cancer Research, Kiel University, except for the MiaPaCa-2 cell line, which we kindly received from Prof. Natalia Prevarskaya from

The Laboratory of Cell Physiology, INSERM U1003, University of Lille. [START_REF] Moore | Genetic profile of 22 pancreatic carcinoma cell lines. Analysis of K-ras, p53, p16 and DPC4/Smad4[END_REF][START_REF] Grutzmann | Gene expression profiles of microdissected pancreatic ductal adenocarcinoma[END_REF][START_REF] Deer | Phenotype and genotype of pancreatic cancer cell lines[END_REF]

Cell maintenance

Cell culture experiments were performed under a type II microbiological safety cabinet (PSM) (Faster BH-EN-2003-S). The cells were seeded and cultured in culture flasks of 25 or 75cm2 (Nunc) treated to promote cell adhesion and placed in an incubator with an atmosphere saturated with humidity at 37 °C and 5% CO2.

HPNE cells were grown in a culture medium recommended by ATCC supplemented with 10% FBS (Table 3).

PDAC cell lines were cultured in RPMI-1640 medium. Medium pH was adapted by adjusting the HCO3concentration by adding the appropriate amount of NaHCO3, ensuring equal osmolarity by adjusting [NaCl] (Table 4). Cells were adapted to pH 7.4 and 6.5 by adding the appropriately pH-adjusted medium to freshly split cells and maintaining cells in this medium for 30 days. Cells were, after acidic adaptation, recovered in pH 7.4 for 14 days. Normal pH (7.4) conditions simulate the physiological pH in blood and organs. Acidic pH (6.5) simulates the conditions in the tumor microenvironment. Recovery conditions (7.4) simulate the recovery phase, of where cells potentially leave the tumor microenvironment by invasion and migration (Figure 28). In order to avoid geno-and phenotypic changes of the cells, the cells were passaged maximum 20 times, before a new vial was thawed. All cells were mycoplasma tested before freezing. To adjust the HCO3 -concentration, the Henderson Hasselback equation was used:

Components

!"#$"%&'# -!)&&"*+)*,ℎ: 0! = 02) + *'4 [6")7 +)&" ] [6")7 ),9$ ]
Adapting this equation to a cell culture system will look like this:

0! = 02 + *'4 [!:; < = ]
& * ?:; @ pK = 6.1. s is the inverse of the Henrys law constant for solubility of CO2 in aqueous solution s = 0.24 mmol/(l*kPa) and 5% CO2 gives 1.2 mmol/l CO2 Thus, the equation to have a pH of 6.5 will be:

6.5 = 6.1 + *'4 [!:; < = ]
1.2 * 5

Freezing and thawing of cells

At 80% confluence, the cells were detached by adding trypsin. A quantity of one million cells was centrifuged at 1500 rpm for 7 min, the cell pellet was then resuspended in 1 ml of a freezing medium composed of 90% medium and 10% dimethylsulfoxide (DMSO). The cell suspension was transferred to cryopreservation ampoules, and placed in CoolCellTM freezer boxes (Biocision, Dutscher, Thermofisher, France) at -80 °C, allowing slow and progressive freezing of the cells. The cells were rapidly thawed in a water bath at 37 °C.

The cells were transferred to an Eppendorf tube and then centrifuged at 1500 rpm for 5 minutes. The supernatant containing the DMSO (toxic to the cells) was then eliminated. The pellet composed of the cells was resuspended in their corresponding cell culture medium in a culture flask of 25 cm 2 and then placed in the incubator at 37° C and 5% CO2. Cells were kept for ~14 days before being used for experimental procedures.

Transfection

The principle of transfection is the process of introducing e.g., genetic material such as a plasmid or mRNA into eukaryotic cells, either to suppress or overexpress a gene. In this study, we have introduced a knock-down (KD) of a gene with the siRNA transfection approach. Here, we used the technique of electroporation, which is a physical transfection method that permeabilizes the cell membrane by applying an electrical pulse to move molecules (e.g., siRNA), with the help of a cell type-specific nucleofection buffer (Nucleofector Kit V, Amaxa) via the electrical field into the cell.

Control pH 7.4

Physiological pH in blood Acidic-adapted pH 6.5

Simulating pH in tumor microenvironment

Acid-recovered pH 7.4

Simulating condition where cells leave the tumor microenvironment

For transfection, cells were detached by trypsinization and counted (1 × 10 6 ). The cells were then centrifuged for 7 min at 1500 rpm, and the pellet was resuspended in 100 µL of transfection buffer to which we added 4

µg of Control (siCTRL) or target siRNA, in this case, the KD of TRPC1 (siTRPC1) (Table 5). Transfection efficiency was validated by mRNA and protein expression.

Generation of spheroids

It is well-accepted that 3D models imitate in vivo cell-cell and cell-extracellular matrix interactions better than traditional two-dimensional (2D) cell cultures. Therefore, spheroid models were included in this study to investigate ion channel expression and proliferation. In this study, both non-transfected and transfected cells were used. Monolayer PANC-1 cells were detached with trypsin and counted 2×10 3 cells per spheroid in 200 µL media. Cells were resuspended in ice-cold media containing 2% GelTrex (Gibco, #A1413202). Media containing cells and Geltrex TM (Gibco, A1413202) were transferred to a reservoir and then distributed to an ultra-low attachment round bottom 96-well plate (Corning, #7007). Fastly, the plate was centrifuged for 20 min at 750 RCF. It was checked whether cells formed proper spheroids in a bright field microscope. Spheroids were kept at 37° C and 5% CO2. Every second day the media was changed on spheroids by removing 100 µL of media and adding 100 µL of new media from each well. Pictures were taken every 2 nd , 4 th , 7 th , and 9 th day to control the spheroids' size.

Cell proliferation assays

• Trypan blue assay

The viability of cells was analyzed by the trypan blue assay. Trypan blue is an impermeable dye, which can pass the plasma membrane of dead cells but not alive cells. Here, we used trypan blue to assess the viability of PANC-1 cells, grown under the three different pH conditions. Media was removed from cells grown in 35mm Petri dishes and washed once with 200 µL PBS, then 200 µL trypsin to detach the cells. The effect of trypsin was inhibited with the removed media that the cells were grown in. Cells in suspension were mixed with 0.4% Trypan Blue reagent (Sigma-Aldrich) in a ratio 1:5. Cells were counted 6 times using the standard Malassez cell method. The viability was calculated as the total number of viable cells (cells alive/white cells) normalized to the control, and the mortality was calculated as the percentage of dead cells (blue cells) compared to the control.

• CellTiter-Glo® Assay

The viability of 3D cultured spheroids was evaluated with the CellTiter-Glo® 3D Assay (Promega). This reagent measures ATP as an indicator of viability and generates a luminescent readout. Spheroids grown for nine days were transferred to a black 96-well plate with 100 µL of media. For each well, 100 µL of CellTiter-Glo® were added. The plate was placed on a shaker for 5 minutes and for incubating without shaking for 25 minutes. Results were obtained with a FLUOSTAR microplate reader.

• Flow Cytometry

Flow cytometry was carried out on ethanol-fixed cells by a propidium iodide (PI) assay. The intercalating agent PI binds DNA, which can be emitted (excitation at 535nm/ emission at 617nm) by a fluorescent signal.

The premise with fluorescent dyes, such as PI, is that they are stoichiometric. That is they bind in proportion to the amount of DNA present in the cell. Cells that are in S phase will have more DNA than cells in G0/G1 phase, and cells in G2/M phase will have approximately the double amount of DNA than cells in G1. The more DNA, the more fluorescent the cells will be. Thus, the fluorescent signal can be used to distinguish between cells in G0/G1, S and cells in G2/M-phase, by a flow cytometer. Duplicates of 2×10 5 PANC-1 cells were seeded in 60 mm Petri dishes. The cells were either non-transfected or transfected for 72 h. For each condition, cells were washed in PBS and harvested in 400 µL trypsin, and resuspended in 3 ml media. The Petri dishes were washed with 4 ml PBS, which was pooled with the rest of the media. The cells were centrifuged for 7 min at 1000 RPM, washed in PBS, and centrifuged again. 3×10 5 cells were counted and transferred to an Eppendorf tube and centrifuged again. The pellet was resuspended in 150 µL PBS + EDTA 5 mM and fixed in 350 µL ice-cold Absolut ethanol during vortexing. Before staining with PI, the samples were kept at 4° C for at least one week. On the day of flow cytometry, cells were centrifuged for 7 min at 1000 RPM, and the supernatant was removed. Cells were resuspended in 100 µL of PBS + EDTA 5 mM. RNAse A was added to a final concentration of 20 µg/mL for 30 minutes at room temperature. Nuclei staining was performed with PI (50 µg/mL) immediately before the acquisition, which was performed using BD Accuri C6 flow cytometry.

Flow cytometry data was analyzed in Cyflogic, and figures were made in FCS Express 7.

Calcium Imaging

Calcium Imaging makes it possible to detect Ca 2+ concentrations in real-time. Variations in intracellular Ca 2+ concentrations can be measured by using a fluorescent probe, in this case, Fura-2. The Fura-2 is loaded with an AM (acetoxymethyl ester) group, which allows the probe to cross the plasma membrane of cells. When entered, the AM group is hydrolyzed by esterases resulting in the fluorescent signal of the cell cytoplasm.

Fura-2 has the characteristic of being ratiometric. Fura-2 is excited simultaneously at two wavelengths, 340 nm and 380 nm, and emitted at 510 nm. The binding of Ca 2+ to the probe causes a variation in fluorescence.

Thus, the fluorescence measured at 340 nm increases, and that at 380 nm decreases. Conversely, during a loss of affinity for Ca 2+ , the fluorescence at 340 nm decreases and increases at 380 nm. The ratio of the intensities emitted at 510 nm, after the excitation at the two wavelengths mentioned above, makes it possible to estimate the fluctuations of the Ca 2+ intracellular concentration.

20×10 3 transfected cells were seeded in the middle of an autoclaved coverslip in a 35 mm petri dish. 72 h after transfection, Fura-2 AM was loaded in a final concentration of 3.3 µM for 45 minutes. Coverslips were rinsed two times with Ca 2+ imaging solutions (Table 6) to remove excessive Fura-2. The coverslip was then attached to a plastic dish with a perforated bottom using silicone grease. The cells are then exposed to different excitation wavelengths using a monochromator (Polychrome V, Till Photonics). A CCD camera captures the fluorescence variations of the Fura-2 probe, and Metafluor acquisition software transforms the light signal into a digital signal. The software then quantifies the variations in Fura-2 emission fluorescence for each of the excitation wavelengths. Throughout the experiment, a perfusion/aspiration system allows the control of the extracellular environment. During the different Ca 2+ imaging protocols, the extracellular environment is composed as described in Table 6. The data is finally analyzed using Origin8 and GraphPad Prism Software. • Manganese quenching assay

Chemical Compounds

The principle of the Manganese (Mn 2+ ) quenching assay is based on fluorescent quenching. Mn 2+ is able to bind to Fura-2, which causes an irreversible quenching of the fluorescent signal and a conformational change of the probe. Since Mn 2+ permeate the cell membrane by the same pathways as Ca 2+ , the entry of extracellular Mn 2+ into the cells represents an indirect measurement of intracellular Ca 2+ movements. When Mn 2+ is present in the cells, it competes with Ca 2+ to bind Fura-2. At equal concentrations of Ca 2+ and Mn 2+ , the latter binds more than 99% of Fura-2, compared to Ca 2+ , which leads to elimination of the fluorescent signal. Thus, the greater the fluorescent quenching kinetics, the greater the influx of Mn 2+ , which can suggest a greater Ca 2+ entry. During the Mn 2+ quenching assay, the fluorescent probe is excited at 360 nm, corresponding to the isosbestic point of Fura-2. Excitation at this wavelength is important since the fluorescence of the probe is independent of the intracellular calcium concentration. For the experimental setup of the Mn 2+ quenching assay, cells are perfused with basic extracellular medium containing 2 mM Ca 2+ . After 90 sec, the extracellular medium is replaced by a medium containing 2 mM of Mn 2+ for 3 min. Replacing extracellular Ca 2+ with Mn 2+ leads to quenching of the fluorescent signal of Fura-2. By measuring the slope of the Mn 2+ quench, we can interpret the basal Ca 2+ entry.

• Store-operated channel entry assay

To test the capacity of SOCs to allow extracellular Ca 2+ across the plasma membrane, the cells used in this protocol were perfused with an extracellular Ca 2+ medium containing 2 mM Ca 2+ for 2 min. Then, this medium is replaced by an extracellular medium without Ca 2+ , supplemented with 1 µM thapsigargin, which allows the irreversible depletion of Ca 2+ stocks for 11 min. Next, the cells were again perfused with an extracellular medium containing 2 mM Ca 2+ , for 5 minutes. Finally, the cells were perfused with the 0 mM Ca 2+ solution for 5 minutes.

Transcriptional expression

Transcriptional expression

•

• Reverse transcription

To transform RNA to cDNA, the extracted RNA had to undergo reverse transcription (RT). This was done using a High-Capacity cDNA Reverse Transcriptase kit (Applied Biosystems). A volume corresponding to 2

µg RNA was completed with ultra-pure water to a final volume of 13.2 µL. To this, 6.8 µL of reaction mixture necessary to perform RT was added (Table 7). The heat-resistant tubes containing the RNA-reaction mixture was placed in a thermocycler to perform the RT, consisting of steps: (1) A primer fixing step for 10 min at 25°C. (2) The RT step for 2 hours at 37°C. (3) A step of stopping the reaction for 5 min at 85°C (deactivation of the enzyme). Following this step, the cDNA was stored at -20°C.

Reagents Volume

RT buffer 2 µL

Random primers 2 µL

Deoxyribonucleotides (dNTPs) 0.8 µL

RNase inhibitor 1 µL

Polymerase (MultiScribe TM ) 1 µL • Quantitative PCR Quantitative PCR (qPCR) allows for the amplification and detection of a specific DNA sequence in real-time.

Our qPCR experiments were carried out at the Regional Resource Center for Molecular Biology in Amiens (CRRBM) with the help of Dr. Stéphanie Guénin. The qPCR was performed in a 384-well plate using a thermocycler and Light Cycler® 480 software (Roche Molecular System, Inc.). The cDNA sample obtained during the RT was diluted 1/20 in ultra-pure water, then 2 µL of this diluted cDNA was diluted in the reaction mixture containing the primers, water, and SYBR Green mixture (Roche, France) (Table 8). SYBR Green is a DNA intercalating agent which emits fluorescence is proportional to the number of amplicons formed during PCR. Fluorescence is measured at the end of the elongation phase of each cycle.

Reagents Volume

Ultra-pure water The plate containing cDNA, primer, and SYBR Green mixtures was centrifuged for 30 sec and then placed in the thermocycler for 45 cycles, where each cycle is made up of three steps: (1) a denaturation step at 95°C for 30 s (2) a hybridization step at 60°C for 10 s, and (3) an elongation step at 72°C for 15 s. To quantify the transcriptional expression of our genes of interest, we determined the number of cycles from which the fluorescence linked to the amplification is detectable (cycles above 40 were considered not expressed). This threshold signal, called cycle threshold or Cycle Threshold (Ct) is inversely proportional to the quantity of cDNA initially present in the amplified sample. The quantification of the transcriptional expression of our actors of interest was normalized against the transcriptional expression of beta-2-microglobulin (B2M) using the following formula:

Ratio = (Efficiencytarget) ΔCttarget(control -sample) (Efficiencyreference) ΔCtreference(control -sample)
• Public database analysis

The mRNA expression of ion channels was investigated by using online available datasets. Whisker boxplots of ORAI, STIM and TRPC1 mRNA expression were generated using GEPIA2 ttp://gepia2.cancerpku.cn/) that compiles Genotype-Tissue Expression (GTEx) (http://www.GTEXportal.org/), and The Cancer Genome Atlas (TCGA) (http://www.cancergenome.nih.gov/) datasets of normal and tumor samples from different organs of interest, in our case pancreas and PDAC (PAAD). Survival analysis was performed using the SurvExpress online tool (available at http: bioinformatica.mty.itesm.mx/SurvExpress).

Protein expression

Either transfected or non-transfected cells were washed two times with ice-cold PBS on ice. The total protein was extracted using radioimmunoprecipitation assay (RIPA) protein extraction buffer, supplemented with protease inhibitors (Sigma), sodium orthovanadate (0. 5 mM), and EDTA (5 mM). 50 µL or 100 µL of the complete RIPA buffer was used for 60 mm and 10 cm Petri dishes, respectively. The cells were incubated with RIPA for 30 min, scrapped, and transferred into an Eppendorf tube. The sample was centrifuged for 15 min, at 14000 RPM at 4°C. After centrifugation, the supernatant containing the proteins was transferred into a new Eppendorf tube. The protein concentration was determined using the the Bradford colorimetric method (DC protein assay, Biorad) and using a BSA-based standard range. The assay is performed by measuring the optical density at 620 nm using a plate reader spectrophotometer (Tecan®) and Tecan I-Control software. The proteins were finally stored at -80°C.

• Western blot

Protein samples were diluted in 5X Laemmli and 1X Laemmli buffer to have the same concentration and amount of protein for each sample. The proteins were denatured at 95 °C for 10 min. After the denaturation step, the samples were loaded into an acrylamide gel, and proteins were separated by gel electrophoresis carried out in a Bio-Rad system using the Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE)

technique. Electrophoresis was permitted by the use of an electrophoresis buffer and carried out for 15 minutes at 100 volts (V) and 1 hour at 180 V. Following electrophoretic separation, the proteins were transferred to a nitrocellulose membrane by electroblotting. The transfer step was performed using a transfer buffer for 90 min at 60 V. The nitrocellulose membrane was then incubated for 1 h with gentle shaking at room temperature, in a Tris Buffered Saline (TBS) solution containing 0.1% Tween-20 (TBS-T) and 5% milk or 5% BSA, in order to prevent non-specific antibodies binding the membrane. The membrane was incubated in a primary antibody solution (diluted in TBS-T 5% BSA) overnight at 4°C with gentle shaking (Table 9 shows primary antibodies included in this study). After 3 washes with TBS-T of 5 minutes each, the membrane was incubated for 1 hour with gentle shaking in a secondary antibody solution (diluted in TBS-T 5% BSA), corresponding to the specie of the primary antibody, at room temperature. After the secondary antibody incubation, the membrane was finally washed with TBS-T (5 min each). The proteins recognized by the antibodies were revealed by chemiluminescence using the ECL reagent (Enhanced ChemiLuminescence, Biorad). The light signal emitted was captured by the ChemiDoc XRS device (Biorad) and integrated using the Quantity One® software (Biorad). The intensity of the signals was measured by densimetry. Photo analysis and quantification of protein bands were performed using ImageJ software. The expression of all the proteins of interest was normalized to the protein expression of GAPDH.

room temperature. After another sequential washing step, the proteins were eluted according to the manufacturer's protocol. The proteins were denatured and subjected to Western blotting, as described above.

To detect the input, 50 µg of proteins from the corresponding co-immunoprecipitation samples were used.

Proximity ligation assay

Proximity ligation assay (PLA) allows in situ detection of protein interactions with high sensitivity and specificity. In this study, 8 × 10 4 non-transfected or transfected PANC-1 cells were grown on coverslips 72 h before the PLA experiment. First, the cells were washed twice in PBS and fixed with 4% PFA at room temperature for 20 min. Following two washes with PBS, cells were permeabilized with 0.1% TritonTM X-100) for 10 min. The Duolink in situ PLA detection kit (Sigma-Aldrich, Saint-Quentin-Fallavier, France) was used to detect interactions/proximity between TRPC1 and the PI3K-p85α subunit. Experiments were performed according to the manufacturer's protocol. The red fluorescent oligonucleotides produced as the end product of the procedure were visualized using the Zeiss Observer Z1 microscope 60X oil objective (Carl Zeiss, Oberkochen, Germany). Images were analyzed using ImageJ, where puncta per cell were counted and normalized to the respective control; normal pH conditions (pH 7.4) for non-transfected cells, and siCTRL in their respective medium (pH 6.5 or 7.4R). Approximately 20 pictures per condition were captured and analyzed and presented as relative number puncta/cell.

Biotinylation

Biotinylation allows for specific isolation and quantification of proteins in the cell surface membrane. The biotinylation technique consists of labeling cell surface proteins with a biotin reagent before lysing the cells and isolating these biotin-tagged proteins with a streptavidin pull-down. In this study, 1 × 10 6 HPNE cells or 8 × 10 5 PANC-1 cells were seeded and collected after 48 h. Cells were washed three times with cold PBS, then incubated with 3 mg of Sulfo-NHS-SS-biotin (Thermo Scientific) and slightly shaken for 1 h at 4° C. The reaction was interrupted by adding cold PBS containing 10 mM glycine. Next, cells were scrapped with RIPA, and approximately 10% of the total lysate was saved as the total lysate fraction. The remaining sample was incubated with 100 µL high-capacity streptavidin-agarose beads (ThermoFisher Scientific, Waltham, MA, USA) with gentle rotation overnight at 4° C. After incubation, beads were washed 4 times with RIPA buffer.

Proteins were eluted from the beads with 50 µl of Laemli buffer 2X and heated at 60° C for 30 min. Both total lysate samples and membrane fraction samples were subjected to Western Blot analysis.

Intracellular pH

Measurements of pHi can be performed by the use of fluorescent dyes, such as the H + -dependent probe 2',7'-bis-(2-carboxyethyl)-5-(and-6)-carboxyfluorescein (BCECF) acetoxymethyl ester (AM). Initially, BCECF is esterified with acetoxymethyl esters, which allow cell entrance but leave BCECF essentially non-fluorescent. Once inside the cells, the esterases remove the ester groups from the probe, keeping it in the cells and enabling its protonation and fluorescent activity. H + quenches the fluorescence of BCECF, meaning that the fluorescence intensity of excited BCECF declines when lowering pH. BCECF is simultaneously excited at two wavelengths, 440 nm, and 485 nm. Excitation at 440 nm is not sensitive to pH changes, whereas excitation at a wavelength of 485 nm results in pH-dependent fluorescence, which is reduced when elevating the H + concentration (lowering pH). The background-corrected fluorescence intensity ratio between the two excitation channels is directly related to pHi and can be converted to pH values by calibration (described in Intracellular pH calibration). 8 × 10 4 cells were seeded in WillCo glass-bottom dishes WillCo Wells. After 48 h of seeding, cells were incubated in a growth medium containing 4 µM BCECF for 30 min in the dark at 37 °C, 95% humidity, 5% CO2. Cells were washed twice in HCO3 -containing Ringer solution (Table 10). Then, the cells in the glass-bottom dish containing Ringer solution adjusted to the respective pH were placed in a temperature-controlled compartment (37°C) equipped with gas. A group of cells was focused and monitored using the software EasyRatioPro, in which a measuring area inside certain cells was marked. In this area, the 440-and 485 nm intensities were simultaneously measured, and the emission was measured at 520 nm. The steady-state pHi measurements were carried out for 10 min.

• Intracellular pH calibration

Because BCECF is a quencher, its quantum yields diverge in different buffers, which is why calibration in situ, is required. In the present work calibration using the high K + /Nigericin method was obtained for each cell line (Boyarsky et al. 1996). Nigericin is an ionophore antiporting K + /H + . Supplying the cells with K + -based Ringer in a concentration equal to the intracellular, i.e. [K + ]i=[K + ]e, the transport will be driven by the electrochemical gradient of H + only. Therefore, pHi is clamped at the equilibrium at which

[K + ]i/[K + ]e=[H + ]i/[H + ]e.

Immunofluorescence analysis

To investigate the localization of TRPC1 and the PI3K-p85α subunit, we performed an immunofluorescence analysis assay with subsequent confocal imaging. 8 × 10 4 non-transfected HPNE or PANC-1 cells were seeded on coverslips for 48 h. Then, cells were washed twice in cold PBS and fixed for 20 min at room temperature in 4% paraformaldehyde. The cells were washed twice in PBS and permeabilized in 0.1% TritonTMX-100 for 10 min. Next, cells were blocked in 5% Bovine Serum Albumin (BSA) for 30 min, followed by the addition of primary antibodies (Table 12) overnight at 4 °C. Cells were washed three times in PBS, and secondary antibodies (AlexaFluor® 488/550 conjugated antibody 1:600) were applied for 1 h at room temperature, followed by treatment with 1% DAPI for 5 min to stain nuclei. Coverslips were washed three times in PBS and mounted on slides using Prolong® Gold antifade reagent. Images were collected on an Olympus Cell Vivo IX83 with a Yokogawa CSU-W1 confocal scanning unit. Z-stacks were deconvoluted in Olympus Cell Sens software using a constrained iterative algorithm. Controls without primary and secondary antibodies were made to rule out unspecific binding. No or negligible labeling was seen in the absence of primary and secondary antibodies. Overlays and brightness/contrast/background adjustments were carried out using ImageJ software. Mander's overlapping R coefficient was calculated using the ImageJ software plugin JACoP, which calculates the proportion of the green signal coincident with the magenta signal over the total intensity [START_REF] Bolte | A guided tour into subcellular colocalization analysis in light microscopy[END_REF]. The threshold setting was the same for both images.

Antibody

Migration assay

The Boyden Chamber assay is used to study the migration of cells across a microporous membrane. Cells are placed in the upper compartment of the chamber and allows the cells to migrate through the pores of the membrane into the lower compartment. After an appropriate incubation time, the membrane between the upper and lower compartment is fixed and stained, and the number of cells that migrated to the lower side of the membrane can be determined. In this study we used Boyden chambers with 8 µm pore size. 4 × 10 4 nontransfected or transfected PANC-1 cells were seeded in the upper compartment of the chamber. Both the upper and lower compartment were filled with the respective culture medium containing 10% FBS (meaning that no chemo-attractant was present). After 24 h of incubation at 37 °C, 95% humidity, and 5% CO2, inserts were washed in PBS and fixed in methanol for 15 min at room temperature, followed by staining with hematoxylin for 5 min. Inserts were washed in Milli-Q water and cleaned with a cotton swab. 20 adjacent fields were counted per insert in a brightfield microscope at ×400 magnification. The number of migrating cells was normalized to their respective control. To ensure that there was no difference in viability between the conditions after 24 h, the trypan blue assay (as described above) was performed. For Ca 2+ chelation assays, (see below) medium in both the upper and lower chamber was changed after 8 h of seeding, and Ca 2+ depleted medium or new normal medium containing Ca 2+ were added. Then cells migrated for 24 h.

Calcium depletion and calmodulin inhibition

To investigate the effect of extracellular Ca 2+ concentrations on either migration or proliferation, we chelated extracellular Ca 2+ concentrations by adding 0.4 mM Ethylene Glycol Tetraacetic Acid (EGTA). For proliferation assays Ca 2+ where chelated for 48 h, and for migration assays Ca 2+ where chelated for 24 h.

CaM is activated by Ca 2+ and is a connecting protein between TRPC1 and CaM. Therefore, we aimed to investigate the phosphorylation of AKT and ERK upon CaM inhibition. CaM was inhibited with the treatment of the antagonist W7 (25 µM) for 72 h.

Immunohistochemistry

Patient samples from this study were collected at the Amiens University Hospital. 21 samples from patients diagnosed with PDAC between 2018 and 2021 were used. A physician made the diagnosis of a paraffin block.

The samples were used anonymously and retrospectively in the Department of Pathological Anatomy and Cytology-Tumorotheque of Picardy in the context of research not involving the human person.

All experimental protocols were approved by the ethical committee of the University Hospital Center of Amiens (reference: PI2021_843_0027).

Classical immunohistochemistry was performed from formalin-fixed paraffin-embedded PDAC tumor material. First, 4 µM thick sections were deparaffinized in xylene and then rehydrated in ethanol. Next, the endogenous peroxidase activity was blocked with a 3% hydrogen peroxide solution before the antigen retrieval. The cell conditioning solution CC1 was used for antigen retrieval. Adding of antibodies was carried out using an automatic immunohistochemical staining was carried out on a BenchMark ULTRA system. First, primary antibodies were added and next biotin-labeled secondary antibody was applied, followed by the addition of avidin-biotin-peroxidase complex treatment. Reactions were developed using a chromogenic reaction with 3,3′-diaminobenzidine tetrahydrochloride. All tissue sections were counterstained with hematoxylin. To evaluate nerve invasion, slides were stained with S100, which marks the nerves. For vascular invasion, slides were stained with Factor VIII or ERG, which are expressed in vascular endothelial cells.

Negative controls were performed with the same technique and conditions, without adding the primary antibody. The marking intensity score ranged from 0 to 3 (0 = no immunostaining, 1 = weak immunostaining, 2 = moderate immunostaining, 3 = strong immunostaining). The localization of ion channels was evaluated as a percentage of being present in the cytoplasm or membrane. Primary and secondary antibodies against ion channels were used, as described in Table 13. The dilution and incubation time of primary antibodies were chosen by orchestrated time points and a dilution curve.

Antibody

Statistical analysis

In this study, all our data are shown as representative images or mean measurements with standard error of means (SEM) error bars and represent at least three independent experiments. n refers to the number of independent experiments performed or to the number of cells analyzed (as described in either text or figure legends). Welch's correction t-test or Tukey's multiple comparison test was applied to test for statistically significant differences between the two groups. *, **, and *** and **** denotes p < 0.05, p < 0.01, and p < 0.001, p < 0.0001, respectively. All graphs and statistical analysis were generated in GraphPad Prism 9.0 software.

Bisulfite sequencing

• Concept of bisulfite sequencing Bisulfite sequencing is considered the 'golden standard' method for studying DNA methylation. Standard DNA sequencing technologies do not possess the ability to distinguish cytosine and methylcytosine. The bisulfite treatment of DNA mediates the deamination of cytosine into uracil. Uracil is converted into thymine and is determined by PCR amplification and subsequent Sanger sequencing analysis. However, 5mC residues are resistant to the conversion provided by the bisulfite treatment and, so, will remain read as cytosine.

Therefore, comparing the Sanger sequencing read from an untreated DNA sample to the same sample following bisulfite treatment allows the detection of the methylated cytosines. With the advances in nextgeneration sequencing (NGS), the bisulfite treatment approach can be extended to DNA methylation analysis across an entire genome. However, the bisulfite treatment and conversion reduce genome complexity to three nucleotides (except the methylated cytosines, 5mC), and sequence alignment can become a more difficult task.

Thus, a less complex method was taken into use in this study, namely the bisulfite conversion-specific methylation-specific PCR (BS-MSP) [START_REF] Kurdyukov | DNA Methylation Analysis: Choosing the Right Method[END_REF]. Here, the DNA sequence of interest is amplified by PCR with primers specific for methylated and unmethylated DNA. The workflow of performing bisulfite sequencing is described in Figure 29.

Bisulfite Sequencing Procedures

Design primers in MethPrimer Make an overview of primer location in UCSC. • Bisulfite conversion-specific methylation-specific PCR CpG sites or upstream/downstream promoter regions of different ion channels were designed using the MethPrimer software (http://www.urogene.org/methprimer/) (Table 14). 4 µl of bisulfite-treated DNA was amplified by PCR with RDA buffer. A touchdown PCR cycling approach was used for all amplicons, and the specificity of the PCR was checked on a 2% agarose gel. The PCR product was extracted from the agarose gel with a NucleoSpin Gel and PCR Clean-up kit (Machinery Nagel #740609.250).

DNA preperation

Extract

Gene promoter

R ACCCACCTACCCCTACAAAAC 56

Table 14. Overview of bisulfite sequencing primers.

• Cloning and sequencing

After purification, the PCR product was cloned into the vector pCR Ò 2.1 (TA Cloning kit, Invitrogen). The reaction mixture is described in Table 15.

• Semiquantitative analysis method

The semiquantitative analysis method is based on the fact that several inserts from different clones are sequenced at the same time, and it gives a notion of whether the specific CpG sites are methylated. The semiquantitative analysis distinguishes between C's or T's at the CpG site at a specific ratio. The percentage of conversion of non-CpG cytosines was used as an index of overall bisulfite reaction efficiency (Figure 30).

The sequence was aligned to an 'in silico bisulfite-converted sequence' corresponding to the same gene promoter by using Clustal Omega alignment tool. The conversion efficiency of >97% was included in the study.

• Quantitative analysis method

The quantitative analysis method is used for more accurate analysis. Here, only one plasmid is sequenced alone, and it can be directly interpreted if the C's remain or is converted into T's (Figure 30). Thus, the quantitative method distinguishes between methylated (100) or not methylated (0). The sequence was aligned to an 'in silico bisulfite-converted sequence' corresponding to the same gene promoter by using Clustal Omega alignment tool. The conversion efficiency of >97% was included in the study.

97

RESULTS

Part 1: The TRPC1 channel forms a PI3K/CaM complex and regulates pancreatic ductal adenocarcinoma cell proliferation in a Ca 2+ -independent manner Ca 2+ channels are overexpressed in human PDAC tissue and cell lines Several ion channels, including Ca 2+ channels, are dysregulated in different types of cancer (Tajada and Villalobos 2020). Even though several studies have implicated these Ca 2+ channels in PDAC progression, a comprehensive overview of their expression in human PDAC tissue has not yet been accomplished. Thus, we compared the mRNA expression of Ca 2+ channels between normal pancreatic tissue and human PDAC samples using the PAAD TCGA dataset of normal and tumor samples. Specifically, we found that ORAI1, ORAI2, ORAI3, TRPC1, and STIM1 were overexpressed in PDAC tissue (Figure 31). Hence, we aimed to investigate the protein expression of these Ca 2+ channels in our local cohort of human PDAC samples. Our IHC results confirmed that ORAI3 (Figure 32A, n = 12, p < 0.05) and TRPC1

(Figure 32B n = 21, p < 0.05) were significantly overexpressed by 60.2 ± 24.3% and 33 ± 12.5%, respectively, in human PDAC tissue compared to adjacent non-tumor tissue. The other Ca 2+ channels did not show any significant difference in expression (Figure 33). Interestingly, both ORAI3 and TRPC1 were more localized to the plasma membrane in tumor cells when compared to non-tumor cells, where both were found mainly expressed in the cytoplasm. Further, we investigated the mRNA expression of these Ca 2+ channels in different PDAC cell lines.

Here, we demonstrated that these Ca 2+ channel expression profiles differed among cell lines. Notably, TRPC1 was overexpressed in the highly aggressive PDAC cell line PANC-1 compared to the normal-like duct cell line HPNE, where ORAI3 and STIM2 seemed to be overexpressed in the less aggressive cell lines BxPC-3 and AsPC-1. STIM1 was significantly upregulated in AsPC-1 and PANC-1 cells.

These results indicate that STIM, ORAI and TRPC1 are overexpressed in human PDAC tissue, at least at the transcriptomic level. Additionally, they are differentially expressed among cell lines. The role of ORAI3 has recently been demonstrated in human PDAC cell lines and tissue [START_REF] Arora | Orai3 Regulates Pancreatic Cancer Metastasis by Encoding a Functional Store Operated Calcium Entry Channel[END_REF][START_REF] Dubois | ORAI3 silencing alters cell proliferation and promotes mitotic catastrophe and apoptosis in pancreatic adenocarcinoma[END_REF]).

In our study, TRPC1 was consistently overexpressed in human PDAC tissue at a transcriptomic and protein level and additionally highly expressed in the aggressive PDAC cell line, PANC-1. Combined with the sparse knowledge of TRPC1 in PDAC carcinogenesis, our further work was based on these findings and aimed to investigate the role of TRPC1 in PDAC progression. 102 Summary PDAC is a highly aggressive neoplasm and is predicted to become the second leading cause of cancer by 2030, surpassing colorectal-and breast cancer [START_REF] Rahib | Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States[END_REF]. Due to the lack of diagnostic biomarkers and early-stage symptoms, diagnosis often occurs at advanced, invasive stages. Despite extensive efforts, both cytotoxic and targeted therapies have provided limited efficacy and marginally prolonged survival for patients with PDAC [START_REF] Mizrahi | Pancreatic cancer[END_REF]). Thus, new strategies for screening and detecting PDAC tumors at earlier stages are desperately needed to make a clinically significant impact.

Ca 2+ is an intracellular messenger involved in both physio-and pathophysiological conditions, as cellular functions depend on Ca 2+ homeostasis. The regulation of Ca 2+ levels through Ca 2+ channels is essential for maintaining cellular processes, such as proliferation. Transient receptor potential channels and storeoperated channels (SOC) are important players in maintaining these Ca 2+ levels in epithelial cells (Borowiec et al. 2014, Hodeify et al. 2018). The first identified member of the TRP canonical subfamily (TRPC1) is involved in tumor progression in different types of cancer and is recognized as a potential biomarker (Elzamzamy et al. 2020). The impact of TRPC1 in carcinogenesis is demonstrated through both Ca 2+dependent and -independent mechanisms. One study has shown that Ca 2+ entry through TRPC1 promotes migration of the PDAC cell line BxPC-3 (Dong et al. 2010). However, other studies have shown that TRPC1 regulates carcinogenesis in a Ca 2+ -independent manner (El Boustany et al. 2008, Davis et al. 2012, Madsen et al. 2012, Asghar et al. 2015, Selli et al. 2015, Selli et al. 2016, Sun et al. 2021). Until present, the expression and role of TRPC1 in highly aggressive PDAC cell lines have not yet been demonstrated. Based on our data described above, we first aimed to investigate if TRPC1 could be a potential biomarker of PDAC and if its overexpression correlated with clinical factors. Next, we aimed to investigate the functional role of TRPC1 in PDAC progression.

In our study, we demonstrated that the mRNA overexpression of TRPC1, analyzed by PAAD TCGA datasets, was significantly higher in the aggressive basal-like PDAC subtype compared to TRPC1 expression in the classical subtype. Additionally, a Kaplan-Meier survival analysis using Survexpress revealed that patients with high levels of TRPC1 displayed a significantly low overall survival compared to patients with low levels of TRPC1.

Here, the data demonstrating the high TRPC1 expression and plasma membrane localization in human PDAC samples from our local cohort were presented. We showed that cell lines, preliminary investigated for TRPC1 mRNA expression, displayed high TRPC1 protein expression. Interestingly, the expression was significantly higher in MiaPaCa-2 and PANC-1 cells compared to the normal-like duct cell line HPNE. As TRPC1 was overexpressed in the remarkably aggressive PDAC cell line PANC-1, we chose to investigate the downstream mechanisms of TRPC1 in this cell line. In PANC-1 cells, we found a robust plasma membrane localization of TRPC1, which we did not find in HPNE cells where TRPC1 seemed to be localized in cytoplasmic compartments.

To investigate the downstream effects of TRPC1, we developed a loss-of-function model by silencing TRPC1 with a siRNA approach. The efficiency of the KD was validated by qPCR and immunoblot analysis. Subsequently, we investigated the role of TRPC1 in PANC-1 cell and spheroid proliferation. We demonstrated that TRPC1 silencing decreased cell proliferation and spheroid viability. Additionally, flow cytometric analysis revealed that TRPC1 KD resulted in an accumulation of cells in the G1 phase along with a reduced number of cells in the S phase. These observations correlated with the decreased expression of the cell cycle regulating proteins CDK6, CDK2, and Cyclin A and the increased expression of p21.

As the role of TRPC1 in Ca 2+ entry has been contradictory among different cell lines, we sought to determine the Ca 2+ signature specific to TRPC1 in PANC-1 cells. Indeed, we found that TRPC1 silencing did not affect either basal or SOCE. Furthermore, the proliferative role of PANC-1 cells did not depend on Ca 2+ entry, as there was no significant difference between the proliferation of PANC-1 cells grown in a medium with normal extracellular Ca 2+ levels or in a medium with low extracellular Ca 2+ levels.

The PANC-1 cell line has mutations in three out of four driver genes (KRAS, TP53, CDKN2A), and TRPC1 has been shown to regulate cancer cell proliferation through downstream pathways of these oncogenes. Thus, we aimed to investigate if TRPC1 regulated PANC-1 cell proliferation through the PI3K/AKT and MAPK/ERK pathways. We found that TRPC1 KD mainly decreased the activation of AKT and, to less extent, ERK, indicating that TRPC1 regulates PANC-1 cell proliferation through a PI3K/AKT axis rather than the MAPK.

Hence, we investigated the physical interaction between the PI3K-p85 subunit and TRPC1. Our PLA showed proximity between TRPC1 and the PI3K-p85 subunit. Our co-IP, followed by immunoblot analysis, revealed a strong interaction between TRPC1, the PI3K, and their connecting protein calmodulin (CaM). This interaction was abolished upon TRPC1 silencing.

Taken together, our data revealed that TRPC1 is a potential biomarker of PDAC by being upregulated in human PDAC tissue and cell lines. We demonstrated that TRPC1 regulates PANC-1 cell proliferation and spheroid growth through direct interaction with the PI3K and CaM. Thus, activating downstream signaling pathways regulating G1 and S phase progression, likely through Ca 2+ -independent mechanisms.

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent type of pancreatic cancer, accounting for more than 90% of all pancreatic malignancies [1]. With a mortality rate similar to its incidence, the 5-year survival rate remains one of the lowest (less than 10%) of all cancers [2]. When detected, PDAC is often at a late disease stage. Overall, the response rate for late-diagnosed patients is limited. The poor prognosis of PDAC patients is associated with rapid tumor progression and limited available treatments [3].

Calcium (Ca 2+ ) is a ubiquitous intracellular messenger that transduces signals in cellular processes, including cell fertilization, differentiation, cell growth, and death [4]. The influx of Ca 2+ through Ca 2+ channels plays an important role in cell cycle progression in several cell types [5,6]. However, the direct relationship between Ca 2+ and cellular proliferation is complex, as many cell types can proliferate even in the near absence of extracellular Ca 2+ [7]. The transient receptor potential (TRP) and store-operated channels (SOC) are recognized as major regulators of the Ca 2+ influx in epithelial cancer cells [8]. Growing evidence demonstrates that the TRP canonical (TRPC) channel subfamily is involved in tumor development [9,10]. The first identified member of this non-selective cation channel subfamily is TRPC1. TRPC1 is a potential regulator of store-operated Ca 2+ entry (SOCE) pathways [11] and has shown to be a potential biomarker of different cancer types, as its dysregulation correlates with several clinical parameters, including overall survival [12][13][14][15][16][17][18][19][20][21]. At the cellular level, TRPC1 contributes to a plethora of physiological and pathophysiological processes, including tumor cell proliferation and growth. However, it seems that it depends on the cancer cell type, and whether the presence or absence of TRPC1 contributes to cell growth. In a majority of studies, TRPC1 downregulation inhibits the proliferative rate in neuroblastoma [22], glioblastoma [23], thyroid [24], breast [12,[25][26][27], lung, [28], liver [29,30], ovarian [31], and colon cancer [13]. Whereas in other studies, TRPC1 downregulation drives proliferation and growth in esophageal [32] and breast cancer [33]. Additionally, it is controversial whether the influx of Ca 2+ causes this proliferation through TRPC1. In different cancer cell models, the depletion of TRPC1 diminishes SOCE [12,23,[27][28][29], whereas, in others, this increased or did not affect SOCE [13,24,30,[34][35][36][37]. TRPC1 principally regulates proliferation through the phosphoinositol-3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) pathways in several cancers [13,26,28,38]. TRPC1 regulates PI3K and its downstream signaling kinases, such as AKT, differently, depending on whether it is an activator or an inhibitor of proliferation. Thus, in the lung (A549) and hepatocellular (Huh7) cancer cell lines, the depletion of TRPC1 inhibits cell proliferation by decreasing the activation of AKT [28,29]. Meanwhile, TRPC1 downregulation enhances cell proliferation by activating AKT in the esophageal (EC9706 cells) and breast (MCF-7 cells) carcinoma cell lines [32]. Recently, it has been shown that TRPC1 interacts with PI3K through calmodulin (CaM). Here, CaM, a multifunctional intracellular Ca 2+ -binding protein, works as a connecting protein between TRPC1 and PI3K, thereby regulating colorectal cancer progression [13].

Nonetheless, to the best of our knowledge, nothing is known about TRPC1 expression in PDAC tumors and the possible downstream mechanisms that contribute to PDAC cell proliferation. In the present study, we demonstrated that TRPC1 upregulation correlates with low overall survival in PDAC patients. Furthermore, we revealed that TRPC1 regulates cell proliferation and cell cycle progression, particularly in aggressive PDAC cells, independently from Ca 2+ -entry, by forming a complex with the PI3K p85↵ subunit and CaM, leading to activation of AKT.

Results

TRPC1 Upregulation Correlates with the Aggressive Basal-like Subtype of PDAC and with Low Overall Survival

The expression of TRPC1 has been shown to be dysregulated in several types of cancer [1][2][3][4] and was recently shown to be correlated with poor prognosis in colorectal cancer [5]. However, little is known about its expression in PDAC. Therefore, we analyzed the expression of TRPC1 in normal pancreatic tissue and human PDAC samples using the PAAD TCGA dataset of normal and tumor samples. The results showed that TRPC1 mRNA expression was significantly upregulated in PDAC tissue samples compared to non-tumor tissue samples (N = 171 vs. 179, p < 0.01, Figure 1A). Furthermore, the results showed that the upregulation of TRPC1 was significantly higher in samples of a more aggressive basal-like PDAC subtype (N = 171 vs. 65 p < 0.01, Figure 1B) compared to TRPC1 expression in the classical PDAC subtype (N = 171 vs. 86, Figure 1B). To investigate the prognostic significance of TRPC1, we analyzed whether TRPC1 overexpression was associated with survival in PDAC patients. The Kaplan-Meier survival analysis using SurvExpress, an online resource to correlate gene expression with overall survival, showed that patients with high levels of TRPC1 (N = 110) expression were associated with a significantly low overall survival compared to patients with low expression (N = 66, p < 0.01, Figure 1C). Altogether, these online available expression data reveal that TRPC1 is overexpressed in human PDAC tissue, which correlates with low overall survival.

TRPC1 expression in the classical PDAC subtype (N = 171 vs. 86, Figure 1B). To invest the prognostic significance of TRPC1, we analyzed whether TRPC1 overexpression associated with survival in PDAC patients. The Kaplan-Meier survival analysis u SurvExpress, an online resource to correlate gene expression with overall surv showed that patients with high levels of TRPC1 (N = 110) expression were associated a significantly low overall survival compared to patients with low expression (N = 6 0.01, Figure 1C). Altogether, these online available expression data reveal that TRP overexpressed in human PDAC tissue, which correlates with low overall survival.

TRPC1 Is Overexpressed in Cell Lines with an Aggressive Phenotype and Is Localized to the Plasma Membrane

TRPC1 is located both in the plasma membrane and intracellular sites [39]. However, its localization in pancreatic ductal cells and PDAC cells is still unknown, although TRPC1 has been found in the apical and lateral regions of the basolateral membrane of pancreatic acinar cells [40]. Thus, we compared the TRPC1 expression and localization in human PDAC and adjacent non-tumor tissue samples from our local cohort (N = 21). Our immunohistochemistry (IHC) results confirmed the GEPIA2 analysis, showing a significant upregulation of TRPC1 by 33 ± 12.5% (p < 0.05, Figure 2A,B). Moreover, TRPC1 was considerably more localized to the plasma membrane in tumor cells when compared to non-tumor cells, where TRPC1 was found mainly expressed in the cytoplasm (p < 0.0001, Figure 2A,C,D). Transcriptional expression of TRPC1 has been found in different types of commercially available PDAC cell lines (BxPC-3, CAPAN-1, CFPAC, and PANC-1) [41,42]. However, to our knowledge, its expression has not yet been compared to a normal pancreatic cell line. We investigated the protein expression of TRPC1 in different pancreatic cell lines. TRPC1 was overexpressed in five different PDAC cell lines, significantly in the MIA PaCa-2 cell line by 83 ± 22.6% and in the PANC-1 cell line by 88 ± 8.9% when compared to the normal-like pancreatic ductal cell line HPNE (n = 4-5, p < 0.05, Figure 2E). Since the expression of TRPC1 was significantly upregulated in the particularly aggressive PDAC cell line PANC-1, this cell line was the focus of the subsequent study. Hence, we investigated the localization of TRPC1 in PANC-1 and HPNE cells. We found a robust membrane localization of TRPC1 in PANC-1 cells, which we did not find in HPNE cells, where it seems that TRPC1 tended to be localized in the cytoplasm (Figure 2F). Collectively, these findings suggest that TRPC1 is upregulated in human PDAC tissue and cell lines when compared to adjacent non-tumor tissue and a non-cancerous cell line. TRPC1 also localizes to the plasma membrane of tumor cells when compared to non-tumor cells.

The Knockdown of TPRC1 Inhibits PANC-1 Cell and Spheroid Growth

To study the role of TRPC1, we validated our knockdown (KD) model (Supplementary Figure S1). TRPC1 protein expression decreased by 44 ± 10% after 72 h of siRNA transfection against TRPC1. Similar results were obtained by assessing the TRPC1

The Knockdown of TPRC1 Inhibits PANC-1 Cell and Spheroid Growth

To study the role of TRPC1, we validated our knockdown (KD) model (Supplementary Figure S1). TRPC1 protein expression decreased by 44 ± 10% after 72 h of siRNA transfection against TRPC1. Similar results were obtained by assessing the TRPC1 transcriptional levels 48, 72, and 96 h post-transfection (Supplementary Figure S1A). We investigated the role of TRPC1 in PANC-1 cell proliferation by the trypan blue assay. The KD of TRPC1 resulted in a significant decrease of PANC-1 cell viability by 48 ± 17.4% and 38 ± 17.6% after 72 and 96 h post-transfection, respectively (n = 4, p < 0.05, Figure 3A). Even though our trypan blue assay indicated increased mortality 48 h post-transfection, our annexin-5 analysis did not show any significant difference in cell mortality between conditions (Supplementary Figure S2A-C). As 3D models imitate in vivo cell-cell and cell-extracellular matrix interactions better than traditional two-dimensional (2D) cell cultures [43], we established a 3D model of PANC-1 cell spheroids grown for nine days upon a KD of TRPC1. First, we confirmed the KD of TRPC1 after nine days, where TRPC1 protein levels decreased by 22 ± 1.0% (Supplementary Figure S1C). This KD of TRPC1 significantly decreased the viability of spheroids after nine days by 22 ± 2.3% (n = 3, p < 0.05, Figure 3B). Collectively, these results suggest that silencing of TRPC1 inhibits PANC-1 cell and spheroid proliferation. 0.05, Figure 3B). Collectively, these results suggest that silencing of TRPC1 inhibits PANC-1 cell and spheroid proliferation.

The Knockdown of TRPC1 Regulates Cell Cycle Progression by Reducing the Expression of CDK6, 2, and Cyclin A and Increasing the Expression of p21 CIP1

To investigate the possible mechanism by which the KD of TRPC1 affects PANC-1 cell proliferation, the cell cycle distribution was examined by flow cytometry. We found that the KD of TRPC1 increased the number of PANC-1 cells in G0/G1 phase by 13.8 ± 3.7% and decreased the number of cells by 25.7% ±10.3% in S-phase (n = 4, p < 0.05, Figure 4A). To further confirm the TRPC1-dependent regulation of cell cycle progression, we analyzed the expressions of several essential cell cycle-driven proteins involved in the G1-and S-phases. The immunoblot analysis showed that the expressions of CDK6 and CDK2 were significantly decreased by 44 ± 5.3%, 39 ± 1.4%, and Cyclin A by 24 ± 2.3%, respectively, upon KD of TRPC1 (n = 3-4, p < 0.05, Figure 4B). Moreover, the expression of p21 CIP1, known to inhibit the CDK2 and CDK6 complexes, was significantly upregulated by 23 ± 4.6% (n = 3, p < 0.05, Figure 4B). However, TRPC1 KD failed to affect the expression of cyclin B1, D1, D3, and E, along with CDK1 and CDK4 (Supplementary Figure S3). Together, this suggests that TRPC1 depletion arrests cells in the G1 phase and decreases the cell fraction in the S-phase.

that the KD of TRPC1 increased the number of PANC-1 cells in G0/G1 phase by 13.8 ± 3.7% and decreased the number of cells by 25.7% ±10.3% in S-phase (n = 4, p < 0.05, Figure 4A). To further confirm the TRPC1-dependent regulation of cell cycle progression, we analyzed the expressions of several essential cell cycle-driven proteins involved in the G1and S-phases. The immunoblot analysis showed that the expressions of CDK6 and CDK2 were significantly decreased by 44 ± 5.3%, 39 ± 1.4%, and Cyclin A by 24 ± 2.3%, respectively, upon KD of TRPC1 (n = 3-4, p < 0.05, Figure 4B). Moreover, the expression of p21 CIP1, known to inhibit the CDK2 and CDK6 complexes, was significantly upregulated by 23 ± 4.6% (n = 3, p < 0.05, Figure 4B). However, TRPC1 KD failed to affect the expression of cyclin B1, D1, D3, and E, along with CDK1 and CDK4 (Supplementary Figure S3). Together, this suggests that TRPC1 depletion arrests cells in the G1 phase and decreases the cell fraction in the S-phase. Although it has been shown that TRPC1 functions as a SOC channel in the PDAC cell line BxPC-3 [42], it is very controversial whether TRPC1 is a modulator of Ca 2+ entry [44]. In different colorectal, thyroid, and hepatocellular cancer cells, TRPC1 did not contribute to cancer progression through SOCE [13,24,37,45]. Therefore, we investigated the role of TRPC1 in Ca 2+ entry of PANC-1 cells using the manganese-quenching technique. TRPC1 silencing did not affect the Mn 2+ quench (6 ± 9.2% increase, n = 342 and 382, for siCTRL and siTRPC1, respectively, Figure 5A). Furthermore, using the classical SOCE protocol, we showed that TRPC1 silencing did not participate in SOCE (2.6 ± 3.2% increase, n = 303 and 280, for siCTRL and siTRPC1, respectively, Figure 5B,C) or affected the intracellular Ca 2+ concentration estimated by the basal ratio (1.8 ± 1.7% increase, n = 303 and 280, for siCTRL and siTRPC1, respectively, Figure 5B,D). As TRPC1 does not appear to be involved in Ca 2+ entry in PANC-1 cells, we investigated whether PANC-1 cell proliferation was Ca 2+ -dependent or independent. We evaluated the proliferation of PANC-1 cells cultured for 48 h in a medium depleted of Ca 2+ . This extracellular Ca 2+ chelation by EGTA did not decrease cell viability (Figure 5E). Moreover, TRPC1 silencing further decreased the cell proliferation regardless of the extracellular Ca 2+ concentration by 32 ± 5.3% and 37.0 ± 5.2%, with or without Ca 2+ , respectively (n = 3, p < 0.01). These results suggest that TRPC1 is not involved in the Ca 2+ entry of PANC-1 cells and regulates cell proliferation by a Ca 2+ -independent mechanism.

TRPC1 Strongly Regulates AKT Phosphorylation in PANC-1 Cells

Two key downstream proteins responsible for cell proliferation are the serine/threonine kinases AKT and ERK1/2 [46]. The phosphorylation of these kinases has been shown to be dependent on TRPC1 expression [28,47]. We investigated the role of TRPC1 in the phosphorylation of AKT and ERK1/2 in transfected PANC-1 cells starved for 24 h, which were then mitogen-activated with FBS for 30 min. The immunoblot analysis revealed that the KD of TRPC1 significantly reduced AKT activation by 39 ± 7.8%, while total AKT expression remained unchanged (n = 4, p < 0.05, Figure 6A). A slight reduction of ERK1/2 phosphorylation (13 ± 0.4%, (n = 4, p < 0.0001, Figure 6B) was observed in cells transfected with siTRPC1. These results indicate that TRPC1 regulates PANC-1 cell proliferation through activation of AKT.

TRPC1 in the phosphorylation of AKT and ERK1/2 in transfected PANC-1 cells starved for 24 h, which were then mitogen-activated with FBS for 30 min. The immunoblot analysis revealed that the KD of TRPC1 significantly reduced AKT activation by 39 ± 7.8%, while total AKT expression remained unchanged (n = 4, p < 0.05, Figure 6A). A slight reduction of ERK1/2 phosphorylation (13 ± 0.4%, (n = 4, p < 0.0001, Figure 6B) was observed in cells transfected with siTRPC1. These results indicate that TRPC1 regulates PANC-1 cell proliferation through activation of AKT.

TRPC1 Interacts with PI3K, Which Is Attenuated upon the Knockdown of TRPC1

TRPC1 has been shown to be involved in activating the PI3K signaling pathway [13,38,47]. In addition, it has been demonstrated that CaM is a connexin between TRPC1 and the p85↵ subunit of PI3K [13]. Thus, we investigated whether TRPC1 interacts with the PI3K-p85↵ subunit in PANC-1 cells using Co-IP and PLA techniques. Our results by PLA analysis showed that TRPC1 and PI3K are located particularly close to each other (<40 nm) and can possibly interact. There was a relative decrease of 57 ± 7.8% puncta per cell in siTRPC1 cells compared to siCTRL cells (n = 3, p < 0.0001, Figure 7C). By co-IP, we found that TRPC1 interacts with PI3K and CaM in PANC-1 cells (Figure 7A). As an outcome of TRPC1 silencing, the interaction between TRPC1, PI3K, and CaM was reduced (Figure 7B) by 32 ± 4.5%, 51 ± 15.8%, and 31 ± 0.1%, respectively. These results suggest that the loss of TRPC1 can attenuate PI3K signaling.

(<40 nm) and can possibly interact. There was a relative decrease of 57 ± 7.8% puncta per cell in siTRPC1 cells compared to siCTRL cells (n = 3, p < 0.0001, Figure 7C). By co-IP, we found that TRPC1 interacts with PI3K and CaM in PANC-1 cells (Figure 7A). As an outcome of TRPC1 silencing, the interaction between TRPC1, PI3K, and CaM was reduced (Figure 7B) by 32 ± 4.5%, 51 ± 15.8%, and 31 ± 0.1%, respectively. These results suggest that the loss of TRPC1 can attenuate PI3K signaling.

Discussion

A wide range of physiological functions has been attributed to the expression and regulation of TRPC1, including cell proliferation, migration, invasion, and apoptosis [9,10,48,49]. In recent years, there has been increased interest in TRPC1 and its connection with tumorrelated functions, and several studies have reported different downstream mechanisms of TRPC1 in several types of cancers [11]. However, there is sparse evidence of its involvement in PDAC progression. In this study, we revealed the role of TRPC1 and its downstream mechanisms that contribute to PDAC cell proliferation. TRPC1 is upregulated in various types of cancer, such as tongue, breast, gastric, ovarian, colorectal, and renal cell carcinoma, where its expression correlates with different clinical factors [12][13][14][15][16][17][18][19][20][21]. For instance, the high expression of TRPC1 correlated with low overall and event-free survival in colorectal cancer patients [13,17] and disease-free survival in lung cancer patients [21]. In endometrial cancer patients, the high expression of TRPC1 was correlated with low overall survival, even though the expression of TRPC1 was downregulated when comparing endometrial cancer with adjacent tissue samples [15]. In congruence with this, we show that TRPC1 is upregulated in PDAC tissue compared to non-tumor tissue samples. Interestingly, the expression of TRPC1 is higher in the basal-like subtype of PDAC, which is associated with a poorer clinical outcome and loss of differentiation [50]. In addition, our findings show that the high expression of TRPC1 correlated with low overall survival in PDAC patients. However, the dysregulated expression of TRPC1 will remain controversial and seems to be cell type-specific, as the upregulation of TRPC1 appears to have a protective role in prostate [51,52] and some breast cancer patients [33]. Consistent with the increased TRPC1 mRNA expression, TRPC1 protein expression also significantly increased in human PDAC samples, where TRPC1 localizes to the plasma membrane, compared to adjacent non-tumor tissue, where it localizes in the cytoplasmic compartments.

In addition to expression in human tissue, TRPC1 has been shown to be upregulated in cancer cell lines compared to a corresponding non-cancerous cell line. For instance, TRPC1 is upregulated in breast cancer cell lines [33] and colorectal cancer cell lines [13]. To our knowledge, the expression of TRPC1 has not yet been evaluated in commercially-available PDAC cell lines compared to a duct-like control cell line. Interestingly, TRPC1 expression markedly increased in the more aggressive PDAC cell line PANC-1, and the cell line was the focus of the subsequent study. Remarkably, in PANC-1 cells, the localization of TRPC1 is in the cell membrane when compared to the HPNE cells, where TRPC1 seems to be located in the cytoplasm.

To investigate the role of TRPC1 in PDAC proliferation and growth, we performed loss of function experiments in 2D and 3D cell models. We found that TRPC1 silencing inhibited 2D cell proliferation and spheroid growth. The same effect has been found in neuroblastoma [22], glioblastoma [23], thyroid [24], breast [12,[25][26][27], lung, [28], liver [29,30], ovarian [31], and colon cancer [13]. This indicates that the upregulation of TRPC1 stimulates proliferation in several cancer types. Repressed cell proliferation is often associated with disruption of cell cycle progression by the dysregulation of cyclins and cyclin-dependent kinase (CDK) complexes [53]. In this study, the KD of TRPC1 accumulated cells in the G0/G1 phase reduced the number of cells in the S-phase and the expressions of CDK6, CDK2, Cyclin A, and increased p21 CIP1 expression. These proteins are essential in regulating progress through the G1/S phases of the cell cycle. Such a scenario has also been reported for other cancer cell models, for instance, in A549 lung cancer cells, where the KD of TRPC1 decreased the protein expression of Cyclin D1 and D3, leading to an increased number of cells in the G1 phase [28]. In addition, MCF-7 breast cancer cells accumulated in the G1 phase upon the KD of TRPC1 [12], which was also found in the thyroid cancer cell line ML-1, where the expression of the CDK6, Cyclin D2, and D3 decreased, and the expression of their regulating inhibitor p21 increased [24]. This indicates that TRPC1 is important for different cancer cell types to progress through the G1/S phases and that it is cell type-specific how CDK/Cyclin complexes regulate this progression.

The pathophysiological importance of TRPC1 in the plasma membrane is often associated with its role in Ca 2+ entry, as the Ca 2+ flux has been shown to be essential for tumor progression [11]. However, it is controversial whether TRPC1 regulates relevant cellular processes of tumorigenesis through Ca 2+ as several studies have shown that these events can be regulated by TRPC1 independently of Ca 2+ entry [13,24,30,[34][35][36]. Even though SOCE and constitutive Ca 2+ -entry have been shown to regulate cell proliferation through cell cycle progression, it is well accepted that transformed cells can proliferate independently from Ca 2+ -entry [5,7,13,24]. This is consistent with our findings, where the KD of TRPC1 did not affect Ca 2+ -entry, SOCE, which was slightly but not significantly increased, and the chelation of Ca 2+ had no effect on PANC-1 cell proliferation, suggesting that the PANC-1 cell and spheroid proliferation is Ca 2+ independent.

It is well known that the PI3K and MAPK signaling pathways play essential roles in cell proliferation and growth [54]. Inhibition of these proteins can lead to cell cycle arrest in PDAC cell lines [55]. Our findings show that KD of TRPC1 decreases the phosphorylation of AKT and, to a lesser extent, ERK1/2, which could explain the decrease of cell cycle regulating proteins and cell cycle arrest in the G1/S phases. This indicates that the PI3K signaling axis profoundly regulates PANC-1 cell proliferation through TRPC1. Hence, we investigated the physical interaction of TRPC1 and PI3K and its associated connecting protein CaM. It is known that TRPC channels can bind to CaM and thereby regulate physiological and pathophysiological processes [9]. In addition, CaM can bind to the PI3K p85↵ subunit, which removes its inhibitory effect on the catalytic subunit p110, and sequentially activates PI3K signaling [56]. The physical interaction between TRPC1 and PI3K has been shown to regulate myoblast differentiation [57], and only one other study besides ours shows the interaction between TRPC1, PI3K, and CaM [13]. However, a similar interaction of CaM and PI3K with TRPC6 has been found to regulate bovine aortic endothelial cell migration [58]. Here, we found that abolishing TRPC1 decreased the interaction between these proteins. As the phosphorylation of AKT was significantly reduced upon KD of TRPC1, our findings suggest that TRPC1 regulates PANC-1 cell proliferation by forming a complex with PI3K and CaM, thereby activating downstream signaling. However, some studies have shown that KD of TRPC1 decreased SOCE and thereby AKT phosphorylation in different cancer cell models [28,29]. Our results show that the phosphorylation of AKT seems to be Ca 2+ -independent. This finding is in congruence with other reports, where the KD of TRPC1 decreased the phosphorylation of AKT in a Ca 2+ -independent manner. For instance, in the PTEN deficient breast cancer cell line MDA-MB-468, TRPC1 silencing reduced the phosphorylation of AKT even though it slightly increased SOCE levels [36,47]. The same was found in some colorectal cancer cell lines, where it was proposed that TRPC1 regulated the PI3K/CaM/AKT axis independently of Ca 2+ [13].

In conclusion, we show for the first time that TRPC1 is upregulated in aggressive subtypes of PDAC patient tumor tissue and cell lines. TRPC1 regulates PDAC cell and spheroid proliferation through the direct interaction with the PI3K and CaM, thereby activating downstream signaling events implicated in G1 phase progression and G1/S transition, likely through a Ca 2+ -independent mechanism.

Materials and Methods

Public Database Analysis

TRPC1 mRNA expression was investigated by using online available datasets. Whisker boxplots of TRPC1 mRNA expression were generated using GEPIA2 ttp://gepia2.cancerpku.cn/, accessed on 1 June 2021) that compiles Genotype-Tissue Expression (GTEx) (http: //www.GTEXportal.org/, accessed on 1 June 2021), and The Cancer Genome Atlas (TCGA) (http://www.cancergenome.nih.gov/, accessed on 1 June 2021) datasets of normal and tumoral samples from different organs of interest, in our case pancreas and PDAC (PAAD). Survival analysis was performed using the SurvExpress online tool (available at http: //bioinformatica.mty.itesm.mx/SurvExpress, accessed on 2 March 2022), as previously described [59].

Immunohistochemistry in Human PDAC Samples

All experimental protocols were approved by the ethical committee of the University Hospital Center of Amiens (reference: PI2021_843_0027). Human tissue samples from PDAC patients were obtained and processed at the University Hospital Center of Amiens. Classical immunohistochemistry was performed from routinely processed formalin-fixed paraffin-embedded PDAC tumor material. First, 4 µM thick sections were deparaffinized in xylene and then rehydrated in ethanol. Then, the endogenous peroxidase activity was blocked before the antigen retrieval. The cell conditioning solution CC1 (BenchMark XT, Ventana, Rotkreuz, Switzerland) was used for antigen retrieval. Automatic immunohistochemical staining was carried out on a BenchMark ULTRA system (Ventana, Rotkreuz, Switzerland) using antibodies against TRPC1 (1/50, Abcam, Waltham, MA, USA). Next, the biotin-labeled secondary antibody was applied, followed by the addition of avidin-biotinperoxidase complex treatment. Reactions were developed using a chromogenic reaction with 3,3 0 -diaminobenzidine tetrahydrochloride (iVIEW DAB Detection Kit, Ventana). The tissue sections were counterstained with hematoxylin. The TRPC1 antibody was certified for immunohistochemical use by the manufacturer. Negative controls were performed with the same technique and conditions, without the addition of the primary antibody. Histological examination and quantitative evaluation were performed in cooperation with a pathologist (HS, PR), using a Leica inverted microscope. The marking intensity score ranged from 0 to 3 (0 = no immunostaining, 1 = weak immunostaining, 2 = moderate immunostaining, 3 = strong immunostaining). The TRPC1 localization was evaluated as a percentage in the cytoplasm or membrane.

Cell Culture

The hTERT-immortalized Human Pancreatic Nestin-Expressing cells (HPNE) were purchased from the American Type Culture Collection (ATCC, Molsheim, France). HPNE were grown in 75% DMEM without glucose (Sigma, Cat no. D-503, St. Louis, MO, USA), 25% Medium M3 Base (Incell Corp., San Antonio, TX, USA, Cat no. M300F-500), which were completed with 10% fetal bovine serum (Cat no. P30-3031, PAN Biotech, Aidenbach, Germany), 5.5 mM glucose and 750 ng/mL puromycin. Colo357, BxPC-3, AsPC-1, MIA PaCa-2, and PANC-1 cells were kindly provided by Prof. Anna Trauzold (Institute of Experimental Cancer Research, Kiel University, Kiel, Germany). These cell lines were grown in RPMI-1640 (Sigma-Aldrich, Cat no. R8758), supplemented with 10% fetal bovine serum (Cat no. P30-3031, PAN Biotech), 1 mM sodium pyruvate (Gibco, Waltham, MA, USA), and 1% Glutamax (Gibco). Cells were grown at 37 C, 95% humidity, 5% CO2, and passaged with trypsin-EDTA 0.25% (Sigma, Saint-Quentin-Fallavier, France) when cells reached a confluency of 70-80%. Cell cultures were not used for more than 20 passages.

Transient Transfections

Cells were transfected with small interfering RNA (siRNA) by electroporation using nucleofection (Amaxa Biosystems, Lonza, Aubergenville, France). PANC-1 cells (1⇥ 10 6 ) were transiently nucleofected according to the manufacturer's protocol with 4 µg of scrambled siRNA (siCTRL, duplex negative control, Eurogentec) or with siRNA directed against TRPC1, (siTRPC1, ON-TARGET plus SMART pool siRNA, Dharmacon Research, Chicago, IL, USA). All the experiments were performed 72 h after the siRNA transfection.

3D-Spheroid Growth and CellTiter Glo Assay

A total of 2000 transfected PANC-1 cells were seeded per well in round-bottomed, ultra-low attachment 96-well plates (Corning, NY, USA) in 200 µL growth medium, supplemented with 2% GelTrex LDEV-Free reduced growth factor basement membrane matrix (ThermoFisher Scientific, Waltham, MA, USA). Cells were subsequently spun down at 750 RCF for 20 min and were grown for 9 days at 37 C with 95% humidity and 5% CO 2 . 100 µL medium was exchanged every second day. Light microscopic images of the spheroids at 10⇥ magnification were acquired on days 2, 4, 7, and 9. On day 9, spheroids (in a replicate of 3) in 100 µL medium were transferred to a black 96-well plate where 100 µL CellTiter-Glo ® 3D Reagent (Promega, Madison, WI, USA) was added. The black plate was wrapped in aluminum foil, shaken for 5 min, and then incubated for 25 min at room temperature. The luminescence signal was recorded using a FLUOStar Optima microplate reader (BMG Labtech, Ortenberg, Germany).

Western Blot Analysis

Proteins were extracted and separated as previously described [60]. The primary antibodies used were: anti-TRPC1 (1:1000, Abcam, Waltham, MA, USA), anti-↵Tubulin (Sigma-Aldrich, France), anti-CDK6 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-Cyclin A (1:500, Santacruz Biotechnology, Dallas, TX, USA), anti-CDK2 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-p21 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-GAPDH (1:2000, Cell Signaling Tech., Danvers, MA, USA), anti-PI3K p85↵ (1:500, Bioworld Technology), and anti-Calmodulin (1:500, Santacruz Biotechnology, Dallas, TX, USA). Secondary antibodies were coupled to horseradish peroxidase, permitting protein detection with an enhanced chemiluminescence kit (Ozyme, Saint-Cyr-l'Ecole, France). Quantification was performed with the ImageJ analysis tool. All experiments were normalized to ↵-Tubulin or GAPDH, which were used as reference proteins.

Co-Immunoprecipitation

A total of 500 µg of proteins from non-transfected or transfected PANC-1 cells were used for co-immunoprecipitation with SureBeads™ Protein A Magnetic Beads (Biorad, France). First, the beads were washed thoroughly, as described in the manufacturer's protocol. Then 1 µg of either TRPC1 antibody (Abcam, Waltham, MA, USA) or PI3K p85↵ antibody was resuspended with the beads for 30 min. After another sequential washing step, protein lysates were added to the beads and slowly rotated for 2 h at room temperature. The beads were washed and eluted according to the manufacturer's protocol. After denaturation, proteins were used for a standard Western blot, as described above. For input, 50 µg of proteins from the corresponding co-immunoprecipitation samples were used.

Trypan Blue Assay

The 8 ⇥ 10 4 PANC-1 cells were seeded in 35 mm Petri-dishes for 72 h after siRNA transfection. Cells were washed in PBS, trypsinized, and diluted (1:5) in trypan blue solution (Sigma-Aldrich, France), then counted six times using the standard Malassez cell method. Proliferation was calculated as the total number of viable cells (cells alive/white cells), normalized to the control, and the mortality was calculated as the percentage of dead cells (blue cells), compared to the control. To test the effect of Ca 2+ on proliferation, the same procedure as described above was carried out, but after 24 h of seeding, the medium was changed to medium with standard conditions containing 1 mM Ca 2+ (referred to as conditions with Ca 2+ ) or containing Ethylene Glycol Tetraacetic Acid (EGTA), to chelate Ca 2+ and to end with a final concentration of 30 µM (referred to conditions without Ca 2+ ). Therefore, cells were transfected for 72 h, and Ca 2+ where chelated for 48 h.

Flow Cytometry

Flow cytometry was carried out on ethanol-fixed cells by a propidium iodide assay. Duplicates of 2 ⇥ 10 5 transfected PANC-1 cells were seeded in 60 mm Petri dishes and collected after 72 h. Cells were washed in PBS, trypsinized, collected in PBS + EDTA (5 mM), and fixed with cold absolute ethanol ( 99.8%, Sigma-Aldrich) for at least 6 h, at 4 C. Then, cells were pelleted, resuspended in PBS + EDTA (5 mM), treated with 20 µg/mL RNase A (Sigma-Aldrich) for 30 min at room temperature, and stained with 50 µg/mL of propidium iodide (Sigma-Aldrich, St. Quentin Fallavier, France). Samples were then analyzed by a flow cytometer (Accuri ® , Dominique Deutscher, Brumath, France), and the cell percentage in different phases was calculated using Cyflogic software and illustrated with FCS Express 7.

Calcium Imaging

Ca 2+ imaging acquisition was performed as previously described [61]. Briefly, 25 ⇥ 10 3 transfected PANC-1 cells were seeded on glass coverslips 72 h before each experiment. Then, cells were incubated with 3.33 µM Fura-2/AM (Sigma, Saint-Quentin-Fallavier, France) at 37 C in the dark for 45 min. Cells on the coverslip were washed twice with extracellular saline solution (145 mM NaCl, 5 mM KCl, 2 mM CaCl 2 , 1 mM MgCl 2 , 5 mM glucose, 10 mM HEPES, pH 7.4), and placed on the stage of a fluorescence microscope (Axiovert 200;Carl Zeiss,Oberkochen,Germany). Here, cells were excited at 340 and 380 nm using a monochromator (polychrome IV, TILL Photonics, Gräfelfing, Germany), and fluorescent emission was captured with a Cool SNAPHQ camera (Princeton Instruments, Lisses, France) after filtration through a long-pass filter (510 nm). Metafluor software (version 7.1.7.0, Molecular Devices, San Jose, CA, USA) was used for signal acquisition and data analysis. During acquisition, cells were continuously perfused with the saline solution. Store-operated Ca 2+ entry (SOCE) was triggered by applying the classical protocol, first by perfusing 2 mM Ca 2+ (for 1 min), then 0 mM Ca 2+ during 1 min followed by 1 µM thapsigargin in 0 mM Ca 2+ for Ca 2+ store depletion for 12 min, followed by perfusion of 2 mM Ca 2+ (for 5 min). The intracellular Ca 2+ concentration is derived from the ratio of emitted fluorescence intensities for each of the excitation wavelengths (F340/F380). To estimate divalent cation influx under basal conditions, we used the manganese (Mn 2+ ) quenching technique. After Fura2/AM loading, cells were washed and excited at 360 nm, where fluorescence was recorded at 510 nm. After 1.5 min, the Ca 2+ (2 mM) present in the saline solution was replaced by 2 mM Mn 2+ solution. The Mn 2+ quenching extracellular solution was composed of 145 mM NaCl, 5 mM KCl, 2 mM MnCl 2 , 1 mM MgCl 2 , 5 mM glucose, and 10 mM HEPES (pH 7.4). The Mn 2+ influx, a corroborate of the Ca 2+ influx, was estimated from the quenching rate of fluorescence at 360 nm by calculating the slope.

Immunofluorescence

The 8 ⇥ 10 4 non-transfected HPNE or PANC-1 cells were seeded on coverslips. After 48 h, cells were washed in cold PBS fixed for 20 min at room temperature in 4% paraformaldehyde (PFA, Sigma-Aldrich) and washed twice in PBS. Cells were permeabilized in 0.1% Triton TM X-100 (Sigma, Saint-Quentin-Fallavier, France) for 10 min and blocked in 5% Bovine Serum Albumin (BSA, Sigma Aldrich no. A7906) for 30 min. Primary antibodies (anti-TRPC1, 1:100, Santacruz Biotechnology, Dallas, TX, USA, NBCn1 was used as a membrane marker, 1:400, Abcam, Waltham, MA, USA) were added overnight at 4 C and secondary antibodies for 1 h at room temperature. Cells were treated with 4 0 ,6-diamidino-2-phenylindole (DAPI; 1%) for 5 min to stain nuclei, washed 3 times in 1% BSA, and mounted on slides using Prolong ® Gold antifade reagent. Images were collected on an Olympus Cell Vivo IX83 with a Yokogawa CSU-W1 confocal scanning unit. Z-stacks were deconvoluted in Olympus Cell Sens software using a constrained iterative algorithm. No or negligible labeling was seen in the absence of primary antibodies (data not shown). Overlays and brightness/contrast/background adjustments were carried out using ImageJ software.

Proximity Ligation Assay

The 8 ⇥ 10 4 transfected PANC-1 cells were seeded on coverslips 72 h before the proximity ligation assay (PLA) experiment. As described before [61], cells were washed with PBS and fixed with PFA (4%) at room temperature for 20 min. Thereafter, cells were washed and permeabilized with 0.1% Triton TM X-100 (Sigma, Saint-Quentin-Fallavier, France) for 10 min. The Duolink in situ PLA detection kit (Sigma-Aldrich, Saint-Quentin-

Supplemental Materials and Methods

Quantitative Real Time PCR (qRT PCR)

Total RNA was extracted with the Trizol reagent (Sigma, Saint Quentin Fallavier, France) method as previously described [60]. RNA concentration and purity were determined using a spectrophotometer (NanoDrop 2000, Wilmington, NC, USA). 2 g of RNA was converted into cDNA with the MultiScribe™ Reverse Transcriptase kit (Applied Biosystems, Carlsbad, CA, USA). Real time PCR was performed on a LightCycler 480 System (Roche, Basel, Switzerland) using SYBR Green I PCR master mix (Life Science, Roche, Basel, Switzerland), and sense and antisense PCR primers specific to TRPC1 (forward 5'GAGGTGATGGCGCTGAAGG 3' and reverse 5' GCACGCCAGCAAGAAAAGC 3') and B2M (forward 5'GTCTTTCAGCAAGGACTGGTC3' and reverse CAAATGCGGCATCTTCAAACC3'). TRPC1 mRNA expression was normalized to B2M, used as housekeeping gene, and compared to the control sample, using the Pfaffl method [62].

FACS analysis of annexin V and propidium iodide staining

To evaluate the percentage of apoptotic and necrotic cells, we detected phosphatidylserine residues at the outer plasma membrane by the FITC Annexin V Apoptosis Detection Kit I (BD Biosciences Pharmingen, Le Pont de Claix, France). 5 × 10 5 transfected PANC 1 cells were seeded, and collected after 72 h. Both detached and adherent cells were collected by trypsinization. Then the cells were pelleted, washed twice with ice cold PBS and resuspended in 1× binding buffer (BD Biosciences Pharmingen). Following the PE Annexin V Apoptosis Detection Kit staining protocol, we added FITC Annexin V and propidium iodide to the cell pellets and incubated them at 25°C in the dark for 15 min. Binding buffer was then added to each tube and samples were directly analysed by the flow cytometer (Accuri ® ) in order to determine the percentage of apoptotic cells.

Complementary results

We have shown that TRPC1 is highly expressed in PDAC tissue compared to adjacent tissue. Our complementary results revealed that patients with vascular and nerve tumor invasion and with overexpression of TRPC1 (n = 12/21) displayed an increased plasma membrane localization of TRPC1. This was not found in patients without vascular or nerve invasion, indicating that the plasma membrane localization of TRPC1 correlates with aggressiveness. is not constant but rather temporal and spatial, with some regions exhibiting near-neutral to neutral pH values, and other areas are highly acidic with a pH as low as pH 5.6 (Vaupel et al. 1989, Helmlinger et al. 1997, Rohani et al. 2019, Boedtkjer and Pedersen 2020). The effect of extracellular acidity depends on the duration and extent of acidity. Several studies have shown that a long-term acidic treatment selects for a more aggressive phenotype, as only cells that have adapted to the hostile microenvironment can survive and proliferate.

Interestingly, the acidic microenvironment renders the cancer cells more motile, invasive, and resistant to cytotoxic treatments. The acidic-induced selection is particularly of interest when the cancer cells encounter a less acidic or neutral microenvironment, as an increase in pHi can enhance proliferation (Flinck et al. 2018, Boedtkjer and Pedersen 2020, Andersen et al. 2021[START_REF] Elingaard-Larsen | How Reciprocal Interactions Between the Tumor Microenvironment and Ion Transport Proteins Drive Cancer Progression[END_REF].

Ion channels, often known as sensors of the surrounding microenvironment, can be affected by pHo changes and transduce the signal (Petho et al. 2020). Among ion channels is the TRPC1, known to be a mechanosensitive ion channel, for instance, by transducing signals from pressure and hypoxia (Fels et al. 2016, Azimi et al. 2017, Radoslavova et al. 2022). To date, it has not been shown how acidosis can affect TRPC1, but other TRPC channels are activated by acidification. As we have described that TRPC1 is overexpressed in human PDAC tissue and cell lines and how it regulates proliferation through the PI3K/CaM/AKT axis, we in the following study aimed to investigate how the fluctuating acidic tumor microenvironment could affect the function of TRPC1 and downstream mechanistic properties of PDAC.

To assess the influence of the fluctuating acidic tumor microenvironment, we developed a model where PANC-1 cells were grown in either normal conditions (pH 7.4), acid-adapted (30 days in pH 6.5), or in recovery conditions (cells adapted to pH 6.5 and reseeded for 14 days in pH 7.4).

Initially, our pHi measurements demonstrated that acid-adapted PANC-1 cells exhibit a lower pHi than cells grown in normal pH conditions. Further, acid-adapted cells measured in normal pHo conditions exhibited an even more alkaline pHi. Next, our western blot analysis, confocal imaging, and biotinylation assay demonstrated that acid adaptation decreased the total expression of TRPC1 but favored its plasma membrane localization. The TRPC1 expression was further increased and maintained in the plasma membrane in the recovery conditions.

We further showed that acid adaptation promoted PANC-1 cell migration but inhibited proliferation.

Interestingly, the proliferation was enhanced in recovery conditions in 2D and 3D models.

To demonstrate the role of TRPC1 in the acidic tumor microenvironment, we used the siRNA KD approach. We showed that TRPC1 KD inhibited PANC-1 cell migration in normal, acid-adapted, andrecovered conditions. Furthermore, we showed that silencing of TRPC1 strongly inhibited the proliferation of acid-recovered PANC-1 cells and spheroids, compared to the control, while this effect was less evident in acidadapted conditions.

We aimed to investigate the underlying mechanism of the tumor microenvironment and TRPC1 in PANC-1 cells. Our flow cytometric analysis revealed that acid adaptation resulted in an increased number of cells in the G0/G1 phase and a decreased number in the G2/M phase. Notably, the acid-recovered cells showed an increased number of cells in the S phase. The TRPC1 KD resulted in a further accumulation of cells in the G0/G1 phase and a reduction in the G2/M phase. This phenotype was maintained in acid-recovered conditions.

Along with the cell cycle analysis, our immunoblot analysis of cell cycle regulating proteins revealed that silencing of TRPC1 reduced the expression of CDK6, 2, and 1, and cyclin A while increasing the expression of p21. Notably, the TRPC1 KD had a more substantial effect in recovered conditions than in normal and acidic conditions.

As we previously have shown that TRPC1 forms a complex with PI3K and CaM, we aimed to demonstrate the role of the acidic tumor microenvironment and TRPC1 in association with PI3K signaling. Our confocal imaging and subsequent co-localization analysis showed that TRPC1 co-localized with the PI3K-p85α subunit in acid-adapted conditions, which was maintained upon recovery. These results were confirmed by PLA and co-IP, which revealed a strong interaction between TRPC1 and the PI3K-p85α subunit in acid-adapted PANC-1 cells. TRPC1 also interacted with the connecting protein CaM in all pH conditions. These interactions were attenuated upon TRPC1 silencing. Thus, we aimed to investigate the downstream effect of the interaction between TRPC1 and PI3K. We found that the activation of ERK1/2 was profoundly inhibited upon TRPC1 KD in both acidic and recovered conditions, compared to what we previously observed in normal pH conditions. Furthermore, the TRPC1 silencing also decreased the activation of AKT, particularly in acid-recovered conditions. Additionally, inhibition of CaM reduced the activation of AKT solely in acid-recovered cells, while ERK1/2 levels were affected in all conditions, but notably in acid-adapted and acid-recovered conditions.

Our Ca 2+ imaging assay revealed that basal Ca 2+ entry was increased in acid-recovered cells compared to cells grown in normal and acidic conditions. Furthermore, the TRPC1 KD only affected the Ca 2+ entry in acid-adapted and -recovered cells. TRPC1 silencing did not affect SOCE in either acid-adapted or recovered PANC-1 cells.

Given that TRPC1 could regulate the basal Ca 2+ , we finally investigated if extracellular Ca 2+ levels could influence cell migration and proliferation. Here, we found that low extracellular Ca 2+ levels decreased cell proliferation and migration solely in acid-adapted and -recovered conditions but not in normal pH conditions. In these conditions, TRPC1 KD slightly reduced migration and proliferation.

Taken together, these data revealed a novel insight into the interplay between the tumor microenvironment and the mechanosensitive ion channel TRPC1. We showed that the fluctuations of the tumor microenvironment translocate TRPC1 to the plasma membrane, favoring the interaction with PI3K/CaM and Ca 2+ entry that regulates PANC-1 migration and proliferation, both through the AKT and ERK1/2 axis (Figure 37).

Figure 37. (A) Acid adaptation promotes migration but attenuates proliferation, whereas acid recovery impairs this migration but further accelerates proliferation. (B) The fluctuations of the acidic tumor microenvironment affect TRPC1 expression and localization. TRPC1 is downregulated in acid-adapted PANC-1 cells but favors plasma membrane localization, which is maintained in acidrecovered PANC-1 cells, where the expression of TRPC1 is upregulated. In the plasma membrane of acid-adapted and -recovered conditions, TRPC1 permits Ca 2+ entry and, in interaction with the PI3K-p85α subunit and CaM, regulates PANC-1 cell migration, proliferation and cell cycle progression. (The figure is generated with www.Biorender.com.)

Simple Summary: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers globally, with a 5-year overall survival of less than 10%. The development and progression of PDAC are linked to its fluctuating acidic tumor microenvironment. Ion channels act as important sensors of this acidic tumor microenvironment. They transduce extracellular signals and regulate signaling pathways involved in all hallmarks of cancer. In this study, we evaluated the interplay between a pH-sensitive ion channel, the calcium (Ca 2+ ) channel transient receptor potential C1 (TRPC1), and three different stages of the tumor microenvironment, normal pH, acid adaptation, and acid recovery, and its impact on PDAC cell migration, proliferation, and cell cycle progression. In acid adaptation and recovery conditions, TRPC1 localizes to the plasma membrane, where it interacts with PI3K and calmodulin, and permits Ca 2+ entry, which results in downstream signaling, leading to proliferation and migration. Thus, TRPC1 exerts a more aggressive role after adaptation to the acidic tumor microenvironment.

Abstract: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a low overall survival rate of less than 10% and limited therapeutic options. Fluctuations in tumor microenvironment pH are a hallmark of PDAC development and progression. Many ion channels are bona fide cellular sensors of changes in pH. Yet, the interplay between the acidic tumor microenvironment and ion channel regulation in PDAC is poorly understood. In this study, we show that acid adaption increases PANC-1 cell migration but attenuates proliferation and spheroid growth, which are restored upon recovery. Moreover, acid adaptation and recovery conditions favor the plasma membrane localization of the pH-sensitive calcium (Ca 2+ ) channel transient receptor potential C1 (TRPC1), TRPC1-mediated Ca 2+ influx, channel interaction with the PI3K p85↵ subunit and calmodulin (CaM), and AKT and ERK1/2 activation. Knockdown (KD) of TRPC1 suppresses cell migration, proliferation, and spheroid growth, notably in acid-recovered cells. KD of TRPC1 causes the accumulation of cells in G0/G1 and G2/M phases, along with reduced expression of CDK6, 2, and 1, and cyclin A, and increased expression of p21 CIP1 . TRPC1 silencing decreases the basal Ca 2+ influx in acid-adapted and -recovered cells, but not in normal pH conditions, and Ca 2+ chelation reduces cell migration and proliferation solely in acid adaptation and recovery conditions. In conclusion, acid adaptation and recovery reinforce the involvement of TRPC1 in migration, proliferation, and cell cycle progression by permitting Ca 2+ entry and forming a complex with the PI3K p85↵ subunit and CaM.

Introduction

Pancreatic ductal adenocarcinoma (PDAC) accounts for up to 90% of pancreatic cancer incidences, and is the seventh leading cause of cancer-related deaths worldwide [1,2]. The poor prognosis of PDAC patients is mainly caused by late diagnosis, at a stage where the disease is often advanced, metastatic, and non-resectable [3,4]. The cytotoxic therapies available at present are modestly effective, and there is a compelling need to explore underlying PDAC development and progression mechanisms to develop better treatment options [3].

The development and progression of PDAC is linked to the physiology and microenvironment of the exocrine pancreas. Pancreatic epithelial and stromal cells are exposed to cyclic changes in the extracellular pH (pH o ) due to the production of alkaline pancreatic juices rich in HCO 3 . The apical exposure to this alkaline pH o is coupled to the parallel acidification of the basolateral membrane, leading to an acidic pancreatic interstitium [5,6]. Interestingly, extracellular acidification is one of the key characteristics of the tumor microenvironment, where it is caused by low perfusion in combination with high extrusion of H + from fermentative glycolysis and acid in the form of CO 2 from oxidative phosphorylation [7][8][9]. While the interstitial space of solid tumors is generally acidic, and pH o values as low as 5.6 have been measured, most values are in the range of 6.4-7. Where regions of the tumor with poor vascularization will typically be acidic, well-vascularized areas will exhibit a pH o closer to neutral [8,[10][11][12]. The intracellular pH (pH i ) is more alkaline than the pH o in tumors, yet cancer cells in an acidic microenvironment still exhibit an acidic pH i [13,14] compared to healthy cells in the normal pancreas.

Long-term acidosis acts as an evolutionary selection pressure. It causes adaptive responses that can establish cancer cell populations with more malignant phenotypes in the form of invasive and metastatic potential [8,[15][16][17]. In addition, acidosis limits proliferation by keeping the cancer cells in a dormant state [18]. This adaptation can be of particular impact once the cancer cells encounter a more neutral microenvironment, as an increase in pH i can further accelerate proliferation [8,9,19,20]. Changes in the pH can produce a multitude of cellular physiological effects, as numerous proteins are sensitive to pH in the range encountered in tumors [19][20][21]. Transmembrane proteins, such as ion channels, can function as pH sensors and transduce extracellular signals as changes in pH o [19,22]. They can potentially regulate signaling pathways related to all hallmarks of cancer by being affected by both pH o and pH i [19][20][21]. In recent years, the role of calcium (Ca 2+ ) channels as drivers of cancer mechanisms has been extensively investigated [23][24][25]. The transient receptor potential canonical (TRPC) channel subfamily represents a group of Ca 2+ -permeable non-selective cation channels [26]. Different physiochemical stimuli can activate their gating mechanisms and affect their expression, thus being categorized as cellular sensors [27]. The TRPC1 isoform is involved in various physiological and pathological processes [27,28] through different stimuli. For instance, the expression of TRPC1 increases and modulates proliferation and migration via hypoxia-induced signaling in breast and follicular thyroid cancer cells [29,30]. TRPC1 expression increases upon 24 h of pressure in pancreatic stellate cells (PSCs) [31,32]. The ambient pressure activates TRPC1 to form a complex with ↵ smooth muscle actin (↵SMA) and phosphorylated SMAD2. This physical interaction between TRPC1/↵SMA/SMAD2 is essential for activating two major pathways underlying PSC activation, namely ERK1/2 and SMAD2 pathways, resulting in IL-6 secretion and PSC proliferation [32]. Interestingly, the TRPC1 plasma membrane expression decreases upon PI3K inhibition in glioblastoma cells, which is associated with reduced chemotaxis and cell migration [33]. Although the response of TRPC1 to acidification has, to our knowledge, not been reported, other TRPC channels have been shown to Cancers 2022, 14, 4946 3 of 27 be affected by acidification [34]. For instance, TRPC4 and TRPC5 are activated by acidic pH in HEK293 cell models. TRPC4 is activated by acidic pH i (6.75-6.25), in combination with increased cytosolic Ca 2+ levels and G-protein-coupled receptor activation [35], while TRPC5 is activated both through G-protein activation and directly through protonation (pH 6.5) [36].

We have recently shown that TRPC1 is overexpressed in PDAC tissue and cell lines but does not regulate either basal Ca 2+ entry or store-operated Ca 2+ entry (SOCE). However, TRPC1 regulates PANC-1 cell proliferation by interacting with phosphoinositol-3-kinase (PI3K) and calmodulin (CaM) and regulating AKT signaling in normal pH conditions [37].

In the present study, we demonstrate the role of the fluctuating acidic tumor microenvironment and TRPC1 in PDAC cell migration, proliferation, and cell cycle progression. We showed that in acid-adapted PDAC cells, total TRPC1 expression decreased, but plasma membrane localization increased. In acid-recovered cells, TRPC1 expression increased, high plasma membrane localization of the channel was maintained, and Ca 2+ influx increased. As we have demonstrated before, TRPC1 formed a complex with PI3K/CaM, activating the downstream serine/threonine protein kinase AKT, but in this study, TRPC1 also activated the extracellular signal-regulated kinase 1 and 2 (ERK1/2) that synergically control cell migration, proliferation, and cell cycle progression, in acid adaptation and recovery conditions.

Materials and Methods

Cell Culture and Experimental pH Setup

The normal duct-like cell line human pancreatic nestin-expressing cells (HPNE), immortalized with hTERT, was purchased from the American Type Culture Collection (ATCC, Molsheim, France). HPNE were grown in 75% DMEM without glucose (Sigma-Aldrich, Saint-Quentin-Fallavier, France), 25% Medium M3 Base (Incell Corp. Cat#M300F-500), and 10% fetal bovine serum (Cat#P30-3031, PAN Biotech), 5.5 mM glucose, and 750 ng/mL Puromycin. The human PDAC cell line PANC-1 cells were kindly provided by Prof. Anna Trauzold (Institute of Experimental Cancer Research, Kiel University, Kiel, Germany). PANC-1 cells were cultured in RPMI-1640 medium already containing glucose (Sigma-Aldrich, Saint-Quentin-Fallavier, France) supplemented with 10% fetal bovine serum (Cat#P30-3031, PAN Biotech), 1 mM sodium pyruvate (Gibco, Waltham, MA, USA), and 1% Glutamax (Gibco). Cells were grown at 37 C, 95% humidity, 5% CO 2 , and passaged with trypsin-EDTA 0.25% (Sigma-Aldrich, Saint-Quentin-Fallavier, France) when cells reached a confluency of 70-80%. Cell cultures were not used for more than 20 passages. The medium pH was adapted to pH 6.5 by adjusting the HCO 3 concentration by adding the appropriate amount of NaHCO 3 and ensuring equal osmolarity by changing [NaCl] as suggested by Michl et al.,[38], and as performed previously by Flinck et al.,Yao et al.,. All cell lines were regularly tested for mycoplasma.

PANC-1 cells were thawed and grown under normal pH conditions (pH 7.4), then transferred to medium with pH 6.5, and maintained in this medium for a period of 30 days. These cells are referred to as acid-adapted cells (pH 6.5). The acid-adapted PANC-1 cells were then reseeded in a pH 7.4 medium for 14 days and are referred to as acid-recovered cells (pH 7.4R).

Live Imaging of Intracellular pH

As previously described, the pH i measurements of non-transfected PANC-1 cells were performed [41,42]. In detail, 8 ⇥ 10 4 cells were seeded in WillCo glass-bottom dishes WillCo Wells, Amsterdam, The Netherlands. After 48 h of seeding, cells were incubated in a growth medium containing 4 µM 2,7-bis-(2-carboxyethyl)-5-(and-6)-carboxyfluorescein acetoxymethyl ester (BCECF-AM, Invitrogen) for 30 min in the dark at 37 C, 95% humidity, 5% CO 2 . Cells were washed twice in HCO 3 containing Ringer solution; 115 mM (for pH 7.4) or 135 mM (for pH 6.5) NaCl, 24 mM (for pH 7.4) or 3 mM (for pH 6.5) NaHCO 3 , 5 mM KCl, 1 mM MgSO 4 , 1 mM Na 2 HPO 4 , 1 mM CaCl 2 , 3.3 mM 3-(-N-morpholino) propanesulfonic acid (MOPS), 3.3 mM 2 [Tris(hydroxymethyl)-methylamino]-ethanesulfonic acid (TES), 5 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), adjusted with NaOH or HCl to pH 7.4 or 6.5 at 37 C. Then, the cells in the glass-bottom dish containing Ringer solution adjusted to the respective pH were placed in a temperature-controlled compartment (37 C) equipped with gas. The steady-state pH i measurements were carried out using a Nikon Eclipse Ti microscope equipped with a Xenon lamp for fluorescence excitation, a 40⇥ oil 1.4 NA objective, and EasyRatioPro imaging software (PTI), for 10 min. Emission was measured at 520 nm after excitation at 440 nm and 485 nm. Calibration was carried out using the high K + /nigericin technique [43], employing KCl solutions (156 mM KCl, 1 mM MgSO 4 , 1 mM CaCl 2 , 1 mM K 2 HPO 4 , 3.3 mM MOPS, 3.3 mM TES, 5 mM HEPES) of pH 6.6, 7.0, 7.4, and 7.8, and 10 µM Nigericin (Sigma-Aldrich), which generated a fourpoint linear calibration curve to calibrate pH i values. Fluorescence measured from the two excitation channels (440 nm and 485 nm) was corrected for their respective background fluorescence during each experiment. The background fluorescence was assessed by measuring in a cell-free area during the experiment. The ratio 485 nm/440 nm was then calculated, and the calibration data were fitted to a linear function in the applied pH range. The experimental data were inserted and converted to corrected steady-state pH values.

Transient Transfections

Cells were transfected with small interfering RNA (siRNA) by electroporation using nucleofection (Amaxa Biosystems, Lonza, Aubergenville, France) as previously described [37]. Briefly, PANC-1 cells (1 ⇥ 10 6 ) grown under either normal pH, acid adaptation, or acid recovery conditions, were transiently nucleofected according to the manufacturer's protocol. To achieve this, 4 µg of scrambled siRNA (siCTRL, negative duplex control, Eurogentec) or siRNA directed against TRPC1 (siTRPC1, ON-TARGET plus SMART pool siRNA, Dharmacon Research, Chicago, IL, USA) were used. Experiments were performed 72 h after siRNA transfection unless otherwise indicated.

3D Spheroid Growth and CellTiter-Glo Assay

Non-transfected or transfected PANC-1 cells grown under either normal or acid adaptation conditions were formed into spheroids in their respective medium or in normal pH conditions following acid adaptation to simulate the 2D model of acid recovery conditions. In total, 2000 PANC-1 cells were seeded in round-bottomed, ultralow attachment 96-well plates (Corning, NY, USA) in 200 µL growth medium, supplemented with 2% GelTrex LDEV-Free reduced growth factor basement membrane matrix (Thermo Fisher Scientific, Waltham, MA, USA). After seeding, cells were spun down at 750 RCF for 20 min and were grown for 9 days at 37 C with 95% humidity and 5% CO 2 , and 100 µL of the respective pH medium was exchanged every second day. Light microscopic images of the spheroids at 10⇥ magnification were acquired on days 2, 4, 7, and 9. On day 9, PANC-1 spheroids, either non-transfected or transfected cells (in replicates of three) were transferred to a black 96-well plate with 100 µL of the respective pH medium and 100 µL CellTiter-Glo ® 3D Reagent (Promega, Madison, WI, USA). This plate was wrapped in aluminum foil, shaken for 5 min, and then incubated without shaking for 25 min at room temperature. The luminescence signal was recorded using a FLUOStar Optima microplate reader (BMG Labtech, Ortenberg, Germany).

Western Blot Analysis

Proteins were extracted, determined, and separated by the SDS-page technique as previously described [44]. The primary antibodies used were: anti-TRPC1 (1:1000, Abcam, Waltham, MA, USA), anti-GAPDH (1:2000, Cell Signaling Tech., Danvers, MA, USA), anti-CDK6 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-Cyclin A (1:500, Santacruz Biotechnology, Dallas, TX, USA), anti-CDK2 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-CDK1 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-p21 CIP1 (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-PI3K p85↵ (1:500, Bioworld Technology, tebu-bio, France), anti-calmodulin (1:500, Santacruz Biotechnology, Dallas, TX, USA), anti-pAKT (Ser473) (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-AKT (1:500, Cell Signaling Tech., Danvers, MA, USA), anti-pERK1/2 (Thr202/Tyr204) (1:500, Cell Signaling Tech., Danvers, MA, USA), and anti-ERK1/2 (1:500, Cell Signaling Tech., Danvers, MA, USA). Secondary antibodies (1:4000, Cell Signaling Tech., Danvers, MA, USA) were coupled to horseradish peroxidase, and proteins were detected using enhanced chemiluminescence (Ozyme, Saint-Cyr-l'Ecole, France). Quantification was performed with the ImageJ software 1.53a (National Institute of Health, Bethesda, MD, USA) analysis tool. All experiments were normalized to the level of GAPDH.

Cell Surface Biotinylation Assay

To determine the membrane fraction of TRPC1, 1 ⇥ 10 6 HPNE cells or 8 ⇥ 10 5 PANC-1 cells grown in normal pH, acid adaptation, or acid recovery conditions were seeded in 60 mm Petri dishes for 48 h and collected as previously described [45]. Briefly, cells were washed three times with cold PBS, then incubated with 3 mg of sulfo-NHS-SS-biotin (Thermo Fisher Scientific) and slightly shaken for 1 h at 4 C. The reaction was interrupted by the addition of cold PBS containing 10 mM glycine. Cells were scrapped with RIPA buffer, and ~10% of the total lysate was saved as the total lysate fraction. The remaining lysate portion (corresponding to the membrane fraction) was incubated with high-capacity streptavidin agarose beads (Thermo Fisher Scientific, Waltham, MA, USA) with gentle rotation overnight at 4 C. After incubation, beads were washed four times with RIPA buffer. Proteins were eluted from the beads with 50 µL of Laemmli buffer 2X and heated at 60 C for 30 min. Both total lysate samples and membrane fraction samples were used for Western blot analysis, as described above.

Co-Immunoprecipitation

The 6 ⇥ 10 5 non-transfected or 1 ⇥ 10 6 transfected PANC-1 cells grown in the three different pH conditions were seeded in 10 cm Petri dishes and collected after 72 h. As previously described [37], 500 µg of proteins were used for co-immunoprecipitation with SureBeads™ Protein A Magnetic Beads (Bio-Rad, France). Beads were washed thoroughly, according to the manufacturer's protocol. Then, 1 µg of either TRPC1 antibody (Abcam, Waltham, MA, USA), PI3K p85↵ antibody (Bioworld Technology, tebu-bio, France), or a control HRP-linked anti-rabbit IgG antibody (Cell Signaling Tech., Danvers, MA, USA) were resuspended with the beads for 30 min. Protein lysates were subsequently washed and added to the beads, which were slowly rotated for 2 h at room temperature. After another sequential washing step of the beads, proteins were eluted according to the manufacturer's protocol. After denaturation, proteins were subjected to Western blotting as described above. To detect the input, 50 µg of proteins from the corresponding co-immunoprecipitation samples were used.

Immunofluorescence Assay and Analysis

The 8 ⇥ 10 4 non-transfected PANC-1 cells, grown under the three different pH conditions, were seeded on coverslips for 48 h. Immunofluorescent staining was performed as previously described [37]. Briefly, cells were washed in cold PBS and fixed for 20 min at room temperature in 4% paraformaldehyde (PFA, Sigma, Saint-Quentin-Fallavier, France). Cells were washed twice in PBS and permeabilized in 0.1% Triton TM X-100 (Sigma, Saint-Quentin-Fallavier, France) for 10 min. Next, cells were blocked in 5% bovine serum albumin (BSA, Sigma, Saint-Quentin-Fallavier, France) for 30 min, followed by the addition of primary antibodies overnight at 4 C. The antibodies used were anti-TRPC1, (1:100, Santacruz Biotechnology, Dallas, TX, USA), with Na + /HCO 3 co-transporter (NBCn1) used as a membrane marker (1:400, Abcam, Waltham, MA, USA), and anti-PI3K p85↵ (1:100, Bioworld Technology, tebu-bio, France). Secondary antibodies (AlexaFluor ® 488/550 conjugated antibody 1:600) were applied for 1 h at room temperature, followed by treatment with 4 0 ,6-diamidino-2-phenylindole (DAPI; 1%) for 5 min to stain nuclei. Coverslips were washed three times and mounted on slides using Prolong ® Gold antifade reagent. Images were collected on an Olympus Cell Vivo IX83 with a Yokogawa CSU-W1 confocal scanning unit. Z-stacks were deconvoluted in Olympus Cell Sens software using a constrained iterative algorithm. No or negligible labeling was seen in the absence of primary antibodies. Overlays and brightness/contrast/background adjustments were carried out using ImageJ software. Mander's overlapping R coefficient was calculated using the ImageJ software plugin JACoP, which calculates the proportion of the green signal coincident with the magenta signal over the total intensity [46]. The threshold setting was the same for both images.

Boyden Chamber Assay

Cell migration was evaluated using a Boyden chamber assay with 8 µm pore size cell culture inserts (Falcon ® , Corning, Boulogne-Billancourt, France), as previously described [47]. Briefly, 4 ⇥ 10 4 non-transfected or transfected PANC-1 cells, grown under the three different pH conditions, were seeded in the upper compartment of the chamber. Both the upper and lower compartments were filled with the respective culture medium containing 10% FBS. After 24 h of incubation at 37 C, 95% humidity, and 5% CO 2 , inserts were washed in PBS and fixed in methanol for 15 min at room temperature, followed by staining with hematoxylin for 5 min. Inserts were washed in Milli-Q water and cleaned with a cotton swab; 20 adjacent fields were counted per insert at ⇥400 magnification. The number of migrating cells was normalized to their respective control (normal pH conditions (pH 7.4) for non-transfected PANC-1 cells and siCTRL in normal pH conditions (pH 7.4) for transfected PANC-1 cells). To ensure that there was no difference in viability between the conditions after 24 h, the trypan blue assay (as described below) was performed.

To investigate the effect of extracellular Ca 2+ concentrations on migration, we used the same Boyden chamber procedure as described above, but after 8 h of seeding, medium in the upper and lower chamber was changed to the respective medium, either with standard conditions containing 1 mM Ca 2+ (referred to as conditions with Ca 2+ ) or containing ethylene glycol tetraacetic acid (EGTA), to chelate Ca 2+ and to end with a final concentration of 30 µM (referred to conditions without Ca 2+ ). Thus, cells were transfected for 72 h, where Ca 2+ where chelated for 24 h in total during the migration process.

Trypan Blue Assay

Non-transfected (4 ⇥ 10 4 ) or transfected (8 ⇥ 10 4 ) PANC-1 cells were seeded in 35 mm Petri dishes. Subsequently, 24, 48, 72, or 96 h after seeding, cells were washed in PBS, trypsinized, and diluted (1:5) in trypan blue solution (Sigma, Saint-Quentin-Fallavier, France). All conditions were counted six times using the standard Malassez cell method. Proliferation was calculated as the total number of viable cells (alive/white cells) normalized to the control. As previously described, we tested the effect of extracellular Ca 2+ concentrations on proliferation [37]. Here, the same counting procedure as described above was carried out, but after 24 h of seeding, the medium was changed to medium with standard conditions containing 1 mM Ca 2+ (referred to as conditions with Ca 2+ ) or containing EGTA to chelate Ca 2+ and to end with a final concentration of 30 µM (referred to conditions without Ca 2+ ). Cells were transfected for 72 h, and Ca 2+ was chelated for 48 h.

Flow Cytometry

Flow cytometry was carried out as described previously [37]. Briefly, duplicates of 2 ⇥ 10 5 non-transfected or transfected PANC-1 cells were seeded in 60 mm Petri dishes and collected after 72 h. Cells were washed in PBS, trypsinized, and collected in PBS + EDTA (5 mM), followed by fixation with cold absolute ethanol ( 99.8%, Sigma, Saint-Quentin-Fallavier, France). Cells were kept at 4 C for at least 6 h post-fixation. To prepare for analysis, cells were pelleted, resuspended in PBS + EDTA (5 mM), treated with 20 µg/mL RNase A (Sigma-Aldrich, St. Quentin Fallavier, France) for 30 min at room temperature, and stained with 50 µg/mL of propidium iodide (Sigma-Aldrich, St. Quentin Fallavier, France). The cell cycle distribution of each sample was determined by flow cytometry analysis of nuclear DNA content using a flow cytometer (Accuri ® , Dominique Deutscher, Brumath, France). The cell percentage in different phases was calculated using Cyflogic software and illustrated with FCS Express 7.

Proximity Ligation Assay

The 8 ⇥ 10 4 non-transfected or transfected PANC-1 cells grown in one of the three pH media were seeded on coverslips 72 h before the proximity ligation assay (PLA) experiment. As described before [47], cells were washed twice with PBS, then fixed with PFA (4%) at room temperature for 20 min. Cells were washed twice in PBS and permeabilized with 0.1% TritonTM X-100 (Sigma, Saint-Quentin-Fallavier, France) for 10 min. The Duolink in situ PLA detection kit (Sigma-Aldrich, Saint-Quentin-Fallavier, France) was used to detect interactions between TRPC1 and the PI3K p85↵ subunit. Experiments were performed according to the manufacturer's protocol. Red fluorescent oligonucleotides produced as the end product of the procedure were visualized using the Zeiss Observer Z1 microscope 60X oil objective (Carl Zeiss, Oberkochen, Germany). Images were analyzed using ImageJ, where puncta per cell were counted and normalized to the respective control; normal pH conditions (pH 7.4) for non-transfected cells, and siCTRL in their respective medium (pH 6.5 or 7.4R). A total of 20 pictures per condition were captured and analyzed, and are presented as relative number puncta/cell.

Manganese Quench Assay

To estimate divalent cation influx under basal conditions, we used the manganese (Mn 2+ ) quenching technique as previously described [47]. Briefly, 25 ⇥ 10 3 transfected PANC-1 cells, grown under one of the three pH conditions, were seeded on glass coverslips for 72 h. At the beginning of each experiment, cells were incubated with 3.33 µM Fura-2/AM (Sigma, Saint-Quentin-Fallavier, France) at 37 C, 95% humidity, 5% CO 2 for 45 min in the dark. Cells on the coverslip were washed twice with extracellular saline solution (145 mM NaCl, 5 mM KCl, 2 mM CaCl 2 , 1 mM MgCl 2 , 5 mM glucose, 10 mM HEPES, pH 7.4 or pH 6.5), and placed on the stage of a fluorescence microscope (Axiovert 200; Carl Zeiss, Oberkochen, Germany). Cells were excited at 360 nm using a monochromator (polychrome IV, TILL Photonics, Gräfelfing, Germany), and fluorescent emission was captured with a Cool SNAPHQ camera (Princeton Instruments, Lisses, France) after filtration through a long-pass filter (510 nm). Metafluor software (version 7.1.7.0, Molecular Devices, San Jose, CA, USA) was used for signal acquisition and data analysis. After 1.5 min, the saline solution (including 2 mM Ca 2+ ) was replaced by 2 mM Mn 2+ solution by perfusion. The Mn 2+ quenching extracellular solution contains 145 mM NaCl, 5 mM KCl, 2 mM MnCl 2 , 1 mM MgCl 2 , 5 mM glucose, and 10 mM HEPES, and was adjusted with NaOH or HCl to pH 7.4 or 6.5. The Mn 2+ influx, a corroborate of Ca 2+ influx, was estimated from the quenching rate of fluorescence at 360 nm by calculating the slope.

Statistical Analysis

All data are shown as representative images or as mean measurements with standard error of means (SEM) error bars and represent at least three independent experiments. N refers to the number of independent experiments performed, or to the number of cells analyzed. Welch's correction t-test or Tukey's multiple comparison test was applied to test for statistically significant differences between two groups. *, **, and *** denotes p < 0.05, p < 0.01, and p < 0.001, respectively. All graphs and statistics were generated in GraphPad Prism 9.0 software (San Diego, CA, USA).

Results

Acid Adaptation Promotes Membrane Localization of TRPC1 in PANC-1 Cells

Before investigating the impact of the acidic tumor microenvironment on the growth and migration of PANC-1 cells, we studied the pH i values in different pH o conditions buffered with HCO 3 / CO 2 . We observed that PANC-1 cells grown in normal pH conditions

Cancers 2022, 14, 4946 8 of 27 (pH 7.4) exhibited a pH i of 7.3. This value decreased to 6.9 in acid-adapted cells (pH 6.5), and increased to 7.6 in acid-adapted cells measured at pH 7.4 (n = 6-11, p < 0.05, Figure 1A). Recently, we have shown an overexpression of TRPC1 in human PDAC tissue and the aggressive PANC-1 cell line [37]. Hence, we investigated the effect of the acidic tumor microenvironment on the expression and the localization of TRPC1 in PANC-1 cells. The protein levels of TRPC1 were significantly reduced by 37 ± 9% in acid-adapted PANC-1 cells compared to cells cultured in normal conditions (n = 3-4, p < 0.05, Figure 1B). Moreover, TRPC1 protein expression in acid-recovered PANC-1 cells (pH 7.4R) was significantly increased by 60 ± 16.9% compared to acid-adapted PANC-1 cells (n = 3-4, p < 0.05, Figure 1B). The protein levels of TRPC1 in spheroid PANC-1 cells grown in different pH conditions were comparable with those found in the 2D model (n = 3-5, p < 0.05, Figure 1C). Using surface biotinylation and confocal imaging, we found that TRPC1 was expressed in the plasma membrane of PANC-1 cells in all three pH conditions compared to a duct-like cell line HPNE. However, the membrane fraction was increased in the majority of acid-adapted cells (n = 3, Figure 1D,E). These results indicate that acid adaptation decreases the global expression of TRPC1, but favors its plasma membrane localization.

The Knockdown of TRPC1 Inhibits Cell Migration and the Growth of PANC-1 Cells and Spheroids under Acid Recovery Conditions

It is well known that the acidic tumor microenvironment can promote migration and slow down the proliferation of cancer cells [8,41,48,49]. First, we investigated the effect of pH on cell migration and viability. As expected, we found that acid-adapted PANC-1 cells migrated more than cells grown in normal pH and acid recovery conditions (75 ± 11.4%, n = 3, p < 0.001, Figure 2A), and showed a significant decrease in viability (25 ± 10.7% and 36 ± 6.3% for 72 h and 96 h of cell culture, respectively) when compared to cells cultured in pH 7.4 (n = 3, p < 0.05, Figure 2B). Similar results were found in PANC-1 spheroids (n = 4, p < 0.01, Figure 2C,D). Indeed, acid-adapted PANC-1 spheroids grown for 9 days displayed lower viability by 25 ± 4% and by 43 ± 4.8% compared to normal pH and recovery conditions, respectively (n = 4-5, p < 0.01, Figure 2C,D).

To investigate the role of TRPC1, we validated our knockdown (KD) model. In normal pH, TRPC1 protein expression was reduced by 44 ± 10% 72 h post-transfection [37] and by 46 ± 3% and 59 ± 6.6% in acid adaptation and recovery conditions, respectively (Figure S1C). Similar results were found at the transcriptional level after 48, 72, and 96 h (Figure S1A,B). Silencing of TRPC1 reduced cell migration by 25 ± 6.8% in normal pH, 43 ± 5.1% in acid adaptation, and 49 ± 3.7% in acid recovery conditions (n = 3-4, p < 0.05 and 0.001, Figure 3A). We did not observe a significant effect of TRPC1 KD on viability after 24 h of seeding (Figure S2A). KD of TRPC1 in PANC-1 cells in normal pH conditions inhibited cell proliferation by 48 ± 17.4% and 38 ± 17.6% after 72 and 96 h, respectively [37], and spheroid growth by 22 ± 2.3% [37]. KD of TRPC1 decreased the viability of acid-adapted and -recovered cells by 31.5 ± 12.2% (n = 3-4, p < 0.05, Figure 3B) and 33 ± 12%, respectively 72 h post-transfection (n = 5, p < 0.01, Figure 3C). In addition, the annexin-5 analysis did not show any significant effect on apoptosis or necrosis (Figure S2E,F). To investigate whether the acid adaptation and recovery emphasize the involvement of TRPC1 in spheroid growth, we developed a siRNA-based KD of TRPC1 in spheroids. First, we confirmed the KD of TRPC1 after 9 days, where TRPC1 protein levels were decreased by 27 ± 16% and 41 ± 8% in acid adaptation and recovery conditions, respectively (Figure S1D). This KD of TRPC1 significantly decreased the viability of spheroids by 38 ± 6.5% in acid recovery conditions (n = 3, p < 0.05, Figure 3D,E). However, the silencing of TRPC1 did not affect the viability of acid-adapted spheroids (n = 3, Figure 3D,E). These results indicate that TRPC1 contributes to cell migration and proliferation of PANC-1 cells considerably in acid recovery conditions. To investigate the mechanism by which pH and TRPC1 KD affect PANC-1 cell proliferation, we examined the cell cycle distribution by flow cytometry. First, we discovered that non-transfected cells grown in both acid adaptation and recovery conditions accumulated in the G0/G1 phase compared to cells cultured under normal pH conditions by 13.8 ± 4% and 10.7 ± 2.2%, respectively (n = 3, p < 0.01, Figure 4A). Furthermore, the number of cells in the S phase decreased significantly by 21 ± 6.4% in acid adaptation conditions. It increased significantly by 17 ± 5% in acid recovery conditions when compared to cells in normal pH conditions (n = 3, p < 0.01, Figure 4A). In the G2-M phase, the number of cells were decreased by 26 ± 5.8% and 26 ± 3.8% in acid adaptation and recovery conditions, respectively, compared to normal pH conditions (n = 3, p < 0.01 and 0.001, Figure 4A). These results indicate that acid adaptation of PANC-1 cells arrests them in the G0/G1 phase. In contrast, when they recover from this acid adaptation, they accumulate in the S phase and proliferate to a greater extent than cells grown in control conditions.

TRPC1 Strongly Modulates the Expression of CDKs and Cyclin A in Acid Adaptation and Recovery Conditions

In normal pH conditions, the KD of TRPC1 reduced the expression of CDK6, CDK2, and cyclin A and increased p21 CIP1 expression [37]. We investigated the effect of siTRPC1 In addition to the effect of pH, we investigated the role of TRPC1 in the cell cycle distribution in acid-adapted and -recovered cells. We have previously shown that silencing of TRPC1 accumulated cells grown in normal pH conditions in the G0/G1 phase and decreased the number of cells in the S phase [37]. Here, we show, in the acid adaptation conditions, that TRPC1 silencing resulted in a slight accumulation (10 ± 4.3%) of cells in the G0/G1 phase and a decrease in the number of cells in the G2/M phase by 17 ± 7.4% (n = 4, p < 0.05, Figure 4B). This profile was maintained upon TRPC1 KD in acid recovery conditions; with an increase in the number of cells by 9.4 ± 4% in the G0/G1 phase and a decrease of 15.1 ± 4% in the G2/M phase (n = 4, p < 0.05 and 0.01, Figure 4C). These results suggest that TRPC1 is involved in G0/G1 progression, regardless of the pH condition. Furthermore, the role of TRPC1 in cell cycle progression shifts from the S phase in normal pH conditions to the G2/M phase in acidic and recovery conditions.

TRPC1 Strongly Modulates the Expression of CDKs and Cyclin A in Acid Adaptation and Recovery Conditions

In normal pH conditions, the KD of TRPC1 reduced the expression of CDK6, CDK2, and cyclin A and increased p21 CIP1 expression [37]. We investigated the effect of siTRPC1 on the expression of these proteins in both acid-adapted and -recovered cells. Our immunoblot analysis showed that the expression of CDK6 and CDK2 was more affected in acid-adapted and -recovered cells depleted of TRPC1. CDK6 protein expression was decreased by 53 ± 5.3% and 73 ± 1.5% and CDK2 expression was decreased by 43 ± 1.3% and 70 ± 1.5% in acid-adapted (n = 3-4, p < 0.01 and 0.001, Figure 5A,B) and -recovered cells (n = 3-6, p < 0.05 and 0.01, Figure 5A,C), respectively. A similar profile was observed for cyclin A and p21 CIP1 expression. The expression of cyclin A was reduced by 45 ± 7.8% and 44 ± 4.2%, and the expression of p21 CIP1 was upregulated by 31% ± 6.2% and 34% ± 2.7%, in acid-adapted and -recovered cells, respectively (n = 4, p < 0.05 and 0.01, Figure 5A,E,F). The expression of CDK1, the regulator driving cells through the G2/M phase, was not affected by TRPC1 KD in normal pH conditions [37]. In this study, the silencing of TRPC1 decreased CDK1 expression by 20 ± 4.9% and 45 ±1.4% for cells grown in acid adaptation and recovery conditions, respectively (n = 3-5, p < 0.05, Figure 5A,D). Moreover, TRPC1 KD failed to affect the expression of cyclin B1, D1, D3, and E, along with CDK4 in both acid-adaptated and -recovered cells (Figure S3A). Collectively, these results suggest that the depletion of TRPC1 has a stronger effect on the expression of the cell cycle regulating proteins, CDK1, -2, and -6, cyclin A, and p21 CIP1 in acid-recovered PANC-1 cells than in normal pH and acid-adapted cells.

TRPC1 Interacts Strongly with the PI3K p85a Subunit and CaM under Acid Adaptation and Recovery Conditions

The PI3K signaling cascade is a regulator of cell cycle progression, as it activates transcription of cell cycle regulating proteins [50]. TRPC1 has been shown to be involved in activating the PI3K signaling pathway [30,33,51], and we have recently demonstrated that TRPC1 formed a complex with the PI3K p85↵ subunit and its associated connecting protein CaM, thereby regulating PANC-1 cell proliferation under normal pH conditions [37]. Thus, we aimed to investigate the role of the acidic tumor microenvironment and TRPC1 in association with PI3K signaling. Through confocal imaging, we found that TRPC1 also co-localized with the PI3K p85↵ subunit in acid-adapted PANC-1 cells, and that this was maintained under acid recovery conditions (Figure 6A). This co-localization was illustrated by the calculation of Mander's overlapping R coefficient, which was 0.13, 0.58, and 0.48 in normal pH, acid adaptation, and acid recovery conditions, respectively (Figure 6A). We further investigated the protein interaction between the PI3K p85↵ subunit and TRPC1. With PLA analysis, we found an increase in the proximity between the PI3K p85↵ subunit and TRPC1 in acid-adapted cells by 43.8 ± 5.6% and by 28 ± 7.2% in acid-recovered cells, compared to cells grown under normal pH conditions, respectively (n = 3, p < 0.01 and 0.001, Figure 6B,C). The proximity was decreased by 21 ± 6.7% in acid-recovered cells compared to acid-adapted cells (n = 3, p < 0.01, Figure 6B,C). The protein-protein interaction was then confirmed by co-IP analysis, where we found similar results with the pull-down of both TRPC1 and PI3K p85↵ (Figure 6D). In addition, we investigated the interaction between CaM and TRPC1. Indeed, CaM can function as a connecting protein between TRPC1 and the p85↵ subunit of PI3K [51]. We found that CaM interacted with TRPC1 and the PI3K p85↵ subunit in all three pH conditions (Figure 6D). To strengthen the indication of a complex between TRPC1, PI3K, and CaM, we first performed PLA analysis on PANC-1 cells upon the silencing of TRPC1. We observed that the protein interaction between the PI3K p85↵ subunit and TRPC1 was decreased by 50.7 ± 6.2% and 34.2 ± 8.0% under acid adaptation and recovery conditions, respectively (n = 3, p < 0.001, Figure 7A,B). Next, we determined the protein-protein interaction upon the KD of TRPC1 by co-IP. Compared to siCTRL conditions, the interaction between TRPC1 and the PI3K p85↵ subunit was significantly decreased in siTRPC1 conditions by 79.8 ± 8.5% and 47.2 ± 14.5% in acid-adapted and -recovered cells, respectively (n = 4, p < 0.05 and 0.01, Figure 7C,D). Furthermore, a significant decrease in protein-protein interaction by 40.3 ± 10.8% and 23.0 ± 6.0% was observed between TRPC1 and CaM in acid-adapted and -recovered cells, respectively (n = 4, p < 0.05 and 0.01, Figure 7C,E). Collectively, these results indicate that TRPC1 interacts strongly with the PI3K p85↵ subunit under acidic and recovery conditions, probably in assembly with CaM. In normal pH conditions, TRPC1 silencing regulates AKT to a greater extent than ERK1/2, with a decrease of 39 ± 7.8% and 13 ± 0.4%, respectively [37]. Hence, we investigated the effect of TRPC1 silencing on the phosphorylation of AKT and ERK1/2 in acid-adapted and -recovered cells. The KD of TRPC1 reduced the activation of AKT less in acid-adapted cells (27.4 ± 4.2%), and more in acid-recovered cells (48.0 ± 5.6%), when compared to normal pH (n = 4-5, p < 0.01, Figure 8A,B). Moreover, AKT total expression remained unchanged. Silencing of TRPC1 reduced the activation of ERK1/2 strongly in acid-adapted and -recovered cells when compared to pH 7.4 (32.0 ± 6.9% and 39.0 ± 10.7%), respectively, without affecting the total ERK1/2 protein expression (n = 4, p < 0.05, Figure 8C,D). Taken together, these results indicate that TRPC1 affects the activation of AKT to a greater extent in acid-recovered PANC-1 cells and ERK1/2 phosphorylation in both conditions.

Once we had established that TRPC1 and the PI3K p85↵ subunit interact with CaM, and that TRPC1 regulates AKT and ERK1/2 phosphorylation, we investigated whether the inhibition of CaM affected the downstream signaling protein kinases AKT and/or ERK1/2. Treatment of cells with the CaM inhibitor W7 for 72 h decreased the phosphorylation of AKT by 25 ± 6.8% in acid recovery conditions (n = 4, p < 0.05, Figure S4E). No significant decrease was found in normal pH or acid adaptation conditions (n = 3-4, Figure S4A,C). Furthermore, we found that the treatment with W7 decreased the phosphorylation of ERK1/2 by 23.8 ± 1.9%, 35.0 ± 10.5%, and 40.0 ± 6.0% in normal pH, acid adaptation, and acid recovery conditions, respectively (n = 4, p < 0.05 and 0.01, Figure S4B,D,F). These results indicate that CaM-dependent mechanisms regulate AKT solely in acid-recovered cells, while ERK1/2 levels are affected in all conditions and notably in acid-adapted and in acid-recovered PANC-1 cells.

PANC-1 Cell

Migration and Proliferation Depend Mainly on Extracellular Ca 2+ Entry, Likely through TRPC1, in Acid-Adapted and -Recovered PANC-1 Cells TRPC1 is not involved in SOCE, nor in basal Ca 2+ entry in normal pH conditions; instead, it regulates PANC-1 cell proliferation through a Ca 2+ -independent mechanism [37]. As TRPC1 was more localized at the plasma membrane in both acid-adapted and -recovered cells compared to control, we investigated whether TRPC1 participates in Ca 2+ entry in these conditions. First, we found an increase in Mn 2+ quenching in acid-recovered cells (34.7 ± 5.8% and 57 ± 6.2%), compared to cells grown in normal pH and acid adaptation conditions, respectively, (n = 150, 405, and 325, p < 0.01 and 0.001, Figure 9A-D). Furthermore, we found that KD of TRPC1 decreased Mn 2+ quenching by 60.2 ± 6.8% in acid-adapted cells (n = 5, p < 0.001, Figure 9B,D) and by 21.5 ± 6.8% in acid-recovered cells (n = 5, p < 0.01, Figure 9C,D), whereas no effect was observed in normal pH conditions (n = 3, Figure 9A,D). Moreover, TRPC1 KD elicited a decrease of 12.8 ± 2.4% in the basal Ca 2+ ratio in acid-adapted cells only (n = 3, p < 0.001, Figure S5A,B), and failed to affect SOCE in acid adaptation and recovery conditions (n = 4, respectively, Figure S5A,C-F).

Given the ability of TRPC1 to regulate basal Ca 2+ entry in acid-adapted and -recovered cells, and to understand whether Ca 2+ is involved in cell migration and proliferation, we cultured cells in normal and low Ca 2+ (30 µM free Ca 2+ ) medium. Cell migration decreased by 40 ± 3.7% and 34.2 ± 5.6% in acid-adapted and -recovered cells, respectively, in the low Ca 2+ medium (n = 3 and 4, p < 0.001, Figure 10B,C). KD of TRPC1 in this condition reduced migration additionally by 15.2 ± 4.7% and 12.5 ± 6.3% in acid-adapted and -recovered cells, respectively (n = 3 and 4, p < 0.001 and < 0.05, Figure 10B,C). Furthermore, no significant difference was found between the cell migration of siTRPC1 cells in normal Ca 2+ medium and in siCTRL cells in low Ca 2+ medium, indicating that TRPC1 mainly regulates PANC-1 cell migration in a Ca 2+ -dependent manner in acid adaptation conditions (n = 3, Figure 10B). In normal pH conditions, low Ca 2+ medium failed to affect cell migration, and silencing of Growth in low Ca 2+ medium for 48 h decreased cell proliferation by 24.1 ± 5.3% and 30 ± 3.5% in acid adaptation and recovery conditions, respectively (n = 4 and 5, p < 0.001, Figure 10D,E). Furthermore, in low Ca 2+ conditions, KD of TRPC1 decreased cell proliferation additionally by 16.2 ± 5.8% in acid-adapted and by 15.3 ± 4.9% in acid-recovered cells (n = 4 and 5, p < 0.01 and 0.001, Figure 10D,E). These results suggest that in acid-adapted and -recovered PANC-1 cells, proliferation and migration exhibit increased dependence on extracellular Ca 2+ levels. TRPC1 permits Ca 2+ entry, which regulates cell migration and proliferation by Ca 2+ -dependent and, to some extent, -independent mechanisms. Figure 10. The role of TRPC1 in PANC-1 cell migration and proliferation shifts from being Ca 2+independent in normal pH conditions to being substantially Ca 2+ -dependent in acid adaptation and recovery conditions. (A) Boyden chamber assay analysis of transfected PANC-1 cells grown in normal pH conditions, (B) in acid-adapted (6.5) conditions, or (C) in acid-recovered (7.4R) conditions. Cells were transfected for 72 h in total. After 48 h, cells were seeded in Boyden inserts for 8 h, and were then treated with medium containing extracellular Ca 2+ concentrations (+ Ca 2+ ), or with a medium depleted of extracellular Ca 2+ (-Ca 2+ ), for 24 h (n = 3). (D) Trypan blue assay analysis of transfected PANC-1 cells grown in acid-adapted (6.5) conditions or (E) in acid-recovered (7.4R) conditions. Cells were transfected for 72 h in total and either treated with medium containing extracellular Ca 2+ concentrations (+ Ca 2+ ), or with medium depleted of extracellular Ca 2+ (-Ca 2+ ), for 48 h (n = 3). Tukey's multiple comparison test was used to determine significant differences between conditions. ns indicates non-significance. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Discussion

Numerous studies have addressed the impact of TRPC1 dysregulation on hallmarks of cancer. However, the interplay between the acidic tumor microenvironment and TRPC1 expression and downstream mechanisms contributing to PDAC progression are unexplored.

Figure 10. The role of TRPC1 in PANC-1 cell migration and proliferation shifts from being Ca 2+ -independent in normal pH conditions to being substantially Ca 2+ -dependent in acid adaptation and recovery conditions. (A) Boyden chamber assay analysis of transfected PANC-1 cells grown in normal pH conditions, (B) in acid-adapted (6.5) conditions, or (C) in acid-recovered (7.4R) conditions. Cells were transfected for 72 h in total. After 48 h, cells were seeded in Boyden inserts for 8 h, and were then treated with medium containing extracellular Ca 2+ concentrations (+ Ca 2+ ), or with a medium depleted of extracellular Ca 2+ ( Ca 2+ ), for 24 h (n = 3). (D) Trypan blue assay analysis of transfected PANC-1 cells grown in acid-adapted (6.5) conditions or (E) in acid-recovered (7.4R) conditions. Cells were transfected for 72 h in total and either treated with medium containing extracellular Ca 2+ concentrations (+ Ca 2+ ), or with medium depleted of extracellular Ca 2+ ( Ca 2+ ), for 48 h (n = 3). Tukey's multiple comparison test was used to determine significant differences between conditions. ns indicates non-significance. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Discussion

Numerous studies have addressed the impact of TRPC1 dysregulation on hallmarks of cancer. However, the interplay between the acidic tumor microenvironment and TRPC1 expression and downstream mechanisms contributing to PDAC progression are unexplored.

The key findings of this study are: (i) The acidic tumor microenvironment promotes PDAC cell migration but attenuates proliferation, which is restored upon recovery. (ii) Acid adaptation reduces TRPC1 expression but favors its plasma membrane localization and its interaction with the PI3K p85↵ subunit and CaM. (iii) TRPC1 regulates acid-adapted and -recovered PANC-1 cell migration and proliferation by both Ca 2+ -dependent and -independent mechanisms. This likely occurs through the PI3K/CaM axis and the downstream activation of AKT and ERK1/2.

Acid adaptation creates an evolutionary selection pressure that contributes to a malignant phenotype [52,53]. Our results show that acid adaptation reduces PANC-1 cell viability and spheroid growth. In congruence with this, other studies have found the same events in different types of cancer cells [54][55][56], including PDAC cell lines [40,57,58]. Although acid adaptation is becoming of interest, not much is known about the recovery of and fluctuations in the acidic microenvironment. However, one study has shown that oral squamous cell carcinomas can restore their proliferation capacity after 7 and 21 days of acid treatments (pH 6.8) followed by 7 days of recovery (pH 7.4). To our knowledge, we are the first to show that 14 days of acid recovery restores PANC-1 proliferation rates, and that PANC-1 spheroid viability is enhanced after 9 days of recovery in normal pH conditions.

It is well accepted that proliferation and cell cycle progression depend on a permissive and slightly alkaline pH i [41,48]. Our results show that acid-adapted PANC-1 cells exposed to pH 7.4 exhibited a more alkaline pH i . The acid adaptation and recovery conditions led to the accumulation of cells in G0/G1 phases and decreased the number of cells in G2/M phases. Regarding the S phase, the number of cells was increased in the acid recovery conditions, suggesting that acid adaptation promotes a more alkaline pH i , which results in the improved cell proliferation of acid-recovered PANC-1 cells.

Moreover, long-term acidosis enhances extracellular matrix degradation that promotes cell migration and invasion [8,15]. Our findings are in congruence with previous reports showing that acid adaptation increased the migratory abilities of cancer cells, including PANC-1 cells [39,52,[54][55][56]59]. However, the cell migration was reduced upon recovery conditions to the same levels as for normal pH conditions. Similar results were found in prostate carcinoma cells, where acute acidosis (3 h) followed by 24 h of pH 7.4 treatment decreased cell motility [60]. In oral squamous carcinoma cells, no difference in cell migration was found between acid-adapted (21 days) and -recovered (7 days) conditions. However, after only 7 days of acid treatment and 7 days of recovery under normal conditions, cell migration increased [54]. In a mouse model of metastatic breast cancer, an increase in pH to 7.4 after acid adaptation led to reduced spontaneous metastases [61]. These results suggest that migratory properties of acid-recovered cells are cell type-specific and depend on the time of acidosis and recovery.

We recently demonstrated that TRPC1 does not contribute to Ca 2+ entry in PANC-1 cells grown under normal pH conditions [37]. Here, we show that there is a decrease in TRPC1 expression along with an increase in the plasma membrane fraction of TRPC1 in acid-adapted cells. In acid-recovered cells, the expression increased and increased plasma membrane localization of TRPC1 was maintained. In addition, TRPC1 was involved in Ca 2+ entry in acid adaptation and recovery conditions. Moreover, the Ca 2+ entry was increased upon acid recovery, indicating that PANC-1 cells grown in these conditions depend more on extracellular Ca 2+ concentrations. It is unknown whether TRPC1 expression and function are affected by changes in pH. However, acidic pH activates its homologs TRPC4 and TRPC5 [35,36], leading to Ca 2+ entry. In addition, other ion channels, transporters, and receptors can function as extracellular acid/base sensors, thereby increasing Ca 2+ concentrations [48,62]. Furthermore, it has been reported that TRPC1 plasma membrane levels are low when in an inactive form, and that the transfer and activation of the channel depends on Ca 2+ entry through ORAI1 and STIM1 [63,64]. Additional to other Ca 2+ channels, TRPC1 trafficking to the plasma membrane can depend on other membrane-bound proteins. For instance, the GTP-binding protein RhoA promotes the plasma membrane translocation [65] and activation of TRPC1, which leads to SOCE [66]. The interaction between RhoA and TRPC1 leads to cell migration of intestinal epithelial cells [66]. In a glioblastoma cell line, TRPC1 translocation to the plasma membrane depends on PI3K mediated transport, which results in Ca 2+ entry, chemotaxis, and cell migration [33]. We show that the interaction between TRPC1 and the PI3K p85↵ subunit/CaM was enhanced after acid adaptation. Thus, our results suggest that the acidic tumor microenvironment induces the trafficking of TRPC1 to the plasma membrane, likely in association with the PI3K p85↵ subunit and CaM, which are proteins near the plasma membrane. Here, TRPC1 promotes Ca 2+ entry, in acid adaptation and recovery conditions. However, the precise mechanism of TRPC1 trafficking upon acid adaptation and recovery needs further investigation.

TRPC1 regulates the cell cycle G1 and S phases, leading to PANC-1 cell proliferation in a Ca 2+ -independent manner [37]. In acidic and recovery conditions, we show that silencing of TRPC1 accumulated cells in the G0/G1 phases but decreased the number of cells in the G2/M phases. Remarkably, TRPC1 KD reduced the expression of CDK1, -2, -6, and cyclin A and increased the levels of p21 CIP1 excessively in acid recovery conditions compared to normal pH and acid adaptation conditions. In addition, TRPC1 KD inhibited PANC-1 cell proliferation and spheroid growth to a greater extent than in the two other conditions. This indicates that TRPC1 expression in acid recovery conditions is of more importance in cell proliferation and spheroid growth. Furthermore, the proliferation of PANC-1 cells in acidic and recovery conditions, contrary to normal pH conditions [37], depends on extracellular Ca 2+ levels, as the proliferation rate was decreased upon Ca 2+ chelation.

TRPC1 regulates the migratory properties of several cancer cell types, including PDAC cell lines [29,30,[67][68][69][70]. In this study, KD of TRPC1 decreased the migratory properties of PANC-1 cells in normal, acid-adapted, and acid-recovered PANC-1 cells. However, the decrease was more prominent in acid recovery conditions. The migration of PANC-1 cells highly depends on extracellular Ca 2+ solely in acid-adapted and -recovered cells, as cell migration decreased upon Ca 2+ chelation. Meanwhile, no effect was found under normal pH conditions. These results indicate that, as for proliferation, TRPC1 regulates cell migration in the acidic tumor microenvironment through Ca 2+ -dependent mechanisms.

TRPC1 forms a complex with the PI3K p85↵ subunit and the associated connecting protein CaM, and activates AKT and, to a lesser extent, ERK1/2 in normal pH conditions [37,51]. We report that TRPC1 strongly formed a complex with the PI3K p85↵ subunit, probably through CaM in acid-adapted and -recovered PANC-1 cells. This interaction was abolished upon the KD of TRPC1. Moreover, the silencing of TRPC1 resulted in a substantial decrease in AKT and ERK1/2 activation in acid-adapted and -recovered cells, which could result in the downregulation of cell-cycle-regulating proteins and, thereby, cell cycle arrest in the G0/G1 and G2/M phases. These results indicate that in these conditions, TRPC1 regulates proliferation and migration both through the PI3K and MAPK signaling axis, and that TRPC1 exerts a more aggressive role in acid-recovered PANC-1 cells.

AKT and ERK1/2 have previously been shown to be regulated through TRPC1 by Ca 2+ -dependent and -independent mechanisms. The activation of AKT depends on Ca 2+ through TRPC1 in lung cancer and hepatocellular carcinoma cell lines [71,72], and the activation of ERK1/2 depends on Ca 2+ through TRPC1 in thyroid and different breast cancer cell lines [29,73,74]. Here, the activation of AKT and ERK1/2 seemed to be regulated, at least partially, by Ca 2+ through TRPC1 in acid adaptation and recovery conditions. As TRPC1 forms a complex with PI3K p85↵ subunit and the Ca 2+ binding messenger CaM, we investigated whether the inhibition of CaM affected the activation of AKT and ERK1/2. This inhibition only decreased the activating phosphorylation of AKT in acid recovery conditions, where the activation of ERK1/2 was reduced in all conditions, but notably in acid-adapted and -recovered cells. Our results designate the importance of CaM and Ca 2+ downstream signaling in acid recovery conditions.

Interestingly, in more than 90% of PDAC tumors, the oncogene KRAS is mutated, and KRAS G12D is the predominant driver mutation in this type of adenocarcinoma [75]. Furthermore, KRAS is involved in reprogramming cell metabolism, including glucose metabolism, and the mutations are known to promote aerobic glycolysis (also known as the Warburg effect) [76]. The change in aerobic glycolysis in cancer cells is well known to produce waste products in the form of H + , causing increased proton extrusion and an acidic extracellular space. As TRPC1 can potentially regulate MAPK signaling cascades through KRAS in liver and colorectal cancer cells lines [51,77], it would be interesting to further investigate the interplay between TRPC1, KRAS, and the metabolic changes implicated in the acidification of the tumor microenvironment of PDAC.

Conclusions

In conclusion, we show that pH fluctuations in the tumor microenvironment affect PDAC cell migration, proliferation, and spheroid growth. We demonstrate that acid adaptation permits TRPC1 localization to the plasma membrane. Here, TRPC1 reinforces a complex with PI3K p85↵/CaM and promotes Ca 2+ entry. Synergically, this regulates AKT and ERK1/2 activation, which in turn controls cell cycle progression, proliferation, and migration. This indicates that the fluctuations in the acidic tumor microenvironment confer a more aggressive role to TRPC1 (Figure 11).

Cancers 2022, 14, 4946 27 of 31 Interestingly, in more than 90% of PDAC tumors, the oncogene KRAS is mutated, and KRAS G12D is the predominant driver mutation in this type of adenocarcinoma [75]. Furthermore, KRAS is involved in reprogramming cell metabolism, including glucose metabolism, and the mutations are known to promote aerobic glycolysis (also known as the Warburg effect) [76]. The change in aerobic glycolysis in cancer cells is well known to produce waste products in the form of H + , causing increased proton extrusion and an acidic extracellular space. As TRPC1 can potentially regulate MAPK signaling cascades through KRAS in liver and colorectal cancer cells lines [51,77], it would be interesting to further investigate the interplay between TRPC1, KRAS, and the metabolic changes implicated in the acidification of the tumor microenvironment of PDAC.

Conclusions

In conclusion, we show that pH fluctuations in the tumor microenvironment affect PDAC cell migration, proliferation, and spheroid growth. We demonstrate that acid adaptation permits TRPC1 localization to the plasma membrane. Here, TRPC1 reinforces a complex with PI3K p85α/CaM and promotes Ca 2+ entry. Synergically, this regulates AKT and ERK1/2 activation, which in turn controls cell cycle progression, proliferation, and migration. This indicates that the fluctuations in the acidic tumor microenvironment confer a more aggressive role to TRPC1 (Figure 11). Trypan blue assay performed in parallel with Boyden chamber assay (24 h after seeding). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions (n = 3-4). Ns indicates non-significant. (B) Trypan blue assay performed in parallel with Boyden chamber assay, with (+ Ca 2+ ) or without (-Ca 2+ ) calcium for 24 h in PANC-1 cells grown under normal pH conditions (7.4), (n = 3) (C) in acid-adapted (n = 4) or, (D) acid-recovered conditions (n = 3). Tukey's multiple comparison test was used to determine significant differences between conditions. Ns indicates non-significant. (E) Quantification of Annexin-5 analysis of cells in apoptosis or, (F) necrotic cells 72 h after transfection with siCTRL and siTRPC1 in acid-adapted (6.5) or acid-recovered (7.4R) PANC-1 cells (n = 3). Welch's correction t-test was used to determine the significant differences between siCTRL and siTRPC1 conditions. Ns indicates non-significant. Materials and methods for Annexin-5 analysis are described below. (A) phosphorlyated AKT (pAKT) and total AKT in normal conditions (7.4). (B) phosphorlyated ERK1/2 (pERK) and total ERK1/2 in normal conditions (7.4). (C) phosphorlyated AKT (pAKT) and total AKT in acid-adapted conditions (6.5). (D) phosphorlyated ERK1/2 (pERK) and total ERK1/2 in acid-adapted conditions (6.5). (E) phosphorlyated AKT (pAKT) and total AKT in acid-recovered conditions (7.4R). (F) phosphorlyated ERK1/2 (pERK) and total ERK1/2 in acid-recovered conditions (7.4R). (n = 3-4). Welch's correction t-test was used to determine the significant difference between conditions. Ns indicates non-significant. * and ** indicate p < 0.05 and 0.01, respectively.

Complementary results

TRPC1 silencing does not change the expression of other store-operated channels As we did not find any difference in SOCE in either pH 7.4, 6.5 or 7.4R conditions we investigated if other major SOC could compensate for the loss of TRPC1. However, our immunoblot analysis did not show any significant upregulation of either ORAI1, ORAI3, STIM1 or STIM2 but to some extend the same expression as the control conditions, indicating that the expression of these channels are not affected by TRPC1 silencing (Figure 38). Acid adaptation does not affect the transcriptional expression of other Ca 2+ channels Acidification has been shown to affect the function of several ion channels (Petho et al. 2020). For instance, acidification inhibits the function of ORAI channels and their activator, STIM1. Our study investigated the expression of different Ca 2+ channels in the aggressive PDAC cell lines PANC-1 and MiaPaCa-2. However, we did not find any significant difference in the mRNA expression of these ion channels (Figure 39), suggesting that even though the ion channels are functionally affected, their expression is not affected by acid adaptation. Acute acidification increases Ca 2+ entry through TRPC1 TRPC1 localizes to the plasma membrane in acid-adapted PANC-1 cells and regulates basal Ca 2+ entry here.

It has to our knowledge, not yet been shown if TRPC1 is functionally active upon acidification, as it has been shown for other TRPC channels. Thus, we aimed to investigate if acute acidification also could activate the Ca 2+ entry through TRPC1. Here, our Mn 2+ quench assay showed that PANC-1 cells grown in normal pH conditions (pH 7.4) display a higher Ca 2+ entry when exposed acutely to pH 6.5 by 16.8 ± 7.6% compared to cells exposed to pH 7.4 (Figure 40, n = 1). The Ca 2+ entry was abolished by 18.7 ± 6.3% upon TRPC1 KD in normal pH conditions, and by 59.2 ± 8.9% in pH 6.5 (Figure 40, n = 1) (Figure 40). These results suggest that TRPC1 activates Ca 2+ entry upon acute acidification.

The TRPC1 localization correlates with the acidic tumor microenvironment

We aimed to reveal the acidic tumor microenvironment in human PDAC tissue samples, with markers indicating acidity. We used two proteins that previously described the acidification of solid tumor microenvironments. The LAMP2 and the NBCn1 proteins. LAMP2 is highly expressed in more acidic regions The role of transmembrane proteins, including ion channels, in the healthy exocrine pancreas is well established. The ductal epithelial cells are, like other epithelia, well-organized. They are equipped with a highly polarized set of ion channels and transporters, which maintain the net bicarbonate excretion across the apical membrane, balanced by the net efflux of acid across the basolateral membrane to maintain their intracellular pH. Thus, the correct distribution of ion channels and transporters is vital to preserve the secreting function of the exocrine pancreas (Novak et al. 2013). However, it is well known that when epithelial cells transform into a malignant phenotype, they lose their apicobasal polarity, resulting in an altered localization of ion channels (Coradini et al. 2011, Pedersen andStock 2013). Until present, the role of ion channels in the exocrine pancreas and PDAC have not been described. Thus, we made a comprehensive literature study, summarizing the localization and function of ion channels involved in fluid secretion and their role in the development and progression of PDAC. Additionally, we outlined how different ion channels can be potential biomarkers of PDAC. This work was published as a review named 'Ion channel signature in healthy pancreas and pancreatic ductal adenocarcinoma' in Frontiers in Pharmacology.

In parallel with our literature study, we screened several ion channel expressions in PDAC cell lines, focusing on Ca 2+ channels, as presented here. Numerous studies have shown the implication of different Ca 2+ channels in cancer progression, including PDAC (Prevarskaya et al. 2007, Borowiec et al. 2014, Shapovalov et al. 2016[START_REF] Humeau | Calcium signaling and cell cycle: Progression or death[END_REF], Chen et al. 2019, Tajada and Villalobos 2020). We found that mRNA expression of Ca 2+ channels was upregulated in human PDAC tissue cell lines, compared to adjacent nontumor tissue and a normal-like control cell line. However, their expression profile in our local cohort of human PDAC tissue was less evident. Only two Ca 2+ channels were significantly upregulated in our study, ORAI3, and TRPC1, and both channels seemed to localize to the plasma membrane of tumor cells. Furthermore, our transcriptomic analysis showed that TRPC1 was highly upregulated in the aggressive PDAC cell line PANC-1, whereas ORAI3 was primarily upregulated in the less aggressive PDAC cell lines BxPC-3 and AsPC-1.

Interestingly, TP53 is mutated in these two cell lines, in contrast to the Colo357 cell line. Mutations in TP53 is known to results in the over expression of ORAI3 in other cancer cell types [START_REF] Hasna | Orai3 calcium channel and resistance to chemotherapy in breast cancer cells: the p53 connection[END_REF]. Furthermore, two recent reports have shown that ORAI3 was highly expressed in several PDAC cell lines [START_REF] Arora | Orai3 Regulates Pancreatic Cancer Metastasis by Encoding a Functional Store Operated Calcium Entry Channel[END_REF][START_REF] Dubois | ORAI3 silencing alters cell proliferation and promotes mitotic catastrophe and apoptosis in pancreatic adenocarcinoma[END_REF]. We showed that ORAI3 was upregulated at the transcriptomic level with our TCGA approach. Arora et al. showed the same upregulation of ORAI3 and that patients with a high expression of ORAI3 displayed shorter overall survival time; however, this was not significant.

There is strong evidence that TRPC1 is involved in other types of cancer progression (Elzamzamy et al. 2020). Yet, only one study before ours has shown the role of TRPC1 in BxPC-3 cell migration (Dong et al. 2010). Taking the sparse knowledge into account with our preliminary results, which indicated an upregulation of TRPC1 in PDAC cell lines and tissue, we, therefore, aimed to investigate the downstream role of TRPC1 in PDAC cell proliferation and as a potential biomarker of PDAC. We worked with TCGA data, human PDAC tissue from our local cohort, and the aggressive PANC-1 cell line to demonstrate this. The result obtained during this work was published in the article 'The TRPC1 channel forms a PI3K/CaM complex and regulates pancreatic ductal adenocarcinoma cell proliferation in a Ca 2+ -independent manner' in the International Journal of Molecular Sciences.

We further aimed to investigate the interplay between TRPC1 and the fluctuations of the acidic tumor microenvironment, which is now in revision as the article 'Acid adaptation promotes TRPC1 plasma membrane localization leading to pancreatic ductal adenocarcinoma cell proliferation and migration through Ca 2+ entry and interaction with PI3K/CaM' in Cancers.

TRPC1 is a potential biomarker of PDAC Several studies have demonstrated that TRPC1 is a potential biomarker of different kinds of cancer, including tongue, breast, gastric, ovarian, colorectal, and renal cell carcinoma (Mandavilli et al. 2012, Faouzi et al. 2016, Liu et al. 2016, Xu et al. 2017, Ibrahim et al. 2019, Zhang et al. 2020, Sun et al. 2021, Wang et al. 2021, Chen et al. 2022, Ke and Long 2022). As we have summarized in our review, other ion channels have shown to be potential biomarkers of PDAC. In congruence with previous studies, we showed that TRPC1 was upregulated in human PDAC tissue, notably in the basal-like subtype of PDAC. The high expression of TRPC1 correlated with low overall survival. Additionally, the localization of TRPC1 in the plasma membrane was associated with nerve and vascular invasion. It has previously been reported that the GTP-binding protein RhoA promotes the plasma membrane localization and activation of TRPC1-mediated Ca 2+ entry in pulmonary artery endothelial cells and intestinal epithelial cells (Mehta et al. 2003, Chung et al. 2015). TRPC1 translocation to the plasma membrane depends on PI3K mediated transport, leading to Ca 2+ entry, which promotes glioma cell migration (Lepannetier et al. 2016). Furthermore, TRPC1 levels are low in the plasma membrane when in an inactive form. The transfer and activation of the channels depend on STIM1 Ca 2+ entry through ORAI1 (Cheng et al. 2011, Ambudkar et al. 2017). Collectively, our results and previous reports indicate that TRPC1 exerts an aggressive role when located in the plasma membrane of PDAC tumor cells. One could speculate if this role is designated the interplay between the acidic tumor microenvironment of PDAC and TRPC1, as the plasma membrane location of TRPC1 correlated with the acidification marker LAMP2, which has previously been described to correlate with acidosis of breast cancer tissue and cell lines (Damaghi et al. 2015).

TRPC1 localizes to the plasma membrane and is functionally active solely in acid-adapted and -recovered

PANC-1 cells

As we demonstrated that TRPC1 is expressed in the cytoplasmic compartments of a normal-like duct cell line and non-tumor cells and translocate to the plasma membrane in PANC-1 and tumor cells of human PDAC tissue, we aimed to investigate how the localization was affected by the acidic tumor microenvironment. We found that the acid adaptation promoted the plasma membrane localization of TRPC1, which was maintained in acid-recovered conditions. The interaction between TRPC1 with other complexes, promotes its translocalization to the plasma membrane, as described above.

The enhanced TRPC1 plasma membrane localization resulted in Ca 2+ entry solely in acid-adapted and -recovered conditions, as TRPC1 did not contribute to Ca 2+ entry under normal pH conditions. This notion was supported by our Ca 2+ entry experiments, where PANC-1 cells grown in normal pH conditions were acutely exposed to acidosis, which resulted in a decreased Ca 2+ entry of 60% upon TRPC1 silencing. This effect was not found in normal pH conditions. These results indicate that TRPC1 is active upon acidification and leads to downstream mechanisms of Ca 2+ entry, both in acid-adapted and acid-recovered conditions. Even though it has not previously been described whether TRPC1 is activated by acidification, other TRPC channels as TRPC4 and TRPC5, are activated upon low pH values (~6.5) (Semtner et al. 2007, Thakur et al. 2020). Thus, one could speculate that TRPC1 can translocate to the plasma membrane, where it becomes active and lead to Ca 2+ entry. This could be due to its interaction with other ion channels, transporters, receptors or cytosolic proteins, which could also be affected by acidification and recovery.

TRPC1 regulates proliferation and migration through Ca 2+ -dependent mechanisms in acid-adapted andrecovered conditions

To investigate the interplay between TRPC1 and the fluctuations of the acidic tumor microenvironment, we initially demonstrated the effect of acid adaptation and recovery on PANC-1 cells. As previously described for other cell lines, acid adaptation inhibited PANC-1 cell proliferation (Shin et al. 2020, Hagelund and Trauzold 2022, Wu et al. 2022) and induced their migratory properties (Sutoo et al. 2020, Yao et al. 2020). However, we found that the proliferation and viability of acid-recovered cells and spheroids were enhanced. Along was the number of acid-recovered cells increased in the S-phase. Interestingly, the acid-adapted cells exhibited a more alkaline pHi when exposed to a neutral pH. Together, these results confirm that acid-adapted cells encountering a neutral microenvironment favors an increased pHi, resulting in enhanced proliferation (Flinck M et al. 2018, Flinck et al. 2018). Additionally, we showed an improved migration property of PANC-1 cells, which was decreased in recovery conditions to the same level as for normal pH conditions. The same effect has been demonstrated in other cell lines, where the motility of acid-induced cells increased for a short period upon exposure to pH 7.4 but decreased to lower levels than in acid-induced conditions after longer exposures (Robey et al. 2009, Riemann et al. 2014[START_REF] Riemann | Acidosis Promotes Metastasis Formation by Enhancing Tumor Cell Motility[END_REF], de Bem Prunes et al. 2022). These results suggest that the migratory properties are cell type-specific and depend on the duration of acidosis and recovery.

The role of TRPC1 in Ca 2+ entry is still under debate (Ambudkar et al. 2017, Elzamzamy et al. 2020).

However, the activation of TRPC1 seems to depend on cell type and microenvironmental conditions. Our group and others have shown that Ca 2+ entry through TRPC1 is activated upon ambient pressure leading to cell proliferation and migration of PSCs (Fels et al. 2016, Radoslavova et al. 2022). Furthermore, TRPC1 is overexpressed in hypoxic conditions where it regulates breast cancer cell migration through SOCE (Azimi et al. 2017). This study showed that silencing of TRPC1 did not affect constitutive Ca 2+ entry or SOCE under normal pH conditions. Additionally, the depletion of the extracellular Ca 2+ did not affect either PANC-1 cell proliferation or migration. These results are in congruence with previous studies, showing that TRPC1 regulates cellular processes independently of Ca 2+ entry (Davis et al. 2012, Madsen et al. 2012, Asghar et al. 2015, Selli et al. 2015, Selli et al. 2016, Sun et al. 2021). It is also in congruence with the literature, describing that transformed cells can proliferate in the absence of Ca 2+ and that the downregulation of several ion channels has no effect on Ca 2+ entry but attenuates proliferation (Capiod 2013, Borowiec et al. 2014). This designates the Ca 2+ -independent role of TRPC1 in normal pH conditions.

Interestingly, TRPC1 regulates constitutive Ca 2+ entry, but not SOCE, in acid-adapted and recovered PANC-1 cells. We aimed to investigate if other SOC was responsible for compensating for the loss of TRPC1.

However, our results did not show any clear picture of an upregulation of other Ca 2+ channels, indicating that other channels could compensate for the loss of TRPC1 during SOCE.

Indeed, our results suggest that TRPC1 is activated upon acidic conditions leading to Ca 2+ entry.

Additionally, PANC-1 cell proliferation and migration were reduced upon Ca 2+ depletion in acid-adapted and -recovered conditions. Together with its translocation to the membrane, these results designate that TRPC1 becomes active in acid-adapted and -recovered cells where it regulates proliferation and migration also via a Ca 2+ -dependent mechanism.

TRPC1 regulates proliferation and migration through the PI3K/AKT and MAPK/ERK1/2 axis in acidrecovered conditions

We showed that TRPC1 regulated proliferation and migration through PI3K/AKT and MAPK/ERK1/2, particularly in acid-recovered PANC-1 cells. TRPC1 strongly interacted with the PI3K-p85α subunit, which removes its inhibitory effect on the catalytic subunit p110 and sequentially activates downstream PI3K

signaling (Nussinov et al. 2017). The interaction between TRPC1 and the PI3K-p85α subunit was enhanced in acid-adapted cells, and maintained in acid-recovered conditions. The silencing of TRPC1 resulted in potent inhibition of AKT and ERK1/2 phosphorylation in acid-adapted and recovered cells. This inhibition explains the downregulation of cell cycle regulating proteins and cell cycle arrest in the G0/G1 and G2/M phases.

TRPC1 KD affected ERK1/2 phosphorylation to less extent in normal pH conditions, which was more evident in acidic and recovered conditions, indicating that TRPC1 regulates cell proliferation and migration through the PI3K and MAPK signaling axis and exerts a more aggressive role in acid-recovered PANC-1 cells.

As TRPC1 forms a complex with the Ca 2+ binding protein CaM in all pH conditions, we investigated whether the inhibition of CaM, which is activated by Ca 2+ , affected the downstream signaling pathways AKT and ERK1/2. Here, we revealed that this inhibition decreased the activation of AKT solely in acid-recovered PANC-1 cells. The activation of ERK1/2 was reduced in all conditions but to a greater extent in acid-adapted and -recovered cells. This designates the role of CaM and Ca 2+ downstream signaling, notably in acid-adapted and -recovered conditions.

Taken together, this study shows that TRPC1 is upregulated in human PDAC tissue and cell lines. Its total expression is downregulated upon acid adaptation, but favors a localization in the plasma membrane.

Acid-recovery restores the total expression of TRPC1 and maintains the expression in the plasma membrane.

In acid-adapted and -recovered conditions, TRPC1 forms a complex with PI3K and CaM, and enhances Ca 2+ entry, which regulates AKT and ERK1/2 activation. This activation of the PI3K/AKT and MAPK/ERK1/2 signaling control cell cycle progression, proliferation and migration, notably in the acid-recovered conditions.

The acidic microenvironment affects the DNA methylation of ion channels

Introduction

The term 'epigenetics' was described by C.H. Waddington in the 1940s and addressed as: 'the branch of biology which studies the causal interactions between genes and their products, which bring the phenotype into being' [START_REF] Waddington | The evolution of an evolutionist[END_REF]. Since then, implications of epigenetic changes have been extended in a wide range of biological processes, and accumulating evidence suggested that heritable changes in the genome can occur independently of alterations in somatic cells regardless of their differentiation status [START_REF] Bird | Perceptions of epigenetics[END_REF]. The heritable changes require fine-tuned epigenetic modifications, including DNA methylation, histone or chromatin post-translational modifications, and non-coding RNA regulations. If the fine-tuning of epigenetic modifications fails, it may cause inappropriate initiation or inhibition of gene expression, which leads to pathological changes, such as cancers (Jones andBaylin 2002, Egger et al. 2004).

Cancer is a consequence of genomic mutations, epigenetic alterations, and environmental factors [START_REF] Easwaran | Cancer epigenetics: tumor heterogeneity, plasticity of stemlike states, and drug resistance[END_REF]. Numerous studies have characterized the genomic landscape of cancers from oncogene-driven signaling to the mutation spectrum of different cancer types. Epigenetic changes differ from genomic changes as they modify gene expression without permanent changes in the genomic sequence [START_REF] Easwaran | Cancer epigenetics: tumor heterogeneity, plasticity of stemlike states, and drug resistance[END_REF]). These changes favor cancer cells as epigenetic alterations are reversible and faster regulated than genomic evolution. Except for the traditional changes that occur to somatic cells upon malignant transformation, multiple forces shape the landscape of cancer, including the tumor microenvironment. Current epigenetic modifications investigations are focused on the progress of cancer cell development and the interaction between the tumor microenvironment and cancer cells [START_REF] Lu | Epigenetic regulation in human cancer: the potential role of epidrug in cancer therapy[END_REF].

DNA methylation patterns in PDAC

DNA methylation is the most extensively studied epigenetic modification and displays a fundamental function in development and diseases, including embryonic development, genomic imprinting, cell identity establishment, lineage specification, and X chromosome deactivation [START_REF] Bird | CpG-rich islands and the function of DNA methylation[END_REF][START_REF] Gopalakrishnan | DNA methylation in development and human disease[END_REF][START_REF] Lister | Human DNA methylomes at base resolution show widespread epigenomic differences[END_REF], Zhang et al. 2020). DNA methylation appears by the covalent binding of a methyl group from S-adenosylmethionine to the 5' position of the cytosine pyrimidine ring. These methylations often occur in cytosine-phosphate-guanine (CpG) rich regions (also known as CpG islands), particularly concentrated in the promoter region of many genes. The binding of the methyl group can either prevent the access of transcription factors to the binding sites of DNA or recruit methyl-binding domain proteins, combined with histone modifications to rearrange the chromatin structure, leading to repressive gene expression (Issa 2004, Kanwal and[START_REF] Kanwal | Epigenetic modifications in cancer[END_REF].

The enzymes, namely the DNA methyltransferases (DNMT) 1, 3a, and 3b, are orchestrated to catalyze adding the methyl group to the DNA [START_REF] Bestor | The DNA methyltransferases of mammals[END_REF]. The DNMT1 is responsible for maintaining methylation patterns of the parental DNA strand to the newly synthesized daughter strand [START_REF] Pradhan | Recombinant human DNA (cytosine-5) methyltransferase. I. Expression, purification, and comparison of de novo and maintenance methylation[END_REF][START_REF] Bestor | The DNA methyltransferases of mammals[END_REF]. DNMT3a and 3b are thought to be responsible for applying de novo methyl groups to the DNA. In contrast, demethylation is the reverse action that recovers silenced genes [START_REF] Okano | DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development[END_REF]. The enzyme family Ten-eleven translocation methylcytosine dioxygenases (TET) can turn the 5-methylcytosine (m5C) into 5-hydroxymethylcytosine (5hmC). The homeostasis between methylation and demethylation of the genome occurs as a dynamic mechanism of gene expression regulation [START_REF] Tahiliani | Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1[END_REF][START_REF] Scourzic | TET proteins and the control of cytosine demethylation in cancer[END_REF].

The extensive addition or removal of methyl groups from the DNA is referred to as hypermethylation or hypomethylation.

In PDAC, DNA methylation is a well-known mechanism to inactivate tumor suppressor genes.

Specifically, the inactivation of the promoter region by methylation of the CDK2A/p16 tumor suppressor gene has been established. As described in cell cycle progression, the p16 protein (a CKI) inhibits the binding of cyclin D to their dependent kinases CDK4 and 6, and the loss of the p16 protein can result in increased phosphorylation of Rb and a subsequent progression through the G1 and S phase. It has been shown that this hypermethylation of CDKN2A/p16 occurs in the early stages of PDAC [START_REF] Fukushima | Aberrant methylation of preproenkephalin and p16 genes in pancreatic intraepithelial neoplasia and pancreatic ductal adenocarcinoma[END_REF]. PanIN lesions of patients with chronic pancreatitis show a loss of p16 expression, suggesting that this alteration may contribute to PDAC development [START_REF] Rosty | p16 Inactivation in pancreatic intraepithelial neoplasias (PanINs) arising in patients with chronic pancreatitis[END_REF]. Methylation of the CpG islands of the CDKN2A/p16

gene is one of the most common mechanisms to silence p16 in PDAC, emphasizing the significance of this epigenetic mechanism in modulating tumor progression in PDAC [START_REF] Schutte | Abrogation of the Rb/p16 tumor-suppressive pathway in virtually all pancreatic carcinomas[END_REF][START_REF] Wilentz | Inactivation of the p16 (INK4A) tumor-suppressor gene in pancreatic duct lesions: loss of intranuclear expression[END_REF][START_REF] Fukushima | Aberrant methylation of preproenkephalin and p16 genes in pancreatic intraepithelial neoplasia and pancreatic ductal adenocarcinoma[END_REF]. Other genes promoting PDAC progression have also been identified as hypermethylated [START_REF] Zhang | Analysis of Methylation-driven Genes in Pancreatic Ductal Adenocarcinoma for Predicting Prognosis[END_REF]. On the contrary, several genes have shown to be hypomethylated in PDAC, including CCND1 and 3 (coding for cyclin D1 and 3) and S100A4 and S100P (calcium-binding protein), which are proteins involved in cell cycle progression, and cell motility and invasion [START_REF] Bararia | Differential methylation landscape of pancreatic ductal adenocarcinoma and its precancerous lesions[END_REF].

Interestingly, the expression of several types of ion channels is regulated by methylation in a wide range of cancers [START_REF] Ouadid-Ahidouch | DNA methylation of channel-related genes in cancers[END_REF]. Regarding PDAC, different genes encoding ion channels are associated with DNA methylation. Two voltage-gated ion channels have shown to be hypermethylated.

Namely, the CACNA1 gene, coding for the CaV3.1 channel, was hypermethylated in 16% of PDAC tumors [START_REF] Ueki | Hypermethylation of multiple genes in pancreatic adenocarcinoma[END_REF]. The KCNA3 gene promoter (voltage-gated potassium channel, Kv1.3) was hypermethylated, and its expression was decreased in 69.7% of PDAC tumors. Furthermore, this hypermethylation was associated with low overall survival (Brevet et al. 2009). A recent study exploring the genome-wide DNA methylation profile of PDAC tumors compared to non-tumor tissues showed that different actors of Ca 2+

signaling were associated with methylation patterns [START_REF] Gregorio | Calcium Signaling Alterations Caused by Epigenetic Mechanisms in Pancreatic Cancer: From Early Markers to Prognostic Impact[END_REF]. They observed that Ca 2+ signaling pathways had a large number of genes significantly hypo-and hypermethylated. Interestingly, the ORAI2 gene promoter was hypomethylated, associated with an increased expression. Furthermore, this expression correlated with better overall survival [START_REF] Gregorio | Calcium Signaling Alterations Caused by Epigenetic Mechanisms in Pancreatic Cancer: From Early Markers to Prognostic Impact[END_REF]. In another study, investigating the DNA methylome of PDAC samples and from the TCGA cohort, authors found hypermethylation of CACNB2

(coding for the Voltage-dependent L-type calcium channel subunit beta-2), KCNA6 (Kv1.6) and KCNA3, as previously described [START_REF] Chatterjee | Altered DNA methylation in ion transport and immune signalling genes is associated with severity in Pancreatic Ductal Adenocarcinoma[END_REF].

Changes in pH are a reciprocal concept concerning genomic stability. As described in the section 'Cellular adaptation to extracellular acidosis in carcinogenesis', changes in intracellular pH greatly affect genomic stability. These changes in pHi can be due to changes in pHo. Still, they can also be created by the cells' biodynamics, as many genetic and epigenetic alterations exert their function by altering the metabolism in cancer cells, causing changes in pH [START_REF] Ordway | Causes and Consequences of Variable Tumor Cell Metabolism on Heritable Modifications and Tumor Evolution[END_REF].

However, it is not well known how acidification directly affects epigenetic changes. The concept of histone acetylation is better described in terms of acidification. Acidification can affect gene expression by changing mRNA stability, and influence the stability of DNA binding proteins by changing their protein-protein and protein-DNA complex affinities, for instance, transcription factors such as AP-1, NFκB, and Sp1 (Xu andFidler 2000, Torigoe et al. 2003). Sp1 binds CpG sites, protecting specific regions from methylation, and is activated by increasing acidity [START_REF] Torigoe | Low pH enhances Sp1 DNA binding activity and interaction with TBP[END_REF].

Acidification can disrupt the oligomerization of DNMT3A, decreasing its catalytic activity. This could potentially result in specific gene promoter hypomethylation and, thus, an upregulation of oncogenes (Holz-Schietinger and Reich 2015).

How acid adaptation affects DNA methylation levels of ion channel promoter regions, and thus gene expression, has to our knowledge, never been studied before. In the following chapter, we aimed to reveal how acid adaptation could affect gene promoter methylation of, specifically, ASIC1, SCN8A (coding for the sodium voltage-gated channel alpha subunit 8, NaV1.6), and TRPC1.

• VGSC/NaV channels Voltage-gated sodium channels (NaV channels) allow the permeability of Na + across the membrane. They are comprised of nine α subunit isoforms (NaV1.1-1.9) and four β subunits (β1-4) and are encoded by SCN_A/B genes (de Lera [START_REF] De Lera Ruiz | Voltage-Gated Sodium Channels: Structure, Function, Pharmacology, and Clinical Indications[END_REF]. NaV channels are known as critical proteins for the initiation of the action potential [START_REF] Catterall | From ionic currents to molecular mechanisms: the structure and function of voltagegated sodium channels[END_REF]. It has been shown that a high membrane potential can facilitate the proliferation of cells, which is believed to be associated with the initiation of DNA synthesis and mitosis (Orr et al. 1972, Binggeli and[START_REF] Binggeli | Membrane potentials and sodium channels: hypotheses for growth regulation and cancer formation based on changes in sodium channels and gap junctions[END_REF]. Cancer cells often have a higher membrane potential than their normal counterparts, which might be associated with their rapid proliferation [START_REF] Yang | Membrane potential and cancer progression[END_REF].

Interestingly, some tumor tissues have been shown to exhibit a higher level of Na + levels compared to non-123 cancer tissues [START_REF] Smith | Differences in the intracellular concentration of elements in normal and cancerous liver cells as determined by X-ray microanalysis[END_REF][START_REF] Cameron | Intracellular concentration of sodium and other elements as related to mitogenesis and oncogenesis in vivo[END_REF][START_REF] Sparks | Effects of amiloride on tumor growth and intracellular element content of tumor cells in vivo[END_REF]. This implies that intracellular Na + levels could determine the abnormal membrane potential in cancer cells. Thus, Na + permeable channels, such as NaV channels, might play a critical role in cancers [START_REF] Mao | The Emerging Role of Voltage-Gated Sodium Channels in Tumor Biology[END_REF]. It has been demonstrated that NaV takes part in regulating the pH of the tumor microenvironment [START_REF] Besson | How do voltage-gated sodium channels enhance migration and invasiveness in cancer cells?[END_REF]. This mechanism is caused by the high expression of NaV channels leading to a high influx of Na + . Interestingly, NaV channels are coexpressed with NHE1 [START_REF] Carrithers | Regulation of podosome formation in macrophages by a splice variant of the sodium channel SCN8A[END_REF][START_REF] Brisson | Na(V)1.5 enhances breast cancer cell invasiveness by increasing NHE1-dependent H(+) efflux in caveolae[END_REF][START_REF] Brisson | NaV1.5 Na(+) channels allosterically regulate the NHE-1 exchanger and promote the activity of breast cancer cell invadopodia[END_REF]. The high increase of Na + causes a high efflux of protons through NHE1. This decreases the extracellular pH, facilitating the activation of cathepsins that degrade the ECM, thereby enhancing pH-dependent tumor cell invasion and metastasis. [START_REF] Carrithers | Regulation of podosome formation in macrophages by a splice variant of the sodium channel SCN8A[END_REF][START_REF] Gillet | Voltage-gated Sodium Channel Activity Promotes Cysteine Cathepsin-dependent Invasiveness and Colony Growth of Human Cancer Cells[END_REF][START_REF] Brisson | Na(V)1.5 enhances breast cancer cell invasiveness by increasing NHE1-dependent H(+) efflux in caveolae[END_REF][START_REF] Brisson | NaV1.5 Na(+) channels allosterically regulate the NHE-1 exchanger and promote the activity of breast cancer cell invadopodia[END_REF]. Interestingly, the high influx of Na + can activate VGCCs, which increase intracellular Ca 2+ concentrations [START_REF] Tong | Ca(2+) signaling evoked by activation of Na(+) channels and Na(+)/Ca(2+) exchangers is required for GABA-induced NG2 cell migration[END_REF][START_REF] Yao | Nav1.5-dependent persistent Na+ influx activates CaMKII in rat ventricular myocytes and N1325S mice[END_REF]).

The NaV1.6 isoform is overexpressed in lymphoma, cervical, prostate, and colorectal cancers, where it promotes cell invasion and metastatic behaviors, probably in cooperation with NHE1 [START_REF] Mao | The Emerging Role of Voltage-Gated Sodium Channels in Tumor Biology[END_REF].

Interestingly, another study showed, that a significantly lower level of NaV1.6 mRNA expression was found in colorectal adenocarcinomas tissues compared with paired neighboring non-cancerous tissues [START_REF] Igci | Expression profiling of SCN8A and NDUFC2 genes in colorectal carcinoma[END_REF].

• ASICs

The acid-sensing ion channels (ASICs) are widely expressed throughout the nervous system, and recently they have been shown to be expressed in non-excitable tissues, such as vascular smooth model cells and epithelialderived cancer cells [START_REF] Cheng | Acid-sensing ion channels: dual function proteins for chemo-sensing and mechano-sensing[END_REF], Zhang et al. 2022). ASICs belong to the voltage-insensitive, amiloride-sensitive epithelial sodium channel (ENac)/degenerin (dEG) channel family, which is a group of distantly related, non-voltage-gated Na + channels found in mammals [START_REF] Garty | Epithelial sodium channels: function, structure, and regulation[END_REF]Palmer 1997, Benos and[START_REF] Benos | Functional domains within the degenerin/epithelial sodium channel (Deg/ENaC) superfamily of ion channels[END_REF]. There are four isoforms encoded by ASIC functional genes in humans and rodents, namely ASIC1-4. Functional ASICs are aggregated by three homologous or heterologous subunits, which have different properties. The subunits allow for differences in pH sensitivity and ion selectivity between different ASICs [START_REF] Rotin | Function and Regulation of the Epithelial Na(+) Channel ENaC[END_REF]. ASIC1-3 is directly affected by protons, whereas ASIC4 generally does not exhibit a functional role alone (Holzer 2009). When extracellular pH drops rapidly from 7.4 to <6.9, the ASICs are activated, allowing the passage of Na + , Ca 2+ and K + (permeability index Na + > Ca 2+ > K + ). Although ASICs are rapidly deactivated after activation, they can still monitor long-term acidosis [START_REF] Krishtal | A receptor for protons in the nerve cell membrane[END_REF], Waldmann et al. 1997, Waldmann et al. 1997). Several cancer types are associated with ASIC expression, including gliomas, breast, liver, colorectal and pancreatic cancer [START_REF] Berdiev | Acid-sensing ion channels in malignant gliomas[END_REF][START_REF] Sheng | Acid-sensing ion channel 1 (ASIC1) mediates weak acid-induced migration of human malignant glioma cells[END_REF], Zhang et al. 2022). In PDAC cancer cells, ASIC1 and 3 are upregulated and promote EMT, as described in the section 'Calcium and pH'.

Results

ASIC1 and NaV1.6 expression is dysregulated in human PDAC tissue and affected by acid adaptation in PDAC cell lines

We have shown that TRPC1 is upregulated in human PDAC tissue and downregulated upon acid adaptation.

We found that ASIC1 tended to be upregulated by 50% (Figure 43A, n = 2), and NaV1.6 was downregulated by 33 ± 13.2% (Figure 43B, n = 20, p < 0.05) in PDAC tissue compared to adjacent non-tumor tissue. By investigating the mRNA levels of ASIC1 and NaV1.6, we showed that ASIC1 was highly upregulated by 79.5 Initially, we investigated the methylation levels by semiquantitative analysis of the ASIC1 promoter region in MiaPaCa-2 and PANC-1 cells. The semiquantitative method was used to calculate the ratio between the C and the G on the specific CpG sites from at least 10 pooled clones. We found that ASIC1 seems to be hypomethylated in acid-adapted MiaPaCa-2 cells, as the sum of methylation levels from all the CpG sites was less than 2%, compared to cells grown in normal pH conditions, where the sum of methylation where 61.5% in average (Figure 44, n = 2). On the contrary, PANC-1 cells seemed to be hypermethylated in the ASIC1 promoter region, as the sum of methylation on average was 303% (Figure 45, n = 2). The quantitative analysis method reveals that the ASIC1 region is not hypomethylated upon acid-adaptation

As our results indicated that the ASIC1 promoter region could be hypomethylated in MiaPaCa-2 cells, we chose to investigate further the methylation levels of the ASIC1 promoter region in this cell line by the quantitative analysis method, where bisulfite-converted DNA from single clones is sequenced separately. The outcome will be either a C or a G. With this method, we found that none of the CpG sites within the ASIC1 gene promoter were methylated in acid-adapted MiaPaCa-2 cells. However, we only found one CpG site methylated in one out of 14 clones of MiaPaCa-2 cells (Figure 46, n = 2). This indicates that methylation of the ASIC1 promoter region is not strongly affected by acid adaptation compared to that of normal pH conditions. 7.4: 14, 6.5: 14).

The SCN8A gene promoter is hypermethylated in acid-adapted PANC-1 cells

As the NaV1.6 channel was downregulated in human PDAC tissue and the MiaPaCa-2 cell line upon acid adaptation, by the semiquantitative analysis method, we investigated if the SCN8A promoter displayed methylation levels in these conditions. We showed an increased tendency by 7.9% of DNA methylation in the SCN8A gene promoter in a pool of clones (Figure 47, n = 2). Thus, we used the quantitative analysis method to investigate if any CpG sites in this promoter region were methylated. Here, we used another primer pair with 52 CpG sites included instead of 11, which we used for the semi-quantitative analysis. Our results showed that four CpG sites in the SCN8A gene promoter were methylated in PANC-1 cells, in contrast to two CpG sites in cells grown in normal pH conditions. The four CpG sites were methylated in three different clones out of 11, from acid-adapted PANC-1 cells, and the two methylated CpG sites were from two clones out of 9, from PANC-1 cells grown in normal pH conditions (Figure 48, n = 2). This could suggest that the promoter region of the SCN8A gene is hypermethylated upon acid adaptation. 129

The TRPC1 gene promoter is hypomethylated upon acid-adaptation

As TRPC1 was downregulated at the protein level upon acid adaptation, we initially used the quantitative analysis method to investigate DNA methylation of the TRPC1 gene promoter. We observed that there were five out of 12 clones (Figure 49, n = 2) displaying methylation in different CpG sites in the TRPC1 promoter region in PANC-1 cells grown in normal pH conditions, where there were no clones out of 8 displaying methylation in any CpG sites in acid-adapted PANC-1 cells (Figure 49, n = 2). This suggests that the gene promoter of TRPC1 is hypomethylated upon acid adaptation. 130

Discussion

It is well-known that epigenetic changes affect gene expression and are essential drivers of carcinogenesis [START_REF] Lu | Epigenetic regulation in human cancer: the potential role of epidrug in cancer therapy[END_REF]. Of interest is DNA methylation as this epigenetic mechanism is persistent and can be passed down through generations to provide further generations a 'memory' to survive the tumor microenvironment. In contrast, the more transient modalities as histone acetylation that, are imposed to help cancer cells survive acute disruption in their microenvironmental homeostasis [START_REF] Ordway | Causes and Consequences of Variable Tumor Cell Metabolism on Heritable Modifications and Tumor Evolution[END_REF]. Studies have shown that genetic and epigenetic alterations contribute to PDAC development and progression [START_REF] Roalso | Emerging Role of Epigenetic Alterations as Biomarkers and Novel Targets for Treatments in Pancreatic Ductal Adenocarcinoma[END_REF].

Interestingly, the expression of several ion channels is known to be regulated by either hypo-or hypermethylation of their gene promoter in different cancer types, including PDAC (Ouadid-Ahidouch et al.

2015)

. Furthermore, acidosis can affect genetic stability and cause double-stranded DNA breaks [START_REF] Morita | Clastogenicity of low pH to various cultured mammalian cells[END_REF]. Epigenetic changes themselves exert their function by altering the metabolism of cancer cells and are acquired by signaling cascades initiated by sensing the extracellular microenvironment [START_REF] Ordway | Causes and Consequences of Variable Tumor Cell Metabolism on Heritable Modifications and Tumor Evolution[END_REF]).

However, it is not known how the acidic tumor microenvironment affects DNA methylation alterations of ion channel gene promoters and if this can be the cause of up-or down-regulation of specific ion channels. In this study, we used a bisulfite sequencing approach and a quantitative and semi-quantitative analysis method to explore the DNA methylation levels of genes coding for ion channels whose expression is affected by acid adaptation (Figure 50). We showed that NaV1.6 was downregulated in acid-adapted MiaPaCa-2 cells and human PDAC tissue, compared to adjacent non-tumor tissue. Furthermore, we showed that the SCN8A gene promoter is hypermethylated in acid-adapted MiaPaCa-2 cells compared to cells grown in normal pH conditions. However, it cannot be anticipated that this hypermethylation, shown in very few clones, regulates the expression of SCNA8 alone. To further investigate if the hypermethylation causes the downregulation of SCN8A, a demethylation agent as 5-azadeoxycytidine could be used to remove the m5C and then investigate if both the hypermethylation will disappear and the expression of NaV1.6 will increase.

We furthermore showed that the gene promoter regions of ASIC1 and TRPC1 were not hypo-or hypermethylated upon acid adaptation, respectively, when compared to normal pH conditions. This indicates that pH does not modulate DNA methylation at these specific promoter sites, and might not regulate the expression of ASIC1 and TRPC1.

One could speculate if the acid adaptation affects other epigenetic alterations causing the aberrant expression of ASIC1 and TRPC1. Acidosis is known to deacetylate histones globally by activating HDACs, resulting in gene silencing [START_REF] Mcbrian | Histone acetylation regulates intracellular pH[END_REF]). This could be the case for the TRPC1 gene promoter, as the protein expression of TRPC1 is decreased upon acid adaptation. In addition, there was no remarkable change in the DNA methylation of the ASIC1 gene promoter and these specific CpG sites. One could argue that acidosis increases the activation of specific transcription factors binding to CpG sites and protects the promoter from methylation, such as Sp1 [START_REF] Torigoe | Low pH enhances Sp1 DNA binding activity and interaction with TBP[END_REF]. Epigenetic approaches cannot investigate these activities.

This thesis has given novel insight into the role of ion channels, specifically the impact of TRPC1 and the acidic microenvironment in PDAC progression. First, we elucidated the role of TRPC1 in PDAC cell proliferation and if it could be used as a potential biomarker. Next, we evaluated the interplay between fluctuations of the acidic microenvironment and TRPC1, resulting in downstream signaling events that regulate PDAC cell proliferation and migration. Finally, we investigated whether DNA methylation of specific pH-sensitive ion channels regulated their expression.

Thus, in this thesis work, we specifically highlighted that:

1. Ion channels are involved in PDAC development and progression 2. TRPC1 is overexpressed in human PDAC tissue and cell lines, which correlates with aggressive clinical factors and a poor outcome.

3. Acid adaptation increases TRPC1 plasma membrane localization, even if its total expression is decreased.

4. In acid-recovered conditions, the total TRPC1 expression is increased, and the plasma membrane localization maintained.

5. TRPC1 regulates PDAC cell proliferation and migration through PI3K/CaM in a Ca 2+independent manner in normal pH conditions, where it regulates these processes through Ca 2+dependent mechanisms upon acid adaptation and recovery.

6. The TRPC1/PI3K/CaM complex controls cell cycle progression, proliferation, and migration through AKT and ERK1/2 activation.

7. The SCN8A gene promoter tends to be hypermethylated, causing its downregulation in acidadapted MiaPaCa-2 cells.

8. ORAI1, 2 and 3 and STIM1 are upregulated at the transcriptional level in human PDAC samples, where only ORAI3 is overexpressed in human PDAC tissue at the protein level.

To complete our story about the interplay between the acidic tumor microenvironment and TRPC1, it could be of purpose to further investigate different factors (Figure 51):

In this study, TRPC1 regulates PANC-1 cell proliferation in a Ca 2+ -independent manner in normal pH conditions. Although, through Ca 2+ -dependent mechanisms in acid-adapted and -recovered conditions. We hypothesize this is due to the TRPC1 translocalization in the plasma membrane in these conditions. Thus, it could be interesting to investigate if TRPC1 activation is caused directly by acidification and recovery. This could be explored by using the patch-clamp technique.

It would also be interesting to investigate the trafficking of TRPC1 to the plasma membrane in these conditions. It is proposed that TRPC1 is active in the membrane when activated by forming a complex with ORAI1/STIM1. Thus, it could be interesting to see how the fluctuations of the acidic tumor microenvironment affect these processes.

Furthermore, we showed that the inhibition of CaM (Ca 2+ -activated protein) decreases the activation of ERK1/2 to a smaller extent in normal pH conditions than in acid-adapted and -recovered conditions.

Notably, the activation of AKT was only affected by CaM inhibition in acid-recovered cells, suggesting that the activation of ERK1/2 and AKT in acid-recovered conditions are strongly Ca 2+ -dependent. The inhibition of CaM is an indirect way to investigate if these processes, to some extent, are Ca 2+ -dependent. Thus, exploring the direct effect of Ca 2+ depletion on ERK1/2 and AKT activation could be of interest. Furthermore, these findings could reveal if the proliferation and migration of acid-recovered PANC-1 cells are more dependent on Ca 2+ entry through TRPC1 than on the TRPC1/PI3K/CaM complex.

This study also showed that the acidic tumor microenvironment enhanced PANC-1 cell migration.

Additionally, the inhibition of TRPC1 decreased cell migration in all pH conditions. While it is well known that acidosis enhances the EMT process of cancer cells, including PDAC cells (Wu et al. 2022) and that hypoxia induces TRPC1-dependent breast-cancer cell migration (Azimi et al. 2017), it is not known how the interplay between the acidic microenvironment and TRPC1 regulates the EMT process and hence invasion and migration of PDAC cells. Therefore, it could be interesting to elucidate if TRPC1 is involved in this process by investigating epithelial markers and parameters of cell motility.

To further investigate the role of TRPC1and the acidic tumor microenvironment in PDAC cell cycle progression, it could be of interest to synchronize PDAC cells, expose them to the fluctuations of the acidic environment and investigate the expression of TRPC1 in the different phases of the cell cycle. Here, it would also be interesting to examine if the silencing of TRPC1 affected the cell cycle phases differently. This study showed that in non-synchronized cells, TRPC1 KD accumulated cells in the G0/G1 phase in all conditions.

However, the TRPC1 KD decreased the number of cells in the S-phase in normal pH conditions and increased the number of cells in the G2/M phases in acidic and recovered conditions, indicating that the role of TRPC1 shifts in different conditions. We revealed that both the acidic tumor microenvironment and TRPC1 affected the growth of PANC-1 spheroids. Moreover, we have recently shown that in activated PSCs, TRPC1 is involved in cell proliferation and secretion of the cytokine IL-6 (Radoslavova et al. 2022). Thus, it could be interesting to develop a 3D model with a co-culture of PDAC cells and PSCs and investigate the role of TRPC1 by comparing the aggressiveness, in the form of proliferation and invasion, between the different pH conditions and the cocultured and not co-cultured conditions (Figure 52A).

We elucidated that TRPC1 localization and the downstream mechanism were affected by the fluctuations of the acidic microenvironment. These processes could, to some extent, be studied in vivo by using a TRPC1 deficient mouse model and a pH indicator such as pHlourin, SNARF, or pHLIPS. TRPC1-deficient mice have been shown to decrease the number of colorectal cancer metastases and tumor growth. In vivo results from a TRPC1 deficient mouse model, which will take the acidic microenvironment into account, could provide data about the proportion of acidic tissue in the tumor, tumor size, and metastases profile (Figure 52B). et al. 2015). In our local cohort, only the plasma membrane localization of TRPC1 correlated with clinical factors. However, to implement ion channel expression as a screening method, the marking intensity profile would be preferable. To encounter this, a larger cohort is needed to investigate if the channel expression correlates with clinical factors and can function as a diagnostic and prognostic element in clinical practice.

There are several methods to examine, for instance, nerve and vascular invasion. However, it is less used in clinical practice to demonstrate the direct invasion mechanisms, such as ECM degradation, EMT, and cell-cell adhesion. Since dysregulation of ion channels is involved in these cellular processes, they could be potential partners to investigate along with classical invasion markers.

The acidic tumor microenvironment in human PDAC tissue is a difficult task to overcome. First, the pH changes are rapidly affected, for instance, during the surgical procedure when the tumor is removed and upon tissue fixation. However, it is still interesting to investigate how the acidic tumor microenvironment in its present form behaves. In our study, we implemented both NBCn1 and LAMP2 as potential biomarkers of acidification. However, tumor cells and normal cells in the adjacent tumor tissue showed a high expression of these proteins, meaning they are essential both in normal ducts and PDAC cells. 3. L'effet direct de l'appauvrissement en Ca 2+ sur l'activation de ERK1/2 et AKT.

Introduction

Invasive cancers, regardless of their origin, acquire characteristic phenotypic traits during their development, including self-su ciency with respect to growth signals, apoptosis evasion, profound metabolic changes, chemotherapy resistance, and the ability to invade and spread to secondary niches [1]. These changes are the result of a clonal evolution process, in which the combination of somatic mutations and evolutionary selection pressure leads to the preferential expansion of clones of cells that are particularly fit for survival and expansion in the harsh tumor microenvironment [2][3][4].

The microenvironmental conditions in solid tumors are a result of rapid cancer cell proliferation and growth which, in combination with insu cient vascularization, leads to hypoxia, glucose depletion, [5][6][7][8][9]. A plethora of studies have investigated the impact of hypoxia on cancer development and the therapeutic potential of targeting hypoxia-inducible factors (reviewed in, e.g., [10]). In contrast, the role of extracellular acidosis in this process remains incompletely understood.

Recent studies, mostly employing the acid adaptation of cultured cancer cells, have supported the hypothesis that extracellular acidosis is a driver of cancer aggressiveness. Thus, adaptation to acidosis was shown to favor epithelial-to-mesenchymal transition (EMT) [11,12], invasiveness and metastasis in cell culture and xenograft models of melanoma, cervical cancer, and breast and colon cancer [13][14][15][16]. Accordingly, studies of mouse breast tumors in vivo showed that acidosis (detected by pH (low) insertion peptide (pHLIP) labeling), carbonic anhydrase (CA9) expression and plasma membrane-localized LAMP2 correlated with invasive features such as the absence of laminin and the expression of matrix metalloproteinase (MMP)-9 and -14 [17]. Other phenotypic changes induced by the adaptation of cancer cells to acidosis include a shift from glycolytic metabolism toward increased glutaminolysis, fatty acids uptake and -oxidation [9,15,[18][19][20]. Cancer cell proliferation and growth are, however, generally reduced, or unaltered, as long as acidic pH e is maintained [12,13].

The molecular mechanisms through which growth under chronic extracellular acidosis leads to this profound rewiring of cancer cells are poorly understood. While several studies have examined global changes in gene expression upon acidosis or lactic acidosis [15,21,22], the overlap between the changes induced by acidosis and those found in patient tumors, and the correlation of acidosis-responsive gene expression to overall patient survival, have to our knowledge never been comprehensively examined. Because acidic growth seems to drive at least some phenotypes akin to those found in highly aggressive cancers, an important question is whether there is a generic response to acid adaptation that is shared between cancer cells, and whether this response reflects the expression changes observed between tumors and normal tissues in patient samples. Such correlations may indicate that an acidic microenvironment can increase cancer aggressiveness, which in turn should be correlated to patient survival.

In the present study, by applying RNA-seq to three acid-adapted cancer cell lines we identify a shared acid adaptation response gene signature, which we compare with rich expression data from human tumors and normal tissue across many cancers, and overall survival data from the same patients. Our results reveal significant overlaps between gene signatures of acid-adapted cells and tumor tissues for subsets of patients, and we identify sets of shared genes from these signatures that correlate significantly-positively as wel as negatively-with patient survival.

Results

Gene Expression Changes Induced by Chronic Adaptation of Cancer Cells to Acidosis

To understand the changes in gene expression profile induced by changes in environmental pH (pH e ) across multiple cancer cell types, rather than in a single cancer cell type, we adapted three different cancer cell lines to growth at either pH 7.6 or 6.5 by adjusting the HCO 3 concentration of the medium [23], followed by culturing at the respective pH for at least 1 month at 5% CO 2 . Cells were lysed, and RNA was isolated and subjected to global RNA-seq in triplicates (Figure 1A,top). Principal component (PC) analysis of gene expression estimates from RNA-seq libraries showed that PC1 and PC2 separated the three cell lines, while PC3 and PC4 separated acid-adapted cells from control cells, indicating a shared acid adaptation response across the three cell lines (Figure 1B). Given this, we set out to analyze the shared acid adaptation response, and compared it to tumor-specific expression profiles and patient survival using a strategy outlined in Figure 1A. ) were acid-adapted to pH 6.5 and 7.6 over a period of 1 month and subjected to RNA-sequencing analysis (RNA-seq). Below this, an overview of computational analyses performed is shown. Briefly, we used two strategies to define a shared acid adaptation gene expression profile: by defining sets of statistically significant genes, or by ranking genes by their expression fold change (pH 6.5 vs. 7.6; Figure 2). These lists were then subject to over-representation analyses (Figure 2), survival analysis in multiple cancers (Figure 3), and comparison to tumor-control tissue (ctrl.) RNAseq experiments from patient samples (Figures 4 and5), to identify a final list of genes that are up-/downregulated in acid adaptation as well as in tumor vs. ctrl. experiments, and whose in vivo expression is associated with overall patient survival (Figure 6). ) were acid-adapted to pH 6.5 and 7.6 over a period of 1 month and subjected to RNA-sequencing analysis (RNA-seq). Below this, an overview of computational analyses performed is shown. Briefly, we used two strategies to define a shared acid adaptation gene expression profile: by defining sets of statistically significant genes, or by ranking genes by their expression fold change (pH 6.5 vs. 7.6; Figure 2). These lists were then subject to over-representation analyses (Figure 2), survival analysis in multiple cancers (Figure 3), and comparison to tumor-control tissue (ctrl.) RNA-seq experiments from patient samples (Figures 4 and5), to identify a final list of genes that are up-/downregulated in acid adaptation as wel as in tumor vs. ctrl. experiments, and whose in vivo expression is associated with overall patient survival (Figure 6). Venn diagrams show overlaps between acid adaptation-upregulated genes (from Figure 2B), of genes significant in overall survival (OS) analysis in at least two types of cancer (based on TCGA data, Figure 4), and genes identified as having significant rank correlations between acid adaptation and tumorcontrol gene rank lists (RRHO analysis, Figures 4 and5). (B) Overlaps between downregulated genes, OS and RRHO analyses Venn diagrams arranged as in A but focused on acid adaptationdownregulated genes.

Identification of A Shared Acid Adaptation Gene Response Profile

Discussion

Acidosis is one of the key characteristics of the microenvironment of solid tumors [3,9,20,54]. Agreeing with the idea that cancer is largely an evolutionary disease driven by selection pressure, it has been proposed that chronic acidosis selects for changes in cancer cell genotype and phenotype that increase their "fitness", and hence aggressiveness [3,55,56]. Such adaptations would potentially render the cells resistant not only to sustained acidosis, but also to other stress stimuli, such as nutrient limitations, hypoxia and chemotherapy, as well as to anti-tumor immunity [9,57,58]. Although individual genes and pathways have previously been compared between acid-adapted cells and patient tumors (e.g., [15,24,59]), a comprehensive integrative analysis comparing genes Figure 6. Integrative analysis. (A) Overlaps between upregulated genes, OS and RRHO analyses. Venn diagrams show overlaps between acid adaptation-upregulated genes (from Figure 2B), of genes significant in overall survival (OS) analysis in at least two types of cancer (based on TCGA data, Figure 4), and genes identified as having significant rank correlations between acid adaptation and tumor-control gene rank lists (RRHO analysis, Figures 4 and5). (B) Overlaps between downregulated genes, OS and RRHO analyses Venn diagrams arranged as in (A) but focused on acid adaptation-downregulated genes.

Identification of a Shared Acid Adaptation Gene Response Profile

The Limma method was used to identify genes with a significant and shared expression response to acid adaptation using a linear model (See Materials and Methods). Out of the 12,750 expressed genes, 478 were significantly upregulated, and 255 were downregulated across all three cell lines (abs (log 2 fold change, log 2 FC) > 0.5, False Discovery Rate (FDR) < 0.05). Figure 2A shows a shared log 2 FC-ranked list of all expressed genes, colored by significance, while Figure 2B shows the mean log 2 FC in each cell line across triplicates for di↵erentially expressed genes. Tables S1 andS2 list all significantly upand downregulated genes, respectively. The response to pH was overall highly similar between the three cancer cell lines, although the magnitude of change in the expressions of specific genes di↵ered between cell lines (Figure 2B). Among the top 10 upregulated genes was thioredoxin-interacting protein (TXNIP, also known as Vitamin D3-upregulated protein 1, VDUP1), previously reported to be upregulated in response to extracellular acidosis [22,24] (Figure 2A). The TXNIP protein has several important physiological roles: it is a potent negative regulator of glycolysis, and involved in redox homeostasis, di↵erentiation and growth. TXNIP is generally downregulated in cancers, at least in part because it is negatively regulated by oncogenes such as Myc and ErbB2, and low TXNIP expression is associated with poor prognosis [25][26][27]. Confirming the relevance of this pathway, the TXNIP paralogs ARRDC2 and ARRDC4 were also among the significantly upregulated genes (Table S1).

Interestingly, several cation channels previously implicated in cancer development were significantly upregulated. For example, the ↵ subunit of the epithelial sodium channel ENaC (SCNN1A) and the 4 subunit of the voltage-dependent calcium channel (CACNG4) (Figure 2A) were among the 10 most upregulated genes. The genes encoding the acid-stimulated ion channel-1 (ASIC1), and the 1 subunit of the voltage-gated sodium channel (SCN1B), were also significantly upregulated in acid-adapted cells (Table S1). In accordance with our findings, ASIC1 and ASIC2 are upregulated in colorectal cancer cells subjected to acidosis [28]. ASICs and ENaC belong to the same channel family, and both ASIC1 [29] and ENaC [30] are acutely activated by acidic pH, and both channels are implicated in cancer development [11,31]. Similarly, both CACNG4 [32] and SCN1B [33] are upregulated in cancer tissue and their gene products have been assigned a role in cancer progression.

Other highly upregulated genes included interferon-induced transmembrane protein 1 (IFITM1), which, together with other interferon-regulated genes, are highly upregulated in several cancers and assigned key roles in driving aggressiveness and chemotherapy resistance [34,35]. In addition, the genes encoding Sushi-containing Domain-3 (SUSD3), an estrogen-regulated membrane-localized protein previously found to be upregulated by chronic acidosis [15] and to play a key role in breast cancer cell migration [36], and LARGE2, a bifunctional glycosyltransferase involved in proteoglycan modification and hence in cell-extracellular matrix (ECM) interaction [37], were among the 10 most upregulated genes (Figure 2A).

The 10 most downregulated genes across all three acid-adapted cell lines included, firstly, the gene encoding the multidomain scaffold protein A-kinase anchoring protein-5 (AKAP5, a.k.a. AKAP79/150). AKAP5 is a key regulator of cellular cAMP and Ca 2+ signaling and, downstream from this, a plethora of physiological processes, including glucose metabolism [38]. AKAP5 is not widely linked to cancer in the literature, yet low AKAP5 expression was correlated with poor prognosis in some stomach adenocarcinomas [39]. NIBAN1, a.k.a. FAM129A, which was also downregulated by acidic growth, is frequently upregulated in cancers, favoring cell motility yet decreasing autophagy [40,41]. Furthermore, mucolipin-3 (MCOLN3) was strongly downregulated upon acidosis-induced selection. Interestingly, MCOLN3 codes for a predominantly endosomal Ca 2+ channel of the TRP channel family, which is inhibited by acidic pH and plays important roles in endosomal Ca 2+ and pH homeostasis [42]. Other genes strongly downregulated across all three cell lines included those coding for the tight junction protein cingulin (CGN), the E3 ubiquitin ligase TRIM36, and SYNE1 (a.k.a. Nesprin-1), a nuclear envelope protein.

Gene Ontology (GO) terms associated to ECM composition and remodeling, and lipid and carboxylic acid metabolism, were over-represented in the upregulated genes, while GO terms associated with cell proliferation, replication fork function and DNA repair were over-represented in the downregulated genes (Figure 2C). Furthermore, the upregulation of cation channels (Figure 2A and above) was reflected in GO term analysis (Table S3, while Table S4 shows the GO terms for downregulated genes). KEGG pathway analysis showed an over-representation of cytochrome P450-drug and xenobiotic metabolism, chemical carcinogenesis, propanoate metabolism and glutaminergic synapse pathways in the upregulated genes, while downregulated genes were over-represented in the cell cycle, DNA replication, homologous recombination, glutathione metabolism and Fanconi anemia pathways. Notably, a downregulated glutathione metabolism was previously reported in acid-adapted cells, and shown to reflect a shift from glutathione production towards utilization of glutamine as a metabolic fuel [18]. The ranked acid adaptation gene set from Figure 2A was used to complement the above GO analysis with gene set enrichment analysis (GSEA) using the SigDb database of gene sets (Figure 2D). This revealed a clear gene rank enrichment of several oncological gene sets: acid adaptation-upregulated genes were enriched for gene sets associated with increased migration and invasiveness, gene sets upregulated after expression of CyclinD1 (CCND1) (a key regulator of G1-S phase transition), and genes downregulated after mTOR inhibition (Figure 2D). The link to mTOR signaling is notable, given the key role of mTOR in metabolic control. The pH sensitivity of mTOR signaling has previously been assigned a role in the impact of acidosis on metabolism, albeit in a short-term study (i.e., not long enough for acid-induced selection) where cytoplasmic acidosis was found to inhibit mTOR signaling [43,44]. Acid adaptation-downregulated genes were, correspondingly, enriched in gene sets upregulated by mTOR inhibition, or by overexpression of the transcription factor E2F1, a key player in the control of cell cycle progression.

Taken together, these analyses show that across multiple cancer cell types, chronic acidosis is associated with gene expression changes expected to reflect a profound metabolic shift, including the downregulation of fermentative glycolysis and upregulation of glutamine-and lipid-based metabolism, and the downregulation of cell division and DNA repair, as wel as changes in ECM remodeling and ion channel activity.

In Vivo Expression of Genes Reacting to Chronic Acidosis Is Predictive of Cancer Patient Survival

The above analysis indicated that there was an overlap between cancer-regulated and acid adaptation-regulated gene sets, motivating a global investigation into whether the expression of acid adaptation-induced genes in patient tumors is correlated to patient overall survival (OS). To do this, RNA-seq data for multiple cancer types from the TCGA database were used. For each gene di↵erentially expressed in all cell lines in the acid adaptation experiment above, patients were classified based on their mRNA expression of the specific genes into a high and low expression group, respectively, using the median expression of genes as the cut-o↵ value.

Kaplan-Meier analysis showed that 267 genes upregulated by chronic acidosis and 138 genes downregulated by chronic acidosis were significantly associated with OS. Specifically, expression of 114 genes upregulated by chronic acidosis in all cell lines was significantly correlated with OS of pancreatic cancer patients. In luminal B breast cancer, 56 acid adaptation-upregulated genes correlated significantly with OS, followed by lung cancer (adenocarcinoma), glioblastoma, colon cancer, ovarian cancer, thyroid cancer and stomach cancer (44,36,35,32,30 and 29 genes,respectively;Figure 3A). In pancreatic, lung and thyroid cancer, a high expression of the majority of acid adaptation-upregulated genes correlated with better OS. Breast, glioblastoma, colon, ovarian and stomach cancer cohorts shared the reverse pattern: for the majority of acid adaptation-upregulated genes, high expression correlated with poor OS outcome (Figure 3A). Additionally, we found 70 acid adaptation-downregulated genes whose expression correlated with OS of lung adenocarcinoma patients. The counts in descending order for other types of cancer were: Pancreatic cancer-59, stomach cancer-24, ovarian cancer-23, luminal B breast cancer-21, thyroid cancer-17, colon cancer-15 and glioblastoma-11 (Figure 3B). High expressions of the majority of acid adaptation-downregulated genes in lung adenocarcinoma, pancreatic cancer, breast cancer and glioblastoma correlated with poor OS. On the contrary, high expressions of the majority of acid adaptation-downregulated genes in stomach, ovarian, thyroid and colon cancers were associated with better OS (Figure 3B).

The data in Figure 3A,B are collectively consistent with the hypothesis that in stomach, ovarian and colon cancers, acidosis-related changes in gene expression may be more likely to be linked to worse OS, whereas in pancreatic and lung cancer, they are more likely to be linked to better OS. A necessary caveat is that these analyses are only correlative (see also Discussion), and the statistical power of the OS analysis is limited by the number of patient datasets available.

Two genes stood out in terms of their high correlation with OS in multiple cancers. Among the acid adaptation-upregulated genes, high expression of the gene encoding the transcription regulator SMAD9 (a.k.a. SMAD8) showed correlation with good OS in four types of cancer (pancreatic, lung, colon and glioblastoma; Figure 3C, Table 1). SMAD9, a receptor-SMAD activated by Bone Morphogenetic Protein (BMP) receptors, was also upregulated by acidosis in colon cancer cells [45]. Although the link of high expression to better OS makes SMAD9 upregulation an unlikely driver of acidosis-induced pro-tumorigenic e↵ects, activating SMAD9 mutations were linked to some gastric cancers [46]. We also identified 5 genes (LGR4, RARG, PNISR, PCOLCE2, RALGDS) that shared the same patterns across three types of cancer, and 39 genes with two overlaps across eight cancer types (Table 1). As high expression of LGR4, RARG and PCOLCE2 correlated with poor OS, these are interesting candidates for genes selected for in acidosis and linked to poor OS. The most common gene classes (based on the UniProt database) among genes with significant OS analysis results in at least two types of cancer were transcription regulators (9 genes), followed by genes involved in transport processes (8 genes), di↵erentiation/morphogenesis (5 genes) and metabolism (4 genes) (Table 1).

Another gene with multiple cancer OS associations was the transcription factor ZNF557, which was downregulated by acid adaptation. Its low expression was associated with a worse OS outcome in five types of cancer (pancreatic, breast luminal B, lung adenocarcinoma, stomach and glioblastoma) (Figure 3D, Table 2). This supports that upregulation of ZNF557, an essentially unstudied member of the KRAB-ZNF family of zinc finger transcription factors and a transcriptional target of STAT3 [47], may be particularly relevant to the pro-tumorigenic effects of the acidic microenvironment, a possibility to be addressed in future studies. We furthermore discovered 5 genes (MDGA1, VEGFC, MCM10, CTBP1-DT, CHMP4A) with three OS correlations, and 22 genes with two OS correlations, across eight cancer types (Table 2). Of these, low expressions of CTBP1-DT and CHMP4A correlated with poor OS, making them possible candidates for acidosis-stimulated cancer aggressiveness. Among the acid adaptation-downregulated genes significant in OS analysis in at least two types of cancer, we found 17 genes associated with DNA replication/repair/cell cycle, 5 involved in transcription regulation and 4 playing key roles in differentiation and morphogenesis (Table 2).

All 182 acid adaptation-upregulated, and 84 acid adaptation-downregulated, genes that were significant in OS analysis in only one type of cancer are listed in Tables S5 andS6, respectively. Genes that showed contradictory OS results across cancer types (i.e., high and low expression was significantly associated with poor OS in di↵erent cancers) are listed in Table S7 (acid adaptation-upregulated) and Table S8 (acid adaptation-downregulated). Figures S1-S16 show plots for all genes with statistically significant OS results.

Taken together, these results show that a large fraction of acid adaptation-responsive genes correlate with patient survival across multiple cancers. Importantly, these genes fall into four major groups: acid adaptation-upregulated genes correlating with either good or poor OS, and acid adaptation-downregulated genes correlating with either better or worse OS across several types of cancers. Histone-binding, metal ion-binding PAAD-pancreatic cancer (dark blue), BRCA-breast cancer-luminal B (pink), LUAD-lung cancer-adenocarcinoma (turquoise), GBM-glioblastoma (orange), COAD-colon cancer (red), OV-ovarian cancer (purple), THCA-thyroid cancer (grey), STAD-stomach cancer (green). Molecular function and/or biological processes according to UniProt database [48].

Types of Cancer

Gene Name

Cont.

Types of Cancer

Table 2. Acid adaptation-upregulated genes significant in OS analysis in at least two types of cancers. Ribosome biogenesis, protein synthesis PAAD-pancreatic cancer (dark blue), BRCA-breast cancer-luminal B (pink), LUAD-lung cancer-adenocarcinoma (turquoise), GBM-glioblastoma (orange), COAD-colon cancer (red), OV-ovarian cancer (purple), THCA-thyroid cancer (grey), STAD-stomach cancer (green). Molecular function and/or biological processes according to UniProt database [48].

Types of Cancer

Gene Name

Cancers 2020, 12, 2183 18 of 27

RRHO Analysis Identifies Substantial Overlap between Genes Upregulated in Acid Adapted Cells and Patient Tumor Tissue

Given that the expression level in vivo of a substantial number of acidosis-induced genes was correlated with overall patient survival, we reasoned that it would be informative to directly compare the acid adaptation gene expression response and the gene expression change between tumor and ctrl. tissue. This requires paired normal and tumor tissue data from the same patient, and we therefore downloaded TCGA RNA-seq data for 642 patients for which such paired data was available. For each patient, we ranked genes according to the tumor vs. ctrl. tissue RNA-seq log 2 FC. We will refer to such lists as "tumor-ctrl. ranked gene lists". Each such ranked list was compared to a ranked gene list based on the pH 6.5 vs. 7.6, log 2 FC, as shown in Figure 2A, referred to as the "acid adaptation ranked gene list". Using the rank-rank hypergeometric test method (RRHO) (Figure 4A), we sought to identify patients whose tumor-ctrl. ranked gene lists had a significantly similar gene order to that of the acid adaptation ranked gene list, and the set of genes that had similar orders in many such pairwise comparisons. In brief, RRHO analysis identifies windows of the two rank gene lists which have higher rank similarities than expected, and assigns p-values for each such window based on hypergeometric tests, which can be visualized as a heat map. For example, the heat map in Figure 4A shows an RRHO comparison between the patient TCGA-EL-A3ZS tumor-ctrl. ranked gene list (y-axis) vs. the acid adaptation ranked gene list (x-axis), where color intensity in the heat map indicates the gene rank similarity significance in a given window across respective ranked lists. In this example, we observed a high overlap in the upregulated genes between the tumor-ctrl. ranked gene list of the TCGA-EL-A3ZS patient and the acid adaptation ranked gene list (red areas), and a less strong but still substantial rank similarity between modestly downregulated genes in both sets (yellow-green areas). To identify clear cases of substantial rank similarity between patient tumor-ctrl. ranked lists and the acid adaptation ranked lists, we counted the fraction of windows in the heat map matrix which had a p-value < 0.05, and defined this number as the "acid adaptation similarity". If >20% of windows had p < 0.05, we considered the patient tumor-ctrl. rank gene list to be highly similar to the acid adaptation ranked gene list. The group of 128/642 (~20%) tumor-ctrl. ranked gene lists satisfying this criterion were defined as the 'high acid adaptation similarity group" (Figure 4C).

Within this group, in most cases, the genes with highest rank similarity were upregulated in pH 6.5 vs. 7.4 and upregulated in tumor vs. ctrl. Figure 4B shows all heat maps from patients in the high acid adaptation similarity group, while Figure 4C shows the distribution of patient ranked gene lists having a given fraction of windows with p < 0.05. Interestingly, some cancer types had particularly high proportions of patients within the high acid adaptation similarity group; for example, 34/51 (~63%) of thyroid cancer patients (TCGA-THCA), 34/69 (~49%) of kidney renal clear cell carcinoma (TCGA-KIRC) patients, and 3/4 (75%) of pancreatic adenocarcinoma (TCGA-PAAD) patients exhibited this pattern. The insert in Figure 4C shows the numbers of patients in each cancer type in the high acid adaptation similarity group. Notably, for some cancer types only small paired tumor-ctrl. sample sets were available; hence, for these cancers, the calculated fractions are less certain.

Next, we investigated if patients in the high acid similarity group had specific clinical characteristics. We observed that patients in the high acid adaptation similarity group had a weakly significant average lower age than remaining patients (two-sided t-test, p = 0.043, means 58.99 and 62.15) (Figure 4D(i)). To investigate metastasis status, we obtained tumor-normal-metastasis (TNM) staging system data from the TCGA database and filtered for M0-M1 stages (presence or not of distant metastasis, 417 patients), N0-N3 stages (degree of spread to regional lymph nodes, 517 patients), and T1-T4 stages (size of the primary tumor, 619 patients) (Figure 4D(ii-iv)). We found no significant relation between acid adaptation similarity groups and metastasis or node status, but patients in the high acid adaptation similarity group were less likely to be classified as T2 (two-sided Fisher's exact test, p = 0.0007, odds ratio = 0.48), and more likely to be classified as T3 (two-sided Fisher's exact test, p = 0.0015, odds ratio = 1.95). This is in congruence with the notion that an acidic gene signature is more likely to correlate with a more advanced primary tumor stage than with earlier stages.

Overall, the RRHO analysis strongly indicates high similarity in acid adaptation response and tumor-ctrl. expression profiles for a subset of patients spread across many cancers, in particular for the upregulated genes. To investigate the overlap on a gene, rather than patient, basis for each tumor-ctrl. and acid adaptation RRHO analysis, we extracted the set of genes that had significant rank similarities. We then sorted these genes via how many times they were identified in the overlap sets among all 128 comparisons. Figure 5A,B show significant GO term and KEGG pathway annotation of such genes occurring in 50 comparisons. STRING [49] protein-protein interaction plots for the up-and downregulated genes with occurrence 50 are shown in Figure 5D,E. The GO/KEGG analyses show that the upregulated overlapping genes were significantly associated with ECM remodeling and cell migration and invasion, whereas the downregulated overlapping genes were generally associated with metabolic processes. STRING analysis confirmed this pattern, with upregulated overlapping genes showing a predominant clustering of genes related to ECM components and remodeling (Figure 5C). Downregulated overlapping genes were less clearly clustered, but a cluster of metabolism-related genes including ME1, PCK2, PGD, GK, IDNK and KHK was evident (Figure 5D).

Collectively, these analyses show that there is a substantial overlap between gene sets up/downregulated by acid adaptation and genes up/downregulated in tumor vs. matched normal tissue, respectively. Furthermore, they indicate that the upregulated overlapping gene sets are strongly dominated by genes involved in cell motility, invasiveness and ECM remodeling, consistent with the notion that these are key processes through which microenvironmental acidosis favors cancer development.

Integration of Survival Data and Rank-Rank Analysis

Above, we have shown that (i) the in vivo expression of many genes selected for during acid adaptation is correlated to overall survival, and (ii) for around 20% of cancer patients investigated, there is a clear correlation in ranked gene expression (tumor-ctrl. vs. acid adaptation response). Seeking to identify a set of genes that both correlated in ranked gene expression between adapted cells and tumors, and was linked to survival, we plotted the overlap of acid adaptation-up-and downregulated genes identified in the respective analyses as Venn diagrams (Figure 6). For survival-related genes, we chose a conservative approach where only genes that were significantly related to survival in at least two cancer types were included. Remarkably, the large majority of such genes overlapped with genes identified by the RRHO analysis, resulting in two consensus gene lists of 36 and 34 genes, respectively (Figure 6A,B), which could be further split based on whether their in vivo expression correlated with higher or lower patient survival.

As expected, the acid adaptation and tumor-upregulated genes that were associated with poor prognosis (Figure 6A, top list) included multiple genes related to ECM and cell motility in various cancers, such as those encoding sperm-associated antigen-4 (SPAG4) [50], microfibril-associated protein-2 (MFAP2) [51], the ADAM protease ADAMTSL4 [52], and ECM components heparan-sulfate proteoglycan-2 (HSPG2) and Procollagen C-Endopeptidase Enhancer 2 (PCOLCE2). Thioredoxin reductase-3 (TXNRD3), likely important for alleviating oxidative stress, the transcription factors HOXA11 and OTX1, as wel as the ENaC subunit SCNN1A, discussed above, were also found in this gene set. The upregulated genes for which high expression correlated with good prognosis in the cancers studied (Figure 6A, lower list) included SMAD9, discussed above, as wel as genes coding for two transport proteins, the Ca 2+ channel ORAI3 and the TMEM16 family member ANO7, which is a lipid transporter and/or ion channel. It should, however, be noted that although ANO7 upregulation is associated with good prognosis in breast and colon cancer (Table 1), it is in fact associated with poor prognosis in prostate cancer [53].

The acid adaptation-downregulated genes overlapping with genes downregulated in patient cancers, and for which high expression was associated with good prognosis (i.e., potential candidates for pro-tumorigenic e↵ects of acid adaptation, Figure 6B, lower list) included AKAP5 and ZNF557, described above, as wel as several DNA replication-and repair-related genes, including the genes encoding the DNA repair protein MMS22L, the DNA replication licensing factor MCM3, and the replication fork complex protein GINS2. Conversely, the downregulated genes for which high expression correlates with poor prognosis (Figure 6B, top list) were dominated by other genes involved in DNA replication, repair and cell cycle control, such as BRCA2, CDC6, CDCA4, CDCA5 and EIF6.

Collectively, these results reveal that genes regulated similarly in acid-adapted cells and in tumor tissue can be linked to both poor and good prognosis, consistent with the notion that tumor acidosis may be both a driver and a repressor of cancer progression. This indicates that while acidosis is likely to favor cancer progression through the upregulation of ECM/motility related genes, it limits it through the downregulation of DNA replication pathways.

Discussion

Acidosis is one of the key characteristics of the microenvironment of solid tumors [3,9,20,54]. Agreeing with the idea that cancer is largely an evolutionary disease driven by selection pressure, it has been proposed that chronic acidosis selects for changes in cancer cell genotype and phenotype that increase their "fitness", and hence aggressiveness [3,55,56]. Such adaptations would potentially render the cells resistant not only to sustained acidosis, but also to other stress stimuli, such as nutrient limitations, hypoxia and chemotherapy, as wel as to anti-tumor immunity [9,57,58]. Although individual genes and pathways have previously been compared between acid-adapted cells and patient tumors (e.g., [15,24,59]), a comprehensive integrative analysis comparing genes upregulated by acidosis, genes upregulated in patient tumors and their relation to patient survival is lacking. This was the aim of the work presented here.

Our analyses show that hundreds of genes are similarly regulated by chronic acidosis, in three cancer cell lines from human breast and pancreatic cancers, allowing for the identification of a characteristic gene set shared between cancer cells selected for growth in an acidic microenvironment. Both the up-and downregulated genes show significant overlaps with genes up-and downregulated in patient tumor tissue, compared to normal tissue, for subsets of patients across multiple cancers. Finally, numerous acid-regulated genes correlate with overall patient survival in at least one cancer type, and many in two or more cancers, pointing to a possible functional role. Importantly, survival correlations were both positive and negative, i.e., some genes selected for by acidosis and in patient tissue correlate with increased, and some with decreased, overall survival; furthermore, the e↵ect on survival is often cancer-specific.

It is important to note that although the overlap between acid adaptation and tumor-specific expression was strong, the overall causality is unclear. Extracellular acidosis within tumors may causally lead to cancer aggression in vivo or potentiate an existing aggressive tumor behavior, or the correlations we observe may be caused by an unobserved factor. To detangle these questions and understand their true relevance to tumor growth and metastasis, it will be necessary to measure and manipulate extracellular acidity in tumors in vivo or in advanced in vitro models, that can mimic not only acidosis but other physicochemical, as wel as cellular, components of the tumor microenvironment.

A limitation of this work is that a given gene may favor the development of one cancer type and counteract another (Tables S7 andS8), and hence correlations demonstrated here will not apply to all cancers. This notwithstanding, clear patterns were observed.

A number of specific observations deserve special attention with respect to their relation to cancer biology. Firstly, our findings are fully in line with the existing studies proposing that tumor acidosis can promote cancer invasiveness. This includes the prominent pattern of upregulation by acidosis of genes involved in ECM remodeling and invasiveness, as wel as the striking extent of upregulation of ASIC1, the ENAC ↵ subunit, and other cation channel genes, many of which have been assigned important roles in cell-cell adhesion and invasion [60,61]. Second, our analyses also support several existing studies that clearly show that adaptation to acidosis is not associated with increased growth of the cancer cells [13,15]. The strong upregulation of TXNIP and its paralogs ARRD2 and ARRD4 by chronic acidosis is consistent with previous reports of the e↵ect of acidosis [18,24] and lactic acidosis [22] on this family of proteins, which are key negative regulators of glycolytic metabolism. In previous work, TXNIP upregulation in acidosis has been shown to involve MondoA [22,24]. The metabolic signature induced by chronic acidosis in this and previous reports is characterized by the downregulation of fermentative glycolysis and the upregulation of glutamine-and lipid-based metabolism [18,62]. In contrast to this, cancer cells are often highly glycolytic, and accordingly, frequently exhibit TXNIP downregulation [25][26][27]. Interestingly, combined inhibition of mTOR and histone deacetylases strongly upregulated TXNIP, triggering oxidative stress-induced cell death in KRAS-driven tumors [63]. This makes it tempting to speculate that TXNIP could be responsible not only for the metabolic shift away from fermentative glycolysis, but also for oxidative stress and growth restriction in acid-adapted cells.

Other mechanisms from those discussed in this work are likely to contribute to the e↵ect of microenvironmental acidosis on cancer aggressiveness. For instance, extracellular acidosis may impact genomic instability and cause epigenetic changes in cancer cells, in line with the substantial downregulation of DNA damage response mechanisms observed in this work [9,17]. Numerous studies have established the strong inhibitory e↵ect of acidosis on cell cycle progression [64]. After several weeks to a few months of culture in acidic medium, cancer cells attain a growth rate similar to that of normal cells grown at pH 7.4, yet not higher [13,15]. This is in itself remarkable, given the acidosis-induced downregulation of pathways associated with cell cycle progression and DNA replication observed in this study. It is, however, consistent with the notion that the acidic TME is likely to act as a brake on proliferation, and may be seen as a niche favoring cells with limited growth but high growth potential [56,65], such as cancer stem cells. Such cells would be growth-limited in an acidic environment, but could have the capacity for extremely rapid growth when encountering regions of normal pH e [9]. In this regard, therapeutic strategies targeting pathways selected for by chronic acidosis, yet functionally limited by these conditions, may be particularly interesting. Similarly, otherwise highly successful strategies of limiting tumor growth by counteracting acidosis [66,67] could carry the risk of exacerbating aggressiveness if applied at a stage when pH normalization might unleash aggressive growth.

Materials and Methods

Cell Culture and Acid Adaptation

Human breast cancer cell lines MDA-MB-231, MCF7 and human pancreatic adenocarcinoma cell line PANC-1 were cultured in RPMI-1640 Medium (Sigma Aldrich, Catalog No. R1383, Saint Louis, MO, USA) supplemented with 10% Fetal Bovine Serum (Sigma Aldrich, Cat. No. F9665, Saint Louis, MO, USA) and 1% Penicillin/Streptomycin (Sigma Aldrich, Cat. No. P0781, Saint Louis, MO, USA). Medium pH was adapted by adjusting the HCO 3 concentration by adding the appropriate amount of NaHCO 3 , ensuring equal osmolarity by adjusting [NaCl]. Cells were adapted to pH 7.6 and 6.5 by adding the appropriately pH-adjusted medium to freshly split cells, and maintaining cells in this medium, splitting or adding fresh medium twice per week for 1 month, until approximately equal growth rates were observed.

RNA Isolation and RNA Sequencing

Cells were grown to 70-90% confluence in 10 cm 2 Petri dishes. RNA isolation was performed using a Nucleospin RNA purification kit (Macherey-Nagel, Cat. # NC0707522, Düren, Germany) and following the manufacturer's instructions. RNA library preparation and sequencing were done as a paid service by BGI (Hongkong), producing 100 bp paired-end non-stranded libraries with ~20 M reads per library, using the BGI-seq platform. Three replicate libraries were made for each cell type and condition (in total 18 libraries).

Figure 2 .

 2 Figure 2. Overview of the pancreatic ducts and the transporters involved in the secretion of the alkaline HCO3 -rich pancreatic fluids and ductal cell pH regulation (Modified from(Ishiguro et al. 2012).

Figure 3 .

 3 Figure 3. The updated 14 hallmarks of cancer (Hanahan 2022).

Figure 4 .

 4 Figure 4. Histology of normal pancreas and PDAC. Panel A) shows normal well-organized pancreatic tissue, and different elements of the normal pancreas are indicated. Acinar cells form lobules and ducts formed by connective tissue aligned with epithelial duct cells. Indicated are the endocrine part of the pancreas, the islets of Langerhans, and adipose tissue. Panel B) shows well-differentiated cancer cells that are enlarged, with enlarged nuclei, forming new ducts (a feature of PDAC). In PDAC tissue, the acini are disrupted by the pressure created by the cancer cells, and only cancer cells and stroma are left. (Magnification indicated above the images. All images represent slides stained with hematoxylin (nuclei, purple) and eosin (extracellular matrix, pink). Images are taken in collaboration with Prof. Sevestre at Amiens Hospital).

  most common and widely studied putative precursor lesions of PDAC are the PanINs. The PanINs are classified into three different stages: PanIN1a to PanIN3. As illustrated in Figure 5 normal duct cells have a low columnar epithelium. The epithelium becomes taller at the PanIN1a stage, and at the PanIN1B stage, the epithelium displays papillary structures. During the PanIN2 stage, the ductal cells lose their polarity, showing cell enlargement, and hyperchromasia. In the PanIN3 stage, the cells display advanced lesions with severe nuclear atypia, luminal necrosis, and epithelial cell budding into the ductal lumen (Makohon-Moore and Iacobuzio-Donahue 2016, Ying et al. 2016). The PanIN1 and PanIN2 stages can be classified as low-grade with a low risk of PDAC development. PanIN3 is classified as high-grade and is almost exclusively found in patients with invasive PDAC and recognizes this precursor lesion as the one with the most significant biological potential for progression (Makohon-Moore and Iacobuzio-Donahue 2016, Ying et al. 2016).

Figure 5 .

 5 Figure 5. Morphology of pancreatic intraepithelial neoplasia (PanIN-1-3) Scale bar: 100 mm (Makohon-Moore and Iacobuzio-Donahue 2016).

Figure 6 .

 6 Figure 6. Genetic alterations during PanIN stages. KRAS mutation functions as an initiating mutation, sequentially followed by mutations in the tumor suppressor genes CDKN2A/INK4A, p53, and SMAD4. (Modified from[START_REF] Morris | KRAS, Hedgehog, Wnt and the twisted developmental biology of pancreatic ductal adenocarcinoma[END_REF]).

Figure 7 .

 7 Figure 7. The three steps in PDAC progression. A) Stage 1/Initiation: Cells with initiating driver mutations that escape apoptosis and senescence are fixed in the epithelium. B) Stage 2/Clonal expansion: Cells acquire further mutations as they evolve. C) Stage 3/Progression: Cells can break free from their population, and by degrading the extracellular matrix with the help of immune infiltration, they can migrate and colonize in a new organ (Makohon-Moore and Iacobuzio-Donahue 2016).

Figure 8 .

 8 Figure 8. Graphic overview of the cell cycle regulatory proteins. A) Indicate the cyclins, their respective cyclin-dependent kinases, and inhibitors of the cell cycle checkpoints, controlling the progression through the cell cycle. B Schematic illustration of how the cyclins fluctuate during the cell cycle (Generated with Biorender).

Figure 10 .

 10 Figure 10. Overview of the metastatic cascade. (1) Cancer cells undergo epithelial-to-mesenchymal transition and degrade the extracellular matrix through tumor cell-secreted factors such as metalloproteases. (2) Next, they intravade the bloodstream, where they (3) are in circulation. Finally, (4) they extravade to a local or distant organ where they can (5) colonize and form metastasis

Figure 11 .

 11 Figure 11. Projected cancer-related deaths in 2030, presenting that PDAC is thought to be the second leading cause of cancer in 2030. (Modified from[START_REF] Rahib | Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States[END_REF])),

4 .

 4 Molecular classification of PDACAs described in the 'Pancreatic carcinogenesis' section, the pathophysiology and progression of PDAC are characterized by complex multistep genetic alterations, including KRAS, CDKN2A, TP53, and SMAD4[START_REF] Mizrahi | Pancreatic cancer[END_REF]. Recent advances in molecular classification pathology have impacted clinical practice.In 2011, Collison et al. described three subtypes based on micro-dissected tumor samples: the classical, exocrine-like, and quasi-mesenchymal[START_REF] Collisson | Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy[END_REF]. In 2015,Moffitt et al. subtyped PDAC into

Figure 12 .

 12 Figure 12. Graphic illustration of the symptoms that patients present developing PDAC; usually, these symptoms are not occurring until the time of diagnosis.[START_REF] Mizrahi | Pancreatic cancer[END_REF]

Figure 13 .

 13 Figure 13. Illustration of the solid tumor microenvironment and the cellular and acellular components. Low O2 levels (hypoxia) and glucose levels correspond to high production of H + and lactate, which occur with the increasing distance from the well-vascularized

Figure 14 .

 14 Figure 14. A simplified overview of the differences between the use and effects of oxidative phosphorylation, anaerobic and aerobic glycolysis (Warburg effect). In the presence of oxygen (oxidative phosphorylation) in normal differentiated/non-proliferating tissues, glucose is first metabolized to pyruvate via glycolysis, then completely oxidized in the mitochondria to CO2, producing 36 ATP/glucose. When oxygen is absent (anaerobic glycolysis), cells can redirect the pyruvate generated by glycolysis by generating lactate, producing only 2 ATP/glucose. During the Warburg effect (aerobic glycolysis), proliferating/tumor cells convert glucose to lactate in the presence or absence of oxygen, even though mitochondrial function and oxidative phosphorylation continue to function. To overcome the low amount of ATP generated by cancer cells, utilize ~10% of glucose in biosynthetic pathways such as glutamine or fatty acid metabolism.

Figure 15 .

 15 Figure 15. Simplified schematic representation of the main transporters involved in pH regulation in cancer cells contributes to maintaining the 'reversed pH gradient'. Due to the glycolytic shift in cancer cells, a large amount of acids in the form of H + , lactate, and CO2 are produced, and tumor cells rely on increased acid extrusion to avoid intracellular acidosis. Glucose transporters (GLUT) import glucose to fuel glycolysis. The Na + /H + exchanger 1 (NHE1) extrude H + directly, by the uptake of Na + , while the Na + , HCO3 -cotransporter 1 (NBCn1) imports HCO3 -to neutralize H + . This reaction is facilitated by intracellular carbonic anhydrase II (CAII) forms H2O and CO2, which can passively exit across the plasma membrane. Extracellular membrane-bound CAIX rehydrate H2O and CO2 to HCO3 -, which can be taken up by NBCn1. Monocarboxylate transporters (MCTs) as MCT1 and -4 co-export lactate and H + where the Vacuolar H + -ATPase V-ATPase pumps out H + at the expense of ATP. Overall, these transporters establish a slightly alkaline pH while creating an acidic extracellular tumor microenvironment (Figure generated with Biorender).

Figure 16 .

 16 Figure 16. Schematic representation of the hypothesis proposed by Pedersen et al., 2017. The left panel represents normal pancreatic duct cells and the unique acid (red) -base (blue) transport occurring across membranes in the exocrine pancreas. The right panel represents the acidic microenvironment contributing to PDAC development and progression by adapting and preconditioning epithelial cells to become intraepithelial neoplasias (PanIN) and PDAC(Pedersen et al. 2017).

Figure 17 .

 17 Figure 17. Overview of processes occurring carcinogenesis caused by the acidic microenvironment. Acidosis affects normal cells to acquire genomic instability, which leads to dysplasia. Long-time acidosis creates a selection pressure resulting in metabolic changes

Figure 18 .

 18 Figure 18. Simplified graphic of Store-operated channel entry of Ca 2+ (SOCE). A) At rest, Ca 2+ is stored in the ER. B) The binding of ligands (such as acetylcholine (ACh) or cholecystokinin (CCK) leads to the activation of PLC, which hydrolyzes PIP2 into IP3 and diacylglycerol (DAG). This activates IP3R, which promotes ER Ca 2+ release, leading to activation of STIM1 and hence SOCE (Generated with Biorender).

Figure 19 .

 19 Figure 19. Schematic overview of ion channels, transporters, pumps, and receptors involved in Ca 2+ homeostasis in mammalian cells(Tajada and Villalobos 2020).

Figure 20 .

 20 Figure 20. Ca 2+ signaling and Ca 2+ channels in cell cycle progression. A) Schematic overview of Ca 2+ and CaM regulating cell cycle progression, Ca 2+ /CaM is required at two points during the reentry from G0 and later near the G1/S boundary. Additionally, Ca 2+ /CaM is implicated in the G2/M transition, M phase progression, and exit from mitosis. B) Representation of the proportion of decreased or increased calcium channel expression (arbitrary units A.U. ) and its consequence on cell cycle distribution (Modified from(Kahl and

Figure 21 .

 21 Figure 21. A simple model of Ca 2+ concentrations in the migration process. The cytosolic Ca 2+ concentration is lower overall in the front of the cell, but during migration, the local Ca 2+ concentration increases and creates Ca 2+ pulses (Modified from[START_REF] Tsai | Ca2+ signaling in cytoskeletal reorganization, cell migration, and cancer metastasis[END_REF]).

Figure 22 .

 22 Figure 22. The effect of pH on protein-bound Ca 2+ and the ionized Ca 2+ in blood. When pH decreases, H + competes for the binding site of Ca 2+, and the amount of ionized Ca 2+ increases. On the contrary, when the blood pH increases, albumin and globulin become more negatively charged, which leads to more binding of Ca 2+ , causing the total amount of circulating ionized Ca 2+ to decrease[START_REF] Mccudden | pH-adjusted ionized calcium[END_REF].

Figure 23 .

 23 Figure 23. Graphical overview of Ca 2+ channels known to be either inhibited or activated by acidic pH (Generated with Biorender).

Figure 24 .

 24 Figure 24. Protein expression of TRPC1 in different tissues. Generated with GTEx data and the human protein atlas. (nTPM: normalized protein-coding transcripts per million).

Figure 25 .

 25 Figure 25. Overview of TRPC1 structure and interacting partners. A) TRPC1 topology in the plasma membrane indicating transmembrane regions (S1-S6) and pore domain. B) Heteromultimerisation potential of TRPC. Possible interacting partners from the TRP family, as well as ORAI and STIM proteins. C) Domain structure of TRPC1, as described in the text[START_REF] Dietrich | Classical Transient Receptor Potential 1 (TRPC1): Channel or Channel Regulator?[END_REF]).

Figure 26 .

 26 Figure 26. Hypothetical models of TRPC1 to store-operated Ca 2+ entry. A) When in resting conditions, TRPC1 resides in the intracellular compartments or vesicles. Upon activation, B) ORAI1 interacts with STIM1 (in the ER) and creates an ICRAC current, and TRPC1 will move to the plasma membrane (PM) as shown in C) where TRPC1 interacts with STIM1 and create an ISOC current. The last scenario in D) is where TRPC1 will form a complex with ORAI1 and contribute to an ICRAC and/or ISOC current (Generated with Biorender).

Figure 27 .

 27 Figure 27. Illustration of TRPC1 as an interactome. A) TRPC1 can interact with other ion channels, such as ORAI1, STIM1, TRPCs, or TRPVs leading to Ca 2+ entry. B) TRPC1 can interact with receptors, such as growth factor receptors. C) Pressure activates TRPC1, which forms a complex with SMAD2 and αSMA that activates ERK1/2, leading to IL-6 secretion. D) Thrombin enhances the formation of a TRPC1/RhoA/IP3R complex in an actin filament polymerization-dependent manner, leading to SOCE. E) TRPC1

FIGURE 1 |

 1 FIGURE 1 | Ion channels in exocrine pancreas. Illustration of the structure of acinar and major ductal segments of secretory glands in pancreas. Acinar cells secrete digestive enzymes (orange circles in acini) and an isotonic NaCl rich fluid which transports the enzymes to the ducts. Fluid secretion in acini cells is regulated by a Cl - secretion process. Cl -secretion is activated by [Ca 2+ ] i , from a Ca 2+ influx through SOCs in the basolateral membrane, where Cl -channels, Ca 2+ activated Cl - channels (CaCC) and different types of K + channels are activated to provide the efflux of their respected ions. K + channels also create a driving force by maintaining a negative membrane potential. The negative charge mediated by a high concentration of Cl -ions results in transport of Na + through tight junctions to the luminal space. NaCl makes the driving force for water to efflux through aquaporins and a cell shrinkage. This cell shrinkage reduces [Ca 2+ ] i , which inhibits Cl -and K + efflux through their channels and in parallel activates basolateral transporters and pumps to restore both Cl -and K + . The digestive enzymes are transported in the NaCl isotonic fluid to the ducts, which is low in HCO 3 -concentration in the proximal ducts, but this concentration increases through the transport to the distal duct cells.

FIGURE 2 |

 2 FIGURE 2 | Ion channels in pancreatic ductal adenocarcinoma (PDAC). Illustration of ion channels, which have been shown to have a role in hallmarks of cancer, thereby PDAC development and progression. As cancer cells lose their polarity, the localization of the channels is unknown, and on the illustration, it should be considered that the channels have no particular localization. The aberrant expression in PDAC cells, are shown for; Store-operated channels (SOCs) and transient receptor potential (TRP) channels, K + channels, Cl -channels, aquaporins (AQP), Na + channels and P2X7R. These channels are known to be involved in PDAC development and progression through proliferation, cell cycle progression, differentiation, migration, invasion, metastasis, and apoptosis. The known pathways and mechanism, which have been shown to be involved in these processes are shown in a grey box next to the channel and are mentioned in Table2. The channels shown to be expressed in PDAC, but where the role is unknown are also shown in Table2.

FIGURE 3 |

 3 FIGURE 3 | Ion channels can function as biomarkers in pancreatic ductal adenocarcinoma (PDAC). Illustration of ion channels, where the expression has been shown to be correlated with clinical factors. Most of the ion channels show a high expression in PDAC, which correlates with clinical factors (indicated in grey boxes). Some ion channels have shown to be to have a low expression in PDAC, which correlates with other clinical factors. The ion channels are grouped as progression and aggressiveness markers, diagnostic markers or therapeutic targets. Among all ion channels, their expression (except CFTR) have been shown to be correlated with a low overall survival.

Figure 28 .

 28 Figure 28. All cell lines were grown in pH 7.4 PANC-1 cells were adapted to acidic pH (6.5) for 30 days. After acid adaptation, cells were grown under recovery conditions (pH 7.4) for 14 days.

  TARGET plus SMART pool siRNA, (Dharmacon Research, IL #L-004191-00050 )

  RNA extraction Total RNA extraction was performed using the Trizol extraction method (TRI Reagent®, Sigma) on cell cultures, either transfected or non-transfected. After extraction, the RNA concentration was measured using a NanoDrop 2000 spectrophotometer (Thermofischer). During the assay, we eliminated all samples with A260/A280 and A260/A230 ratios below 1.8, as they were considered impure. During RNA extraction, all surfaces and technical equipment are cleaned with an RNase Away solution (Molecular Bioproducts) to avoid any contamination by RNases. In addition, all the extraction steps are carried out under a chemical extraction hood.

Figure 29 .

 29 Figure 29. Workflow of bisulfite sequencing approach.

  graduation, same temp. for the same row, but increasing temp.from bottom to top of the plate of the insert by digestion  with EcoRI and a 2% agarose gel Make a PCR with M13 F/R primers on 10 clones from one plate and  visualize on 2% agarose gel • DNA extraction DNA was extracted from PANC-1 or MiaPaca2 cell lines, grown in either pH 7.4 or pH 6.5, with Blood & Cell Culture DNA Mini Kit (QIAGEN #13323), following the manufacturer's protocol. After the DNA extraction, the DNA concentration and purity were determined on a Nanodrop, and 100 ng of DNA samples were loaded on a 1% agarose gel to exclude DNA fragmentation. • Bisulfite treatment The first step is to denature the genomic DNA (5 µg) for 20 min at 50 ℃ in a water bath in the presence of NaOH at a final concentration of 0.3 M in a final volume of 20 µL. Next, deamination is carried out by mixing the 20 µL of denatured genomic DNA with 500 µL of a freshly prepared solution containing 2.5 M sodium bisulfite, 0.5 mM hydroquinone, and 0.35 M NaOH, which were then incubated for 3 h at 70 ℃. The bisulfitetreated DNA was then desalted using Wizard DNA Cleanup Kit (Promega, #A7280) and eluted in 45 µL of low TE buffer. The genomic DNA is now converted into single-stranded DNA.

Figure 30 .

 30 Figure 30. Overview of A) Semiquantitative and B) Quantitative sequencing analysis.

Figure 31 .

 31 Figure 31. ORAI, STIM1 and TRPC1 are overexpressed in human PDAC samples. Whisker boxplots of ORAI1, ORAI2, ORAI3, STIM1, and TRPC1 mRNA expression in normal samples (N) and PDAC tumor tissues (T) were generated by GEPIA2 by using data from The Cancer Genome Atlas (TCGA) cohort PAAD and Genotype-Tissue Expression (GTEx) samples. * Indicate p < 0.01.

Figure 32 .Figure 33 .

 3233 Figure 32. ORAI3 and TRPC1 are overexpressed in human PDAC tissue from the local cohort. A) ORAI3 expression in PDAC tissue compared to non-tumor tissue. The marking intensity score designates the expression between 0(low or no expression) and 3 (high expression). ORAI3 in the cytoplasm or the membrane is designated by percentage (n = 12). B) TRPC1 expression in PDAC tissue compared to non-tumor tissue. The marking intensity score designates the expression between 0 (low or no expression) and 3 (high expression). TRPC1 in the cytoplasmor the membrane is designated by percentage (n = 21). Inserts represent negative controls. All images are shown in 160X magnification. * and **** indicate p < 0.05 and 0.0001, respectively.

Figure 34 .

 34 Figure 34. Ca 2+ channels are overexpressed differentially among PDAC cell lines. mRNA expression of A) ORAI1, B) ORAI2, C) ORAI3, D) STIM1, E) STIM2, and F) TRPC1. n = 3-4. *, **, ***, and **** indicate p < 0.05, 0.01, 0.001 and 0.0001, respectively.

Figure 1 .

 1 Figure 1. TRPC1 overexpression correlates with poor overall survival in PDAC patients Whisker boxplots of TRPC1 mRNA expression in normal samples (N) and PDAC tumor tissu were generated by GEPIA2 using data from The Cancer Genome Atlas (TCGA) cohort PAAD Genotype-Tissue Expression (GTEx) samples. * Indicates p < 0.01. (B) Whisker boxplots of T mRNA expression in normal samples (N) and PDAC tumor tissues (T) in both the basal and cla subtypes of PDAC were generated by GEPIA2 using data from the TCGA cohort PAAD and samples. * Indicates p < 0.01. (C) Overall survival analysis of patients within the PAAD cohor either a high or low expression of TRPC1 was generated using SurvExpress. The Kaplan-

Figure 1 .

 1 Figure 1. TRPC1 overexpression correlates with poor overall survival in PDAC patients. (A) Whisker boxplots of TRPC1 mRNA expression in normal samples (N) and PDAC tumor tissues (T) were generated by GEPIA2 using data from The Cancer Genome Atlas (TCGA) cohort PAAD and Genotype-Tissue Expression (GTEx) samples. * Indicates p < 0.01. (B) Whisker boxplots of TRPC1 mRNA expression in normal samples (N) and PDAC tumor tissues (T) in both the basal and classical subtypes of PDAC were generated by GEPIA2 using data from the TCGA cohort PAAD and GTEx samples. * Indicates p < 0.01. (C) Overall survival analysis of patients within the PAAD cohort with either a high or low expression of TRPC1 was generated using SurvExpress. The Kaplan-Meier curve was analyzed using the optimized SurvExpress Maximize algorithm. The number of analyzed patients across time (days) is indicated below the horizontal axis.

Figure 2 .

 2 Figure 2. Cont.

Figure 2 .

 2 Figure 2. TRPC1 is overexpressed in PDAC tissue and cell lines, where it localizes to the plasma membrane. (A) Representative images of TRPC1 expression in human PDAC tissue, performed by immunohistochemistry (IHC). White arrows indicate expression in the cytoplasm (left panel) and the plasma membrane (right panel). Inserts represent negative controls, scale bar = 40 µm. (B) Quantification of TRPC1 marking intensity score between non-tumor and tumor tissue (N = 21). (C) Quantification of TRPC1 expressed in the cytoplasm and (D) membrane (N = 21). (E) Western blot analysis (left panel) and quantification (right panel) of TRPC1 expression in commercial-available PDAC cell lines (n = 3-5). (F) Representative immunofluorescent analysis of TRPC1 in HPNE and PANC-1 cells (n = 3), scale bar = 20 µm. Welch's correction t-test was used to determine the significant difference between control and tumor conditions. *, *** and **** indicate p < 0.05, 0.01, 0.001, and 0.0001, respectively.

Figure 2 .

 2 Figure 2. TRPC1 is overexpressed in PDAC tissue and cell lines, where it localizes to the plasma membrane. (A) Representative images of TRPC1 expression in human PDAC tissue, performed by immunohistochemistry (IHC). White arrows indicate expression in the cytoplasm (left panel) and the plasma membrane (right panel). Inserts represent negative controls, scale bar = 40 µm. (B) Quantification of TRPC1 marking intensity score between non-tumor and tumor tissue (N = 21). (C) Quantification of TRPC1 expressed in the cytoplasm and (D) membrane (N = 21). (E) Western blot analysis (left panel) and quantification (right panel) of TRPC1 expression in commercial-available PDAC cell lines (n = 3-5). (F) Representative immunofluorescent analysis of TRPC1 in HPNE and PANC-1 cells (n = 3), scale bar = 20 µm. Welch's correction t-test was used to determine the significant difference between control and tumor conditions. *, *** and **** indicate p < 0.05, 0.01, 0.001, and 0.0001, respectively.

Figure 3 . 1 Figure 3 .

 313 Figure 3. The knockdown of TRPC1 inhibits PANC-1 cell proliferation and spheroid growth. (A) trypan blue analysis of transfected PANC-1 cells shows the relative number of viable cells compared to siCTRL 24, 48, 72, and 96 h post-transfection (n = 4). (B) Representative images of PANC-1 Figure 3. The knockdown of TRPC1 inhibits PANC-1 cell proliferation and spheroid growth. (A) trypan blue analysis of transfected PANC-1 cells shows the relative number of viable cells compared to siCTRL 24, 48, 72, and 96 h post-transfection (n = 4). (B) Representative images of PANC-1 spheroids grown for nine days (left panel) and quantification of CellTiter-Glo ® assay (right panel) (n = 3), scale bar = 400 µm. Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1; * and ** indicate p < 0.05 and 0.01, respectively.

Figure 4 .

 4 Figure 4. The knockdown of TRPC1 arrests PANC-1 cells in G1/S phases, decreases the expression of CDK6, 2, Cyclin A, and increases the expression of p21 CIP1 . (A) Quantification of cell cycle analysis

Figure 4 .

 4 Figure 4. The knockdown of TRPC1 arrests PANC-1 cells in G1/S phases, decreases the expression of CDK6, 2, Cyclin A, and increases the expression of p21 CIP1 . (A) Quantification of cell cycle analysis representing the percentage of cells in each cell cycle phase of both transfected PANC-1 cells with either siCTRL or siTRPC1 (left panel) and representative data from FACS acquisition (generated with FCS Express 7) (right panel) (n = 4). (B) Western blot analysis of relevant cyclin-dependent kinase complexes and cyclins and their inhibitor p21 CIP1 (left panel). Quantification of western blot analysis representing the expression of proteins in siTRPC1 lysates compared to siCTRL lysates (right panel) (n = 3-4). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1. *, ** and *** indicate p < 0.05, 0.01 and 0.001, respectively.

2. 5 .

 5 The Knockdown of TRPC1 Does Not Affect Ca 2+ Entry nor Store-Operated Ca 2+ Entry and Decreases Cell Proliferation Independently of Extracellular Ca 2+

Figure 5 .

 5 Figure 5. Cont.

Figure 5 .

 5 Figure 5. The knockdown of TRPC1 does not affect Ca 2+ entry and the proliferative role of PANC-1 cells does not depend on extracellular Ca 2+ concentration. (A) Representative traces of Mn 2+ quenching in PANC-1 cells (left panel) and the quantification of siCTRL and siTRPC1 transfected PANC-1 cells (right panel) (number of analyzed cells siCTRL = 342 and siTRPC n = 382). ns indicates non-significant. (B) Representative traces of the classical store-operated Ca 2+ entry protocol. Cells were perfused with 2 mM Ca 2+ for 1 min, then with 0 mM Ca 2+ and 1 µM thapsigargin (Tg) for 12 min, followed by 2 mM Ca 2+ for 5 min, and finally perfused with 0 mM Ca 2+ . ns indicates nonsignificant. (C) Quantification of basal Ca 2+ ratio (0 mM Ca 2+ ) in siCTRL and siTRPC1 transfected PANC-1 cells (number of analyzed cells siCTRL = 303 and siTRPC1 = 280). ns indicates nonsignificant. (D) Quantification of SOCE (2 mM Ca 2 after internal Ca 2+ -store depletion) in siCTRL and siTRPC1 transfected PANC-1 cells (number of analyzed cells siCTRL = 303 and siTRPC n = 280). (E) Trypan blue assay analysis of siCTRL and siTRPC1 transfected PANC-1 cells (for 72 h) either treated with medium containing extracellular Ca 2+ concentrations (+Ca 2+ ), or with medium depleted for extracellular Ca 2+ (-Ca 2+ ), for 48 h (n = 3). Welch's correction t-test and Tukey's multiple comparison test (E) were used to determine significant difference between siCTRL and siTRPC1 conditions. **, and **** indicate p < 0.01, and 0.0001, respectively.

Figure 5 .

 5 Figure 5. The knockdown of TRPC1 does not affect Ca 2+ entry and the proliferative role of PANC-1 cells does not depend on extracellular Ca 2+ concentration. (A) Representative traces of Mn 2+ quenching in PANC-1 cells (left panel) and the quantification of siCTRL and siTRPC1 transfected PANC-1 cells (right panel) (number of analyzed cells siCTRL = 342 and siTRPC n = 382). ns indicates non-significant. (B) Representative traces of the classical store-operated Ca 2+ entry protocol. Cells were perfused with 2 mM Ca 2+ for 1 min, then with 0 mM Ca 2+ and 1 µM thapsigargin (Tg) for 12 min, followed by 2 mM Ca 2+ for 5 min, and finally perfused with 0 mM Ca 2+ . ns indicates non-significant. (C) Quantification of basal Ca 2+ ratio (0 mM Ca 2+ ) in siCTRL and siTRPC1 transfected PANC-1 cells (number of analyzed cells siCTRL = 303 and siTRPC1 = 280). ns indicates non-significant. (D) Quantification of SOCE (2 mM Ca 2 after internal Ca 2+ -store depletion) in siCTRL and siTRPC1 transfected PANC-1 cells (number of analyzed cells siCTRL = 303 and siTRPC n = 280). (E) Trypan blue assay analysis of siCTRL and siTRPC1 transfected PANC-1 cells (for 72 h) either treated with medium containing extracellular Ca 2+ concentrations (+Ca 2+ ), or with medium depleted for extracellular Ca 2+ ( Ca 2+ ), for 48 h (n = 3). Welch's correction t-test and Tukey's multiple comparison test (E) were used to determine significant difference between siCTRL and siTRPC1 conditions. **, and **** indicate p < 0.01, and 0.0001, respectively.

Figure 6 .

 6 Figure 6. The knockdown of TRPC1 decreases PANC-1 cell proliferation through the phosphorylation of AKT pathways. (A) Western blot analysis of phosphorylated AKT (pAKT) and total AKT in transfected PANC-1 cells after mitogen-activation with FBS for either 0 or 30 min (left panel). Quantification of the western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). * indicates p < 0.05. (B) Western blot analysis of phosphorylated ERK1/2 (pERK1/2) and total ERK in transfected PANC-1 cells after mitogen-action for either 0 or 30 min (left panel). Quantification of the western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions. ns indicate non-significant and **** p < 0.0001, respectively.

Figure 6 .

 6 Figure 6. The knockdown of TRPC1 decreases PANC-1 cell proliferation through the phosphorylation of AKT pathways. (A) Western blot analysis of phosphorylated AKT (pAKT) and total AKT in transfected PANC-1 cells after mitogen-activation with FBS for either 0 or 30 min (left panel). Quantification of the western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). * indicates p < 0.05. (B) Western blot analysis of phosphorylated ERK1/2 (pERK1/2) and total ERK in transfected PANC-1 cells after mitogen-action for either 0 or 30 min (left panel). Quantification of the western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions. ns indicate non-significant and **** p < 0.0001, respectively.

Figure 7 .

 7 Figure 7. TRPC1 forms a complex with the PI3K p85↵ subunit and CaM, which is abolished upon TRPC1 knockdown. (A) Representative western blot analysis of co-immunoprecipitation of TRPC1 and PI3K p85↵ subunit with CaM in non-transfected PANC-1 cells. (B) Representative western blot analysis of co-immunoprecipitation of TRPC1 with PI3K p85↵ and CaM in transfected PANC-1 cells (left panel). Quantification of western blot analysis compared to siCTRL represents the effect of TRPC1 KD on the protein interaction (right panel) (n = 3-4). * and **** indicate p < 0.05 and 0.0001, respectively. (C) Representative images of proximity ligation assay (PLA) in transfected PANC-1 cells (left panel). Quantification of PLA where siTRPC1 is compared to the relative number of siCTRL (n = 3. At least 20 images were analyzed for each experiment, see material and methods for details) (right panel). **** indicates p < 0.0001, respectively.

Figure

  Figure S2: (A) Percentage of dead cells analysed by the Trypan Blue Assay after 24, 48, 72 and 96 h after transfection with siCTRL and siTRPC1 in PANC 1 cells, respectively (n = 4). (B) Quantification of Annexin 5 analysis of cells in apoptosis 72 h after transfection with siCTRL and siTRPC1 in PANC 1 cells (n = 3). Methods and materials for Annexin 5 analysis are described below. (C) Quantification of Annexin 5 analysis of cells necrotic cells 72 h after transfection with siCTRL and siTRPC1 in PANC 1 cells (n = 3). Methods and materials for Annexin 5 analysis are described below. ). * indicate p < 0.05 and ns indicate non significant.

Figure S3 :

 S3 Figure S3: Westernblot analysis of different cell cycle regulating proteins 72 h after transfection with siCTRL and siTRPC1 in PANC 1 cells (n= 3 4, no significance was found).

Figure 36 .

 36 Figure 36. The localization of TRPC1 correlates with clinical factors. The plasma membrane localization of TRPC1 correlates with vascular invasion and nerve invasion in samples from patients with PDAC, where TRPC1 is upregulated (n=12). **** indicates p < 0.0001.

Figure 1 .

 1 Figure 1. TRPC1 protein expression is affected by acid adaptation and recovery and favors the plasma membrane localization. (A) Steady state pHi in PANC-1 cells grown in normal pH or acid adaptation conditions and measured in HCO3 -Ringer adjusted to pH 7.4 or 6.5 (X-axis). 6.5 7.4 indicate acid-adapted cells measured in pHe 7.4. (n = 6-11). (B) Western blot analysis (left panel) and quantification (right panel) of TRPC1 expression in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R) (n = 3-4). (C) Western blot analysis (left panel) and quantification (right panel) of TRPC1 expression in PANC-1 spheroids grown under normal pH(7.4), acid adaptation (6.5), or acid recovery conditions (7.4R) for 9 days (n = 3-5). Welch's correction t-test was used to determine the significant difference between different conditions. *, ** and *** indicate p < 0.05 and 0.01 and 0.001 respectively. (D) Representative immunofluorescent analysis of TRPC1 and the membrane protein Na + /HCO3 -co-transporter (NBCn1, used as membrane marker) in PANC-1 cells grown under normal pH(7.4), acid adaptation(6.5) or acid recovery

Figure 1 .

 1 Figure 1. TRPC1 protein expression is affected by acid adaptation and recovery and favors the plasma membrane localization. (A) Steady state pH i in PANC-1 cells grown in normal pH or acid adaptation conditions and measured in HCO 3 Ringer adjusted to pH 7.4 or 6.5 (X-axis). 6.5 ! 7.4 indicate acid-adapted cells measured in pH e 7.4. (n = 6-11). (B) Western blot analysis (left panel) and quantification (right panel) of TRPC1 expression in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R) (n = 3-4). (C) Western blot analysis (left panel) and quantification (right panel) of TRPC1 expression in PANC-1 spheroids grown under normal pH (7.4), acid adaptation (6.5), or acid recovery conditions (7.4R) for 9 days (n = 3-5). Welch's correction t-test was used to determine the significant difference between different conditions. *, ** and *** indicate p < 0.05 and 0.01 and 0.001 respectively. (D) Representative immunofluorescent analysis of TRPC1 and the membrane protein Na + /HCO 3 co-transporter (NBCn1, used as membrane marker) in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R) (n = 3), scale bars = 20 µm. (E) Cell surface biotinylation followed by Western blotting indicating membrane fraction or total lysate of TRPC1. The uncropped blots are shown in File S1.

Figure 2 .

 2 Figure 2. Acid adaptation promotes PANC-1 cell migration but attenuates proliferation, which is restored upon acid recovery. (A) Cell migration of PANC-1 cells grown under normal pH (7.4), acidadapted (6.5), or acid recovery conditions (7.4R) analyzed by Boyden chamber assay (n = 3). (B) Trypan blue analysis of PANC-1 cells grown under normal pH (7.4), acid-adapted (6.5), or acid recovery conditions (7.4R) shows the relative number of viable cells after 24, 48, 72, and 96 h after seeding (n = 3). (C) Representative images of PANC-1 spheroids grown for 9 days and (D) viability quantification performed with CellTiter-Glo ® assay (n = 4-5), scale bar = 400 μm. Welch's correction t-test was used to determine the significant difference between different conditions. ns indicates non-significance. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Figure 2 .

 2 Figure 2. Acid adaptation promotes PANC-1 cell migration but attenuates proliferation, which is restored upon acid recovery. (A) Cell migration of PANC-1 cells grown under normal pH (7.4), acid-adapted (6.5), or acid recovery conditions (7.4R) analyzed by Boyden chamber assay (n = 3). (B) Trypan blue analysis of PANC-1 cells grown under normal pH (7.4), acid-adapted (6.5), or acid recovery conditions (7.4R) shows the relative number of viable cells after 24, 48, 72, and 96 h after seeding (n = 3). (C) Representative images of PANC-1 spheroids grown for 9 days and (D) viability quantification performed with CellTiter-Glo ® assay (n = 4-5), scale bar = 400 µm. Welch's correction t-test was used to determine the significant difference between different conditions. ns indicates non-significance. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

3. 3 .

 3 Knockdown of TRPC1 Accumulates Cells in the G0/G1 Phase and Decreases the Number of Cells in the G2/M Phase

Figure 3 . 3 . 3 .

 333 Figure 3. TRPC1 silencing inhibits cell migration, proliferation, and the growth of PANC-1 spheroids under acid recovery conditions. (A) Cell migration of siTRPC1 cells grown under normal pH (7.4), acid adaptation (6.5), or acid recovery conditions (7.4R) analyzed by Boyden chamber assay (n = 3-4). Tukey's multiple comparison test was used to determine significant differences between conditions. (B) Trypan blue analysis of siTRPC1 PANC-1 cells grown under acid adaptation (6.5), or (C) acid recovery conditions (7.4R), showing the relative number of viable cells 24, 48, 72, and 96 h posttransfection (n = 3-5). (D) Representative images of siTRPC1 transfected PANC-1 spheroids grown for 9 days, and (E) viability quantification performed with CellTiter-Glo ® assay of siTRPC1 transfected spheroids grown under acid adaptation (6.5) or acid recovery (7.4R) (n = 3), scale bar = 400 μm. Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions. ns indicates non-significance. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Figure 3 .

 3 Figure 3. TRPC1 silencing inhibits cell migration, proliferation, and the growth of PANC-1 spheroids under acid recovery conditions. (A) Cell migration of siTRPC1 cells grown under normal pH (7.4), acid adaptation (6.5), or acid recovery conditions (7.4R) analyzed by Boyden chamber assay (n = 3-4). Tukey's multiple comparison test was used to determine significant differences between conditions. (B) Trypan blue analysis of siTRPC1 PANC-1 cells grown under acid adaptation (6.5), or (C) acid recovery conditions (7.4R), showing the relative number of viable cells 24, 48, 72, and 96 h posttransfection (n = 3-5). (D) Representative images of siTRPC1 transfected PANC-1 spheroids grown for 9 days, and (E) viability quantification performed with CellTiter-Glo ® assay of siTRPC1 transfected spheroids grown under acid adaptation (6.5) or acid recovery (7.4R) (n = 3), scale bar = 400 µm. Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions. ns indicates non-significance. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Figure 4 .

 4 Figure 4. TRPC1 silencing accumulates cells in the G0/G1 phase and reduces the number of cells in the G2/M phase in both acid adaptation and recovery conditions. (A) Quantification of cell cycle analysis representing the percentage of cells in each cell cycle phase of non-transfected PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R) (left panel) and representative data from FACS acquisition (right panel). (B) Quantification of cell cycle analysis representing the percentage of cells in each cell cycle phase of siTRPC1 transfected PANC-1 cells grown under acid adaptation (6.5) or (C) acid recovery conditions (7.4R) (left panel), and representative data from FACS acquisition (right panel). Welch's correction t-test was used to determine the significant difference between different conditions. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Figure 4 .

 4 Figure 4. TRPC1 silencing accumulates cells in the G0/G1 phase and reduces the number of cells in the G2/M phase in both acid adaptation and recovery conditions. (A) Quantification of cell cycle analysis representing the percentage of cells in each cell cycle phase of non-transfected PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R) (left panel) and representative data from FACS acquisition (right panel). (B) Quantification of cell cycle analysis representing the percentage of cells in each cell cycle phase of siTRPC1 transfected PANC-1 cells grown under acid adaptation (6.5) or (C) acid recovery conditions (7.4R) (left panel), and representative data from FACS acquisition (right panel). Welch's correction t-test was used to determine the significant difference between different conditions. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively.

Figure 5 .

 5 Figure 5. TRPC1 silencing decreases the expression of CDK6, -1, -2, and cyclin A and increases the expression of p21 CIP1 to a greater extent in acid recovery conditions. (A) Western blot analysis of relevant cyclin-dependent kinase complexes and cyclins and their inhibitor p21 CIP1 from cells grown under acid adaptation (6.5) or acid recovery conditions (7.4R). (B) Quantification of Western blot analysis representing the expression of CDK6, (C) CDK2, (D) CDK1, (E) cyclin A, and (F) p21 CIP1 in siTRPC1 lysates compared to siCTRL lysates from PANC-1 cells grown under acid adaptation (6.5) or acid recovery (7.4R) conditions (n = 3 -6). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively. The uncropped blots are shown in File S1.

Figure 5 .

 5 Figure 5. TRPC1 silencing decreases the expression of CDK6, -1, -2, and cyclin A and increases the expression of p21 CIP1 to a greater extent in acid recovery conditions. (A) Western blot analysis of relevant cyclin-dependent kinase complexes and cyclins and their inhibitor p21 CIP1 from cells grown under acid adaptation (6.5) or acid recovery conditions (7.4R). (B) Quantification of Western blot analysis representing the expression of CDK6, (C) CDK2, (D) CDK1, (E) cyclin A, and (F) p21 CIP1 in siTRPC1 lysates compared to siCTRL lysates from PANC-1 cells grown under acid adaptation (6.5) or acid recovery (7.4R) conditions (n = 3 6). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively. The uncropped blots are shown in File S1.

Figure 6 .Figure 6 .

 66 Figure 6. TRPC1 strongly interacts with the PI3K p85α subunit and CaM in acid adaptation and recovery conditions. (A) Representative immunofluorescent analysis of TRPC1 and the PI3K p85α subunit in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R), scale bars = 20 μm. Mander's R coefficient was used to quantify the co-localization between the two fluorophores (n = 3). (B) Representative images of proximity ligation assay (PLA) in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5), or acid recovery conditions (7.4R), scale bar = 10 μm. (C) Quantification of PLA where conditions are normalized to normal pH conditions (7.4) (n = 3). Welch's correction t-test was used to determine the significant difference between different conditions. ** and *** indicate p < 0.01 and 0.001, respectively. (D) Representative Western blot analysis of co-immunoprecipitation of TRPC1 and PI3K p85α subunit with CaM inFigure 6. TRPC1 strongly interacts with the PI3K p85↵ subunit and CaM in acid adaptation and recovery conditions. (A) Representative immunofluorescent analysis of TRPC1 and the PI3K p85↵ subunit in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R), scale bars = 20 µm. Mander's R coefficient was used to quantify the co-localization between the two fluorophores (n = 3). (B) Representative images of proximity ligation assay (PLA) in PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5), or acid recovery conditions (7.4R), scale bar = 10 µm. (C) Quantification of PLA where conditions are normalized to normal pH conditions (7.4) (n = 3). Welch's correction t-test was used to determine the significant difference between different conditions. ** and *** indicate p < 0.01 and 0.001, respectively. (D) Representative Western blot analysis of co-immunoprecipitation of TRPC1 and PI3K p85↵ subunit with CaM in non-transfected PANC-1 cells grown under normal pH (7.4), acid adaptation (6.5) or acid recovery conditions (7.4R), (n = 3-5). The control pull-down performed with rabbit IgG is presented in Figure S3B. The uncropped blots are shown in File S1.

Figure 7 .Figure 7 .

 77 Figure 7. TRPC1 silencing inhibits the interaction between the PI3K p85a subunit and CaM. (A Representative images of PLA in transfected PANC-1 cells grown under acid adaptation (6.5) acid recovery conditions (7.4R). Scale bar = 10 μm. (B) Quantification of PLA in transfected PAN 1 cells grown under acid adaptation(6.5) or acid recovery conditions (7.4R), where siTRPC1 is com pared to the relative number of siCTRL (n = 3). Welch's correction t-test was used to determine t Figure 7. TRPC1 silencing inhibits the interaction between the PI3K p85a subunit and CaM. (A) Representative images of PLA in transfected PANC-1 cells grown under acid adaptation (6.5) or acid recovery conditions (7.4R). Scale bar = 10 µm. (B) Quantification of PLA in transfected PANC-1 cells grown under acid adaptation (6.5) or acid recovery conditions (7.4R), where siTRPC1 is compared to the relative number of siCTRL (n = 3). Welch's correction t-test was used to determine the significant difference between different conditions. (C) Representative Western blot analysis of co-immunoprecipitation of TRPC1 with PI3K p85↵ and CaM in transfected PANC-1 cells grown under acid adaptation (6.5) or acid recovery conditions (7.4R). The control pull-down performed with rabbit IgG is presented in Figure S3B. (D) Quantification of PI3K p85↵ subunit intensity and (E) CaM intensity from co-immunoprecipitation (n = 3-4). Welch's correction t-test was used to determine the significant difference between different conditions. *, **, and *** indicate p < 0.05, 0.01, and 0.001, respectively. The uncropped blots are shown in File S1.

3. 6 .

 6 The Knockdown of TRPC1 Decreases the Phosphorylation of AKT and ERK1/2 in Acid-Recovered PANC-1 Cells

Figure 8 .

 8 Figure 8. TRPC1 silencing inhibits the phosphorylation of AKT and ERK1/2, notably in acid recovery conditions. (A) Western blot analysis of phosphorylated AKT (pAKT) and total AKT in transfected PANC-1 cells grown in acid adaptation (6.5) conditions or (B) in acid recovery (7.4R) conditions after mitogen activation with FBS for either 0 or 30 min (left panel). Quantification of the Western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). (C) Western blot analysis of phosphorylated ERK1/2 (pERK1/2) and total ERK1/2 in transfected PANC-1 cells grown in acid adaptation (6.5) conditions or (D) in acid recovery conditions (7.4R) after mitogen activation with FBS for either 0 or 30 min (left panel). Quantification of the Western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1. ns indicates non-significance. * and ** indicate p < 0.05 and 0.01, respectively. The uncropped blots are shown in File S1.

Figure 8 .

 8 Figure 8. TRPC1 silencing inhibits the phosphorylation of AKT and ERK1/2, notably in acid recovery conditions. (A) Western blot analysis of phosphorylated AKT (pAKT) and total AKT in transfected PANC-1 cells grown in acid adaptation (6.5) conditions or (B) in acid recovery (7.4R) conditions after mitogen activation with FBS for either 0 or 30 min (left panel). Quantification of the Western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). (C) Western blot analysis of phosphorylated ERK1/2 (pERK1/2) and total ERK1/2 in transfected PANC-1 cells grown in acid adaptation (6.5) conditions or (D) in acid recovery conditions (7.4R) after mitogen activation with FBS for either 0 or 30 min (left panel). Quantification of the Western blot analysis compared to siCTRL either after 0 min or 30 min of mitogen activation (right panel). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1. ns indicates non-significance. * and ** indicate p < 0.05 and 0.01, respectively. The uncropped blots are shown in File S1.

Figure 9 .

 9 Figure 9. TRPC1 reduces basal Ca 2+ entry in acid adaptation and recovery conditions. (A) Representative traces of Mn 2+ quenching in transfected PANC-1 cells grown in normal pH conditions (7.4), (B) in acid adaptation (6.5) conditions, or (C) in acid recovery conditions (7.4R). (D) Quantification of siCTRL and siTRPC1 transfected PANC-1 cells in all three conditions (number of analyzed cells; pH 7.4 siCTRL n = 150 and siTRPC n = 128, pH 6.5 siCTRL n = 405 and siTRPC n = 326, pH 7.4R siCTRL n = 325 and siTRPC n = 214). Tukey's multiple comparison test was used to determine significant differences between conditions. ns indicates non-significance. ** and *** indicate p < 0.01 and 0.001, respectively.

Figure 9 .

 9 Figure 9. TRPC1 reduces basal Ca 2+ entry in acid adaptation and recovery conditions. (A) Representative traces of Mn 2+ quenching in transfected PANC-1 cells grown in normal pH conditions (7.4), (B) in acid adaptation (6.5) conditions, or (C) in acid recovery conditions (7.4R). (D) Quantification of siCTRL and siTRPC1 transfected PANC-1 cells in all three conditions (number of analyzed cells; pH 7.4 siCTRL n = 150 and siTRPC n = 128, pH 6.5 siCTRL n = 405 and siTRPC n = 326, pH 7.4R siCTRL n = 325 and siTRPC n = 214). Tukey's multiple comparison test was used to determine significant differences between conditions. ns indicates non-significance. ** and *** indicate p < 0.01 and 0.001, respectively.

Figure 11 .

 11 Figure 11. (A) Acid adaptation promotes migration but attenuates proliferation, whereas acid recovery impairs this migration but further accelerates proliferation. (B) The fluctuations in the acidic tumor microenvironment affect TRPC1 expression and localization. TRPC1 is downregulated in acid-adapted PANC-1 cells and favors plasma membrane localization, which is maintained in acidrecovered PANC-1 cells, where the expression of TRPC1 is upregulated. In the plasma membrane of acid-adapted and -recovered cells, TRPC1 permits Ca 2+ entry and, in interactions with the PI3K p85α subunit and CaM, regulates PANC-1 cell migration, proliferation, and cell cycle progression. The figure is generated with www.Biorender.com.

Figure S1 .

 S1 Figure S1. (A) TRPC1 mRNA expression evaluated by qPCR 48, 72 and 96 h after transfection with siCTRL and siTRPC1 in acid-adapted PANC-1 cells (6.5) (n = 3-4). (B) TRPC1 mRNA expression evaluated by qPCR 48, 72 and 96 h after transfection with siCTRL and siTRPC1 in acid-recovered PANC-1 cells (7.4R) (n = 3-4). Materials and methods for qPCR are described below. (C) TRPC1 protein expression evaluated 72 h after transfection with siCTRL and siTRPC1 in acid-adapted (6.5) or acid-recovered (7.4R) PANC-1 cells (n = 4, Western blot analysis left panel and quantification right panel). (D) TRPC1 protein expression evaluated 9 days after transfection with siCTRL and siTRPC1 in acid-adapted PANC-1 spheroids, grown in medium pH 6.5 or 7.4R (n = 3, Western blot analysis left panel and quantification right panel). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions. *, ** and *** indicate p < 0.05, 0.01 and 0.001, respectively.

Figure

  Figure S2. (A)Trypan blue assay performed in parallel with Boyden chamber assay (24 h after seeding). Welch's correction t-test was used to determine the significant difference between siCTRL and siTRPC1 conditions (n = 3-4). Ns indicates non-significant. (B) Trypan blue assay performed in parallel with Boyden chamber assay, with (+ Ca 2+ ) or without (-Ca 2+ ) calcium for 24 h in PANC-1 cells grown under normal pH conditions(7.4), (n = 3) (C) in acid-adapted (n = 4) or, (D) acid-recovered conditions (n = 3). Tukey's multiple comparison test was used to determine significant differences between conditions. Ns indicates non-significant. (E) Quantification of Annexin-5 analysis of cells in apoptosis or, (F) necrotic cells 72 h after transfection with siCTRL and siTRPC1 in acid-adapted(6.5) or acid-recovered (7.4R) PANC-1 cells (n = 3). Welch's correction t-test was used to determine the significant differences between siCTRL and siTRPC1 conditions. Ns indicates non-significant. Materials and methods for Annexin-5 analysis are described below.

Figure S3 .

 S3 Figure S3. (A) Westernblot analysis of different cell cycle regulating proteins 72 h after transfection with siCTRL and siTRPC1 in acid-adapted (6.5) or acid-recovered (7.4R) PANC-1 cells (n= 3-4, no significance was found by using Welch's correction t-test). (B) Representative immunoblot of coimmunoprecipitation with a control IgG Rabbit.

Figure S4 .

 S4 Figure S4. Representative immunoblot analysis of PANC-1 cells treated with 72 h of 25 µM W7, including 24 h of starvation, followed by either 0 min or 30 min of mitogen activation with 10% FBS. (A) phosphorlyated AKT (pAKT) and total AKT in normal conditions(7.4). (B) phosphorlyated ERK1/2 (pERK) and total ERK1/2 in normal conditions(7.4). (C) phosphorlyated AKT (pAKT) and total AKT in acid-adapted conditions (6.5). (D) phosphorlyated ERK1/2 (pERK) and total ERK1/2 in acid-adapted conditions(6.5). (E) phosphorlyated AKT (pAKT) and total AKT in acid-recovered conditions (7.4R). (F) phosphorlyated ERK1/2 (pERK) and total ERK1/2 in acid-recovered conditions (7.4R). (n = 3-4). Welch's correction t-test was used to determine the significant difference between conditions. Ns indicates non-significant. * and ** indicate p < 0.05 and 0.01, respectively.

Figure S5 .

 S5 Figure S5. (A) Representative traces of the classical store-operated Ca 2+ entry protocol. Acidadapted (6.5) PANC-1 cells were perfused with 2mM Ca 2+ for 1 min, then with 0 mM Ca 2+ and 1 µM thapsigargin (Tg) for 12 min, followed by 2 mM Ca 2+ for 5 min, and finally perfused with 0 mM Ca 2+ . (B) Quantification of basal Ca 2+ ratio (0 mM Ca 2+ ) and (C) quantification of SOCE (2 mM Ca 2 after internal Ca 2+ -store depletion) in in acid-adapted (6.5) and transfected PANC-1 cells (number of analyzed cells siCTRL = 183 and siTRPC1 = 158). (D) Representative traces of the classical store-operated Ca 2+ entry protocol used on acid-recovered (7.4R) PANC-1 cells. (E) Quantification of basal Ca 2+ ratio (0 mM Ca 2+ ) and (F) quantification of SOCE (2 mM Ca 2 after internal Ca 2+ -store depletion) in acid-recovered (7.4R) and transfected PANC-1 cells (number of analyzed cells siCTRL = 274 and siTRPC1 = 234). Welch's correction t-test was used to determine the significant difference between conditions. Ns indicates non-significant. * indicates p < 0.05.

Figure 38 .

 38 Figure 38. The protein expression of SOC do not change upon TRPC1 KD. A) Representative western blot of SOC in pH 7.4, 6.5 and 7.4R conditions. Quantification of B) ORAI1, C) ORAI3, D) STIM1, and E) STIM2. No significant difference was found between conditions (n=4).

Figure 39 .

 39 Figure 39. The expression of Ca 2+ channels does not change upon acid adaptation. mRNA expression of A) ORAI1, B) ORAI2, C) ORAI3, D) STIM1, and E) STIM2. No significant difference was found between conditions.

Figure 40 .

 40 Figure 40. TRPC1 regulates Ca 2+ entry upon acute acidification. PANC-1 cells grown in pH 7.4 were measured acutely in either pH 7.4 or 6.5 conditions. A) Representative traces from Mn 2+ quench assay. B) Quantification of Mn 2+ quench assay (n = 1).

Figure 42 .

 42 Figure 42. TRPC1 in the plasma membrane correlates with LAMP2 in the cytoplasm. A) The expression of LAMP2 in the cytoplasm or membrane when TRPC1 is expressed in the membrane. B) The expression of NBCn1in the cytoplasm or membrane when TRPC1 is expressed in the membrane (n=20, ***, p < 0.001).

± 10 .

 10 0% (Figure 43C, n = 3, p < 0.001) in acid-adapted PANC-1 and by 81.5 ± 15.7% (n = 3, p < 0.01) in acidadapted MiaPaCa-2 cells. NaV1.6 was significantly downregulated in MiaPaCa-2 cells upon acid adaptation by 44 ± 9.8% (Figure 43D, n = 3, p < 0.01), indicating that the expression of certain Na + channels is affected by acid adaptation.

Figure 43 .

 43 Figure 43. The Na + channels ASIC1 and NaV1.6 are dysregulated in human PDAC tissue and upon acid adaptation. A) The protein expression of NaV1.6 in human PDAC and adjacent non-tumor tissue (n = 2). B) The protein expression of ASIC1 in human PDAC and adjacent non-tumor tissue (n = 20). C) ASIC1 mRNA expression in acid-adapted PANC-1 and MiaPaCa-2 cells, compared to cells grown in normal pH conditions (n = 3). D) NaV1.6 mRNA expression in acid-adapted PANC-1 and MiaPaCa-2 cells, compared to cells grown in normal pH conditions (n = 3).

Figure 44 .Figure 45 .

 4445 Figure 44. Semiquantitative analysis of DNA methylation levels of the ASIC1 promoter region in MiaPaCa-2 cells. Promoter sites in ASIC1 gene within the specifically designed primers (black dotted box). MiaPaCa-2 cells grown at pH 7.4 are more methylated than MiaPaCa-2 cells grown at pH 6.5. The sum of the methylation represents the sum of the methylation levels of the 26 CpG sites calculated by the semiquantitative analysis method. (CpG sites that are not shown are not methylated). (n=2).

Figure 46 .

 46 Figure 46. Quantitative analysis of DNA methylation levels of the ASIC1 promoter region in MiaPaCa-2 cells. Promoter sites in ASIC1 gene within the specifically designed primers (black dotted box). One clone from MiaPaCa-2 cells grown at pH 7.4 are more methylated than MiaPaCa-2 cells grown at pH 6.5 at the 15 th CpG site(n=2, clones in total; 7.4: 14, 6.5: 14).

Figure 47 .

 47 Figure 47. Semiquantitative analysis of DNA methylation levels of the SCN8A promoter region in MiaPaCa-2 cells. Promoter sites in SCN8A gene within the specifically designed primers (black dotted box). MiaPaCa-2 cells grown at pH 6.5 are more methylated than MiaPaCa-2 cells grown at pH 7.4. The sum of the methylation represents the sum of the methylation levels of the 11 CpG sites calculated by the semiquantitative analysis method (n=2).

Figure 48 .

 48 Figure 48. Quantitative analysis of DNA methylation levels of the SCN8A promoter region in MiaPaCa-2 cells. Promoter sites in SCN8A gene within the specifically designed primers (black dotted box). Three clones from MiaPaCa-2 cells grown at pH 6.5 are more methylated at the 16 th , 24 th , 30 th, and 33 rd CpG site (n=2, clones in total 11) than MiaPaCa-2 cells grown at pH 7.4 which were methylated at the 6 th and 31 st CpG site in two different clones (n=2, clones in total 9) (CpG sites which are not showed, are not methylated).

Figure 49 .

 49 Figure 49. Quantitative analysis of DNA methylation levels of the TRPC1 promoter region in PANC-1 cells. Promoter sites in the TRPC1 gene within the specifically designed primers (black dotted box). Five clones from PANC-1 cells grown in pH 7.4 are more methylated at the 6 th -12 th CpG site (n=2, clones in total 12) than PANC-1 cells grown in pH 6.5 were not methylated in any CpG sites (n=2, clones in total 8).

Figure 51 .

 51 Figure 51. Concluding and perspective figure of how acid adaptation and TRPC1 affect PDAC progression. Questions still to be elucidated are marked in red color: Is TRPC1 activated by acidic pH? Does TRPC1 translocate to the plasma membrane by forming a complex with other channels? Are downstream signaling of TRPC1 in acid-recovered conditions Ca 2+ dependent?

Figure 52 .

 52 Figure 52. Concluding and perspective figure of how A) co-culture with stellate cells in a 3D model could affect PDAC proliferation and invasion, and B) a TRPC1 deficient mouse model with fluorescent indicators could provide in vivo inside of the role of TRPC1 and the tumor microenvironment

4 .

 4 Si TRPC1 est impliqué dans le processus de transition épithélio-mésenchymateuse en étudiant les marqueurs épithéliaux et les paramètres de motilité cellulaire.5. Le rôle de TRPC1 en comparant l'agressivité, sous forme de prolifération et d'invasion cellules, entre les différentes conditions de pH et les cellules cancéreuses co-cultivées ou non avec des cellules stellaires pancréatiques.

Figure 53 .

 53 Figure 53. Représentation schématique présentant les divers mécanismes par lesquels TRPC1 module la progression de l'ACP. Les mécanismes restant à élucider sont marqués en rouge : TRPC1 est-il activé par un pH acide ? TRPC1 se transloque-t-il vers la membrane plasmique en formant un complexe avec d'autres canaux ioniques ? Les voies de signalisation activées par TRPC1 dans des conditions de récupération des cellules du milieu acide dépendent-elles du Ca 2+ ?

Figure 1 .

 1 Figure 1. Overview of study procedures and analyses. (A) Overview of the experimental design, and individual and integrative analyses performed. Three cancer cell lines in triplicates (MDA-MB-231, MCF7 and PANC-1) were acid-adapted to pH 6.5 and 7.6 over a period of 1 month and subjected to RNA-sequencing analysis (RNA-seq). Below this, an overview of computational analyses performed is shown. Briefly, we used two strategies to define a shared acid adaptation gene expression profile: by defining sets of statistically significant genes, or by ranking genes by their expression fold change (pH 6.5 vs. 7.6; Figure2). These lists were then subject to over-representation analyses (Figure2), survival analysis in multiple cancers (Figure3), and comparison to tumor-control tissue (ctrl.) RNAseq experiments from patient samples (Figures4 and 5), to identify a final list of genes that are up-/downregulated in acid adaptation as well as in tumor vs. ctrl. experiments, and whose in vivo expression is associated with overall patient survival (Figure6). (B) Principle component analysis (PCA) based on gene expression. The x-and y-axes show principle components (PCs) 1 and 2 in left panel, 3 and 4 in right panel. Percentage explained variance is shown at each axis. Each dot corresponds to one RNA-seq library. Symbol shapes correspond to cell lines and color corresponds to pH treatment. In the left panel, dashed circles show three groups corresponding to cell lines. In the right panel, the dashed line divides samples by pH treatment.

  Figure 1. Overview of study procedures and analyses. (A) Overview of the experimental design, and individual and integrative analyses performed. Three cancer cell lines in triplicates (MDA-MB-231, MCF7 and PANC-1) were acid-adapted to pH 6.5 and 7.6 over a period of 1 month and subjected to RNA-sequencing analysis (RNA-seq). Below this, an overview of computational analyses performed is shown. Briefly, we used two strategies to define a shared acid adaptation gene expression profile: by defining sets of statistically significant genes, or by ranking genes by their expression fold change (pH 6.5 vs. 7.6; Figure2). These lists were then subject to over-representation analyses (Figure2), survival analysis in multiple cancers (Figure3), and comparison to tumor-control tissue (ctrl.) RNAseq experiments from patient samples (Figures4 and 5), to identify a final list of genes that are up-/downregulated in acid adaptation as well as in tumor vs. ctrl. experiments, and whose in vivo expression is associated with overall patient survival (Figure6). (B) Principle component analysis (PCA) based on gene expression. The x-and y-axes show principle components (PCs) 1 and 2 in left panel, 3 and 4 in right panel. Percentage explained variance is shown at each axis. Each dot corresponds to one RNA-seq library. Symbol shapes correspond to cell lines and color corresponds to pH treatment. In the left panel, dashed circles show three groups corresponding to cell lines. In the right panel, the dashed line divides samples by pH treatment.

Figure 1 .

 1 Figure1. Overview of study procedures and analyses. (A) Overview of the experimental design, and individual and integrative analyses performed. Three cancer cell lines in triplicates (MDA-MB-231, MCF7 and PANC-1) were acid-adapted to pH 6.5 and 7.6 over a period of 1 month and subjected to RNA-sequencing analysis (RNA-seq). Below this, an overview of computational analyses performed is shown. Briefly, we used two strategies to define a shared acid adaptation gene expression profile: by defining sets of statistically significant genes, or by ranking genes by their expression fold change (pH 6.5 vs. 7.6; Figure2). These lists were then subject to over-representation analyses (Figure2), survival analysis in multiple cancers (Figure3), and comparison to tumor-control tissue (ctrl.) RNA-seq experiments from patient samples (Figures4 and 5), to identify a final list of genes that are up-/downregulated in acid adaptation as wel as in tumor vs. ctrl. experiments, and whose in vivo expression is associated with overall patient survival (Figure6). (B) Principle component analysis (PCA) based on gene expression. The x-and y-axes show principle components (PCs) 1 and 2 in left panel, 3 and 4 in right panel. Percentage explained variance is shown at each axis. Each dot corresponds to one RNA-seq library. Symbol shapes correspond to cell lines and color corresponds to pH treatment. In the left panel, dashed circles show three groups corresponding to cell lines. In the right panel, the dashed line divides samples by pH treatment.

  Figure1. Overview of study procedures and analyses. (A) Overview of the experimental design, and individual and integrative analyses performed. Three cancer cell lines in triplicates (MDA-MB-231, MCF7 and PANC-1) were acid-adapted to pH 6.5 and 7.6 over a period of 1 month and subjected to RNA-sequencing analysis (RNA-seq). Below this, an overview of computational analyses performed is shown. Briefly, we used two strategies to define a shared acid adaptation gene expression profile: by defining sets of statistically significant genes, or by ranking genes by their expression fold change (pH 6.5 vs. 7.6; Figure2). These lists were then subject to over-representation analyses (Figure2), survival analysis in multiple cancers (Figure3), and comparison to tumor-control tissue (ctrl.) RNA-seq experiments from patient samples (Figures4 and 5), to identify a final list of genes that are up-/downregulated in acid adaptation as wel as in tumor vs. ctrl. experiments, and whose in vivo expression is associated with overall patient survival (Figure6). (B) Principle component analysis (PCA) based on gene expression. The x-and y-axes show principle components (PCs) 1 and 2 in left panel, 3 and 4 in right panel. Percentage explained variance is shown at each axis. Each dot corresponds to one RNA-seq library. Symbol shapes correspond to cell lines and color corresponds to pH treatment. In the left panel, dashed circles show three groups corresponding to cell lines. In the right panel, the dashed line divides samples by pH treatment.

Figure 5 .

 5 Figure 5. Analysis of overlapping genes between pH ranks and tumor-ctrl. ranks with high similarity. (A) Gene ontology (GO) and KEGG pathway analysis of genes upregulated in acid adaptation and correlated in gene expression rank in tumor-ctrl. comparisons in 50 patients. The upper bar plot shows the number of tumor-ctrl. vs. acid adaptation RRHO analyses in which the gene was identified as significant. Bar color indicates log2 expression FC in the acid adaptation experiment (pH 6.5 vs. 7.6). Gene identifiers are shown below. Rows in the bottom panel correspond to selected GO terms with high significance from three sources (BP-Biological process, MF-Molecular function, CC-Cellular

Figure 5 .

 5 Figure 5. Analysis of overlapping genes between pH ranks and tumor-ctrl. ranks with high similarity. (A) Gene ontology (GO) and KEGG pathway analysis of genes upregulated in acid adaptation and correlated in gene expression rank in tumor-ctrl. comparisons in 50 patients. The upper bar plot shows the number of tumor-ctrl. vs. acid adaptation RRHO analyses in which the gene was identified as significant. Bar color indicates log 2 expression FC in the acid adaptation experiment (pH 6.5 vs. 7.6). Gene identifiers are shown below. Rows in the bottom panel correspond to selected GO terms with high significance from three sources (BP-Biological process, MF-Molecular function, CC-Cellular Component) and pathways from the KEGG database. Columns are genes as indicated above. Grey cells indicate that a given gene is labelled with a given GO term or pathway. (B) Gene ontology (GO) analysis of genes downregulated in acid adaptation correlated in gene expression rank in tumor-ctrl. comparisons in 50 patients, arranged as in (A). (C) STRING database analysis of genes from panel (A). Nodes are genes. Connections indicate STRING database evidence of protein interaction. Fully unconnected genes are not shown. (D) STRING database analysis of genes from panel (B), arranged as in (C).

Figure 6 .

 6 Figure 6. Integrative analysis. (A) Overlaps between upregulated genes, OS and RRHO analyses.Venn diagrams show overlaps between acid adaptation-upregulated genes (from Figure2B), of genes significant in overall survival (OS) analysis in at least two types of cancer (based on TCGA data, Figure4), and genes identified as having significant rank correlations between acid adaptation and tumorcontrol gene rank lists (RRHO analysis, Figures4 and 5). (B) Overlaps between downregulated genes, OS and RRHO analyses Venn diagrams arranged as in A but focused on acid adaptationdownregulated genes.

TABLE 1 |

 1 Expression, localization, and the potential role of ion channels in exocrine pancreas.

	Channel type	Species Pancreatic	Pancreatic	Localization	Function	Ref.
			Acini	Duct
	K + Channels
	Kir2, Kir2.3, Kir7.1,	Rat	+		Basolateral	Unknown	(Kim et al., 2000)
	Kir1.3						(Shuck et al., 1997)
	Kir5.1 & Kir4.2	Rat	+	+	Unknown	Kir5.1 forms heteromeric channels	(Pessia et al., 2001)
		Human				with Kir4.2.	(Liu et al., 2000)
						Might have a role in the pH-dependent
						regulation of K + fuxes?
	TALK-1 & TALK-2	Human	+		Unknown	Highly modulated (activation) by NOS	(Duprat et al., 2005)
						and ROS	(Girard et al., 2001)
	TASK-2	Human	+	+	Luminal in duct	Might drive the force for electrogenic	(Duprat et al., 1997)
						HCO3-secretion?	(Duprat et al., 2005)
							(Hayashi and Novak, 2013)
	minK	Rat	+		Unknown in acinar		(Kim and Greger, 1999)
	KCNQ1(KvLQT1/	Mouse	+	+	Luminal in duct	Cell volume regulation in ducts	(Kottgen et al., 1999)
	Kv7.) & KCNE1	Rat			Lateral and basolateral in acini	Membrane potential in acini	(Warth et al., 2002)
	(minK)					Electrolyte/enzyme secretion with	(Warth and Barhanin, 2002)
						minK	(Demolombe et al., 2001)
							(Hayashi et al., 2012)
	KCa1.1 (BK, maxi-K)		+	+	Basolateral in acini/Luminal in	Activate luminal secretion	(Gray et al., 1990a)
					duct		(Hede et al., 1999)
							(Hede et al., 2005)
	BK (maxi-K)	Pig		+	Basolateral	Cl -secretion	(Iwatsuki and Petersen, 1985a)
							(Iwatsuki and Petersen, 1985b)
							(Suzuki et al., 1985)
							(Petersen and Findlay, 1987)
							(Gallacher et al., 1984)
	BK (maxi-K)	Human		+	Unknown		(Petersen et al., 1985)
	BK (maxi-K)	Guinea-	+		Luminal	Regulation of HCO 3 -secretion-	(Venglovecz et al., 2011)
		pig				induced by the bile acid
						Chenodeoxycholate
	BK (maxi-K)	Rat	+		Basolateral	Might regulate membrane potential	(Gray et al., 1990a)
						hyperpolarzation?	(Hede et al., 2005)
	IK1 (KCa3.1)	Dog (cell	+	+	Basolateral/Luminal	Driving force for Cl -efflux	(Nguyen and Moody, 1998)
		lines,			in duct	Regulate HCO 3 -secretion	(Thompson-Vest et al., 2006)
		PDEC)				Hyperpolarization	(Jung et al., 2006)
	IK1 (KCa3.1)	Mouse		+	Luminal/basolateral	Setting the RMP. Involvement in anion	(Hayashi et al., 2012)
		&				and K + transport in stimulated ducts
		Human
	IK1 (KCa3.1)	Human					(Ishii et al., 1997)
		& Rat					(Joiner et al., 1997)
							(Hede et al., 2005)
	Kv3.4	Mouse	+		Unknown	Unknown	(Kalman et al., 1998)
	Kv1.5	Human	+		Unknown	Might regulate membrane potential?	(Bielanska et al., 2009)
							(Venglovecz et al., 2015)
	Kv11.1 (ERG1)	Human		+	Luminal	Might regulate membrane potential?	(Hayashi et al., 2012)
	Kv10.2	Human		+	Luminal	Might regulate membrane potential?	(Hayashi et al., 2012)
	Calcium
	ORAI1	Mouse	+		Both in acinar	Might drive exocytosis of secretory	(Lur et al., 2009)
					Mostly basolateral	granules or stimulate fluid and	(Hong et al., 2011)
						electrolyte secretion?
	ORAI2	Dog		+	Unknown	Unknown	(Kim et al., 2013)
	ORAI3	Dog		+	Basolateral	Unknown	(Kim et al., 2013)
	STIM1	Mouse	+		Both in acinar	Might drive exocytosis of secretory	(Lur et al., 2009)
					Mostly basolateral	granules or stimulate fluid and	(Hong et al., 2011)
						electrolyte secretion?
	TRPC1	Mouse	+	+	Lateral side of the basolateral	Might drive exocytosis of secretory	(Hong et al., 2011)
					membrane	granules or stimulate fluid and
						electrolyte secretion?
	TRPC3	Mouse	+	+	Basolateral in acini	Might drive exocytosis of secretory
						granules or stimulate fluid and
						electrolyte secretion?

[START_REF] Kim | Homer 1 mediates store-and inositol 1,4,5-trisphosphate receptor-dependent translocation and retrieval of TRPC3 to the plasma membrane[END_REF]

)

(Kim et al., 2009)

(Continued)

Schnipper et al.

Ion Channels in Exocrine Pancreas

TABLE 1 |

 1 Continued

	Channel type	Species Pancreatic	Pancreatic	Localization	Function	Ref.
			Acini	Duct
	TRPC6	Mouse	+		Unknown	Might drive exocytosis of secretory	(Kim et al., 2006)
						granules or stimulate fluid and
						electrolyte secretion?
	TRPV6	Dog		+	Unknown	Unknown	(Kim et al., 2013)
	TRPM7	Zebra		+	Luminal	Regulating epithelial cell-cycle	(Yee et al., 2011)
		fish				progression, growth, and,
						consequently, acinar and ductal
						morphogenesis, also during
						embryogenesis
	TRPM8	Human	+	(To some	Unknown	Unknown	(Yee et al., 2010)
				extend)
	Chloride
	CFTR	Rat	+	+	Luminal in ducts	Drive fluid and HCO 3 -secretion	(Gray et al., 1988)
		Guinea-					(Gray et al., 1989)
		pig					(Gray et al., 1990b)
		Dog					(Marino et al., 1991; Gray et al.,
		Human					1993)
							(Zeng et al., 1997)
	CaCC	Mouse	+	+	Luminal on both	Drive fluid and HCO 3 -secretion	(Park et al., 2001)
	(TMEM16A)	Rat
		Guniea-
		pig
		Dog
		Bovine
	Sodium
	ENaC (d -subunit)	Mouse	+	+	Luminal	Unknown	(McDonald
		Human

[START_REF] Al-Nakkash | Bovine pancreatic duct cells express cAMP-and Ca(2+)-activated apical membrane Cl-conductances[END_REF]

)

[START_REF] Winpenny | Calcium-activated chloride conductance is not increased in pancreatic duct cells of CF mice[END_REF][START_REF] Nguyen | Characterization of two distinct chloride channels in cultured dog pancreatic duct epithelial cells[END_REF]

)

[START_REF] Yokoyama | Different immunohistochemical localization for TMEM16A and CFTR in acinar and ductal cells of rat major salivary glands and exocrine pancreas[END_REF]

)

[START_REF] Zdebik | Chloride channels in the luminal membrane of rat pancreatic acini[END_REF]

)

(Wang and Novak, 2013

)

(Park et al., 2001

)

[START_REF] Yang | TMEM16A confers receptor-activated calcium-dependent chloride conductance[END_REF]

)

[START_REF] Bergmann | Discovered on gastrointestinal stromal tumor 1 (DOG1) is expressed in pancreatic centroacinar cells and in solid-pseudopapillary neoplasms-novel evidence for a histogenetic relationship[END_REF]

)

[START_REF] Ousingsawat | Loss of TMEM16A causes a defect in epithelial Ca2+dependent chloride transport[END_REF]

)

[START_REF] Huang | Studies on expression and function of the TMEM16A calcium-activated chloride channel[END_REF]

)

[START_REF] Randriamampita | Calcium and secretagogues-induced conductances in rat exocrine pancreas[END_REF]

)

[START_REF] Kasai | Cytosolic Ca2+ gradients triggering unidirectional fluid secretion from exocrine pancreas[END_REF]

)

[START_REF] Marty | Three types of calciumdependent channel in rat lacrimal glands[END_REF]

)

[START_REF] Gray | Two types of chloride channel on duct cells cultured from human fetal pancreas[END_REF]

)

(Gray et al., 1990b)

TABLE 2 |

 2 Profile

	Channel	Profile expression Up/	Cell line/Solid	Driving PDAC	Downstream regulation	Channel expression	Ref.
		Downregulated (method used	tumor	formation in	and signaling	correlates with clinical
		for expression profiling)		form of		factors
	Potassium
	KCa3.1	Upregulated	BxPC-3	Proliferation	Ras	High expression:	(Bonito et al., 2016)
		(mRNA, IHC, Microarray,	Capan-1	Cell cycle	Oxidative	Low overall survival	(Jager et al., 2004)
		electrophysiological,	MiaPaCa-2	progression	Phosphorylation	Advanced tumor stage	(Hayashi et al.,
		transcriptome data, TCGA	PANC-1	Migration			2012)
		analysis)	Solid tumors	Invasion			(Jiang et al., 2017)
							(Shen et al., 2017)
							(Kovalenko et al.,
							2016)
							(Zaccagnino et al.,
							2016)
	KCa4.1	mRNA	Capan-1				(Hayashi et al.,
			PANC-1				2012)
	KCa4.2	mRNA	CFPAC				(Hayashi et al.,
			PANC-1				2012)
	K v 1.3	Downregulated in tumors	AsPC-1	Apoptosis		Low expression:	(Brevet et al., 2009)
		(mRNA, IHC)	BxPC-3	Hypermethylation		Hypermethylation correlates	(Zaccagnino et al.,
		Upregulated in cell lines	Capan-1			with survival (not significant)	2017)
		(mRNA, protein)	Colo357				(Bielanska et al.,
			MiaPaCa-2				2009)
			Panc-89
							(Continued)

expression of ion channels in pancreatic ductal adenocarcinoma (PDAC) cell lines and tissue and how they are involved in driving PDAC formation and how channel expression correlate with clinical factors.

TABLE 2 |

 2 Continued

	Schnipper et al.				Ion Channels in Exocrine Pancreas
	Channel	Profile expression Up/	Cell line/Solid	Driving PDAC	Downstream regulation	Channel expression	Ref.
		Downregulated (method used	tumor	formation in	and signaling	correlates with clinical
		for expression profiling)		form of		factors
			Panc-TUI
			Solid tumors
	K v 1.5	Upregulated	Solid tumors				(Bielanska et al.,
		(IHC)					2009)
	K v 7.1	Downregulated	A818-6				(Tawfik et al., 2020)
		(Microarray, Nanostring	HPAF				(Fong et al., 2003)
		electrophysiological)	Solid tumors				(Zaccagnino et al.,
							2016)
	minK	Downregulated	Solid tumors				(Zaccagnino et al.,
		(Microarray)					2016)
	K v 10.1	Unknown	Solid tumors	Tumor growth	Blocking shows antitumor		(Gomez-Varela
					activity		et al., 2007)
							(Pardo and
							Stuhmer, 2014)
	K v 11.1	Upregulated	BxPC-3	Proliferation	miR96	High expression:	(Manoli et al., 2019)
		(mRNA, protein, IHC, Sequencing	CFPAC-1	Cell cycle	EGFR-pathway	Low overall survival	(Lastraioli et al.,
		analysis)	MiaPaCa-2	progression	ERK1/2	High Ki67 expression	2015b)
			PANC-1	Migration	F-actin assembly	Advanced tumor grade	(Zhou et al., 2012)
			SW1990	Invasion			(Feng et al., 2014)
			T3M4	Metastasis			(Sette et al., 2013)
			Solid tumors
	TREK-1	Upregulated	AsPC-1	Proliferation	pH/Vm activated		(Sauter et al., 2016)
		(protein, electrophysiological)	BxPC-3	Migration
			Capan-1
	TASK-1	Downregulated	Solid tumors				(Williams et al.,
		(Microarray database analysis)					2013)
	TASK-2	(mRNA, protein	HPAF				(Fong et al., 2003)
		electrophysiological)
	TWIK-1	Upregulated	Solid tumors				(Williams et al.,
		(Microarray database analysis)					2013)
	TWIK-3	Downregulated	Solid tumors	Cell			(Zaccagnino et al.,
		(Microarray)		differentiation			2016)
	Kir3.1	Upregulated	Solid tumors				(Brevet et al., 2009)
		(mRNA, IHC)
	Kir4.2	Downregulated	Solid tumors	Cell			(Zaccagnino et al.,
		(Microarray)		differentiation			2016)
	Kir5.1	Downregulated	Solid tumors				(Zaccagnino et al.,
		(Microarray)					2016)
	Sodium
	VGSC	Downregulated	MiaPaCa-2	Proliferation	Inhibition of growth with		(Sato et al., 1994;
	SCN9A	(Microarray)	CAV		phenytoin		Koltai, 2015)
	SCNA3		Solid tumors				(Zaccagnino et al.,
							2016)
	ASIC1	Upregulated	AsPC-1	EMT	RhoA		(Zhu et al., 2017)
		(mRNA, protein, IHC)	BxPC-3	Metastasis
			PANC-1
			SW1990
			Solid tumors
	ASIC3	Upregulated	AsPC-1	EMT	RhoA		(Zhu et al., 2017)
		(mRNA, protein, IHC)	BxPC-3	Metastasis
			PANC-1
			SW1990
			Solid tumors
	Calcium
	ORAI1	Different expression in different	AsPC-1	Apoptosis	Calcium-regulated Akt/		(Kondratska et al.,
		cell lines	BxPC-3	Proliferation	mTOR/NFAT signaling		2014)
		(mRNA, protein)	Capan-1				(Khan et al., 2020)
		Downregulated	MiaPaCa-2				(Zaccagnino et al.,
		(Microarray)	PANC-1				2016)
			Solid tumors
							(Continued)

TABLE 2 |

 2 Continued

	Schnipper et al.				Ion Channels in Exocrine Pancreas
	Channel	Profile expression Up/	Cell line/Solid	Driving PDAC	Downstream regulation	Channel expression	Ref.
		Downregulated (method used	tumor	formation in	and signaling	correlates with clinical
		for expression profiling)		form of		factors
			HPAFII		EGFR, Ki-67, and CK7,	Large tumor size	(Zou et al., 2019)
			Solid tumors		down-regulation of E-	Lymph node metastasis	(Direito et al., 2017)
					cadherin and vimentin	Tumor differentiation	(Zaccagnino et al.,
						Invasion	2016)
	AQP4	(mRNA)	Capan-1				(Burghardt et al.,
			Capan-2				2003)
			Solid tumors
	AQP5	Upregulated	Capan-1	Proliferation	Simultaneous	High expression:	(Burghardt et al.,
		(mRNA, IHC)	Capan-2	Differentiation	overexpression of	Low overall survival	2003)
			HPAF	EMT	EGFR, Ki-67, and CK7.	Tumor differentiation	(Direito et al., 2017)
			Solid tumors		Downregulation of E-
					cadhering and vimentin.
	AQP8	mRNA	Solid tumors				(Burghardt et al.,
		Downregulated (Microarray)					2003)
							(Zaccagnino et al.,
							2016)
	Ionotropic
	receptors
	P2X4	mRNA	AsPC-1 BxPC-				(Kunzli et al., 2007)
			3 Capan-1				(Hansen et al., 2008)
			CFPAC-1				(Giannuzzo et al.,
			MiaPaCa-2				2015)
			PANC-1
	P2X6	mRNA	AsPC-1 BxPC-				(Kunzli et al., 2007)
			3 Capan-1				(Hansen et al., 2008)
			CFPAC-1				(Giannuzzo et al.,
			MiaPaCa-2				2015)
			PANC-1
	P2X7	Upregulated	AsPC-1 BxPC-	Proliferation	PKC, PLD		(Giannuzzo et al.,
		(mRNA, protein, IHC)	3 Capan-1	Apoptosis	ERK1/2, and JNK		2015)
			CFPAC-1	Invasion	Decreased nitric oxide		(Kunzli et al., 2007)
			MiaPaCa-2	Migration	synthase		(Hansen et al., 2008)
			PANC-1				(Choi et al., 2018)
			Solid tumors
	NMDAR	(IHC, Microarray)	BxPC-3	Proliferation			(Li and Hanahan,
			HPAFII	Survival			2013)
			SUIT2				(North et al., 2017)
			Solid tumors

Table 2 .

 2 Genetic

	Cell line	Origin	Differentiation	KRAS	p53	CDKN2A/p16	SMAD4/DPC4
			& tumor grade
	HPNE	Pancreas		None	None	None	Unknown
	Colo357	Lymph node	Well, G1-G2	12 Asp	Wildtype	HD, Wildtype	HD or Wildtype
		metastasis		mutation
	BxPC-3	Primary tumor	Moderate to	Wild type	220 Cys	HD, Wildtype	HD or Wildtype
			poor, G2		mutation
	AsPC-1	Ascites	Poor, G2	12 Asp	Frameshift	Δ2 bp frameshift	HD or Wildtype
				mutation	mutation, 135	mutation, HD,
					Δ1 bp,	wildtype
	MiaPaCa-2	Primary tumor	Poor, G3	12 Cys	248 Trp	HD	Wild type
				mutation	mutation
	PANC-1	Primary tumor	Poor, G3	12 Val	176 Ser	HD	Wild type
				mutation	mutation

alterations in human pancreatic cell lines. HD homozygous deletion, Δ-deletion, bp-base pair (Modified from:

Table 3 .

 3 Components of complete hTERT-HPNE medium DMEM without glucose (Sigma Cat#D-503). Medium M3 Base(Incell Corp.

	Cat#M300F-500) Fetal Bovine Serum was purchased from PAN Biotech (Cat#P30-3031, PAN Biotech), and 10% was added as a final
	concentration.
	Components	pH 7.4	pH 6.5
	RPMI-1640	500 ml	4.2 g
	NaHCO3 -	24 mM	3 mM
	NaCl	5 mM	26 mM
	FBS	10%	10%
	Sodium Pyruvate	1 mM	1 mM
	GlutaMax	1%	1%

Table 4 .

 4 Components

of pH corrected

RPMI-1640 medium. For RPMI-1640 pH 7.4

, 500 ml of prepared media was used (Sigma-Aldrich, Cat#R8758), for pH 6.5 RPMI-1640 powder was used for 500 ml of sterile water (Sigma-Aldrich, Cat#R6504-10X1L). Fetal Bovine Serum was purchased from PAN Biotech (Cat#P30-3031, PAN Biotech).

Table 5 .

 5 siRNA used for transfections

Table 6 .

 6 Composition of basic extracellular Ca 2+ imaging medium.

Table 7

 7

. Composition of RT reaction mixture

(1 reaction)

Table 8 .

 8 Composition of the qPCR reaction mixture(1 reaction)

	1.6 µL

Table 10 .

 10 Composition of Ringer solutions for pHi measurements at pH7.4 and pH 6.5.

Table 11 .

 11 Composition of KCl solutions for pHi calibrations.

	KCl Ringer	Concentration
	KCl	140 mM
	K2HPO4	1 mM
	CaCl2	1 mM
	MgCl2	0.5 mM
	MOPS/TES/HEPES (MTH)	3.3/3.3/5 mM

By adding KCl Ringers with different pHs, BCECF at different pHi values can be measured, and a calibration curve can be made (Appendix 1). In this study, we used KCl Ringers (Table

11

) with pH

6.6, 7.0, 7.2, and 7.4

at 37°C infused, and 10 µM Nigericin was added.

Table 12 .

 12 Antibodies used for IF analysis

Table 13

 13

		Host	Dilution Pretreatment/incubation time/	Distributor	Reference
	for IHC			incubation time with secondary
				antibody (min)
	TRPC1	Goat	1/50	CC1/64/32	Abcam	Ab110837
	ORAI1	Rabbit	1/400	CC1/64/32	Sigma Aldrich O8264-200UL
	ORAI2	Rabbit	1/500	CC1/64/32	Abcam	Ab155216
	ORAI3	Rabbit	1/50	CC1/64/32	Sigma Aldrich	HPA015022
	STIM1	Mouse	1/100	CC1/64/32	Santa Cruz	Sc-166840
	STIM2	Rabbit	1/400	CC1/64/32	Alomone	ACC-064
	TRPM7	Goat	1/500	CC1/64/32	Abcam	ab729
	ASIC1	Rabbit	1/400	CC1/64/32	Alomone	ASC-014
	NaV1.6	Rabbit	1/250	CC1/36/32	Abcam	Ab65166
	NBCn1	Rabbit	1/400	CC1/64/32	Abcam	Ab82335
	LAMP2	Rabbit	1/800	CC1/64/32	Abcam	Ab18528

. Antibodies used for IHC. (The cell conditioning solution; CC1)

  When pHi decreases, histones are globally deacetylated by histone deacetylases (HDACs), resulting in more condensed chromatin structure and repression of the gene. The released acetate anions from this process are co-exported with protons through MCTs to maintain the pHi (McBrian et al. 2013). In contrast, when pHi increases, histone acetyltransferases (HAT) are activated, and global histone acetylation increases, resulting in accessible chromatin and gene activation (McBrian et al. 2013). Although the relation between pHi and histone acetylation has been reported, little is known about the pHi-dependent mechanisms of gene expression due to gene promoter methylation.

  canalaire pancréatique (ACP), présentant une survie globale à 5 ans inférieure à 10 %, est l'un des cancers les plus meurtriers au monde. Étant donné que l'ACP devrait devenir la principale cause de mortalité par cancer à l'échelle mondiale d'ici 2030[START_REF] Rahib | Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States[END_REF], une meilleure compréhension des mécanismes moléculaires sous-jacents à la maladie est nécessaire dans le but de développer des thérapies et biomarqueurs efficaces.Plusieurs études ont montré qu'une dérégulation de sécrétion de suc pancréatique exocrine peut contribuer au développement de pathologies du pancréas exocrine, y compris l'ACP. Les principaux rôles du tissu pancréatique exocrine sain sont la sécrétion d'enzymes et de fluides riches en ions bicarbonates, au cours de laquelle les canaux ioniques participent à affiner ces processus biologiques. Par conséquent, la dérégulation des canaux ioniques tant au niveau de leur expression mais également de leur activité est liée à un grand nombre de pathologies(Kim, 2014). De plus, cette dérégulation peut également entraîner la transformation d'un comportement cellulaire normal en un comportement malin[START_REF] Litan | Cancer as a channelopathy: ion channels and pumps in tumor development and progression[END_REF]. Au cours des dernières décennies, une expression aberrante de nombreux canaux ioniques a été rapportée dans divers typesSwietach et al. 2014, Boedtkjer et Pedersen 2020, Andersen et al. 2021). L'espace interstitiel des tumeurs solides est généralement acide et bien que des valeurs de pHE aussi basses que 5,6 ont été mesurées, la plupart des valeurs se situent entre 6,4 et 7. En revanche, les zones bien vascularisées présentent un pHE plus proche de la neutralité(Vaupel et al. 1989, Helmlinger et al. 1997, Rohani et al. 2019, et les échantillons d'ACP humains à l'aide de la base de données TCGA-PAAD d'échantillons normaux et tumoraux. Nous avons constaté que les canaux ORAI1, ORAI2, ORAI3, TRPC1 ainsi que la protéine STIM1 étaient surexprimés dans les tissus d'ACP. De plus, les résultats de notre cohorte locale ont confirmé que ORAI3 et TRPC1 étaient significativement surexprimés dans le tissu d'ACP humain par rapport au tissu non tumoral adjacent. Fait intéressant, nous avons observé que les canaux ORAI3 et TRPC1 étaient localisés au niveau membranaire dans les cellules tumorales, tandis que leur expression était cytoplasmique dans les cellules non tumorales. En outre, nous avons étudié l'expression transcriptionnelle de ces canaux Ca 2+ dans différentes lignées cellulaires d'ACP. Durant ce travail, nous avons démontré que les profils d'expression des canaux Ca 2+ différaient entre les lignées cellulaires. En effet, TRPC1 était surexprimé dans la lignée cellulaire d'ACP très agressive PANC-1 par rapport à la lignée cellulaire HPNE de type normal. ORAI3 et STIM2 semblaient être surexprimés dans les lignées cellulaires cancéreuses moins agressives BxPC-3 et AsPC-1. STIM1 était significativement surexprimé dans les cellules AsPC-1 et PANC-1. L'ensemble de ces résultats indiquent que STIM, ORAI et TRPC1 sont surexprimés dans le tissu d'ACP humain, au moins au niveau transcriptomique. De plus, ils sont exprimés de manière différentielle entre les lignées cellulaires. Le Dans cette lignée, TRPC1 présentait majoritairement une localisation au niveau de la membrane plasmique, que nous n'avons pas retrouvé dans les cellules HPNE dans lesquelles TRPC1 était localisé au niveau cytosolique. Ces données étaient en accord avec ce que nous avons trouvé dans le tissu d'ACP humain.Pour étudier les mécanismes en aval par lesquels TRPC1 régule les processus cancéreux pancréatique, nous avons développé un modèle de perte de fonction de TRPC1 grâce à une approche siARN. L'efficacité de cette invalidation moléculaire de TRPC1 a été validée par qPCR et Western Blot.Par la suite, nous avons étudié le rôle de TRPC1 dans la prolifération des cellules PANC-1 et de sphéroïdes pancréatiques. Nous avons démontré que l'inhibition moléculaire de TRPC1 diminuait la prolifération cellulaire et la viabilité des sphéroïdes. De plus, une analyse par cytométrie en flux, a révélé que siTRPC1 entraînait une accumulation de cellules dans la phase G1 ainsi qu'un nombre réduit de cellules dans la phase S. Ces observations étaient en corrélation avec la diminution de l'expression des protéines de régulation du cycle cellulaire CDK6, CDK2 et la cycline A, ainsi qu'une augmentation de l'expression de p21.Nous avons cherché à déterminer la signature Ca 2+ spécifique à TRPC1 dans les cellules PANC-1. En effet, nous avons constaté que le siTRPC1 n'affecte ni l'entrée calcique basale, ni l'entrée de calcium dépendante des stocks calciques (SOCE). De plus, le rôle prolifératif des cellules PANC-1 ne dépendait pas de l'entrée calcique, car nous n'avons pas trouvé de différences significatives entre la prolifération des cellules PANC-1 cultivées dans un milieu de culture normal et un milieu présentant une faible concentration de Ca 2+ Les canaux ioniques, souvent appelés capteurs du microenvironnement, peuvent être affectés par les changements de pH extracellulaire (pHe) et impacter les voies de signalisation(Petho et al. 2020). TRPC1 est connu pour être activé suite à la variation de pression et à l'hypoxie(Fels et al. 2016, Azimi et al. 2017, Radoslavova et al. 2022). À ce jour, il n'a pas été démontré comment l'acidose peut affecter TRPC1, bien que d'autres canaux de la famille TRPC sont activés par l'acidification. L'objectif de ce 2 ème article était d'étudier si le microenvironnement tumoral acide pourrait affecter la fonction de TRPC1 et les voies de signalisation sous-jacentes. nombre de cellules dans la phase G0/G1 et une diminution dans la phase G2/M. Par ailleurs, les cellules récupérées à l'acide ont montré un nombre accru de cellules en phase S. L'invalidation moléculaire de TRPC1 a entraîné une nouvelle accumulation de cellules dans la phase G0/G1 et une réduction dans la phase G2/M. Ce phénotype a été maintenu dans des conditions de récupération.Nous avons précédemment montré que TRPC1 forme un complexe avec PI3K et CaM. Ainsi, nous avons cherché à démontrer le rôle du microenvironnement tumoral acide et de TRPC1 en association avec la signalisation PI3K. Par imagerie confocale et analyse de colocalisation, nous avons montré que TRPC1 était colocalisé avec la sous-unité PI3K-p85α dans des conditions adaptées au pH acide puis se maintenait après la récupération des cellules dans un milieu normal. Ces résultats ont été confirmés par PLA et co-IP, qui ont révélé une forte interaction entre TRPC1 et la sous-unité PI3K-p85α dans les cellules PANC-1 cultivées dans un pH 6,5. TRPC1 interagit également avec la protéine CaM dans toutes les conditions de pH. Ces interactions ont été atténuées lors de l'extinction moléculaire de TRPC1.Les expériences d'imagerie calciques ont révélé que l'entrée basale de Ca 2+ était augmentée dans les cellules récupérées à l'acide par rapport aux cellules cultivées dans des conditions normales et acides. De plus, siTRPC1 n'affectait l'entrée du Ca 2+ que dans les cellules adaptées au pH acide et récupérées. En revanche, siTRPC1 n'a aucun effet sur l'entrée calcique capacitive (SOCE) dans les cellules PANC-1 adaptées à l'acide ou récupérées.Nous avons, par la suite, cherché à savoir si les niveaux de Ca 2+ extracellulaire pourrait influencer la migration et la prolifération cellulaires. Nous avons constaté que la faible concentration de Ca 2+ extracellulaire diminuaient la prolifération et la migration cellulaires uniquement dans des conditions adaptées et récupérées du milieu acide, mais pas lorsque les cellules sont cultivées dans un milieu de culture à pH normal. Dans ces CaM et l'entrée de Ca 2+ , qui en retour, augmente la migration et la prolifération des cellules PANC-1, via les voies de signalisation AKT et ERK1/2. 4. La localisation cellulaire de TRPC1 est liée au microenvironnement acide de la tumeur : étude sur les échantillons de tissus non cancéreux et cancéreux du pancréas.L'objectif de cette étude était de déterminer si l'expression de TRPC1 est localisée dans les parties acides de la tumeur. Nous avons utilisé deux protéines dont l'expression est dépendante de l'acidification du microenvironnement des tumeurs solides : les protéines LAMP2 et NBCn1. En effet, LAMP2 est fortement exprimé dans les régions les plus acides des tumeurs cancéreuses du sein(Damaghi et al. 2015), tandis que NBCn1 est impliqué dans l'acidification du microenvironnement tumoral et est constamment exprimé dans les tissus du cancer du sein(Lee et al. 2015, Pedersen et al. 2017). Nous avons analysé le score d'intensité de marquage de ces deux marqueurs et nous avons constaté que LAMP2 et NBCn1 étaient exprimés dans les cellules tumorales ainsi que dans les cellules non tumorales adjacentes. LAMP2 était principalement localisé dans le cytoplasme, tandis que NBCn1 a été retrouvée exprimée à la fois au niveau de la membrane plasmique Il est connu que la dérégulation de l'expression de plusieurs types de canaux ioniques dans le cancer est liée une dérégulation de la méthylation de leur ADN[START_REF] Ouadid-Ahidouch | DNA methylation of channel-related genes in cancers[END_REF]. En ce qui concerne l'ACP, différents gènes codant pour les canaux ioniques sont associés à la méthylation de l'ADN(Brevet et al., 2009[START_REF] Gregorio | Calcium Signaling Alterations Caused by Epigenetic Mechanisms in Pancreatic Cancer: From Early Markers to Prognostic Impact[END_REF][START_REF] Chatterjee | Altered DNA methylation in ion transport and immune signalling genes is associated with severity in Pancreatic Ductal Adenocarcinoma[END_REF]. Les changements de pH peuvent affecter la stabilité génomique et réciproquement. Ces changements de pHi peuvent être dus à des changements de pHe. Pourtant, ils peuvent également être créés par la biodynamique des cellules, car de nombreuses altérations génétiques et épigénétiques exercent leur fonction en modifiant le métabolisme des cellules cancéreuses, provoquant des changements de pH[START_REF] Ordway | Causes and Consequences of Variable Tumor Cell Metabolism on Heritable Modifications and Tumor Evolution[END_REF]. Cependant, nous ne comprenons pas très bien comment l'acidification affecte directement les changements épigénétiques. La façon dont l'adaptation acide affecte les niveaux de méthylation de l'ADN des régions promotrices des canaux ioniques, et donc l'expression des gènes, n'a, à notre connaissance, jamais été étudiée auparavant. Dans cette dernière partie de mon travail de thèse, nous avons cherché à déterminer si l'adaptation acide pourrait affecter la méthylation du promoteur des gènes codant les canaux ioniques, en particulier, ASIC1, SCN8A (codant pour la sous-unité alpha 8 du canal voltagedépendant du sodium, NaV1.6) et TRPC1. Nous avons utilisé une approche de séquençage au bisulfite de sodium et une méthode d'analyse quantitative et semi-quantitative pour explorer les niveaux de méthylation de l'ADN des gènes codant pour les canaux ioniques dont l'expression pourrait être affectée par l'adaptation acide. Nous avons montré que l'expression de NaV1.6 était régulée négativement dans les cellules MiaPaCa-2 adaptées à l'acide et le tissu d'ACP humain, par rapport au tissu non tumoral adjacent. De plus, nous avons montré que le promoteur du gène SCN8A est hyperméthylé dans les cellules MiaPaCa-2 adaptées à l'acide par rapport aux cellules cultivées dans des conditions de pH normale. En outre, nous avons montré que les régions promotrices des gènes ASIC1 et TRPC1 ne présentait pas de modifications quant à leur méthylation lors de l'adaptation acide par rapport aux conditions de pH normales.

	3. L'adaptation des cellules à un pH acide favorise (i) la localisation TRPC1 au niveau de la membrane processus cellulaires via des mécanismes dépendants du Ca2+ lors de l'adaptation à l'acide et de la
	plasmique, et (ii) à la prolifération et à la migration des cellules d'ACP de manière dépendante de récupération du milieu acide.
	l'entrée de Ca 2+ et de l'interaction avec PI3K/CaM 6. Le complexe TRPC1/PI3K/CaM contrôle la progression des cellules dans le cycle cellulaire, la
	Article 2 : "Acid adaptation promotes TRPC1 plasma membrane localization leading to pancreatic ductal prolifération et la migration via l'activation d'AKT et ERK1/2.
	adenocarcinoma cell proliferation and migration through Ca2+ entry and interaction with PI3K/CaM". Parallèlement à l'analyse du cycle cellulaire, notre analyse par Western Blot des protéines régulatrices du cycle 7. Le promoteur du gène SCN8A a tendance à être hyperméthylé, provoquant sa régulation à la baisse
	Cancers, 2022. cellulaire a révélé que le siTRPC1 réduisait l'expression de CDK6, 2 et 1 et de la cycline A tout en augmentant dans les cellules MiaPaCa-2 adaptées à un microenvironnement acide.
	l'expression de p21. Notamment, l'inhibition de l'expression de TRPC1 a eu un effet plus substantiel dans des Pour compléter ce travail portant sur l'interaction entre le microenvironnement tumoral acide et le canal
	conditions récupérées que dans des conditions normales et acides. TRPC1, nous proposons d'étudier plus en détails les différents mécanismes impliqués (Figure 53). Par
	exemple, il pourrait être intéressant d'étudier :
	1. Si l'activation de TRPC1 est causée directement par l'acidification et/ou la récupération des cellules
	d'un milieu acide.
	2. Le mécanisme permettant la translocation de TRPC1 vers la membrane plasmique dans différentes
	conditions de pH et si celle-ci dépend de la formation d'un complexe avec ORAI1 et/ou STIM1 par
	exemple.
	Boedtkjer et Pedersen 2020). Le pH intracellulaire (pHi) est plus alcalin que le pHE des tumeurs, mais les cellules cancéreuses dans un microenvironnement acide présentent toujours un pHi acide (Lee et al. 2015, Lee et al. 2016) par rapport aux cellules saines du pancréas normal. Des preuves solides ont été rapportées quant à l'impact du microenvironnement tumoral acide sur l'agressivité de l'ACP en termes de prolifération, de Article 1 : "The TRPC1 Channel Forms a PI3K/CaM Complex and Regulates Pancreatic Ductal Adenocarcinoma Cell Proliferation in a Ca2+-Independent Manner". International Journal Of Molecular Sciences, 2022. Lors de notre étude, nous avons montré que TRPC1 était systématiquement surexprimé dans le tissu d'ACP humain aux niveaux transcriptomique et protéique. En outre, il est fortement exprimé dans la lignée cellulaire cancéreuse pancréatique agressive, PANC-1. Dans cette étude, nous avons démontré que la surexpression de TRPC1, au niveau transcriptionnel, analysée à l'aide de la base de données TCGA-PAAD, était significativement plus élevée dans le sous-type d'ACP agressif de type basal par rapport au sous-type classique. De plus, les patients présentant des niveaux élevés de TRPC1 présentaient une survie globale significativement plus faible par rapport aux patients présentant de faibles niveaux d'expression de TRPC1. Au niveau des lignées cellulaires, l'expression de TRPC1 était significativement plus élevée dans les cellules cancéreuses MiaPaCa-2 et PANC-1 par rapport à la lignée cellulaire saine HPNE. Comme TRPC1 était surexprimé dans la lignée agressive PANC-1, nous avons choisi d'étudier les mécanismes par lesquels TRPC1 régulent les processus cellulaires cancéreux dans cette lignée La lignée cellulaire PANC-1 présente des mutations au sein de trois oncogènes connus (KRAS, TP53, CDKN2A). De plus, il a été rapporté que TRPC1 régule la prolifération des cellules cancéreuses par les voies de signalisation en aval de ces oncogènes (Elzamzamy et al. 2020). Ainsi, nous avons cherché à déterminer siTRPC1 régulait la prolifération des cellules PANC-1 par les voies PI3K/AKT et MAPK/ERK. Nous avons constaté que siTRPC1 diminuait principalement l'activation de AKT et, dans une moindre mesure, ERK, indiquant que TRPC1 régule la prolifération des cellules PANC-1 via l'axe de signalisation PI3K/AKT plutôt que la voie de signalisation MAPK. Nous avons, par la suite, étudié l'interaction physique entre la sous-unité PI3K-p85 et TRPC1. Notre expérience de PLA a montré une proximité entre TRPC1 et la sous-unité PI3K-p85. Cette interaction a été confirmée par co-IP. En effet, TRPC1 interagit fortement avec PI3K et leur protéine de liaison, la calmoduline (CaM). Cette interaction a été abolie lors de l'extinction moléculaire de TRPC1. L'ensemble de ces données ont révélé que TRPC1 pourrait être un biomarqueur potentiel de l'ACP en étant régulé à la hausse dans les tissus humains d'ACP et les lignées cellulaires cancéreuses pancréatiques. Nous avons démontré que TRPC1 régule la prolifération des cellules PANC-1 et la croissance de sphéroïdes pancréatiques par l'interaction directe avec les protéines PI3K et CaM, activant ainsi cette voie de signalisation régulant la progression des cellules dans les phases G1 et S, probablement par des mécanismes indépendants présentent un pHi inférieur à celui des cellules cultivées dans des conditions de pH normales (pH7,4). De plus, les cellules adaptées à l'acide puis récupérées dans des conditions de pHe normales (pH 7,4R) présentaient un pHi plus alcalin. Ensuite, notre analyse par Western Blot, imagerie confocale et test de biotinylation ont démontré que l'adaptation acide diminuait l'expression totale de TRPC1 mais favorisait sa localisation au niveau de la membrane plasmique. L'expression de TRPC1 était encore plus augmentée et maintenue au niveau membranaire dans les conditions de récupération. Nous avons en outre montré que l'adaptation acide favorisait la migration des cellules PANC-1 mais réduisait la prolifération. Similaires résultats ont été trouvés dans les modèles 2D et 3D. Pour démontrer le rôle de TRPC1 dans le microenvironnement tumoral acide, nous avons également choisi l'approche par siRNA afin d'inhiber l'expression de TRPC1. Nous avons montré que siTRPC1 inhibait la migration des cellules PANC-1 dans les conditions normales, adaptées à l'acide et de récupération. De plus, nous avons montré que l'invalidation moléculaire de TRPC1 inhibait fortement la prolifération, en 2D et en 3D, des cellules PANC-1 récupérées de l'environnement acide, par rapport au contrôle, alors que cet effet était moins évident dans des conditions adaptées à l'acide. conditions (bas calcium extracellulaire), siTRPC1 a induit une légère réduction de la migration et la prolifération cellulaires. L'ensemble de ces données a révélé un nouvel aperçu de l'interaction entre le microenvironnement tumoral et Ainsi, durant ce travail de thèse, nous avons spécifiquement mis en évidence que (Figure 53): 1. L'expression de certains canaux ioniques est dérégulée dans le développement et la progression de l'ACP. 2. TRPC1 est surexprimé dans les tissus et les lignées cellulaires d'ACP humaines, et est corrélé à des facteurs cliniques agressifs et à un mauvais pronostic. 3. L'adaptation acide augmente la localisation membranaire de TRPC1, même si son expression totale est réduite. 4. Les cellules récupérées du milieu acide présentent une expression totale de TRPC1 augmentée et une localisation de TRPC1 à la membrane plasmique est maintenue. 5. TRPC1 régule la prolifération et la migration des cellules d'ACP via la voie de signalisation cellulaire. extracellulaire. du Ca 2+ . PI3K/CaM indépendamment du Ca 2+ dans des conditions de pH normales, tandis qu'il régule ces

As there is not yet a standardized method to investigate the acidification of human tissue, it could be of interest if other acidextruding transporters acidifying the extracellular space could be highly expressed in PDAC tissue.

INTRODUCTION

L'adénocarcinome de cancers

(Pedersen et Stock, 2013 ;[START_REF] Djamgoz | Ion transport and cancer: from initiation to metastasis[END_REF]

. Ainsi, une expression et une activité anormales des canaux ioniques pourraient être classées comme des caractéristiques du cancer (« Hallmarks of cancer »)

(Hanahan et Weinberg, 2011)

.

Le développement et la progression de l'ACP sont également liés à la physiologie et au microenvironnement du pancréas exocrine. Les cellules épithéliales et stromales pancréatiques sont exposées à des changements cycliques du pH extracellulaire (pHE) dus à la production de sucs pancréatiques alcalins riches en ion bicarbonate (HCO3 -). L'exposition apicale à ce pHE alcalin est couplée à l'acidification parallèle au niveau de la membrane basolatérale, conduisant à un interstitium pancréatique acide

(Novak et al. 2013, Pedersen et al. 2017)

. Fait intéressant, l'acidification extracellulaire est l'une des principales caractéristiques du microenvironnement tumoral. Celle-ci est causée conjointement par une faible perfusion sanguine et une forte extrusion de protons (H + ) de la glycolyse fermentative et de l'acide sous forme de CO2 provenant de la phosphorylation oxydative (migration et d'invasion ainsi que de résistance à l'apoptose

[START_REF] Orth | Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches[END_REF]

. Cependant, les mécanismes sousjacents sont encore mal compris. tumoral rôle cancéreux d'ORAI3 a récemment été démontré dans des lignées cellulaires et des tissus humains d'ACP (Arora et al. 2021, Dubois et al. 2021). 2. Le canal TRPC1 forme un complexe avec PI3K/CaM et régule la prolifération cellulaire de l'ACP de manière indépendante du Ca2+. Pour évaluer l'influence du microenvironnement tumoral acide, nous avons développé un protocole expérimental où les cellules PANC-1 ont été cultivées dans des conditions normales (pH 7,4), adaptées à un environnement acide (30 jours à pH 6,5) ou dans des conditions de récupération (cellules adaptées à pH 6,5 et réensemencé pendant 14 jours à pH 7,4). Nos mesures de pH intracellulaire (pHi) ont démontré que les cellules PANC-1 adaptées à l'acide (pH 6,5) Notre objectif était d'étudier les mécanismes sous-jacents du microenvironnement tumoral acide et de TRPC1 dans les cellules PANC-1. Notre analyse par cytométrie en flux a révélé que l'adaptation acide entraînait une augmentation du Nous avons constaté que l'activation de ERK1/2 était profondément inhibée lorsque les cellules étaient transfectées avec siTRPC1 dans des conditions acides et récupérées, par rapport à ce que nous avions précédemment observé dans des conditions de pH normales. De plus, siTRPC1 a également diminué l'activation de AKT, en particulier dans des conditions de récupération d'acide. De plus, l'inhibition de la CaM a réduit l'activation de AKT uniquement dans les cellules récupérées de l'environnement acide, tandis que les niveaux de ERK1/2 ont été affectés dans toutes les conditions. le canal ionique TRPC1. Nous avons montré que l'acidification du pH du microenvironnement tumoral favoriserait la translocation du TRPC1 à la membrane plasmique, favorisant ainsi l'interaction avec PI3K/et au niveau du cytoplasme des cellules non tumorales et tumorales. Nous avons précédemment démontré que TRPC1 était localisé à la membrane plasmique des cellules tumorales dans le tissu d'ACP humain et que l'adaptation acide améliore cette localisation. Par conséquent, nous avons cherché à montrer si l'expression de TRPC1 à la membrane était corrélée avec l'expression de LAMP2 ou NBCn1 dans le tissu d'ACP. Durant cette partie du travail, nous avons constaté que la localisation de la membrane plasmique de TRPC1 est associée à la localisation cytoplasmique de LAMP2 dans les cellules tumorales. Nos résultats suggèrent que LAMP2 et NBCn1 sont exprimés dans les tissus non tumoraux et d'ACP, et que la localisation membranaire de TRPC1 est corrélée avec la localisation cytosolique de LAMP2. 5. Le microenvironnement acide affecte la méthylation de l'ADN des canaux ioniques D'autres expériences complémentaires sont nécessaires pour valider nos résultats préliminaires et comprendre comment l'adaptation à l'acide affecte la méthylation de l'ADN et d'autres modifications épigénétiques des promoteurs de gènes de canaux ioniques. CONCLUSION ET PERSPECTIVES Pour conclure, ce travail de thèse a donné un nouvel aperçu du rôle des canaux ioniques, en particulier de l'impact de TRPC1 et du microenvironnement acide dans la progression de l'ACP. Tout d'abord, nous avons élucidé le rôle de TRPC1 dans la prolifération des cellules cancéreuses pancréatiques et s'il pouvait être utilisé comme biomarqueur potentiel. Ensuite, nous avons montré que le dialogue entre les fluctuations du microenvironnement acide et TRPC1, active une cascade de signalisation qui régule la prolifération et la migration des cellules d'ACP.

  of lactate and other metabolites, and profound acidosis. While serum pH is around 7.4, corresponding to a H + concentration ([H + ]) of ~40 nM, the extracellular pH (pH e ) in tumors can reach 6.2-6.8, i.e., [H + ] ~630-160 nM

	Cancers 2020, 12, 2183	2 of 27

Cancers 2020, 12, 2183; doi:10.3390/cancers12082183 www.mdpi.com/journal/cancers accumulation

Table 1 .

 1 Acid adaptation-upregulated genes significant in OS analysis in at least two types of cancers.

Table 1 .

 1

Table 1 .

 1 Cont.Types

of Cancer Gene Name Log 2 FC FDR Correlation with Poor OS PAAD BRCA LUAD GBM COAD OV THCA STAD Molecular Function/Biological Process

	(UniProt)	Chromatin regulator, RNA-binding	Pseudogene	Hydrolase, lipid metabolism, motility
		Low expression	Low expression	High expression	Low expression
		0.0058	0.0376	0.0306	0.0038
		0.5832	0.5302	0.5226	0.5118
		TDRD3	FRG1HP	PLD2	MLLT6

Frontiers in Pharmacology | www.frontiersin.org October 2020 | Volume 11 | Article 568993

Int. J. Mol. Sci. 2022, 23, 7923. https://doi.org/10.3390/ijms23147923 https://www.mdpi.com/journal/ijms

Acknowledgments

During my Ph.D. studies, I have had the opportunity to work with a number of excellent people to whom I am

AUTHOR CONTRIBUTIONS

JS, ID-D, AA, and HO-A: design and manuscript preparation. All authors contributed to the article and approved the submitted version.

FUNDING

JS is grateful for the funding by the Marie Skłodowska-Curie Innovative Training Network (ITN) Grant Agreement number: 813834 -pHioniC -H2020-MSCA-ITN-2018. HO-A is grateful for the funding by the Ministère de l'Enseignement Supeŕieur et de la Recherche, the Reǵion Hauts-de-France (Picardie), the FEDER (Fonds Europeén de Developpement E ́conomique Reǵional), the UniversitéPicardie Jules Verne, and the Ligue Contre le Cancer (Septentrion).

Acknowledgments: We are grateful to Marie-Pierre Mabille (Anatomy and Pathology Department, Amiens Hospital) and Mette Flinck (Department of Biology, University of Copenhagen) for the excellent technical assistance, and to Anna Trauzold (Institute of Experimental Cancer Research, Kiel University, Kiel, Germany) for providing us with the PDAC cell lines.

Acknowledgments:

We are grateful to Mette Flinck (Department of Biology, University of Copenhagen) for excellent technical assistance, and to Anna Trauzold (Institute of Experimental Cancer Research, Kiel University, Kiel, Germany) for providing us with the PANC-1 cell line.

Acknowledgments:

The authors thank Kristo↵er Vitting Seerup, Jens Waaben and Kasper Haldrup Björnsson for help with exploratory RNA-seq analyses.

Funding: This study was supported by funds from the Danish Cancer society (A.S. and S.F.P.), the Novo Nordisk Foundation (A.S. and S.F.P.), the European Union (H2020-MSCA-ITN-2018, grant 813834, A.S. and S.F.P.) and the Carlsberg Foundation (A.S.).

Data Availability Statement: Not applicable.

Data Availability Statement:

The data presented in this study are available in this article and Supplementary Material.

Conflict of Interest:

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Antibody for WB Host Dilution Distributor Reference

Co-immunoprecipitation

Co-immunoprecipitation (co-IP) is a standard technique to identify a physically relevant protein-protein interaction by using target protein-specific antibodies to capture proteins bound to a specific target protein indirectly. In this study, we aimed to investigate the protein-protein interaction between TRPC1 and the PI3K-p85α subunit. In this study, we used SureBeads™ Protein A Magnetic Beads (Biorad # 161-4013) as they have a high affinity for rabbit antibodies. First, 6 × 10 5 non-transfected or 1 × 10 6 transfected PANC-1 cells were seeded in a 10 cm Petri dish and collected after 72 h. Co-IP was carried out according to the manufacturer's protocol. The beads were washed and preincubated with 1 µg of the TRPC1 (Rabbit, Abcam) or PI3K-p85α subunit antibody or a control Anti-rabbit IgG antibody for 30 min. After a sequential washing step, 500 µg of protein lysates from RIPA scrapped samples were added to the beads, which were slowly rotated for 2 h at This mixture is incubated overnight at 14°C then stored at -20°C. The INVαF' bacteria (One Shot Ò competent cells, Invitrogen) were transformed with the ligation product into pCR Ò 2.1 according to the manufacturer's protocol. Competent bacteria (50 µl) were incubated for 30 min on ice in the presence of 2 µL of ligation product, then heat shocked for 30 s at 42° C. and finally placed again on ice for 2 min. The transformed bacteria were then incubated for 1 hour at 37°C upon shaking in SOC medium (250 µl), and then spread (80 µl) on LB-Agar plates containing ampicillin (50 µg/ml) and X-Gal (40 µl of a 50 mg/ml) on Petri dishes and incubated overnight at 37°C. The X-Gal allows for the selection of clones due to the blue color of the X-Gal substrate.

The pCR Ò 2.1 vector encodes the first 146 amino acids of β-galactosidase. If β-galactosidase is produced, X-Gal is hydrolyzed and produces an insoluble blue pigment. The colonies formed by non-recombinant cells do not contain the expected insert and will appear blue, while the recombinant ones, having the inserts, appear white. The desired recombinant colonies were picked for either the semiquantitative analysis or the quantitative analysis method. For the semiquantitative analysis method 10 clones were picked and pooled in the same falcon tube with 5 ml LB medium containing ampicillin (50 µg/ml). For the quantitative method, single clones were picked and grown separately in falcon tubes with 5 ml LB medium containing ampicillin (50 µg/ml).

From here, two approaches can be used: (1) Clones were grown overnight, and the plasmids were extracted using the NucleoSpin Plasmid, Mini kit for plasmid DNA (Machinery Nagel, #740588.250), according to the manufacturer's protocol. 1 µL of plasmid DNA was then mixed with the restriction enzyme EcoRI, 1 µL of its belonging 10X digestion buffer, cutting at both sites of the insertion site of pCR Ò 2.1 vector, and 8 µL of water, and incubated at 1 h at 37° C. The 10 µL of digestion product was then loaded on a 2% agarose gel to verify that the plasmid contained the bisulfite insert. ( 2) When clones were picked, they were first scratched on a new LB-agarose plate, and the rest of the clones were used for colony PCR. With this approach, the two primers encoded in the pCR Ò 2.1 vector M13 forward and reverse were used to do a colony PCR. After the PCR, the products were loaded on a 2% agarose gel. This approach can be used to be sure that the different clones contain the insert before performing mini-prep. Following the ensuring steps that the plasmid contains the expected insert, the plasmid was sent to sequencing. Plasmid DNA was sequenced on both strands on an infrared-based ABI 3730 XL sequencer (GATC, Eurofins, Konstanz, Germany) using T7 and M13-RP universal primers.

Fallavier, France) was used to detect interactions between TRPC1 and PI3K. Experiments were performed following the manufacturer's protocol. Red fluorescent oligonucleotides produced as the end product of the procedure were visualized using the Zeiss Observer Z1 microscope 60X oil objective (Carl Zeiss, Oberkochen, Germany). Images were analyzed using ImageJ software 1.53a (National Institute of Health, Bethesda, MD, USA), where puncta per cell were counted and normalized to the control. At least 20 pictures per condition were captured and analyzed.

Statistical Analysis

All data are shown as representative images or as mean measurements with standard error of means (SEM) error bars and represent at least three independent experiments. N refers to the population size, where n refers to the number of independent experiments performed or to the number of cells analyzed. Welch's correction t-test or Tukey's multiple comparison test was applied to test for statistically significant differences between two groups. *, **, ***, and **** denotes p < 0.05, p < 0.01, p < 0.001, and p < 0.0001, respectively. All graphs and statistics were generated in GraphPad Prism 9.0 software.

Supplementary Materials:

The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijms23147923/s1. Refs. [60,62] are cited in the supplementary materials. Funding: This work is funded by the Marie Skłodowska-Curie Innovative Training Network (ITN) grant agreement number: 813834-pHioniC-H2020-MSCA-ITN-2018, and by the Ministère de l'Enseignement Supérieur et de la Recherche, the Région Hauts-de-France (Picardie), the FEDER (Fonds Européen de Développement Économique Régional), the Université Picardie Jules Verne, and the Ligue Contre le Cancer (Septentrion).

Author

Institutional Review Board Statement:

The study was conducted according to the tenets of the Declaration of Helsinki and was approved by an institutional review board "Direction de la Recherche, Clinique et de l'Innovation", CHU Amiens-Picardie (reference: Pan-Ionic: PI2021_843_0027).

Informed Consent Statement: Informed consent was obtained from all study participants.

Conflicts of Interest:

The authors declare no conflict of interest. France; julie_schnipper@hotmail.com (JS), Sana Kouba sana.kouba@hotmail.com (SK), fh lnc@u picardie.fr (FH), alban.girault@u picardie.fr (AG), marie sophie.telliez@u picardie.fr (MST), 2 Anatomy and Pathology Department, Amiens Hospital, University of Picardie Jules Verne, Tumorotheque of Picardie, Amiens, France; Rybarczyk.Pierre@chu amiens.fr (PR), Henrisevestre@gmail.com (HS), Teb bakha.Riad@chu amiens.fr (RT) 3 Centre de Ressources Régional en Biologie Moléculaire, Université de Picardie Jules Verne, Amiens, France; stephanie.vandecasteele@u picardie.fr (SG) 4 Biology department, University Ibn Zohr, Agadir, Morocco, ahidouch@gmail.com (AA) 5 Section for Cell Biology and Physiology, Department of Biology, University of Copenhagen, Copenhagen Ø, Denmark; sfpedersen@bio.ku.dk (SFP) * Correspondence: halima.ahidouch ouadid@u picardie.fr (HOA); Tel.: +33 322827646

Supplementary Materials:

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers14194946/s1. Figure S1: Knockdown of TRPC1 in 2D and 3D models evaluated by qPCR and WB. Figure S2: Trypan blue assay performed in parallel with Boyden chamber assay to avoid any bias due to cell proliferation. Annexin-5 assay shows no effect upon siTRPC1. Figure S3: Representative WB of non-affected cell cycle regulating proteins upon the KD of TRPC1 and of the control pull-down with IgG-Rabbit for co-IP. Figure S4:

Supplementary Materials:

The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/cancers14194946/s1. Figure S1: Knockdown of TRPC1 in 2D and 3D models evaluated by qPCR and WB. Figure S2: Trypan blue assay performed in parallel with Boyden chamber assay to avoid any bias due to cell proliferation. Annexin-5 assay shows no effect upon siTRPC1. Figure S3: Representative WB of non-affected cell cycle regulating proteins upon the KD of TRPC1 and of the control pull-down with IgG-Rabbit for co-IP. Figure S4: Representative WB of PANC-1 cells treated with W7, blotted for pERK, ERK, pAKT and AKT. Figure S5: Representative traces of the classical store-operated Ca 2+ entry protocol [78]. File S1. Full pictures of the Western blots. Funding: This work is funded by the Marie Skłodowska-Curie Innovative Training Network (ITN) Grant Agreement number: 813834-pHioniC-H2020-MSCA-ITN-2018, and by the Ministère de l'Enseignement Supérieur et de la Recherche, the Région Hauts-de-France (Picardie), the FEDER (Fonds Européen de Développement Économique Régional), the Université Picardie Jules Verne, and the Ligue Contre le Cancer (Septentrion).

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Conflicts of Interest:

The authors declare no conflict of interest.

Supplementary Figures and Material and Methods

Acid Adaptation

Supplemental Materials and Methods

Store-operated Ca 2+ entry assay

To investigate Store-operated Ca 2+ entry (SOCE) we used the same equipment and reagents as described in the Mn 2+ Quench Assay. SOCE was triggered by applying the classical protocol, first by perfusing a saline solution (145 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 5 mM glucose, 10 mM HEPES, pH 7.4 or pH 6.5) containing 2 mM Ca 2+ (for 1 min), then 0 mM Ca 2+ during 1 min followed by 1 µM thapsigargin in 0 mM Ca 2+ for 12 min to induce Ca 2+ store depletion, followed by perfusion of 2 mM Ca 2+ (for 5 min). The intracellular Ca 2+ concentration is derived from the ratio of emitted fluorescence intensities for each of the excitation wavelengths (F340/F380), and emission at 510 nm.

Quantitative Real-Time PCR (qRT-PCR)

The 2.5 × 10 4 transfected (with either siCTRL or siTRPC1) PANC-1 cells, grown in either pH 6.5 or 7.4R conditions, were seeded for 48, 72, or 96 h respectively, to determine the KD of TRPC1 at the transcriptional level. At the specific time points, total RNA was extracted with the Trizol reagent (Sigma-Aldrich, Saint-Quentin-Fallavier, France) method as previously described [44,47]. After RNA extraction, RNA concentrations and purity were determined using a spectrophotometer (NanoDrop 2000, Wilmington, NC, USA). 2 µg of RNA was converted into cDNA with the MultiScribe™ Reverse Transcriptase kit (Applied Biosystems, Carlsbad, CA, USA). Real-time PCR was performed on a LightCycler 480 System (Roche, Basel, Switzerland) using SYBR Green I PCR master mix (Life Science, Roche, Basel, Switzerland). Sense and antisense PCR primers specific to TRPC1 (forward 5' GAGGTGATGGCGCTGAAGG-3' and reverse 5' -GCACGCCAGCAAGAAAAGC-3') and β2 microglobulin (B2M) (forward 5' GTCTTTCAGCAAGGACTGGTC -3 ' and reverse CAAATGCGGCATCTTCAAACC3'). TRPC1 mRNA expression was normalized to B2M, used as housekeeping gene, and compared to the control sample, using the Pfaffl method [78].

FACS analysis of annexin V and propidium iodide staining

To evaluate the percentage of apoptotic and necrotic cells, we detected phosphatidylserine residues at the outer plasma membrane by the FITC Annexin V Apoptosis Detection Kit I (BD Biosciences Pharmingen, Le Pont-de-Claix, France). 5 × 10 5 transfected PANC-1 cells, grown in either pH 6.5 or 7.4R conditions, were seeded and collected after 72 h. Both detached and adherent cells were collected by trypsinization. Cells were pelleted, washed twice with cold PBS and resuspended in 1X binding buffer (BD Biosciences Pharmingen). Following the Annexin V Apoptosis Detection Kit staining protocol, we added FITC Annexin V and propidium iodide to the cell pellets and incubated them at room temperature in the dark for 15 min. The binding buffer was then added to each sample, which were immediately analyzed by flow cytometry (Accuri®) in order to determine the percentage of apoptotic and necrotic cells.

of breast cancer tumors (Damaghi et al. 2015). NBCn1 is involved in acidifying the tumor microenvironment and is consistently expressed in breast cancer tissue (Lee et al. 2015, Pedersen et al. 2017). We analyzed the marking intensity score and found that both LAMP2 and NBCn1 were highly expressed in both tumor and adjacent non-tumor cells (Figure 41A,B). LAMP2 was mainly located in the cytoplasm (91.7% and 83.6% in non-tumor and tumor tissue, respectively, n = 20), where NBCn1 was found both in the plasma membrane and the cytoplasm of non-tumor and tumor cells (~50% in cytoplasm and membrane, respectively, n = 20). We have previously demonstrated that TRPC1 localizes to the plasma membrane of tumor cells in human PDAC tissue and that acid adaptation enhances this localization. Therefore, we aimed to analyze if TRPC1 correlated with the LAMP2 or NBCn1 expression in PDAC tissue. Here, we found that the plasma membrane localization of TRPC1 is associated with the cytoplasmic localization of LAMP2 in tumor cells (Figure 42A). Together, our results suggest that LAMP2 and NBCn1 are highly expressed in non-tumor and PDAC tissue, and TRPC1 plasma membrane localization correlates with the localization of LAMP2 in the cytoplasm.

EPIGENETIC PROJECT

However, this case is more complex to explain, it could be worth investigating if the DNA methylation or histone modification are found on other sites of the gene promoter.

Taken together, further studies and replicates are needed to conclude how acid-adaptation affects DNA methylation and other epigenetic changes of ion channel gene promoters. were calibrated with KCl ringers, and pHi was calculated by using the slope. glioblastoma correlated with poor OS. On the contrary, high expressions of the majority of acid adaptation-downregulated genes in stomach, ovarian, thyroid and colon cancers were associated with better OS (Figure 3B). response (pH 6.5 vs. 7.6). These ranked gene lists are compared in the rank-rank heat map below (exemplified by the comparison of data from the TCGA patient TCGA-EL-A3ZS and the acid adaptation gene list), identifying windows of genes with correlated ranks in respective gene lists and the significance of such correlated ranks, as indicated by color (based on ln(hypergeometric p-values) as shown). (B) Heat maps resulting from patient tumor-ctrl. vs. acid adaption gene list RRHO analyses showing high gene rank similarity. Each heat map corresponds to patient tumor-ctrl. vs. acid adaptation gene list analysis as in (A), where the acid adaptation gene list is always at the x-axis and the color scale is as in (A). Cancer types are indicated on top of heat maps: consecutive heat maps to the right have the same cancer type unless otherwise indicated (BRCA-breast cancer (luminal B), BLCA-bladder urothelial carcinoma, ESCA-esophageal carcinoma, STAD-stomach cancer, CHOL-cholangiocarcinoma, UCEC-uterine corpus endometrial carcinoma, PCPG-pheochromocytoma and paraganglioma, PAAD-pancreatic cancer, COAD-colon cancer, SARC-sarcoma, READ-renal adenocarcinoma, HNSC-head and neck squamous cell carcinoma, LIHC-liver hepatocellular carcinoma, LUAD-lung cancer (adenocarcinoma), PRAD-prostate adenocarcinoma, KICH-kidney chromophobe, KIRP-kidney renal papillary cell carcinoma, KIRC-kidney renal clear cell carcinoma, THCA-thyroid cancer). (C) Distribution of RRHO similarity scores across TCGA patients. The y-axis shows the number of patients with a given RRHO similarity score (x-axis) calculated as the fraction of windows with a p < 0.05 in rank-rank heat maps (out of a total of 100 windows). Analyses resulting in >20 windows with p < 0.05 (highlighted in yellow) were considered "high acid adaptation similarity". The number of analyzed patients and the number of analyses resulting in high acid adaptation similarity scores are shown as an insert table. (D) Relation between high acid adaptation similarity score and patient metadata. Subpanel i shows the distribution of age of diagnosis split by whether patients are in the "high acid adaptation similarity" group, visualized as box plots. p-value is from two-sided t test. Subpanel ii-iv shows fraction of patients classified by TNM staging system. T: size of the primary tumor. T1, T2, T3, T4-size and/or extension of the primary tumor. N: degree of spread to regional lymph nodes. N0-no regional lymph nodes metastasis; N1-regional lymph node metastasis present (at some sites, tumor spread to closest or small number of regional lymph nodes); N2 -tumor spreads to an extent between N1 and N3; N3-tumor spread to more distant or numerous regional lymph nodes. M: presence of distant metastasis. M0-no distant metastasis; M1-metastasis to distant organs (beyond regional lymph nodes). Bars are split by whether patients are in the "high acid adaptation similarity" group. p-values from Fisher exact tests are shown, testing the decrease in T1 and increase in T2 in the "high acid adaptation similarity" group vs. remaining patients. Numbers on bars show patient counts.

Analyses of RNA-Seq Data

RNA-seq reads were pseudoaligned to Gencode transcriptome release 34 and quantified using Salmon v1.1.0 with flags-validateMappings for selective alignment and l A for automatic library type inference [68]; Trimmed Mean of M values (TMM) normalization [69] and pre-filtering for low counts were performed using calcNormFactors and filterByExpr function in edgeR package [70,71]. Voom transformation [29] was then applied with a design matrix that used pH treatment as coe cient. To perform di↵erential expression analyses in shared response to pH, inter-subject correlation within three cell lines was performed by duplicateCorrelation function, and was put into the linear model fit using Limma R package [72]. Di↵erential expression, given the above settings, was defined as Benjamini-Hochberg FDR < 0.05 and an absolute log 2 FC > 0.5. Validation of key up/downregulated genes by qPCR and immunoblotting is provided in a manuscript in preparation and confirms the RNA-seq results.

GO Enrichment Analysis and Gene Set Enrichment Analysis (GSEA)

Enrichment tests for GO-terms were performed on differentially expressed genes sets as defined above using gProfiler [73]. The background gene set was set to all expressed genes in the experiment. Significance threshold was set to Benjamini-Hochberg FDR < 0.05. The Gene Set Enrichment Analysis (GSEA) pre-ranked function was performed on the fold change ranked acid adaptation gene list using the Broad Institute GSEA java tool version 4.0.3. C6: Oncogenic signatures database v7.1, gene sets WU_CELL_MIGRATION (M2001) and ANASTASSIOU_MULTICANCER_INVASIVENESS_SIGNATURE (M2572) were used and the number of permutations was set to 1000 [74].

RRHO Analysis

First, using Limma and Voom as above, we ranked all expressed genes from the RNA-seq experiments by their shared acid adaptation response across cells (log 2 fold change pH 6.5 vs. pH 7.4). We will refer to this ranked gene list as the 'acid adaptation ranked gene list'. To be able to compare this to human data, we extracted processed patient RNA-seq data from Cancer Genome Atlas (TCGA) [75] using the University of California Santa Cruz Xena portal [76]. For every patient and cancer where expression data from paired tumor and control tissue were available, and for each such case, we ranked genes according to their log2 fold change (tumor vs. control (ctrl.) tissue). Next, we compared the acid adaptation ranked list to each ranked patient gene lists in a pairwise fashion, using the Rank-Rank Hypergeometric Overlap (RRHO) method [77], as implemented in R [78]. For each comparison, we obtained heat maps showing rank-rank correlations, colored by log-transformed hypergeometric P-value of local rank overlaps between sets, and the identifiers of genes in each overlap.

Patient Survival Analysis

TCGA cancer patient data was downloaded from the University of California Santa Cruz Xena portal [76]. The following datasets containing gene expression RNAseq counts, survival data and phenotype information were analyzed: GDC TCGA Pancreatic Cancer (PAAD), GDC TCGA Breast Cancer (BRCA), GDC TCGA Lung Adenocarcinoma (LUAD), GDC TCGA Glioblastoma (GBM), GDC TCGA Colon Cancer (COAD), GDC TCGA Ovarian Cancer (OV), GDC TCGA Thyroid Cancer (THCA) and GDC TCGA Stomach Cancer (STAD).

Kaplan-Meier analysis was performed to estimate the overall survival of patients. Patients were categorized into high and low gene expression groups according to the cut-o↵ value determined by median gene expression. p-values for significance of di↵erence between the two groups were calculated using the log-rank test. Statistical analyses were performed using R's "survival" and "survminer" packages. p-values < 0.05 were considered statistically significant.

Data Availability

RNA-sequencing data from this study has been deposited in GEO database under accession number GSE152345.

Conclusions

We have defined a shared acid adaptation expression response across three cancer cell models, dominated by ECM remodeling, metabolic rewiring and altered cell cycle regulation. Many genes which are upregulated by acid adaption are significantly correlated to patient survival, and there are clear correlations between acid adaptation expression response and expression change between normal and tumor tissues for a large subset of cancer patients. Importantly, our analyses reveal that genes whose expressions are changed by acid adaptation are linked both to increased and decreased overall patient survival. Thus, in conclusion, our data support the notion that adaptation to microenvironmental acidosis can drive the selection of highly invasive cancer cells and ECM remodeling in human patient tumors. However, consistent with existing experimental data, they also show that acid adaptation exerts inherently growth-limiting e↵ects, which could be important for cancer stem cell maintenance but may per se limit full-blown cancer development, until selected against or otherwise eliminated. Future studies should address what dictates the balance between these e↵ects, and hence the net e↵ects of acid adaptation on cancer development in vivo.

Supplementary Materials:

The following are available online at http://www.mdpi.com/2072-6694/12/8/2183/s1, Figures S1-S16: Kaplan-Meier overall survival analysis of cancer patients stratified by acidosis up-and downregulated gene expression levels, Table S1: Upregulated genes in pH 6.5 vs. pH 7.6, Table S2: Downregulated genes in pH 6.5 vs. pH 7.6, Table S3: GO and KEGG analysis of upregulated genes in pH 6.5 vs. pH 7.6, Table S4: GO and KEGG analysis of downregulated genes in pH 6.5 vs. pH 7.6, Table S5: Acidosis-upregulated genes significant in overall survival analysis in one type of cancer, Table S6: Acidosis-downregulated genes significant in overall survival analysis in one type of cancer; Table S7: Acidosis-upregulated genes, which showed contradictory survival analysis results across cancer types, Table S8: Acid adaptation-downregulated genes, which showed contradictory survival analysis results across cancer types.

Conflicts of Interest:

The authors declare no conflicts of interest.

Abstract

The transient receptor potential canonical 1 channel (TRPC1) is one of the most prominent nonselective cation channels involved in several diseases, including cancer progression. TRPCs can be activated by different physio-chemical stimuli of their surroundings, for instance, pH. Another hallmark of cancer is the variable extracellular pH landscape, notably in epithelial cancers such as pancreatic ductal adenocarcinoma (PDAC). PDAC progression and development are linked to the physiology and microenvironment of the exocrine pancreas. There are strong indications that PDAC aggressiveness is caused by the interplay between the tumor acidic microenvironment and ion channel dysregulation. However, this interaction has never been studied before. Here, we investigate if TRPC1 is involved in PDAC progression in the form of proliferation and migration and if the pH fluctuations of the acidic tumor microenvironment affect these processes. We found that TRPC1 was significantly upregulated in PDAC tumor tissue compared to adjacent normal tissue, and in the aggressive PDAC cell line PANC-1, compared to a duct-like cell line, hTERT-HPNE. To investigate if fluctuations of the acidic tumor microenvironment affect TRPC1 dysregulation, PANC-1 cells were incubated in a medium with a pH of 7.4 or 6.5 over 30 days, where after cells were recovered in pH 7.4 for 14 days (7.4R). Acid adaptation (6.5) reduced TRPC1 protein expression but favored its membrane localization compared to the control (7.4). pH recovery treatment (7.4R) resulted in an upregulation of TRPC1 expression with a high membrane localization, both in 2D and 3D models. We found that pH fluctuations and the siRNA-based knock-down (KD) of TRPC1 affected 2D and spheroid PANC-1 proliferation, respectively. In our 2D model, flow cytometry and cell cycle regulating protein immunoblotting showed that TRPC1 KD affected the progression through G0/G1 phase under all conditions and S-phase under control pH 7.4, which shifts to the G2/M phase in pH 6.5 and 7.4R. In addition, pH 6.5 enhanced, and the KD of TRPC1 decreased cell migration, respectively. Furthermore, we found that TRPC1 interacted strongly with PI3K under acidic conditions and CaM under all conditions, and a KD of TRPC1 decreased both this interaction and the activation of AKT and ERK1/2. Finally, basal Ca 2+ entry was significantly reduced upon the KD of TRPC1 in pH 6.5 and 7.4R, where the entry was enhanced. The reduction of extracellular Ca 2+ concentration resulted in an additional decrease in proliferation and migration of cells transfected with siTRPC1 growing in pH 6.5 and 7.4R, but not in normal pH 7.4 conditions. Collectively, our results show that TRPC1 is upregulated in PDAC tissue and cell lines. The acidic tumor microenvironment favors its plasma membrane localization, and its interaction with PI3K/CaM and Ca 2+ entry leads to PDAC cells proliferation and migration. In addition, we performed an expression profile screening of ORAI channels, their partner STIM1, and a voltage-activated sodium channel (Nav1.6), and an acid-sensing ion channel (ASIC1) in PDAC tissues and cell lines, and investigated whether the acidic tumor microenvironment affects epigenetic regulation of ion channel expression. We found that ORAI3 was upregulated in PDAC tissue compared to normal tissue, where STIM1 and NaV1.6 were significantly downregulated. Moreover, ORAI3 was more localized in the plasma membrane in tumor tissue. Acid-adaptation had a differential effect on Ca 2+ channel expression. Furthermore, our preliminary results show that the acidic tumor microenvironment does not affect the methylation levels of the ASIC1 or TRPC1 promoter region, but so some extend the SCN8A gene promoter. Keywords: Pancreatic cancer -Tumor microenvironment -Ion channels -Epigenetics Résumé Le canal TRPC1 (pour transient receptor potential canonical 1) est l'un des canaux cationiques non sélectifs les plus impliqués dans plusieurs maladies, y compris la progression du cancer. Les TRPC peuvent être activés par différents stimuli physico-chimiques dont le pH. Par ailleurs, l'une des caractéristiques du cancer représente les variations pH extracellulaire, notamment dans l'adénocarcinome canalaire pancréatique (ACP). Il existe de fortes indications quant à l'agressivité de l'ACP qui est causée par l'interaction entre le microenvironnement acide de la tumeur et la dérégulation des canaux ioniques. Cependant, cette interaction n'a jamais été étudiée. Lors de ce travail, nous avons étudié si TRPC1 ainsi que les fluctuations du pH acide du microenvironnement tumoral régulent la progression de l'ACP et plus particulièrement la prolifération et de migration cellulaires. Nous avons constaté que TRPC1 était surexprimé dans le tissu tumoral pancréatique par rapport au tissu normal, et dans la lignée cellulaire agressive PANC-1, par rapport à une lignée cellulaire de type canalaire, hTERT-HPNE. Pour déterminer si les fluctuations du microenvironnement acide de la tumeur affectent la dérégulation de TRPC1, les cellules PANC-1 ont été incubées dans un milieu présentant un pH de 7,4 ou 6,5 pendant 30 jours, après quoi les cellules ont été récupérées à pH 7,4 pendant 14 jours (7.4 R). L'adaptation acide (6.5) a réduit l'expression de la protéine TRPC1 mais a favorisé sa localisation membranaire par rapport au contrôle (7.4). Dans des conditions de pH 7,4R, les cellules cancéreuses présentaient une expression de TRPC1 exacerbée avec une localisation membranaire élevée, à la fois dans les modèles 2D et 3D. Nous avons constaté que les fluctuations de pH et l'invalidation moléculaire par siARN (KD) de TRPC1 affectaient respectivement la prolifération de PANC-1 dans un modèle 2D et sphéroïde. Dans notre modèle 2D, nous avons montré que TRPC1 KD affectait la progression à travers la phase G0/G1 dans toutes les conditions et la phase S lorsque les cellules sont cultivées dans un milieu pH 7,4, et la phase G2/M dans les conditions pH 6,5 et 7,4 R. En outre, pH 6,5 a amélioré tandis que le KD de TRPC1 a diminué la migration cellulaire. De plus, nous avons constaté que TRPC1 interagissait fortement avec PI3K dans des conditions acides, et CaM dans toutes les conditions. Le KD de TRPC1 diminuait à la fois cette interaction et l'activation de AKT et ERK1/2. Enfin, l'entrée basale de Ca 2+ a été significativement réduite par le KD de TRPC1 dans les conditions de pH 6,5 et 7,4R. La réduction de la concentration de Ca 2+ extracellulaire a entraîné une diminution additionnelle de la prolifération et de la migration des cellules transfectées avec siTRPC1 cultivées à pH 6,5 et 7,4R, mais pas dans des conditions normales de pH 7