Élodie Barthout
email: elodie.barthout@unilim.fr

Élisa Lambert
email: elisa.lambert@xlim.fr

Céline Hervieu
email: celine.hervieu@unilim.fr

Sofiane Saada
email: sofiane.saada@hotmail.fr

Rémi Manczak
email: remi.manczak@xlim.fr

Julie Pannequin
email: julie.pannequin@igf.cnrs.fr

Arnaud Pothier
email: arnaud.pothier@xlim.fr

Claire Dalmay
email: claire.dalmay@xlim.fr

Fabrice Lalloué
email: fabrice.lalloue@unilim.fr

Muriel Mathonnet
email: muriel.mathonnet@unilim.fr

Barbara Bessette
email: barbara.bessette@unilim.fr

UHF-Dielectrophoresis Microfluidic Lab-on-a-Chip to detect the transformation potential of extracellular vesicles derived from Cancer Stem Cells

Keywords: colorectal cancer, cancer stem cells, extracellular vesicles, high frequency dielectrophoresis, microfluidic lab-on-a-chip

Cancer stem cells remain a challenge to isolate and characterize because of their plastic phenotype. Using a microfluidic lab-on-a-chip based on ultra-high frequency dielectophoresis, we measured the electromagnetic signature of colorectal cancer cells and demonstrated that cancer stem cells show a distinct and lower electromagnetic signature than differentiated cells. The release of extracellular vesicles from tumor cells can drive tumor progression and metastasis development. As extracellular vesicles from cancer stem cells carry more aggressive content, we treated colorectal cancer cells with these vesicles to test whether the lab-on-a-chip can detect a change in phenotype. The electromagnetic signature of treated cells is modified in comparison to untreated cells and sometimes even when no biological change is observed. The lab-on-a-chip provides rapid and relevant result without prior labeling compared to conventional biological approaches. It could be useful in the clinic for early detection of cancer stem cells in the tumor mass and for monitoring the aggressive potential of extracellular vesicles in the bloodstream in order to adapt therapeutic management and prevent relapse.

Introduction

Colorectal cancer (CRC) is the second most diagnosed cancer in women and third most in men yet mortality in women is 25% lower than in men. Industrialized countries have the highest rates of CRC but they appear to be stabilizing or even decreasing due to screening campaigns and increased use of colonoscopy. Despite this, CRC is the fourth most deadly cancer in the world with nearly 900 000 deaths per year [START_REF] Dekker | Colorectal cancer[END_REF]. Furthermore, almost 25% of newly diagnosed CRC show distant metastasis [START_REF] Zhou | Tumor-derived exosomes in colorectal cancer progression and their clinical applications[END_REF] 50% of patients will develop metastasis during their lifetime [START_REF] Morand Du Puch | Chemotherapy outcome predictive effectiveness by the Oncogramme: pilot trial on stage-IV colorectal cancer[END_REF][START_REF] Manhas | Characterization of cancer stem cells from different grades of human colorectal cancer[END_REF]. Over the last decades, the diagnosis and care of CRC patients have improved considerably but relapses still occur and may be related to therapeutic resistance and/or the presence of a minimal residual disease (MRD).

A particular subpopulation within the heterogeneous tumor mass, known as cancer stem cells (CSCs) or tumor-initiating cells, is incriminated for both phenomena [START_REF] Hervieu | The Role of Cancer Stem Cells in Colorectal Cancer: From the Basics to Novel Clinical Trials[END_REF][START_REF] Hirata | Heterogeneity of Colon Cancer Stem Cells[END_REF]. These are highly plastic undifferentiated cells, resistant to conventional therapies due to their stemness and self-renewal capabilities. In CRC, it has been reported a direct correlation between the number of undifferentiated cells and high risks of relapse [START_REF] Manhas | Characterization of cancer stem cells from different grades of human colorectal cancer[END_REF][START_REF] Kong | Cancer Stem Cells and Epithelial-to-Mesenchymal Transition (EMT)-Phenotypic Cells: Are They Cousins or Twins?[END_REF].

Inside the stem cell niche, CSCs communicate with their microenvironment and this crosstalk relies on the secretion of extracellular vesicles (EVs). These are nanosized membrane vesicles ranging in size from 50 to 150 nm released by exocytosis of multivesicular bodies (MVB) from both tumor and healthy cells. They are found in all body fluids but usually, tumor cells release more EVs than their healthy counterparts [START_REF] Sumrin | Exosomes as Biomarker of Cancer[END_REF][START_REF] Kalluri | The biology and function of exosomes in cancer[END_REF].

The function of EVs in tumor development [START_REF] Zhou | Tumor-derived exosomes in colorectal cancer progression and their clinical applications[END_REF][START_REF] Morand Du Puch | Chemotherapy outcome predictive effectiveness by the Oncogramme: pilot trial on stage-IV colorectal cancer[END_REF][START_REF] Manhas | Characterization of cancer stem cells from different grades of human colorectal cancer[END_REF][START_REF] Hervieu | The Role of Cancer Stem Cells in Colorectal Cancer: From the Basics to Novel Clinical Trials[END_REF][START_REF] Hirata | Heterogeneity of Colon Cancer Stem Cells[END_REF][START_REF] Kong | Cancer Stem Cells and Epithelial-to-Mesenchymal Transition (EMT)-Phenotypic Cells: Are They Cousins or Twins?[END_REF][START_REF] Azmi | Exosomes in cancer development, metastasis, and drug resistance: a comprehensive review[END_REF], drug resistance [START_REF] Zhou | Tumor-derived exosomes in colorectal cancer progression and their clinical applications[END_REF][START_REF] Azmi | Exosomes in cancer development, metastasis, and drug resistance: a comprehensive review[END_REF] and the transfer of aggressiveness [START_REF] Zhou | Tumor-derived exosomes in colorectal cancer progression and their clinical applications[END_REF][START_REF] Pinet | TrkB-containing exosomes promote the transfer of glioblastoma aggressiveness to YKL-40-inactivated glioblastoma cells[END_REF][START_REF] Chiba | Exosomes secreted from human colorectal cancer cell lines contain mRNAs, microRNAs and natural antisense RNAs, that can transfer into the human hepatoma HepG2 and lung cancer A549 cell lines[END_REF][START_REF] Chiba | Exosomes derived from SW480 colorectal cancer cells promote cell migration in HepG2 hepatocellular cancer cells via the mitogen-activated protein kinase pathway[END_REF][START_REF] Wang | Investigation of the roles of exosomes in colorectal cancer liver metastasis[END_REF][START_REF] Huang | Exosomes Derived From Hypoxic Colorectal Cancer Cells Promote Angiogenesis Through Wnt4-Induced β-Catenin Signaling in Endothelial Cells[END_REF][START_REF] Wang | Transfer of microRNA-25 by colorectal cancer cell-derived extracellular vesicles facilitates colorectal cancer development and metastasis[END_REF] in solid cancers is widely documented. EVs act as a way of communication between cells by the exchange of genetic material [START_REF] Sumrin | Exosomes as Biomarker of Cancer[END_REF]. We previously demonstrated that EVs can induce an aggressive phenotype by transferring neutrotrophin receptors (TrkB) to YKL-40-inactivated glioblastoma cells that have lost their aggressive potential [START_REF] Pinet | TrkB-containing exosomes promote the transfer of glioblastoma aggressiveness to YKL-40-inactivated glioblastoma cells[END_REF]. Similarly, in glioblastoma (GBM), EVs can transfer the EGFRvIII, the truncated EGFR receptor associated with tumor progression [START_REF] Al-Nedawi | Intercellular transfer of the oncogenic receptor EGFRvIII by microvesicles derived from tumour cells[END_REF]. In CRC, many studies have highlighted the role of EVs on the transfer of aggressiveness. EVs derived from CRC cell lines can deliver mRNAs, microRNAs and natural antisense RNAs to other solid cancer cell lines to control their gene expression [START_REF] Chiba | Exosomes secreted from human colorectal cancer cell lines contain mRNAs, microRNAs and natural antisense RNAs, that can transfer into the human hepatoma HepG2 and lung cancer A549 cell lines[END_REF] or to promote the cell migration of a hepatocellular cancer cell line [START_REF] Chiba | Exosomes derived from SW480 colorectal cancer cells promote cell migration in HepG2 hepatocellular cancer cells via the mitogen-activated protein kinase pathway[END_REF]. Colon cancer-derived EVs may stimulate the tumor angiogenesis by activating endothelial cells [START_REF] Huang | Exosomes Derived From Hypoxic Colorectal Cancer Cells Promote Angiogenesis Through Wnt4-Induced β-Catenin Signaling in Endothelial Cells[END_REF], promote acquired resistance to 5-FluoroUracile (5-FU) [START_REF] Zhang | Exosomal transfer of p-STAT3 promotes acquired 5-FU resistance in colorectal cancer cells[END_REF] and facilitate the development and metastasis of CRC [START_REF] Wang | Transfer of microRNA-25 by colorectal cancer cell-derived extracellular vesicles facilitates colorectal cancer development and metastasis[END_REF]. EVs can also affect the antitumor immune response. Indeed, they facilitate immune escape by inhibiting macrophage activation [START_REF] Popēna | Effect of colorectal cancer-derived extracellular vesicles on the immunophenotype and cytokine secretion profile of monocytes and macrophages[END_REF], by blocking T cell proliferation and promoting regulator T cell expansion [START_REF] Yamada | Colorectal cancer cell-derived extracellular vesicles induce phenotypic alteration of T cells into tumor-growth supporting cells with transforming growth factor-β1-mediated suppression[END_REF]. In summary, EVs are considered an important source of circulating tumor biomarkers. Therefore, they could represent an efficient strategy to remotely monitor exchanges between CSCs and their microenvironment and thus predict drug resistance, tumor progression or the risk of relapse.

Isolation and characterization of CSCs are difficult because they represent less than 10% of the tumor mass [START_REF] Hanahan | Hallmarks of Cancer: New Dimensions[END_REF] and the biological markers commonly used are shared with normal stem cells. Moreover, the level of expression of biological markers is not sufficient to characterize these cells and functional properties need to be explored. All these techniques are time consuming and quite expansive. Thus, the last few years, we developed a new label-free approach based on the detection of biophysical cell properties. It consists in measuring the electromagnetic (EM) signature of individual cells by dieletrophoresis (DEP) technique in the ultra-high frequency (UHF) range. A lab-on-a-chip implemented in a microfluidic channel allows the manipulation of individual cells to determine their EM signature called "crossover frequency". This precise frequency is related to the intracellular content of the characterized cell. CSCs and differentiated cells from brain tumors have already been characterized with this device [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF][START_REF] Casciati | Human Medulloblastoma Cell Lines: Investigating on Cancer Stem Cell-Like Phenotype[END_REF] making it an interesting tool for CSCs diagnosis in clinical routine.

In this work, we used this lab-on-a-chip on colorectal cancer-derived cells to investigate whether CSCs exhibit a different EM signature than differentiated cells, as previously observed in brain tumors [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF][START_REF] Casciati | Human Medulloblastoma Cell Lines: Investigating on Cancer Stem Cell-Like Phenotype[END_REF]. In addition, EVs derived from CSCs carry more aggressive content than differentiated cells. We therefore performed aggressiveness transfer to demonstrate that the lab-on-a-chip can monitor phenotypic transformation. Here, we reported that CSCs show a lower EM signature than their differentiated counterparts, in both cell lines and primary CRC cultures. Moreover, this lab-on-a-chip can detect cellular changes caused by EVs intake that may eventually be missed in biology. This label-free technique allows biophysical characterization of cells and could be useful for early detection of CSCs in the tumor mass to improve the management of CRC patients.

Preprints

Materials and Methods

Cell culture

2.1.1 Cell lines and primary cultures of patient SW480 and SW620 cell lines were purchased from the American Type Culture Collection (ATCC/LGC Promochem, Molsheim, France) and were grown in RPMI 1640 Glu-taMAX TM (Gibco™, Thermo Fisher, MA, USA) medium supplemented with 10% FBS, 1% sodium pyruvate and 1% of penicillin / streptomycin (Thermo Fisher).

Two primary cultures from patients (CPP) were gently provided by Julie Pannequinfrom the Institute of Fonctional Genomics (Univ. Montpellier, France) after informed consent of patients (Material Transfer Agreement CNRS 190287). CPP were grown in DMEM GlutaMAX TM medium supplemented with 10% FBS and 1% penicillin / streptomycin (Thermo Fisher).

Culture under FBS will be referenced as "Normal Medium" (NM).

Cancer stem cells (CSCs) enrichment

To enrich the cell population in CSCs, cell lines or CPP were cultured for at least one week in a "Define Medium" (DM): DMEM/F-12 (Thermo Fisher) medium without FBS but supplemented with 5 µg/mL of insulin, N-2 supplement (1X), 1% of penicillin / streptomycin (Thermo Fisher), 20 ng/mL of EGF and 20 ng/mL of bFGF (MACS Miltenyi Biotec, Bergisch Gladbach, Germany).

All cell types were cultured at 37°C in a humidified atmosphere of 5% CO2 and 95% air.

Cell treatment with extracellular vesicles (EVs)

To undergo EVs transfer aggressiveness, cells were seeded in a 6-wells plate at 0,25.10 6 cells and treated with EVs from 1.10 6 cells (NM or DM cultured cells) resuspended in a "exo-free" culture medium. Exo-free culture medium is a conventional culture medium with EVs-deprived FBS by ultracentrifugation at 120 000g for 16h. Cells were treated for 24h or 72h, once or twice with the same amount of EVs each time.

Extracellular vesicles

Isolation

Cells were seeded in a T75 flask at 1.10 6 cells for 10 mL of medium and cultured for 48h before collection of culture supernatant. To collect EVs, the culture supernatant was ultracentrifugated at 120 000g for 90 min twice to pellet and wash vesicles. Then, EVs were resuspended in phosphate-buffered saline (PBS, Thermo Fisher) for nanoparticle tracking analysis (NTA) or in culture medium for cell treatment or in RIPA buffer for western blot analysis.

Nanoparticle tracking analysis (NTA)

NTA was performed using NanoSight NS300 (Malvern Panalytical Ltd.) with specific parameters according to the manufacturer's user manual (NanoSight NS300 User Manual, MAN0541-01-EN-00, 2017). Captures and analysis were achieved by using the built-in NanoSight Software NTA3.3.301 (Malvern Panalytical Ltd.). The camera level was set at 14 and the detection threshold was fixed at 5. Samples were diluted in PBS (Thermo Fisher) and their concentration was adjusted by observing a particles/frame rate of around 50 (30-100 particles/frame). For each measurement, five consecutive 60-s videos were recorded under the following conditions: cell temperature-25 • C, syringe speed-22 μL/s (100 a.u.). Particles (EVs) were detected using a 488 nm laser (blue), and a scientific CMOS camera. Among the information given by the software, the following were studied: mode (i.e., the most represented EVs size population), the percentage of EVs between 50-150 nm and particles/mL. Using the last one and the number of cells collected, we calculated an EVs/cell ratio for each condition.

RNA extraction and RT-qPCR

Total RNA was extracted using RNeasy kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions and quantified by NanoDrop 2000 (Thermo Fischer). For RT-qPCR analyses, 2 µg of RNA was reverse-transcribed into cDNA using the cDNA Archive kit (Applied Biosystems, MA, USA). Quantitative gene expression was performed using SensiFAST Probe Hi-ROX kit (Bioline, London, UK) on QuantStudio 5 (Thermo Fischer) and stemness related genes (PROM1, NANOG, SOX2, POU5F1, BMI1, LGR5) were analyzed. Results were normalized to GADPH and HPRT1 expressions and analyzed using the ∆∆Ct method (control condition defined as 1).

Western blot

After collection, EVs were resuspended and lysed in RIPA buffer (50 mM Tris-HCl, pH 7.4, 1% NP-40, 0.5% Na-deoxycholate, 0.1% SDS, 150 mM NaCl, 2 mM EDTA, 50 mM NaF) supplemented extemporaneously with a cocktail of protease inhibitors (Roche, Bâle, Switzerland). Samples were separated on a 12% SDS-polyacrylamide gel electrophoresis, transferred to polyvinylidene difluoride (PVDF) membrane, blocked for 1 h in 5% (w/v) bovine serum albumin (BSA) in PBS and probed overnight at 4 °C with primary antibodies specific of EVs (Alix, Hsc70 and CD9). Membranes were then incubated with the proper secondary antibodies for 1 h and proteins revealed by Immobilon ECL Ultra (Merck Millipore, MA, USA) using a G-box imager with GeneSnap software (Syngene).

Flow cytometry

Stemness markers

Differentiated cells (NM) or CSCs (DM) were rinsed in PBS and 1.10 6 cells were labelled with extracellular anti-CD133, anti-Lgr5 and viability marker antibodies. Cells were incubated 30 min at RT in the dark, washed in PBS and then fixed 10 min in 4% PFA. After a wash, cells were permeabilized 30 min at 4°C in Perm buffer III (BD Biosciences, Le Pont de Claix, France). Finally, cells were labelled with intracellular antibodies of anti-Bmi1, anti-Oct4 and anti-Nanog for 30 min at RT in the dark. Samples were analyzed with a CytoFLEX flow cytometer (Beckman Coulter, CA, USA). Data analysis was performed using Kaluza software (v2.1, Beckman Coulter).

Cell cycle analysis

Cells were washed with ice-cold PBS, resuspended in ice-cold 70% ethanol and placed at -20°C overnight. The next day, after a wash, cells were incubated 20 min with RNase A (Sigma Aldrich, MO, USA) and Propidium Iodide (PI) before analysis on a Cy-toFLEX flow cytometer (Beckman Coulter). Results were analyzed using ModFit LT™ software (v5.0.9, Verity Software House, ME, USA).

Proliferation Assay

Five thousand cells were seeded in a 96-well plate and proliferation was measured using BrdU Cell Proliferation Assay Kit (Cell Signaling, MA, USA) according to the manufacturer's instructions. Absorbance was measured at 450 nm with a Multiskan FC Thermo Scientific microplate photometer (Thermo Fisher).

Metabolic activity assay

Five thousand cells were seeded in a 96-well plate and treated or not by EVs from NM or DM cultured cells for 24 or 72h at the same ratio as. After

Migration and invasion assays

Fifty thousand cells were seeded in an Incucyte® Imagelock 96-well Plate (Sartorius, Goettingen, Germany) and scratch migration and invasion assays were performed according to the manufacturer's instructions. Briefly, cells were seeded and allowed to adhere overnight. The next day, wounds were created with the 96-well WoundMaker (Sartorius), cells were washed twice and 100 µL of culture medium containing or not EVs was added to the wells.

For invasion assay, after wound creation, cells were overlay with 50 µL of Matrigel® (Corning, NY, USA) solution. After 30 min at 37°C for Matrigel® polymerization, 100 µL of culture medium containing or not EVs was added to the wells. The plate was placed in the Incucyte® system (Sartorius) and wound closure was analyzed every 2h for 2 days using IncuCyte 2021A software (Sartorius).

Self-renewal capacity

Five hundred of NM or DM cultured cells were seeded in a 96-well plate in define medium for 7 days and analyzed every 24h with the Incucyte® system (Sartorius) and analyzed using IncuCyte 2021A software (Sartorius).

UHF-DEP Crossover frequency measurement

With UHF-DEP, we are able to electromanipulate particles, such as biological cells. In a microfluidic channel is implemented a quadrupole electrode in which a suspension of individual cells is injected. The microfluidic flow allows to stop a single cell at the center of the microelectrode for its individual DEP characterization (Figure 1H). Signals in the Ultra-High Frequency (UHF) range of 30-450 MHz are used to probe the intracellular content of the cell. The movement of the cells from a "repulsive" state (nDEP) at the center of the quadrupole to an "attractive" state (pDEP) at one edge of the electrodes is done at a specific frequency called "crossover frequency" which is the cell's electromagnetic signature. The measurement of this crossover frequency allows to discrimintate cells by measuring the dielectric properties of their cytoplasmic content without any labeling. For further information, please see our precedent publication [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF].

Statistical analysis

Values are represented by mean ± SEM obtained from at least three independent experiments except values from DEP analyses, represented as mean ± SD. Statistical analysis was performed using PAST software (version 2.17c) by one-way ANOVA (*: p < 0.05, **: p < 0.01, ***: p < 0.001).

Results

Cancer stem cells from colorectal cancer cell lines show a lower EM signature than their differentiated counterparts

To test the lab-on-a-chip on CRC, two cell lines from the same CRC patient: SW480 as a stage II and SW620 as a stage III (tumor-invaded lymph nodes) were chosen. is a medium without FBS but supplemented with growth factors to generate stress on cells and force them to acquire stem-like cells properties. As shown in Figure 1A, cells cultured in DM are no longer adherent but grow as colonospheres, resulting in the acquisition of "stemness" properties. To confirm that these conditions induce a phenotypic shift to CSCs, we assessed their phenotypical and functional properties. Both cell lines cultured under define medium overexpress almost all stemness tested genes (CD133, Sox2, Oct4).

Interestingly for both cell lines, stem-like cells underexpress Lgr5 which is related to the level of cell activation, and SW620-DM overexpress Bmi1 which is correlated to a quiescence state (Figure 1B). The same markers were investigated by flow cytometry to analyze their protein counterparts. No significant differences were observed with SW480 cell line whereas all markers were overexpressed by SW620 cells cultured in DM compared to SW620-NM, except from CD133 (Figure 1C). The SW480 cell line appears to require a longer time in define medium to overexpress these markers than the SW620 cell line, suggesting that stage III-derived cells have a more pronounced "cancer stem cells" burden. Indeed, SW620 cells always overexpress stemness related proteins compared to SW480 cells, regardless of culture conditions (Figure S1B). Since an overexpression of stemness related markers is not sufficient to consider a cell as a CSC, we explored its functional properties as well. For both cell lines, stem-like cells show a lower proliferation rate than differentiated cells (Figure 1D). Furthermore, the proportion of SW480-DM cells in the G2/M phase of the cell cycle is higher than that of SW480-NM cells, while the rate of cells in the G0/G1 phase is higher for SW620-DM cells than for SW620-NM cells (Figure 1G), consistent with the aforementioned overexpression of Bmi1. In a similar way, cellular response to 5-FU chemotherapy treatment (chemoresistance) was assessed by measuring metabolic activity and stem-like cells show a 5-fold higher IC50 than the differentiated ones (Figure 1E). Finally, we explored the ability of cells to self-renew by culturing them in define medium for seven days. For both cell lines, stem-like cells form more and larger colonospheres (Figure 1F). Altogether, these results allow us to consider cells cultured under define medium as cancer stem cells. In a previous work, we biophysically characterized brain tumor cells and the U87-MG glioblastoma cell line with the lab-on-a-chip and established a first EM signature related to it. Our results demonstrated that CSCs display a lower EM signature in the fx02 range whereas no difference was observed in the fx01 range [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF]. On this basis, the fx02 range was selected to test CRC cells in our experiments. Similar results were observed for both CRC cell lines, as previously in the brain model, the EM signature is lower in CSCs than in differentiated cells (Figure 1I). Furthermore, we observe a complete change in electromagnetic signatures between CSCs and differentiated cells. For both cell lines, almost 100% of the differentiated cells show a crossover frequency between 200 and 400 MHz (88% for SW480 and 100% for SW620) while both CSCs show 100% of the cells between 0 and 100 MHz (Table 1, Figure S1I). and stemness markers (C) were analyzed. Functional properties were explored with proliferation (D), response to chemotherapy (E), self-renewal capacity (F) and cell cycle analysis (G). The EM signature of both cell types was measured at UHF (fx02) with a lab-on-a-chip (H-I). EVs from SW620 cells (differentiated cells or CSCs) were collected by ultracentrifugation (J) and expression of EVs markers was assessed by western blot (K). NTA was performed on EVs regarding size distribution (L), percentage of EVs between 50 and 150 nm (M) and number of secreted EVs per cell (N). All results are represented as mean ± SEM except EM signatures represented as mean ± SD, NS p-value indicate not significant result, * p-value < 0.05, ** p-value < 0.01, *** p-value < 0.001 using one-way ANOVA test. Although these results confirm that CSCs are enriched in both CRC cell lines cultured in define medium, SW480-DM and SW620-DM are not dependent of the same step of cell cycle. Thus, SW480-DM appear to be a proliferative type of CSCs while SW620-DM appear to be a quiescent one. This EM signature is consistent with those previously obtained for glioblastoma and medulloblastoma tumors [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF][START_REF] Casciati | Human Medulloblastoma Cell Lines: Investigating on Cancer Stem Cell-Like Phenotype[END_REF].

Extracellular vesicles transfer some aggressive properties and this change in state can be detected by biophysics in colorectal cancer cell lines

As EVs transfer genetic and protein materials derived from tumors, CSCs-derived EVs might transfer additional tumor aggressiveness compared to differentiated cells due to their more aggressive content. Indeed, our previous results put on evidence that EVs from undifferentiated cells related to CSCs transferred tumor aggressiveness to less aggressive tumor cells. In this context, SW480-NM (early-stage) was treated with EVs from the SW620 cell lines (late-stage) to assess a putative aggressiveness transfer. After culturing the SW620 cell line under both culture conditions, supernatant were ultracentrifugated to collect EVs (Figure 1J). NTA and western blot analyses confirmed their characteristics and CSCs secrete less EVs than differentiated cells (Figure 1K-N). The SW480 cell line, cultured in NM, was treated once for 24h with EVs derived from SW620 cell line (cultured in NM or DM) (Figure 2A). Analysis of stemness-related gene expression demonstrated that cells treated with EVs from SW620-DM overexpress CD133, Sox2 and Lgr5 whereas no difference was observed with EVs from SW620-NM (Figure 2B). Conversely, cells treated with EVs from SW620-NM show a higher proliferation rate that increases overtime, although no change was observed with EVs from SW620-DM (Figure 2C). Strikingly, this lack of change when cells are treated with EVs derived from CSCs suggests that these cells may be blocked in G0/G1 phase like SW620-DM cells, but the distribution in the cell cycle remains unchanged (Figure 2D). Regarding the response to chemotherapy, both types of EVs result to a 3-fold higher IC50 of treated cells (Figure 2E). Migration and invasion can lead to metastasis, a main hallmark of cancer [START_REF] Hanahan | Hallmarks of Cancer: New Dimensions[END_REF]. These abilities were investigated upon EVs treatment, and no difference is observed on migration (Figure 2F) but both types of EVs improve the invasion of SW480-NM. Nevertheless, EVs derived from SW620-DM significantly enhance invasion properties that are triggered only 6 hours after treatment whereas the effect of EVs from SW620-NM is delayed to 48 hours (Figure 2G). Since the phenotype of targeted cells could be influenced by EVs derived from CSCs, the EM signatures of SW480-NM treated with EVs from the SW620 cell line were measured to demonstrate that the effects of EVs are not restricted to biological modifications. Cells treated with EVs from CSCs show a lower EM signature than untreated cells (Figure 2I), whereas the EM signature remains the same with EVs from differentiated cells (Figure 2H). To determine if the amount of EVs influences the treated cells in a dosedependent manner, cells were treated twice for 72h. No dose effect is observed for cells treated with EVs from SW620-NM while the EM signature is even lower for cells treated with EVs from CSCs (Figure 2H,I). However, we observe a slight redistribution of the EM signatures with the appearance of cells with an EM below 100 MHz and 10% of additional cells with an EM higher than 300 MHz for cells treated once with EVs from SW620-NM, and 17% when treated twice (Table 2 and Figure S2B). promote proliferation while both types enhance invasion and metabolic activity. Regarding the EM signatures, the lab-on-a-chip appears to detect a difference only for cells treated with EVs from CSCs. Since part of the biological changes triggered by CSCs derived-EVs are correlated with the change in EM signature, EM signature might be of primary importance to monitor the phenotypic transformation induced by the transfer of aggressive content from EVs.

Cancer stem cells from primary cultures of patient show a lower EM signature than their differentiated counterparts

To achieve a proof of concept in clinical conditions, our first results were transposed to tumor cells from CRC patients. Two primary cultures of patient (CPP) from primary tumors were used: CPP14 from a stage I and CPP6 from a stage IV (metastasis stage). As above, cells were cultured in the same two culture conditions and in define medium, they grow as colonospheres (Figure 3A) and overexpress all stemness related genes except Bmi1 and Lgr5 (Figure 3B). As for cell lines, CSCs show a lower EM signature compared to differentiated cells (Figure 3C). Compared to cell lines and CPP6, EM signature of CSCs from CPP14 is not opposite to that of differentiated CPP14, there is just a loss of cells between 200 and 300 MHz and an enrichment of cells between 0 and 100 MHz. For CPP6, 100% of differentiated cells are between 100 and 400 MHz while only 15% of CSCs are (Table 3 and Figure S3B).

Extracellular vesicles from primary cultures of patient can transfer aggressive properties and induce EM signature changes detected by biophysics

To demonstrate the transfer of aggressiveness due to EVs derived from aggressive cells, CPP14-NM cells were treated with EVs from CPP6 derived from a metastatic tumor (stage IV). CPP6 was cultured under normal or define medium to collect EVs by ultracentrifugation (Figure 3D). Both types of vesicles express specific EVs markers such as Alix, Hsc70 and CD9 (Figure 3E) and are between 50 and 150 nm in size (Figure 3F,G). Nevertheless, as previously described, CSCs tend to secrete less EVs than differentiated cells (Figure 3H). As with the cell lines, CPP14-NM were treated with EVs from CPP6-NM or CPP6-DM. Since the EM signature result for SW480-NM treated with EVs from SW620-DM was more pronounced with a two-step treatment for 72h, we chose to keep only this treatment (Figure 4A). When CPP14-NM are treated with EVs from CPP6-DM, they overexpress Nanog, Sox2 and Oct4, whereas with EVs from CPP6-NM, cells significantly underexpress CD133, Nanog and Oct4 (Figure 4B). In contrast, no significant effect of EVs on cell cycle (Figure 4C) or 5-FU response is obtained, although there is a trend toward increased metabolic activity, especially for cells treated with EVs from CSCs (Figure 4D). Strikingly, regardless of the origin of EVs used to treat CPP14-NM cells, the EM signatures increase significantly upon treatment suggesting that the biological changes (increase of CSCs-related genes) that were previously observed are not related to the change in EM signatures (Figure 4E,F, Table 4). Both EVs alter the state of treated cells with a distinct higher EM signature. Biologically, we only see an overexpression of some stemness related genes for cells treated with EVs from CSCs and a trend toward increased metabolic activity.

Preprints

Extracellular vesicles from the same primary culture of patient have an impact on their EM signature

Because CPP14 and CPP6 come from two CRC patients, they are genetically different and come from a different microenvironment, so we treated CPP6-NM with EVs from the same CPP but cultured in define medium, twice for 72h (Figure 5A). Unfortunately, we do not see any difference in stemness markers expression, cell cycle distribution or response to 5-FU upon treatment (Figure 5B-D). Interestingly, we observe a distinct and lower EM signature when cells are treated with EVs from CSCs (Figure 5E). No biological effects are observed when CPP6-NM are treated with EVs from CPP6-DM but the EM signature is lower. This does not mean that no biological change has occur but that those testes have not evolved with EVs intake. Moreover, this result highlights the relevance of the EM signature which is complementary to biological analysis and can reveal changes that may be missed in biology.

Preprints

Discussion

Our work highlights the relevance of our lab-on-a-chip using UHF-DEP analysis to discriminate and track cells status. Previously, the lab-on-a-chip allowed us to distinguish differentiated cells and CSCs in two types of brain tumors. In both cases, the study revealed that CSCs show a distinct and consistently lower EM signature than differentiated cells [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF][START_REF] Casciati | Human Medulloblastoma Cell Lines: Investigating on Cancer Stem Cell-Like Phenotype[END_REF]. Our first goal was to transfer this technology to CRC to determine if the changes in EM signatures are solely a signature of brain tumors or if they can be applied to other tumors. Our main objective is to demonstrate that EM signatures can be modified when tumor cells are treated with EVs derived from aggressive tumor cells related to CSCs. By culturing cells in a define medium to enrich in CSCs, we observed in cell lines and in primary cultures of CRC patient that CSCs show a distinct and consistently lower EM signature than differentiated cells. The characterization and discrimination of CSCs in a heterogeneous tumor mass remains a challenge since their discovery two decades ago. Initially, the scientific community thought that only stemness markers were needed to label a cell as a CSC. For many years, a lot of scientists have tried to find the best markers and characterization techniques to identify CSCs [START_REF] Hervieu | The Role of Cancer Stem Cells in Colorectal Cancer: From the Basics to Novel Clinical Trials[END_REF]. Since these markers are also expressed by normal stem cells, only their expression level could be useful to distinguish normal from cancer stem cells. Next, functional properties were assessed to complete the phenotypic characterization and to overcome the lack of universal CSC markers. Unfortunately, new evidence of massive cellular plasticity has emerged in recent years and has been adopted by the scientific community as a new "Hallmark of Cancer" in 2022 [START_REF] Hanahan | Hallmarks of Cancer: New Dimensions[END_REF]. Due to this dynamic plasticity, it is more complicated to qualify a cell as a CSC based on phenotypic and functional characterizations. Moreover, these techniques are expensive, time consuming and require special equipment not still available in laboratories. Although these approaches are time consuming, they were necessary to ensure that cells cultured in define medium were enriched in CSCs. In contrast, UHF-DEP analysis allows us to characterize and discriminate CSCs in a short time of about one hour without prior labeling.

Second, as EVs have received increasing interest in recent years due to their ability to transfer aggressive properties to other cells or cells in the tumor microenvironment [START_REF] Zhou | Tumor-derived exosomes in colorectal cancer progression and their clinical applications[END_REF][START_REF] Pinet | TrkB-containing exosomes promote the transfer of glioblastoma aggressiveness to YKL-40-inactivated glioblastoma cells[END_REF][START_REF] Chiba | Exosomes secreted from human colorectal cancer cell lines contain mRNAs, microRNAs and natural antisense RNAs, that can transfer into the human hepatoma HepG2 and lung cancer A549 cell lines[END_REF][START_REF] Chiba | Exosomes derived from SW480 colorectal cancer cells promote cell migration in HepG2 hepatocellular cancer cells via the mitogen-activated protein kinase pathway[END_REF][START_REF] Wang | Investigation of the roles of exosomes in colorectal cancer liver metastasis[END_REF][START_REF] Huang | Exosomes Derived From Hypoxic Colorectal Cancer Cells Promote Angiogenesis Through Wnt4-Induced β-Catenin Signaling in Endothelial Cells[END_REF][START_REF] Wang | Transfer of microRNA-25 by colorectal cancer cell-derived extracellular vesicles facilitates colorectal cancer development and metastasis[END_REF] (tumor cells, immune cells, stromal cells …), we wanted to test whether the lab-on-achip could detect a phenotypic change induced by EVs intake. We started with two cell lines from the same CRC patient. Based on EVs cargo secreted by CSCs carry more aggressive properties than those secreted by differentiated cells, SW480 cell line cultured under normal medium (SW480-NM) was treated with EVs from the SW620 cell line cultured under normal or define medium (SW620-NM or SW620-DM). Biological results confirm that stemness related genes (CD133, Sox2, Lgr5) were overexpressed by cells treated with EVs from CSCs. In contrast to the proliferation rate which was mainly increased in cells treated with EVs from differentiated cells. Regardless of the EVs treatment, resistance to chemotherapy increased threefold. No EM signature changes were detected between native SW480 and SW480 treated with EVs derived from SW620-NM suggesting that the EV content of the latter is unlikely to increase SW480 aggressiveness and induce the acquisition of stemness properties. On the contrary, when SW480 were treated with SW620-DM, the EM signature was significantly reduced compared to untreated SW480. Similar experiments were performed with primary CRC cells derived from two patients. However, treatment of early-stage primary cells (CPP14) with EVs from primary cells derived from a late-stage tumor (CPP6) was achieved to determine if EVs are able to transfer tumor aggressiveness as previously demonstrated in glioblastoma [START_REF] Pinet | TrkB-containing exosomes promote the transfer of glioblastoma aggressiveness to YKL-40-inactivated glioblastoma cells[END_REF]. As expected, gene expression analysis confirms that only CPP14 treated with EVs from CPP6-DM overexpress genes related to CSCs (Nanog, Sox2, Oct4), suggesting that the ability of EVs to transfer aggressiveness depends on the nature of the cells that released them. The results also show that the cell cycle distribution was not altered by EVs intake compared to untreated cells and that the metabolic activity tended to increase by the supply of EVs from CSCs. Strikingly, the EM signatures increased with both EVs indicating a phenotypic change even for cells treated with EVs from differentiated cells while no biological changes were detected. This experiment suggests that the lab-on-a-chip might help to detect changes that are difficult to demonstrate by conventional biological approaches. In contrast, the last experiment showed that when CPP6-NM cells were treated with EVs from CPP6-DM, they retained similar phenotypic characteristics. However, the EM signature is significantly reduced upon treatment, confirming that biophysical properties are relevant for detecting changes that can potentially be missed in biology. The lab-on-a-chip provides relevant results without pre-labeling and is less expensive to use than most biological techniques. It allows to distinguish CSCs from differentiated cells in several types of solid tumors but also to follow the cells to see their evolution [START_REF] Lambert | Microfluidic Lab-on-a-Chip Based on UHF-Dielectrophoresis for Stemness Phenotype Characterization and Discrimination among Glioblastoma Cells[END_REF][START_REF] Casciati | Human Medulloblastoma Cell Lines: Investigating on Cancer Stem Cell-Like Phenotype[END_REF]. We used it to track cells treated with EVs, but it could be used on liquid biopsies to detect EVs in peripheral blood and monitor their aggressive potential even before analyzing their contents. The analysis of the EM signature of EVs would complement their biological analysis and allow assessment of tumor heterogeneity and the risk of relapse induced by the transfer of genetic and protein materials from therapy resistant cells. In addition, the development of a sorting device based on this technology could be used to isolate CSCs from the tumor mass. The isolation of CSCs will be faster and less expensive than conventional techniques based on phenotypic and functional properties of the cells without altering their properties by prior labelling. As a high number of undifferentiated cells is known to correlate with a high risk of relapse in CRC [START_REF] Manhas | Characterization of cancer stem cells from different grades of human colorectal cancer[END_REF][START_REF] Kong | Cancer Stem Cells and Epithelial-to-Mesenchymal Transition (EMT)-Phenotypic Cells: Are They Cousins or Twins?[END_REF], this tool would allow potential early detection of the CSCs subpopulation in the tumor and therefore adapt the care of CRC patients.

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  Each cell line was cultured under two distinct conditions: Normal Medium (NM) to enrich cell population in differentiated cells or Define Medium (DM) to enrich in CSCs. Define medium Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 19 October 2022 doi:10.20944/preprints202210.0276.v1

PreprintsBFigure 1 .

 1 Figure 1. Characterization of cell lines and their extracellular vesicles according to culture conditions. (A) Cells were cultured under Normal Medium (NM) or Define Medium (DM) to enrich cell population in differentiated cells or CSCs. To validate culture conditions, stemness related genes (B)

Preprints

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Figure 2 .

 2 Figure2. Impact of EVs derived from SW620 on the SW480 cell line. (A) SW480-NM cells were treated once for 24 h with EVs derived from the SW620 cell line (NM or DM cultured cells) to test an aggressiveness transfer. To assess the biological effects of this treatment, stemness related genes (B) were analyzed, as well as the proliferation rate (C), cell cycle (D) and chemotherapy response (E). The ability of cells to migrate (F) or invade (G) has also been explored (*: +EVs SW620 versus untreated SW480, £: +EVs SW620 NM versus untreated SW480) and EM signatures measured (H-I). All results are represented as mean ± SEM except EM signatures represented as mean ± SD, NS pvalue indicate not significant result, * and £ p-value < 0.05, ** p-value < 0.01, *** p-value < 0.001 using one-way ANOVA test.Both types of EVs influence treated cells but not at the same level. EVs from CSCs lead to the overexpression of some stemness-related genes, EVs from differentiated cells

Figure 3 .

 3 Figure 3. Characterization of primary cultures of patient and their extracellular vesicles according to culture conditions. (A) Two primary cultures of patients at different stages of CRC were cultured under NM or DM to enrich cell population in differentiated cells or in CSCs. The expression of stemness-related genes (B) was explored and EM signatures (C) measured. EVs from CPP6 (NM or DM cultured cells) were collected by ultracentrifugation (D) and expression of EVs markers was assessed by western blot (E). NTA was performed on EVs regarding size distribution (F), percentage of EVs between 50 and 150 nm (G) and number of secreted EVs per cell (H). All results are represented as mean ± SEM except EM signatures represented as mean ± SD, NS p-value indicate not significant result, * p-value < 0.05, ** p-value < 0.01, *** p-value < 0.001 using one-way ANOVA test.

Figure 4 .

 4 Figure 4. Impact of extracellular vesicles from CPP6 on CPP14 cells. (A) EVs from CPP6 cells (NM or DM cultured cells) were used to treat CPP14-NM cells twice and for 72h. To assess the biological effect of EVs, expression of stemness related genes (B), cell cycle (C), chemotherapy response (D) and EM signatures (E-F) were analyzed. All results are represented as mean ± SEM except EM signatures represented as mean ± SD, NS p-value indicate not significant result, * p-value < 0.05, ** pvalue < 0.01, *** p-value < 0.001 using one-way ANOVA test.

Figure 5 .

 5 Figure 5. Impact of extracellular vesicles from CPP6 on the same type of cells. (A) EVs from CPP6 cultured under define medium were used to treat CPP6-NM cells twice and for 72h. To undergo the biological effect, stemness related genes (B), cell cycle (C), chemotherapy response (D) and EM signatures (E) were analyzed. All results are represented as mean ± SEM except EM signatures represented as mean ± SD, NS p-value indicate not significant result, * p-value < 0.05, ** p-value < 0.01, *** p-value < 0.001 using one-way ANOVA test.

Preprints

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24 or 72h of treatment, Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 19 October 2022 doi:10.20944/preprints202210.0276.v1

	cells were treated with decreasing doses of 5-FU for 48h (500 µM to 1 µM). Cell toxicity
	was measured using CellTiter 96	®	AQ ueous	One Solution Cell Proliferation Assay
	(Promega, WI, UA) according to the manufacturer's instructions and IC50 was determined
	graphically (GraphPad Prism 7.04).

Table 1 .

 1 Cell proportions per frequency range for colorectal cancer cell lines

		SW480		SW620
		Normal medium	Define medium	Normal medium	Define medium
	0-100 MHz	0%	70%	0%	78%
	100-200 MHz	12%	30%	0%	22%
	200-300 MHz	68%	0%	24%	0%
	300-400 MHz	20%	0%	76%	0%

Table 2 .

 2 Cell proportions per frequency range for SW480 treated with EVs

	Preprints (www.
		SW480	+ EVs SW620 NM	+ EVs SW620 DM
		Normal medium	24h	72h	24h	72h
	0-100 MHz	0%	3%	2%	12%	15%
	100-200 MHz	12%	19%	19%	31%	51%
	200-300 MHz	68%	48%	42%	45%	27%
	300-400 MHz	20%	30%	37%	11%	8%

preprints.org) | NOT PEER-REVIEWED | Posted: 19 October 2022 doi:10.20944/preprints202210.0276.v1

Table 3 .

 3 Cell proportions per frequency range for primary cultures of patient

		CPP14		CPP6
		Normal medium Define medium	Normal medium	Define medium
	0-100 MHz	29%	55%	0%	85%
	100-200 MHz	53%	45%	35%	15%
	200-300 MHz	18%	0%	49%	0%
	300-400 MHz	0%	0%	16%	0%
		Like CRC cell lines, both CPP show the same behavior with a distinct EM signature
	for CSCs and always lower than cells cultured in normal medium.

Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 19 October 2022 doi:10.20944/preprints202210.0276.v1

Table 4 .

 4 Cell proportions per frequency range for CPP14 treated with EVs

		CPP14	+ EVs CPP6 NM + EVs CPP6 DM
		Normal medium	72h	72h
	0-100 MHz	0%	2%	2%
	100-200 MHz	12%	34%	37%
	200-300 MHz	68%	60%	60%
	300-400 MHz	20%	5%	1%

Table 5 .

 5 Cell proportions per frequency range for CPP6 treated with EVs

		CPP6	+ EVs CPP6 DM
		Normal medium	72h
	0-100 MHz	0%	7%
	100-200 MHz	35%	46%
	200-300 MHz	49%	45%
	300-400 MHz	16%	2%

Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 19 October 2022 doi:10.20944/preprints202210.0276.v1

Data Availability Statement: UMR INSERM 1308-CAPTuR "Control of Cell Activation in Tumor Progression and Therapeutic Resistance" lab.

Supplementary Materials:

The following supporting information can be downloaded at: www.mdpi.com/xxx/s1, Figure S1 Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Conflicts of Interest:

The authors declare no conflict of interest


Marianna Tzekaki
email: tzekaki@auth.gr

Patterning in Early Years, A Synthesis of Research

Keywords: patterning, definitions of pattern, pattern activities, pattern abilities, pattern strategies

This paper attempts to summarize the research related to patterning in early childhood (4-8 years). In doing so, the basic concepts, rationales, methods, and findings are systematized to provide a foundation for forthcoming design. The purpose of this presentation and the suggested discussion is not to present new data but to systematize existing as a guide for future research.

Introduction

Systematic exploration of early patterning begins in nineties as an important element of early mathematics education. Researchers accept that children's familiarization with patterns and structures influences their future mathematical development [START_REF] Clements | Learning and teaching early math: The learning trajectories approach[END_REF]) and provides a foundation for understanding complex mathematical situations and making generalizations [START_REF] Rivera | Pattern generalization processing of younger and older Students: similarities and differences[END_REF].

To date, a large number of different studies have been conducted on early patterning in mathematics education. These studies approach the idea of pattern differently, use a variety of pattern forms, propose similar but also dissimilar pattern activities and understand the connection of pattern to mathematics in various ways. Therefore, we believe it is important and mature to attempt a synthetic presentation of this research in the following axes, covering aspects such as: (a) the conceptual definitions and types of patterns, (b) the rationales for linking patterns to mathematical development in different contexts, (c) the research related to patterning skills and strategies. These elements are considered important for planning future research. A synthesis of the research of this content would also require an outline of the main findings, but as we will see, due to the diversity of research, this synthesis could only be done on certain axes, therefore it is limit to presenting only findings on patterning skills and strategies.

Clarifications Pattern definitions

Not all researchers define the meaning of pattern in the same way, since pattern is not a distinct mathematical concept. A first approach describes pattern as a sequence of elements of different nature (numbers, shapes, sounds, symbols) organized according to a rule. This definition implies regularity and therefore predictability [START_REF] Papic | Assessing the Development of Pre-schoolers' Mathematical Patterning[END_REF][START_REF] Radford | Iconicity and contraction: a semiotic investigation of forms of algebraic generalizations of patterns in different contexts[END_REF].

However, according to [START_REF] Liljedahl | Repeating pattern or number pattern: the distinction is blurred[END_REF], the nature of the elements of a pattern is crucial. He argues that the concept of a pattern is a primary notion defined within the set of specific forms of regularities to which it belongs (e.g., sound, space, arithmetic, etc.) and has features within that set. Thus, he supports that, for example, a sound or a spatial pattern, even if they have the same e.g. ABB structure as an arithmetic pattern, they are of different natures and can be approached differently.

Extending the above view, [START_REF] Papic | Assessing the Development of Pre-schoolers' Mathematical Patterning[END_REF] identify patterns in the context of mathematics as, a) a regularity in an object in which some of its elements are related in a systematic way, b) an ordered set of objects in which each element is connected to the next by a specific relation, and c) two ordered sets of objects whose elements correspond to each other. So, the above researchers extend the corresponding concept by including elements organized on the basis of a structure (such as a clock), endogenous or constructed or introduced by a mathematical system [START_REF] Mulligan | Reconceptualising Early Mathematics Learning: The Fundamental Role of Pattern and Structure[END_REF].

Summarizing the above, it is understood that different research approaches in pattern definition are recorded, but the basic component of a pattern -common to all views -is the relationship between the elements that constitute it, which either enforce its organization into a structure or allow the prediction of the subsequent terms of its sequence [START_REF] Radford | Iconicity and contraction: a semiotic investigation of forms of algebraic generalizations of patterns in different contexts[END_REF][START_REF] Rivera | Visual templates in pattern generalization[END_REF]Warren & Cooper, 2008).

Pattern categories

There are also a variety of categories and terms regarding patterns that appear in relevant research. In general, researchers have identified and widely reported three specific forms: repetitive, evolving, or relational patterns (Lünken, 2018;[START_REF] Mulligan | Integrating concepts and processes in early mathematics: The Australian Pattern and Structure Mathematics Awareness Project[END_REF][START_REF] Threlfall | Repeating patterns in the early primary years[END_REF].

For repetitive patterns, a further distinction is made based on the type of iteration unit (e.g. ABAB, ABABA, [START_REF] Liljedahl | Repeating pattern or number pattern: the distinction is blurred[END_REF][START_REF] Papic | Assessing the Development of Pre-schoolers' Mathematical Patterning[END_REF][START_REF] Threlfall | Repeating patterns in the early primary years[END_REF], but also on the changing parameters (e.g. shape only, or shape and size, etc., [START_REF] Fyfe | Relations between patterning skill and differing aspects of early mathematics knowledge[END_REF][START_REF] Skoumpourdi | Kindergartners' performance levels on patterning[END_REF]. As for the developing patterns, [START_REF] Rivera | Visual templates in pattern generalization[END_REF] group them into additives or multiplicatives. [START_REF] Rivera | Pattern generalization processing of younger and older Students: similarities and differences[END_REF] also distinguishes patterns in terms of their elements in arithmetic and geometric forms, while [START_REF] Warren | Young children's ability to generalize the pattern rule for growing patterns[END_REF] includes regularities with elements in the form of shapes, colors, movements, sensations and sounds (especially for young children). The relevant findings are related to these categories.

To these forms [START_REF] Mulligan | Integrating concepts and processes in early mathematics: The Australian Pattern and Structure Mathematics Awareness Project[END_REF] add algebraic (triangular formations with numbers), metric (with repetition of unit elements) and diagrams, but also two or three-dimensional formations [START_REF] Mulligan | Reconceptualising Early Mathematics Learning: The Fundamental Role of Pattern and Structure[END_REF]. Similarly, [START_REF] Ma | Characterizing students' algebraic thinking in linear pattern with pictorial contents[END_REF] refers to iconographic patterns (mainly geometric) that lead to the formulation of verbal rules.

In this category, [START_REF] Chua | Rethinking and researching task design in pattern generalization[END_REF], who study schematic or figurative forms that lead to arithmetic relations and refer to rules (function type), distinguish their categories on the basis of the formations, but also of the type of the function type to which each form refers (e.g. some lead to types of linear functions, e.g. 5 + 3ν, while others lead to types of secondary functions, ν 2 + 2ν, etc.).

Composing the above, a variety of categories emerges in the relevant research, which can be organized in the following axes, with mainly mathematical content (i.e. without sound or kinetic patterns) and corresponding combinations: content or type of elements of the pattern (iconographic, schematic, geometric, metric, arithmetic, algebraic, etc.), type of development (repetitive, evolving, retrospectively evolving, etc.), spatial dimensions of development (e.g. one-dimensional, twodimensional, three-dimensional), structure of the pattern (for repetitive: AB, ABB, ABBA, etc.developing: additive, multiplicative, etc.), material (tangible, virtual and/or symbolic). The research has been conducted only in some of these categories.

Pattern activities

In this section, it is important to add the activities suggested by the researchers from the youngest to the older students.

At young ages, activities with patterns include replication with or without copying, continuation or extension of regularities, and recognition of structurally similar regularities. To these activities there is also research with pattern creation [START_REF] Papic | Assessing the Development of Pre-schoolers' Mathematical Patterning[END_REF], search of a missing element [START_REF] Warren | Young children's ability to generalize the pattern rule for growing patterns[END_REF], and alteration of material [START_REF] Clements | Learning and teaching early math: The learning trajectories approach[END_REF].

Finding and describing the iteration unit or smallest unit of a pattern is recognized by many researchers to be a particularly important activity [START_REF] Mulligan | Reconceptualising Early Mathematics Learning: The Fundamental Role of Pattern and Structure[END_REF][START_REF] Clements | Learning and teaching early math: The learning trajectories approach[END_REF]. Similarly, predicting later terms for generalization (near or far) [START_REF] Ma | Characterizing students' algebraic thinking in linear pattern with pictorial contents[END_REF]. These two activities, distinguishing units and predicting terms, as well as linking them to a next position (e.g. what is the 10 th term?) are considered very important as they lead to generalizations and symbolism [START_REF] Michael | Levels of understanding of patterns in multiple representation[END_REF][START_REF] Lannin | Generalization and justification: The challenge of introducing algebraic reasoning through patterning activities[END_REF]. It is argued that pattern generalization but also verbal explanations [START_REF] Lüken | Influence of early repeating patterning ability on school mathematics learning[END_REF], drawings, or other forms of symbolism [START_REF] Mulligan | Reconceptualising Early Mathematics Learning: The Fundamental Role of Pattern and Structure[END_REF] are an important introduction to both later numerical or developing patterns leading to formulas at this age.

In composing, research suggests the following activities, different in their treatment and difficulty: copying, reproducing, extending, transferring to another material, recognizing the repetition unit, identifying the same units of repetition, finding the missing element (interpolation), finding the error [START_REF] Wijns | Young Children's Patterning Competencies and Mathematical Development: A Review[END_REF], generalization (finding a formula, finding a term in a specific position, [START_REF] Lannin | Generalization and justification: The challenge of introducing algebraic reasoning through patterning activities[END_REF].

Students' skills in pattern's development

The finding that young students (ages 4-8, kindergarten and elementary school) have an ability to develop patterns is a common thread throughout the literature. The results of research on children's performance on activities that involve patterns reveal the basic types of regularities and the types of activities that young children successfully master without a specific didactic approach. Thus, in general, even preschoolers are able to explore repetitive patterns, language patterns, and some linear patterns and perceive regularities during their leisure activities [START_REF] Lüken | Is patterning a mathematical activity? -An analysis of young children's strategies in working with repeating[END_REF][START_REF] Fox | Connecting algebraic development to mathematical patterning in early childhood[END_REF][START_REF] Waters | A Study of mathematical patterning in early childhood settings[END_REF].

Most research in early childhood focuses on examining performance on repetitive patterns, with the majority of children able to reproduce, continue, and create a repetitive pattern AB or ABC (see, e.g., [START_REF] Skoumpourdi | Kindergartners' performance levels on patterning[END_REF]Papadopoulou, 2010;Warren & Cooper, 2008). More complex forms, including those of the ABB type, seem to cause greater difficulty, while the pattern material does not seem to have a significant impact.

However, analyzing the pattern in its structural elements and finding the iteration unit is becoming more demanding issue, which has led researchers to consider iteration unit location, complementing (finding the missing element) and identifying (which patterns are the same? is this a pattern?) at a higher developmental level of the respective ability [START_REF] Wijns | Young Children's Patterning Competencies and Mathematical Development: A Review[END_REF].

Developing patterns that is an early introduction to functional reasoning, appears to be more challenging, leading to less emphasis at younger ages. Although the performance of young children has not been systematically studied, the relevant research mainly concerns children in the last grades of elementary school and the first grades of high school, it seems that in this area the material and the structure play a crucial role (one-dimensional or two-dimensional growth). Several researchers point out that children reach high percentages in repetitive patterns by the 2nd grade, but less in increasing or arithmetic patterns (Papadopoulou, 2010;[START_REF] Warren | Young children's ability to generalize the pattern rule for growing patterns[END_REF]etc.).

In relation to the building patterns of objects of different types [START_REF] Mulligan | Reconceptualising Early Mathematics Learning: The Fundamental Role of Pattern and Structure[END_REF], the developmental trajectory of young children has been studied in depth through a systematic program of activities from the prestructural to the structural level (intermediate levels: emerging and partially structural). This view brings the importance of curriculum and instruction to the first level, as a number of studies -(not examined in detail in this paper) -highlight the positive impact of appropriate educational interventions and programs.

In summary, children up to first grades succeed, even without educational help, to recognize patterns with simple structures or materials and identify a simple rule, but have difficulty with more complex forms as well as numerical, developing patterns. There is a lack of meaningful research on systematic and verbal finding of the unit of repetition and near or far generalization (e.g., what is the form at the next or next but one place -near generalization, or what is the form at the 10th or 20th place -far generalization).

Patterning strategies

By studying the activities of students with patterns, some researchers have also studied the strategies they use at an early age. A common assumption is that children make one-to-one correspondences to the proposed pattern activities that mainly involve copying, reproducing, extending, or transferring to other material, or that they take a rhythmic approach based on a sequence (which, however, according to Threlfall, 1999, cannot lead to generalization), such as finding the unit of repetition or 'breaking into pieces' [START_REF] Mulligan | Reconceptualising Early Mathematics Learning: The Fundamental Role of Pattern and Structure[END_REF]. 2011) categorize children's strategies into direct matching, alternation, repetition of basic units, and integrated repetition of units. Accordingly, [START_REF] Lüken | Is patterning a mathematical activity? -An analysis of young children's strategies in working with repeating[END_REF] summarizes relevant results and records five strategies of students in solving activities with patterns: in the 1st, there is no reference to the design, except for the holistic reproduction of the pattern; in the 2nd, the focus is on some features; in the 3rd, on comparison and classification; in the 4th, on the sequence; and finally, in the 5th, there is a focus on the unit of repetition.

Papic et al. (

In summary, young children successfully develop strategies to find the next element in a pattern or its rule, but according to some researchers (see [START_REF] Lüken | Is patterning a mathematical activity? -An analysis of young children's strategies in working with repeating[END_REF]), copying, imitating or reproducing without generalization and symbolism cannot be recognized as a mathematical activity, that is the finding of the iteration unit, its generalization and its possible symbolism. The next section gives some answers about the importance of developing patterning skills and strategies.

Relationship between pattern development and mathematics

Researchers engaged in studies with patterns argue that patterns are important because "... Mathematics is the science and language of regularities" (Steen, 1990, p. 5, in Fox, 2006) and familiarity with them also promotes mathematical thinking, exercises the ability to find rules and structures, both in everyday situations and in symbolic objects or symbols, such as the elements of algebra [START_REF] Vogel | Patternsa fundamental idea of mathematical thinking and learning[END_REF].

In general, connections to Mathematics relate patterns to numbers (e.g. repetitive structure of the decimal system, cumulative and multiplicative structures), to geometry (e.g. regular shapes), to measurement (e.g. creating and repeating a unit of measurement), and to data processing (e.g. finding rules and relationships) [START_REF] Lüken | Is patterning a mathematical activity? -An analysis of young children's strategies in working with repeating[END_REF][START_REF] Mulligan | Integrating concepts and processes in early mathematics: The Australian Pattern and Structure Mathematics Awareness Project[END_REF].

The connection with algebraic reasoning [START_REF] Fox | Connecting algebraic development to mathematical patterning in early childhood[END_REF] as well as with functions [START_REF] Warren | Young children's ability to generalize the pattern rule for growing patterns[END_REF] is another axis that many researchers have worked on (see [START_REF] Ma | Characterizing students' algebraic thinking in linear pattern with pictorial contents[END_REF][START_REF] Papic | Assessing the Development of Pre-schoolers' Mathematical Patterning[END_REF]. More generally, it is agreed that the formation of generalizations, subtractions and symbolizations enhanced by pattern activities as an indispensable element of Mathematics [START_REF] Lüken | Influence of early repeating patterning ability on school mathematics learning[END_REF].

Several studies examining the relationship between performance in patterns and performance in other mathematical domains (e.g. arithmetic) or other cognitive skills (e.g. reading, memory, etc., [START_REF] Fyfe | Relations between patterning skill and differing aspects of early mathematics knowledge[END_REF] show important connections. Some others, also investigating whether high performance in patterning is a predictor of later mathematical achievement (Rittle-Johnson, Zippert, & Boice, 2016), reach different conclusions.

Combining the above, it becomes clear that different pattern forms and activities support different aspects of mathematical concepts. Thus, repetitive patterns (with the characteristic feature of circular character and repetition unit) and activities requiring continuity, completion, finding a missing element, finding an error, finding a unit of repetition, etc., can help students approach mathematical objects or processes that are systematically repeated phenomena, such as number systems, regularities in shapes, repetition of units of measurement, etc. [START_REF] Liljedahl | Repeating pattern or number pattern: the distinction is blurred[END_REF]; generalization, and symbolism are important in mathematical domains such as problem solving [START_REF] Rivera | Visual templates in pattern generalization[END_REF][START_REF] Radford | Iconicity and contraction: a semiotic investigation of forms of algebraic generalizations of patterns in different contexts[END_REF] or equations [START_REF] Mcneil | Why Won't You Change Your Mind? Knowledge of Operational Patterns Hinders Learning and Performance on Equations[END_REF]. Accordingly, arithmetic regularities and activities requiring finding not only some next elements or the type/function that generates them (e.g., a number sequence 1, 5, 8, ...), but also some elements of the pattern that are in a particular position (far generalisation), support functional thinking from an early age.

Discussion for future research

From the above review, we need to highlight the following points for future research: First, the number of studies that have been conducted on early patterning is large, but there is a variety of contents, aims, questions and approaches, thus the concepts and terms used in them are not always clearly or similarly defined. For this reason, systematic concern regarding terms, categories and activities are needed in any future research.

Then, the review presented show that regularities or patterns, as well as related activities, can be categorized in many dimensions. Therefore, it would be important to conduct synthetic comparisons and compare performances surveys but only in common approaches. Also it is also important to systematically investigate the extent to which certain pattern forms and activities are related to mathematical content and the mathematical skills they promote, as not all regularities lead to mathematical activity and thus to Mathematics.

Finally, we know that children in general can develop important patterning skills at a younger age, but not all of them are related to mathematics. Therefore, in research or classroom practice, the researcher/teacher needs to know which developmental pathway serves which content, material, structure, and/or action.

Acknowledgment

In the initial preparation of this paper M. Kaldrimidou and X. Vamvakousi offer their help