Pineau

Hugnot Jp

Affiliations

N Leventoux

Meera Augustus

S Azar

S Riquier

J P Villemin

S Guelfi

L Falha

L Bauchet

C Gozé

W Ritchie

T Commes

H Duffau

V Rigau

J P Hugnot

Juliette Bertorello

Julie Sesen

Julia Gilhodes

Solène Evrard

Monique Courtade-Saïdi

Emmanuelle Uro-Coste

Christine Toulas

Elizabeth Cohen-

Jonathan Moyal

Catherine Seva

Erik Dassi

Anne Cammas

Nicolas Skuli

Stefania Millevoi
email: stefania.millevoi@inserm.fr

Identification of astrocyte and oligodendrocyte-like cells in diffuse low-grade gliomas and implication of Notch signaling in their genesis

IDH1-mutated gliomas are slow-growing brain tumours which progress into high-grade gliomas. The early molecular events causing this progression are ill-defined. Previous studies revealed that 20% of these tumours already have transformation foci. These foci offer opportunities to better understand malignant progression. We used immunohistochemistry and high throughput RNA profiling to characterize foci cells. These have higher pSTAT3 staining revealing activation of JAK/STAT signaling.

They downregulate RNAs involved in Wnt signaling (DAAM2, SFRP2), EGFR signaling (MLC1), cytoskeleton and cell-cell communication (EZR, GJA1

). In addition, foci cells show reduced levels of RNA coding for Ethanolamine-Phosphate Phospho-Lyase (ETNPPL/AGXT2L1), a lipid metabolism enzyme. ETNPPL is involved in the catabolism of phosphoethanolamine implicated in membrane synthesis. We detected ETNPPL protein in glioma cells as well as in astrocytes in the human brain. Its nuclear localization suggests additional roles for this enzyme. ETNPPL expression is inversely correlated to glioma grade and we found no ETNPPL protein in glioblastomas. Overexpression of ETNPPL reduces the growth of glioma stem cells indicating that this enzyme opposes gliomagenesis. Collectively, these results suggest that a combined alteration in membrane lipid metabolism and STAT3 pathway promotes IDH1-mutated glioma malignant progression.

Diffuse low-grade gliomas (DLGG, WHO grade II) is a subtype of glial brain tumours typically affecting young patients in their third or fourth decades 1 . Compared to glioblastomas, much less is known about these tumours. They are mostly found in the brain white matter and are probably derived from transformation of oligodendrocyte progenitors which are the main proliferative cell population in the brain. They are most often found in functional brain areas such as the motor cortex, Broca's area, frontal lobe and insula. Histologically, diffuse low-grade

without expressing my gratitude to each and everyone who have been a part of this journey.

Life as a PhD student had been a great learning platform. More than the skills and expertise I gained, the science and research I learned, it has taught me some real life lessons. It has taught me patience, to be hopeful when things don't work out the way I want, to stay peaceful amidst the chaos, to be humble and appreciate the smallest of efforts others do for you. This journey would have been excruciating without all the people directly and indirectly involved in my life.

I begin by extending my gratitude to my mentor and guide Dr. Jean-philippe Hugnot. Since the day I got selected for the PhD scholarship, you have been of great help. Even before joining the lab, you had taken out your time to explain me about the project, took initiative for all the administrative processes for my travel and even accommodating me in your house for one month until I managed to find my residence. I cannot thank you enough for this. But more than that you have been a great supervisor during the course of my PhD. You have always found time to discuss and design experiments and was always a helping hand whenever I required. Thank you for all the help and advices you have given during each of my poster and oral presentations. Your each words of appreciation even for the simplest of things I do -for a beautiful staining, or the qPCR results, have motivated me immensely and given me the strength to push through to overcome each challenges we faced during the work progression.

My project would not have taken its current shape without your timely suggestions and advices. I am always fascinated by your passion and love for science and that is something I wish to carry forward in my career. Thank you Jean-philippe.

I extend my sincere thanks to Dr. Hugues Duffau who provides us with the patient samples.

Without him, it is not even possible to conceive a project that primarily depends on patient samples. Thank you for the opportunities you have given me to observe real human operations at the hospital and providing with large number of human samples that I acknowledge I have been very lucky to be part of such a project and not every PhD student working on glioma gets such an opportunity. I also thank all the patients and their families for agreeing to use their samples for research purposes. you have extended, for teaching me the most important technique I needed in the completion of my work-freezing and sectioning of tissues on cryostat, immunostaining on tissue sections I owe you a big thank you. For all the science we discussed, the help you did for standardizing the in vitro culture systems and also for the personal advices you gave me. How can I thank you enough for all the help you offered for administrative issues I keep bumping into. You were always there to help me when it was required to talk to in French. And I missed you after you left the lab:( I will cherish all the moments we shared together-for the dance in Scotland, for the birthday surprise in restaurant, visiting you in Nimes ;). Hope to meet you soon-may be in Japan or in India.

I extend my thanks to all past and present members of the lab for the friendly environment.

Hussein, for constantly irritating me and creating fun and Sophie Muxel, for all the help with cultures. You have been of great help with the cultures when I needed the most. You have played an important role in taking the project forward. I also thank Robert and Donovan for being very friendly. Robert, you were a good company since you joined the lab as a master student. Donovan-for the help with cell cultures towards the end of my PhD and for all the project discussions. I am sure that you would take the project much ahead during your PhD. I wish you both the best in your PhD journey. Sophie Guelfi, though we have not worked together in the lab, you have been very kind in providing me all the scientific information through e-mail. I thank you for sending me protocols and other details whenever I asked for.

Thank you Yuvraj for the friendly conversations we had in the corridors of the Institute.

I am indebted to my committee members-Thierry Virolle, Julie Pannequin, Emmanuelle Huillard and Marie-Luce Vignais for the valuable suggestions during the committee meetings that have helped to steer the project in the right direction.

I greatly acknowledge the help INM and MRI facilities have provided in the completion of the project. Chantal, for helping me with tissue sectioning and for the house party you arranged. I thank all the staff of microscopy facilities at INM and IGH for the help extended. I take this opportunity to thank Christophe at cell-sorting facility for teaching me to I would like to extend my heartfelt gratitude to all the funding agencies that supported me throughout these four years. I immensely thank the jury of CBS2 scholarship who agreed to interview me online and granted me the scholarship for 3 years of the doctoral studies. I would also like to thank "Fondation ARC pour la recherche sur le cancer" for granting me 6 months funding in the fourth year. I am deeply indebted to the Association pour la Recherche des Tumeurs Cérébrales Sud (ARTC-Sud) for considering my situation and financially supporting me for the last 6 months of my PhD. Without their aid, it would have been really painful to wrap up the work for submission. This acknowledgement would be incomplete without mentioning the people outside of the scientific world who have been my constant support and encouragement. Satish, would words be adequate to express my gratitude? Thank you for having my back and being there throughout giving me the strength. I would not have reached here without you. For believing in me when I had failed to, for all the scientific discussions, for all the timely ideas and for all the motivations, thank you. My friends in Montpellier-Deethu, Parvathy, Jeethu, Anusha and Anshab. Thank you for all the wonderful memories and friendship you have given me to cherish for a lifetime. Cheers to all the weekend fun, the trips together, and the wildest of dreams we share. Deethu and Parvathy, thank you for always accommodating me at your place, for the late night stays, for the amazing food you offered every time I come. You both have made me feel-at-home. Jeethu and Anusha, love and hugs for all the moments we had, canteen lunches, sharing PhD tensions and the bond we have built over the years. Though far, but always near at heart, Aparna and Catherine, I thank you for the friendship that we share.

For still being close even when we have moved apart with our lives, for checking on me that I am doing well. I wish to meet you both soon and have our own time as always have been.

Thameez chetta and Nitheesh chetta, thank you for all the love you show to me.

Words fall short to express my love and gratitude towards my family. Appa and Amma, I thank you for all the opportunities you have given me in my life. For believing in me and loving me dearly and for giving me wings that I could fly. I strive to be as sincere and dedicated as you towards my work and I hope to make you proud one day. Appa, thank you for all the love and care, for the interest you show in knowing about my research, for sending me newspaper reports on cancer research that motivates me. Amma, the encouraging words Acknowledgements you always say -'who else can achieve if it's not possible for you', have given me the strength to push my limits. Though not near me physically, your encouraging words always rings in me. Thank you for being the positive sound that echoes in me. Ammu chechi and Riya, kisses for being my best sisters. I feel bad that we were away during the most beautiful times of our lives but you make up for all the missing when I come home and gift me beautiful memories. I am waiting for the days when we could be together, travel and experience everything and be the best of friends more than sisters.

Aunty, how do I express what I feel for you. I miss you terribly and no day passes by without thinking of you. Thank you for making me who I am today. You have played an irreplaceable role in my life. I had begun to appreciate and love you more when I began to live independently. I hope you will be happy up in the heaven seeing what I could achieve. But I will miss running back to you and be at the safest of the places I could ever be.

~Meera

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List of figures

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Summary in French

Summary in French

Les gliomes diffus de bas grade (DLGG) sont des tumeurs gliales de grade II qui affectent principalement les jeunes adultes. Elles sont caractérisées par une croissance lente et une activité mitotique réduite. Cependant, ces tumeurs diffusent et envahissent le cerveau sain via les vaisseaux sanguins et les fibres nerveuses. Après plusieurs années de croissance lente, ces tumeurs peuvent évoluer vers des glioblastomes, des tumeurs cérébrales très agressives dont la survie médiane moyenne est alors de 12 à 15 mois après le diagnostic. La caractérisation cellulaire des DLGG est encore limitée ce qui nuit à la recherche d'un traitement à un stade précoce.

Dans ma thèse de doctorat, je me suis focalisée sur la caractérisation de l'hétérogénéité cellulaire des DLGG mutés pour IDH1. En effectuant une analyse d'immunofluorescence sur des astrocytomes et oligodendrogliomes de grade II, j'ai identifié deux sous-populations cellulaires largement non chevauchantes et exprimant respectivement les facteurs de transcription SOX9 et OLIG1. Ces cellules s'apparentent à des cellules de type astrocytaire et oligodendrocytaire et expriment des marqueurs moléculaires distincts. Les cellules SOX9 expriment APOE, KCNN3, CRYAB et ID4, tandis que les cellules OLIG1 expriment préfentiellement PDGFRA, SOX8, MASH1 et SOX4. Par ailleurs, j'ai montré que les cellules SOX9 présentent une activation particulière des voies de signalisation, notamment Notch, BMP et leurs cibles en aval.

Pour étudier le rôle de la voie de signalisation Notch dans la formation de ces 2 souspopulations tumorales, j'ai purifié par tri magnétique les cellules tumorales à partir d'échantillons de gliomes fraîchement réséqués et j'ai surexprimé le domaine intracellulaire Notch (NICD), une forme active de Notch. J'ai ainsi montré que cette activation augmentait l'expression des marqueurs cellulaires associés aux cellules SOX9 + et une baisse de ceux associés aux cellules OLIG1 + . J'ai ensuite étendu ces analyses à une lignée cellulaire anaplasique dérivée d'un patient et mutée pour IDH1. Ces resultats indiquent un role clé de la signalisation Notch dans la régulation de la plasticité des cellules tumorales. Des expériences similaires pour étudier l'activation de la signalisation BMP (bone morphogenetic protein) n'ont pas montré d'effet notable sur la plasticité. Néanmoins, le traitement des cellules par des members de la famille BMP a fortement augmenté l'expression de CRYAB, un marqueur associé à SOX9, et a diminué l'expression de OLIG1 et OLIG2.

Summary in French

En conclusion, j'ai identifié deux sous-populations tumorales non chevauchantes dans des gliomes diffus de bas grade et j'ai démontré le rôle déterminant de la voie de signalisation Notch dans leur formation. Ces résultats permettront de mieux comprendre l'hétérogénéité tumorale dans les DLGG et de concevoir de nouvelles stratégies thérapeutiques contre ces tumeurs.

Summary in French

Contexte/Introduction

Les gliomes représentent environ 30 % des tumeurs du système nerveux central et 80 % de toutes les tumeurs cérébrales malignes (Ostrom et al., 2018). Les gliomes chez l'adulte peuvent être classés principalement en gliomes diffus de bas grade (DLGG, grade II), en gliomes anaplasiques (grade III) et en glioblastomes multiformes (GBM, grade IV) en fonction de la densité cellulaire, de l'atypie nucléaire, de l'indice mitotique et de la nécrose définissant les grades pathologiques (Louis et al., 2007). Alors que des études approfondies sont réalisées sur l'hétérogénéité génétique et cellulaire des glioblastomes, la DLGG reste mal comprise, ce qui limite les possibilités de traitement. La modalité de traitement la plus efficace actuellement en pratique est la résection chirurgicale du tissu tumoral (Duffau and Mandonnet, 2013). Cependant, en raison de la nature diffuse et des régions sensibles où ces tumeurs se développent, l'ablation complète de la tumeur est presque impossible. Il est donc de plus en plus nécessaire de caractériser les DLGG pour faciliter le développement de nouvelles thérapies.

Au niveau cellulaire, le DLGG a été largement divisé en deux grands types : l'astrocytome et l'oligodendrogliome. Au niveau moléculaire, l'une des mutations les plus fréquemment observées dans les DLGG est celle de l'enzyme Isocitrate déshydrogénase (IDH) 1/2, que l'on trouve à la fois dans l'astrocytome et l'oligodendrogliome [START_REF] Yan | IDH1 and IDH2 mutations in gliomas[END_REF]. Les autres marqueurs observés exclusivement dans l'astrocytome sont la mutation p53 et les mutations de perte de fonction ATRX, tandis que l'oligodendrogliome présente une codélétion 1p/19q, les mutations du promoteur TERT (Brennan et al., 2013;Jiao et al., 2012) [START_REF] Reifenberger | Molecular genetic analysis of oligodendroglial tumors shows preferential allelic deletions on 19q and 1p[END_REF] (Arita et al., 2013). En plus des anomalies génétiques, des rapports suggèrent l'importance de l'altération des voies de signalisation dans les gliomes. Ces cas sont bien documentés dans les gliomes de grade supérieur avec l'implication d'une signalisation dérégulée du récepteur tyrosine kinase (facteur de croissance épithélial (EGFR) (Furnari et al., 2015), facteur de croissance dérivé des plaquettes (PDGFR) (Szerlip et al., 2012), signalisation PI3K-AKT-mTOR et Ras-MAPK (Lino and Merlo, 2011). Cependant, il n'existe qu'une poignée d'études explorant l'aspect de la signalisation dans les DLGG (Pierscianek et al., 2013) (Motomura et al., 2013) (Bao et al., 2014) (Azar et al., 2018).

Dans le glioblastome, des études approfondies ont caractérisé les tumeurs en quatre sousgroupes moléculaires avec des états transcriptionnels distincts (Verhaak et al., 2010). Cette hétérogénéité a également été explorée au niveau inter et intra tumoral (Aum et al., 2014). En outre, ces sous-populations cellulaires pourraient avoir un territoire spatial au sein d'une Summary in French tumeur et échanger leur identité en fonction des indices environnementaux requis pour leur durabilité [START_REF] Minata | Phenotypic Plasticity of Invasive Edge Glioma Stem-like Cells in Response to Ionizing Radiation[END_REF]. Mais des études aussi approfondies et élaborées sont très rares dans le domaine des gliomes diffus de bas grade. Des études antérieures basées sur la microscopie électronique (Baloyannis, 1981) et l'immunohistochimie des DLGG (Rousseau et al., 2006) (Liang et al., 2005) ont décrit la présence d'une hétérogénéité phénotypique au sein des cellules tumorales. En particulier, dans les oligodendrogliomes, des sous-populations d'oligodendrocytes gliofibrillaires ont été signalées (Herpers and Budka, 1984;Kros et al., 1996;Matyja et al., 2001). Récemment, la composition cellulaire de la DLGG mutée par l'IDH1 a également été étudiée à l'aide d'une approche technologique plus récente basée sur le séquençage de l'ARN d'une seule cellule (Tirosh et al., 2016) (Venteicher et al., 2017). Ces études ont signalé la présence de trois sous-populations de cellules malignes : des cellules non prolifératives différenciées le long des lignées astrocytaires et oligodendrocytaires et des cellules prolifératives indifférenciées qui ressemblent à des cellules souches/progénitrices neurales.

Néanmoins, il reste à comprendre si les profils d'expression d'ARN ou de gènes rapportés valident leur expression protéique respective, qui détermine finalement l'identité des cellules.

En outre, on ne sait rien de la genèse d'une telle hétérogénéité cellulaire dans les DLGG. Estil possible de modifier cette hétérogénéité en manipulant extérieurement l'expression des gènes ou les voies de signalisation ? Il est essentiel de répondre à ces questions non seulement pour comprendre le paysage de l'hétérogénéité des DLGG, mais aussi et surtout pour concevoir de meilleures thérapies.

L'objectif central de mon projet de doctorat était de caractériser systématiquement les gliomes diffus de bas grade mutés en IDH1 et d'étudier le rôle des voies de signalisation potentielles dans la genèse des sous-populations tumorales dans les DLGG.

Pour y parvenir, mes objectifs spécifiques étaient les suivants

Objectif 1: identifier les sous-populations tumorales potentielles dans les gliomes diffus de bas grade chez l'homme Objectif 2: caractériser les populations tumorales identifiées pour l'expression de facteurs de transcription distincts et de voies de signalisation activées.

Objectif 3: étudier le potentiel des voies de signalisation activées pour déterminer le sort des sous-populations tumorales dans les DLGG ?

Summary in French

Pour confirmer que ces populations de cellules non chevauchantes sont tumorales, j'ai effectué une co-coloration de SOX9 et OLIG1 avec IDH1R132H ou ATRX dans les sections tumorales de l'oligodendrogliome et de l'astrocytome, respectivement. Dans l'astrocytome, presque toutes les cellules positives SOX9 et OLIG1 sont co-labellisées avec ATRX, et confirment ainsi leur identité tumorale. Il est intéressant de noter que dans l'oligodendrogliome, plus de 90 % des cellules OLIG1 + ont exprimé la protéine IDH1R132H, alors que seulement 25 % environ des cellules SOX9 + étaient positives pour la coloration IDH1R132H.

Objectif 2 : caractériser les populations tumorales identifiées pour l'expression de facteurs de transcription distincts et de voies de signalisation activées.

Mes résultats de l'objectif 1 montrant la présence de deux sous-populations dans la DLGG ont soulevé une question intrigante sur la genèse de ces populations cellulaires. Ces populations cellulaires se développent-elles de manière indépendante ou y a-t-il un changement phénotypique entre ces sous-populations de cellules ? Afin de répondre à ces questions, j'ai pensé qu'il était important de délimiter d'abord les caractéristiques des deux sous-populations.

Plus précisément, j'ai demandé si ces cellules sont entièrement exclusives ou si elles partagent l'expression de protéines spécifiques à la lignée ou de voies de signalisation. Dans l'objectif 2, j'ai caractérisé les sous-populations tumorales identifiées pour leur expression différentielle de facteurs de transcription distincts et de voies de signalisation activées. Sur la base de la littérature publiée et des bases de données disponibles, j'ai choisi APOE, CRYAB, KCNN3 et ID4 comme protéines de lignage astrocytaire et PDGFRA, SOX8 et GPR17 comme protéines de lignage oligodendrocytaire. Une analyse systématique approfondie des deux sous-types DLGG a révélé que tous les marqueurs de lignage astrocytaire sont fortement associés aux cellules positives SOX9, avec une association de moins de 15% avec les cellules OLIG1 + . À l'exception de la GPR17, j'ai trouvé une forte corrélation des marqueurs de la lignée oligodendrocytique avec les cellules positives OLIG1.

La présence de populations de cellules à double ségrégation dans le DLGG suggère qu'elles pourraient avoir un statut de récepteur différent, des voies de signalisation et probablement un potentiel de ténacité. Pour tenter d'identifier les cellules progénitrices entre les cellules SOX9 + et OLIG1 + , j'ai procédé à l'immunocoloration de certains des facteurs de transcription exprimés par les cellules souches/progénitrices neurales pendant le développement du cerveau et dans les glioblastomes tels que SOX2, SOX4 et MASH1 [START_REF] Archer | Interaction of Sox1, Sox2, Sox3 and Oct4 during primary neurogenesis[END_REF] (Miyagi et Summary in French al., 2009) [START_REF] Bhattaram | Organogenesis relies on SoxC transcription factors for the survival of neural and mesenchymal progenitors[END_REF] (Ikushima et al., 2011). La co-coloration avec SOX9 et OLIG1 a montré que les deux types de cellules dans l'astrocytome et l'oligodendrogliome exprimaient SOX2 de manière égale. En revanche, SOX4 et MASH1 étaient principalement exprimés dans les cellules OLIG1 + . J'ai étudié plus en détail les profils d'expression des voies de signalisation qui sont souvent impliquées dans les DLGG, notamment la signalisation Notch, BMP, ERK/MAPK, EGFR [START_REF] Burel-Vandenbos | EGFR immunolabeling pattern may discriminate low-grade gliomas from gliosis[END_REF] et PTPRZ1 (Bao et al., 2014). Pour évaluer le profil de la voie Notch activée, j'ai évalué l'expression de HEY1 et HEY2, facteurs de transcription en aval de la signalisation Notch sur les coupes de tissus DLGG. Mon analyse a montré que les cellules SOX9 + dans les oligodendrogliomes et les astrocytomes exprimaient préférentiellement HEY1 et HEY2, ce qui suggère une activation de la voie notch régulée à la hausse dans cette population de cellules.

En ce qui concerne la signalisation des BMP, j'ai recherché l'activation de la voie en effectuant une co-coloration avec la protéine phosphorylée Smad1/5 (p-Smad1/5), facteur en aval dans la signalisation des BMP. Ces analyses ont montré que la p-Smad1/5 est fortement associée aux cellules SOX9 + dans les astrocytomes et les oligodendrogliomes. J'ai également trouvé une activation de la signalisation ERK/MAPK dans les cellules SOX9 + d'oligodendrogliome et d'astrocytome, car la coloration phospho-ERK était spécifiquement associée aux cellules SOX9 + .

En plus des voies de signalisation, j'ai également évalué le statut des récepteurs de l'EGFR et de la tyrosine-protéine phosphatase zêta 1 (PTPRZ1), qui sont déjà impliqués dans le grade de gliome et la malignité (Pedeutour-Braccini et al., 2015) (Ohgaki et al., 2004) (Ekstrand et al., 1992) (Muller et al., 2003) (Ulbricht et al., 2003). Il est intéressant de noter que ces deux récepteurs étaient davantage exprimés dans les cellules OLIG1 + . L'ensemble de ces résultats a révélé que les deux populations cellulaires détectées dans le DLGG expriment différemment les marqueurs et les récepteurs cellulaires et diffèrent également dans l'activation des voies de signalisation.

Objectif 3 : étudier le potentiel des voies de signalisation activées pour déterminer le sort des sous-populations tumorales dans les DLGG

Pour étudier le rôle potentiel des voies de signalisation dans la détermination du sort des souspopulations tumorales (objectif 3), j'ai cherché à isoler et à purifier les cellules tumorales du Summary in French tissu humain DLGG. Cependant, la principale préoccupation était de décider du marqueur de surface cellulaire qui représente la majorité de la population de tumeurs mutantes IDH1. Pour comprendre cela, j'ai d'abord effectué une caractérisation par cytométrie de flux des cellules tumorales dissociées pour différents marqueurs de surface cellulaire connus : GLAST, CD44 (exprimé par les astrocytes), O4 (oligodendrocyte) et A2B5, PSA-NCAM (cellules progénitrices précoces). Malgré la variabilité inhérente aux tumeurs analysées, ces expériences ont montré que les cellules obtenues comprennent principalement O4 / CD44 / A2B5 comme marqueurs de surface cellulaire, les cellules O4 étant le pourcentage le plus élevé de cellules dans un tissu tumoral donné. Par la suite, j'ai établi une méthode utilisant le tri magnétique pour purifier les cellules O4 des tissus tumoraux.

Dans un premier temps, les cellules O4 ont été purifiées et cultivées en présence des facteurs de croissance EGF, FGF2 et PDGF pendant deux semaines, fixées et utilisées pour l'analyse par immunocoloration. L'immunocoloration avec l'anticorps O4 a montré qu'environ 90% des cellules sont positives pour l'O4, validant ainsi les méthodes de purification. La coloration IDH1R132H a montré une grande variabilité entre les cultures exprimant 30 à 100% des cellules tumorales. J'ai observé que O4 pouvait isoler à la fois les oligodendrocytes tumoraux et non tumoraux en fonction de la résection tissulaire obtenue. Ces cellules pouvaient être différenciées en fonction de leur morphologie nucléaire ainsi que de l'expression de protéines spécifiques. Par rapport à la situation in vivo, je n'ai pas pu identifier deux cellules tumorales SOX9 + contre OLIG1 + clairement distinctes et la majorité des cellules co-expriment OLIG1 et SOX9.

J'ai également examiné le rôle potentiel de la signalisation "notch" et de la signalisation BMP dans la régulation des phénotypes des cellules tumorales. Les signaux Notch et BMP sont deux voies principales impliquées dans la génération des astrocytes au cours du développement. En outre, notre laboratoire a déjà signalé que dans les glioblastomes, l'activation de la voie Notch entraînait une forte modification phénotypique des cellules par la régulation à la hausse des facteurs de transcription HEY1 et HEY2 (Guichet et al., 2015). Ainsi, j'avais émis l'hypothèse que les voies Notch et BMP pourraient influencer le phénotype des cellules de gliome de bas grade, car j'ai observé que les cellules SOX9 + et OLIG1 + ont une expression différentielle de ces protéines de signalisation (HEY 1/2 et p-SMAD1/5). Pour tester l'influence de la voie Notch sur les cellules DLGG, j'ai sélectionné 4 cultures de cellules tumorales contenant >70% de cellules mutées IDH1 qui ont également été mutées pour ATRX. Les cellules ont été infectées par un lentivirus exprimant la forme constitutivement Summary in French active de la signalisation Notch, le NICD-YFP (Notch intracellular domain) ou un YFP témoin pendant 5 jours. J'ai ensuite analysé l'expression de l'ARNm de 18 gènes qui semblaient être différentiellement exprimés par les cellules SOX9 + et OLIG1 + dans les tissus en utilisant la RCPQ. Il s'agit des gènes ASCL1, EGFR, IDH1 OLIG1/2, PDGFRA, PTPRZ1 et SOX4/8 pour les cellules OLIG1 + et APOE, CRYAB, HEY1/2, ID4, KCNN3, SOX9 pour les cellules SOX9 + . Mes analyses ont montré que 8/10 des gènes associés aux cellules OLIG1 + ont été significativement réduits par l'expression des NICD (ASCL1, IDH1, OLIG1/2, PDGFRA, PTPRZ, SOX4/8) tandis que 4/8 des gènes associés aux cellules SOX9 + (CRYAB, KCNN3, HEY1/2) ont été régulés à la hausse. L'influence des maladies neurodégénératives sur l'APOE, l'EGFR et la SOX9 était très variable selon les cultures et aucune influence significative des maladies neurodégénératives n'a pu être détectée.Pour confirmer ces résultats, j'ai utilisé une lignée cellulaire (appelée LGG275) dérivée d'un patient atteint d'un gliome anaplasique porteur de la mutation IDH1 R132H et ATRX et qui croît très lentement (temps de doublement de la culture = 2 semaines). La transduction de ces cellules par le lentivirus NICD a permis de réguler à la baisse 8/10 des gènes oligodendrocytaires (ASCL1, IDH1, OLIG1/2, PDGFRA, PTPRZ1, EGFR, SOX8) tandis que 4/8 des gènes astrocytaires (CRYAB, HEY1/2, KCNN3) ont été régulés à la hausse (n=5, expérience indépendante). J'ai pu confirmer la régulation à la hausse induite par Notch des protéines CRYAB, HEY1/2 et KCNN3 par immunofluorescence. Pour valider davantage l'influence de la signalisation Notch, j'ai traité des cellules LGG275 avec deux inhibiteurs de la ?-secretase qui bloquent l'activation de Notch : DAPT et LY411575. Il en est résulté une régulation à la baisse légère mais significative de l'APOE et, inversement, une régulation à la hausse de l'ASCL1, de l'IDH1 et de l'EGFR.

Parallèlement à l'évaluation du rôle de Notch dans la régulation des phénotypes des souspopulations tumorales, j'ai également testé l'effet de la signalisation des BMP dans le contrôle du phénotype cellulaire. À cette fin, les cellules LGG275 ont été traitées avec la BMP2 et la BMP4 pendant 5 jours et une RCPQ a été effectuée pour 18 marqueurs mentionnés ci-dessus. Contrairement à Notch, les effets ont été moins spectaculaires pour la surexpression de la BMP. Mon analyse de la surexpression de la BMP a établi que le CRYAB a été régulé à la hausse plus de deux fois, tandis que l'OLIG1/2 et l'EGFR ont été régulés à la baisse. Pris ensemble, ces résultats suggèrent que la signalisation Notch module le phénotype des cellules O4 + dans le DLGG en abaissant les marqueurs associés aux oligodendrocytes et en augmentant les protéines associées aux cellules SOX9 + , ce qui met en lumière leur plasticité?

Summary in French

Conclusions et implications

Dans ma thèse de doctorat, j'ai étudié l'hétérogénéité tumorale des gliomes diffus de bas grade mutés en IDH1, un sous-type de gliomes pour lequel on sait peu de choses au niveau cellulaire et au niveau des voies d'accès. Pour répondre à ces questions, j'ai utilisé des sections de tumeurs fraîchement réséquées, une culture de cellules primaires provenant de tissus tumoraux et une nouvelle lignée cellulaire de LGG de grade II. J'ai démontré qu'il existe au moins deux populations non chevauchantes dans les tumeurs DLGG, identifiées par l'expression de OLIG1 et SOX9, marqueurs moléculaires caractéristiques des lignées oligodendrocytaires et astrocytaires, respectivement (figure 2). En outre, j'ai montré que ces sous-populations tumorales identifiées diffèrent dans l'expression de divers autres facteurs de transcription ainsi que dans les voies de signalisation. Les cellules de type astrocytaire expriment des niveaux élevés de HEY1/HEY2, ID4 tandis que les cellules de type oligo présentent de fortes colorations pour les facteurs de transcription ASCL1/MASH1, OLIG1 et SOX4/SOX8. J'ai également identifié que les cellules oligo-like avaient des niveaux plus élevés de 3 récepteurs (EGFR, PDGFRA et PTPRZ1) que les cellules astro-like. Enfin, j'ai observé un niveau plus élevé d'apolipoprotéine E (APOE), de BMP4, de canal K + activé par le Ca2 + à faible conductance (SK3/KCNN3) et d'alpha-cristalline B (CRYAB) dans les cellules astro-like alors que l'enzyme IDH1 semble être davantage exprimée dans les cellules oligolike. Dans le but final de la thèse, j'ai montré comment l'altération des voies de signalisation Notch1 pouvait modifier les phénotypes des cellules tumorales. La régulation à la hausse de a signalisation Notch1 dans les cellules tumorales a entraîné une augmentation de l'expression des marqueurs cellulaires associés au SOX9, ce qui suggère que Notch est l'acteur clé dans le contrôle des phénotypes cellulaires et dans la détermination de l'hétérogénéité des DLGG.

Pour renforcer encore cette observation, j'ai inhibé la signalisation de notch dans les cellules tumorales et montré une expression accrue des marqueurs cellulaires associés à OLIG1. De manière frappante, j'ai également montré que les changements d'expression génétique induits par la modification de la signalisation notch ont des implications fonctionnelles. L'un des gènes sensibles aux modifications de la signalisation du notch est le KCNN3, un canal K + hautement exprimé dans le cerveau. Suite à mon observation selon laquelle la surexpression de notch augmente le KCNN3, j'ai évalué si cette expression accrue modifie les propriétés électrophysiologiques des cellules DLGG. Il est intéressant de noter que les cellules surexprimées par Notch ont montré une augmentation du Ca2 + par l'Ionomycine, ce qui a contexte tumoral respectif, ce qui permettrait de faire la lumière sur les cibles thérapeutiques potentielles au stade précoce du gliome?

Summary in English

Summary in English

Diffuse Low-Grade Gliomas (DLGG) is WHO grade II glial tumors affecting younger adults. They are characterized as silent, slow growing tumors with fewer mitotic activities. However, they diffuse and invade the healthy brain via blood vessels and nerve fibers. These, over a period of years develop to malignant Glioblastoma, aggressive brain tumors where patients have an average medial survival of 12-15 months after diagnosis. Ill-defined phenotypic and cellular diversity of DLGG poses serious limitation to treatment and prevention at the early stage.

In my PhD thesis, I aimed to address this limitation by characterizing the cellular heterogeneity in IDH1-mutated DLGG. By performing immunofluorescence analysis on grade II astrocytoma and oligodendroglioma, I have identified two largely non-overlapping cellular subpopulations expressing SOX9 and OLIG1 transcription factors, which represent astrocyte-like and oligodendrocyte-like cells, respectively. Upon further investigation, I have shown that these subpopulations express distinct molecular markers. SOX9 cells are associated with APOE, KCNN3, CRYAB and ID4, while OLIG1 cells showed strong correlation with the expression of PDGFRA, SOX8, MASH1, and SOX4. In addition, the SOX9 cells show a particular activation of signaling pathways including Notch, BMP and their downstream targets.

To ascertain the role of Notch signaling in regulating the formation of these tumoral subpopulations, I used magnetic sorting of these cells from freshly resected glioma samples and overexpressed Notch Intracellular Domain (NICD), an active form of Notch. Increased Notch activation resulted in an upregulation of Sox9-and downregulation of Olig1-associated cell markers. I have then extended these analyses on one anaplastic IDH1 mutated patient derived cell line which reproduced similar gene expression profile confirming the robustness of the role of Notch signaling in regulating the plasticity of the cells. Parallel experiments performed by activation of BMP signaling on IDH1 mutated cell line did not show a prominent effect on the plasticity. Nevertheless, BMP signal activation highly upregulated CRYAB, a SOX9 related marker and downregulated OLIG1 and OLIG2.

In conclusion, I have identified two non-overlapping tumor subpopulations in diffuse lowgrade gliomas and demonstrated the deterministic role of Notch signaling pathway in their formation. I believe that these findings would aid in better understanding tumoral heterogeneity in DLGG and be extended in designing new therapeutic strategies against these tumors.

List of Abbreviations

List of Abbreviations

GPR17

G-protein-coupled receptor 17 Anatomically, mammalian nervous system is divided into Central Nervous system (CNS) and Peripheral Nervous system, in which CNS is composed of brain and Spinal Cord. Brain is a highly complex organ that controls whole of the bodily functions including movements, sensation, speech and memory. At the cellular level, brain is primarily composed of two major cell types -Neurons and Glial cells.

Neurons are the building blocks of the nervous system, highly specialized cell types forming intricate network to communicate with each other to produce physical responses and actions.

There are an estimated number of 86 billion neurons in the human brain [START_REF] Herculano-Houzel | The human brain in numbers: a linearly scaled-up primate brain[END_REF]. To carry out the critical and crucial signaling of neurons, they require the help of the other cell types collectively named as glial cells. Initially identified by Virchow in 1846, these cells were considered as gluing cells forming a connective network for the functioning of the neurons [START_REF] Somjen | Nervenkitt: notes on the history of the concept of neuroglia[END_REF]. But it very well clear that glial cells are much more diverse in their forms and functions and is an integral part of the nervous system, equally important as neurons for the nervous system to function. Human brain has an almost equal numbers of neurons and glia [START_REF] Von Bartheld | The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting[END_REF]. The three major glial cell types in the brain are astrocytes, oligodendrocytes and microglial cells with an estimated proportion of 20%, 25%

and 5-15% of cells respectively [START_REF] Salter | Microglia emerge as central players in brain disease[END_REF][START_REF] Von Bartheld | The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting[END_REF]. The interactions between neurons and glia are highly dynamic and bidirectional that they mutually coexist for their survival and functions. The influence of glia on neurons begins from the early stages of development where they play key regulatory roles in determining neuronal cell numbers [START_REF] Taverna | The cell biology of neurogenesis: toward an understanding of the development and evolution of the neocortex[END_REF], axon guidance and [START_REF] Minocha | Nkx2.1-derived astrocytes and neurons together with Slit2 are indispensable for anterior commissure formation[END_REF] synapse formation [START_REF] Allen | Cell Biology of Astrocyte-Synapse Interactions[END_REF][START_REF] Reemst | The Indispensable Roles of Microglia and Astrocytes during Brain Development[END_REF] The specific roles of each glial type are mentioned below.

Introduction

Astrocytes

Astrocytes are one of the abundant glial cell type involved in performing a plethora of essential functions in the central nervous system. These are star shaped cells with multiple processes forming connections with almost all cell types of the brain. Their major function is to maintain tissue homeostasis by taking part in molecular, cellular and metabolic processes.

They are involved in neural conduction through transport of ions and protons, release of neurotransmitter precursors or by scavenging neurotransmitters and reactive oxygen species.

One of the critical functions of astrocytes is to regulate neurotransmitter homeostasis (Figure 1). Excess glutamate in the synapse and extra-synaptic space leads to neuronal hyperexcitation and subsequently neuronal death. Therefore, unused and excess glutamate has to be rapidly cleared and this is achieved by astrocytes through the glutamate transporters.

They also secrete gliotransmitters that signals neurons and other cell types to enhance neuronal plasticity [START_REF] Allen | Astrocyte regulation of synaptic behavior[END_REF][START_REF] Araque | Gliotransmitters travel in time and space[END_REF][START_REF] Khakh | Astrocyte calcium signaling: from observations to functions and the challenges therein[END_REF]. They also control the excitability of neurons by scavenging the K + ions from the extracellular space that would otherwise results in continued firing [START_REF] Larsen | Contributions of the Na(+)/K(+)-ATPase, NKCC1, and Kir4.1 to hippocampal K(+) clearance and volume responses[END_REF]. Astrocytes regulate the metabolism of the neurons by synthesizing and supplying glycogen that are converted to lactate and transferred to neurons [START_REF] Magistretti | Lactate in the brain: from metabolic end-product to signalling molecule[END_REF]. They actively synthesis lipid molecules such as cholesterol and are transported to neurons essential for their synaptic functions [START_REF] Allen | Cell Biology of Astrocyte-Synapse Interactions[END_REF]. Through vascular endfeets, astrocytes interact with the blood vessels to actively supply nutrients that are otherwise limited due to blood-brain barrier [START_REF] Daneman | The blood-brain barrier[END_REF][START_REF] Nortley | Control of brain energy supply by astrocytes[END_REF]. They also release vasoactive substances thus regulating the blood supply to the different parts of the brain. Apart from these diverse functions, these cells are also involved in the defense mechanisms along with the immune systems through activation of reactive astrocytes during injury and inflammations [START_REF] Sofroniew | Astrocyte barriers to neurotoxic inflammation[END_REF].

Oligodendrocytes

Oligodendrocytes are involved in ensheathing the axons of neurons with a layer of myelin increasing the velocity of signal conduction. These cells are formed through the differentiation of Oligodendrocyte precursor cells (OPC) that constitute about 3 -10% in human brain [START_REF] Dimou | Glial cells as progenitors and stem cells: new roles in the healthy and diseased brain[END_REF]. Similar to astrocytes, OPCs are also shown to have an effect on the synaptic activity of the neurons as well as in regulating the K + ion levels in the milieu [START_REF] Larsen | Contributions of the Na(+)/K(+)-ATPase, NKCC1, and Kir4.1 to hippocampal K(+) clearance and volume responses[END_REF]. Knockout of Kir4.1, an inward rectifying potassium channel in myelinating oligodendrocytes resulted in poor K + clearance [START_REF] Larson | Oligodendrocytes control potassium accumulation in white matter and seizure susceptibility[END_REF].

Introduction

Myelinating oligodendrocytes also provide metabolic support to the neurons at the regions of axons by transporting lactate. Also during the time of high-frequency axonal activity, Nmethyl-D-aspartate (NMDA), a glutamate receptor is activated triggering glucose uptake and subsequent lactate transport to axons to cater to the energy requirements [START_REF] Saab | Myelin dynamics: protecting and shaping neuronal functions[END_REF]. Myelination not only increases the speed of impulse transmission but also have an influence in the neuronal behaviour. Learning of new motor activities generates new oligodendrocytes in the brain and the loss of which impairs the process of learning [START_REF] Almeida | On Myelinated Axon Plasticity and Neuronal Circuit Formation and Function[END_REF].

Microglia

They are the resident macrophages of the CNS. They are derived from erythromyeloid progenitors, which migrate to the CNS during the early stages of development and proliferate and colonize the brain and spinal cord [START_REF] Ginhoux | Origin of microglia: current concepts and past controversies[END_REF]. They are the first line of defense system in the CNS. They regulate the neuronal survival and phagocytose the apoptotic neurons [START_REF] Kierdorf | Microglia in steady state[END_REF]. They also perform various other functions like the other glial cells. One important function of microglia is the synaptic pruning, eliminating the weak synapses [START_REF] Reemst | The Indispensable Roles of Microglia and Astrocytes during Brain Development[END_REF]. Interleukin-33 released by the astrocytes activates the microglia to regulate synaptic pruning [START_REF] Vainchtein | Astrocyte-derived interleukin-33 promotes microglial synapse engulfment and neural circuit development[END_REF]. Motor learning is impaired when microglia are eliminated in the juvenile mice brain and deregulation of microglial functions can have an influence in the synaptic and circuit functions [START_REF] Salter | Microglia emerge as central players in brain disease[END_REF].

Ependymal cells

Ependymal cells are the fourth type of glial cells present in the central nervous system. These Vertebrate CNS development begins with the neural tube formation lined by a single layer of neuroepithelial cells. As the neural tube develops, stem cells are confined to the ventricular zone lining the lumen and the generated post-mitotic cells migrate radially towards the brain surface forming layers [START_REF] Altmann | Neural patterning in the vertebrate embryo[END_REF]. The neuroepithelial cells are characterized to have epithelial features and maintain an apico-basal polarity with apical region towards the ventricular zone and basal region extending towards the pial surface (Figure 2) [START_REF] Huttner | Asymmetric division and polarity of neuroepithelial cells[END_REF]. These cells undergo symmetric division to generate an extensive pool of stem cells before asymmetric division sets in to generate the other cell types [START_REF] Chenn | Cleavage orientation and the asymmetric inheritance of Notch1 immunoreactivity in mammalian neurogenesis[END_REF][START_REF] Takahashi | Mode of cell proliferation in the developing mouse neocortex[END_REF]. During the onset of neurogenesis, these neuroepithelial cells gradually transform into radial glial cells, which has lost certain epithelial features such as loss of tight junction and gain astroglial features but not apico-basal polarity [START_REF] Malatesta | Isolation of radial glial cells by fluorescent-activated cell sorting reveals a neuronal lineage[END_REF] [START_REF] Grove | Multiple restricted lineages in the embryonic rat cerebral cortex[END_REF][START_REF] Kriegstein | Radial glia diversity: a matter of cell fate[END_REF]. The transition of neuroepithelial cells to radial glial cells occurs in embryonic day (E) 9-10 in mice. They undergo asymmetrical division to give rise to an immature neuron or an intermediate progenitor cell that in turn can generate daughter progenitors or neurons. [START_REF] Haubensak | Neurons arise in the basal neuroepithelium of the early mammalian telencephalon: a major site of neurogenesis[END_REF][START_REF] Miyata | Asymmetric production of surface-dividing and non-surface-dividing cortical progenitor cells[END_REF][START_REF] Noctor | Cortical neurons arise in symmetric and asymmetric division zones and migrate through specific phases[END_REF].

In human brain majority of the radial glial cells are located in the outer subventricular zone and are termed as outer radial glial cells (oRG). These cells lack apical junction and exhibit distinct migratory behavior and are involved in generating majority of the cortical neurons.

They are enriched in genes involved in stem cell maintenance, epithelial to mesenchymal transition and extracellular matrix production [START_REF] Hansen | Neurogenic radial glia in the outer subventricular zone of human neocortex[END_REF][START_REF] Lewitus | Conical expansion of the outer subventricular zone and the role of neocortical folding in evolution and development[END_REF][START_REF] Pollen | Molecular identity of human outer radial glia during cortical development[END_REF].

Oligodendrogenesis

Oligodendrocytes begin to appear around birth in mice. But OPCs are generated successively in three-wave process starting around E11.5-E12.5 [START_REF] Kessaris | Competing waves of oligodendrocytes in the forebrain and postnatal elimination of an embryonic lineage[END_REF]. As the brain develops, these OPCs proliferate and migrate dorsally to disperse in the forebrain before they start to differentiate to pre-myelinating oligodendrocytes (pre-OLs) around E16.5 in mice. In humans, OPC generation begins at 13 gestational weeks and pre-OLs around 17-20 weeks [START_REF] Jakovcevski | Oligodendrocyte development and the onset of myelination in the human fetal brain[END_REF]. The pre-OLs could remain for about 3 months in the brain before they differentiate into myelinating oligodendrocytes in humans [START_REF] Back | Arrested oligodendrocyte lineage progression during human cerebral white matter development: dissociation between the timing of progenitor differentiation and myelinogenesis[END_REF]. The pre-OLs undergo proliferation and differentiate into mature myelinating oligodendrocytes, which produce myelin sheath to wrap around the axon of neurons for saltatory conduction of neural antigens, whereas mature oligodendrocytes have long processes wrapping neuronal fibers and express myelin related protein such as myelin basic protein (MBP) and myelin proteolipid protein (PLP) [START_REF] Jiang | Cellular and molecular introduction to brain development[END_REF][START_REF] Rowitch | Developmental genetics of vertebrate glialcell specification[END_REF].

Astrogenesis

Development and lineage tracing of astrocytes is not clearly understood compared to the oligodendrocytes owing to the lack of reliable cellular markers expressed by the stage-specific astrocytes. Astrogenesis begins after neurogenesis at around E16 in mice. Early stage astrocytes can be directly generated from the radial glia cells in the ventricular zone and migrate along the radial glial process to colonize in the CNS and in later stages, they are generated as astrocyte progenitors from radial glia cells that migrate to various regions before they differentiate [START_REF] Bayraktar | Astrocyte development and heterogeneity[END_REF][START_REF] Rowitch | Glial specification in the vertebrate neural tube[END_REF][START_REF] Rowitch | Developmental genetics of vertebrate glialcell specification[END_REF]. In rodents, astrocytes after birth can also be generated by the proliferation of locally differentiating astrocytes and get integrated into the functional glial networks of the CNS as mature astrocytes [START_REF] Ge | Local generation of glia is a major astrocyte source in postnatal cortex[END_REF]. They express various markers such as Glial fibrillary acidic protein (GFAP), Aldehyde Dehydrogenase 1 Family Member L1 (ALDH1L1),

Aldolase C (ALDOC), aquaporin 4 etc. [START_REF] Molofsky | Astrocytes and disease: a neurodevelopmental perspective[END_REF]. Morphologically, they are subdivided into two types -Fibrous astrocytes, seen in the white matter are star shaped cells and protoplasmic astrocytes, characterized as bushy with irregular processes are often found in the grey matter.

Introduction

Signaling pathways and transcription factors regulating gliogenesis.

There are several signaling pathways involved to play crucial roles in the generation and specification of gliogenesis. Extensive studies have been carried out implicating the role of Sonic Hedgehog (Shh), Fibroblast Growth Factor 2 (FGF2), Wnt/β-catenin, Bone morphogenetic proteins (BMP) and Notch signaling in the specification of oligodendrocyte lineage. Shh is expressed by the precursor cells located ventrally in the sub-ventricular zone from which OPC are generated, induces the expression of Olig2, necessary of OPC specification [START_REF] Nery | Sonic hedgehog contributes to oligodendrocyte specification in the mammalian forebrain[END_REF][START_REF] Takebayashi | The basic helix-loop-helix factor olig2 is essential for the development of motoneuron and oligodendrocyte lineages[END_REF][START_REF] Tekki-Kessaris | Hedgehog-dependent oligodendrocyte lineage specification in the telencephalon[END_REF]. FGF is another signaling essential for OPC specification in the ventral telencephalon. FGF receptors 1-3 are expressed in the developing CNS and knockout of FGFR 1 or 2 results in reduced production of OPC [START_REF] Furusho | Fibroblast growth factor signaling is required for the generation of oligodendrocyte progenitors from the embryonic forebrain[END_REF]. Dorsally located Wnt and BMP signaling negatively regulate oligodendrocyte lineage specification. Wnt/b-catenin inhibits OPC generation and promotes oligodendrocyte differentiation, while BMP signaling is involved in astrocyte specification at the expense of oligodendrogenesis [START_REF] Dai | Stagespecific regulation of oligodendrocyte development by Wnt/beta-catenin signaling[END_REF][START_REF] Gomes | Transgenic overexpression of BMP4 increases astroglial and decreases oligodendroglial lineage commitment[END_REF]. Expression of Jagged-1, a ligand for Notch signaling by the committed neuron progenitors prevents neighbouring OPC differentiation through the activation of Notch signaling, and the decline of Jagged-1 by neurons allows OPC differentiation and maturation (Wang et al., 1998). The active proliferation of OPCs during migration is regulated mainly through the PDGFRA signaling, where PDGFA is secreted by the neurons and astrocytes. As

OPCs start to differentiate they lose the PDGF receptors [START_REF] Calver | Oligodendrocyte population dynamics and the role of PDGF in vivo[END_REF][START_REF] Fruttiger | Defective oligodendrocyte development and severe hypomyelination in PDGF-A knockout mice[END_REF]) (Figure 3). Other signaling pathways regulating proliferation include FGF members, insulin and insulin-like growth factors and neurotrophin-3 [START_REF] Mitew | Mechanisms regulating the development of oligodendrocytes and central nervous system myelin[END_REF]. Several positive regulators of oligodendrocyte differentiation include transcription factors such as OLIG1/2, SOX10, NK2 Homeobox 2, (NKX2.2), and Mammalian Achaete-scute homolog-1

(MASH-1) etc. while G-protein-coupled receptor 17 (GPR17), Hes Family BHLH Transcription Factor 5 (HES5), Inhibitor of Differentiation 2 (ID2) and ID4 exert a negative effect [START_REF] Emery | Regulation of oligodendrocyte differentiation and myelination[END_REF][START_REF] Mitew | Mechanisms regulating the development of oligodendrocytes and central nervous system myelin[END_REF][START_REF] Rosenberg | Receiving mixed signals: uncoupling oligodendrocyte differentiation and myelination[END_REF]. Epigenetic factors and chromatin remodeling molecules such as Histone deacetylases and DNA methyl transferases (DNMT), Dnmt3a also regulate the differentiation process of oligodendrocytes [START_REF] Zuchero | Intrinsic and extrinsic control of oligodendrocyte development[END_REF].

Astrogenesis is repressed during neurogenesis. Thus, generation of astrocytes begins when pro-neural signals Neurogenin 1(NGN1) and Erb-B2 Receptor Tyrosine Kinase 2 (ERBB2), anti-astrogenesis growth factor get downregulated [START_REF] Rowitch | Developmental genetics of vertebrate glialcell specification[END_REF].

Introduction express NG2 and PDGFRA along with OLIG2. Cells that commit to myelinating oligodendrocytes continue to express OLIG2. Upon cell fate decision towards astrocytes, NG2 loses OLIG2 and begin expressing astrocytic markers GFAP and ALDH1L1.

C) The developmental stages of astrocyte lineage are poorly defined. Notch Signaling and JAK/STAT3 signaling activation initiates astrocyte maturation. STAT3 cooperates with NFIA to drive the expression of GFAP in a Notch dependent manner. Notch plays a role in astrogenesis through binding of Notch Intracellular Domain (NICD) to its transcription co-activator CSL (CBF1/ RBPjk/ Suppressor of Hairless/ LAG1) to activate astrocytic gene transcription [START_REF] Ge | Notch signaling promotes astrogliogenesis via direct CSL-mediated glial gene activation[END_REF]. Activation of Nuclear Factor 1a (NFIA) results

in the dissociation of DNMT1 from the GFAP promoter allowing STAT3 binding to drive its transcription [START_REF] Namihira | Committed neuronal precursors confer astrocytic potential on residual neural precursor cells[END_REF]. Sox9 regulates gliogenesis through the induction of NFIA [START_REF] Stolt | The Sox9 transcription factor determines glial fate choice in the developing spinal cord[END_REF]) [START_REF] Kang | Sox9 and NFIA coordinate a transcriptional regulatory cascade during the initiation of gliogenesis[END_REF].

In addition to Notch, another important signaling pathway involved in gliogenesis is BMP signaling. BMP is involved in the specification of astrocytes from Neural Progenitor cells (NPC) [START_REF] Rowitch | Developmental genetics of vertebrate glialcell specification[END_REF]. Exposure to BMP4 can commit radial glial cells to astrogenesis inhibiting oligodendrogenesis while BMP2 can inhibit neurogenesis in cultured NPC by activating negative regulators such as HES5 and ID proteins to inhibit pro-neural MASH-1 and NGN2 [START_REF] Gomes | Transgenic overexpression of BMP4 increases astroglial and decreases oligodendroglial lineage commitment[END_REF][START_REF] Nakashima | BMP2-mediated alteration in the developmental pathway of fetal mouse brain cells from neurogenesis to astrocytogenesis[END_REF]. BMP2 and Leukemia

Inhibitory Factor (LIF), a cytokine together can transcriptionally activate GFAP through STAT3/p300/Smad1 complex in fetal NPC to induce astrocytes [START_REF] Nakashima | Synergistic signaling in fetal brain by STAT3-Smad1 complex bridged by p300[END_REF].

Also, BMP plays a role in survival and maturation of astrocytes [START_REF] Scholze | BMP signaling in astrocytes downregulates EGFR to modulate survival and maturation[END_REF].

IL-6 cytokine family members such as LIF and Ciliary Neurotrophic Factor (CNTF) also promote astrocytic differentiation in vivo and in vitro by activating JAK/STAT signaling [START_REF] Bonni | Regulation of gliogenesis in the central nervous system by the JAK-STAT signaling pathway[END_REF][START_REF] Nakashima | Synergistic signaling in fetal brain by STAT3-Smad1 complex bridged by p300[END_REF].

In conclusion, the development of various cell types in brain is very well orchestrated in a timely manner through interactions of specific signaling pathways.

Introduction

1.
3. Glioma, their grades and epidemiology

Gliomas

Gliomas are the most common primary intracranial tumors comprising around 80% of malignant tumors (Ostrom et al., 2014a). Although relatively rare, mortality and morbidity are highly significant in these tumors. Gliomas are characterized based on morphological features and degree of anaplasia. Despite the advances in surgery, radiotherapy and chemotherapy, the prognosis of grade IV tumors or Glioblastoma (GBM) is barely improved, with a median survival of 12-15 months. Around 10% of grade IV tumors develop from a precursor lesion progressing from grade II through grade IV. These tumors are identified to have a better prognosis than the de novo developed primary GBM tumors. This thesis is focused on understanding the cellular heterogeneity in grade II glioma in adults. We have attempted to characterize the cellular subgroups and identified key molecular players and pathways involved in regulating the phenotype and plasticity of these cell types that could prevail in the tumoral condition. The aim is to identify molecular markers that contribute to the disease progression or act as tumor suppressors that could be manipulated to prevent the progression to high grades.

History of Classifications in glioma

Over the history of classification, the Glioma were grouped and graded based on the histological characteristics of tumor tissues. The initial classification of glioma by Bailey and Cushing characterized tumors based on cytological resemblance of predominant tumor cell type to their normal counterparts. This led to the identification of 2 tumor subtypesoligodendroglioma and astrocytoma. Astrocytomas were further subdivided into protoplasmic and fibrillary astrocytoma based on the morphological features of astrocytes. [START_REF] Bailey | A classification of tumours of the Glioma group on a Histogenetic Basis with a correlation study of prognosis[END_REF]. Morphologically, oligodendroglioma resembled oligodendrocytes that had fried egg morphology with round nuclei cells surrounded by a ring of cytoplasm. When tumors shared cytological features of both astrocytes and oligodendrocytes, these were classified as oligoastrocytoma. [START_REF] Era | The relation of oligocytes and astrocytes in cerebral tumours[END_REF] The term 'anaplasia' was introduced to define the undifferentiated state of the tumor cells that develop as a process of dedifferentiation of normal mature cells (D; J.). This led to the advancement of grading tumors based on their prognosis and degree of malignancy, which progress from grade II tumors with cellular atypia and differentiated normal looking cells to malignant tumors at grade IV with anaplastic transformation along with proliferation, vascularization and necrosis [START_REF] Kernohan | A simplified classification of the gliomas[END_REF] Introduction oligodendroglioma and oligoastrocytoma. At grade III, tumor shows anaplasia and mitotic activity while, grade IV tumors additionally show microvascular proliferation and necrosis (Louis et al., 2007). The classifications based on histology had several limitations. Interpersonal variability was the major drawback. Unavailability of reliable staining markers, and the difficulty in accurately determining the grades of the tumor was severely compromised. In regards to the oligoastrocytoma subtype, it was even problematic to determine the proportions of each component to classify them into this subtype of tumor, which was also very subjective. The accurate determination of grades of the tumor is essential for the proper patient management and prognostic determination and response to treatment [START_REF] Rigau | Histological Classification[END_REF].

Thus arose a need for a new classification system that could provide a unified basis of understanding and determining the grades and reduce the variability.

Current classification of glioma

The fifth edition of WHO classification is the latest classification of Central Nervous System tumors published in 2016 (Louis et al., 2016). This was a major breakthrough in the field of Thus, even if a diffuse glioma histologically resembles astrocytes, but carry IDH mutation and 1p/19q co-deletion, it is considered an oligodendroglioma. Similarly, IDH mutation, ATRX and P53 mutation, commonly identified in astrocytoma labels tumors as astrocytic irrespective of their oligodendrocytic appearance. The genetic analysis of tumors abrogated the existence of complex subtype of mixed oligoastrocytoma, as they now started falling into Introduction either of the other subtype. Thus, diffuse astrocytomas and oligodendrogliomas have now been classified together as grade II if they have their respective genetic aberration along with nuclear atypia and no anaplastic transformation. Anaplastic astrocytoma and oligodendroglioma form the grade III of these tumors. Glioblastoma with IDH wild type and secondary glioblastoma with IDH mutation makes the grade IV of gliomas. If the IDH status cannot be determined they have been grouped as a third category of NOS (not otherwise specified). Another subtype of glioma categorized in grade IV is the diffuse midline glioma with H3K27M mutation, which mostly arises in the brain stem, spinal cord and thalamus of both children and young adults. This substantial step taken forward will help in accurate characterization leading to improved patient management and implementation of better therapeutic strategy (Louis et al., 2016).

With the advancement in understanding the effect of molecular alterations in better predicting the outcome of disease as well as in diagnosis of tumors, several modifications are proposed to be included in the next update on classification system. One of the major recommendations is to separate the IDH wildtype glioblastomas from IDH-mutated GBM that have better prognosis. Other than the histological grading based on microvascular proliferation and necrosis, molecular alterations also gain prominence in assigning the grades. In particular, IDH wildtype glioblastoma contain TERT promoter mutation, EGFR amplification or combination of loss of chromosome 10 and gain of chromosome 7. Similarly, IDH-mutated astrocytoma comprise of 3 grades-Astrocytoma, IDH-mutant, WHO grade 2, diffusely infiltrating differentiated tumors, Astrocytoma, IDH-mutant, WHO grade 3 that exhibit anaplasia and mitotic activity and Astrocytoma, IDH-mutant WHO grade 4 exhibiting microvascular proliferation or necrosis or CDKN2A/B homozygous deletion or their combination [START_REF] Louis | cIMPACT-NOW update 6: new entity and diagnostic principle recommendations of the cIMPACT-Utrecht meeting on future CNS tumor classification and grading[END_REF].

This thesis primarily focuses of grade II IDH1 mutated diffuse low-grade glioma in adults.

Next section describes the epidemiology and common genetic alterations identified in the two subtypes-astrocytoma and oligodendroglioma. Epidemiology and genetics 1.3.5.1.1. Epidemiology of DLGG DLGGs are slowing-growing tumors that have a growth rate of 4mm/year and most often transform into anaplastic lesions or a secondary GBM within a decade (Mandonnet et al., 2003). The progression can be grouped into three stages; (i) a presymptomatic stage of unknown duration until the discovery of the tumor (Mandonnet et al., 2003). (ii) a symptomatic stage of about 7 years after the initial seizure and patients may lead a regular life if seizures can be controlled [START_REF] Pallud | Velocity of tumor spontaneous expansion predicts long-term outcomes for diffuse low-grade gliomas[END_REF], (iii) 2-3 years of rapid tumor progression associated with anaplastic induction [START_REF] Pignatti | Prognostic factors for survival in adult patients with cerebral low-grade glioma[END_REF]. There are no stable or steady DLGGs identified. Adverse prognostic features include patients above 40 years, nonseizure symptoms, neurological deficits and tumor size exceeding 6cm, tumor crossing midline and astrocytic cellular features in histology [START_REF] Pignatti | Prognostic factors for survival in adult patients with cerebral low-grade glioma[END_REF].

IDH mutated diffuse low-grade glioma are broadly divided into two subtypes -astrocytoma and oligodendroglioma. Low-grade glioma accounts for 6.4% of all adult primary CNS tumors. They are often present in younger adults between 25-45 years of age. In general, chance of diagnosis of IDH mutated grade II and grade III glioma decreases in patients older than 50 to 55 years of age. Grade II gliomas have preferential brain localizations, commonly found in eloquent areas; regions of brain involved in motor, language, memory and visuospatial functions [START_REF] Duffau | Preferential brain locations of low-grade gliomas[END_REF][START_REF] Sanai | Low-grade gliomas in adults[END_REF]. Current treatment method is maximal safe surgical resection to improve seizure control and increase progression free survival (PFS) and Overall Survival (OS). The general principles of surgery generally accepted by the neurosurgical community is underlined by Professor Hughes Duffau -"early radical surgery, awake surgery in high eloquent areas, cortical mapping, resection according to cortico-subcortical functional and not oncological boundaries, and multistage resection in critical regions" (Duffau and Mandonnet, 2013). 1.3.5.1.2 [START_REF] Bogdanovic | IDH1, lipid metabolism and cancer: Shedding new light on old ideas[END_REF]Geisbrecht and Gould, 1999; Introduction VEGF, required for angiogenesis [START_REF] Zhao | Glioma-derived mutations in IDH1 dominantly inhibit IDH1 catalytic activity and induce HIF-1alpha[END_REF]. Inhibition of collagen hydroxylase results in defective maturation of collagen impairing the basement membrane. The depletion of NADPH pool by IDH1R132H enzyme can affect other cellular processes such as lipid biosynthesis and repair of oxidative damage leading to accumulation of Reactive Oxygen Species (ROS). Figure adapted from [START_REF] Liu | Genetics and Epigenetics of Glioblastoma: Applications and Overall Incidence of IDH1 Mutation[END_REF][START_REF] Tommasini-Ghelfi | Cancer-associated mutation and beyond: The emerging biology of isocitrate dehydrogenases in human disease[END_REF] Introduction

Reports have also demonstrated that 2-HG increases the activity of Hypoxia Inducible Factor-1α (HIF1α) and thereby increases the levels of its downstream target, Vascular Endothelial Growth Factor (VEGF) initiating angiogenesis [START_REF] Sasaki | D-2-hydroxyglutarate produced by mutant IDH1 perturbs collagen maturation and basement membrane function[END_REF]. Though initial discovery of the mutation was identified in secondary GBMs, 80-90% of diffuse grade II and anaplastic grade III tumors are mutated for IDH1 making it a gold standard to classify these tumors subtypes. Other substitutions that are also observed include R132L, R132C, R132S, and R132G [START_REF] Hartmann | Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas[END_REF]. The mutations are identified generally in younger patients (Parsons et al., 2008;[START_REF] Yan | IDH1 and IDH2 mutations in gliomas[END_REF]. It also has a positive correlation to the survival of the patients making it a favorable prognostic marker (Parsons et al., 2008). Though not so common, IDH2 mutations are also observed in 1% of patients diagnosed with R172H mutation [START_REF] Hartmann | Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas[END_REF][START_REF] Yan | IDH1 and IDH2 mutations in gliomas[END_REF].

One of the common features accompanying IDH mutation is the hyper methylated phenotype of CpG islands (CG islands) commonly referred to as G-CIMP (Noushmehr et al., 2010) (Turcan et al., 2012). Introduction of IDH1 mutation on human primary astrocytes was sufficient to alter the methylated status and induce hyper histone methylation in the cells similar to G-CIMP + gliomas (Turcan et al., 2012). This methylation interferes with the terminal differentiation of cells predisposing them to malignant transformation. (Lu et al., 2012a) [START_REF] Rohle | An inhibitor of mutant IDH1 delays growth and promotes differentiation of glioma cells[END_REF].

Several studies have been published corroborating the relationship between IDH mutation and improved prognosis in early grades and well as in GBM. Univariate analysis on 271 grade II diffuse glioma showed a significant increased Overall Survival (OS) [START_REF] Houillier | IDH1 or IDH2 mutations predict longer survival and response to temozolomide in low-grade gliomas[END_REF].

Similarly, another study performed on grade II and III of diffuse glioma also showed an improved overall survival in IDH mutated tumors compared to the IDH wild-type glioma irrespective of their grades (Olar et al., 2015). Comprehensive genomic analysis performed by

The Cancer Genome Atlas (TCGA) Research Network on 293 Grade II and grade III glioma identified 1p/19q co-deletion to have an improved additive prognosis on tumors with IDH mutation. Tumors with both the mutations (oligodendroglioma) had an OS of 8 years, which is huge comparing to an OS of 6.3 years for an astrocytoma with 1p/19q intact, while IDH wild-type tumors have only an OS of 1.7 years (Cancer Genome Atlas Research et al., 2015).

OS and progression free survival (PFS) was also significant in IDH mutated grade III glioma patients and responded better to radiotherapy, temozolomide (TMZ) or nitrosourea (Chang et al., 2017).

IDH wildtype (IDH-wt) tumors are a minority in grade II gliomas representing around 20%. [START_REF] Aoki | Prognostic relevance of genetic alterations in diffuse lower-grade gliomas[END_REF]Pekmezci et al., 2017). AII occur in younger adults at a peak incidence of 20-34 years of age representing about 25.2% of malignant brain tumors [START_REF] Ostrom | CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2007-2011[END_REF]. Higher incidences of AII are observed in the anterior regions such as frontal region followed by temporal and insular regions on the left side [START_REF] Laigle-Donadey | Correlations between molecular profile and radiologic pattern in oligodendroglial tumors[END_REF]) [START_REF] Capelle | Spontaneous and therapeutic prognostic factors in adult hemispheric World Health Organization Grade II gliomas: a series of 1097 cases: clinical article[END_REF][START_REF] Latini | Differences in the preferential location and invasiveness of diffuse low-grade gliomas and their impact on outcome[END_REF]. Seizures are the most common symptom observed in up to 80% cases at the debut. Other symptoms include behavioral and personality changes, visual impairment etc. AII are more confined to white matter regions [START_REF] Giese | Glioma invasion in the central nervous system[END_REF]. Low-grade astrocytomas show extensive infiltration to adjacent subcortical regions [START_REF] Guthrie | Supratentorial low-grade gliomas[END_REF]. MRI is the golden standard of imaging tool used for diagnosis. They form homogeneous signal intensity in T2

weighted images and often have a distinct border [START_REF] Ștefan Ioan Florian | Diffuse Astrocytoma and Oligodendroglioma: An Integrated Diagnosis and Management[END_REF]. In adults, most AII progresses to anaplastic astrocytoma and further to secondary glioblastoma.

Genetic alterations in diffuse astrocytoma

Astrocytomas are typically associated with ATRX mutation and p53 mutation. In the below sections, I will describe in detail about these mutations in astrocytoma (Figure 6).

ATRX mutation

Mutations on the Alpha-Thalassemia/ Mental Retardation Syndrome X-linked (ATRX) gene are very commonly observed in DLGG, specifically in astrocytoma (Louis et al., 2016). The loss of function mutation of ATRX is observed in approximately 75% of grade II and grade III as well as in secondary glioblastomas (Jiao et al., 2012). ATRX mutations are mutually Introduction exclusive to TERT promoter mutations in glioma making it a very specific marker for diffuse astrocytoma [START_REF] Karsy | New Molecular Considerations for Glioma: IDH, ATRX, BRAF, TERT, H3 K27M[END_REF][START_REF] Killela | TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal[END_REF]. ATRX mutational status correlates with the age, grade and prognosis. ATRX mutations are associated with low grade glioma observed in younger patients and confer a better progression free and overall survival to patients with IDH1 mutation without 1p/19q co-deletion (Jiao et al., 2012;[START_REF] Leeper | IDH mutation, 1p19q codeletion and ATRX loss in WHO grade II gliomas[END_REF][START_REF] Wiestler | ATRX loss refines the classification of anaplastic gliomas and identifies a subgroup of IDH mutant astrocytic tumors with better prognosis[END_REF]. Even though ATRX is rarely mutated in primary glioblastoma, patients with ATRX mutation in IDH1 wildtype tumors have increased survival when compared to ATRX wildtype group (Olar and Sulman, 2015). ATRX is a chromatin remodeling protein belonging to the SWI/SNF2 (SWItch/Sucrose Non Fermentable) family known to deposit H3.3 at telomeres and pericentromeric heterochromatin regions (Pekmezci et al., 2017).

Through its chromatin remodeling functions and interactions with other binding proteins, ATRX performs wide range of functions such as maintaining genomic stability by eliciting DNA damage response and regulating gene transcriptions [START_REF] Clynes | ATRX dysfunction induces replication defects in primary mouse cells[END_REF][START_REF] Tang | A novel transcription regulatory complex containing death domain-associated protein and the ATR-X syndrome protein[END_REF]. Loss of ATRX increases genetic instability, impairs non-homologous end joining (NHEJ) and increases cellular sensitivity to double strand breaks inducing DNA damaging agents [START_REF] Koschmann | ATRX mutations and glioblastoma: Impaired DNA damage repair, alternative lengthening of telomeres, and genetic instability[END_REF]. ATRX loss promotes Alternative Lengthening of Telomeres (ALT) in glioma [START_REF] Abedalthagafi | The alternative lengthening of telomere phenotype is significantly associated with loss of ATRX expression in highgrade pediatric and adult astrocytomas: a multi-institutional study of 214 astrocytomas[END_REF][START_REF] Amorim | The Role of ATRX in the Alternative Lengthening of Telomeres (ALT) Phenotype[END_REF].

Information we gained so far on ATRX and their mutations in glioma are majorly correlative.

One such study identified a positive correlation of ATRX loss with PDGFRA amplification [START_REF] Abedalthagafi | The alternative lengthening of telomere phenotype is significantly associated with loss of ATRX expression in highgrade pediatric and adult astrocytomas: a multi-institutional study of 214 astrocytomas[END_REF]. Future studies should look into the prospects of inhibiting this signaling cascade for specialized therapeutic strategy in this subset of tumor. Also, extensive DNA methylation and mRNA profiling on a cohort of 82 astrocytic tumors demonstrated a distinct gene methylation profile in patients with ATRX mutation compared to ATRX wildtype. Mutated ATRX downregulates the expression of O 6 -methylguanine-DNA methyltransferase (MGMT) through hypermethylation of its promoter signifying its prognostic role. Knockdown of ATRX in a glioma cell line reduced tumor proliferation and cell migration and increased cellular apoptosis shedding light to their importance in gliomas [START_REF] Cai | Loss of ATRX, associated with DNA methylation pattern of chromosome end, impacted biological behaviors of astrocytic tumors[END_REF]. There has not been a systematic study on ATRX in the context of glioma to provide insights into its functional role. Future studies should focus on addressing the role of ATRX in glioma pathogenesis and its potential role as a therapeutic target. [START_REF] Zilfou | Tumor suppressive functions of p53[END_REF]. It is also the most commonly mutated tumor suppressor gene in all cancers including glioma. TP53 mutations are observed in around 28% lower grade glioma but with a co-occurrence in IDH1 mutated astrocytoma in around 90% tumors (Brennan et al., 2013). While TP53 mutations also occur in 22% of primary glioblastoma, it is considered as an early event in low-grade astrocytoma and secondary glioblastoma, (Ohgaki et al., 2004;[START_REF] Ohgaki | Genetic pathways to primary and secondary glioblastoma[END_REF]. Among the four molecular subtypes in primary GBM, p53 mutations are widely seen in proneural (54%), followed by mesenchymal (32%), neural (21%) and classical (0%) (Verhaak et al., 2010). Inactivating mutations in p53 is correlated to more invasive, proliferative, stem-like and less apoptotic phenotype in GBM [START_REF] Djuzenova | Actin cytoskeleton organization, cell surface modification and invasion rate of 5 glioblastoma cell lines differing in PTEN and p53 status[END_REF][START_REF] England | Current understanding of the role and targeting of tumor suppressor p53 in glioblastoma multiforme[END_REF][START_REF] Park | Induction of p53-mediated apoptosis and recovery of chemosensitivity through p53 transduction in human glioblastoma cells by cisplatin[END_REF][START_REF] Zheng | p53 and Pten control neural and glioma stem/progenitor cell renewal and differentiation[END_REF]. CDKN2A/ARF is frequently deregulated in younger GBM patients and is mutually exclusive to p53 mutations probably owing to their redundant functions in the tumor [START_REF] Biernat | Mutations of TP53, amplification of EGFR, MDM2 and CDK4, and deletions of CDKN2A in malignant astrocytomas[END_REF][START_REF] Fulci | p53 gene mutation and ink4a-arf deletion appear to be two mutually exclusive events in human glioblastoma[END_REF][START_REF] Zadeh | Frequent homozygous deletion of p16/CDKN2A gene in malignant gliomas of Iranian patients[END_REF]. Homozygous deletion of P16, a cell cycle inhibitor or its downregulation through promoter methylation is often found in secondary glioblastoma [START_REF] Nakamura | p14ARF deletion and methylation in genetic pathways to glioblastomas[END_REF]. Genetic alterations in TP53 are mostly missense mutations in DNA binding domain disrupting its transcriptional regulation. These mutations impart oncogenic functions enhancing tumorigenic potential in cells expressing mut-p53 such as increased proliferation, migration, invasion and resistance to therapy [START_REF] Dittmer | Gain of function mutations in p53[END_REF][START_REF] Muller | Mutant p53 drives invasion by promoting integrin recycling[END_REF]. The "hot spot" codon mutational rates are observed higher in secondary GBM (65%) than in primary (30%) where mutations are more equally distributed [START_REF] Ohgaki | Genetic pathways to glioblastomas[END_REF][START_REF] Watanabe | Incidence and timing of p53 mutations during astrocytoma progression in patients with multiple biopsies[END_REF]. This suggests the acquisition of mutations in these glioma subtypes occur through independent mechanisms. Also, early TP53 mutations observed in DLGG compared to de novo glioblastoma also suggest the potential role of p53 in tumor progression from low grade to high grade. Localization of mut-p53 in primary and secondary GBM is variably identified. In secondary GBM, p53 expression is localized to the nucleus while in primary there is preferential cytoplasmic localization [START_REF] Nagpal | Revisiting the role of p53 in primary and secondary glioblastomas[END_REF]. Studies on p53 fail to distinguish between TP53 deletion and gain of function mutations [START_REF] Kraus | TP53 gene mutations, nuclear p53 accumulation, expression of Waf/p21, Bcl-2, and CD95 (APO-1/Fas) proteins are not prognostic factors in de novo glioblastoma multiforme[END_REF][START_REF] Modrek | Low-Grade Astrocytoma Mutations in IDH1, P53, and ATRX Cooperate to Block Differentiation of Human Neural Stem Cells via Repression of SOX2[END_REF][START_REF] Nagpal | Revisiting the role of p53 in primary and secondary glioblastomas[END_REF]. As p53 is rarely deleted in GBM, knock in mouse models of mut-p53 should also be developed and evaluated along with p53 knockout xenograft models of DLGG lesions or IDH1 mutant glioblastoma. and the longest median survival of 17.5 years [START_REF] Aoki | Prognostic relevance of genetic alterations in diffuse lower-grade gliomas[END_REF]Pekmezci et al., 2017).

Clinical presentation is seizures followed by other neurological signs such as mental disturbance, neurological deficits or intracranial pressure mostly as headaches are observed (J. Drummond, 2012). CT scan is the commonly used imaging technique. These are hypodense lesions with intratumoral or peripheral calcification. Oligodendrogliomas can exist at the interface between white and gray matter with an affinity to cerebral cortex (Ștefan Ioan Florian, 2018).

1 .3.5.3.2. Genetics in Diffuse oligodendroglioma 1.3.5.3.2.1. 1p/19q Codeletion Combined deletion of loss of heterozygosity (LOH) at 1p and 19q arms of the chromosomes was initially observed through the molecular genetic analysis performed on grade II and III of oligodendroglioma and oligoastrocytoma [START_REF] Reifenberger | Molecular genetic analysis of oligodendroglial tumors shows preferential allelic deletions on 19q and 1p[END_REF]. This has from then been the most prominent marker specific to oligodendroglial tumors. The deletion occurs due to the unbalanced translocation between chromosomes 1 and 19, resulting in the simultaneous loss of the arms [START_REF] Griffin | Identification of der(1;19)(q10;p10) in five oligodendrogliomas suggests mechanism of concurrent 1p and 19q loss[END_REF][START_REF] Jenkins | A t(1;19)(q10;p10) mediates the combined deletions of 1p and 19q and predicts a better prognosis of patients with oligodendroglioma[END_REF]. Of the commonly mutated genes that follow include CIC (Capicua Transcriptional Repressor) and FUBP1 (far-upstream element (FUSE) binding protein) located in chromosome 19q and 1p respectively [START_REF] Bettegowda | Mutations in CIC and FUBP1 contribute to human oligodendroglioma[END_REF] A recent CIC knockout mouse model has identified the critical role of CIC in neuronal differentiation [START_REF] Hwang | CIC is a critical regulator of neuronal differentiation[END_REF]. FUBP1 and CIC are also involved in MYC expression and repression of Receptor Tyrosine Kinase (RTK) signaling respectively [START_REF] Jiménez | The Capicua repressor -a general sensor of RTK signaling in development and disease[END_REF][START_REF] Liu | The FUSE/FBP/FIR/TFIIH system is a molecular machine programming a pulse of c-myc expression[END_REF] indicating their tumor suppressive functions. 1p/19q codeletion has been shown to be almost always associated with IDH1 mutation and confers a hyper methylated phenotype implying its association to G-CIMP [START_REF] Eckel-Passow | Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors[END_REF][START_REF] Mur | Codeletion of 1p and 19q determines distinct gene methylation and expression profiles in IDH-mutated oligodendroglial tumors[END_REF]Noushmehr et al., 2010).

1p/19q codeletion is identified as the most favorable prognostic subtypes to prolonged OS and has also been associated for its sensitivity to treatment modalities. In a large study undertaken to compare the efficacy of 3-drug chemotherapy regimen (lomustine, procarbazine and vincristine) combined with radiation therapy to radiation alone on grade II glioma revealed longer OS and PFS in patients with codeletion [START_REF] Buckner | Radiation plus Procarbazine, CCNU, and Vincristine in Low-Grade Glioma[END_REF]. Also phase III randomized study on efficacy of TMZ in combination with radiation therapy to treat grade II Introduction glioma indicated that patients with IDH mutation and 1p/19q codeletion (oligodendroglioma) experienced longest PFS of 62 months compared to patients harboring IDH mutation alone (48 months) or IDH wildtype (20 months) [START_REF] Baumert | Temozolomide chemotherapy versus radiotherapy in high-risk low-grade glioma (EORTC 22033-26033): a randomised, open-label, phase 3 intergroup study[END_REF]. 1.3.5.3.2.2

. TERT promoter mutations

Telomerase, a ribonucleoprotein consisting of RNA subunit and telomerase reverse transcriptase (TERT) catalytic subunit, adds telomere repeats to chromosome ends to maintain telomere length [START_REF] Blackburn | Structure and function of telomeres[END_REF]. Increased telomerase activity to overcome replicative telomere shortening is a hallmark of cancer for unrestricted growth of cancer cells [START_REF] Kim | Specific association of human telomerase activity with immortal cells and cancer[END_REF]. Point mutation in the promoter of Telomerase reverse transcriptase is yet another marker of oligodendroglioma that is closely associated with 1p/19q codeletion (98%) (Arita et al., 2013). Two hotspot mutations-C228T and C250T in the TERT promoter are recurrently observed in various cancers including glioma [START_REF] Huang | Highly recurrent TERT promoter mutations in human melanoma[END_REF][START_REF] Killela | TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal[END_REF][START_REF] Nonoguchi | TERT promoter mutations in primary and secondary glioblastomas[END_REF]. These point mutations create a new binding motif for E-twenty-six family of transcription factors increasing transcriptional activity by two to four-fold (Huang et al., 2013). TERT promoter mutations are also observed in IDH wildtype DLGG and GBM [START_REF] Killela | TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal[END_REF]. There are mixed reports of the prognostic effect of TERT mutations.

When they occur together with IDH mutation, TERT mutations seems to have a better prognosis while this mutation exerts a negative impact on IDH wildtype tumors adversely affecting the survival of the patients [START_REF] Vuong | TERT promoter mutation and its interaction with IDH mutations in glioma: Combined TERT promoter and IDH mutations stratifies lowergrade glioma into distinct survival subgroups-A meta-analysis of aggregate data[END_REF]

Primary Glioblastoma

Primary Glioblastoma or Glioblastoma Multiforme (GBM) is the most malignant and frequently occurring astrocytoma accounting for more than 60% of primary brain tumors in adults as de novo without any clinical and histological evidence of precursor lesions [START_REF] Jemal | Cancer statistics, 2010[END_REF]. Despite the advances in the treatment modalities, they are extremely deadly with poor prognosis with a median survival of approximately 14 to 15 months from diagnosis [START_REF] Ohka | Current trends in targeted therapies for glioblastoma multiforme[END_REF][START_REF] Thakkar | Epidemiologic and molecular prognostic review of glioblastoma[END_REF]. GBMs are aggressive and invasive and designated as grade IV primary astrocytoma by WHO (Louis et al., 2016).

Epidemiology and pathogenesis

Introduction

GBMs has a global incidence of less than 10 per 100,000 people but is the third most cause of death in younger patients in the range of 15-34 years of age [START_REF] Hanif | Glioblastoma Multiforme: A Review of its Epidemiology and Pathogenesis through Clinical Presentation and Treatment[END_REF][START_REF] Iacob | Current data and strategy in glioblastoma multiforme[END_REF]. GBM is primarily diagnosed in older age with a median age of 64 years with higher incidence in males than in females [START_REF] Chakrabarti | A population-based description of glioblastoma multiforme in Los Angeles County, 1974-1999[END_REF]Ohgaki and Kleihues, 2005a;[START_REF] Ostrom | CBTRUS statistical report: Primary brain and central nervous system tumors diagnosed in the United States in 2006-2010[END_REF][START_REF] Thakkar | Epidemiologic and molecular prognostic review of glioblastoma[END_REF]. The profusely found location for GBM is in cerebral hemispheres with 95% arising in the supratentorial region [START_REF] Nakada | Aberrant signaling pathways in glioma[END_REF].

Macroscopic and Histological features of GBM

They largely appear as a single irregular shaped lesion usually arising in the white matter comprising of pleomorphic cell populations ranging from poorly differentiated cells to multinucleate cells with some regions appearing soft and yellow while others are firm and white (Nelson andCha, 2003) (MP, 2013). There exist a great variation in the gross appearance of tumor from one region to another. Histological features include pseudopalisading cells with high mitotic activity and region of necrosis and multifocal hemorrhage.

Proliferations of microvascular endothelial cells are also characteristic features of these highgrade tumors [START_REF] Agnihotri | Glioblastoma, a brief review of history, molecular genetics, animal models and novel therapeutic strategies[END_REF][START_REF] Smith | Diagnosis and pathogenesis of gliomas[END_REF].

Treatment modalities

The primary standard of care for primary glioblastoma is surgery [START_REF] Ohka | Current trends in targeted therapies for glioblastoma multiforme[END_REF]. But the extend of resection depends on the location and eloquence of the brain area involved due to which they cannot be removed completely. Most often these tumor relapses in approximately 80% of the cases [START_REF] Iacob | Current data and strategy in glioblastoma multiforme[END_REF]. Radiotherapy and chemotherapy mostly with the alkylating drug Temozolomide (TMZ), the standard chemotherapeutic agent follows surgical treatment [START_REF] Iacob | Current data and strategy in glioblastoma multiforme[END_REF][START_REF] Scott | Effectiveness of radiotherapy for elderly patients with glioblastoma[END_REF]Stupp et al., 2005).

Secondary Glioblastoma

Secondary glioblastoma are also Grade IV tumors but have a histopathological evidence of a precursor low-grade or anaplastic astrocytoma [START_REF] Ohgaki | Genetic pathways to primary and secondary glioblastoma[END_REF]. They are characterized by the presence of IDH1 mutation and comprise 10% of all glioblastoma [START_REF] Ichimura | IDH1 mutations are present in the majority of common adult gliomas but rare in primary glioblastomas[END_REF][START_REF] Mansouri | Molecular Genetics of Secondary Glioblastoma[END_REF]. Secondary GBM belongs to the proneural subtype of GBM (Verhaak et al., 2010).

Epidemiology and pathogenesis

Clinical diagnoses suggest that secondary GBM arise in patients on an average of 17 years younger to those with primary GBM with an average incidence age of 45 years and have a Introduction longer survival compared to IDH1 wildtype GBMs (Ohgaki et al., 2004;[START_REF] Ohgaki | Genetic pathways to primary and secondary glioblastoma[END_REF]. The average time of progression from low grade to glioblastoma is 5 years and from anaplastic glioma to GBM is 2 years (Ohgaki and Kleihues, 2005b). The preferential brain location of incidence is in the frontal lobe as seen for diffuse low grade glioma [START_REF] Lai | Evidence for sequenced molecular evolution of IDH1 mutant glioblastoma from a distinct cell of origin[END_REF] Secondary glioblastoma are more frequently found in females compared to males [START_REF] Ohgaki | The definition of primary and secondary glioblastoma[END_REF].

Macroscopic and Histological features of GBM Histological features of secondary GBM are similar to that of primary glioblastoma. WHO classifies GBMs as mitotic tumors with pseudo palisading cells with microvascular endothelial proliferation, and necrotic regions (Louis et al., 2007;Louis et al., 2016).

Treatment Modalities

Standard treatment for secondary glioblastoma consists of surgery followed by radiotherapy and chemotherapy (Stupp et al., 2005). Only 25% of patients with progressive or recurrent GBM are subjected to surgery [START_REF] Park | Scale to predict survival after surgery for recurrent glioblastoma multiforme[END_REF].

Genetic mutations

Genetic mutations in secondary GBM depend on the precursor lesions from which they originate. Thus they carry P53 and ATRX mutation. While EGFR amplification and PTEN mutations are hallmarks of primary GBMs, secondary GBMs carry P53 mutations [START_REF] Watanabe | Overexpression of the EGF receptor and p53 mutations are mutually exclusive in the evolution of primary and secondary glioblastomas[END_REF]. TERT promoter mutation and LOH of chromosome 10 are commonly observed in both primary and secondary GBMs [START_REF] Eckel-Passow | Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors[END_REF][START_REF] Fujisawa | Loss of heterozygosity on chromosome 10 is more extensive in primary (de novo) than in secondary glioblastomas[END_REF]. One of the specific genetic aberrations identified recurrently in secondary glioblastoma is PTPRZ1-MET gene fusion (15%) (Bao et al., 2014).

Gliomas as presented in the current section, are tumors arising in adults. Each subtype of these tumors has a preferential location and carries their significant hallmark mutations, which in turn carry their respective prognostic effects. Several questions needs to be addressed in the field-which are the possible cell types in the brain that could give rise to There are several evidences published over the years projecting primarily three cellular subtypes in the brain to be involved in the transformation process namely Neural Stem cells (NSCs), OPCs and mature astrocytes (Figure 7). This section focuses on the current understanding of the cellular origins in malignant glioma.

Neural Stem cells as putative cell of origin in glioma

In mammalian CNS, neural stem cells are located in the ventricular zone of embryonic brain and subventricular zone and the subgranular zone of dendate gyrus in adult brain. These are the stem cells that have the properties of both self-renewal and differentiation potential into all three lineages -neurons, astrocytes and oligodendrocytes. The proliferative and regenerative ability make NSCs a potential candidate to be at the origin of glioma.

Cancer stem cells isolated from GBM shares many markers that are normally expressed by NSCs such as Nestin, Cluster of Differentiation 133 (CD133/ Prominin-1), Glial fibrillary acidic protein (GFAP), and SRY (sex determining region Y)-box 2 (SOX2). These cells are able to generate self-renewing spheres in culture and can also differentiate into three lineage cells [START_REF] Bao | Glioma stem cells promote radioresistance by preferential activation of the DNA damage response[END_REF][START_REF] Singh | Identification of human brain tumour initiating cells[END_REF]. The isolated neural stem cells can be genetically modified in vitro and generate tumors in mice when implanted [START_REF] Bachoo | Epidermal growth factor receptor and Ink4a/Arf: convergent mechanisms governing terminal differentiation and transformation along the neural stem cell to astrocyte axis[END_REF][START_REF] Duan | PTEN deficiency reprogrammes human neural stem cells towards a glioblastoma stem cell-like phenotype[END_REF]. Several studies conducted on mouse models by overexpressing oncogenes and or knockdown/ knock out tumor suppressor genes in SVZ of neonatal, embryonic and adult mice using retroviral injections could generate tumors of glioblastoma features [START_REF] Llaguno | Malignant astrocytomas originate from neural stem/progenitor cells in a somatic tumor suppressor mouse model[END_REF][START_REF] Breunig | Ets Factors Regulate Neural Stem Cell Depletion and Gliogenesis in Ras Pathway Glioma[END_REF][START_REF] Zuckermann | Somatic Bibliography CRISPR/Cas9-mediated tumour suppressor disruption enables versatile brain tumour modelling[END_REF]. Lineage-tracing experiments using Genetically Engineered Mouse Models (GEMMs) using hGFAP-Cre, Nestin-Cre or Nestin-Cre ER showed that mouse NSCs are capable of transforming and can generate highgrade glioma upon TP53, Neurofibromatose 1 (NF1) and/or Phosphatase and tensin homolog (PTEN) loss (Alcantara [START_REF] Llaguno | Malignant astrocytomas originate from neural stem/progenitor cells in a somatic tumor suppressor mouse model[END_REF][START_REF] Chen | A restricted cell population propagates glioblastoma growth after chemotherapy[END_REF][START_REF] Zhu | Early inactivation of p53 tumor suppressor gene cooperating with NF1 loss induces malignant astrocytoma[END_REF]. Another evidence suggesting NSCs to be at the glioma origin is the frequent association of GBM close to SVZ region [START_REF] Barami | Relationship of gliomas to the ventricular walls[END_REF]. It has also been shown that NSCs does not require carrying transformation mutations initially to be at the origin of tumor. The physiological Introduction activation of PDGFα signaling in NSCs induced hyperproliferation and cellular hyperplasia and invasion to the surrounding regions resembling low-grade glioma. The hyper-proliferated cells expressed Nestin and Olig2, markers of human glioma. This suggest that increased PDGFRα signaling can indeed activate the proliferation of these cells inducing growth while withdrawal of the PDGFα growth factor resulted in the regression of these glioma-like growth pointing to the potential effect, signaling has on NSCs to make them susceptible to transformation [START_REF] Jackson | PDGFR alpha-positive B cells are neural Bibliography stem cells in the adult SVZ that form glioma-like growths in response to increased PDGF signaling[END_REF]. Whole exome sequencing performed on triple matched samples of 28 patients for TERTp mutations in tumoral mass, tumor-free SVZ and normal cortical tissue identified that GFAP + NSCs in SVZ carry low level of the tumor driver mutations further implying the potential role of NSCs at tumor origin [START_REF] Lee | Human glioblastoma arises from subventricular zone cells with low-level driver mutations[END_REF].

While these evidences demonstrate that NSCs are susceptible to transformation, several issues needs to be understood. Recently, clonal analysis of postnatal NSCs suggest that a single NSC does not divide repeatedly to generate olfactory bulb neurons nor give rise to cortical glial cells and neurons simultaneously raising doubts about considering neural stem cells as defined 'stem cells' in the brain that could accumulate mutations [START_REF] Fuentealba | Embryonic Origin of Postnatal Neural Stem Cells[END_REF].

Secondly, stem cells features could be gained through the de-differentiation process of lineage committed progenitor or mature cells [START_REF] Batlle | Cancer stem cells revisited[END_REF]. Thirdly, the cancer stem cells markers identified as NSC markers are not specific to NSC. For example, nestin can also be expressed by reactive astrocytes [START_REF] Ernst | The putative neural stem cell marker, nestin, is expressed in heterogeneous cell types in the adult rat neocortex[END_REF]. SVZ are a frequent site of spread for GBM and this association co-relates with decreased survival and tumor recurrence [START_REF] Chaichana | Relationship of glioblastoma multiforme to the lateral ventricles predicts survival following tumor resection[END_REF][START_REF] Chen | Glioblastoma recurrence patterns near neural stem cell regions[END_REF][START_REF] Mistry | Decreased survival in glioblastomas is specific to contact with the ventricular-subventricular zone, not subgranular zone or corpus callosum[END_REF]. It is a point of debate whether this stem cell niche could be a site of tumoral origin. But it cannot be neglected that SVZ can function as niche that support tumor growth and thus they migrate towards [START_REF] Qin | Neural Precursor-Derived Pleiotrophin Mediates Subventricular Zone Invasion by Glioma[END_REF].

There are also evidences that suggest that initial genetic insult does not affect the proliferation rate in NSCs. The pre-malignant NSCs can readily differentiate to OPCs that continue to proliferate rapidly and migrate towards cortex to give rise to tumors at distant locations [START_REF] Lee | Human glioblastoma arises from subventricular zone cells with low-level driver mutations[END_REF][START_REF] Liu | Mosaic analysis with double markers reveals tumor cell of origin in glioma[END_REF].

Introduction

Oligodendrocyte progenitor cells (OPC) as glioma cell of origin

Another potential candidate to be at the cell origin of glioma are OPCs. In adult brain, OPC constitute around 5% of the cell population. These cells are proliferative and outnumber NSCs in adult brain making them a potential candidate [START_REF] Dawson | NG2-expressing glial progenitor cells: an abundant and widespread population of cycling cells in the adult rat CNS[END_REF][START_REF] Dimou | Progeny of Olig2expressing progenitors in the gray and white matter of the adult mouse cerebral cortex[END_REF].

OPCs can also differentiate into astrocytes and/or neurons in vivo and can be re-programmed into NSC-like cells in vitro [START_REF] Kondo | Oligodendrocyte precursor cells reprogrammed to become multipotential CNS stem cells[END_REF][START_REF] Richardson | NG2-glia as multipotent neural stem cells: fact or fantasy?[END_REF][START_REF] Rivers | PDGFRA/NG2 glia generate myelinating oligodendrocytes and piriform projection neurons in adult mice[END_REF][START_REF] Zhu | NG2 cells generate both oligodendrocytes and gray matter astrocytes[END_REF]. There are several lines of evidence in the literature, which support the notion that OPCs are at the cellular origin of glioma. First line of evidence comes from the histopathological evidence of glioma samples showing that tumor cells express proteins such as NG2, PDGFRα, OLIG2, O4 that are markers for OPC. NG2 and PDGFRA are expressed by oligodendroglioma as well as in GBM; PDGFRs are overexpressed in malignant astrocytoma. OLIG2 has also been found in diffuse glioma tissues [START_REF] Guha | Proliferation of human malignant astrocytomas is dependent on Ras activation[END_REF][START_REF] Shoshan | Expression of oligodendrocyte progenitor cell antigens by gliomas: implications for the histogenesis of brain tumors[END_REF]) [START_REF] Bouvier | Shared oligodendrocyte lineage gene expression in gliomas and oligodendrocyte progenitor cells[END_REF][START_REF] Chekenya | NG2 precursor cells in neoplasia: functional, histogenesis and therapeutic implications for malignant brain tumours[END_REF][START_REF] Ligon | The oligodendroglial lineage marker OLIG2 is universally expressed in diffuse gliomas[END_REF][START_REF] Lu | Oligodendrocyte lineage genes (OLIG) as molecular markers for human glial brain tumors[END_REF][START_REF] Wade | Proteoglycans and their roles in brain cancer[END_REF]. While most of the these markers are representative of the early stage of lineage of oligodendrocytes, the more mature markers such as MAG are rarely found in oligodendroglioma tissues suggesting that the cells are either blocked in their differentiation process thus retaining the undifferentiated phenotype or the mature cells undergo a dedifferentiation process imparting some proliferative and survival advantages. The classification of glioblastoma based on the molecular signatures revealed that the proneural subtype of GBM have a profile similar to that of OPCs suggesting a possible link between the two (Verhaak et al., 2010). Third, several studies using mouse models showed that glioma could arise from the oligodendrocyte progenitor cells.

PDGF signaling plays an important role in proliferation of OPCs [START_REF] Wolswijk | Cooperation between PDGF and FGF converts slowly dividing O-2Aadult progenitor cells to rapidly dividing cells with characteristics of O-2Aperinatal progenitor cells[END_REF]. Overexpression of PDGFΒ alone or in combination to p53 and pten loss in the white matter of mice brain induced glioma with histological features of glioblastoma. The proliferative glioma cells expressed OPC markers such as NG2 and PDGFRα suggesting the role of OPC in glioma formation. Gene expression analysis comparing the generated murine tumors to human GBMs of different subtypes showed a clustering specific to the proneural subtypes and associated closer to OPCs [START_REF] Assanah | Glial progenitors in adult white matter are driven to form malignant gliomas by plateletderived growth factor-expressing retroviruses[END_REF]) [START_REF] Lei | Glioblastoma models reveal the connection between adult glial progenitors and the proneural phenotype[END_REF]. Additionally, cell specific expression of PDGFB in CNPase positive myelinating OPCs also resulted in oligodendroglioma formation further supporting the transformation capacity of OPC [START_REF] Lindberg | Oligodendrocyte progenitor cells can act as cell of origin for experimental glioma[END_REF]. Constitutive expression of EGFR signaling in subcortical white matter regions of the brain resulted in increased proliferation of the cells and thus hyperplasia. These Introduction EGFR + positive cells expressed OPC markers such as NG2, PDGFRA and OLIG2 markers and maintained an immature state [START_REF] Ivkovic | Constitutive EGFR signaling in oligodendrocyte progenitors leads to diffuse hyperplasia in postnatal white matter[END_REF]. Transgenic mouse model expressing activated EGFR (v-erbB) under the control of S100b promoter; a protein specifically expressed by astrocytes, OPCs and ependymal cells in a p53 deleted background generated oligodendroglioma. There was predominant increase in the number of NG2 + Olig2 + OPC expressing v-erbB [START_REF] Persson | Non-stem cell origin for oligodendroglioma[END_REF][START_REF] Weiss | Genetic determinants of malignancy in a mouse model for oligodendroglioma[END_REF]. NG2 + cells isolated from these tumors were highly tumorigenic and were able to generate secondary tumors even at a low density of 50 cells, while CD15 + NSC cells were not able to generate tumors at a density of 1000 cells [START_REF] Persson | Non-stem cell origin for oligodendroglioma[END_REF]. OPC-specific NG2-Cre or NG2-Cre ERT acquiring p53 and Nf1 mutations can be directly transformed into gliomas resembling proneural subtype of GBM (Alcantara [START_REF] Llaguno | Adult Lineage-Restricted CNS Progenitors Specify Distinct Glioblastoma Subtypes[END_REF][START_REF] Galvao | Transformation of quiescent adult oligodendrocyte precursor cells into malignant glioma through a multistep reactivation process[END_REF][START_REF] Liu | Mosaic analysis with double markers reveals tumor cell of origin in glioma[END_REF].

Astrocytes as cellular origin of glioma

The idea that astrocytes could undergo transformation was based on several observations. For a long time, before the discovery of adult NSCs, astrocytes were thought to be the only proliferating cells in the adult brain [START_REF] Cavanagh | The proliferation of astrocytes around a needle wound in the rat brain[END_REF]. In rodent postnatal cortex, differentiated astrocytes proliferate locally to give rise to mature astrocytes through symmetric division that peaks at 2 weeks postnatal but can be detected even at postnatal 52 days [START_REF] Ge | Local generation of glia is a major astrocyte source in postnatal cortex[END_REF]. Identifying that perivascular astrocytes in adult brain can re-enter cell cycle and undergo extensive proliferation upon brain injuries supported the hypothesis that astrocytes could also be at the cellular origin of glioma [START_REF] Bardehle | Live imaging of astrocyte responses to acute injury reveals selective juxtavascular proliferation[END_REF]. Moreover, glioma tissues strongly expressing astrocytic marker further strengthened the hypothesis [START_REF] Jones | Anaplastic human gliomas grown in athymic mice. Morphology and glial fibrillary acidic protein expression[END_REF]. These observations have prompted scientists to understand the contribution of astrocytes in transformation process. Earlier approaches used primary astrocyte cultures to manipulate genetic aberrations in vitro. Deletion of p16 INKa and p14 ARF in astrocytes and constitutive expression of EGFR dedifferentiated astrocytes to immature cells in culture. These cells when transplanted orthotopically to mice brain induced tumor similar to NSCs. The dedifferentiation process in astrocytes was specific to combined deletion of p16 INKa and P14 ARF and was not reproducible with EGF exposure in p53-deleted mice suggesting the genetic background in the cells determine the phenotype [START_REF] Bachoo | Epidermal growth factor receptor and Ink4a/Arf: convergent mechanisms governing terminal differentiation and transformation along the neural stem cell to astrocyte axis[END_REF].

Similar study on primary astrocytes from day 2 postnatal mice using three common mutations seen in HGG-Pten and p53 deletion and EGFRvIII expression synergized to render astrocytes tumorigenic potential in a reproducible manner [START_REF] Endersby | Nonredundant functions for Akt isoforms in astrocyte growth and gliomagenesis in an orthotopic transplantation model[END_REF]. There are a few additional studies performed on primary astrocytes using various combinations of genetic Introduction variations commonly observed in glioma, also indicate the potential role of astrocytes in gliomagenesis [START_REF] Ghazi | Cell of origin determines tumor phenotype in an oncogenic Ras/p53 knockout transgenic model of high-grade glioma[END_REF][START_REF] Radke | Akt and c-Myc induce stem-cell markers in mature primary p53(-)/(-) astrocytes and render these cells gliomagenic in the brain of immunocompetent mice[END_REF]. But the genetic manipulations in the earlier studies used gfap to drive astrocytic specific mutations. But use of gfap to drive Crerecombinase can results in Cre-mediated recombination in NSCs and their progenies along with GFAP positive astrocytes. This challenge has been overcome partly using Tamoxifen induced GFAP-Cre ER transgene that could be regulated to take into account developmental stage dependent expression of GFAP in specific cell types. Towards this end, tamoxifeninduced GFAP-Cre ER transgene was used to delete Tp53 and Pten in mature mice so as to specifically induce genetic lesions in mature astrocytes [START_REF] Chow | Cooperativity within and among Pten, p53, and Rb pathways induces high-grade astrocytoma in adult brain[END_REF]. But it was also targeted to minor population of NSCs residing in the neurogenic niches. This model generated high-grade astrocytoma mostly in the proliferative niches indicating that the NSCs residing in these regions where primarily affected. However, around 20% of astrocytoma was formed in the non-neurogenic regions of the brain such as cortex, cerebellum and spinal cord with no detectable dissemination of cells from proliferative niches. Two possibilities could explain this context. It could either be through the dedifferentiation and proliferation of mature astrocytes or it is also possible that locally resident progenitor cells be involved in tumor generation [START_REF] Dufour | Astrocytes reverted to a neural progenitor-like state with transforming growth factor alpha are sensitized to cancerous transformation[END_REF][START_REF] Ge | Local generation of glia is a major astrocyte source in postnatal cortex[END_REF][START_REF] Laywell | Identification of a multipotent astrocytic stem cell in the immature and adult mouse brain[END_REF][START_REF] Lee | Isolation of neural stem cells from the postnatal cerebellum[END_REF].

Underlying mutations could be a determining factor in determining whether a cell type could be at the origin of tumors. Inactivation of Retinoblastoma (Rb) in GFAP expressing mature astrocytes in adult brain could lead to their hyperproliferation resulting in a histopathological features similar to grade II astrocytomas. Activation of RAS or PTEN loss alone failed to induce tumor in these cells, while cooperated loss of Rb generated high-grade tumors [START_REF] Song | Evolutionary etiology of high-grade astrocytomas[END_REF]. In another GFAP-Cre ER mouse model using RAS mutation and PTEN deletions, Vitucci et al. observed that murine astrocytes could be transformed into high-grade glioma that resemble human mesenchymal, proneural and neural GBM [START_REF] Vitucci | Genomic profiles of low-grade murine gliomas evolve during progression to glioblastoma[END_REF]. Further validations are required to exclude the possibility of targeting NSCs or OPCs when attempting to manipulate mature astrocytes.

Among these three subpopulations, studies in the recent times strongly points towards OPCs at the cellular origin of glioma at the same time providing evidence why NSCs could not be so. In large-brained mammals such as humans, SVZ neurogenesis decline drastically in the postnatal life and disappears at around 18 months long before glioma arise [START_REF] Lipp | Adult Neurogenesis in Mammals: Variations and Confusions[END_REF][START_REF] Paredes | Brain size and limits to adult neurogenesis[END_REF]. Proliferation of SVZ cells was rarely found in adults. [START_REF] Dennis | Human adult neurogenesis across the ages: An immunohistochemical study[END_REF][START_REF] Wang | Identification and characterization of neuroblasts in the subventricular zone and rostral migratory stream of the adult human brain[END_REF]. When the turn over rates was measured in grey Introduction matter oligodendrocytes, it does not reach a plateau until the fourth decade of life and continue to maintain an annual rate as high as 2.5% [START_REF] Yeung | Dynamics of oligodendrocyte generation and myelination in the human brain[END_REF]. Also, proliferation rate of OPC in epilepsy patients were significantly elevated [START_REF] Geha | NG2+/Olig2+ cells are the major cycle-related cell population of the adult human normal brain[END_REF]. Epilepsy is often associated with glioma patients raising the possibility of contribution of aberrant neuronal activity in OPC proliferation [START_REF] Englot | Epilepsy and brain tumors[END_REF][START_REF] Iuchi | Epilepsy in patients with gliomas: incidence and control of seizures[END_REF]. This hypothesis has been verified further in mice models where artificial enhancement of neuronal activity stimulated the proliferation of normal resident OPC and engrafted GBM cells [START_REF] Gibson | Neuronal activity promotes oligodendrogenesis and adaptive myelination in the mammalian brain[END_REF][START_REF] Venkatesh | Neuronal Activity Promotes Glioma Growth through Neuroligin-3 Secretion[END_REF].

It is possible that a same cell of origin can give rise to GBM with different molecular features while distinct cell types could evolve in parallel to give rise to tumors with similar molecular features. OPCs were initially considered to give rise to oligodendrogliomas and proneural GBMs [START_REF] Galvao | Transformation of quiescent adult oligodendrocyte precursor cells into malignant glioma through a multistep reactivation process[END_REF][START_REF] Lei | Glioblastoma models reveal the connection between adult glial progenitors and the proneural phenotype[END_REF][START_REF] Liu | Mosaic analysis with double markers reveals tumor cell of origin in glioma[END_REF][START_REF] Weiss | Genetic determinants of malignancy in a mouse model for oligodendroglioma[END_REF]. But evidences suggest that OPC can give rise to astrocytoma as well as GBM depending on the initial mutations introduced [START_REF] Bhat | Mesenchymal differentiation mediated by NF-kappaB promotes radiation resistance in glioblastoma[END_REF][START_REF] Carro | The transcriptional network for mesenchymal transformation of brain tumours[END_REF]. For example, removal of Olig2 switches tumors from proneural to classical subtype, or overexpression of TAZ or suppression of NF1 induces mesenchymal GBM [START_REF] Bhat | The transcriptional coactivator TAZ regulates mesenchymal differentiation in malignant glioma[END_REF][START_REF] Lu | Olig2-Dependent Reciprocal Shift in PDGF and EGF Receptor Signaling Regulates Tumor Phenotype and Mitotic Growth in Malignant Glioma[END_REF][START_REF] Ozawa | Most human non-GCIMP glioblastoma subtypes evolve from a common proneural-like precursor glioma[END_REF]. The recurrent GBM also switches their molecular features different from their primary tumors (Kim et al., 2015b;Kim et al., 2015c;[START_REF] Wang | Clonal evolution of glioblastoma under therapy[END_REF]. Thus, molecular features of a particular tumor may not reliably predict the tumor cell origin.

All these studies suggest that cell-specific combination of genetic lesions can potentiate

Molecular heterogeneity

There are largely three major theories explaining the generation of tumor heterogeneity and evolution. Firstly, the Darwinian theory of clonal evolution and natural selection explains that tumor cells acquire genetic variations of which those that attain a proliferative advantage and therapy resistance gets selected leading to tumor progression [START_REF] Nowell | The clonal evolution of tumor cell populations[END_REF]Parker et al., 2015). Within the selected clones there arise sub clones, which differ at genetic and epigenetic level giving rise to tumor heterogeneity. Second is the theory of Cancer Stem Cells (CSC).

These are the subpopulation of cells that acquire the ability to proliferate continuously and give rise to clones with genetic variability generating heterogeneity [START_REF] Cheshier | A NEUROSURGEON'S GUIDE TO STEM CELLS[END_REF][START_REF] Reya | Stem cells, cancer, and cancer stem cells[END_REF]. In addition, these cells also display a great phenotypic plasticity and differentiate into different lineage associated cells, often at metastasized tissues [START_REF] Tang | Understanding cancer stem cell heterogeneity and plasticity[END_REF].

These genetically different clones can have distinct metabolism, therapy resistance, tissue architecture and spatial localization [START_REF] Larjavaara | Incidence of gliomas by anatomic location[END_REF]. A more recent theory of heterogeneity is the interclonal cooperativity in which genetically variable tumor clones cooperate and interact with each other as well as the microenvironment to create a more favorable and sustainable milieu [START_REF] Bonavia | Heterogeneity maintenance in glioblastoma: a social network[END_REF][START_REF] Lyons | Clonal diversity in carcinomas: its implications for tumour progression and the contribution made to it by epithelial-mesenchymal transitions[END_REF][START_REF] Marusyk | Intra-tumour heterogeneity: a looking glass for cancer?[END_REF]. Highly complex tumoral environment comprising of various cellular populations such as immune cells, surrounding reactive astrocytes, blood vessels and factors such as hypoxia, necrosis and microvascular proliferation could feeds back to the tumor cells to enhance their proliferative potential and aggressiveness [START_REF] Calabrese | A perivascular niche for brain tumor stem cells[END_REF]Parker et al., 2015).

Inter and intratumoral heterogeneity is a salient feature of cancer including glioma.

Intertumoral heterogeneity arises due to the differential genetic alterations that occur in individual tumors while intratumoral heterogeneity arises from the cellular heterogeneity.

Understanding the molecular pathways differing in patients is unavoidable in developing effective treatments. Intratumoral diversity creates the major obstacle in the development of effective therapies for glioma. Thus understanding the heterogeneity is of prime importance.

Hallmark genetic alterations in primary glioblastoma include egfr amplification, LOH of 10q resulting in pten deletion, MDM2 overexpression, p16 deletion and tert promoter mutation.

Each mutation can confer specific prognostic significance to the tumors. tert promoter mutations frequently occur in 80% GBM confers worse prognosis [START_REF] Killela | TERT promoter mutations occur frequently in gliomas and a subset of tumors derived from cells with low rates of self-renewal[END_REF][START_REF] Simon | TERT promoter mutations: a novel independent prognostic factor in primary glioblastomas[END_REF]. Meta-analysis on 1074 patients demonstrated that egfr amplification or Introduction mutations is associated with poor prognosis [START_REF] Li | Prognostic significance of epidermal growth factor receptor expression in glioma patients[END_REF]. Single cell sequencing identified different subclones of cells with varying genetic aberrations on egfr within the same tumor [START_REF] Francis | EGFR variant heterogeneity in glioblastoma resolved through single-nucleus sequencing[END_REF]. Subclones expressing EGFRvIII variant remained sensitive to tyrosine kinase inhibitors and were lost during tumor recurrence [START_REF] Van Den Bent | Changes in the EGFR amplification and EGFRvIII expression between paired primary and recurrent glioblastomas[END_REF]. Variations can also occur at the epigenetic levels. Around 40% of GBM contain MGMT hypermethylation, an enzyme that removes alkyl groups from O 6 position of guanine. MGMT hypermethylation results in downregulation of gene expression and improves sensitivity to temozolomide, an alkylating chemotherapeutic agent [START_REF] Esteller | Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents[END_REF]. Receptor tyrosine kinases (RTK) are frequently activated in human GBM. Targeting single RTK through RTK inhibitors results in RTK-switching whereby other RTKs drive tumor growth and maintain active downstream signaling [START_REF] Furnari | Malignant astrocytic glioma: genetics, biology, and paths to treatment[END_REF]. Co-amplification of two RTKs are very rare in single cell and most tumors are composed of heterogeneous groups of cells with amplification on any one RTK forcing for combinatorial therapy (Figure 8) (Szerlip et al., 2012). Gene expression profiling studies done by two independent groups laid the foundation for classification of gliomas based on transcriptional subtypes (Phillips et al., 2006;Verhaak et al., 2010). Integrated genomic profiling of 200 GBMs identified four subtypes of tumorsclassical, proneural, mesenchymal and neural. These subtypes are distinguished based on the signature genetic alterations commonly found in GBM. Classical type contains egfr amplification and INK4a/ARF deletion. Proneural is classified based on pdgfra amplification, tp53 and idh1 mutations. Secondary GBM and low-grade lesions belong to this subtype.

Mesenchymal subtype is more aggressive with high expression of CHI3L1 and MET and strong association of nf1 deletion. Neural subtype contains cells of differentiated phenotype with cellular signatures associated with neurons, astrocytes and oligodendrocytes [START_REF] Verhaak | Cancer Genome Atlas Research Network. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1[END_REF]. In contrast to Verhaak et al., Philips et al. identified three distinct glioblastoma subtypes based on differential gene expression namely, proneural, mesenchymal and proliferative (Phillips et al., 2006). The genes independently identified that are associated to proneural and mesenchymal subtypes were robust. Both the groups identified DLL3 and OLIG2 gene expression associated with proneural class and CHI3L1 and CD44 were associated with mesenchymal subclass and short-term survival. To determine whether genomically different tumor subtypes predict biological and clinical differences, targeted proteomics were performed to segregate tumors based on different signaling pathways [START_REF] Brennan | Glioblastoma subclasses can be defined by activity among signal transduction pathways and associated genomic alterations[END_REF]. Unsupervised clustering of 57 proteins, identified non-overlapping glioma subtypes defined by EGFR, PDGFR signaling and protein associated with nf1 deletion. Interestingly, in PDGF subtype tumors, PDGF protein was highly expressed but no Introduction somatic copy number alteration in pdgf gene and low PDGF mRNA expression were observed. Moreover, EGFR-subtype tumors were associated with active Notch signaling that did not reflect in copy number, sequencing or expression. Thus regulations of signaling and molecular pathways in glioma can be highly layered and may not be evident from single omics analysis.

There are evidences that tumors can shift their subtype depending on the cues they receive.

For example, upon recurrence proneural tumors switch to aggressive mesenchymal phenotype expressing signature proteins such as chitinase 3-like 1 (CHI3L1 or YKL40), CD44 and STAT3 (Phillips et al., 2006). Further adding to the complexity of the disease, it has been more evident that tumors have intra-tumoral heterogeneity with multiple molecular subtypes [START_REF] Sottoriva | Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics[END_REF]. Heterogeneity also exists in a temporal manner where selective pressure results in expansion or regression of specific tumor cell subpopulation [START_REF] Nickel | Characterizing mutational heterogeneity in a glioblastoma patient with double recurrence[END_REF].

Heterogeneity in glioma seems to be the crux of the problem in achieving effective treatment modality. When heterogeneity per se becomes challenging, transition of cellular states and subtypes worsen the situation. It is necessary to identify the underlying factors and signaling factors involved in the generation of heterogeneity. Inducing or blocking cells in a specific cellular state and developing the drugs that target those cells could be a way to abolish tumors to a larger extend.

Introduction

Cellular heterogeneity

Cellular heterogeneity in primary glioblastoma is evidently manifested in the field in comparison to DLGG. Cellular heterogeneity is widely understood through the cancer stem cell model that identifies subpopulation of cells with stem cell features such as self-renewal and ability to differentiate to multiple cell types, as tumor initiating cells that can recapitulate tumoral heterogeneity when injected orthotopically into mice [START_REF] Singh | Identification of a cancer stem cell in human brain tumors[END_REF][START_REF] Singh | Identification of human brain tumour initiating cells[END_REF]. Thus tumor mass is composed of cells at different developmental states differing in their proliferative and differentiative capabilities and resistance to therapy. Such a subpopulations of stem like cells called glioma stem cells (GSC) are identified in GBM.

These play important role in mediating therapeutic resistance to radiotherapy and chemotherapy [START_REF] Bao | Glioma stem cells promote radioresistance by preferential activation of the DNA damage response[END_REF]Liu et al., 2006a), tumor recurrence [START_REF] Chen | A restricted cell population propagates glioblastoma growth after chemotherapy[END_REF], angiogenesis [START_REF] Cheng | Glioblastoma stem cells generate vascular pericytes to support vessel function and tumor growth[END_REF] and invasion [START_REF] Wakimoto | Human glioblastoma-derived cancer stem cells: establishment of invasive glioma models and treatment with oncolytic herpes simplex virus vectors[END_REF]. GSCs do not provide information on the tumoral cell of origin. While proliferating stem cells or progenitor cells are more susceptible to transformation we cannot exclude the possibility of differentiated cells gaining access to stemness pathway through genetic aberrations (Friedmann-Morvinski, 2014).

Great efforts have been employed to characterize markers expressed by the glioma stem cells to isolate and perform functional studies. Most of these markers are originally identified as markers of neural stem cells including NESTIN, SOX2, OLIG2, MYC and NANOG [START_REF] Ben-Porath | An embryonic stem cell-like gene expression signature in poorly differentiated aggressive human tumors[END_REF][START_REF] Kim | A Myc network accounts for similarities between embryonic stem and cancer cell transcription programs[END_REF][START_REF] Ligon | Olig2-regulated lineage-restricted pathway controls replication competence in neural stem cells and malignant glioma[END_REF][START_REF] Tunici | Genetic alterations and in vivo tumorigenicity of neurospheres derived from an adult glioblastoma[END_REF]. To isolate these specific cellular subpopulations from tumor masses, several cell surface markers are also extensively in use such as CD133, CD15, CD44, L1CAM, A2B5 [START_REF] Brescia | Current strategies for identification of glioma stem cells: adequate or unsatisfactory?[END_REF] [START_REF] Bao | Targeting cancer stem cells through L1CAM suppresses glioma growth[END_REF][START_REF] Beier | CD133(+) and CD133(-) glioblastomaderived cancer stem cells show differential growth characteristics and molecular profiles[END_REF][START_REF] Tchoghandjian | A2B5 cells from human glioblastoma have cancer stem cell properties[END_REF] [START_REF] Ogden | Identification of A2B5+CD133-tumorinitiating cells in adult human gliomas[END_REF]. But none of the so far identified markers represent an ideal marker for all GSCs. The cellular states of GSCs are highly dynamic in nature. Due to their plasticity, the cells interconvert between GSC and non-GSC states [START_REF] Safa | Glioblastoma stem cells (GSCs) epigenetic plasticity and interconversion between differentiated non-GSCs and GSCs[END_REF]. They can be regulated through various intrinsic and extrinsic factors such as genetic, epigenetic, metabolic, cell signaling, cell-cell interactions and microenvironmental cues such as hypoxia, nutrient deprivation, radiation etc. [START_REF] Gimple | Glioblastoma stem cells: lessons from the tumor hierarchy in a lethal cancer[END_REF]. A very recent study suggest that phenotypic heterogeneity does not exist in a hierarchical manner and the stemness results from the intrinsic cellular plasticity (Dirkse et al., 2019). All GBM subpopulations in culture maintained stemness and tumorigenecity and reverted back and forth to any phenotypic state depending on the environmental cues (Dirkse et al., 2019).

Introduction

Several players are identified that regulate GSCs at the epigenetic level. Global methylation profiling on primary and recurrent GBMs, identified transcriptional subtypes, intracellular heterogeneity of tumor cells and immune cells [START_REF] Klughammer | The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space[END_REF]. Glioma subtypes are also spatially regulated. In vascular regions of tumor, EZH2, a PRC2 epigenetic regulator predominates and drives proneural-like transcription profile, while in nutrient-deprived necrotic areas BMI1 signaling drives mesenchymal signatures [START_REF] Jin | Targeting glioma stem cells through combined BMI1 and EZH2 inhibition[END_REF]. When GSCs are treated with Notch inhibitors, ASCL1 reorganize chromatin to drive neuronal differentiation of cells and suppress tumorigenecity [START_REF] Park | ASCL1 Reorganizes Chromatin to Direct Neuronal Fate and Suppress Tumorigenicity of Glioblastoma Stem Cells[END_REF]. Oncogenes and tumor suppressors also functions to shape the epigenome. EGFRvIII activation overexpresses SOX9 and FOXG1 activating proliferative programs (Liu et al., 2015a). SOX2, OLIG2 and ZEB1 transform astrocytes to tumor initiating cells even in the absence of driver mutations [START_REF] Singh | Oncogenes Activate an Autonomous Transcriptional Regulatory Circuit That Drives Glioblastoma[END_REF].

Studies have also focused on understanding metabolic heterogeneity in glioma. The high demand on energy metabolites in rapidly proliferating cells are accommodated through upregulation of glucose transporters such as GLUT3, which is in turn used for nucleotide biosynthesis. [START_REF] Cosset | Glut3 Addiction Is a Druggable Vulnerability for a Molecularly Defined Subpopulation of Glioblastoma[END_REF][START_REF] Flavahan | Brain tumor initiating cells adapt to restricted nutrition through preferential glucose uptake[END_REF]. Glioblastomas rely on acetyl-CoA synthetase namely ACSS2 to convert acetate to acetyl-CoA and can also promote lipid biosynthesis under nutrient deprivation or hypoxia [START_REF] Gao | Acetate functions as an epigenetic metabolite to promote lipid synthesis under hypoxia[END_REF][START_REF] Mashimo | Acetate is a bioenergetic substrate for human glioblastoma and brain metastases[END_REF].

Under conditions of stress, AMP-kinase (AMPK) regulates glycolysis and mitochondrial metabolism [START_REF] Chhipa | AMP kinase promotes glioblastoma bioenergetics and tumour growth[END_REF]. GSCs upregulate serine metabolism enzyme SHMT2 to inhibit pyruvate kinase and limit oxygen consumption (Kim et al., 2015a). Metabolic heterogeneity is identified in GBMs, where fast-cycling cells are dependent on anaerobic glycolysis and slow-cycling cells prefer oxidative phosphorylation and lipid oxidation [START_REF] Hoang-Minh | Infiltrative and drugresistant slow-cycling cells support metabolic heterogeneity in glioblastoma[END_REF]. EGFR-driven glioma showed higher dependence on lipid metabolism and fatty acid synthesis upregulating, SREBP-1, a master regulator of lipogenesis [START_REF] Guo | EGFR signaling through an Akt-SREBP-1dependent, rapamycin-resistant pathway sensitizes glioblastomas to antilipogenic therapy[END_REF].

GSCs are easily adaptable to its microenvironmental changes. Interactions of GSCs with various stromal cells are quite well studied. Several factors and molecules are identified mediating these interactions. The interactions with blood vessels, immune cells and neurons are also essential for their GSC maintenance. OLIG2 + oligodendrocyte precursor-like glioma cells invade by single-cell vessel option through activation of Wnt7b expression [START_REF] Griveau | A Glial Signature and Wnt7 Signaling Regulate Glioma-Vascular Interactions and Tumor Microenvironment[END_REF]. While VEGF promotes angiogenesis, its inhibition can drive glioma cells to acquire a more aggressive mesenchymal phenotype (Lu et al., 2012b). Osteopontin in Introduction perivascular niche can promote glioma survival and aggressiveness through the activation of CD44-HIF2a signaling pathway [START_REF] Pietras | Osteopontin-CD44 signaling in the glioma perivascular niche enhances cancer stem cell phenotypes and promotes aggressive tumor growth[END_REF]. Under hypoxic conditions, vasorin gets upregulated and interact with Notch to help maintain its stemness [START_REF] Man | Hypoxic Induction of Vasorin Regulates Notch1 Turnover to Maintain Glioma Stem-like Cells[END_REF].

In addition to their interaction with microenvironment, GSCs also possess the ability to transdifferentiate to vascular pericytes or endothelial cells to remodel blood vessels (Guichet et al., 2015;[START_REF] Ricci-Vitiani | Tumour vascularization via endothelial differentiation of glioblastoma stem-like cells[END_REF][START_REF] Wang | Glioblastoma stem-like cells give rise to tumour endothelium[END_REF]. GSC-derived pericytes involve in maintaining the blood-tumor barrier integrity through TGF-β and BMX tyrosine kinase activity, while GSC-derived endothelial cells rely on WNT5A signaling in maintaining the endothelial phenotypes [START_REF] Cheng | Glioblastoma stem cells generate vascular pericytes to support vessel function and tumor growth[END_REF][START_REF] Hu | Epigenetic Activation of WNT5A Drives Glioblastoma Stem Cell Differentiation and Invasive Growth[END_REF][START_REF] Zhou | Targeting Glioma Stem Cell-Derived Pericytes Disrupts the Blood-Tumor Barrier and Improves Chemotherapeutic Efficacy[END_REF].

Signals from neurons are also identified critical for GSC maintenance. Modulation of dopaminergic, cholinergic and serotonergic pathways affected the glioblastoma neural stem cells (GNS) and specifically, inhibition of dopaminergic receptor DRD4 selectively inhibited GNS growth leading to cell cycle arrest and apoptosis [START_REF] Dolma | Inhibition of Dopamine Receptor D4 Impedes Autophagic Flux, Proliferation, and Survival of Glioblastoma Stem Cells[END_REF]. Jagged, a NOTCH ligand expressed on the axons provides a migratory route to GSC to invade along the white matter tracts through upregulation of SOX9 and SOX2 [START_REF] Wang | Invasion of white matter tracts by glioma stem cells is regulated by a NOTCH1-SOX2 positive-feedback loop[END_REF].

Another important subset of cells adding to tumor microenvironmental diversity is immune cells. Tumor-associated macrophages (TAMs) constitute around 30-40% of cells in GBM [START_REF] Charles | The brain tumor microenvironment[END_REF]. The cellular constituents have an association to tumor subtype.

Enrichment of immune response-related genes was identified in mesenchymal subtype of GBM and was related to nf1 deletion in this subtype [START_REF] Engler | Increased microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas[END_REF][START_REF] Wang | Tumor Evolution of Glioma-Intrinsic Gene Expression Subtypes Associates with Immunological Changes in the Microenvironment[END_REF].

The proangiogenic and inflamed microenvironment results in leaky blood-brain barrier, which give access to leukocytes to infiltrate tumor mass [START_REF] Chen | Immune Microenvironment in Glioblastoma Subtypes[END_REF]. T cells account for the most infiltrated lymphoid cells in GBM and are identified with an immunosuppressed phenotype [START_REF] Han | Rescuing defective tumor-infiltrating T-cell proliferation in glioblastoma patients[END_REF]. GBM cells secrete CCL22 that recruits T reg cells to the tumor microenvironment, another reason for immunosuppression [START_REF] Crane | Soluble factors secreted by glioblastoma cell lines facilitate recruitment, survival, and expansion of regulatory T cells: implications for immunotherapy[END_REF]. TAMs comprise of resident microglia and bone marrow-derived monocytes.

Infiltrating monocytes undergo transformation to mature macrophages in situ following homing to the tumor regions [START_REF] Dal-Secco | A dynamic spectrum of monocytes arising from the in situ reprogramming of CCR2+ monocytes at a site of sterile injury[END_REF]. Using PDGFB-driven GBM GEMMs, a study have shown that majority of TAMs are infiltrated bone marrow derived monocytes/macrophages preferentially locating to the perivascular regions while resident macrophages are found in peritumoral regions [START_REF] Chen | Cellular and Molecular Identity of Tumor-Associated Macrophages in Glioblastoma[END_REF]. Bone marrow derived monocytes secrete IL-1β promoting cell proliferation in GSCs [START_REF] Feng | Loss of CX3CR1 increases accumulation of inflammatory monocytes and promotes gliomagenesis[END_REF]. TAMs are highly plastic cells that can interconvert between pro-inflammatory M1 and anti-inflammatory Introduction M2 phenotypes. GBMs host both subtypes of macrophages. Attempts are being made to polarize TAMs to M1 fate and remains challenging to succeed as soluble factors such as TGF-β released by tumor cells can revert them back to M2 phenotype that sustain tumor growth [START_REF] Wang | Molecular mechanisms that influence the macrophage m1-m2 polarization balance[END_REF][START_REF] Wu | Glioma cancer stem cells induce immunosuppressive macrophages/microglia[END_REF].

Thus primary glioblastoma still remains a notorious foe challenging the life of patients and the scientific community equally. It appears that the glioblastoma cells develop its own ecosystem within human brain to sustain the growth and survival. As they are highly heterogenic and plastic at the same time, treatments should be aimed at targeting multiple cell types within the tumor microenvironment. Cellular plasticity lies at the foundation of the heterogeneous nature of any cancer including glioma. Researches should focus on identifying factors and molecules and signaling pathways imparting plasticity to cells.

Introduction

Heterogeneity in diffuse low grade glioma 1.5.2.1. Genetic Heterogeneity

The primary line of evidence for heterogeneity lies in the underlying genetic mutations that tumor cells carry. The hallmarks mutations of astrocytoma and oligodendroglioma have made its way to the latest classification system of glioma in 2016. Gliomas with IDH1/2 mutations had astrocytic morphologies but when expressed along with TERT mutations had oligodendroglial morphologies [START_REF] Killela | Mutations in IDH1, IDH2, and in the TERT promoter define clinically distinct subgroups of adult malignant gliomas[END_REF]. Gliomas with TERT mutations alone had the aggressive tumor phenotype with grade IV tumors and were found in oldest age group with poor survival benefits. Gliomas with TERT and IDH1 mutations were almost always carried 1p/19q co-deletions. Triple negative gliomas developed grade IV tumors mostly in younger patients in comparison to group with TERT mutation alone [START_REF] Eckel-Passow | Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors[END_REF]. IDH1 mutated DLGGs predominantly occupied the front lobe of the brain suggesting of preferential localization of these tumors. Somatic mutations and copy number variations have a negative prognosis on these tumors. Several other mutations were found to be associated with the subtypes. NOTCH1 mutations in IDH1 mut /1p/19q co-deleted oligodendroglioma have a favorable prognosis while PIK3R1 and Retinoblastoma pathway genes in IDH1mut astrocytoma have poor prognostic effect and reduced overall survival [START_REF] Aoki | Prognostic relevance of genetic alterations in diffuse lower-grade gliomas[END_REF]Suzuki et al., 2015).

Cellular subtypes: Insights from single cell approaches

Earlier studies based on electron microscopy (Baloyannis, 1981) and immunohistochemistry of DLGGs (Liang et al., 2005;Rousseau et al., 2006) have demonstrated that there exists a phenotypic heterogeneity within tumoral cells. For instance, in oligodendrogliomas, subpopulations of gliofibrillary oligodendrocytes have been identified (Herpers and Budka, 1984;Kros et al., 1996;Matyja et al., 2001). Recently, our knowledge on tumoral Single cell RNA sequencing performed on grade II oligodendroglioma with IDH1 or IDH2 mutations and 1p/1q co-deleted tumors suggested a developmental hierarchy (Tirosh et al., 2016). They observed that bulk tumor tissue was composed of differentiated astrocytes and oligodendrocytes that does not proliferate along with a minor population of undifferentiated cycling cells who had an expression profile similar to neural progenitor cells and neural stem cells suggesting that cancer cells of origin could be NSC rather than OPC (Tirosh et al., 2016). Interestingly, such a similar cellular composition and hierarchy was also observed in grade II IDH1 mutated astrocytoma (Figure 9) implying that DLGG astrocytoma and oligodendroglioma could arise from a single cell of origin and follow a similar pattern of tumor development and the phenotypic differences arise from the different genetic lesions that both tumor subtypes carry. They observed that almost half of bulk differences in expression patterns observed in TCGA samples primarily comes from the genetic variations that in turn affects the phenotypes and tumor microenvironment (Venteicher et al., 2017). The biology of glioma is highly influenced by the tumor microenvironment and their interactions. In oligodendroglioma, the non-malignant cells are mostly composed of mature oligodendrocytes and microglia (Tirosh et al., 2016). With the increase in the aggressiveness of tumor and clinical grade, the scRNA-seq revealed a shift in the transcriptional states of immune cells from resident microglia state to infiltrating macrophages that also closely associate with endothelial program (Venteicher et al., 2017) Introduction including brain. These were able to generate more colonies in soft agar assays compared to CD24 -cells, suggesting its clonogenicity. Gene enrichment analysis identified positive enrichment of MYC targets, WNT signaling, cholesterol biosynthesis and embryonic stem cell pathways, suggesting a stem cell program in these cells. In LGGs, CD24 expression was associated with CIMP + gliomas. Extensive studies are required on these cell population to identify its potential role in gliomagenesis and progression [START_REF] Turcan | Mutant-IDH1-dependent chromatin state reprogramming, reversibility, and persistence[END_REF].

Introduction

1.5.2.3.
Differences in metabolism 1.5.2.3.1. IDH

in a normal cell's metabolism

Isocitrate dehydrogenase is one of the crucial proteins in mediating the metabolic needs of the cells in various tissues including liver, heart muscles and skeletal muscles [START_REF] Laporte | Phosphorylation of isocitrate dehydrogenase as a demonstration of enhanced sensitivity in covalent regulation[END_REF]. It is involved in a wide variety of basic metabolic processes including and not confined to regulating glutamine metabolism, mitochondrial oxidative phosphorylation and lipogenesis [START_REF] Reitman | Isocitrate dehydrogenase 1 and 2 mutations in cancer: alterations at a crossroads of cellular metabolism[END_REF]. It has been also known to participate in glucose sensing and in regulating cellular redox status. The IDH family comprises three isozymes:

Nicotinamide adenine dinucleotide phosphate (NADP) -dependent IDH (IDH1 and IDH2) and

Nicotinamide adenine dinucleotide (NAD) -dependent IDH (IDH3) [START_REF] Yen | Cancer-associated IDH mutations: biomarker and therapeutic opportunities[END_REF]. Of these enzymes, IDH1 is localized in the cytoplasm and peroxisomes and controls the antioxidant system and stimulates lipid synthesis. IDH2 and IDH3 are present in the mitochondria, where they play a key role in regulating tricarboxylic acid (TCA) or Krebs cycle and thus, are implicated in energy metabolism in the cells. TCA cycle is an evolutionarily conserved pathway occurring in the mitochondria for the generation of ATP.

The NADH and NADPH synthesized during the reaction are used in the electron transport chain for ATP production. Besides ATP synthesis, TCA cycle also provides substrates for lipid biosynthesis and amino acid synthesis [START_REF] Maus | Glutamate and alpha-ketoglutarate: key players in glioma metabolism[END_REF].

One of the primary functions of IDH is to catalyze the oxidative decarboxylation of isocitrate to alpha-ketoglutarate (aKG), which is an important metabolite of TCA cycle to reduce the NAD to NADH in the mitochondria and NADP to NADPH in cytoplasm. NADPH is an important reducing factor in regulating cellular defense response against oxidative damage [START_REF] Biaglow | The thioredoxin reductase/thioredoxin system: novel redox targets for cancer therapy[END_REF] and for lipid synthesis [START_REF] Bogdanovic | IDH1, lipid metabolism and cancer: Shedding new light on old ideas[END_REF][START_REF] Shechter | IDH1 gene transcription is sterol regulated and activated by SREBP-1a and SREBP-2 in human hepatoma HepG2 cells: evidence that IDH1 may regulate lipogenesis in hepatic cells[END_REF].

Further, it is also an essential player in formation of activated catalase, an anti-oxidant enzyme [START_REF] Kirkman | Mechanisms of protection of catalase by NADPH. Kinetics and stoichiometry[END_REF].

Owing to the plethora of important functions mediated by IDH in maintaining the cellular homeostasis, it is conceivable that loss or reduction of IDH proteins results in impairment of several detoxification mechanisms. These perturbed cellular mechanisms results in accumulation of DNA damage and genome instability, which eventually results in formation of tumors.

IDH and metabolic differences in glioma

As IDH is involved in a critical metabolic pathway, mutation on it has profound effects on the metabolism of the glioma cells. The mutated IDH acquires a neomorphic function of Introduction converting aKG to D2HG using NADPH cofactor, thus reducing its availability (Dang et al., 2009). Besides that, the availability of aKG in cells is reduced, which is required for the functioning of TCA cycle. Also, in normal conditions aKG undergoes reverse conversion to citrate and further to acetyl-CoA that forms the substrate for lipid synthesis [START_REF] Filipp | Reverse TCA cycle flux through isocitrate dehydrogenases 1 and 2 is required for lipogenesis in hypoxic melanoma cells[END_REF]. These processes get malfunctioned in IDH mutated glioma. Metabolomic profiling of human oligodendroglioma cells expressing mutant IDH1 and IDH2 showed altered levels of TCA metabolites, free amino acids and glutathione metabolites [START_REF] Reitman | Profiling the effects of isocitrate dehydrogenase 1 and 2 mutations on the cellular metabolome[END_REF]. To maintain the levels of critical metabolites in the cells, tumor cells adopt to various metabolic changes. In cells, glucose and glutamate are two major sources of nutrients. In hypoxic conditions, HIF-1α inhibits the activity of pyruvate dehydrogenase enzyme preventing the entry of glucose-derived metabolites to the TCA cycle [START_REF] Kim | HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia[END_REF]. This makes cells more dependent on glutamate for carbon source of TCA metabolites. It has been shown that IDH1 mutated cells had significantly lower levels of glutamine and glutamate relative to wild type IDH1 cells while maintaining TCA metabolite levels [START_REF] Ohka | Quantitative metabolome analysis profiles activation of glutaminolysis in glioma with IDH1 mutation[END_REF]. This suggest that IDH1 mutated cells increases glutaminolysis to generate glutamate from glutamine which further gets converted to aKG to replenish the substrate (Waitkus et al., 2016). In support of this, it has been shown that glioma cells are highly sensitive to the inhibition of enzymes involved in the above-mentioned reactions, which are glutaminase (GLS) and glutamate dehydrogenase (GDH) [START_REF] Seltzer | Inhibition of glutaminase preferentially slows growth of glioma cells with mutant IDH1[END_REF]) (Figure 10). Also, mRNA levels of GDH1 and GDH2 were found to be significantly increased in IDH1 mutated GBM [START_REF] Chen | Hominoid-specific enzyme GLUD2 promotes growth of IDH1R132H glioma[END_REF].

As αKG get converted to D-2HG, the reverse conversion of aKG to citrate is reduced lowering the level of citrate in these cells. Citrate is required for the synthesis of acetyl-CoA, which is the key metabolite for fatty acid synthesis. Lower citrate implies lower acetyl-CoA, thus IDH mutations leads to altered levels of sphingolipids or phospholipids (Waitkus et al., 2016). NAPDH is the cofactor involved in the synthesis of Glutathione (GSH), the antagonist of Reactive Oxygen Species (ROS). As NAPDH reservoirs are lowered in tumor cells, GSH coupled enzymes levels get reduced, which could make the cells more susceptible to ROS production and thus apoptosis. Sensitivity of IDH mutated cells to treatments methods could be an indirect effect of the altered metabolism (Waitkus et al., 2016). Furthermore, D2HG is found to inhibit ATP synthase thus reducing ATP levels and mitochondrial respiration (Fu et al., 2015).

Introduction

Another important signaling regulating the metabolism is mammalian target of rapamycin (mTOR) pathway. Phosphoinositide 3-kinase, (PI3K)/ mTOR signaling is known to control cell survival, proliferation and apoptosis [START_REF] Laplante | mTOR signaling in growth control and disease[END_REF][START_REF] Mayer | The PI3K/AKT Pathway as a Target for Cancer Treatment[END_REF][START_REF] Porta | Targeting PI3K/Akt/mTOR Signaling in Cancer[END_REF]. Activation of this pathway is often observed in LGG and secondary GBM resulting from the upregulation of PDGF signaling or inactivation of PTEN [START_REF] Flavahan | Insulator dysfunction and oncogene activation in IDH mutant gliomas[END_REF][START_REF] Wakimoto | Targetable signaling pathway mutations are associated with malignant phenotype in IDH-mutant gliomas[END_REF][START_REF] Wiencke | Methylation of the PTEN promoter defines low-grade gliomas and secondary glioblastoma[END_REF]. It has also been reported that D2HG activate mTORC1/mTORC2 [START_REF] Carbonneau | The oncometabolite 2-hydroxyglutarate activates the mTOR signalling pathway[END_REF]. While AKT dependent mTORC1 is mostly associated to cell growth and survival, the second complex mTORC2 is known to act as glucose sensor in GBM. In glucose-rich conditions, mTORC2 gets activated through the acetylation of Rictor protein, the main component of the complex via Acetyl-coA [START_REF] Masui | Glucose-dependent acetylation of Rictor promotes targeted cancer therapy resistance[END_REF]. The activated mTORC2 inhibits the activity of cysteine-glutamate antiporter implicating its role as amino acid sensor. Under low-nutrient conditions, lower mTORC2 signaling activates the transporter to uptake cysteine for glutathione synthesis and thus protects cells from metabolic stress [START_REF] Gu | mTORC2 Regulates Amino Acid Metabolism in Cancer by Phosphorylation of the Cystine-Glutamate Antiporter xCT[END_REF]. A recent paper showed that, IDH1 mutated cells activates mTORC2 complex to enhance endocytosis for nutrient internalization [START_REF] Liu | mTORC2/Rac1 Pathway Predisposes Cancer Aggressiveness in IDH1-Mutated Glioma[END_REF].

Epigenetics

As the oncometabolite produced by the IDH mutated protein is structurally similar to aKG, it functions as a competitive inhibitor interfering with the functions of aKG dependent processes [START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. aKG act as a co-substrate for many dioxygenases involved in demethylation.

D2HG is shown to interfere with both histone demethylases and DNA demethylases [START_REF] Chowdhury | The oncometabolite 2-hydroxyglutarate inhibits histone lysine demethylases[END_REF]. D2HG primarily inhibits Jumonji family of histone demethylases,

where it has been shown that administration of cell permeable D2HG in U87MG GBM cells increased H3K9 and K3K79 methylation [START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. Also, overexpression of IDH1R132H or IDH2R172K expression on immortalized human astrocytes could increase H3K9 and H3K27 trimethylation (Lu et al., 2012a). Another phenotype observed in IDH1 mutated glioma is hyper methylated phenotype known as G-CIMP (CpG island methylation phenotype). IDH1R132H mutation was sufficient to generate this phenotype in human astrocytes suggesting the G-CIMP observed in grade II/III gliomas is primarily via this mutation [START_REF] Guan | Molecular subtypes of glioblastoma are relevant to lower grade glioma[END_REF][START_REF] Lai | Evidence for sequenced molecular evolution of IDH1 mutant glioblastoma from a distinct cell of origin[END_REF]Turcan et al., 2012). This is due to the inhibition of aKG dependent DNA demethylases by D2HG. It has been observed that D2HG inhibits the function of Ten-Eleven Tanslocation (TET) family of 5-methylcytosine hydroxylases leading to DNA hypermethylation [START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. The TET family of enzymes functions by Introduction converting 5-methylcytosine to unmethylated form through 5-hydroxymethylcytosine (5-hmC) intermediate [START_REF] Kohli | TET enzymes, TDG and the dynamics of DNA demethylation[END_REF]. Using heterozygous IDH1 mutated knock-in mouse model, it has been demonstrated that expression of IDH1 mutated protein in neural stem cells is sufficient to reduce 5-hmC levels [START_REF] Sasaki | D-2-hydroxyglutarate produced by mutant IDH1 perturbs collagen maturation and basement membrane function[END_REF]. Also, it is observed that 5-hmC levels are lower in IDH1 mutated glioma compared to IDH1 wild type glioma [START_REF] Xu | Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of alphaketoglutarate-dependent dioxygenases[END_REF]. Thus IDH1 is majorly involved in the tumorigenesis process through epigenetic regulation.

Epigenetic changes through IDH1 mutation inhibit the differentiation of the cells imparting tumor cells an undifferentiated phenotype (Lu et al., 2012a). The repressive histone methylation prevents the activation of astrocytic lineage markers (may be also of oligodendrocytic lineage markers) inhibiting differentiation. Inhibition of IDH1 mutated protein, induced differentiation of neural stem cells and slowed the growth of tumors in mice models [START_REF] Rohle | An inhibitor of mutant IDH1 delays growth and promotes differentiation of glioma cells[END_REF].

Recently, studies have focused on understanding the role of IDH1 mutation on chromosome structure. The genome is organized into topologically associated domains (TAD) that are selfinteracting. CCCTC-binding factor (CTCF) acts as insulators preventing interactions between TADs that helps in insulating gene in one domain from activation by an enhancer located in the neighbouring domain. Comparing the 3D DNA structure in, patient derived cultures or cells bearing wild type IDH or IDH1R132H, it has been shown that hyper methylation prevents the binding of CTCF to the DNA thereby activating new sets of genes possibly involved in tumorigenesis. Based on the model they proposed that loss of domain boundary between the constitutive enhancer upstream of FIP1L1 gene and PDGFRΑ induces its aberrant expression up to 5 fold [START_REF] Flavahan | Insulator dysfunction and oncogene activation in IDH mutant gliomas[END_REF]. Using a mouse model to generate low-grade astrocytoma by introducing IDH1R132H mutation along with P53 and ATRX silencing, the study proposes that in control mice, CTCF binding brings a downstream enhancer closer to the SOX2 promoter by forming a DNA loop thus activating its expression.

This interaction is lost in glioma model due to the loss of CTCF binding results in loss of SOX2 expression in cells blocking their differentiation [START_REF] Modrek | Low-Grade Astrocytoma Mutations in IDH1, P53, and ATRX Cooperate to Block Differentiation of Human Neural Stem Cells via Repression of SOX2[END_REF].

IDH mutations could also have a direct influence on mRNA in cells. N 6 -adenosine methylation (m 6 A) is a post-transcriptional modification on the mRNA controlling RNA splicing, stability, export and translation. This methylation is catalyzed by RNA methyltransferase complex such as METTL3, METTL14 etc. and is reversed by 2 aKG dependent dioxygenases, FTO (fat mass and obesity associated protein) and ALKBH5 (L et Introduction al., 2017). In the context of AML (acute myeloid leukemia), it has been reported that D2HG inhibits the function of FTO and results in global increase of m 6 A markers on mRNA resulting in the degradation of transcripts involved in cellular growth. This paper indicated the tumor suppressor role of D2HG in AML [START_REF] Su | R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m(6)A/MYC/CEBPA Signaling[END_REF]. Further studies are required to understand a similar tumor suppressive role of D2HG in IDH1 mutated glioma.

Epigenetics also plays an important role in defining the phenotypes of the tumor cells during recurrence. Based on the DNA methylation status, IDH1 mutated gliomas has been divided into three major subtypes-co-deleted (1p/19q co-deleted), non-codeleted G-CIMP high and G-CIMP low (Ceccarelli et al., 2016). Comprehensive DNA methylation longitudinal analysis of IDH1 mutated and wild type primary and first recurrence tumors exhibited methylation shift in a subset of G-CIMP high non co-deleted tumors upon recurrence. They observed that upon recurrence around 17% of IDH1 mutated LGG G-CIMP high tumors shifted to G-CIMP low phenotype tumors upon recurrence, which shared epigenetic features with worst prognostic IDH1 wildtype GBM. It also revealed hypo-methylation on STAT3 DNA motif gene, a master regulator of mesenchymal transition, the aggressive phenotype. Several transcription factor binding DNA motifs were also hypomethylated suggesting their activation. Of these, significant alterations were observed on SOX and c-Jun/AP-1 (activating protein-1) transcription factors binding motifs [START_REF] De Souza | A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence[END_REF]. AP-1 is involved in cellular proliferation, transformation and apoptosis [START_REF] Shaulian | AP-1 as a regulator of cell life and death[END_REF]. The role of AP-1 in tumor progression seems to be coherent as chromatin accessibility mapping performed on IDH co-deleted and non co-deleted tumors by an independent group also observed open chromatin accessibility in IDH non-co-deleted subtype than co-deleted subtype revealing epigenetic heterogeneity among grade II diffuse glioma. This study also revealed heterogeneity in methylation of long non-coding RNA named CYTOR among these subtypes, which was also hypo-methylated in non co-deleted subtype [START_REF] Al-Ali | Single-nucleus chromatin accessibility reveals intratumoral epigenetic heterogeneity in IDH1 mutant gliomas[END_REF]. CYTOR has been implicated in various cancers and is upregulated in diffuse glioma and IDH wild type GBM and correlates with poor survival [START_REF] Reon | LINC00152 Promotes Invasion through a 3'-Hairpin Structure and Associates with Prognosis in Glioblastoma[END_REF][START_REF] Zou | lncRNAs PVT1 and HAR1A are prognosis biomarkers and indicate therapy outcome for diffuse glioma patients[END_REF]. These epigenetic reprogramming that occur in IDH mutated tumors are highly dynamic and can be reversible while some of these markers were found to be consistent over generations in vitro even after the withdrawal of IDH1R132H expression of astrocytic cells suggesting a permanent epigenetic reprogramming in tumor cells. Though IDH mutation is known to induce hyper methylation on DNA, CHIP-sequencing analysis of histone modifications showed that DNA could also be hypo-methylated in specific regions and have enrichment of H3K4me3, an Introduction active transcription marks on those regions. These open chromatin areas indicate a role in tumor progression. One such gene that was found to enrich H3K4me3 on their promoter within 2 days of exposure to IDH1 mutated protein, was PDGFRA, a gene most commonly overexpressed in IDH mutated glioma [START_REF] Turcan | Mutant-IDH1-dependent chromatin state reprogramming, reversibility, and persistence[END_REF].

Introduction

Progression of Diffuse Low grade glioma to high grade glioma

In an attempt to understand the progression of low-grade glioma to higher grade, several transcriptomic and genetic profiling were carried out in tumor samples from grade II through grade IV. Genetic profiling of LGG and GBM combining data from copy number, mutation and fusion transcripts identified significantly mutated genes and several driver pathways of glioma such as Ras-Raf-MEK-ERK, p53, PI3K/AKT/mTOR, chromatin modifications and cell cycle-associated pathways. Notably, Ras-Raf-MEK-ERK signaling cascades were altered in IDH1 wildtype gliomas (73%) while genetic alterations in IDH1 mutated astrocytoma mostly targeted chromatin remodelers (54%). Among the newly identified genetic alterations included cohesion complex, a protein complex responsible for adhesion of sister chromatids responsible for faithful chromosome segregations. While cohesion complex gene STAG2, was previously reported in GBM, 16% of LGG were identified for these mutations, suggesting it as a prominent pathway to drive tumor progression. As TERTp and ATRX mutations are mutually exclusive and identified in oligodendroglioma and astrocytoma respectively and is involved in telomere lengthening, whole genome sequencing identified tumors and were aggressive in nature (Ceccarelli et al., 2016).

A cellular subpopulation that has been identified commonly from grade II to grade IV expresses A2B5 marker. These cells generate neurospheres and can be propagated in vitro and are invariably tumorigenic generating highly proliferative and invasive tumors during orthotopic grafting (Auvergne et al., 2013). A2B5 -cells were also tumorigenic at higher cellular density hinting to the possibility of yet unknown tumor propagating cells. Gene expression analysis of all A2B5 + cells across the grades identified some common set of genes dysregulated right from the early stages of disease progression. These included transcripts such as CD24, SIX1 homeodomain transcription factor and its binding partners, dedifferentiation associated gene and invasion-associated genes like MMP3, IGFBP2 and Introduction GAP43 along with EGFR, MYC, ID1 and ID4. These upregulated genes are essential in maintaining their proliferation, survival and tumorigenecity (Auvergne et al., 2013); inhibition of SIX1 gene using shRNA revealed that tumor cell properties are highly dependent on them [START_REF] Zhang | Six1 expression is associated with a poor prognosis in patients with glioma[END_REF]. Apart from these, A2B5 + cells were enriched for pathways such as Wnt/β-catenin, BMP and TGFβ signaling suggesting their significance during glioma progression. While A2B5 + cells at a lower grade shared gene expression patterns indicative of their proneural phenotype, their progression to aggressive phenotype was related to enrichment of gene set related to invasion, angiogenesis and mesenchymal transition. The A2B5 + cells were significantly enriched for other cell surface markers such as CD133, CD140a and CD44, all markers of GSCs (Auvergne et al., 2013).

Combining high-throughput genetic analysis data from grade II and III glioma from Japan cohort and The Cancer Genome Atlas (TCGA) cohorts, Suzuki et. al. and group were able to delineate the landscape of genetic lesions and identify a few driver genes involved in disease progression. Astrocytoma, oligodendroglioma and IDH-wt glioma represented three nonoverlapping tumor subtypes for the driver mutations. The driver genetic alterations identified in grade II and III include NOTCH1 pathway and a few histone methyltransferase genes as well as multiple components of SWI/SNF chromatin remodeling complex and PI3K-mTOR pathways (PIK3CA, PTEN, EGFR) (Bai et al., 2016). The authors further report that cell cycle regulators such as CDKN2A, CDKN2B, RB1, CDK4, and CCDN2 were commonly mutated in IDH wildtype type III glioma. However, recent reports suggest the prognostic role of CDKN2A in IDH mutated gliomas. In IDH mutated grade III astrocytoma and oligodendroglioma, homozygous deletion of CDKN2A is predictive of shorter progression free survival and overall survival while the deletion was not observed in IDH mutated grade II glioma [START_REF] Appay | CDKN2A homozygous deletion is a strong adverse prognosis factor in diffuse malignant IDH-mutant gliomas[END_REF]. Similar observation has also been made in another independent cohort that identified CDKN2A/B homozygous deletion as a worst prognosis of IDH mutated glioma progression [START_REF] Shirahata | Novel, improved grading system(s) for IDHmutant astrocytic gliomas[END_REF].

NOTCH1 mutations were frequently associated with the progression of oligodendroglioma, while astrocytoma had frequent deletions of chromosome 11p and gain of 8q, 10p and 12p (Suzuki et al., 2015). Several publications have reported the mutations in NOTCH1 gene specific to oligodendroglioma, an inactivation mutation resulting in the downregulation of the downstream targets (Bai et al., 2016;Suzuki et al., 2015) (Cancer Genome Atlas Research et al., 2015). Another important signaling could be possibly involved in glioma progression in both astrocytoma and oligodendroglioma was upregulation of MYC signaling and MYC-Introduction associated factors as well as downregulation of its suppressors and chromosome deletions of 9p, encompassing CDKN2A-CDKN2B and PTEN and FAT receptors. Additionally, majority of tumors overexpressed EZH2, catalytic subunit of PRC2 complex upon progression [START_REF] Bai | Integrated genomic characterization of IDH1-mutant glioma malignant progression[END_REF]. The complex is involved in catalyzing H3K27me3,a repressive marker in genome thus epigenetically regulating tumor progression [START_REF] Cao | Role of histone H3 lysine 27 methylation in Polycomb-group silencing[END_REF][START_REF] Margueron | The Polycomb complex PRC2 and its mark in life[END_REF]. Alterations in cell-cycle regulators and downregulation of differentiation and developmental genes through epigenetic modifications confers tumor cells self-renewal capacity and a state of stemness.

Exome sequencing analysis of 23 grade II gliomas at initial diagnosis and at recurrence revealed the dynamic nature of tumor evolution. Around 54% somatic mutations were shared between initial and recurrent tumors while remaining ones were private to either group.

IDH1R132H mutation was the only mutation shared in all cases studied implicating its importance in tumor genesis and progression. There are a few patient cases reported to contain a distinct point mutations on TP53 and ATRX in recurrent tumors that were absent in their original counterparts. Comparison studies on initial and recurrent tumors showed patterns of linear and branched clonal evolution. As temozolomide (TMZ), a conventional chemotherapeutic agent alkylates the genome, the study also looked into its effects on genome as a mutagen. Hypermutations were detected in tumors of patients that received temozolomide treatment with 31.9-90.9 mutations per Mb when compared to recurrent tumors with no chemotherapy with 0.2-4.5 mutations per Mb (Bai et al., 2016;Johnson et al., 2014).

Most often resistance to TMZ arises due to the acquisitions of mutations in DNA mismatch repair pathways. Analyzing hypermutated pathways that give survival advantages and rapid progression to GBM revealed the influence of retinoblastoma (Rb) and AKT-mTOR pathways. Transcriptomic sequencing confirmed the presence of mutations in domains of Rb involved in growth suppression as well as mutations in CDKN2A that induce cell cycle arrest.

Also TMZ-associated mutations induce hyperactivation of Akt and induce mTOR induced transformation as well as silence PTEN functions (Johnson et al., 2014).

Taken together the results from various sequencing data on whole genome, exomes, gene expression, DNA methylation and copy number variations performed in comparison with grade II and III gliomas with their recurrent tumors have helped in understanding the following regarding the glioma progression.

Introduction

• Progression of glioma from low grade to high grade is highly dynamic. IDH1R132H mutation continues to be shared between the initial and recurrent tumors implicating its role in gliomagenesis and progression.

• Depending on the genetic variations in the seeding cells of tumor recurrence, the glioma evolution could be a linear clonal progression or tumors can have branched clonal evolution with differing mutations occurring temporally and spatially.

• Among the few consistent mutations observed during tumor progression includes an inactivating mutation in NOTCH1 pathway in oligodendroglioma. But activating mutations are very often found to be associated with MYC signaling, RTK-PI3K pathway, various cell cycle regulators as well as chromatin remodeling complexes that modify the epigenome.

• Temozolomide treatment of IDH1 mutant LGG generates a hypermethylated genotype contributing to malignancy in 60% cases. In contrast, hypermutations in IDH1-wt tumors exhibited better prognosis to chemotherapy in 20% cases.

Given that there are several specific genetic abnormalities that grade II cells accumulate to be able to transform to malignancy, could it be possible that the transforming cells within the tumor tissue be identified earlier in their progression? Histological analysis of grade II glioma tissues led to the identification of hypercellular foci in 20% patients and had a poor prognosis compared to non-foci glioma (Pedeutour-Braccini et al., 2015). Further analysis on cellular markers of transformation, proliferation and vascularization demonstrated that hypercellular foci were significantly higher for proliferation marker KI67, vascularization marker CD31, and hypoxia factor HIF-1α. Foci specific polysomy of chromosome 7 (contain EGFR) and 12

(contain MDM2) were also identified suggesting that microfoci within DLGG tissues are early signs of progression towards malignancy (Pedeutour-Braccini et al., 2015). Detailed investigation of these foci could shed light to early transformation pathways in DLGG.

In vivo models of DLGG

The onset of the use of in vivo model systems in DLGG began with the identification of IDH1 mutations as an early marker of tumorigenesis (Figure 11). Thus many of the data published so far uses genetically engineered knock-in mouse models of IDH1R132H. One of the early studies that developed such a model system generated brain specific IDH1 mutation in Nestin-Cre transgenic mice to conditionally knock-in mutation in neural stem cells. Induction of IDH1 mutation as early as embryonic day 10.5 resulted in perinatal deaths of the pups that resulted from massive hemorrhage in the cerebrum and cerebellum. Even though they could not observe development of glioma, they observed downstream effects of IDH1 mutation in the brain such as accumulation of D2HG, the oncometabolite, stabilization of hypoxia inducible factor 1 alpha (HIF1a) and upregulation of vascular endothelial growth factor (VEGF), a HIF1a target gene as well as disruption of collagen maturation. To further extend their study, the group used GFAP-cre transgenic mice to specifically mutate IDH1 in astrocytes. Cre expression began around E14.5 and did not induce any abnormality until E15.5 after which 60% embryos exhibited brain hemorrhage. Interestingly 8.3% mice survived until adulthood with milder phenotypes but did not develop glioma suggesting that IDH1 mutation alone is not sufficient to generate glioma [START_REF] Sasaki | D-2-hydroxyglutarate produced by mutant IDH1 perturbs collagen maturation and basement membrane function[END_REF]. To circumvent the problems of embryonic lethality, Bardella et. al. and colleagues generated IDH1R132H glioma model using tamoxifen-inducible Nestin-Cre to induce mutant protein expression in adult mice. This restricted the expression in adult NSCs residing in the neurogenic regions of the brain such as SVZ and SGZ of the hippocampal dendate gyrus. They observed significant proliferation and infiltration of the labeled cells and progenitors in the brain as well as production of D2HG and methylation phenotype. mRNA expression profile analysis of the mutant cells shared expression signature to the proneural GBM subtype. But similar to the previous model, this model also failed to generate glioma in vivo [START_REF] Bardella | Expression of Idh1(R132H) in the Murine Subventricular Zone Stem Cell Niche Recapitulates Features of Early Gliomagenesis[END_REF].

Infection of NSC expressing IDH1 mutant protein along with p53 and ATRX knockdown in NOD/SCID mice recapitulated the diffuse invasion nature of low-grade astrocytoma, which was not observed when cells were mutated alone for IDH1 or IDH1 and p53 suggesting the importance of ATRX in LGG phenotype. This work also provided hints on the order of oncogenic hits during gliomagenesis with IDH1 mutation being the earlier followed by p53 loss and finally ATRX mutation as they observed that cells underwent apoptosis with ATRX loss in the wildtype p53 background. Though they provide insights to the mechanism of block of differentiation of IDH1 mutated cells, this model could not generate glioma in vivo apart Introduction from observing invasion of cells, which point to the requirement of additional genetic alterations [START_REF] Modrek | Low-Grade Astrocytoma Mutations in IDH1, P53, and ATRX Cooperate to Block Differentiation of Human Neural Stem Cells via Repression of SOX2[END_REF]. Generation of IDH1 mutated mouse model with p53 knockdown in the background of CDKN2A deletion required PDGF signaling. Glioma development was not observed with IDH1 mutation alone or in combination with p53 loss and/or CDKN2A loss, while survival of mice was significantly affected by the mutational status of CDKN2A. There was no significant difference in the survival of mice expressing wildtype or mutant IDH1 in the genetic background of cdkn2a loss. These suggest the relevance of these alterations in glioma formation. This model system also generated tumors of higher grade in the presence of CDKN2A mutations [START_REF] Amankulor | Mutant IDH1 regulates the tumor-associated immune system in gliomas[END_REF]. Philip et. al.

and group were the first to demonstrate that IDH1R132H mutation could promote glioma formation in vivo in mice in the background of several genetic alterations such as ATRX, CDKN2A and PTEN loss along with PDGFA expression commonly found in astrocytoma.

This was achieved through RCAS/TVA retroviral vector to direct infection to Nestin TVA:

ATRX/CDKN2A/PTEN floxed mice with RCAS-Cre, RCAS-PDGFA or RCAS-IDH1 wildtype or mutated protein alone or in combination to locally infect Nestin positive cells in the brain. The combined loss of ATRX/CDKN2A and PTEN along with PDGFA expression was able to induce glioma in 20% mice but in the presence of IDH1 mutations, the percentage of incidence increased to 88% emphasizing the role of IDH1 mutation in glioma formation.

The generated glioma resembled proneural IDH1 mutated glioblastomas. There was no significant survival difference in mice harboring tumors expressing PDGF alone or in combination with IDH1 wildtype or mutant in the context of cdkn2a loss or in combination of Pten loss [START_REF] Philip | Mutant IDH1 Promotes Glioma Formation In Vivo[END_REF]. IDH1 mutation has also been identified to have antitumorigenic properties. This was established in a mouse model to generate brain tumors under RAS activation in the context of p53 and ATRX knockdown in the presence or absence of IDH1 mutation. They observed genetic stability in IDH1mut glioma model owing to the increased activity of DNA damage response pathway through the epigenetic reprogramming.

Epigenetic modifications activate the promoter of ATM, a protein involved in DNA double strand break repair thus activating repair mechanisms in the cells that helps their survival.

This model system provided novel treatment strategies to combine radiation with DNA damage response inhibitors to improve the therapeutic efficiency [START_REF] Nunez | IDH1-R132H acts as a tumor suppressor in glioma via epigenetic up-regulation of the DNA damage response[END_REF].

There has been no mouse model developed so far that could recapitulate oligodendroglioma containing IDH1 mutation. Some of the early mouse models that generated oligodendroglioma were based on PDGF and EGF signaling expression. Overexpression of PDGFB through retroviral system in neural progenitor cells or OPC in mouse embryos could Introduction generate tumors resembling oligodendroglioma while expression of the same in adult OPC failed to generate tumors [START_REF] Appolloni | PDGF-B induces a homogeneous class of oligodendrogliomas from embryonic neural progenitors[END_REF][START_REF] Dai | PDGF autocrine stimulation dedifferentiates cultured astrocytes and induces oligodendrogliomas and oligoastrocytomas from neural progenitors and astrocytes in vivo[END_REF][START_REF] Lindberg | Oligodendrocyte progenitor cells can act as cell of origin for experimental glioma[END_REF].

Likewise, the expression of activated form of EGFR (v-erbB) under the promoter of s100b generates low-grade oligodendroglioma with loss of chromosome 4, orthologous of human 1p chromosome, while additional background mutations on Ink4a/Arf or p53 aggravated the malignancy [START_REF] Weiss | Genetic determinants of malignancy in a mouse model for oligodendroglioma[END_REF]. These early models of oligodendroglioma are not bona fide models, as they have not been analyzed for the characteristic genetic lesions of OII such as IDH1 mutation, 1p/19q co-deletion or intact atrx. Recent studies published on cic and fubp1, common deletions observed in oligodendroglioma provide insight to their potential to be developed as new model systems. Knockout of cic induces aberrant proliferation of neural stem/progenitor cells in SVZ [START_REF] Yang | Cic Loss Promotes Gliomagenesis via Aberrant Neural Stem Cell Proliferation and Differentiation[END_REF]. Inactivation of CIC in neural stem/progenitor cells failed to induce lesion in brain while arresting cells in OPC-like state and inhibiting their differentiation [START_REF] Ahmad | Capicua regulates neural stem cell proliferation and lineage specification through control of Ets factors[END_REF][START_REF] Simon-Carrasco | Inactivation of Capicua in adult mice causes T-cell lymphoblastic lymphoma[END_REF]Yang et al., 2017). FUBP1 was found to be necessary for the cell cycle exit and differentiation of neural progenitors. Tumor development was promoted by the downregulation of FUBP1 when combined with IDH1R132H, loss of cdkn2a and pik3ca inactivating mutation [START_REF] Hwang | Far Upstream Element-Binding Protein 1 Regulates LSD1 Alternative Splicing to Promote Terminal Differentiation of Neural Progenitors[END_REF]. Development of oligodendroglioma models would be necessary to understand their molecular and cellular mechanisms and their development in parallel to shedding light on the roles of the signature genetic mutations in disease progression. should be the developmental stage of the host organism, which methods are to be followed to introduce the mutations. There are a lot of hurdles to be crossed to develop a good model system. Equally challenging is to develop an in vitro model system in low-grade glioma. With the development of neural stem culture system propagated as neurospheres, cultures of GBM have been relatively easy to develop. These neurospheres maintain the phenotype and genotype of the primary tumor and can be propagated over generation [START_REF] Lee | Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines[END_REF]. They are extensively used for in vitro analysis of proliferation, differentiation, migration, and invasion to name a few. They can also be transplanted in mice brain to generate secondary tumors.

But developing a culture system in vitro still remain challenging for DLGG, primarily because they cannot be derived as neurospheres following the same protocol probably due to fewer stem cells present in them (Figure 11). Fewer attempts made to derive cell lines have become unsuccessful due to the elimination of IDH1 mutant cells in culture [START_REF] Piaskowski | Glioma cells showing IDH1 mutation cannot be propagated in standard cell culture conditions[END_REF]. These cells grow very slowly in vitro and are mostly unresponsive to culture conditions [START_REF] Kelly | Oligodendroglioma cell lines containing t(1;19)(q10;p10)[END_REF][START_REF] Klink | A novel, diffusely infiltrative Bibliography xenograft model of human anaplastic oligodendroglioma with mutations in FUBP1, CIC, and IDH1[END_REF]. Successful derivation of IDH1 mutant cell lines is mostly obtained from anaplastic grade of tumor suggesting the necessity of additional genetic aberrations [START_REF] Kelly | Oligodendroglioma cell lines containing t(1;19)(q10;p10)[END_REF][START_REF] Klink | A novel, diffusely infiltrative Bibliography xenograft model of human anaplastic oligodendroglioma with mutations in FUBP1, CIC, and IDH1[END_REF][START_REF] Luchman | An in vivo patientderived model of endogenous IDH1-mutant glioma[END_REF][START_REF] Rohle | An inhibitor of mutant IDH1 delays growth and promotes differentiation of glioma cells[END_REF]. Thus extensive studies are required to establish a standard culture system. (Liu et al., 2015b).

Conversion of cells to terminally differentiated neurons also represents a potential treatment strategy for glioma to block their aggressive proliferation and impede progression. Ectopic expression of neuronal transcription factors ASCL1, BRN2 and NGN2 efficiently converted 20-40% glioma cell lines to functional neurons with impaired proliferation in vitro and in vivo [START_REF] Zhao | Neuronal transcription factors induce conversion of human glioma cells to neurons and inhibit tumorigenesis[END_REF]. Similar observations were also made when glioma cells overexpressed NGN2 and SOX11, both markers of neuronal differentiation. They observed that transduced cells exit cell cycle and become non-proliferative. The study was also extended by in vivo lentivirus injection of these transcription factors to preexisting brain tumors. They observed in vivo reprogramming of tumor cells though majority of the NGN2/SOX11 positive cells underwent cell death [START_REF] Su | Reprogramming the fate of human glioma cells to impede brain tumor development[END_REF]. A recent study has reported that ASCL1 is the master regulator of neuronal reprogramming. Expression of this single transcription factor was sufficient enough to covert 94% of infected cells to TUBB3 + neuronal cells inhibiting tumor development [START_REF] Cheng | Inhibition of Glioma Development by ASCL1-Mediated Direct Neuronal Reprogramming[END_REF]. Our lab has also published previously that introduction of NGN2 in glioblastoma stem cells induced neuronal differentiation of cells affecting their proliferation [START_REF] Guichet | Cell death and neuronal differentiation of glioblastoma stem-like cells induced by neurogenic transcription factors[END_REF].

Introduction

Plasticity of the glial cells has also been explored for the inter-conversion of glial cells from astrocytes to oligodendrocytes or vice versa. This type of plasticity was initially explored on oligodendrocytic precursor, O-2A cells of the optic nerve that begin to express astrocytic markers when cultured in the presence of cytokines such as LIF, CNTF as well as in serum [START_REF] Behar | Analysis of fractal dimension of O2A glial cells differentiating in vitro[END_REF][START_REF] Gard | Oligodendroblasts distinguished from O-2A glial progenitors by surface phenotype (O4+GalC-) and response to cytokines using signal transducer LIFR beta[END_REF][START_REF] Lillien | Differentiation signals in the CNS: type-2 astrocyte development in vitro as a model system[END_REF]. These astrocytes are termed type II astrocytes to distinguish from type I astrocytes derived from glial precursors, though functional differences between these two types are not clearly elucidated. This could be possible due to the inherent plasticity of the immature glia to generate both oligodendrocytes and astrocytes [START_REF] Suzuki | Differentiation of Oligodendrocyte Precursor Cells from Sox10-Venus Mice to Oligodendrocytes and Astrocytes[END_REF][START_REF] Zhu | NG2 cells generate both oligodendrocytes and gray matter astrocytes[END_REF]. Reversion of the cellular state is also possible. It is demonstrated that PDGF exposure to A2B5-/O4 + cells in vitro revert the cells to A2B5 + /O4-, an immature state [START_REF] Mason | A2B5+ and O4+ Cycling progenitors in the adult forebrain white matter respond differentially to PDGF-AA, FGF-2, and IGF-1[END_REF].

In the context of glioma, OLIG2 gene seems to be playing an important role in determining the phenotype of the tumor cells. Deletion of Olig2 in a proneural GBM model carrying p53/Pten deletion and PDGFRB overexpression resulted in EGFR upregulation and OPC to astrocytic switch with enrichment of GFAP and NFIA alongside expression shift from proneural to classical phenotype. The tumors formed in this model could be generated directly from OPC or conversion of OPC like oligodendrocytic cells [START_REF] Lu | Olig2-Dependent Reciprocal Shift in PDGF and EGF Receptor Signaling Regulates Tumor Phenotype and Mitotic Growth in Malignant Glioma[END_REF]. OLIG2

downregulation in proneural GSC cell lines upregulated mesenchymal markers such as CHI3L1, CD44, STAT3 and TGFB1, suggesting transition to a more aggressive phenotype [START_REF] Kupp | Lineage-Restricted OLIG2-RTK Signaling Governs the Molecular Subtype of Glioma Stem-like Cells[END_REF]. Role of OLIG2 in cell fate determination during development has also been studied. Deletion of Olig2 in neural stem cells resulted in increased expression of GFAP in astrocytes in vivo [START_REF] Cai | A crucial role for Olig2 in white matter astrocyte development[END_REF]. Similarly, downregulation or cytoplasmic translocation of OLIG2 in NSCs in vitro switched cell fate from oligodendrocytes to astrocytes [START_REF] Fukuda | Negative regulatory effect of an oligodendrocytic bHLH factor OLIG2 on the astrocytic differentiation pathway[END_REF][START_REF] Setoguchi | Nuclear export of OLIG2 in neural stem cells is essential for ciliary neurotrophic factor-induced astrocyte differentiation[END_REF]. Constitutive deletion of Olig2 from NG2 cells of mice resulted in generation of astrocytes at the expense of oligodendrocytes in neocortex and corpus callosum implying the importance of Olig2 is maintaining oligodendrocytic phenotype [START_REF] Zhu | Olig2-dependent developmental fate switch of NG2 cells[END_REF].

Phenotypic plasticity can also be achieved through differential expression of signaling pathways. Combined activation of both AKT and RAS pathways as well as constitutive activation of PDGF in Nestin positive cells in mice give rise to GBM and oligodendroglioma respectively. Given that the same cell type could induce distinct phenotypes, signaling pathways play a crucial role. Forced activation of AKT in Pdgf induced oligodendroglioma transformed double infected cells to GFAP positive astrocytic like cells [START_REF] Dai | The characteristics of astrocytomas and oligodendrogliomas are caused by two distinct and interchangeable signaling formats[END_REF].

Introduction

Whereas inhibition of mTOR, a downstream target of Akt signaling, in Ras/Akt activated GBM mouse model resulted in conversion of astrocytoma to oligodendroglioma like cells with morphological changes -observed by round nuclei cells with clear cytoplasm, histological features of oligodendroglioma cells, and strong expression of OLIG2, suggesting mTOR activity is required for the maintenance of astrocyte character in tumor cells [START_REF] Hu | mTOR promotes survival and astrocytic characteristics induced by Pten/AKT signaling in glioblastoma[END_REF].

The above examples of phenotypic plasticity came from the research performed on glioma stem cells and in vivo models of GBM. Studies have still not focused on understanding the biology of glial cells in DLGG. A recent study published in 2019 discusses a possible phenotypic plasticity of cells in these low-grade tumors. This stems from the observation of subtype shift in 2 patients after recurrence. While primary lesions present in these patients were of oligodendroglioma with 1p/19q co-deletion, the group identified that the recurred tumor was astrocytoma comprising of tumor cells with ATRX and P53 mutations with the absence of cells with oligodendroglioma features. This could be due to two possibilities.

During the progression, tumor cells could have acquired these new mutations providing evidence to the lineage conversion of these tumor cells. Another possibility is that primary tumors could have already been comprised of tumor cells with different genetic variations with oligodendroglial clones representing majority of the tumor tissue. And over the years with the chemotherapy treatment astrocytoma clones could have gained more proliferative advantages over oligodendroglioma cells, outnumbering them in the recurrent tumor (Kim et al., 2019).

This observation opens up novel areas for research in the glioma field. First of all, molecular characterizations should be carried out extensively in larger number of paired cases of primary and recurrent tumor to confirm if this is a frequent phenomenon. It also needs to be understood which among the above-mentioned hypothesis is the foundation for the cause. If it turns out the first hypothesis is true, research needs to focus on understanding the signaling pathways involved in these conversions in vivo. New methods/drugs/inhibitors should be discovered to prevent the lineage conversion at the lower grade stage that could impede in their progression, which will be beneficial to the health conditions of the patients. It is possible that the molecular players in DLGG progression to secondary glioblastoma are different from GBM, as we know that subtype specific genetic aberrations are involved in phenotypic determinations. But at the same time signaling pathways also have their definitive

role. An understanding of these features of DLGG could take this field forward.

Introduction 1.9. Involvement of Notch and BMP signaling in glioma pathogenesis

Notch Signaling

Notch signaling is an evolutionarily conserved pathway that plays critical roles in various cellular and developmental processes such as cell proliferation, cell fate determination, tissue homeostasis, and stem cell maintenance [START_REF] Andersson | Notch signaling: simplicity in design, versatility in function[END_REF][START_REF] Basak | Neurogenic subventricular zone stem/progenitor cells are Notch1-dependent in their active but not quiescent state[END_REF][START_REF] Guruharsha | The Notch signalling system: recent insights into the complexity of a conserved pathway[END_REF][START_REF] Imayoshi | Essential roles of Notch signaling in maintenance of neural stem cells in developing and adult brains[END_REF][START_REF] Yang | Notch activation induces apoptosis in neural progenitor cells through a p53-dependent pathway[END_REF]. In mammals, it is composed of four receptors-Notch1, Notch2, Notch3 and Notch4 that bind to two family of ligands-Delta-like (Dll1, 3,4) and Jagged (Jag1, 2) [START_REF] Hori | Notch signaling at a glance[END_REF]. The interaction between receptor and ligand can be either cis or trans-when both are present in same cell or neighbouring cell respectively. Trans interaction activates the pathway while cis inhibits the signaling [START_REF] Del Alamo | Mechanism and significance of cis-inhibition in Notch signalling[END_REF][START_REF] Kopan | The canonical Notch signaling pathway: unfolding the activation mechanism[END_REF][START_REF] Lebon | Fringe proteins modulate Notch-ligand cis and trans interactions to specify signaling states[END_REF].

The trans activation results in conformational change in the Notch receptor leading to cleavage of the intracellular domain by γ-secretase complex releasing active form of Notch intracellular domain (NICD) in the cytoplasm [START_REF] De Strooper | A presenilin-1-dependent gammasecretase-like protease mediates release of Notch intracellular domain[END_REF]. NICD further translocates to the nucleus and binds to several DNA-binding proteins of CSL (CBF1 in Homo sapiens and RBPJK in Mus musculus) family recruiting transcriptional co-activators mastermind-like protein (MAML), Ski-interacting protein (SKIP), histone acetyltransferases CREB-binding protein (CBP)/p300 and p300/CBP-associated factor (PCAF)/GCN5 (PCAF-B) [START_REF] Wallberg | p300 and PCAF act cooperatively to mediate transcriptional activation from chromatin templates by notch intracellular domains in vitro[END_REF][START_REF] Wu | Modulation of Notch signaling by mastermind-like (MAML) transcriptional co-activators and their involvement in tumorigenesis[END_REF]. This results in upregulation of two transcriptional repressor family-Hairy Enhancer of Split (HES) and HES-related proteins (HEY) involved in lineage commitment decisions [START_REF] Iso | HERP, a new primary target of Notch regulated by ligand binding[END_REF][START_REF] Jarriault | Signalling downstream of activated mammalian Notch[END_REF].

Notch1 signaling in Glioma

Since Notch1 plays central role in cell fate determination in CNS, it is quite evident that any deregulation in the pathway can influence the pathological conditions. Deregulation of Notch pathway has been widely studied in various cancer models [START_REF] Penton | Notch signaling in human development and disease[END_REF][START_REF] Ranganathan | Notch signalling in solid tumours: a little bit of everything but not all the time[END_REF][START_REF] Takebe | Targeting notch signaling pathway in cancer: clinical development advances and challenges[END_REF] including brain tumors. Higher expression of NOTCH1, 3, 4, Dll1, HEY1, correlates with higher-grade glioma and poor prognosis indicating the role of Notch signaling in promoting aggressive tumor phenotype [START_REF] Kanamori | Contribution of Notch signaling activation to human glioblastoma multiforme[END_REF]Phillips et al., 2006;[START_REF] Somasundaram | Upregulation of ASCL1 and inhibition of Notch signaling pathway characterize progressive astrocytoma[END_REF][START_REF] Zhang | Notch activation promotes cell proliferation and the formation of neural stem cell-like colonies in human glioma cells[END_REF]. However, the role of Notch 1 in gliomagenesis remains controversial. Several studies have reported Notch as a tumor promoter gene while others support the reverse. While mRNA and protein levels of NOTCH1, DLL1, DLL4, JAGGED1, HEY1, HEY2 and HES1 are reported to be higher in Introduction tumor cells than normal cells, NOTCH1 expression was found higher in patients survived 1 year longer than other patients indicating a possible protective role of Notch1 [START_REF] Brennan | Glioblastoma subclasses can be defined by activity among signal transduction pathways and associated genomic alterations[END_REF][START_REF] El Hindy | Implications of Dll4-Notch signaling activation in primary glioblastoma multiforme[END_REF][START_REF] Hulleman | A role for the transcription factor HEY1 in glioblastoma[END_REF][START_REF] Kanamori | Contribution of Notch signaling activation to human glioblastoma multiforme[END_REF][START_REF] Xing | Elevated expression of Notch-1 and EGFR induced apoptosis in glioblastoma multiforme patients[END_REF].

Tsung et al. showed that Hey1 promoter is hypomethylated at CpG island in GBM tissues compared to normal brain resulting in its overexpression. Knockdown of Hey1 reduced cell proliferation, migration and invasion [START_REF] Tsung | Methylation regulates HEY1 expression in glioblastoma[END_REF]. Overexpression of NOTCH1

promotes AKT activation, which in turn induces nuclear localization of β-CATENIN and NFκB, together with overexpression of SNAIL, ZEB1 and VIMENTIN to promote cell migration and invasion [START_REF] Zhang | Notch1 promotes glioma cell migration and invasion by stimulating beta-catenin and NF-kappaB signaling via AKT activation[END_REF]. Neurospheres with high NOTCH1 levels had more infiltrative phenotype than NOTCH1 low cells [START_REF] Kristoffersen | Inhibition of Notch signaling alters the phenotype of orthotopic tumors formed from glioblastoma multiforme neurosphere cells but does not hamper intracranial tumor growth regardless of endogene Notch pathway signature[END_REF]. NOTCH1 also plays an important role in maintaining the stemness of GSCs. Overexpression of NICD in human glioma cell line SHG-44 led to enhanced proliferation with increased sphere forming and higher colony forming potentials [START_REF] Zhang | Notch activation promotes cell proliferation and the formation of neural stem cell-like colonies in human glioma cells[END_REF]. Notch signaling and its downstream targets get activated under hypoxic conditions and help GSCs to maintain their undifferentiated phenotype [START_REF] Bar | Hypoxia increases the expression of stem-cell markers and promotes clonogenicity in glioblastoma neurospheres[END_REF]. Nestin, a widely used stem cell marker is a direct transcriptional activating target of Notch signaling further supporting the findings that Notch could regulate the stemness of GSCs [START_REF] Shih | Notch signaling enhances nestin expression in gliomas[END_REF]. Notch-related genes were most highly expressed in mesenchymal subtype again proving its association to aggressive phenotype [START_REF] Cheng | Bioinformatic analyses reveal a distinct Notch activation induced by STAT3 phosphorylation in the mesenchymal subtype of glioblastoma[END_REF].

On the contrary, Notch has also been implicated in tumor suppressor functions. A few studies have also reported that there is lower expression of NOTCH1 and its related components in glioblastoma [START_REF] Cheung | Polypyrimidine tract binding protein and Notch1 are independently re-expressed in glioma[END_REF][START_REF] Dell'albani | Differential patterns of NOTCH1-4 receptor expression are markers of glioma cell differentiation[END_REF]. Espinoza et al. reported abnormal expression of NOTCH1 in all grades except grade IV [START_REF] Cheung | Polypyrimidine tract binding protein and Notch1 are independently re-expressed in glioma[END_REF]. Our team has demonstrated that upregulation of NOTCH1 in GBM cell-lines reduced proliferation and migration of cells but upregulated pericyte-markers indicating transdifferentiation of cells.

NOTCH1 overexpressing GSCs when implanted into nude mice, formed highly vascularized tumors but were less invasive (Guichet et al., 2015). Taken together, the current consensus on the role of Notch in glioma is still debatable and can differ according to the tumor microenvironment.

Introduction

1.9.1.2.

Role of Notch1 in DLGG and secondary Glioblastoma

Most of the evidences from the gene expression and DNA sequencing studies point towards tumor suppressor functions of NOTCH1 in DLGG, particularly in oligodendroglioma. A gene expression study performed on low grade and high-grade proneural glioma identified NOTCH1 pathway as an important gene regulatory hub (Cooper et al., 2010). There was differential regulation of notch pathway in low grade and high-grade glioma with decrease in pathway activity as the glioma progresses. Proneural gliomas are predicted to have a better clinical outcome when compared to other subtypes. Several components of Notch pathway such as DLL3 and HEY2 were downregulated while Notch inhibitors were upregulated during the course of progression (Cooper et al., 2010). Also expression of HES1, another transcriptional target of Notch signaling was nearly absent in secondary glioblastoma.

Mutations in Notch1 gene have been frequently observed and have been proposed as an early driver mutation in oligodendroglioma during progression [START_REF] Bettegowda | Mutations in CIC and FUBP1 contribute to human oligodendroglioma[END_REF]Suzuki et al., 2015;[START_REF] Yip | Concurrent CIC mutations, IDH mutations, and 1p/19q loss distinguish oligodendrogliomas from other cancers[END_REF]. This mutation is considered to be an inactivating one as mutations in similar regions was identified as loss-of-function mutations in other cancers such as head and neck squamous carcinoma (Cancer Genome Atlas Research et al., 2015) [START_REF] Agrawal | Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1[END_REF]. In addition, Notch mutation was associated with lower expression of its downstream targets such as HES1, HEY1 and HEY2 and correlated with higher cell proliferation and worse prognosis in oligodendroglioma (Halani et al., 2018). The mechanistic role of this pathway has to be further investigated in glioma. Notch tumor suppression activity was explored in a PDGF-induced low-grade glioma model (Giachino et al., 2015). Deletion of

BMP signaling

The Bone Morphogenetic Proteins belonging to the Transforming growth factor beta (TGFβ)

super family play critical roles in development and is also involved in regulating self-renewal and differentiation of adult NSC populations [START_REF] Johnston | Keeping them quiet: BMPs maintain adult neural stem cell quiescence[END_REF][START_REF] Lim | Noggin antagonizes BMP signaling to create a niche for adult neurogenesis[END_REF][START_REF] Qi | BMP4 supports self-renewal of embryonic stem cells by inhibiting mitogenactivated protein kinase pathways[END_REF][START_REF] Xiao | BMP signaling specifies the development of a large and fast CNS synapse[END_REF]. BMP ligands exert its effect through serine-threonine kinase receptors that form tetrameric complex consisting of type I (BMPRIA and BMPRIB) and type II (BMPRII) receptors. During canonical signaling, binding of BMP ligands to the receptor complex results in phosphorylation of BMPRI receptor by BMPRII. BMPRI in turn phosphorylates R-Smad 1/5/8 and binds to co-smad SMAD4. The complex then translocates to the nucleus to transcriptionally regulate their specific targets [START_REF] Singh | The Yin and Yang of bone morphogenetic proteins in cancer[END_REF].

Extracellular and intracellular modulators can regulate BMP signaling. Extracellular antagonists include Noggin, chordin, dan, cerebrus to name a few [START_REF] Holley | The Xenopus dorsalizing factor noggin ventralizes Drosophila embryos by preventing DPP from activating its receptor[END_REF][START_REF] Piccolo | Dorsoventral patterning in Xenopus: inhibition of ventral signals by direct binding of chordin to BMP-4[END_REF][START_REF] Walsh | Extracellular BMP-antagonist regulation in development and disease: tied up in knots[END_REF]. Primary intracellular inhibitors of BMP signaling are SMAD6 and SMAD7 exerting their inhibitory effects through either competing for phosphorylation by type I receptors or by binding to SMAD4 [START_REF] Hover | Genomic Analysis of the BMP Family in Glioblastomas[END_REF].

BMP signaling in Glioma

BMP signaling has also been implicated in gliomagenesis. Due to its function as a prodifferentiating signal, BMPs are considered to be a tumor suppressor signaling. Treatment of human GSCs in vitro and in vivo with BMP4 for 48 hours reduced proliferation and promoted astrocytic differentiation affecting the tumorigenic potential of GSCs [START_REF] Piccirillo | Bone morphogenetic proteins inhibit the tumorigenic potential of human brain tumour-initiating cells[END_REF].

Exposure of BMP4 to GSCs resulted in downregulation of cyclin D1 reducing their proliferation and induced apoptosis through Bax induction and inhibition of anti-apoptotic Bcl-2 and Bcl-xL proteins {Zhou, 2011 #2108). Intracranial injection of BMP4 virus in tumor bearing mice resulted in rapid tumor regression and improved survival [START_REF] Duggal | Vaccinia virus expressing bone morphogenetic protein-4 in novel glioblastoma orthotopic models facilitates enhanced tumor regression and long-term survival[END_REF].

Similarly, BMP7 also exerts anti-tumorigenic properties on GSCs by reducing their stemness and self-renewal capacity and induces astrocytic differentiation both in vitro and in vivo [START_REF] Chirasani | Bone morphogenetic protein-7 release from endogenous neural precursor cells suppresses the tumourigenicity of stemlike glioblastoma cells[END_REF]. On EGFR-overexpressing glioma cells, BMP7 induced cell cycle arrest and apoptosis [START_REF] Klose | Imaging bone morphogenetic protein 7 induced cell cycle arrest in experimental gliomas[END_REF]. Inhibition of proliferation, angiogenesis and Introduction stemness markers and reduced tumor growth were also observed in vivo when BMP7 variant overexpressed GSCs were subcutaneously and orthotopically grafted in mice [START_REF] Tate | A BMP7 variant inhibits the tumorigenic potential of glioblastoma stem-like cells[END_REF] while BMP2 treatment sensitized GBM derived stem cells to temozolomide treatment by downregulating MGMT [START_REF] Persano | BMP2 sensitizes glioblastoma stem-like cells to Temozolomide by affecting HIF-1alpha stability and MGMT expression[END_REF]. All these provide evidence to the antitumoral effects of BMP signaling in glioma.

Gene expression studies on glioma patient samples identified that BMP4 expression is lowered in tumor cells compared to normal cells and shows an inverse correlation to the tumor grade. Lowered BMP4 levels correlated to higher expression of KI67. Kaplan-Meier analyses demonstrate that patients with higher BMP4 expression had better survival [START_REF] Bao | BMP4, a strong better prognosis predictor, has a subtype preference and cell development association in gliomas[END_REF][START_REF] Wu | BMP4, a new prognostic factor for glioma[END_REF]. BMP4 treatment on oligodendroglioma propagating cells from primary grade III oligodendroglioma reduced stemness and proliferation and induced astrocytic differentiation (Srikanth et al., 2014). BMP4 is reported to be higher in patients with IDH1 mutation as well as in proneural GBM [START_REF] Ohgaki | The definition of primary and secondary glioblastoma[END_REF]Phillips et al., 2006;Verhaak et al., 2010;[START_REF] Yan | Molecular classification of gliomas based on whole genome gene expression: a systematic report of 225 samples from the Chinese Glioma Cooperative Group[END_REF]. Reduced p-SMAD expression is associated with anaplastic astrocytoma and GBM compared to low-grade glioma. BMPRIB receptor expression is downregulated in high-grade glioma [START_REF] Liu | Expression and functional roles of Smad1 and BMPR-IB in glioma development[END_REF]. Epigenetic mediated silencing of BMPRIB impairs astroglial differentiation and enhances tumorigenesis in GSC (Lee et al., 2008).

While majority of the studies on glioma reports anti-tumoral properties of BMP signaling, there are reports that provide information on oncogenic roles of BMP. A very recent study has demonstrated that BMP4 expression in glioma cells can enhance aggressiveness in IDH1 mutant glioma. The study suggests that there exist a BMP4 autocrine loop in IDH mutant glioma cells that promote their migration and invasion. Activated BMP signaling in turns upregulates FZD1, a receptor of Wnt/β-catenin pathway and promotes its activity by upregulating its downstream targets c-Myc and Axin2 indicating cross talk between BMP and Wnt signaling [START_REF] Zhou | Autocrine BMP4 Signaling Enhances Tumor Aggressiveness via Promoting Wnt/beta-Catenin Signaling in IDH1-mutant Gliomas[END_REF]. Significant expression of BMP2 is reported in higher grade and correlated to shorter survival (Liu et al., 2009a). Tissue microarray performed on grade III and grade IV tumors indicates that p-Smad1/5/8 was upregulated in 70-100% tumor cells.

Further the study was extended to understand the role of BMPRIA in a murine model of astrocytoma generated using KRAS G12D expression and p53 deletion in astrocytes. Bmpr1a

intact and knockout mice equally generated tumors with similar histological features.

Markedly increased proliferation rate and migration was observed in Bmpr1a intact tumors suggesting the importance of BMP signaling in tumor progression [START_REF] Hover | Bone morphogenetic protein signaling promotes tumorigenesis in a murine model of high-grade glioma[END_REF].

Introduction

Taken together BMP signaling can be explored as a potential therapeutic target in glioma.

Genetic and epigenetic regulation of BMP signaling in tumor cells has to be further explored.

BMP signals can modulate both tumor cells and microenvironment. Understanding the role of microenvironmental niche on tumor cells in regulating this potential tumor suppressor pathway needs to be elucidated. As there are contradictory reports on the role of BMP signaling in gliomagenesis, it could imply that the cellular context in which studies are carried out is also important. More insights on this signaling mechanism can be obtained by studying the differential regulation of BMP signaling in GSCs and bulk differentiated cells.

Context, Aims and Approaches

Context, aims and experimental approaches of my thesis

Context

Gliomas accounts for around 30% of the central nervous system tumors and 80% of all malignant brain tumors (Ostrom et al., 2018. Gliomas in adults can be primarily classified into Diffuse Low Grade Gliomas (DLGG, Grade II), Anaplastic Gliomas (Grade III) and Glioblastoma Multiforme (GBM, Grade IV) based on cellular density, nuclear atypia, mitotic index and necrosis defining the pathological grades {Louis, 2007 #118). While extensive studies are made on the genetic and cellular heterogeneity in glioblastomas, DLGG remains poorly understood, leading to the limited possibilities of treatment. The most effective modality of treatment currently in practice is the surgical resection of the tumor tissue (Duffau and Mandonnet, 2013). However, due to the diffusive nature and the sensitive regions at which these tumors develop, complete removal of the tumor is almost impossible. Hence, there is an increasing necessity for characterization of DLGGs that facilitates development of novel therapeutics.

DLGG at the cellular level has been broadly divided into two major types-astrocytoma and oligodendroglioma. At the molecular level, one of the most commonly observed mutations in the DLGGs is in the Isocitrate dehydrogenase enzyme (IDH) 1/2, which is found in both astrocytoma and oligodendroglioma [START_REF] Yan | IDH1 and IDH2 mutations in gliomas[END_REF]. The other markers observed exclusively in astrocytoma are P53 mutation and ATRX loss of function mutations while oligodendroglioma bears 1p/19q co-deletion, TERT promoter mutations (Jiao et al., 2012) (Brennan et al., 2013) [START_REF] Reifenberger | Molecular genetic analysis of oligodendroglial tumors shows preferential allelic deletions on 19q and 1p[END_REF]) (Arita et al., 2013). In addition to genetic abnormalities, there have been reports suggesting the importance of altered signaling pathways in the gliomas. These cases are well documented in higher grade gliomas with the implication of dysregulated receptor tyrosine kinase signaling -Epithelial growth factor (EGF) (Furnari et al., 2015), platelet-derived growth factor (PDGF) (Szerlip et al., 2012), PI3K-AKT-mTOR and Ras-MAPK signaling (Lino and Merlo, 2011). However, there are only a handful of studies exploring the signaling aspect in DLGGs (Pierscianek et al., 2013) (Motomura et al., 2013) (Bao et al., 2014) (Azar et al., 2018).

In glioblastoma, extensive studies characterized the tumors into four molecular subgroups with distinct transcriptional states (Verhaak et al., 2010). This heterogeneity has been also explored at both inter and intra tumoral levels (Aum et al., 2014. Also, these cellular subpopulations could have a spatial territory within a tumor as well as interchange their identity depending on the environmental cues required for their sustainability {Minata, 2019

Context, Aims and Approaches #1906). But such extensive and elaborate studies are very rare in the field of diffuse lowgrade glioma. Former studies based on electron microscopy (Baloyannis, 1981) and immunohistochemistry of DLGGs (Liang et al., 2005;Rousseau et al., 2006) have described the presence of a phenotypic heterogeneity within tumoral cells. In particular, in oligodendrogliomas, subpopulations of gliofibrillary oligodendrocytes have been reported (Herpers and Budka, 1984;Kros et al., 1996;Matyja et al., 2001). Recently, the cellular composition of IDH1-mutated DLGG was also explored using the newer technological approach based on single cell RNA sequencing (Tirosh et al., 2016;Venteicher et al., 2017).

These studies reported the presence of three subpopulations of malignant cells:

nonproliferating cells differentiated along the astrocytic and oligodendrocytic lineages and proliferative undifferentiated cells that resemble neural stem/progenitor cells.

Nevertheless, it remains to be understood if the reported RNA or gene expression profiles validate their respective protein expression, which ultimately determines the identity of the cells. Further, there are no insights into the genesis of such cellular heterogeneity in DLGGs.

Is it possible to alter this heterogeneity by externally manipulating gene expression or signaling pathways? Is there a subpopulation of cells in DLGGs that act as cancer stem cells?

Answering these questions is of highest prominence not only to understand the landscape of heterogeneity in DLGGs but most importantly for designing better therapeutics. The significant number of patients operated for DLGG in Montpellier Hospital allow the possibility to directly assess the cellular diversity and active signaling in these tumor using fresh resection to perform immune characterization and cell cultures. antibodies that label astrocyte and oligodendrocyte subpopulations, respectively. Using this approach, percentage of cells expressing either SOX9 or OLIG1or both the markers were quantified. These analyses performed in 6 tumors consistently showed that there exist two highly independent cell populations (Sox9-positive and Olig1-positive cells) with a mere overlap of less than 10%.

The central goal of my

Further, these identified tumor subpopulations were characterized for their expression of distinct transcription factors and activated signaling pathways (aim 2). To this end, I costained tissue sections with proteins of interest and SOX9 or OLIG1 antibodies. Analyses of these data revealed that the SOX9 + and OLIG1 + subpopulations indeed express unique set of signaling and transcription factors. Taken together, these results demonstrate the presence of two independent tumoral subpopulations in the DLGGs.

To study the potential role of signaling pathways in determining the fate of tumor subpopulations (aim 3), I sought to isolate and purify the tumoral cells from human DLGG tissue. However, the major concern was to decide on the cell surface marker that could represent the majority of the IDH1 mutant tumor population. To understand this, I have first performed a flow cytometric characterization of the dissociated tumoral cells (24 independent cultures used) for various known cell surface markers GLAST, CD44 (expressed by astrocytes), O4 (oligodendrocyte) and A2B5, PSA-NCAM (early progenitor cells). Despite the inherent variability amongst the analyzed tumors, these experiments showed that the obtained cells majorly comprise O4 / CD44 / A2B5 as cell surface markers, with O4 cells being the highest percentage of cells in a given tumor tissue. Following this, I have then established method using magnetic sorting to purify the O4 cells from tumor tissues.

To begin with, O4 cells were purified and grown in the presence of growth factors EGF, FGF2 and PDGFα for two weeks, fixed and used for immunostaining analysis.

Immunostaining with O4 antibody showed that approximately 90% of cells are positive for O4 thus validating our purification methods. IDH1R132H staining showed great variability between cultures expressing 30-100% of tumor cells. I observed that O4 could isolate both tumoral and non-tumoral oligodendrocytes depending on the tissue resection obtained. Thus, the method of purification and culturing of low-grade glioma cells was quite successfully established.

As I observed that Notch signaling was specifically activated in SOX9 + cells, tumoral O4 + This side project is also discussed in the results section of the thesis (chapter 3.2).

Results

Results

PhD main project

Identification of astrocyte and oligodendrocyte like cells in diffuse low-grade gliomas and implication of notch signaling in their genesis

In this project, I have investigated the heterogeneity in diffuse low-grade gliomas using freshly resected tumor samples. The results obtained from this project are currently being written as a manuscript and will be submitted for publication. I have attached the manuscript (see below) in its current form as part of the results for my PhD thesis. I am the first-author on this manuscript.

Introduction

Glioma represents nearly 26% of all the central nervous system tumors and 80% of primary malignant brain tumors (Ostrom et al., 2018). Based on the histopathological and clinical evaluations, glioma in adults has been classified into low grade (grade II), anaplastic (grade III) and glioblastoma (GBM, grade IV) (Louis et al., 2007). Diffuse Low-Grade Glioma primarily occurs in younger adults in third or fourth decade of their lifetime (Pekmezci et al., 2017). These are characterized as slow growing tumors with an annual growth of 4 to 6 mm in diameter (Mandonnet et al., 2003). Grade II tumors, despite their slow growing, are infiltrative and if left untreated can progress in to higher grades of tumor (Jaeckle et al., 2011;Oberheim Bush and Chang, 2016).

Most of the grade II gliomas carry a recurrent mutation R132H in the gene encoding cytosolic isocitrate dehydrogenase 1 (IDH1) (Parsons et al., 2008). IDH1R132H mutation is very reliably detected in these grade such that it has also formed the basis of 2016 molecular classification of the glioma according to WHO (Louis et al., 2016). IDH1 is a cytoplasmic protein involved in the oxidative carboxylation of isocitrate to -ketoglutarate resulting in the production of nicotinamide adenine dinucleotide phosphate (NAPDH) and thus play a crucial role in Krebs cycle (Geisbrecht and Gould, 1999). A point mutation in Isocitrate dehydrogenase I (IDH1) enzyme impart new enzymatic activity to the protein promoting the conversion of a-ketoglutarate to R-2-hydroxyglutarate (R-2-HG) (Dang et al., 2009). The accumulation of 2-HG is an oncometabolite favoring malignant progression of tumors, most likely by inducing DNA hypermethylation (CpG island methylator phenotype, CIMP) and obstructing the cellular differentiation (Lu et al., 2012;Turcan et al., 2012). IDH1 mutated gliomas are further sub grouped into oligodendroglioma or astrocytoma by the presence or absence of unbalanced translocation of chromosomes 1 and 19 with deletion of 1p and 19q

(1p/19q co-deletion), respectively (Louis et al., 2016). Other genetic biomarker often found concomitantly in oligodendroglioma is CIC, FUBP1, TERT promoter mutation while astrocytoma most often carries ATRX and p53 mutations (Cahill et al., 2015;Cancer Genome Atlas Research et al., 2015;Jiao et al., 2012).

In addition to genetic abnormalities, there have been reports suggesting the importance of altered signaling pathways in the gliomas. These cases are well documented in higher grade gliomas with the implication of dysregulated receptor tyrosine kinase signaling (Epithelial growth factor (EGFR) (Furnari et al., 2015), platelet-derived growth factor (PDGFR) (Szerlip et al., 2012), PI3K-AKT-mTOR and Ras-MAPK signaling (Lino and Merlo, 2011). However, there are only a handful of studies exploring the signaling aspect in DLGGs (Pierscianek et al., 2013) (Motomura et al., 2013) (Bao et al., 2014) (Azar et al., 2018).

Current modality of treatment in DLGGs is primarily through maximal safe surgical resection followed by surveillance. Postsurgical treatment of DLGGs with chemotherapy and ionizing radiation are very limited in its efficacy, reasons mostly attributed to the highly infiltrative nature of these tumors. These restraints directly affect the treatment of the patient and in most cases results in the relapse of the tumor, that progress into aggressive higher-grade tumors (Duffau, 2018). However, one major bottleneck in designing better therapeutics for overcoming the above limitations is primarily due to lack of our understanding about the molecular and cellular heterogeneity in IDH1 mutated DLGG tumors.

In glioblastoma, extensive studies characterized the tumors into four molecular subgroups with distinct transcriptional states (Verhaak et al., 2010). This heterogeneity has been also explored at both inter and intra tumoral levels (Aum et al., 2014

Results

Two distinct populations of astrocytic-like and oligodendrocytic-like tumoral cells in DLGG

In order to distinguish several cell populations in DLGG tumors, we examined three astrocytoma tumors with IDH1 R132H and ATRX mutations and three oligodendroglioma tumors with IDH1 R132H and 1p19q codeletion (Table S1). To identify two potential cell types in these tumors, we used OLIG1 and SOX9 as well-known markers for oligodendrocytic and astrocytic-lineage cell respectively (Fig S1 ). Figure 1A and Fig S2A

shows that in the 6 examined tumors, two largely non-overlapping populations of OLIG1 + and SOX9 + cells were present. To make sure that these 2 cell populations were tumoral, we performed co-stainings of SOX9 and OLIG1 with the (i) R132H mutated form of IDH1 in one oligodendroglioma and (ii) ATRX for the one astrocytoma. Figure S2B shows that in the studied astrocytoma, the majority (>90%) of OLIG1 + and SOX9 + cells did not express ATRX and are thus tumoral (Fig. S2C). For the oligodendroglioma, >90% of OLIG1 + cells were costained with IDH1 R132H whereas only around 25% of SOX9+ cells showed a faint IDH1

R132H staining (Fig. S2C). However, as indicated below, this number is probably an underestimation as the level of expression of the IDH1 enzyme is lower in SOX9+ astrocytic than OLIG1 + cells.

To ascertain that SOX9 + cells show astrocytic features, further stainings were performed. We selected proteins that are expressed in DLGG tumors and for which literature and database analyses (Fig. S1, Table S2) show a clear preferential expression in the astrocytic lineage. We chose APOE, ID4, KCNN3 astrocytic proteins for which reliable antibodies were used in combination with OLIG1 and SOX9 transcription factor. We also analyzed the expression of CRYAB (alpha-B crystallin) as this protein was recently described as elevated up to 22-fold in IDH1 mutated tumors (Avliyakulov et al., 2014). Stainings for these 4 proteins were performed in one oligodendroglioma and one astrocytoma tumor with IDH1 R132H and 1p/19q and ATRX mutations respectively. Results presented in figure 1B,C (oligodendroglioma) and figure S3 (astrocytoma) showed that the expression of these 4

proteins were more associated with SOX9 + cells than OLIG1 + cells.

We then performed the same analysis with proteins that are hallmarks of the oligodendrocytic lineage, namely GPR17, PDGFRA and SOX8 (Fig. S1). PDGFRA and SOX8 was clearly more associated with OLIG1+ cells in both astrocytoma and oligodendroglioma (Fig. 2A,B; Fig. S4). For GPR17, its expression was more confined to OLIG1 + cells in the oligodendroglioma whereas a similar expression was found in the SOX9+ and OLIG1+ subpopulations in the explored astrocytoma.

Collectively, these results indicate the presence of at least two cell populations in DLGG

showing an astro and oligo-like phenotype.

Astro-and oligo-like cells have different levels of receptors and pathways

Considering the distinct phenotype of SOX9+ and OLIG1+ cells, we reasoned that these cells might present different active pathways, receptors and neural developmental transcription factors. We started addressing this issue by performing co-stainings for SOX9

and OLIG1 with other transcription factors which are highly expressed by neural precursor cells during brain development (ASCL1/MASH1, SOX2, SOX4). We found that SOX2 was expressed at the same level in both cell types (Fig. S5 and Fig. 3A). On the contrary, ASCL1

and SOX4 expression was clearly more expressed in OLIG1 + cells (Fig. 3 and Fig. S5) for astrocytoma).

We next studied the expression of proteins that are considered as good readouts of activation by Notch1, BMP and ERK/MAP pathways. We previously reported that in glioblastomas, Notch pathway activation led to the upregulation of HEY1 and HEY2 transcription factors (Guichet et al., 2015). This observation led us to assess HEY1 and HEY2 stainings in the two cellular populations. Results presented on figures 4A, D for oligodendrogliomas and figures S6A, D for astrocytoma indicate that HEY1 and HEY2 were preferentially expressed in SOX9 + cells suggesting that Notch signaling activation could be higher in these cells. With regards to the BMP signaling, this pathway is often associated with the generation of astrocytes during brain development and in several pathological situations (Gross et al., 1996;Srikanth et al., 2014). We looked for activation of this pathway by performing co-staining for p-SMAD1/5 and SOX9 and OLIG1. We found that the phosphorylated form of SMAD1/5 was preferentially associated with the SOX9 + population (Fig. 4B, D and Fig. S6B,D). This suggested that DLGG might express BMP RNA and protein. Indeed two-database mining indicate significant upregulation of BMP2 in grade II/III oligodendroglioma and astrocytoma compared to non-tumoral tissue and BMP4 was overexpressed oligodendroglioma in one database (Fig. S7A). Correlation analysis also showed that BMP2 and BMP4 expression are highly correlated in these tumors (Fig S7B .).

We confirmed this result in our samples by qPCR and WB for BMP2 and 4. Results presented in figure S8A show a clear expression of these two BMP members. To study which cell types express BMP2 and 4 in DLGG, we performed IF for these proteins. We could not obtain a reliable staining for BMP2 using different antibodies, however we detected a preferential expression of BMP4 in astrocytic SOX9 + cells (Fig. 4B, D and S6B, D for astrocytoma).

The receptors for EGF (EGFR) and for PTN (PTPRZ1) have important roles in the genesis of gliomas (Ekstrand et al., 1992;Muller et al., 2003;Ohgaki et al., 2004;Pedeutour-Braccini et al., 2015;Ulbricht et al., 2003). We thus examined their expression in the two cell populations. Surprisingly, we found that these two receptors were more expressed in OLIG1 + cells (Fig. 5 andS9). Activation of EGFR activates the ERK/MAPK pathway leading to phosphorylation of the ERK protein (p-ERK). We thus questioned the presence of p-ERK in the two populations by IF. Results presented on figures 4C, D and S6C, D show that the SOX9 + population appears to have higher activation of ERK/MAPK pathway.

All together, these results show that the two detected cell populations in DLGG express different level of receptors and signaling pathways.

Astrocyte and oligodendrocyte-like cells express different level of IDH1 enzyme.

IDH1 is a cytoplasmic enzyme that converts isocitrate into alpha ketoglutarate (Geisbrecht and Gould, 1999). Exploration of mouse and human brain single cell databases shows that RNAs for IDH1 are more present in the oligodendrocyte lineage compared to astrocyte lineage (Fig. S10). This observation prompted us to explore the presence of IDH1 enzyme in glioma SOX9 + and OLIG1 + cells by IF with an antibody raised against the wild type enzyme. Results presented on figures 5A, B and S9A, B show that in the explored oligodendroglioma IDH1 staining was preferentially associated with the OLIG1 + cell population. In the astrocytoma that was studied, this expression bias toward OLIG1 + cell was less pronounced.

Notch1 activation modifies DLGG cells phenotype and reduces their proliferation

The identification of at least 2 clearly distinct cell types in DLGG questioned how these cells are generated. We hypothesized that the Notch and BMP pathways may influence DLGG cell phenotype especially as we found that SOX9 + and OLIG1 + cells have a differential expression of proteins typically involved in these signaling (HEY1/2 and SMAD1/5). To evaluate this possibility, we derived primary cultures from DLGG resections mutated for ATRX and IDH1 R132H (Fig. S11). These cultures were enriched for tumoral cells by magnetic sorting for O4+ antigen that is expressed both by oligodendrocytes and bipotent astro-oligodendrocyte progenitors in brain [START_REF] Trotter | Cells positive for the O4 surface antigen isolated by cell sorting are able to differentiate into astrocytes or oligodendrocytes[END_REF]. The presence of tumoral cells in the cultures was evaluated by IF against IDH1 R132H and ATRX. Resected samples can contain both tumoral and non-tumoral territories in variable proportion especially in supratotal resections (Yordanova and Duffau, 2017) and depending on the samples the percentage of IDH1 R132H + ATRX -cells in the cultures ranged between from 5% to 90%. When few mutated cells were present, the cultures mainly consisted of highly-branched cells with a small nuclei (perimeter =22.95µm ± 0.2621, Fig. S12A)

expressing high level of ATRX, CNP, OLIG1, O4 and SOX10 whereas stainings for IDH1R132H, EGFR, GFAP and SOX9 were rare or absent in these cells (Fig. S12C).

Considering their morphology and their markers these cells are very likely to be non-tumoral oligodendrocytic cells. In culture containing lots of tumoral cells, we noted that these have a larger and often abnormal nucleus (perimeter =30.68 µm ± 0.4316, Fig. S11A), and express high levels of EGFR, OLIG1, SOX9 and weak staining for CNP and SOX10 (Fig. S11C).

Compared to the in vivo situation, we could not identify two clearly distinct SOX9 + and OLIG1 + tumoral cells in these cultures and the majority of cells co-express OLIG1 and SOX9 (Fig. S11C). This could be due to phenotypic modifications induced by cell culture conditions as observed for instance in cultured neural stem cells (Dromard et al., 2007).

To test the influence of the Notch1 pathway on DLGG cells, we selected 4 independent cultures containing >70% of IDH1 R132H and ATRX mutated cells. Cells were infected with a lentivirus expressing the constitutively active form of Notch1 (Notch intracellular domain, NICD) and YFP (Fig. 6A). Transduction of cells with NICD virus strongly upregulated NOTCH-1 mRNA expression. We analyzed by QPCR the expression of some of the genes that we found differentially expressed by SOX9 + and OLIG1 + cells in DLGG tissues. These are ASCL1, EGFR, GPR17, IDH1 OLIG1, PDGFRA, PTPRZ1and SOX4/8 for OLIG1 + cells and APOE, CRYAB, HEY1/2, KCNN3, SOX9 for SOX9 + cells.

OLIG2 gene was also included in the analysis. Results presented on figure 6A indicate that 8/10 of the gene associated with OLIG1 cells were significantly reduced by NICD expression (ASCL1, IDH1, OLIG1/2, PDGFRA, PTPRZ, SOX4/8) while 4/7 of the genes preferentially expressed in SOX9 + cells (APOE, HEY1/2, KCNN3) were significantly upregulated. The influence of NICD on EGFR, GPR17, ID4, SOX9 was highly variable between the cultures and no significance influence of NICD could be detected.

To confirm these results, we used a cell line (named LGG275), which was derived from a DLGG patient with IDH1 and ATRX mutations. This cell line contains bipolar and multipolar cells expressing IDH1 R132H but not ATRX (Fig. S13) and grow very slowly (culture doubling time is approximately 2 weeks). IF on Fig. S13B show that LGG275 cells express both SOX9 and OLIG1 markers together with EGFR and CNP as seen in tumoral primary cultures (Fig. S11). IF against NICD shows a clear nuclear localization of this protein fragment in NICD-transduced cells, which is corroborated, with strong upregulation of Notch1 RNA (Fig. 6B,C). Transduction of these cells with NICD lentivirus, downregulate 8/10 of oligodendrocytic genes (ASCL1, EGFR, IDH1, OLIG1/2, PDGFRA, PTPRZ1 and SOX8) while 5/8 of astrocytic genes (APOE, CRYAB, HEY1/2, KCNN3) was upregulated (n=5, independent experiments). We could confirm the upregulation of CRYAB, HEY1 and KCNN3 proteins by NICD by IF (Figs. 6C and7A). To validate further the influence of Notch signaling, we treated LGG275 cells with two γ-secretase inhibitors that blocks Notch activation: DAPT and LY411575. This resulted in the mild but significant downregulation of APOE and conversely to upregulation of ASCL1, IDH1 and OLIG1/2 (Fig. 6E).

Finally, as we previously found that Notch1 activation drastically reduced the rate of proliferation of glioblastoma stem cells (Guichet et al., 2015), we also assessed the effect of NICD on proliferation of LGG275 cells by measuring the % of Ki67 cells and QPCR. As presented on figure 6C andD, we observed that NICD expression led to a sharp reduction in proliferation. Collectively, these results show a major role for Notch signaling in controlling phenotype and proliferation of DLGG cells.

Notch1 activation modifies electrophysiological properties of DLGG cells

KCNN3 (also known as SK3) is a small conductance K + channel activated by Ca2 + which can be specifically blocked by the bee venom Apamine (Adelman et al., 2012). This channel is highly expressed in the brain but its role in astrocytes and gliomas is currently unknown. To see whether NICD could elicit KCNN3/SK3 current, we performed electrophysiology in LGG275 cells on control or NICD-transduced LGG275 cells. Results presented on figure 7B, showed that in NICD transduced cells, increase of Ca2 + by ionomycin led to an outward K+ current which is blocked by Apamine. This indicates that NICD can induce robust and functional KCNN3 channels in DLGG cells.

Notch1 activation induces Sox9 in human oligodendrocytes

As mentioned before, we did not observe an upregulation of SOX9 by Notch1 activation in

LGG275 cells and tumoral primary cultures (Figs. 6B and6A). We reasoned that in fact, the high level and maybe saturated expression of SOX9 in these cells (Fig. S14C) might preclude a higher expression after NICD transduction. To test this hypothesis, we used primary cultures derived from DLGG supra total resections, which contained mostly (>90%) nontumoral SOX10 high oligodendrocytic cells where SOX9 could be barely detected by IF (Fig. S11C). QPCR for SOX9 validated this low level of expression compared to tumoral and

LGG275 cells (Fig. S13C). As presented in figure S13A, overexpression of NICD in these cells, induced a sharp upregulation of SOX9 that could also be observed at the protein level by IF (Fig. S13B). As seen in LGG275 and tumoral primary cultures, NICD globally also reduced oligodendrocytic genes while increasing astrocytic genes except APOE (Fig. S13A).

BMPs influence on DLGG cells

BMPs proteins are important regulators of neural precursor fate by controlling their phenotype and proliferation (Gross et al., 1996). BMP can also induce astrocytic differentiation of oligodendroglioma propagating cells (Srikanth et al., 2014). Their effect not only hinge on the canonical Smad pathway but also by interacting with the Notch pathway and Hey1/2 transcription factors (Kluppel and Wrana, 2005). The high expression of BMP proteins found in DLGG tumors especially in astro-like cells (Fig. 4B, D and Fig. S6B,D) prompted us to determine the effect of BMP2/4 on LGG275 cell phenotype. The cells were treated with BMP2 or 4 and their phenotype was assessed by QPCR as done for Notch.

Results in figure 8A show that the effects were much less contrasted than for Notch and only OLIG1/2, and APOE were slightly downregulated by both cytokines (Fig. 8A). The only remarkable variation was observed for CRYAB that was upregulated 10 and 2 fold by BMP2 and BMP4 treatment respectively (Fig. 8A). The CRYAB protein not detected in control

LGG275 cells by IF become clearly present in a fraction of cells exposed to BMP2 (Fig. 8B andC). Last, mining of the DLGG TCGA glioma databases (Fig. S7A andB) show that expression of BMP2/4 is highly correlated to the expression of the BMP-inhibitor NOG (NOGGIN) gene. QPCR for NOG in our DLGG samples also confirmed this tight correlation (Fig. 8A). This suggested that BMP2 or 4 cytokines might control NOG expression in DLGG. Indeed, using QPCR, we found that BMP2 was a powerful regulator of NOG with a 30-fold increase. BMP4 could also significantly upregulate NOG however but only 3 fold (Fig. 8A).

Discussion

In this article, we studied tumoral cell heterogeneity in IDH1-mutated diffuse lowgrade gliomas, a subtype of gliomas for which little is known at the cellular and pathway level. We used primary cell cultures, a new cell line and sections directly derived from freshly resected samples so as to maximize relevance to the pathology. We provide evidence for the existence of two main non-overlapping populations in these tumors that can be easily distinguished on the basis of differential OLIG1 and SOX9 expression. We used doublestainings to further characterize these cells and found that SOX9+ cells are related to the astrocytic lineage while OLIG1+ cells are more associated with the oligodendrocyte lineage.

The phenotype of these two cell types is summarized on fig. 9 and differs in several aspects.

At the transcriptional level, astrocyte-like cells express high levels of HEY1/HEY2, ID4 and SOX9 while oligo-like cells display strong stainings for ASCL1/MASH1, OLIG1 and SOX4/SOX8. We also identified that oligo-like cells had higher levels of 3 receptors (EGFR, PDGFRA and PTPRZ1) than astro-like cells. Finally, we observed a higher level of apolipoprotein E (APOE), of BMP4, of small-conductance Ca 2+ -activated K + channel (SK3/KCNN3) and of alpha-crystallin B (CRYAB) in astro-like cells whereas the IDH1 enzyme appears to be more expressed in oligo-like cells. SOX9 + and OLIG1 + cells were observed in 6/6 of the samples that we explored suggesting that there are likely to be present in a majority of DLGG with IDH1 R132H mutation. These 2 cell types account for the majority of tumoral cells but their relative proportion is variable between patients (Fig. 1A and S2A).

Former studies based on electron microscopy (Baloyannis, 1981) and immunohistochemistry of DLGGs (Liang et al., 2005;Rousseau et al., 2006) have described the presence of a phenotypic heterogeneity within tumoral cells. In particular, in oligodendrogliomas, subpopulations of gliofibrillary oligodendrocytes have been reported (Kros et al., 1996), (Matyja et al., 2001), (Herpers and Budka, 1984). While this work was performed, the cellular composition of IDH1-mutated DLGG was also explored using the recent technological approach based on single cell RNA seq (Tirosh et al., 2016;Venteicher et al., 2017). These studies reported the presence of three subpopulations of malignant cells:

nonproliferating cells differentiated along the astrocytic and oligodendrocytic lineages and proliferative undifferentiated cells that resemble neural stem/progenitor cells. Bioinformatics analysis further established the formation of a tumoral lineage in DLGG and enrichment for SOX4 expression in the proliferative undifferentiated subpopulation. Here we found a widespread expression of SOX4 in the tumor, in particular in OLIG1 cells (Fig. 3A andS5A) and so far could not clearly assign this marker to a specific subpopulations acting as a cancer stem cells. Collectively, the present immunofluorescence analysis, former electron microscopic/IHC studies and single cell RNA sequencing approaches all converge to identify the presence of astro-like and oligo-like cells in DLGG. In the normal brain, oligodendrocytes and astrocytes have very distinct properties. For instance, they differ at the metabolic, angiogenic and migration levels. It remains to be established whether oligo-like and astro-like cells found in DLGG show similar dichotomic properties.

One unexpected finding of our study is the highest expression of IDH1 in oligo-like cells than astro-like cells. This was observed using an antibody for the mutated form of IDH1 (R132H) but also confirmed with an antibody against wild type IDH1. In fact, in accordance with these findings, recent databases for single cell RNA analysis of the human and mouse adult brain revealed that IDH1 is more expressed in the oligodendrocytic lineage, especially in immature oligodendrocytes, than in the astrocytic lineage (Fig. S10). We also found that IDH1 expression is negatively regulated by activation of Notch signaling (Fig. 6A) which repress several oligodendrocytic genes in DLGG cells. What could be the function of IDH1 in oligodendrocytic cells? Compared to IDH2 that is located in the mitochondria to generate alpha ketoglutarate and NADH, H+ for Krebs cycle, IDH1 enzyme is located in the cytoplasm where it generates alpha ketoglutarate and NADPH, H+. NADPH, H+ is a key metabolite for lipid and myelin synthesis (Bourre, 1989) and thus the high expression of IDH1 observed in the oligodendrocyte lineage may serve the requirement for a high lipid metabolism in these cells.

Another unexpected finding is the specific expression of CRYAB in astro-like tumoral cells.

This crystallin protein is typically expressed in inflammatory contexts such as multiple sclerosis (Ousman et al., 2007). This small heat-shock protein works as an assembly chaperon and have anti-apoptotic, neuroprotective and anti-inflammatory functions (Zhang et al., 2019). It can accumulate in large amounts in astrocytes in pathological conditions (Iwaki et al., 1989). In cancer, CRYAB can act as an oncoprotein or a tumor suppressor (Zhang et al., 2019). CRYAB is a transcriptional target of BMP signaling in endothelial cells (Ciumas et al., 2013) and accordingly, we found that its strongly upregulated by BMP and NOTCH signaling is DLGG cultures. The link between CRYAB, NOTCH and BMP pathway is also supported by DLGG RNA profile in TCGA database showing a significant correlation 123 between CRYAB, BMP2 and HEY2 (Fig S15A). The role of CRYAB in DLGG cells is not known and remains to be elucidated.

The discovery of astro-and oligo-like tumoral cells prompted us to analyse the expression of the G protein-coupled receptor GPR17 as in the normal human and mouse brain, GPR17 is almost exclusively expressed by oligodendrocyte progenitors and committed oligodendrocytes cells (Lecca et al., 2020). It participates to the differentiation and maturation oligodendrocyte process by binding to several ligands such as leukotrienes and uracil nucleotides. Considering its expression profile, we expected GPR17 to be only expressed in OLIG1+ cells however we found it to be also present in a substantial number of SOX9+ astrocytic cells. In an inflammatory context, GPR17 can be expressed in nonoligodendrocytic cells (Lecca et al., 2020) so a similar phenomenon could occur in DLGG.

Alternatively, astro-like cells could be derived from differentiation of GPR17 + oligodendrocyte progenitors and maintain this marker expression. Whatever its origin and considering that GPR17 activation can impede progenitor differentiation (Lecca et al., 2020), its high expression in astro-and oligo-like cells may contribute to the differentiation blockage observed in DLGG cells (Lu et al., 2012).

The identification of two distinct cell types in DLGG raised the question of what are the molecular mechanisms underlying their formation. We found that the Notch pathway deeply influence DLGG cell phenotype, globally reducing the expression of oligodendrocytic genes and concomitantly increasing two markers (APOE and KCNN3) typically associated with the astrocytic lineage. This was observed using an IDH1/ATRX double mutated cell line we isolated and confirmed with tumoral primary cultures derived from four patients. Using nontumoral human O4-purified cells, we also found that activation of Notch reduced oligodendrocytic gene expression while upregulating KCNN3 and CRYAB. These results are consistent with the literature showing that Notch activation in neural precursor cells promotes astroglial lineage entry (Gaiano and Fishell, 2002) and block oligodendrocyte differentiation (Wang et al., 1998). Considering the high expression of SOX9 in astro-like cells (Fig. 1A and S2A) and that SOX9 is a target of Notch1 during nervous system development (Martini et al., 2013;Muto et al., 2009) and in other non-neural tissues (Capaccione et al., 2014;Shih et al., 2012), we also expected SOX9 expression to be upregulated by Notch activation in our cell line and DLGG primary cultures. This was however not observed in these cells which in fact already expressed a high and may be saturated level of SOX9 (Fig. S13C). This may result from EGF receptor activation by EGF in the media that can upregulate SOX9 as seen in other cell types (Ling et al., 2011). In contrast, in non-tumoral cells oligodendrocytic O4 + cells, which do not express EGFR neither SOX9 (Fig. S10C), both SOX9 gene and protein were strongly induced by Notch activation. To our knowledge, this is the first demonstration of a Notch-induced SOX9 expression in oligodendrocytic cells. Besides modifying their phenotype, we also found that Notch activation impacts electrophysiological properties of DLGG cells. We demonstrated that Notch activation induced the expression of electrophysiologically active KCNN3/SK3 channels in DLGG cells. Considering the high fold change in KCNN3 expression induced by Notch activation in the 3 cell explored cell types (between 20 to 100), it is possible that this channel is a direct target of this pathway.

Ca 2+ activated K+ channels are involved in membrane hyperpolarization but also regulate cellular shape, migration and proliferation (Weaver et al., 2006). Likewise, they may also regulate these properties in DLGG cells. Last, we found that Notch activation reduces cell proliferation in the cell line we isolated. This result is consistent with the work by Giachino et al (Giachino et al., 2015) showing that a PDGF-driven mouse glioma model, genetic activation of the Notch pathway reduces glioma growth and increases survival. Additionally, in oligodendrogliomas, HEY1 and HEY2 showed reduced expression with advanced disease, and tumors with low HEY2 had greater cell density and were more proliferative (Halani et al., 2018). Finally in the TCGA database, expression of the Notch-target HEY1 and HEY2 are reduced in grade III and IV gliomas compared to grade II tumors (Fig S15B).

Collectively, these data fuel the emerging notion that Notch pathway acts as a tumor suppressor in DLGG.

Despite the presence of high expression of BMP proteins in DLGG (Fig. S7A), especially in astro-like cells for BMP4 (Fig. 4B andS6B), the effect of BMP2/4 treatment on the genes we explored was less prominent than Notch. Only induction of CRYAB and NOGGIN were strongly upregulated. The induction of the NOGGIN inhibitor by BMP probably reflects the presence of negative retro control for this pathway in DLGG cells. With regards to CRYAB, BMPs protect endothelial cells from apoptosis, in part, by upregulating CRYAB that acts as an anti-apoptotic factor (Ciumas et al., 2013) and a similar situation could occur in DLGG cells.

Beside Notch and BMP which other pathways could be involved in the generation of SOX9 + and OLIG1 + cells? In a mouse glioma model derived from oligodendrocyte progenitor cells, overexpression of K-RAS and AKT generate tumor with astro-like cells (Lindberg et al., 2014). RAS pathway and its downstream target ERK/MEK are also strong drivers of astrocytic differentiation of normal neural precursor cells (Li et al., 2012) and they positively regulate SOX9 expression in glioma [START_REF] Sabelstrom | Driving Neuronal Differentiation through Reversal of an ERK1/2-miR-124-SOX9 Axis Abrogates Glioblastoma Aggressiveness[END_REF]. Considering the presence of p-ERK in a fraction of DLGG SOX9 + cells (Fig. 4C and S6C), ERK pathway is also a good candidate to regulate DLGG phenotype plasticity.

In conclusion, the identification of astro-like SOX9 + and oligo-like OLIG1 + tumoral cells in DLGG raise several new questions. Do these cells show same sensitivity to treatment? Do they have the same ability to invade the brain, a major obstacle to treat these tumors? Can they interconvert in the tumor? These issues merits further investigation to derive new therapeutic strategies against these tumors.

Materials and Methods

Patient Samples

Tumors samples were obtained from patients of written consents from "Centre de Ressources

Biologiques" located at the Montpellier hospital (see supplemental Table 1). Grade II diffuse low grade gliomas were classified based on WHO (Louis et al., 2016) criteria by a trained neuropathologist (Pr. V Rigau, Montpellier hospital). Tumors were categorized as astrocytoma based on IDH1R132H and p53 staining and loss of nuclear staining of ATRX by IHC and oligodendroglioma based on IDH1R132H mutation and 1p19q codeletion.

IDH1mutation was also confirmed by sequencing of IDH1 gene located on exon 4.

Confirmation of 1p/19q co-deletion was confirmed by molecular detection of loss of heterozygosity using polymorphic markers to screen whole chromosome arms of 1p and 19q as described previously (Goze et al., 2012).

Immunofluorescence on DLGG tissues

Immunofluorescence were performed on frozen tissues that were fixed using 4% paraformaldehyde for 1 hour at room temperature (RT) followed by cryopreservation using successive concentration of 10%, 20% and 30% sucrose solution, each for a period of 24 hours. Tissues were then embedded in Tissue-Tek O.C.T. (Sakura Finetek #4583) and frozen on Isopentane using SnapFrost 80 (Alphelys). Tissues were sectioned into 10-µm thickness using Leica CM3050S. They were incubated with 0.1M PBS-Glycine for 30 minutes with change of solution every 10 minutes, to reduce the background signal. Permeabilization and blocking were performed together using 0.3% Triton X-100 and 10% Donkey serum (Sigma) respectively for 1 hour at RT in a humid chamber followed by primary antibody incubation using respective antibodies overnight at 4°C. Secondary antibody incubation was performed at RT for 1-hour using Alexa antibodies 488 or Cy-3 (Jackson ImmunoResearch). Incubation of tissues using secondary antibodies without a primary antibody has been used as a negative control, each time when required. Nucleus has been counterstained using Hoechst 33342 and mounted using Fluoromount-G (Thermo Fisher) solution. Sections were imaged using Zeiss Apotome 2 microscope at 40X magnification. Two individuals performed counting manually independently. Minimum of 300 cells have been counted to distinguish two non-overlapping cell populations in each tumor tissues analysed. For the analysis of cellular markers, signaling molecules and receptors expressed by each subpopulation, a minimum of 100 cells each of SOX9 + and OLIG1 + are counted to calculate the percentage of their specific expression.

Cell purification of O4 + tumoral cells from fresh DLGG tissues

Freshly resected tumor piece were chopped finely using a scalpel and dissociated using a combination of enzymes-Trypsin (Sigma #T4799, 13-mg/ml), Hyaluronidase (Sigma, #H3884, 7-mg/ml) and DNase I (Roche, #10104159001, 10-mg/ml). The amount of enzyme used was determined each time according to the tumor size obtained. For example: 130µl of Trypsin, 130 µl of Hyaluronidase and 25µl of DNase I was added to 500µl of HBSS -/-to dissociate 40mg of tumor piece. Tissue dissociation was performed in a sterile water bath at 37°C for around 45 minutes to 2 hours, until maximum tissue get dissociated. After dissociation, cell suspension is diluted in HBSS -/-and centrifuged at 380*g for 5 minutes. The cell pellet was then resuspended in 600µl of HBSS-/-with 20µl of Trypsin Inhibitor (Sigma, #T9003, 50-mg/ml) or proportionally increased according to pellet size. Single cell suspension is collected using a 70µm cell strainer (MACS SmartStrainer, #130-098-462).

Strainer is washed with 3ml HBSS-/-and centrifuged at 380*g. To remove myelin and red blood cells, we used a two-step percoll (Sigma, #GE17-0891-02) density gradient method. To remove myelin, percoll solution is prepared in a final concentration of 33% Percoll and 66% HBSS -/-in a volume sufficient enough for the cell pellet to be resuspended. The centrifugation was carried out at 800*g for 30 minutes. A white layer of myelin forms on the surface of the cell suspension. Myelin and supernatant are aspirated using a suction pump and the pellet is resuspended in 66% percoll and 33% HBSS -/-. Centrifuge at the same speed as above for 10 minutes. In this step, red blood cells form a pellet at the bottom and cells of interest are in the suspension. The cell suspension is collected and washed with 5 times more of HBSS -/-to dilute the excess percoll and centrifuged at 300*g for 20 minutes. Then cell purification using O4-microbeads antibody purchased from Miltenyi Biotech (#130-096-670) is carried out as per Manufacturer's protocol. To avoid the possible contamination of microglia cells in the purified culture, we performed magnetic purification using CD11b microbeads prior to O4 cell purification. The purified O4+ cells were grown as adherent cultures on coverslips coated with Poly D-lysine (Sigma, #P7886; 25-µg/ml) and Laminin (Sigma, #L2020-1MG, 2-µg/cm 2 ). Cells were cultured in DMEM/F12 1:1 media (Gibco) supplemented with N2 (Thermo Fisher, #17502048), D-glucose (Sigma, 0.6%), L-glutamine (Thermo Fisher, #25030024, 2mM) B27 w/o vitamin A (Invitrogen) and growth factors such as EGF (Peprotech, 20-ng/ml), FGF (Peprotech, 10-ng/ml), PDGFA (Peprotech, 20-ng/ml) and Heparin (Sigma, 2-µg/ml). Cells were maintained for about 2 weeks before they were used for further experiments.

Immunofluorescence on O4 cells and LGG 275 cells

The cells in culture were fixed using 4% Paraformaldehyde for 20 minutes. Permeabilization and blocking were performed using 0.1% Triton X-100 and 5% donkey serum for 1 hour at RT. Primary antibody incubations were performed overnight at 4°C. Alexa 488 and/or 596 secondary antibodies were incubated for 1 hour at RT following which nuclear staining was performed using Hoechst 33342. In case of staining of O4, immunofluorescence was performed without the permeabilization step, but blocking for 1hour using donkey serum and continuing with the remaining steps. In case of double staining of a nuclear marker with O4, staining for O4 is completed until the secondary washes followed by permeabilization and blockage of the cells and continuing with the usual steps of immunostaining. Individual stainings on primary cultures are performed on a minimum of 3 patient samples. Images were taken using Zeiss Apotome Z2 microscope at 40x magnification.

RNA extraction and qPCR

Purified O4 cells cultured in vitro for about a week and LGG 275 cells were infected with either a control-YFP or NICD-YFP virus. On Day-5 after transduction, cells are lysed and RNA was extracted using Arcturus Picopure RNA extraction kit (Thermo Fisher, #15295033) following Manufacturer's protocol. Subsequently, 100-200µg of cDNA was synthesised with random primers and reverse Transcriptase (Promega, GoScript). Quantitative PCR was performed using 2.5µg of cDNA per reaction and was repeated in duplicates. Primers were purchased from Sigma-Aldrich (See Supplementary Table No. 3 for the list of primers used).

KAPA SYBR PCR KIT (Sigma, #KK4610) was used for qPCR and was measured using Light Cycler 480. Gene expression was calculated using 2 -ΔΔCt method. B-actin (ACTB) has been used as the housekeeping gene for the experiments. QPCR was performed on O4 cultures from 4 patient samples with tumoral cells and 3 cultures of non-tumoral cells. In DLGG 275 cells, 5 independent experiments have been performed. Unpaired t-test was used for statistics calculations using GraphPad.

LGG 275 cells were treated with g-secretase inhibitors-DAPT and LY411575 at 10µM for 5 days before RNA was extracted for qPCR (N=2). For qPCR experiments with BMP signaling, cells were treated with 10ng of BMP-2 or BMP4 for 5 days with addition of new cytokine every 2 days (N=3).

Measuring KCNN3 channel activity following Notch-1 activation on LGG 275 cells

The LGG 275 cells were transduced either with control-YFP or NICD-YFP in a 24-well plate. 3 days after the infection, cells were used to measure the activity of KCNN3 channels. Current analysis was performed using Clampfit version 10 (Axon Instruments).

Western Blotting

Tissue samples were lysed using RIPA lysis buffer (Sigma) consisting of 50 mM Tris-HCl pH 8.0, 150 mM NaCl, 1% NP40, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulfate, 5 mM sodium fluoride, 0.5 mM sodium vanadate, and 13-protease inhibitor cocktail (Roche).

Samples were incubated on ice for 30 minutes followed by centrifugation at 13, 000 rpm for 20 minutes at 4°C. Protein concentrations were determined using DC protein Assay (bioRad).

Samples were mixed with Laemmli Buffer and proteins were separated by SDS-PAGE and further blotted on 0.2mm PVDF membranes (BioRad). Blocking was performed by incubating the membrane in 5% nonfat dried milk in TBST (Tris-buffered saline, 0.1% Tween 20) for 2 hours followed by primary antibody incubation using respective antibodies at 4°C. After rinsing the membranes in TBST, blots were incubated with peroxidase secondary antibodies at room temperature for 1 hour. Images were captured using ChemiDoc TM XRS Imaging system.

Statistical Analysis

Immunofluorescence data on DLGG tissues are presented as pie diagram. GraphPad 6 was used for statistical analysis. Unpaired t-test with equal standard deviation was used for qPCR analysis. *, **, *** represent p < .05, <0.01, and <0.0001, respectively. highest expression in newly formed oligodendrocytes while expression in astrocyte is very low. In human brain, highest expression is observed in PDGFRA + oligodendrocyte cells (OPC). Mice brain transcriptomic data used to draw these histograms were obtained from (http://mousebrain.org/) (Zeisel et al., 2018) and (https://celltypes.brain-map.org/rnaseq/human_m1_10x) (Hodge et al., 2019) respectively. The different cell categories are those that are indicated on the database websites. Unpaired t-test is used for significance calculation. The expression of SOX9 was higher in tumoral cells. The number of cases is indicated in brackets. These scatter dot diagrams and correlation matrix were created with the database mining website GLIOVIS (Bowman et al., 2017). (Chen et al., 2009;Ou et al., 2016) PTPRZ1 Oligodendrocytes (Lamprianou et al., 2011) Supplementary Table 3: PCR primer pairs used for quantitative RT-PCR. (A) RNA levels for BMP2, BMP4 and NOGGIN in non tumoral brain, oligodendrogliomas, astrocytomas and oligoastrocytomas in Rembrandt [START_REF] Madhavan | Rembrandt: helping personalized medicine become a reality through integrative translational research[END_REF] and Kamoun (Kamoun et al., 2016) Single cell transcriptomic data from adult mice and human brain reveals oligodendrocytic specific expression of wildtype IDH1. In mice, oligodendrocytic cells of different developmental stages express IDH1 with highest expression in newly formed oligodendrocytes while expression in astrocyte is very low. In human brain, highest expression is observed in PDGFRA + oligodendrocyte cells (OPC). Mice brain transcriptomic data used to draw these histograms were obtained from (http://mousebrain.org/) (Zeisel et al., 2018) and (https://celltypes.brainmap.org/rnaseq/human_m1_10x) (Hodge et al., 2019) respectively. The different cell categories are those that are indicated on the database websites. Unpaired t-test is used for significance calculation. The expression of SOX9 was higher in tumoral cells. The number of cases is indicated in brackets. These scatter dot diagrams and correlation matrix were created with the database mining website GLIOVIS (Bowman et al., 2017).

Gene Forward primer Reverse primer ACTB

Results

Collaborations during PhD

Transformation Foci in IDH1-mutated Gliomas Show STAT3 Phosphorylation and

Downregulate the Metabolic Enzyme ETNPPL, a Negative Regulator of Glioma Growth

This project was collaboration within our team and the goal was to characterize the transformation foci identified in DLGG tissues that are regions of hypercellularity, indicative of anaplastic transformation. Previous study from our team has identified these foci in 20%

patients and was correlated with worse prognosis compared to foci-free patients. These transformation foci contained cells with higher mitotic index and hypoxia factors (HIF-1α) {Pedeutour-Braccini, 2015 #1865}. Using Immunohistochemistry (IHC) and high throughput RNA profiling, we characterized cellular markers and pathways specific to these regions and identified a metabolic enzyme, Ethanolamine-Phosphate Phospho-Lyase (ETNPPL) as a negative regulator of glioma growth.

Using IHC, we observed that ETNPPL could be located either in nucleus or cytoplasm of cells in FFPE samples. I contributed to this project in understanding the specific localization of ETNPPL to the tumor cells. To do so, I performed immunostaining of ETNPPL on oligodendroglioma and astrocytoma tissues with IDH1R132H or ATRX proteins. We observed that ETNPPL could be expressed either in nucleus or cytoplasm of tumor cells. As ETNPPL is a least studied protein, we confirmed the specificity of the staining using a second antibody and repeated the stainings in different patient samples. Also, I used 2 primary cultures of DLGG cells to examine the expression pattern of ETNPPL in vitro. We observed that most of IDH1R132H positive tumor cells in culture showed a cytoplasmic localization invariably. I was also involved with the project during its revision to refine some of the experiments performed on ETNPPL overexpressed cell line. This work has been recently published in Scientific Reports [START_REF] Leventoux | Transformation Foci in IDH1-mutated Gliomas Show STAT3 Phosphorylation and Downregulate the Metabolic Enzyme ETNPPL, a Negative Regulator of Glioma Growth[END_REF] and I am the second author (manuscript below).

gliomas are divided into astrocytomas and oligodendrogliomas as tumoral cells look like normal brain astrocytes or oligodendrocytes 2 . However, recent works based on single-cell RNA-sequencing approaches have revealed that diffuse low-grade gliomas are in fact composed of at least two tumoral cell types with similarities to astrocytes and oligodendrocytes 3,4 . With regards to the mutational landscape, one recurrent DNA alteration found in 80% of patients is a missense mutation for the IDH1 gene (isocitrate dehydrogenase) involved in metabolism and epigenetic regulations 5 . Astrocytomas have an additional mutation for the ATRX gene whereas oligodendrogliomas show a 1p19q co-deletion. These mutations negatively influence the differentiation of progenitors which then accumulate in the brain. Treatment of these tumours consists of a maximal surgical resection often performed in awake-condition so as to preserve brain functional areas 6 . However, owing to the infiltrative nature of these tumours, it is not possible to remove all tumoral tissue and the tumour inexorably relapses. After an initial slow growth (2 mm per year), diffuse low-grade gliomas inescapably progress into rapidly-growing tumours, namely grade III gliomas or glioblastomas. The mutational landscape of these high-grade gliomas derived from low-grade lesions has been fully explored recently 7,8 . This malignant transformation then leads to rapid patient death. The duration of transition from low-grade to high-grade glioma is highly variable between patients. This can be very short (6 months) or very long (>15 years). Currently, there is no good predictive tool to evaluate this time and this poses important problems for clinicians to monitor the patients and give appropriate treatments. If patients could be identified with increased risk for progression, they might be offered early adjuvant treatment or targeted new therapeutic approaches. In order to do so, we need to understand in depth, the early molecular mechanisms by which an initial diffuse low-grade glioma progresses into a higher grade, a process which is still unclear. One major difficulty to characterize this initial malignant progression is to be able to capture the key transformation steps occurring in the tumour. We attempted to fill this gap by extensive examination of diffuse low-grade glioma sections. This led us to identify foci of hypercellularity in diffuse low-grade gliomas 9 . These foci are present in 20% of patients. Importantly, these patients have a worse prognosis compared to foci-free patients. We reported a first partial characterization of the cellular and DNA alterations found in these foci using IHC and FISH. We found that foci cells 1-have a higher mitotic index (Ki67 + cells) and vascular density, 2-can show sign of hypoxia (HIFα staining), 3-can have frequent chromosome 7 polysomy as well as higher intensity for EGFR and AKT stainings compared to the rest of the tumour. These alterations strongly suggest that these foci are composed of cells undergoing further transformation events.

In this article, we wanted to understand further how diffuse low-grade gliomas progress into high-grade gliomas by characterizing early histological signs of transformation. We thus focused our study on these foci which are likely candidates of early transformation. Our objectives were 1/to study pathways which might allow formation of these foci, 2/to identify genes whose expression is dysregulated in these foci, 3/to perform functional analysis of one identified gene in vitro. We used IHC and high throughput RNA profiling to characterize these foci in 8 tumours. This led us to identify a metabolic enzyme (ETNPPL, Ethanolamine-Phosphate Phospho-Lyase) which was further studied at the functional level.

Material and Methods

Selection of patients.

All methods and all experimental protocols used in this article were carried out and approved in accordance with relevant guidelines and regulations of the French "Institut National de la Santé et de la Recherche Médicale" (INSERM). Glioma samples were obtained from the "Centre de Ressources Biologiques" (Collection NEUROLOGIE ( 8) DC-2013-2027/DC-2010-1185/Authorization AC-2017-3055/Research Protocol P487) and our research approved by the Institutional Review Board (2019_IRB-MTP_10-15) of the Montpellier Hospital. Informed and written consents were obtained from the patients before using their samples. Gliomas were graded by a neuropathologist (Pr V. Rigau) and cases with foci were selected according to criteria reported in 9 e.g. ( 1) higher cellular density compared to the rest of the tumour, (2) nuclear atypia with or without anisocaryosis, (3) enhanced vascularization of the foci with early signs of endothelial proliferation. Clinical and tumour pathological features are summarized in Table S1. For RNA extraction, samples were obtained from patients who had a first surgery and no pre-operative therapies. IDH1 mutation was established by immunohistochemistry against the IDH1 R132H epitope with at least 80% of positive cells in both DLGG and foci for each tumour. IDH1 mutation was then confirmed by sequencing of the IDH1 gene exon 4. 1p/19q mutation was identified by molecular detection of loss of heterozygosity using polymorphic markers to screen both whole 1p and 19q chromosome arms as described in 10 . ATRX mutation was established by loss of nuclear staining with IHC using ATRX polyclonal antibody (SIGMA Ref HPA001906). To explore the expression of ETNPPL by immunofluorescence in the non-tumoral human, we used a cortical sample removed during neurosurgical approach for meningioma resection.

Immunohistochemistry (IHC) and Immunofluorescence (IF).

All antibody references and dilutions are indicated in Table S2. IHC for pSTAT3 and ETNPPL were performed on paraffin-embedded tumours fixed with formalin 37% (FFPE) for 1 day. Stainings were done using 4 µm sections and the Leica Biosystems' Bond Polymer Refine Detection kit (DS9800) after suitable epitope retrieval with citrate buffer and according to manufacturer's protocol. Immunofluorescences were done on frozen sections of tumours fixed with paraformaldehyde 4% for 1 hour and cryopreserved in successive sucrose solutions (10%, 20%, 30%, 24 h each). Sections (10 µm) were permeabilized and saturated with 3% triton X-100 and 10% donkey serum diluted in PBS 1X and then incubated overnight with primary antibodies. Secondary conjugated antibodies Alexa 488 or Cy3 (Jackson & Molecular Probe) were incubated for 90 minutes. Incubations without primary antibody or with antibodies against GFP were used as negative controls to avoid misinterpretation due to the presence of autofluorescent compounds (lipofuscin). To check ETNPPL antibody specificity, the blocking peptide (Novus NBP1-91655PEP) was incubated with the antibody (ratio of 10:1 peptide/antibody) at room temperature for one hour before the staining.

Equipment and settings. Bright field images were taken with a Nikon Eclipse microscope and a NIH-elements software using standard settings. Fluorescent images were taken with a Zeiss apotome Axio Imager 2 equipped with a Zeiss ZEN software. Main settings were: binning 2 × 2, apoptome mode: 5. Quantifications were obtained by two investigators (N.L., M.A.) on image captures and with ImageJ software manual cell counting tool. For western blots, proteins were detected using an Odyssey CLx Li-Cor apparatus and accompanying software. Exposure times were 7 minutes.

RNA profiling.

Tumours with foci of at least four millimeters in diameter, assessed by hematoxylin & eosin stainings and with at least 80% of IDH1 R132H positive cells were selected. Four drills (two in foci and two in the other part of the tumour -Fig. S2B) were performed in the FFPE tumour blocks using a two millimetres punch from a Tissue Micro Array apparatus (Master 3DHistech LTD, Hungary) in RNAse-free conditions. After the punches, the adequate selection of tumour areas was checked by hematoxylin & eosin stainings of sections (Fig. S2B). Total RNA was extracted using the Qiagen RNeasy FFPE kit, quantified with Nanodrop 1000 (Thermo Fisher) and the RNA integrity number (RIN) was determined using a Bioanalyzer 2100 (Agilent Technologies). The RIN was on average 2.5 thus indicating degraded RNA. This was expected using FFPE samples but the RNA were still suitable for labelling and hybridization on DNA chips according to the Affymetrix technical department. After amplification and labelling with an Affymetrix WT Pico Kit, cDNA were hybridized on Human Gene 2.1 ST chips. Arrays CEL files were processed with Affymetrix Expression Console software (GC-RMA (Robust Multiarray Average) algorithm) and Affymetrix Transcriptome Analysis Console (TAC 3.1.0.5) softwares. Array CEL files were also analyzed in parallel using R software 3.6. In that case, files were preprocessed by RMA algorithm from the Oligo R Package version 1.48.0. Then Limma package version 3.40.6 was used to identify genes differentially expressed. Genes identified both by Transcriptome Analysis Console 3.1.0.5 and Limma algorithms and with a p-value ≤ 0.05 (unpaired tests) and a fold change ≥1.3 (DLGG/foci) were considered as differentially expressed (Table 1). The raw data that support the findings of our study are openly available at the functional genomics data Gene Expression Omnibus (GEO: GSE130149).

RT-qPCR. cDNA synthesis was performed using 1-5 µg of total RNA with random hexamers and reverse transcriptase (Promega, GoScript). Quantitative RT-qPCR was performed in triplicate for each tumour sample using the KAPA SYBR PCR kit (Sigma Aldrich KK4600) with a LightCycler 480 apparatus (Roche). 1 µL of cDNA was used for each reaction. Primers are listed in Table S2. Expression values were calculated using the 2 -∆∆CT method and normalized using the housekeeping gene RPLP0.

Comparative genomic hybridization array (CGHa). The LGG85 cell line was established from a male

patient diagnosed with a grade-IV IDH1-mutated glioma with culture conditions used for Gli4 and Gli7 glioblastoma cell lines 11 . Array CGH profiling for the LGG85 line and from the original tumour were performed with the Human Agilent Sureprint G3 8 60 K Microarray Kit (Agilent Technologies, USA). LGG85 DNA was labelled with cyanin 5 (Cy5) while reference DNA from a male subject was labelled with cyanin 3 (Cy3). Sample and reference DNAs were pooled and hybridized for 24 hours at 67 °C on the arrays. The fluorescence was read by the Agilent SureScan Microarray scanner and the Cy5 /Cy3 ratios were converted into log2 transformed values with the Agilent Cytogenomics software. DLRS (Derivative Log Ratio Spread), gRepro, rSignalIntensity and LogRatioImbalance were 0.2, 0.009, 450.68 and -0.1 respectively. A single copy loss was associated with a value of the log2 below -0,8 (log2 (1/2) = -1) since a single copy gain was associated with a value of the log2 above 0,5 (log2 3/2) = 0,58).

Lentiviral vectors and glioma cell culture.

To study the effect of ETNPPL overexpression, we designed two lentiviral vectors combining an EGFP-T2A-Puromycine resistance gene and the coding sequence for Human ETNPPL or Luciferase, controlled by a doxycycline-regulated Tre3G promoter (Vectorbuilder). A third lentivirus was built to express a blasticidin resistance gene and the doxycycline-regulated Tet-on activator. Mycoplasma-free Gli4, Gli7 and LGG85 cells were cultured as described 12 on poly-HEMA coated vessels and in defined media (DMEM/F12 1:1 (Invitrogen) supplemented with N2 (Invitrogen), 2 mM glutamine (Invitrogen), 2 µg/mL heparin (Sigma), 10 ng/mL EGF (Peprotech) and 10 ng/mL FGF2 (Peprotech)). 100,000 dissociated cells were infected with the Luciferase-EGFP or ETNPPL-EGFP viruses (MOI 7), grew for two weeks and transduced cells were selected by sorting for green fluorescence (GFP) (Aria cytometer BD). Cells were then infected with the Tet3G lentivirus and selected for 2 weeks with blasticidin (0.5 µg/mL). ETNPPL expression was induced by doxycycline 1 µg/mL and checked with ETNPPL antibody by WB and by immunofluorescence on cells seeded on poly-D-lysine/laminin coated coverslips. Effect of ETNPPL on cell growth was measured by seeding 5,000 infected cells per well in 1 mL of media in 24-well plates. After 8 days, the number of cells were determined by dissociation with trypsin and automatic counting with Z2 counter (Beckman Coulter). For EdU incorporation, cells were incubated with EdU 10 µM for 4 hours and processed for staining following manufacturer's recommendation (Baseclick kit). Explant cultures of IDH1-mutated diffuse low-grade gliomas used to explore the expression of ETNPPL are described in 12 .

Western blots. Total proteins from tissue samples and cultured cells were obtained and used for Western Blot as described by 12 . Proteins were detected using the Odyssey CLx Li-Cor technology. Briefly, primary antibodies were incubated in Li-Cor PBS buffer overnight at 4 °C. After washing, membranes were incubated with secondary fluorescent dye (IRDye 800CW for ETNPPL and IRDye 680LT for β-actin).

Statistical analysis and countings.

All statistical tests used and sample sizes (n) are indicated in the figure legends. Tests were performed using the GraphPad Prism software (v8.2.1). Significances: ****, ***, **, * represent p < 0.0001, p < 0.001, p < 0.01 and p ≤ 0.05 respectively. For cell countings, at least 5 independent fields of 10,000 µm² were counted. The effect of ETNPPL overexpression in Gli4, Gli7 and LGG85 cell was performed in 3 independent experiments.

Results

Foci show activated STAT3 pathway and dysregulated gene expression.

To molecularly characterize foci found in DLGG patients (Fig. 1A), we selected 8 tumours with mutations for IDH1 (IDH1 R132H) with and without 1p19q co-deletion (4 oligodendrogliomas and 4 astrocytomas respectively) (Table S1). These 8 cases contained foci which were selected on the basis of a local increase in cell density (Figs. 1A,S1). During tumorigenesis, canonical pathways controlling cell proliferation and fate are frequently dysregulated. We explored this possibility by using IHC for Notch, STAT3, BMP, and Ras signalings. We assessed the expression and subcellular location of key proteins for these pathways, respectively activated Notch (NICD), pSTAT3 (phosphorylated on tyrosine 705), BMP4 and p-ERK. Only pSTAT3 stainings showed a clear modification in the foci compared to the rest of the tumour (Fig. 1B). The eight studied tumours showed a small number of scattered pSTAT3 + cells, however a sharp and statistically-significant increase of their percentage was observed in foci (Fig. 1B). To ascertain that these cells were tumoral and not cells of the tumour environment, we performed double labelling for pSTAT3 and proteins which are frequently altered in DLGG, namely the mutated form of IDH1 (R132H) and loss of ATRX. In the 4 examined oligodendrogliomas (Fig. 1C), we found that >90% of pSTAT3 + cells in the foci or in the rest of the tumour also expressed the mutated form of IDH1 R132H. Expression of IDH1 R132H assessed by IF in the astrocytomas was too weak to perform reliable double pSTAT3/IDH1 R132H stainings so, as an alternative, pSTAT3/ATRX stainings were done. Figure 1C shows that in the 4 astrocytomas, most of pSTAT3 + cells in or outside the foci have lost ATRX expression (>90% of cells). Taken together, these results provide evidence that tumoral cells in foci increase STAT3 signaling.

We then investigated whether we could identify genes whose expression is specifically dysregulated in foci compared to the rest of the tumour. We used FFPE blocks to microdissect a tumoral region within or outside the foci for the 8 tumours (Fig. S2B). RNAs were extracted and profilings were performed. The RNA quality obtained from hospital FFPE blocks precluded the use of a RNA sequencing approach so DNA microarrays were used instead. Clustering analysis performed with the 5,000 top-expressed genes indicates that the tumour and its foci (with the exception of tumour 3) are closely transcriptionally-related and cluster together (Fig. S3).

To identify differentially-expressed genes, the statistical analysis was performed using the 8 tumours together to increase statistical power. A fold change value of 1.3 was selected as a more selective threshold retrieved very few genes. Table 1 shows a list of the 13 identified genes. All were downregulated in foci. Literature analysis shows that these genes are implicated in various pathways and cellular processes such as Wnt signaling (DAAM2, SFRP2), glutamate transport (SLC1A3), metabolism (ALDOC, ETNPPL), cytoskeleton (EZR), cell-cell adhesion (GJA1) and cyclic AMP pathway (ADCYAP1R1).

In order to validate these results with an independent approach, we performed RT-qPCR on 10 tumours (those used for RNA profiling + 2 additional tumours). We selected 7 genes which are involved in EGFR signalling (MLC1), metabolism (ALDOC, ETNPPL), Wnt signaling (SFRP2), protease inhibition (CST3), skeleton function (EZR) and glutamate transport (SLC1A3). Figure 2A shows a significant downregulation of these 7 genes in the foci of the 10 analysed tumours. These results corroborate those obtained with the DNA microarray technology.

There was a possibility that the genes identified as differentially-expressed were in fact the consequence of a different number of non tumoral cells (for instance immune or stromal cells) in foci areas versus the rest of the tumour. We explored this hypothesis using two approaches. First we measured the percentage of tumoral cells in or outside the foci with IHC against IDH1 R132H (Fig. S2A). We found that both areas were mainly composed of tumoral cells (>80%) and no statistically-significant difference can be detected (Fig. S2C). Second, we used a bioinformatics approach using gene expression signatures to infer the fraction of stromal and immune cells in Expression of indicated genes in grade II and grade III gliomas retrieved from the TCGA database. A similar analysis done for all identified genes is presented in Table S3. OII (Oligodendroglioma grade II, 108 patients). OIII (Oligodendroglioma grade III, 76 patients). AII (Astrocytoma grade II, 87 patients). AIII (Astrocytoma grade III, 98 patients). Tests = Kruskal-Wallis with a Dunn post-hoc test.

G Gc i G G c i G Gc i G G c i D L F o D L F o D L F o D L
tumour samples as described in 13 . This method called ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumours using Expression data) calculates scores (between 0 and 1) predictive of tumour infiltration by stromal and immune cells and consequently, of tumour purity. All samples (8 tumours + 8 foci) were analyzed by ESTIMATE and results presented in Fig. S2D show that tumour and foci purity were very high (>0.8). No statistical differences in purity could be detected between the tumour and the foci areas (Fig. S2D). These analyses indicate that the genes identified as differentially-expressed genes are very likely expressed by tumoral cells. We then explored whether the genes dysregulated in foci were also differentially-expressed with tumoral progression. To this aim, we retrieved the expression value for the 13 identified genes from the cancer genome atlas (TCGA) 14 in grade II and grade III gliomas. Statistical analyses performed in IDH1-mutated tumours show that these genes were differentially-expressed between both type of grade II and III gliomas (Table S3). Examples of TCGA gene expression for the 7 quantitative PCR-validated genes (Fig. 2A) are presented on Fig. 2B.

These results suggest that the observed dysregulation of genes in foci account for a malignant progression taking place in this part of the tumour.

Glioma cells express the ETNPPL lipid metabolism enzyme. Lipid metabolism is altered in cancer cells 15 . The expression of a lipid metabolic enzyme called Ethanolamine-Phosphate Phospho-Lyase (ETNPPL, also known as AGXT2L1) was found reduced in foci (Table 1). ETNPPL is involved in the catabolism of phosphoethanolamine (Fig. S4A), a key compound for the synthesis of phosphatidylethanolamine which is a major phospholipid of the cellular membrane 16 . ETNPPL is mainly expressed in brain and in liver according to NCBI gene database (Fig. S4B) 17 . In human brain, its expression appears to be restricted to mature astrocytes (Fig. S4C) 18 . Little is known about ETNPPL (13 publications) and a potential link with brain tumours has not been established. This prompted us to explore the expression and role of ETNPPL in the human brain and gliomas. We started by performing IF for ETNPPL using one human cortical sample removed during neurosurgical approach for meningioma resection. The ETNPPL protein was detected by a fraction of cells either in the nuclei or in the cytoplasm (Fig. 3A, left-hand and central images). Immunofluorescence specificity was assessed by loss of signal if the antibody is pre-incubated with an ETNPPL peptide (Fig. 3A, right-hand image). To confirm the preferential expression of ETNPPL in astrocytes, double immunofluorescences were performed for four astrocytic markers (ALDH1L1, CHI3L1, GFAP, VIM). A very large fraction of ETNPPL + cells (>95%, >450 cells counted for each markers) were positive for these four markers (Fig. 3B). Surprisingly for a metabolic enzyme, ETNPPL staining was located in the cell nuclei. ETNPPL antibody quality was indicated by the presence of a band at the expected size (55 kDa) on a western blot (WB) performed with DLGG extracts (Fig. 4A). These results confirmed the astrocytic expression of ETNPPL as suggested by RNA expression databases. We then analyzed ETNPPL expression in diffuse low-grade gliomas samples. By WB, ETNPPL was detected as a single band in 5 of the 6 analyzed grade II tumours (Figs. 4A and S8A). By IHC and reminiscent of what was observed in the normal brain, ETNPPL was detected either in the cytoplasm or the nuclei of the cells in one grade II astrocytoma (Fig. 4B). DLGG can contain normal and mutated cells so it was important to establish that ETNPPL + cells were tumoral. This was addressed by performing double IF for ETNPPL and IDH1 R132H (1 oligodendroglioma) and ATRX (2 astrocytomas). As mentioned previously, expression of IDH1 R132H assessed by IF in the astrocytomas was too weak to be quantified accurately. In the oligodendroglioma (Figs. 5A,C, S6A,B), we found that >95% of ETNPPL + cells also expressed the mutated form of IDH1 R132H. Figure 5B-C shows that in the 2 astrocytomas, most of ETNPPL + cells have lost ATRX expression (>95% of cells). We also examined the ETNPPL expression in gliomas cells using DLGG primary cultures (Fig. 5D). In the two explored cultures, most of IDH1 R132H + cells (>90%, 150 cells counted) co-expressed ETNPPL. In these 2 patients, the protein was mainly in the cytoplasm.

The ETNPPL expression in diffuse low-grade glioma cells was also validated using a second antibody (HPA072938) directed against another part of the protein (Table S2). The quality of this antibody was checked by WB and immunofluorescence with ETNPPL-overexpressing cells (see below) (Fig. S7A,B). Either cytoplasmic or nuclear expression of ETNPPL was detected in tumoral cells identified by the expression of IDH1R132H in one oligodendroglioma (Fig. S7C). ETNPPL was also detected with this antibody in the cytoplasm or the nucleus of diffuse low-grade gliomas cells in culture (Fig. S7D).

All together, these results demonstrate that ETNPPL is expressed by tumoral cells in DLGG.

Foci and high-grade gliomas have a reduced expression of ETNPPL. Microarray and qPCR anal-

yses indicate that ETNPPL RNA is reduced in the foci (Table 1, Fig. 2A). First, we validated this at the protein level using IHC in seven DLGG containing foci. Figure 6A,B shows a significant reduction of the percentage of ETNPPL + cells in the foci even if its expression is highly variable between tumours. Second, we also explored glioma databases for the expression of ETNPPL in different tumour grades. All three databases (TCGA, Rembrandt and NCBI dataset GDS1962) showed a sharp reduction of ETNPPL RNA in high-grade tumours compared to low-grade tumours (Fig. S4D) 14,19,20 . We confirmed this decrease by using IHC in a glioblastoma tumour.

Result presented on Fig. 6C shows the absence of ETNPPL in this tumour. To validate this further, we used proteins extracted from one grade III astrocytoma and six GBM and compared with grade II tumours using WB. Figure 4A and Fig. S8A indicate that ETNPPL was absent or low in the 6 GBM samples whereas the protein was readily detected in 5 of the 7 non-GBM tumours.

Collectively, these data show that ETNPPL is expressed in diffuse low-grade tumours and is reduced with malignant progression.

ETNPPL reduces glioma cell growth. The reduction of ETNPPL in high-grade gliomas suggested that this enzyme might oppose proliferation which is enhanced in these tumours. We addressed this issue by performing gain of function experiments in three glioma cell cultures. We used two previously characterized glioma stem cell cultures (Gli4 and Gli7) which we derived from GBM-affected patients 11 . In order to use cells bearing mutations typically found in DLGG, we derived a third culture named LGG85 from a patient affected by a secondary GBM and containing a mutated IDH1 gene. LGG85 cells grow as neurospheres, express nestin (NES), an intermediate filament specific for neural immature cells, as well as two transcription factors highly expressed in gliomas (OLIG2, SOX2) (Fig. S5A,B). WB analysis and DNA sequencing show the expression of the IDH1 R132H protein in the cells and the IDH1 395 G > A mutation (Fig. S5C,D respectively). In addition, CGH array performed with the initial resection and with the LGG85 cells show a very good coincidence of DNA alterations between the tumour and the culture (Fig. S5E). ETNPPL was overexpressed in Gli4, Gli7, LGG85 cultures using a doxycycline-controlled lentivirus. Western blot analysis indicates that while endogenous ETNPPL in these 3 cultures was not detected (Fig. 7A), addition of doxycycline induced a strong ETNPPL expression compared to control luciferase-expressing cells. Immunofluorescence confirmed the induction of ETNPPL by doxycycline and the protein was localized in cell nuclei (Figs. 7B, S7B). Using these constructs in a growth assay, we found that ETNPPL overexpression reduced the cell number obtained after 8 days of culture in Gli7 and LGG85 cells (3 independent experiments, Fig. 7C), but not in Gli4 cells (not shown). EdU incorporation performed in Gli7 cells for 4 hours show a reduction in the proliferation rate (Fig. 7D) while the number of apoptotic cells detected by cleaved-caspase 3 was unchanged (not shown). These results show an inhibitory role for ETNPPL in the growth of 2 out of 3 GBM cell lines.

Discussion

In this article we characterized further the high-density foci observed in 20% of DLGG-affected patients by using IHC and RNA profiling. We provide evidence for dysregulation of specific pathways and gene expression in these tumour areas. In addition, this led us to identify expression of ETNPPL in gliomas, a barely-studied metabolic enzyme, which was further studied in vitro.

Three main conclusions can be drawn from this study.

High activation of STAT3 pathway in foci. We first showed that foci have a higher percentage of pSTAT3 + cells which indicates STAT3 pathway activation in these cells. Phosphorylated STAT3 translocates to the cell nucleus to regulate many genes involved in proliferation, apoptosis and angiogenesis 21 . As such, phosphorylation of STAT proteins, notably STAT3, is involved in the pathogenesis of many cancers, including GBM, by promoting cell cycle progression, stimulating angiogenesis, and impairing tumour immune surveillance 21 . What could activate the STAT3 pathway in foci? STAT3 is phosphorylated through activation of several receptors such as IL-6 cytokine receptor, c-met receptor, PDGFR and EGFR receptors. Indeed, EGFR is frequently co-expressed with phosphorylated STAT3 in high-grade gliomas 22 . We previously reported that EGFR staining was higher (Hirsch score) in foci than the rest of the tumour which may be linked to the STAT3 activation we observed in these tumour areas 9 . In vitro STAT3 can also be activated by cell confluence 23 which may be somewhat related to its activation in foci where cell density is increased (Figs. 1A,S1).

What could be the significance of STAT3 activation in glioma foci? STAT3 expression promotes tumour incidence in combination with PDGF in a glioma mouse model 24 . Activated STAT3 also correlates positively with glioma grade 22,25 . STAT3 is essential for maintenance and proliferation of aggressive glioblastoma stem cells 26,27 and is involved in the transition of glioblastomas toward the even more aggressive mesenchymal glioblastoma subtype 28 .

All together, these data support the notion that STAT3 activation in foci may be linked to malignant progression which warrants further investigations. 208

Foci show dysregulated gene expression.

A second outcome of this study is the identification of a modified expression of 13 genes which were downregulated in foci. Individual analysis of the literature for these genes reveals interesting features. ADCYAP1R1 (a receptor for PACAP) is a protein involved in cAMP production. High cAMP can oppose gliomagenesis 29 so the observed decrease of ADCYAP1R1 might promotes foci cell proliferation. Expression of 2 genes coding for metabolic enzymes (ALDOC, ETNPPL) was modified suggesting that foci might have an altered metabolism as often observed during cancer progression. Gene analysis also suggests that foci cells are likely to have modifications in 2 pathways, namely Wnt and EGFR pathways. The Wnt signalling which is central in gliomagenesis 30 , may be affected in foci cells as we observed downregulation of 2 genes participating in the regulation of this pathway, namely DAAM2 31 and SFRP2 32 . The reduction of SFRP2 gene expression is particularly significant as this Wnt pathway inhibitor is often reduced by DNA hypermethylation in the progression of various cancers 33 . Regarding EGFR signaling, reduction of MLC1, a gene which favors EGFR degradation 34 , may leads to the higher EGFR expression we previously observed by IHC in foci 9 . The cytoskeleton might also be affected in foci as gene coding for ezrin (EZR) a linker protein between plasma membrane and actin cytoskeleton, is reduced. Finally, cell-cell communication is likely to be altered. This is illustrated by the decrease of GJA1, the gene coding for connexin 43, a major connexin protein of glial cells 35 .

The fact that the downregulated genes in foci are also decreased in high-grade tumours (Table S3) suggests that foci are cells undergoing transformation. In addition, for 3 of these genes, namely MLC1, CST3 and GJA1, it has been demonstrated that they oppose tumorigenesis when overexpressed in glioma lines 34,36,37 and thus they present tumour suppressor activity. Similarly, the reduction of expression of these 3 genes might promote foci expansion and transformation.

Further investigations are needed to evaluate whether other genes identified in this study behave in a similar way.

ETNPPL negatively regulates glioma cell growth. The third series of data we report here concerns ETNPPL, a metabolic enzyme barely studied so far. We demonstrated that the ETNPPL protein is present in normal astrocytes as well as in diffuse low-grade glioma cells but is downregulated with malignant progression. The situation may be reminiscent of the liver context, where ETNPPL is expressed in normal tissue but is downregulated in hepatocarcinoma 38 . One unexpected finding was our observation of a nuclear localization for ETNPPL. This was observed in normal astrocytes, in glioma cells but also in vitro when the protein was overexpressed in glioblastoma stem cell cultures. In some glioma tumours, we also observed subpopulations of cells with ETNPPL in the cytoplasm. The nuclear or cytoplasmic expression of ETNPPL in gliomas can also be observed in the human protein atlas 39 which validates our observation further (Fig. S4E). It is now established that metabolic enzymes can have non-metabolic roles and can act in the nuclei as transcriptional regulators (the so-called moonlighting phenomenon 40 ). A similar situation may apply to ETNPPL which warrants further investigations.

We found that ETNPPL RNA and protein are reduced in foci cells and absent in glioblastomas. This is consistent with glioma database analyses showing that ETNPPL expression is inversely correlated to STAT3 and MKI67 (Fig. S4F) whose expression are higher in foci and glioblastomas. In addition, Kaplan-Meier analysis shows that patients with low expression of ETNPPL have lower overall survival (Fig. S4G). These observations suggested that this enzyme may oppose glioma cells proliferation. We demonstrated this hypothesis by overexpressing ETNPPL in 3 glioblastoma cell cultures (Gli4, Gli7, LGG85). Gli7 and LGG85 cells were sensitive to ETNPPL overexpression which reduced their growth while no effect was detected in Gli4 cells. These glioblastoma-derived cultures have different types of mutations. Notably, Gli4 cells have lost one copy of the NF1 gene (unpublished data) which characterizes the mesenchymal subtype of glioblastomas 41 . This most aggressive subtype of glioblastoma may have a specific metabolism conferring insensitivity to ETNPPL.

How could ETNPPL reduce Gli7 and LGG85 cell growth? This enzyme catalyzes the breakdown of phosphoethanolamine, converting it to ammonia, inorganic phosphate and acetaldehyde (Fig. S4A). Phosphoethanolamine is a primary amine which has a critical role in the biosynthesis of membrane phospholipids, notably phosphatidylethanolamines which are enriched in the nervous tissue. Ethanolamine and its phosphorylated form phosphoethanolamine have been shown to be potent mitogens for cancer cell lines 42,43 . We can thus speculate that the high expression of ETNPPL found in diffuse low-grade gliomas and its overexpression done here in glioblastoma cells may reduce phosphoethanolamine concentration and phosphatidylethanolamine synthesis causing reduction in glioma cell growth. In support of this notion, magnetic resonance spectroscopy investigation found that IDH1-mutant tumours are characterized by decreased levels of phosphoethanolamine 44 .

Our study presents two limitations. First, we found only a limited number of dysregulated genes in foci. The suboptimal quality of RNA extracted from patient FFPE blocks may account for this restricted gene identification. Second, we cannot formally rule out that few of the genes which were identified are in fact not expressed by tumoral cells but by tumour environment cells such as microglia cells. However, this is unlikely as both quantifications of tumoral cells in the DLGG and its foci and bioinformatics analyses performed with the ESTIMATE approach did not reveal a different cellular composition in both compartments. In addition, literature review indicated that most of the genes are expressed by neural cells and, at least for ETNPPL, we have demonstrated that this gene is expressed by tumoral cells.

In conclusion, diffuse low-grade gliomas inexorably progress into high-grade tumours. Patients with foci have a reduced overall survival 9 so it is important to characterize these areas with specific molecular tools. We found that the increase in pSTAT3 and the decrease in ETNPPL stainings characterize these foci which could help to detect cells progressing toward malignancy and thus to stratify patients.

Transformation Foci in IDH1-mutated Gliomas Show STAT3

Phosphorylation and Downregulate the Metabolic Enzyme ETNPPL, a Negative Regulator of Glioma Growth Leventoux N 1,2 , Augustus M 1 , Azar S 1 , Riquier S 3 , Villemin JP 4 , Guelfi S 1 , Falha L 1 , Bauchet L 1,5 , Gozé C 1,6 , Ritchie W 4 , Commes T 3 , Duffau H 1,5 , Rigau V 1,7,9 andHugnot JP 1,8, heterogeneity and plasticity are two sides of a coin that needs to be addressed simultaneously.

In my PhD project, I investigated the cellular heterogeneity and the underlying molecular mechanisms governing the generation of the heterogeneity and plasticity in IDH1 mutated diffuse low-grade glioma. Results obtained from the project demonstrate that there exist two non-overlapping cellular subpopulations in both oligodendroglioma and astrocytoma. The characterization of the cellular markers identifies them to be astrocytic and oligodendrocytic cell types. Further analysis also showed that the cells differ in their active signaling pathways.

Using in vitro cultures of purified cells from tumor tissue, we propose that Notch signaling could play a deterministic role in regulating the phenotype of the tumor cells.

Two non-overlapping cell populations in IDH1-mutated DLGG

Understanding the tumor heterogeneity and thereby investigating the presence of cellular subtypes is largely hindered by several technical limitations. Amongst these, one of the primary limitations includes unavailability of a reliable model system (lack of DLGG cell lines restricts the study to primary tumor cultures, see chapter 1.7.2) and molecular markers that could distinguish any existing subpopulations. In the current study, I investigated the composition of astrocytic and oligodendrocytic lineage cells using tissue sections of freshly resected tumor samples.

General discussion and Perspectives

Apart from the molecular markers used to distinguish tumor cells in patient biopsies, cellular composition of the grade II gliomas are not defined over the years. Knowledge about cellular types, their molecular markers and underlying signaling mechanisms are important in understanding the biology of the disease that could open new avenues of research to develop treatment modalities. This motivated us to explore the tumoral cellular subpopulations. A large body of research is dedicated in defining the genetic abnormalities and comparative studies across grades to identify early event of tumor development and progression. The intratumoral heterogeneity in primary glioblastoma has been vastly explored through the works of many independent groups [START_REF] Darmanis | Single-Cell RNA-Seq Analysis of Infiltrating Neoplastic Cells at the Migrating Front of Human Glioblastoma[END_REF][START_REF] Patel | Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma[END_REF]Verhaak et al., 2010).

However, such elaborate and extensive studies on the cellular heterogeneity are not carried out in diffuse low-grade gliomas that invariably progresses to high grade. First of such evidence shedding light on the cellular heterogeneity came recently using single cell RNA sequencing technology proposing a developmental hierarchy within oligodendroglioma (Tirosh et al., 2016). But there are no reports yet demonstrating how transcriptionally available information translates to proteins, that ultimately defines the phenotypes of the cells.

This lack of information prompted us to explore the tumoral cell architecture in IDH1 mutated diffuse low-grade glioma. I employed immunofluorescence to identify cellular subtypes and the associated markers. The terms astrocytoma and oligodendroglioma were coined due to the morphological similarity of tumoral neoplastic cells to corresponding astrocytes and oligodendrocytes respectively. Through this study I show that both oligodendroglioma and astrocytoma are comprised of astrocytic-like and oligodendrocytic-like cell types that are almost independently co-existing. Though SOX9 + and OLIG1 + cells are identified through IF, whether these cell types can be distinguished at the histology level needs further investigation.

There are very interesting questions that needs to be explored in the future. What determines the cellular composition in these tumors? Does it depend on the underlying genetic variability observed in these tumors? Evidences for genetic predisposition in determining cellular phenotypes could be explained through the following studies. It is well established that astrocytoma and oligodendroglioma differ in their molecular markers. One such genetic event is the deletion of CIC following 19q deletion in oligodendroglioma.

Analyzing the cell-type specific expression of CIC in the forebrain of the mice identified higher expression in GFAP + ALDH1L1 + astrocytes than in NSCs, OPCs and in oligodendroglial lineage cells. Using a conditional Cic-knockout mouse model, the authors show that deletion of Cic increases SOX9 + cells and OLIG2 + PDGFRA + OPC populations at the expense of neurons, suggesting activation of gliogenic differentiation program. Upon culturing the Cic-null and control NSCs in vitro, they identified that Cic deficiency bias the cells towards oligodendrocytic lineage differentiation generating significantly higher number of OPC compared to astrocytes. Together, this finding suggests that Cic deletion in the early genetic events could favor the generation of OPC and oligodendrocytes in oligodendroglioma [START_REF] Ahmad | Capicua regulates neural stem cell proliferation and lineage specification through control of Ets factors[END_REF]. Similarly, a study performed to understand the role of ATRX in gliomagenesis, identified ATRX to play important role in cellular phenotype. Induced differentiation of mouse neural progenitor cells (mNPC) in the genetic background of Tp53 -/- and Atrx deletion altered the differentiation profile of mNPC. Induced differentiation of Atrx deficient cells abrogated the expression of neuronal marker β3-tubulin (Tubb3) and oligodendrocytic marker OLIG2 and upregulated astrocytic GFAP marker [START_REF] Danussi | Atrx inactivation drives diseasedefining phenotypes in glioma cells of origin through global epigenomic remodeling[END_REF]. These could explain the roles of genetic players in determining the phenotypes of the cells. However, the co-existence of both these cell populations in two tumor types is intriguing.

Implications on cellular origin of glioma

Analysis of all six tumors (3 oligodendroglioma and 3 astrocytoma) consistently showed the presence of two independent populations. One intriguing question to address in the future is to assess the cellular origin of these tumors. There are two possibilities that could be thought of.

First possibility is that the cell of origin could be a bipotent cell that is able to differentiate into two lineage cells. This leads to hypothesize that the cell of origin can either be neural stem cells or oligodendrocytic progenitor cell both of which are able to generate oligodendrocytes and astrocytes that are considered to be putative cellular origins of glioma.

General discussion and Perspectives

A second possibility is the formation of either one-lineage cells first and then in vivo conversion to another glial lineage. It has also been shown that endothelial and microglial cells can promote the differentiation towards astrocytic lineage at least in vitro [START_REF] Mi | Induction of astrocyte differentiation by endothelial cells[END_REF][START_REF] Nakanishi | Microglia-derived interleukin-6 and leukaemia inhibitory factor promote astrocytic differentiation of neural stem/progenitor cells[END_REF]. This is also another possibility that cannot be neglected as tumoral microenvironment has large influence on the tumoral cells. Since mature astrocytes are also considered to undergo dedifferentiation and act as cellular origins, it cannot be neglected that astrocytes could be the first cell type generated following the lineage conversion to oligodendrocytes [START_REF] Farhangi | In vivo conversion of astrocytes to oligodendrocyte lineage cells in adult mice demyelinated brains by Sox2[END_REF][START_REF] Mokhtarzadeh Khanghahi | In vivo conversion of astrocytes into oligodendrocyte lineage cells with transcription factor Sox10; Promise for myelin repair in multiple sclerosis[END_REF].

Irrespective of the characteristic genetic abnormalities in the tumor subtypes, indistinguishable cellular composition in both oligodendroglioma and astrocytoma implies that cellular origin and the signaling pathways effectively determine the heterogeneity of the tumors beyond genetic mutations.

Cellular markers of SOX9 + and OLIG1 + cells.

In an attempt to characterize the SOX9 + and OLIG1 + cells, we identified cell type specific markers that characterize them to astrocytic and oligodendrocytic components (Figure 13).

Sox9 + cells were associated with astrocytic markers such as APOE and ID4 (Tirosh et al., 2016). Interestingly, one study reported that APOE is differentially expressed in oligodendroglioma and astrocytoma and can be used as a potential marker to distinguish these tumors at the cellular level (Rousseau et al., 2006). However, this is not the case in my study where ApoE is expressed at similar proportions in both oligodendroglioma and astrocytoma.

In addition we observed the specific expression of CRYAB and KCNN3 in the SOX9 + cells.

Alpha-B crystallin (CRYAB/ hspB5) is a heatshock protein and a molecular chaperone. They bind unfolded proteins inhibiting their aggregation and prevent degradation thereby promoting survival, inhibiting apoptosis. CRYAB expression has been identified in several cancers including glioma and is associated with poor prognosis [START_REF] Chan | Increased alpha-B-crystallin expression in mammary metaplastic carcinomas[END_REF]Goplen et al., 2010;[START_REF] Malin | alphaB-crystallin: a novel regulator of breast cancer metastasis to the brain[END_REF][START_REF] Mao | Alpha B-crystallin is a new prognostic marker for laryngeal squamous cell carcinoma[END_REF][START_REF] Qin | Elevated expression of CRYAB predicts unfavorable prognosis in non-small cell lung cancer[END_REF]. In glioma, CRYAB is reported to be elevated in apoptotic resistant glioblastoma cells and also in IDH1 mutated anaplastic glioma (Avliyakulov et al., 2014;Goplen et al., 2010). These results raise an intriguing possibility that specific expression of CRYAB in SOX9 + cells could allow these cells to be more resistant to cellular stress such as treatment and in avoiding apoptosis.

KCNN3 was another protein identified as the cellular marker of SOX9 + cells. KCNN3 belonging to small conductance calcium activated potassium channel (SK channels) family are predominantly expressed in nervous system, is a voltage independent channel regulated by General discussion and Perspectives intracellular calcium levels [START_REF] Stocker | Ca(2+)-activated K+ channels: molecular determinants and function of the SK family[END_REF]. Ion channels in general have been implicated in glioma. They can be functionally involved in cell proliferation as well as in migration and invasion [START_REF] Molenaar | Ion channels in glioblastoma[END_REF]. They regulate the effects through modulation of resting membrane potential. It has been observed that K + channel activity can facilitate proliferation by regulating G1/S checkpoint [START_REF] Weaver | Role for calcium-activated potassium channels (BK) in growth control of human malignant glioma cells[END_REF]. There are primarily 3 families of Ca2 +activated K + channels-big conductance (BK), Intermediate conductance (IK) and small conductance (SK) channels. Specifically majority of studies on glioblastoma are performed using BK and IK channels. Studies show that these channels exhibit oncogenic functions involving in cell proliferation, migration and invasion as well as resistance to radiation therapy whereas functions of SK channels are not elucidated [START_REF] Basrai | BK channel blockers inhibit potassium-induced proliferation of human astrocytoma cells[END_REF][START_REF] Lui | Invasion of human glioma cells is regulated by multiple chloride channels including ClC-3[END_REF][START_REF] Weaver | Role for calcium-activated potassium channels (BK) in growth control of human malignant glioma cells[END_REF][START_REF] D'alessandro | KCa3.1 channels are involved in the infiltrative behavior of glioblastoma in vivo[END_REF][START_REF] Jager | Blockage of intermediate-conductance Ca2+-activated K+ channels inhibit human pancreatic cancer cell growth in vitro[END_REF][START_REF] Stegen | Ca2+-Activated IK K+ Channel Blockade Radiosensitizes Glioblastoma Cells[END_REF][START_REF] Steudel | SK4 channels modulate Ca(2+) signalling and cell cycle progression in murine breast cancer[END_REF]. A gene expression study conducted to identify ion channels as predictive markers of glioma found KCNN3 as a favorable prognostic marker. KCNN3 expression was higher in grade II glioma and was downregulated in grade IV [START_REF] Wang | Ion channel gene expression predicts survival in glioma patients[END_REF]. An earlier study had also identified that, even though transcripts of SK channels were found in GBM samples, BK channels were the only functional channels in their study (Weaver et al., 2006).

A recent study in bladder cancer identified KCNN3 as a negative regulator of proliferation, invasion and migration [START_REF] Zhu | MiR-652-3p promotes bladder cancer migration and invasion by targeting KCNN3[END_REF]. Recent publication from our group also identified KCNN3 as a gene downregulated in transformation foci of DLGG, a histological sign of malignancy [START_REF] Leventoux | Transformation Foci in IDH1-mutated Gliomas Show STAT3 Phosphorylation and Downregulate the Metabolic Enzyme ETNPPL, a Negative Regulator of Glioma Growth[END_REF]. Taken together, it appears that KCNN3 could have tumor suppressive functions and is a good candidate that needs to be further characterized in the context of glioma.

With regards to OLIG1 + cells, they express oligodendrocytic lineage markers such as PDGFRA, a marker of OPC and SOX8, a protein implicated in differentiation of oligodendrocytes [START_REF] Stolt | Transcription factors Sox8 and Sox10 perform non-equivalent roles during oligodendrocyte development despite functional redundancy[END_REF][START_REF] Turnescu | Sox8 and Sox10 jointly maintain myelin gene expression in oligodendrocytes[END_REF]. Apart from these, OLIG1 + cells expressed progenitor cell markers such as SOX4 and MASH1. MASH1/ASCL1 has been implicated in glioma progression and its expression positively correlates to malignancy from DLGG to secondary GBM [START_REF] Somasundaram | Upregulation of ASCL1 and inhibition of Notch signaling pathway characterize progressive astrocytoma[END_REF]. Role of SOX4 in maintaining the cancer initiating cells in GBM is well established. SOX4-SOX2 axis is critical in maintaining the stemness of GSCs (Ikushima et al., 2011).

While this study was being carried out, the tumoral heterogeneity in IDH1 mutated glioma was published using single cell RNA sequencing method. The group demonstrated that at the transcriptional level, astrocytoma and oligodendroglioma are composed of three cellular subpopulations (Venteicher et al., 2017), consisting of differentiated astrocytes and General discussion and Perspectives oligodendrocytes similar to what we observed and thus confirmed our results. But they also suggest the presence of a minority of stem cell population that are the cycling cells in the glioma. One of the markers they identified specific to this stem cell population was SOX4.

But our analysis shows that SOX4 was associated with the OLIG1 + cell type. It could be possible that the cycling SOX4 are a subpopulation within OLIG1 + cell type. To ascertain this hypothesis, we performed immunostaining with KI67, a proliferation marker on 6 DLGG (data not shown). As expected, the percentage of KI67 + cells was low in the tissues but I could not associate them to a particular cell type. Moreover, the SOX4 cells were not a minor population in the tissues analyzed as opposed to the results from single cell RNA sequencing.

This discrepancy at the transcriptional and translational levels signifies the importance of posttranscriptional regulations.

The almost non-overlapping expression of several of the marker proteins between the cell types questions their co-existence within the tumor tissue. In the quest of identifying any cellular markers commonly expressed by both cell types, we identified SOX2 and GPR17.

Several studies are published signifying the role of SOX2 in glioblastoma [START_REF] Garros-Regulez | Targeting SOX2 as a Therapeutic Strategy in Glioblastoma[END_REF]. They are associated with tumor aggressiveness and poor prognosis [START_REF] Ben-Porath | An embryonic stem cell-like gene expression signature in poorly differentiated aggressive human tumors[END_REF][START_REF] Sathyan | Mir-21-Sox2 Axis Delineates Glioblastoma Subtypes with Prognostic Impact[END_REF]. SOX2 plays important role in maintaining the stemness of GSCs [START_REF] Gangemi | SOX2 silencing in glioblastoma tumor-initiating cells causes stop of proliferation and loss of tumorigenicity[END_REF][START_REF] Hagerstrand | Identification of a SOX2-dependent subset of tumor-and sphere-forming glioblastoma cells with a distinct tyrosine kinase inhibitor sensitivity profile[END_REF]Ikushima et al., 2011). SOX2 have the potential to reprogram differentiated glioma cells to induce GSCs when expressed along with other transcription factors such as OLIG2, POU3F2 and SALL2 [START_REF] Suva | Reconstructing and reprogramming the tumor-propagating potential of glioblastoma stem-like cells[END_REF].

Interestingly we observed GPR17, an oligodendrocyte-associated marker to be expressed both by OLIG1 + and SOX9 + cells in the tissues. G protein-coupled receptor 17 (GPR17) is considered an intrinsic timer of oligodendrocyte differentiation and myelination (Chen et al., 2009). The activation of this receptor in OPC promotes differentiation of preoligodendrocytes to mature myelinating oligodendrocytes [START_REF] Lecca | The recently identified P2Y-like receptor GPR17 is a sensor of brain damage and a new target for brain repair[END_REF]. In contrast, activation of GPR17 in differentiating oligodendrocytes downregulates MBP expression and inhibits maturation [START_REF] Simon | The Orphan G Protein-coupled Receptor GPR17 Negatively Regulates Oligodendrocyte Differentiation via Galphai/o and Its Downstream Effector Molecules[END_REF]. Thus the function of GPR17 is cell state specific.

GPR17 can also serve as sensor of brain damage. Its endogenous ligands such as uracil nucleotides, uridine diphosphate (UDP), UDP-glucose and leukotriene D4 and E4 are released extracellular from damaged tissue sites of inflammation, trauma and ischemia, which result in upregulated expression of GPR17 around the lesions [START_REF] Ceruti | The P2Y-like receptor GPR17 as a sensor of damage and a new potential target in spinal cord injury[END_REF][START_REF] Lecca | The recently identified P2Y-like receptor GPR17 is a sensor of brain damage and a new target for brain repair[END_REF]. I observed heterogeneity in the expression of GPR17 in our cell types. Although both the cell types express it, highly positive cells were associated with OLIG1 + cells. It could be speculated that GPR17 regulate the maturation state of these cell types. The expression of General discussion and Perspectives IDH1R132H confirming the tumoral identity. Surprisingly, only a minor population (~20%) of SOX9 + cells expressed the mutant form of IDH1. This was quite unexpected as IDH1 is considered a universal marker to identify tumor cells and is commonly used in tissue biopsies to distinguish tumoral regions. This differential expression was more prominent in oligodendroglioma compared to astrocytoma. The absence of IDH1R132H expression raised the question whether SOX9 + cells are tumoral in nature. To confirm this, I performed ATRX staining on astrocytoma tissue and observed that most cells were mutated for the protein confirming that they are indeed tumoral. While such a confirmation is lacking in oligodendroglioma due to the unavailability of a reliable marker further insisting the need to discover novel biomarkers for this tumor subtype. But the phenotypic similarity of SOX9 + cells in both the tumor subtypes compels to believe that majority of SOX9 + cells in oligodendroglioma are tumoral. The cell type specific expression of IDH1R132H prompted me to explore the expression pattern of wildtype IDH1 in the two cell types to understand whether it is a cell intrinsic phenomenon. Immunostaining revealed that IDH1 wildtype expression is also cell type specific and difference was more striking in oligodendroglioma.

Only ~40% of SOX9 + cells expressed the wildtype IDH1. Database search on cell type specific expression of IDH1 revealed that at transcriptomic level, IDH1 could be expressed more in oligodendrocytic lineage cells as compared to astrocytes in both mouse and human adult brain. This has to be confirmed at the protein level both in normal and tumoral conditions. As IDH mutation is the early genetic event, is OLIG1 + cells be the early tumoral cells generated? IDH being a metabolic enzyme, it could imply that the metabolism be different in both cell types. Also, it is known that IDH mutation can influence the epigenome and results in hypermethylated phenotype. It is interesting to further investigate whether the effects of IDH1 that are currently known is specific to one cell type in DLGG. Another interesting aspect to look at is the sensitivity of cells to chemotherapy. As IDH mutated cells are sensitive to chemotherapeutic agents, can it be possible that only OLIG1 + cells are sensitive to treatment? Does it mean that SOX9 + cells could be resistant subpopulations?

Could these cells be at the origin of recurrent tumors? More importantly, it is also worth investigating why SOX9 + cells do not express IDH1R132H protein in the first place. Is it a tumor specific phenomenon to suppress the protein expression? Does it impart any cellular advantage? It can also be possible that downregulation of IDH1 be an after-effect of activity of other molecular players. (The effect of signaling on IDH1 will be explained in the coming section.)

General discussion and Perspectives

Subpopulation specific receptor expression and signaling pathways in DLGG

As I observed a dichotomous expression of cellular markers in the tumor subpopulations, it indicated that the underlying signaling pathways could also be characteristic to individual population. Our lab has previously published that tumoral cells in DLGG express PDGFRA, EGFR and PTPRZ1 receptors (Azar et al., 2018). However the prime focus of that study was to characterize the IDH1 mutated cells in these tumors. As I observed that IDH1 expression and the PDGFRA expression was characteristic of oligo-like cells, I speculated that the expression of EGFR and PTPRZ1 could also be oligo-cell specific. Confirming this speculation, I observed that indeed both these receptors are associated with OLIG1 + cells in grade II astrocytoma and oligodendroglioma. EGFR and PDGFR are well-established oncogenes in glioma. PDGFRA amplification is characteristic of proneural GBM and EGFR mutation and amplification in classical GBM (Verhaak et al., 2010). One of the emerging biomarkers of secondary glioblastoma is PTPRZ1. PTPRZ1-MET gene fusion transcripts are frequently found in grade III astrocytoma and secondary glioblastoma suggesting the relevance of these genes in malignancy (Bao et al., 2014;[START_REF] Zeng | Tumour exosomes from cells harbouring PTPRZ1-MET fusion contribute to a malignant phenotype and temozolomide chemoresistance in glioblastoma[END_REF]. PTPRZ1 encodes for receptor-type tyrosine-protein phosphatase zeta 1 dephosphorylating its target proteins.

PTPRZ1 are strongly expressed in malignant glioma and plays oncogenic functions [START_REF] Fujikawa | Small-molecule inhibition of PTPRZ reduces tumor growth in a rat model of glioblastoma[END_REF][START_REF] Fujikawa | Targeting PTPRZ inhibits stem cell-like properties and tumorigenicity in glioblastoma cells[END_REF]Muller et al., 2003;Ulbricht et al., 2003;[START_REF] Ulbricht | RNA interference targeting protein tyrosine phosphatase zeta/receptor-type protein tyrosine phosphatase beta suppresses glioblastoma growth in vitro and in vivo[END_REF]. The cell type specific expression of PTPRZ1 in oligo-like cells in DLGG could hint to their role in glioma growth and tumorigenicity. Functional role of this malignant marker in oligo-like cells has to be explored in details. While astro-like cells showed preferential expression of p-ERK signaling indicating the activation of MAPK pathway but the upstream activators are yet to be identified in these cells.

I further probed into analysing signaling pathways that have the potential to modify the phenotype of cells. To this end, I investigated the expression profiles of two key pathways: Notch and BMP signaling, which are earlier reported to participate in regulating the cellular phenotypes during development [START_REF] Basak | Neurogenic subventricular zone stem/progenitor cells are Notch1-dependent in their active but not quiescent state[END_REF][START_REF] Imayoshi | Essential roles of Notch signaling in maintenance of neural stem cells in developing and adult brains[END_REF]) [START_REF] Johnston | Keeping them quiet: BMPs maintain adult neural stem cell quiescence[END_REF][START_REF] Lim | Noggin antagonizes BMP signaling to create a niche for adult neurogenesis[END_REF] and in the context of glioma [START_REF] Bar | Hypoxia increases the expression of stem-cell markers and promotes clonogenicity in glioblastoma neurospheres[END_REF][START_REF] Chirasani | Bone morphogenetic protein-7 release from endogenous neural precursor cells suppresses the tumourigenicity of stemlike glioblastoma cells[END_REF][START_REF] Piccirillo | Bone morphogenetic proteins inhibit the tumorigenic potential of human brain tumour-initiating cells[END_REF][START_REF] Stockhausen | The functional role of Notch signaling in human gliomas[END_REF]. I observed the nuclear expression of transcription factors that are downstream targets of Notch signaling HEY1 and HEY2 in astro-like cells. Similarly, BMP4 and its downstream p-SMAD1/5 were also preferentially expressed in these cells. As Notch and BMP signaling have the potential in driving astrocytic differentiation [START_REF] Angulo-Rojo | Involvement of the Notch pathway in terminal astrocytic differentiation: role of PKA[END_REF][START_REF] Ge | Notch signaling promotes astrogliogenesis via direct CSL-mediated glial gene activation[END_REF][START_REF] Piccirillo | Bone morphogenetic proteins inhibit the tumorigenic potential of human brain tumour-initiating cells[END_REF]Srikanth et General discussion and Perspectives al., 2014) [START_REF] Mabie | Bone morphogenetic proteins induce astroglial differentiation of oligodendroglialastroglial progenitor cells[END_REF], the specificity of their expression in astro cell type suggest their putative role in tumor heterogeneity development. This observation is novel in our study, as it has not been previously reported in DLGG. It is to be understood how the differential expression of these signalling pathways in SOX9 + and OLIG1 + subpopulations impact their cellular processes. Further, it is important to understand if such specific expression of signaling pathways plays a deterministic role in generating tumoral heterogeneity. To investigate this, I have established an experimental paradigm using in vitro cultures that allows me to modify the levels of Notch and BMP signaling (discussed in chapter 4.6).

Experimental paradigm to modify signaling pathways using in vitro cell culture

The ex vivo characterization of the DLGG cell types prompted me to develop a culture system where I could purify the two cellular subpopulations separately and perform functional studies individually. There were a lot of obstacles to overcome for developing a culture system for DLGG cells. To begin with, there are no standardised protocols available for primary DLGG cultures as well as known cellular markers to isolate the cells. As most cellular markers I identified were nuclear and cytoplasmic, initial experimental plan was to identify membrane markers through flow cytometry and use them for purification. Several established markers of oligodendrocytic and astrocytic lineages were used to perform FACS. One of the primary challenges was to develop a tissue dissociation method that does not affect the expression of surface proteins and the health of the cells. As opposed to GBM tissues that are easily dissociated through mechanical dissociation alone, DLGG tissues are sturdy. Thus, mechanical dissociation alone on DLGG tumor tissues often resulted in cell death. To overcome this, we resort to many of the known enzymes used for tissue dissociation such as papain, trypsin, neutral protease, hyaluronidase and Bacillus licheniformis protease [START_REF] Adam | Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts: a molecular atlas of kidney development[END_REF][START_REF] Gomez | Isolation and culture of human brain tumor cells[END_REF][START_REF] Patel | Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma[END_REF][START_REF] Singh | Identification of human brain tumour initiating cells[END_REF][START_REF] Volovitz | A non-aggressive, highly efficient, enzymatic method for dissociation of human brain-tumors and brain-tissues to viable single-cells[END_REF]. But none of them successfully generated single cell suspensions. Some of them were very strong in their activity resulting in cell death while others did not dissociate the tissues completely resulting in cell loss. An improved result was obtained using a combination of trypsin and hyaluronidase, a method previously developed in our lab to generate neural stem cell cultures from mice spinal cord [START_REF] Hugnot | Isolate and culture neural stem cells from the mouse adult spinal cord[END_REF]. With a fewer changes made on this existing protocol, I managed to obtain single cell suspension with viable cells. Flow cytometry analysis using various cell surface markers (A2B5, O4, CD44, PSA-NCAM, GLAST, CD24, EGFR) performed on 24 independent cultures revealed the relative populations of cells expressing these markers. Despite high variation from patient to patient, I General discussion and Perspectives identified that the percentage of O4 + cells are relatively higher in the tissues analysed and a convenient marker to isolate the oligo-like cells in the tumors.

Fluorescence-associated cell sorting (FACS) was not reliable as they gained fewer cells at most times and the purified cells either did not attach to the coverslip coated with PDL/ laminin or underwent cell death. I speculate that the tissue dissociation, percoll treatment for myelin removal as well as FACS, place cells under stress resulting in unsuccessful cultures.

Thus, I decided to use magnetic beads coupled antibody for purification of O4 + cells. Using this method I was able to generate viable cultures enriched with O4 + cells and thus could have a culture system established for DLGG. Despite overcoming several technical limitations, the success rate of this culture system still remained lower due to the variability in many factors.

Primary factor is the quality of the resection obtained. Depending on whether the tissue region is within tumor or non-tumoral area, the number of coverslips that could be seeded ranged from one well to 24 wells. Also depending on the stiffness of the tissue, time required for dissociation varies from 30 minutes to 2 hours that could affect the cell viability. Another fundamental issue in culturing O4 + cells was that O4 marker was not specific to tumoral cells.

While analysing the percentage of tumor cells in culture using IDH1R132H or ATRX, we observed that there are primarily two types of O4 cells-tumoral and non-tumoral cells that can be easily distinguished by SOX10 staining. Non-tumoral O4 cells are highly branched cells with small round nuclei that most often exist in small aggregates. They are highly SOX10 + and express mature oligodendrocytic marker CNP. There is complete overlap in OLIG1 staining with only a few cells expressing SOX9. While tumor cells are large nuclei cells that has fewer branches mostly resembling an immature phenotype but expressed CNP.

The SOX10 expression is weak in these cells. All O4 tumor cells express OLIG1. Unlike in the ex vivo condition, there was no clear dichotomy between SOX9 and OLIG1 expression in vitro. Astrocytoma O4 + cultures have a higher percentage of SOX9 + O4 cells in culture while oligodendroglioma cultures rarely have SOX9 + cells. It can also be possible that the SOX9 induction is the result of phenotypic modifications influenced by in vitro culture conditions (Dromard et al., 2007). One important marker that could distinguish tumoral cultures from non-tumoral cells was EGFR. EGFR expression was found only in tumoral cells and thus could act as an important biomarker to be used in future experiments for DLGG cell isolation.

The selection of cultures for functional studies has been highly challenging. The cultures were chosen based on a few criteria. They had to be enriched with homogeneous O4 cells with less contamination by other cell types and were primarily composed of tumor cells. Mixed General discussion and Perspectives cultures were not taken into consideration for functional studies as it may affect the observations.

General discussion and Perspectives

Notch signaling plays a deterministic role in generating tumoral heterogeneity

Notch signaling is characterized as an important signaling in cell fate decisions both during development and in disease conditions. Its critical role in GBM has portrayed it to be a prooncogenic signaling that help maintain the stemness of GBM CSCs and involved in invasion.

But there are also contradictory reports on its effect as anti-tumorigenic signaling. Genetic analyses performed by multiple groups have identified Notch as a potential tumor suppressor gene in diffuse low-grade oligodendroglioma that gets mutated during their progression to malignancy [START_REF] Bettegowda | Mutations in CIC and FUBP1 contribute to human oligodendroglioma[END_REF]Suzuki et al., 2015;[START_REF] Yip | Concurrent CIC mutations, IDH mutations, and 1p/19q loss distinguish oligodendrogliomas from other cancers[END_REF]. But the role of Notch signaling in DLGG has not been functionally explored. In addition, the results from my study identified specific expression of Notch downstream targets in astro-like cells. This prompted us to investigate the effect of Notch signaling on O4 oligo like-cells from primary culture. Transduction of active form of notch1 signaling, Notch intracellular domain (NICD), and further results from qPCR analysis of 17 genes related to both astrocytic and oligodendrocytic lineage were striking. Active notch signaling in O4 cells significantly downregulated all genes related to oligodendrocytic lineage and upregulated astrocyte associated genes. Huge upregulation was observed in KCNN3 expression suggesting that KCNN3 could be a direct transcriptional target of Notch signaling. Another striking observation was that Notch signaling could negatively regulate the expression of IDH1. This could be one possible explanation for the downregulation of IDH1 expression specifically in astro-like cells of DLGG. How the reduction in IDH1 impacts tumoral behaviour of these cells is yet to be elucidated. As O4 marker also isolated normal oligodendrocytes, we tested the effect of Notch signaling in these cells using cultures where the % of tumoral cells was very low. As observed in tumoral cells, the results demonstrate that normal oligodendrocytes in adult human brain can be manipulated to downregulate oligodendrocytic transcription and upregulate astrocytic-like markers suggesting their phenotypic plasticity.

Immunofluorescence analysis revealed that the upregulated mRNA are translated to proteins and are overexpressed. Morphological differences in NOTCH1 activated cells were also remarkable (Chapter 3.1.1).

Surprisingly, Notch upregulation did not change the expression levels of SOX9 in tumoral O4 + purified cells. I reasoned that this could be because of the fact that O4 + purified tumoral cells have inherently a very high expression of SOX9. Indeed, I confirmed that Notch signaling could regulate the expression of SOX9 in the O4 + purified non-tumoral cultures, where the endogenous SOX9 levels are low.

General discussion and Perspectives

The establishment of an anaplastic IDH1mutated primary cell line was highly beneficial in this study. These cells termed as LGG 275, were highly heterogeneous in their cell shape and were slow growing cells requiring up to 14 days to double in their number. Initial analysis identified cells to co-express both SOX9 and OLIG1 protein. Further in vitro and in vivo analyses are required to investigate on the tumorigenic properties of these cells. As my primary O4 + cultures were not strictly tumor cells, I decided to explore the effect of Notch signaling in this tumoral cell line. I was able to reproduce similar results in these cells suggesting notch is able to downregulate oligodendrocytic markers and upregulate astrocytic markers. I observed strong upregulation of APOE, CRYAB and KCNN3 and significant downregulation of 10 genes of oligodendrocytic specific expression. Of all the genes explored, KCNN3 showed tremendous upregulation of up to 100 fold. This persuaded me to investigate the functionality of these channels. The physiological experiments performed with the help of Dr. Frederique SCAMPS and Aimond FRANCK to measure the SK current of the overexpressed KCNN3 channels demonstrated that they are functionally integrated to the membrane of the cells. It can be assumed that the expression of KCNN3 channel can affect their cellular behaviour regulating the tumoral microenvironment. Our lab has previously shown that activation of notch signaling in GBM primary cell line reduced the proliferation of the cells (Guichet et al., 2015). I examined if notch has similar effect on these anaplastic cell line. I observed that Ki67 mRNA was reduced by 4 fold that reflected also at the protein level of around 50% reduction in proliferation in these cells. This adverse effect of Notch on DLGG proliferation could be reasoned for its inactivating mutations in oligodendroglioma upon progression. But the oligodendroglioma specific mutation of Notch is quite provocative to probe into understanding the counteracting genetic abnormalities in astrocytoma while they progress to higher grades.

Another interesting signaling that captured my attention was BMP signaling. As BMP signaling is a pro-differentiating one, its expression on astro-like cells suggests these cells could be more differentiated than the other. I further examined if BMP could also exert similar effects as Notch on the LGG 275 cell line. I treated the cells with BMP2 and BMP4, expression of whom I observed in our tissue samples. Exposure to BMP signaling in the cells had a milder effect on the genes explored. Strongest effect was observed in CRYAB expression that has been previously reported as a transcriptional target of BMP signaling (Ciumas et al., 2013) and the effect was much higher with BMP2 rather than BMP4. I also observed strong upregulation of Noggin, the antagonist of BMP signaling suggesting the General discussion and Perspectives existence of a negative feedback loop or their release to the microenvironment prevents the activation of BMP signaling in the neighbouring cells regulating their phenotype. Among the oligodendrocytic lineage markers, BMP exerted antagonistic effect on OLIG1 and OLIG2, which is also expected as BMP induces astrocytic differentiation by downregulating OLIG1 and OLIG2 via the upregulation of ID2 and ID4 as previously reported (Srikanth et al., 2014).

Conclusions

The primary goal of my PhD was to characterize the cellular heterogeneity in diffuse lowgrade glioma and understand the signaling pathways that could play in defining cellular phenotypes. I have shown that IDH1 mutated grade II astrocytoma and oligodendroglioma are composed of primarily two distinctive cellular subpopulations with astrocytic-like and oligodendrocytic-like phenotypes. In addition to the differences in lineage specific protein expression, the cells also differ in the active signaling pathways ex vivo. These findings imply that both the grade II gliomas originate from a common cell of origin that give rise to both lineage cells and the differences in the genetic mutation in tumor subtypes are not deterministic of their cellular composition. Beyond the genetic abnormalities, tumoral cell phenotypes could be manipulated by other factors such as signaling. Notch signaling has been identified as a key molecular player involved in preferential differentiation towards astrocytic lineage and that could affect the tumor growth adversely at least in in vitro suggesting the potential use of notch signaling as a therapeutic target.

Major accomplishments/findings from the PhD

• From the conducted immunofluorescence study with the few markers used, it appears that IDH1 mutated diffuse low-grade astrocytoma and oligodendroglioma are very similar and may be indistinguishable in their cellular composition and heterogeneity. Each of them comprises of almost independently co-existing astrocytic and oligodendrocytic lineage cells in varying proportion.

• Globally used tumoral marker IDH1R132H is specifically expressed by oligodendrocyte-like cells in these tumors. Additional cellular markers are essential to identify all tumoral populations.

•

The cellular subpopulations within DLGG differ in the active signaling pathways and the receptor expressions.

• Establishment of an in vitro culture system to isolate specific cell populations from the patient resections.

• Identified Notch1 signaling as a central player that could differentiate oligodendrocytic-like cells to astrocytic-like cells.

• Notch1 act as a tumor suppressor signaling by reducing the cellular proliferation in vitro.

• Notch1 induced potassium channel, KCNN3 are functionally integrated in the cells.

• BMP signaling could act synergistically in regulating differentiation to astrocytes.

The findings of my PhD could provide deeper insights into understanding the role of signaling pathways in DLGG. Farther from the genetic abnormalities, signaling mechanisms could also exert their decisive effects on the phenotypes of these tumors. Future research should further identify the commonalities within the tumor subtypes and dissect out their individual roles in the respective tumoral context thereby shedding light on the potential therapeutic targets at the early stage of glioma.

INTRODUCTION

Glioblastomas (or glioblastoma multiformes, GBMs) are one of the most common brain tumors in adults and represent the second most common cause of death in children and the third in adults in the world (1). Despite the standard treatments, which combine surgical resection followed by radiotherapy and chemotherapy, the median survival does not exceed 14-15 months (2,3). The main reason for this dismal course is the high rate of tumor recurrence, which is associated with both the extremely infiltrative nature of glioblastoma growth and a frequently occurring resistance to conventional treatments, in part due to tumor heterogeneity. Indeed, aside from sharing common characteristics, such as high vascularization, pseudopalisading necrosis and infiltrating growth, these tumors are also very heterogeneous at the genetic, molecular and cellular levels. Among the sources of this heterogeneity are (i) the presence of a wide spectrum of driver mutations ( 4), (ii) distinct molecular subtypes ( 5) and (iii) cellular plasticity relying on cancer stem cells (or glioma stem cells, GSCs) responsible for tumor recurrence and resistance to therapy (6). In this context, in-depth study of gene expression programs in GBM cells and tumors, their mechanisms of regulation and functional consequences provide an opportunity to identify new targets and develop new therapeutics that will fill a major unmet clinical need in oncology.

Translation is the most energetically demanding process in the cell and its deregulation, often associated with the modification of the expression/activity of certain translation factors, contributes to development, tumor progression and the response to therapeutic treatments (7)(8)(9)(10). Beyond an increase in global translation rates supporting cellular proliferation and growth, selective mRNA translation plays key roles in rapidly and precisely regulating gene expression steering distinct aspects of the transformed phenotype. Recent work pointed out the heterogeneity and specialized functions of individual components of the ribosome and of 2 NAR Cancer, 2020, Vol. 2, No. 3 the translation initiation factor complexes eIF3 and eIF4F, which are required for recruitment of the ribosome to the mRNA 5 ′ untranslated region (5 ′ UTR) (11).

Here, we focus on the expression and function of eIF3, a multimeric complex, composed of 13 subunits (a-m), connecting the 43S pre-initiation and the eIF4F initiation complexes. The expression of the different subunits is altered in cancers, but the function associated with this deregulation is not fully understood (9,10). Novel insights into the link between eIF3 and cancer have been provided by recent studies showing that eIF3 specifically recognizes mRNA structures (12), mRNA modifications (m 6 A) or, in the case of the eIF3d subunit, the 5 ′ cap of mRNAs (13,14), suggesting that eIF3 subunits drive selective mRNA translation in cancer. Our previous work showing that eIF3e is essential for proliferation and survival of GBM cells (15) prompted us to investigate whether, where and how this factor impacts GBM patient outcome by regulating mRNA translation. Our results support a model whereby the heterogeneous expression of eIF3e in GBM is linked to its specialized function in mRNA translational regulation and steers functional pathways involved in GBM progression and response to treatments.

MATERIALS AND METHODS

Cell lines and culture conditions

Human glioblastoma cell lines U87 (ATCC HTB-14, obtained from the American Type Culture Collection, Manassas, VA, USA), U251, LN18 and SF767 (obtained from C. Simon's laboratory, UPENN, Philadelphia, PA, USA) were used and routinely maintained in Dulbecco's Modified Eagle Medium (Lonza, Portsmouth, NH, USA) supplemented with 10% fetal bovine serum, 2 mM L-glutamine, 100 U/ml penicillin and 100 g/ml streptomycin at 37 • Cin5%CO 2humidified incubators as previously described. Cells were tested for mycoplasma contamination by PCR. When indicated, cells were treated with cobalt chloride (CoCl 2 ; Sigma, St Louis, MO, USA) at 100 M(2× 50 Mat24hand48h after transfection) or with MG132 (5 M for 2 h; Sigma, St Louis, MO, USA) or irradiated at 5 Gy using the Gammacell 40 Exactor irradiator (Nordion, Ottawa, ON, Canada).

Cell transfection

For siRNA transfections, human glioblastoma cells were transfected with 20 nmol/l of siScramble (siScr: Qiagen, Venlo, Limburg, The Netherlands) or 20 nmol/l of siRNA against human Int6/eIF3e (si3e: SI02662499, FlexiTube eIF3E siRNA, 20 nmol, 5 ′ -CCCAAAGGUCGCGAUAAUAUU-3 ′ , Qiagen; or si3e#2: Dharmacon ON-TARGET plus SMART pool eIF3E siRNA 3646, 10 nmol) or against DDX3X (siDDX3X: SIGMA, 50 nmol, 5 ′ -CCUAGACCUGAACUCUUCAGAUAAU-3 ′ ), combined with Lipofectamine™ RNAiMAX as recommended by the manufacturer (Invitrogen Life Technologies, Carlsbad, CA, USA) as previously described (15). For luciferase mRNA transfections, 250 ng of reporter mRNA was transfected 48h after siRNA transfection in 48-well plates using Lipofectamine 2000 reagent according to the manufacturer's instructions. Cells were subsequently incubated at 37 • C for 16 h following mRNA reporter transfections before harvesting and analysis.

Western blot analysis

Cells were lysed in lysis buffer [50 mM HEPES,pH 7,150 mM NaCl, 10% glycerol, 1% Triton, 100 mM NaF, 1 mM EGTA, 1.5 mM MgCl 2 , 10 mM sodium pyrophosphate complemented by protease inhibitors (Sigma-Aldrich, St Louis, MO, USA) at 1/100]. For immunoblotting analysis, proteins were resolved on 10% denaturing polyacrylamide gels and were transferred to nitrocellulose membranes. The blots were blocked for 30 min with TBST-5% milk and then probed overnight with primary antibodies against Int6/eIF3e (Bethyl, A302-985A), HIF-2␣ (Novus Biologicals, NB100-122), HIF-1␣ (Cayman Chemical, 10006421), GADD45␣ (Cell Signaling, CS4362), CDC45 (Abcam, ab-108350), FAS (Santa Cruz, sc-4233), ␤-actin (Santa Cruz, sc-8432), eIF3c (Cell Signaling, CS2068), eIF3a (Abcam, ab-128996), eIF3b (Santa Cruz, sc-16377), eIF3d (Bethyl, A301-758A), eIF3f (Bethyl, A303-005A), GAPDH (Santa Cruz, sc-32233), DDX3X (Santa Cruz, sc-365768), eIF4E (Cell Signaling, CS9742S), hnRNPU (Santa Cruz, sc-32315), eIF4A (Santa Cruz, sc-50354), eIF4G (Santa Cruz, sc-11373), phospho-ser209-eIF4E (Cell Signaling, CS9741S) and ␤-tubulin (Cell Signaling, CS2146). Gel quantification was performed using ImageJ (Research Services Branch, NIH, Bethesda, MD, USA). The secondary antibody was either HRP-conjugated anti-rabbit or HRPconjugated anti-mouse. The blots were developed using the ECL system (Amersham Pharmacia Biotech) according to the manufacturer's instructions.

RT-qPCR

Reverse Transcription (RT) was performed on 1 gt otal RNA using the RevertAidH Minus First (Thermo Fisher) according to the manufacturer's instructions. A total of 12.5 ng of cDNA was analyzed by qPCR with the SybrGreen (KAPA KK4605) and a StepOnePlus (Applied Biosystems/Life Technologies, Carlsbad, CA, USA). Expression of eIF3e, HIF-1␣,H I F -2 ␣, GADD45␣,F A S , UBE2V1, CDC45 and GAS5 was standardized using B2M as a reference. Relative levels of expression were quantified by calculating 2 ∧ CT, where CT is the difference in CT (cycle number at which the amount of amplified target reaches a fixed threshold) between target and reference. All primer sequences are available in Table 1.

Flow cytometry

72 h after transfection with siRNA (siScr or si3e) and 48 h after ionizing radiation (IR) treatment (5 Gy) or CoCl 2 treatment (100 M), cells were collected, washed in Phosphate-Buffered Saline (PBS) and incubated in 100 lof Annexin-binding buffer 5X (10 mM HEPES, pH 7.4, 140 mM NaCl, 2.5 mM CaCl 2 ), containing 5 l of Annexin V-FITC antibody and 1 l of Propidium Iodide (PI; Invitrogen Life Technologies, Carlsbad, CA, USA) solution After ultracentrifugation, fractions were harvested with a gradient fractionator and polysome profiles were continuously visualized with a monitoring at A 254 nm . The fractions were collected and pooled before mRNA extraction; nonpolysomal (NP), light polysomal (LP) and heavy polysomal (HP) mRNAs. Pooled fraction mRNAs and cytoplasmic mRNAs were extracted using TRIzol ® reagent (Invitrogen). TRIzol ® reagent was added on samples (3 volumes) and incubated for 5 min at room temperature. Chloroform was added (0.2 ml per 1 ml of TRIzol ® ) and samples were shacked vigorously by hand for 15 s and incubated for 2-5 min at room temperature. After centrifugation at 12 000 × g for 15 min at 4 • C, the aqueous phase was recovered and submitted to the RNA isolation with isopropanol (0.5 ml per 1 ml of TRIzol ® ) overnight at -20 • C. The samples were then centrifugated at 12 000 × g for 30 min at 4 • C and RNAs were washed by adding 75% ethanol (1 ml 75% ethanol per 1 ml of TRIzol ® ), vortexing briefly and centrifugating samples (at 7500 × g for 5 min at 4 • C). RNAs were then dried and resuspended in RNase-free water.

Microarray analysis

Before labeling, RNA concentration and integrity were measured using a Nanodrop™ spectrophotometer (Nan-oDrop Technologies, Wilmington, DE, USA) and controlled on 'Lab-on-Chip' by a Bioanalyzer (Agilent Technologies, Stockport, UK), according to the manufacturer's instructions. From each pool, 100 ng of RNA was converted into labeled cRNA with nucleotides coupled to a Cy3 fluorescent dye using the Low Input Quick Amp Labeling kit (Agilent Technologies, Palo Alto, CA, USA) following the manufacturer's instructions. The quality and quantity of the resulting labeled cRNA were assessed using a NanoDrop™ spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). We have done two labelings/sample to obtain the quantity of Cy3 -labeled cRNA necessary for the hybridization (600ng).Each Cy3labeled cRNA was hybridized to human microarray ship (Agilent Human V2 Microarrays, 8*60k, G4858A) for 17 h at 65 • C, 10 rpm as described in the One-Color Microarray-Based Gene ExpressionAnalysis Protocol (Agilent). The hybridized arrays were then washed and scanned using an TECAN MS200 scanner. Data were extracted from the scanned image using Feature Extraction V11.5.1.1 (Agilent Technologies, Redwood City, CA, USA) and analyzed using GeneSpring v.7.2 software (Agilent Technologies). Differential translation analysis was assessed with ANOTA analysis as described previously (16).

′ UTR sequence analysis

Sequence motifs were discovered using DREME (17).

Where more than one transcript from one gene was present, only the longest UTR sequence was used; 156 sequences were used in the analysis. Motifs up to 8 nt long were sought in the 5 ′ UTR sequences against the same sequences randomized using DREME. We considered the predicted consensus sequences with P < 1 × 10 -4 as significant motifs.

Minimum free energies ( G)o f5 ′ UTR secondary structures were calculated using the Vienna RNA package (version 1.8.5) (18). The Kolmogorov-Smirnov test was performed to investigate whether there were significant differences between eIF3e-dependent and eIF3e-independent groups.

Plating efficiency clonogenicity assay

U251 and LN18 glioblastoma cells were transfected with siRNA (siScr or si3e); after 48 h, cells were harvested and plated in six-well plates at different concentrations (10,15 or 20 cells/cm 2 for siScr and 20, 30 or 40 cells/cm 2 for si3e) in duplicate. 48 h later, cells were irradiated with an IR scale (from 0 to 4 Gy) using the Gammacell 40 Exactor irradiator (Nordion, Ottawa, ON, Canada). Cells were then incubated for ∼10 days until colonies were visible with the naked eye without any joining between colonies. Then, plates were 4 NAR Cancer, 2020, Vol. 2, No. 3 washed and cells were fixed with 10% formalin for 10 min, the formalin was removed and cells were covered with 10% crystal violet oxalate (RAL Diagnostics, Martillac, France) for 10 min; plates were rinsed with water until no additional color comes off the plate. Colonies were then counted to calculate the dose enhancement factor (DEF). DEF is measured as follows: for the same biological effect, the dose on the curve radiation alone (here Scr) is divided by the dose on the curve radiation + treatment (here 3e). A DEF >1 means that the treatment is functioning as a radiosensitizer.

Immunohistochemistry and scoring

Formalin-fixed, paraffin-embedded glioblastoma tissue sections were immersed in a Tris-EDTA buffer (pH 9) provided in the EnVision™ FLEX High pH kit K8000 (Dako, Ely, UK) and incubated for 20 min at 96

TCGA GBM

Gene expression from 529 patients in the glioblastoma database of The Cancer Genome Atlas (TCGA; http://xena. ucsc.edu/) and 10 normal tissues was used to compare GBM subtypes and assess correlations between genes among different subgroups.

Statistical analysis

Correlations between quantitative data were assessed using the Spearman's rank correlation coefficient. Differences between subgroups were assessed with the Mann-Whitney U test or t-test. The signed-rank test was used to assess relationships between paired data. Dunn's pairwise comparisons were adjusted for multiple testing with Benjamini-Hochberg correction. For the TCGA cohort, overall survival was defined as the time from initial diagnosis to death from any cause (event) or the last follow-up (censored data). Univariable and multivariable analyses were performed using the log-rank test and Cox proportional hazards model; hazard ratios (HR) were estimated with 95% confidence intervals. Univariable analyses were performed using the logrank test. Two-sided P < 0.05 was considered statistically significant. Significance was represented by asterisks, where * P < 0.05, ** P < 0.01 and *** P < 0.001.

RESULTS

eIF3e regulates HIF mRNA translation

We previously demonstrated that eIF3e inhibition resulted in decreased expression of the hypoxia-inducible factors (HIFs) in GBM cells associated with a decreased proliferation and increased apoptosis (15). HIFs are transcription factors, composed of two subunits: HIF-␣ and HIF-␤, and the two major HIF-␣ subunits are HIF-1␣ and HIF-2␣. These factors control the transcription of >150 genes important for GBM cells, mainly involved in angiogenesis, metabolism, proliferation and cell migration (19).

HIFs and hypoxia are known to compromise the cytotoxic effects of IR and limit the success of radiotherapy (20). To further investigate the eIF3e-HIF interplay, we defined whether eIF3e depletion in U251 and LN18 GBM cell lines downregulated HIF proteins by transcriptional or post-transcriptional mechanisms. As shown in Figure 1A, knockdown of eIF3e in GBM cells decreased HIF protein levels and this effect was maintained in conditions that induce HIF protein accumulation as a result of protein stabilization by the proteasome inhibitor MG132. Consistent with this result, treating GBM cell lines with CoCl 2 ,ah ypoxia mimetic agent that stabilizes HIF proteins, only partially reverses HIF protein loss (Figure 1A) or apoptosis (Figure 1B) induced by eIF3e silencing. The percentage of 6 NAR Cancer, 2020, Vol. 2, No. 3 apoptotic cells (increasing from 7.2% to 25.5% in U251 and from 5.8% to 14% in LN18) following eIF3e depletion is indicative of biological significance. These results demonstrated that the effect of eIF3e modulation on HIF protein levels was related neither to GBM cell type nor solely to a change in protein stability. In addition, eIF3e silencing in U251 cells did not alter HIF mRNA levels (Figure 1C). To explore whether the amount of HIF mRNA engaged in translation was affected by the eIF3e knockdown, we transfected U251 cells with eIF3e-specific (si3e) or control siRNAs (siScr) and then fractionated cytoplasmic extracts of these cells by sucrose density gradient centrifugation. RNA was isolated from translationally inactive (NP) or active (including LP and HP) fractions, and the distribution of HIF mRNA (or the control B2M mRNA) along these fractions was determined by RT-qPCR. We observed that eIF3e loss induced a change in the distribution of the HIF-1α mRNA (Figure 1D), but not the control B2M mRNA or the HIF-2α mRNA (data not shown), along the sucrose gradient. Indeed, HIF-1α mRNAs shifted from the highest to the lowest polysome fractions, suggesting that eIF3e inhibits HIF-1α mRNA translation.

eIF3e affects the translation of mRNAs relevant to GBM progression and response to treatments

Next, based on eIF3 functions in the regulation of both global and mRNA-specific translation (11), we further investigated the potential involvement of eIF3e in protein synthesis. We previously reported that eIF3e knockdown had no significant impact on bulk protein synthesis in GBM cells (15). Therefore, we pushed further our analysis to identify mRNAs whose translation is mediated by eIF3e by performing genome-wide analysis of mRNA polysomal profiles in U251 GBM cells. Interestingly, sucrose density gradient separation revealed no major differences in polysome distribution in U251 cells where eIF3e is silenced (Figure 2A and Supplementary Figure S1A). These data show that eIF3e modulation does not significantly affect global mRNA translation, which corroborates our previous 35 Smethionine metabolic labeling of protein synthesis (15). However, combining polysome profiling and microarray hybridization, we identified 278 differentially expressed mR-NAs between control cells and cells transfected with si3e in total cytosolic fraction, and 650 differentially translated mRNAs associated with polysomes (Supplementary Table S1). Interestingly, the abundance and/or polysome association of 405 mRNAs were increased upon eIF3e knockdown, whereas those of 245 mRNAs were decreased (thereafter called trans-UP and trans-DN, respectively; Figure 2B).

Within the mRNAs affected by eIF3e deletion in GBM cells, we focused our attention on the altered expression of those that are relevant to cancer progression and response to treatments. Translation of two major mRNAs of the p53 pathway, GADD45α and FAS, was increased, respectively, by 6-and 3.5-fold, and translation of the survival and DNA replication/repair response mRNAs FGF11, UBE2V1, JAK3 and CDC45 was decreased, respectively, by 5-, 4-, 2-and 2-fold, in eIF3e-depleted U251 cells (Supplementary Table S1). In order to confirm our analysis, we validated some of these targets, including HIF-1α,b y RT-qPCR on polysomal fractions and total mRNAs from U251 cells (Figure 2C and Supplementary Figure S1B). The expression of the eIF3e-regulated targets identified above followed the same pattern as observed in the microarray data analysis. More specifically, we observed an increased translation of GADD45α and FAS and a decreased translation of UBE2V1 and CDC45 mRNAs (Figure 2C). Consistent with Figure 1D, HIF-1α mRNA translation was significantly decreased by 2-fold in eIF3e-depleted U251 cells (Supplementary Figure S1B). Additionally, we were able to confirm these changes of mRNA levels in polysomes at the protein level by western blot analysis in several GBM cell lines (Figure 2D and Supplementary Figure S1C andD).

Although the effects at the translation and protein levels for all genes were qualitatively consistent, we noted a quantitative difference, in particular for GADD45␣ and FAS (Figure 2D and Supplementary Figure S1C). While this could be explained by previous observations suggesting a rapid turnover of these two proteins (21,22), it remains to be determined in future studies whether this discrepancy is related to eIF3e.

To directly investigate whether the 5 ′ UTR drives eIF3especific translational regulation, we focused on validating eIF3e targets that were highly regulated, either positively or negatively. To this end, we transfected RNA reporters containing the luciferase open reading frame fused to the 5 ′ UTRs of GADD45α, FAS or CDC45 mRNAs into U251 cells (Figure 2E). In agreement with both polysomal profiling and western blot analysis, we found that the activity of 5 ′ UTR-luciferase fusions was either upregulated (for GADD45α or FAS reporters) or downregulated (for CDC45 reporters) upon knockdown of eIF3e relative to control cells (Figure 2E). Differences in the magnitude of the effects (Figure 2C-E and Supplementary Figure S1C andD) indicate the possibility of complex translational and possibly post-translational regulation, which is quite consistent with the multivalent function of eIF3e in translation, and more generally in gene expression. Overall, these results suggest that eIF3e affects the selective translation of mRNAs with opposite effects on protein synthesis and regardless of the GBM cell line. Of note, mRNAs were not the only type of transcripts whose association with polysomes was modulated by eIF3e depletion. Indeed, among the RNAs targeted for translation by eIF3e, we found several other RNA types, including long non-coding RNAs (lncRNAs; Supplementary Figure S2A). While the regulation of lncRNAs by eIF3e remains to date unappreciated, this is consistent with the work of Lee et al. who showed a direct interaction between eIF3 and several ncRNAs (12). To validate this result, we focused on GAS5 since this lncRNA is translationally regulated by eIF3e (Supplementary Table S1) and directly targeted by eIF3 subunits in living cells (12). Importantly, GAS5 plays a role in glioma cell growth, invasion and apoptosis (23). Consistent with polysome profiling data (Supplementary Table S1), we found that eIF3e silencing increased the association of GAS5 with polysomal fractions (Supplementary Figure S2A).

Next, we sought to go further in the investigation of the translatome of eIF3e. Recent transcriptome-wide analysis of in cellulo eIF3-RNA interactions revealed that eIF3 subunits preferentially interacted with specific subsets of mR- NAs, predominantly in 5 ′ UTRs (12). Further structurefunction investigation of eIF3 target mRNAs uncovered the existence of specific stem-loop structures with opposite effects on translation (12). These results are consistent with our eIF3e translation data (Figure 2) and led us to explore and compare 5 ′ UTR features of both eIF3e translationally repressed and activated mRNAs. We found that trans-UP mRNAs had longer 5 ′ UTRs with greater predicted secondary structure stability [i.e. lower minimum free folding energy ( G)] compared to the trans-DN mR-NAs. However, there was no significant relationship with the G/C content (Supplementary Figure S2B). In the trans-UP group of mRNAs, but not in the trans-DN mRNAs, the DREME software showed the enrichment of partially selfcomplementary GC-rich sequences, possibly forming secondary structures (Supplementary Figure S2C). The lack of motif enrichment in the trans-DN mRNAs suggested that this effect is not related to a particular sequence or structure.

Cooperation of eIF3e, eIF3d and DDX3X drives selective translational regulation

Previous works demonstrated that eIF3e forms a binary complex with the d subunit, eIF3d, of the eIF3 multimeric assembly. Moreover, this interaction occurs independently of the whole eIF3 complex and requires the C-terminal region of eIF3e for assembly into eIF3 (24).

Based on these observations, it has been proposed that eIF3e forms a module with eIF3d (25). Since eIF3e could lead to co-depletion of eIF3d (24,26,27), we tested whether this occurs in GBM cells. We found that eIF3e silencing reduced eIF3d expression while leaving the other subunits unaffected (Figure 3A). This suggests that, as proposed by Shah et al. (27), eIF3e could function in synergy with eIF3d to orchestrate an mRNA-specific translational program in GBM cells. Since, unlike eIF3d, eIF3e does not have RNA interaction domains, its binding to the RNA could be mediated by eIF3d. Therefore, to get insights into the molecular mechanism underlying the function of eIF3e in mRNA-specific translation, we studied the network of RNA-binding proteins (RBPs) associated with the 5 ′ UTRs bound by eIF3d (derived by available CLIP datasets) ( 12) using the AURA database (28). The coregulation analysis revealed that the most enriched factor bound to eIF3d-associated 5 ′ UTRs (Supplementary Figure S4A) is DDX3X, an RNA helicase that plays opposite roles in mRNA translation (29)(30)(31). eIF3d and DDX3X (32) shared 1953 sites (62.7% of eIF3d hits, 16.6% of DDX3X hits) that map mainly to 5 ′ UTRs (Figure 3B). Collectively, eIF3d and DDX3X share many target mRNAs, suggesting a possible co-regulation of common target mRNAs by these two RBPs. The possibility that eIF3e, eIF3d and DDX3X may work in concert on the same targets to regulate their translation was first tested by immunoprecipitating DDX3X using GBM cytoplasmic extracts. In agreement with (33), we found that DDX3X co-immunoprecipitated both eIF3 subunits (but not GAPDH that also displays RNA-binding activity) in an RNA/DNA-independent manner (Figure 3C and Supplementary Figure S3). Then, we analyzed whether DDX3X interacted with mRNAs translationally regulated by eIF3e. The intersection of datasets from eIF3e polysome profiling (Supplementary Table S1) and DDX3X CLIP data (32) revealed a significant enrichment of DDX3X with the mRNAs whose translation is increased after eIF3e silencing (Supplementary Figure S4A). Then, we performed RNA chromatography to verify the binding status of eIF3e, eIF3d and DDX3X on two previously validated eIF3e mRNA translational targets, CDC45 and GADD45α, which we showed to be down-and upregulated by eIF3e, respectively (Figure 2C-E). Consistent with the enrichment of DDX3X binding sites on the trans-UP mRNAs (Figure 3B and Supplementary Figure S4A), we found that DDX3X preferentially bound the GADD45α 5 ′ UTR compared to the CDC45 5 ′ UTR (Figure 3D). This differential binding was most evident when comparing uncapped RNAs, and a similar pattern was shared by eIF3e/eIF3d, suggesting that the binding of the three factors to the GADD45α 5 ′ UTR is cap independent and relies on a specific sequence/structure. Another important difference between the two RNAs was the differential binding of eIF3e/eIF3d to capped and uncapped CDC45 or GADD45α RNAs. Indeed, while the recruitment of eIF3e/eIF3d on the CDC45 5 ′ UTR occurred mainly following the addition of the cap, their binding to the GADD45α was mainly cap independent with only a limited change after cap addition (Figure 3D). Consistent with these in vitro results, immunoprecipitation of DDX3X bound to mRNAs from U251 GBM cells resulted in preferential binding of DDX3X to the GADD45α mRNA compared to the CDC45 mRNA (Supplementary Figure S4B). In addition, similarly to Figure 3D, loss of eIF3e decreased the recruitment of DDX3X on GADD45α mRNA but not on CDC45 mRNA (Supplementary Figure S4B), indicating an RNA-specific RBP-helicase cooperative recruitment. To further support this model, we performed polysome analysis of DDX3X-depleted U251 cells (Supplementary Figure S4C). We observed that DDX3X silencing did not significantly modify global polysomal profiles (Supplementary Figure S4C), yet the translation of the GADD45α mRNA was significantly increased compared to that of CDC45 or the B2M control mRNA (Figure 3E). This conclusion was further supported by the analysis of the effect of DDX3X silencing on protein accumulation (Figure 3F and Supplementary Figure S4D) and expression from RNA reporters (Figure 3G). Overall, these results show that the activating and repressive effects of eIF3e on mRNA translation might be explained in part by a distinct binding pattern of eIF3e, eIF3d and DDX3X on the target mRNAs, suggesting the existence of an RBP-helicase cooperative interaction mechanism (34).

In addition to these differential protein/RNA interactions, and in agreement with previous results (35), eIF3e depletion induced a decrease in the phosphorylation of eIF4E (Supplementary Figure S4E). MNK-mediated phosphorylation of eIF4E affects eIF4F activity and is associated with cancer progression, likely by modulating the translation of specific mRNAs (36,37), suggesting that this modification might contribute to the mechanisms underlying eIF3edriven selective mRNA translation.

eIF3e modulation impact on GBM cell radiosensitization

To explore the biological consequences associated with eIF3e modulation, positively and negatively eIF3eregulated mRNAs were subjected to gene ontology (GO) enrichment analysis. The 405 genes that are preferentially translated after eIF3e silencing were largely enriched for genes involved in the cellular response to stress, including response to external stimulus, drugs or IR (Figure 4A). Strikingly, proteins encoded by the trans-DN mRNAs may also influence these pathways. Indeed, among these genes we found ALDH1A (Supplementary Table S1), a GSC marker that is associated with tumor growth and resistance to chemoradiotherapy (38). Radiation is a fundamental component of GBM therapeutic treatments, though radiation-surviving cells can evolve toward more aggressive and invasive phenotypes, constituting one major resistance mechanism (39,40). Tumors respond to radiation-induced DNA lesions by triggering a sophisticated network of DNA damage signaling and repair pathways that determine cellular fate, including survival, death and genomic stability. Based on our previous findings (15), we wondered whether eIF3e silencing could enhance the cytotoxic effects of radiation. To assess the radiosensitizer potential of eIF3e inhibition, we depleted eIF3e in U251 and LN18 GBM cells (that are radiosensitive and radioresistant, respectively) and performed a plating efficiency clonogenic assay. Interestingly, we observed that eIF3e silencing significantly decreased the survival fraction after irradiation of U251 cells with a mean DEF >1(Figure4B). A similar trend was observed for LN18 cells (Figure 4B). This suggests that eIF3e inhibition leads to a radiosensitization phenomenon in both U251 and LN18 cells. Overall, these results suggest that eIF3e knockdown could impact GBM cell response to treatments.

Deregulated expression of eIF3e in specific GBM regions could impinge on selective protein synthesis impacting GBM outcome

The murine Int6 gene, encoding eIF3e, was originally identified as a site of mouse mammary tumor virus (MMTV) integration in MMTV-induced tumors and a neoplastic lesion (41). Since then, the role of eIF3e in tumorigenesis has been controversial and various reports have implicated differing roles for this protein, both as an oncogene and as a tumor suppressor depending on cancer type, tumor stage or the baseline level of eIF3e expression (42,43). To examine the expression pattern of eIF3e in GBM patients, we analyzed eIF3e mRNA expression on a large cohort of GBM cancer patients (Cancer Genome Atlas Network) made available by the TCGA (https://www.cancer. gov/tcga). Strikingly, eIF3e mRNA expression was significantly increased in the primary GBM tumors compared to normal tissue (Figure 5A). This result was reinforced by data extracted from the Oncomine database (http://www. oncomine.org), where several sets that compare expression in GBM with normal brain show a highly significant increase in eIF3e mRNA levels (Supplementary Figure S5A). A Pearson's correlation analysis was performed using the TCGA database, and the results indicated that eIF3e expression was highly correlated with genes with functions in protein synthesis and translational regulation (Supplementary Table S2). As shown in Figure 5B, stratification of samples along low and high expression (median threshold) of the top-ranked eIF3e-correlated genes showed significant differences in overall survival, with high expression associated with poor prognosis. The risk score based on eIF3e and top-ranked correlated genes (linear predictor) was significantly associated with overall survival (HR = 2.72 [1.78; 4.14], P < 0.0001) and remains a good prognostic factor when adjusting on clinical parameters (P = 0.0249; Supplementary Figure S5B). Thus, multivariate analysis supports the clinical relevance of the eIF3e signature. Additionally, eIF3e overexpression in human GBM samples was confirmed at the protein level by western blot analysis of graded human glioma specimens (Figure 5C). The expression of eIF3e correlated with morphologically determined tumor grades, with low levels in low-grade tumors and high levels in high-grade tumors. To investigate whether these results were clinically relevant, we collected eight matched GBM tissues from the initial surgery for untreated tumors and from the second surgery after treatment failure with radiation and chemotherapy (temozolomide) for eIF3e immunohistochemistry (IHC) analysis. We observed an overall trend of increased eIF3e expression in recurrent tumors compared with primary untreated tumor sections (Figure 5D). Similarly, the proportions of eIF3epositive tumor cells were generally increased in recurrent tumors compared with matched primary tumors (Figure 5D). Collectively, these results show that eIF3e is upregulated in post-treatment GBM tissues, indicating that eIF3e may play an important role in the development of chemoand radioresistance.

GBMs are highly heterogeneous malignancies at histological, genetic and gene expression levels (5,44). With the aim to characterize eIF3e mRNA distribution in different GBM histological regions, we explored the Ivy GBM database (http://glioblastoma.alleninstitute.org/) that provides RNA sequencing data from seven lasermicrodissected GBM regions: leading edge, infiltrating tumor, cellular tumor, perinecrotic zone, pseudopalisading cells around necrosis, hyperplastic blood vessels and microvascular proliferation. Data analysis indicated that the expression of eIF3e was highly enriched at the microvascular proliferation and pseudopalisading areas of tumors compared with other regions within the tumor (Figure 6A). To validate these results, we performed IHC and observed that eIF3e staining colocalized with both GBM regions. However, eIF3e subunits showed differential expression over distinct regions of GBM (Supplementary Figure S6A). For instance, the eIF3c mRNA did not show significant enrichment in a specific area of the tumor, while eIF3a expression was significantly increased in hyperplastic blood vessels and microvascular proliferation area but not in pseudopalisading region (Supplementary Figure S6B). It is important to note that the expression of eIF3e in both regions is correlated with gene groups having different functions (Supplementary Figure S7 and Supplementary Table S2). Specifically, in pseudopalisading we found several terms associated with translational regulation. Among the best-correlated genes, we noticed several mRNAs containing an oligopyrimidine tract at their 5 ′ termini (5 ′ TOP). S2) (i). Kaplan-Meyer survival analysis from (ii). (C) Western blot analysis of eIF3a, eIF3e and eIF3d levels in protein extracts from diffuse low-grade gliomas (grade II) and high-grade GBMs (grade IV) (i). Protein levels in (i) from high-grade GBMs were normalized to GAPDH protein levels and plotted relatively to the levels of protein from the low-grade gliomas (ii). Data are presented as mean values ± SEM of two independent experiments; * P < 0.05, NS: non-significant (Wilcoxon test). (D) Representative IHC images for eIF3e expression in primary untreated tumors (i) and post-radiation recurrent tumors (ii) from matched GBM patients. Percentage of eIF3e positive-stained cells in primary untreated tumors and post-radiation recurrent tumors from matched GBM patients (n = 8; P < 0.05, Wilcoxon test) (iii).

14 NAR Cancer, 2020, Vol. 2, No. 3 These mRNAs encode components of the translational machinery whose expression at the transcriptional and translational levels is sensitive to mTOR regulation. This observation, together with previous findings showing that phosphorylated mTOR displayed a predilection for pseudopalisading perinecrotic cells in GBM [START_REF] Korkolopoulou | Phosphorylated 4E-binding protein 1 (p-4E-BP1): a novel prognostic marker in human astrocytomas[END_REF], suggests that eIF3e is part of a specific gene expression program requiring coordinated activation of the translational machinery, possibly under control of mTOR. By contrast, the expression of eIF3e in the microvascular area was correlated with genes involved in chromosome duplication (Supplementary Figure S7), in accordance with the notion that endothelial cells of tumor blood vessels have high frequencies of excess centrosomes [START_REF] Hida | Tumor-associated endothelial cells with cytogenetic abnormalities[END_REF].

Pseudopalisading necrosis and microvascular proliferation are unique histological features that differentiate GBM from lower grade gliomas and make GBM one of the most hypoxic and angiogenic of all tumors [START_REF] Rong | Pseudopalisading' necrosis in glioblastoma: a familiar morphologic feature that links vascular pathology, hypoxia, and angiogenesis[END_REF]. Pseudopalisading cells express high nuclear levels of HIF-1␣ that in turn activates an adaptive transcriptional response to hy-poxia, which includes activation of glycolytic metabolism, secretion of proangiogenic factors and increased cell migration. Importantly, the pseudopalisading areas with a necrotic core create the hypoxic niche for GSCs. Indeed, hypoxia promotes stemness through the activation of genes implicated in self-renewal and dedifferentiation (including HIF-1␣), and protects tumor cells and GSCs from chemoand radiotherapy [START_REF] Hambardzumyan | Glioblastoma: defining tumor niches[END_REF]. Since we observed that eIF3e regulates the expression of HIFs (Figure 1) and GSC markers (ALDH1A1; Supplementary Table S1), we hypothesized that a deregulation of its expression in GSCs could contribute to cell stemness by selectively modifying translation of key GSC regulators. To investigate the expression of eIF3e in GSCs, we analyzed the microarray data from Mao's dataset (GSE67089) including 11 GSC and 5 normal astrocyte samples (38). We found that eIF3e was one of the most upregulated translation factor-encoding gene in GSCs compared with normal human astrocytes (Figure 6B). Then, we analyzed whether eIF3e expression changed between the Mes and the PN subtypes. These are characterized by striking genetic and phenotypic differences, including aberrantly high expression of ALDH1A, marked resistance to radiation and more aggressive phenotype in Mes GSCs (38). Interestingly, eIF3e expression was specifically higher in the Mes subtype than PN one (Figure 6B), indicating that eIF3e might be involved in GBM heterogeneity through directing specific gene expression programs associated with therapeutic resistance in GSCs.

DISCUSSION

The eIF complex is a paradigm of the complexity of the translational apparatus, linked to the deregulation of the expression of its components, their modulability and heterogeneity in cancer cells (7)(8)(9)(10), whose understanding is key for elaborating novel and effective targeting strategies. More recently, this notion of complexity has been broadened by the, as yet poorly understood, ability of some factors, including eIF3 (12,13), to influence both the basic functional mechanisms and those guiding their activity to shape mRNA translation programs allowing cells to respond and adapt to environmental conditions. By focusing on the e subunit of the eIF3 complex, this work revealed additional facets of this complexity associated with both intratumoral heterogeneity of eIF3 expression and the combinatorial activation and repression of eIF3e translational programs linked to GBM resistance to radiation therapy.

Underlying the reduced sensitivity to radiation is the ability of cells to repair damaged DNA, limit apoptosis, evolve to a stem-like phenotype and cope with hypoxic stress and metabolic reprogramming, among others. Our results support the notion that eIF3e is a hub that coordinates these different pathways through combinatorial activation and repression of synthesis of key protein factors at the crossroad of different resistance mechanisms. Among the genes positively regulated by eIF3e, HIF-1␣ stands out because its enhanced expression after irradiation enables adaptation to hypoxic stress through gene expression reprogramming impacting angiogenesis, apoptosis, migration and, as reported more recently, metabolism and is a potential target for the development of future GBM therapeutics [START_REF] Semenza | Targeting HIF-1 for cancer therapy[END_REF]. A possible link between eIF3e and reprogramming of GBM metabolism is also suggested by our polysome profiling analysis showing selective translation of genes involved in glycolysis/gluconeogenesis, including the stem cell marker ALDH1 (Supplementary Table S1). Considering that (i) eIF3e, HIF-1␣ and ALDH1 are strongly expressed in highgrade glioma (Figure 5) [START_REF] Chen | USP9X deubiquitinates ALDH1A3 and maintains mesenchymal identity in glioblastoma stem cells[END_REF], particularly in hypoxic pseudopalisading regions including niches for GSC and conferring survival advantage in the tumor microenvironment (Figure 6)( 51), (ii) the expression of eIF3e is correlated in these areas with a translational signature of poor prognostic possibly related to the mTOR control (Figure 5), (iii) eIF3e increases the translation (but not the accumulation) of HIF-1α (Figure 1)a n dALDH1 mRNAs (Supplementary Table S1) and finally (iv) a link between eIF3e and glucose metabolism has recently been established (27,[START_REF] Guan | A unique ISR program determines cellular responses to chronic stress[END_REF][START_REF] Miao | eIF3a mediates HIF1alpha-dependent glycolytic metabolism in hepatocellular carcinoma cells through translational regulation[END_REF], we propose that eIF3e could activate selective translational programs related to energy metabolism contributing to the mechanisms underlying resistance to treatments in specific GBM regions.

Our polysome profiling results, which were validated at the mRNA and protein levels as well as using RNA reporters (Figure 2), suggest that eIF3 could concomitantly modulate these mechanisms by repressing the translation of mRNAs involved in the stress response, including GADD45α. The activation of this gene with multiple functions in DNA repair, cell cycle, senescence and induction of apoptosis is essential for mediating anticancer activity of multiple genotoxic treatments and its absence might abrogate their effects in cancer cells [START_REF] Tamura | GADD45 proteins: central players in tumorigenesis[END_REF]. In GBMs and GSCs, radiation modifies gene expression primarily at the level of translation and GADD45␣ has been found targeted for increased protein synthesis [START_REF] Lu | Radiation-induced changes in gene expression involve recruitment of existing messenger RNAs to and away from polysomes[END_REF][START_REF] Wahba | Polysome profiling links translational control to the 18 NAR Cancer[END_REF][START_REF] Wahba | Radiation-induced translational control of gene expression[END_REF]. Our study suggests that translational repression modulated by eIF3e high expression in GBM adds to the post-transcriptional regulatory mechanisms targeting GADD45␣ for both selective repression in unstressed cells and activation upon DNA damage [START_REF] Lal | Posttranscriptional derepression of GADD45alpha by genotoxic stress[END_REF][START_REF] Badura | DNA damage and eIF4G1 in breast cancer cells reprogram translation for survival and DNA repair mRNAs[END_REF].

In addition to the alteration of expression and opposite translational effects, this work highlights that the complexity of eIF3e-mediated translational regulation involves multiple overlapping mechanisms. First, the abundance of eIF3e impacts the accumulation and/or activity of other translation factors, including other eIF3 subunits, notably eIF3d [in agreement with (24,27)a n dF i gure 3] with which eIF3e interacts, and eIF4E at both the phosphorylation [in agreement with (35)] and mRNA translation levels (Figure 3 and Supplementary Table S1). Second, the eIF3e-dependent regulatory mechanisms rely on sequence/structure features and protein partners (Figure 3) whose combination may determine the translational outcome. Among the trans-regulators, we identified DDX3X enriched on mRNAs repressed by eIF3e (Figure 3), including GADD45α mRNAs (Figure 3). These results are consistent with the observation that these transcripts have longer andmorestable5 ′ UTRs. While the role of DDX3X bound to these RNAs requires further investigation, the pattern of protein interaction to the CDC45 and GADD45α mRNAs (which are activated and repressed by eIF3e, respectively) displayed a different requirement of eIF3e/eIF3d/DDX3X for the presence of the 5 ′ cap (Figure 3). The ability 16 NAR Cancer, 2020, Vol. 2, No. 3 of eIF3e/eIF3d to similarly bind uncapped and capped GADD45α mRNAs strongly supports the possibility that eIF3e/eIF3d selectively inhibit translation through binding cis-regulatory elements/structures within the 5 ′ UTR (12). Cap addition resulted in a decreased binding of DDX3X to GADD45α 5 ′ UTR, but not to CDC45 5 ′ UTR, which could be explained by its displacement from direct binding to RNA and indirect recruitment by eIF4E, thus participating in the translational repression of GADD45α through the formation of a DDX3X-eIF4E inhibitory complex (30). Based on the observation that DDX3X is abnormally increased in high-grade gliomas [START_REF] Hueng | DDX3X biomarker correlates with poor survival in human gliomas[END_REF], that this increase in expression induces nucleation of stress granules (SGs) depending on the DDX3X-eIF4E interaction [START_REF] Shih | Critical roles of RNA helicase DDX3 and its interactions with eIF4E/PABP1 in stress granule assembly and stress response[END_REF][START_REF] Hilliker | The DEAD-box protein Ded1 modulates translation by the formation and resolution of an eIF4F-mRNA complex[END_REF]andthat SGs associated with translational inhibition also contain eIF3 subunits [START_REF] Buchan | Eukaryotic stress granules: the ins and outs of translation[END_REF], it is possible that the translational regulation of eIF3e targets involves these cellular compartments [START_REF] Buchan | Eukaryotic stress granules: the ins and outs of translation[END_REF]. However, it seems unlikely that eIF3e/DDX3X regulation would involve upstream open reading frames, as proposed for some (but not all) eIF3 subunits ( 31), since we did not find ATF4 mRNA as a translational target for eIF3e.

Taken together, these data indicate that eIF3e acts as an important component of the initiation translation machinery in GBM cells. Although the molecular mechanisms underlying the anti-GBM activity of eIF3e silencing are not clear yet, we could think that by directly regulating the translation of specific subsets of mRNAs involved in tumorigenic pathways, eIF3e seems to support GBM malignant phenotype and progression. In addition to its potential prognostic value, eIF3e inhibition, through the modulation of the HIFs, could also represent an effective adjuvant therapy to the standard radio/chemotherapies. In conclusion, our work shows that eIF3e could become a promising target for GBM patients and it might be of special interest to develop specific new therapeutic agents to reverse eIF3eregulated changes in the protein synthesis profile.

Figure 1 :

 1 Figure 1: Glial cells in the central nervous system and their functions. ..................................

Figure 2 :

 2 Figure 2: Developmental stages of neurons and glial cells in rodent CNS. .............................

Figure 3 :

 3 Figure 3: Transcription factors and signaling in gliogenesis. ..................................................

Figure 4 :

 4 Figure 4: WHO grades and characteristics of glioma. .............................................................

Figure 5 :

 5 Figure 5: Cellular changes induced by IDH1-mutation in glioma cells. ..................................

Figure 6 :

 6 Figure 6: Characteristic genetic mutations in adult gliomas. ...................................................

Figure 7 :

 7 Figure 7: Possible cellular origins of glioma. ..........................................................................

Figure 8 :

 8 Figure 8: Schematic representation of intra tumoral heterogeneity in glioblastoma. ..............

Figure 9 :

 9 Figure 9: DLGG heterogeneity as revealed by single cell RNA sequencing. ..........................

Figure 10 :

 10 Figure 10: Biochemical pathways involved in metabolism .....................................................

Figure 11 :

 11 Figure 11: Model systems in diffuse low-grade glioma. ..........................................................

Figure 12 :

 12 Figure 12: Phenotypic plasticity of glia. ..................................................................................

Figure 13 :

 13 Figure 13: Cellular heterogeneity in IDH1-mutated DLGG. .................................................

Introduction 1 . 2 .

 12 cells line the ventricles and central canal of the brain and spinal cord. They are involved in the synthesis of cerebrospinal fluid. They may contribute to osmotic balance through cotransporters. They express certain transporters such as Na + /K + /Cl -co-transporters, glucose transporters-GLUT-1, GLUT-2 and monocarboxylate transporter MCT1 (MacAulay and Zeuthen, 2010). Thus brain is composed of complex yet intricate network of different cell types that are dependent on each other for their survival and functioning. It is widely accepted that glial cells are equally important in the brain for proper neuronal functioning. An insult to any of the cell type can have huge impact on the normal brain functioning. Deeper understanding on glia biology-their generation, development, properties and functions as well as the intrinsic Introduction and extrinsic factors that influence their behavior in normal and disease conditions are essential to apprehend the complexity of the nervous system. Development of glial cells in the central nervous system

Figure

  Figure adapted from[START_REF] Laug | A glial blueprint for gliomagenesis[END_REF]

  classification that was primarily based on the microscopy, classifying according to the phenotype of cells and their differentiation state. This modified version of 2007 classification for the first time took into consideration the molecular features of the tumors. 2007 classification had grouped all tumors with astrocytic phenotype as astrocytoma even if they were clinically similar or not. 2016 classification based their foundation on the genetic alterations commonly found in different subtypes that are described based on histopathological criteria. Broadly, two major alterations 1) Isocitrate Dehydrogenase (IDH) mutation, a commonly observed mutation in diffuse lower grade glioma and 1p/19q codeletion specifically identified in oligodendroglioma made their way into the classification system. Accordingly, adult diffuse glioma are primarily grouped into five subtypes-grade IVglioblastoma IDH wildtype; glioblastoma IDH-mutant; diffuse (grade II) or anaplastic (grade III) astrocytoma, IDH wildtype; diffuse (grade II) or anaplastic astrocytoma (grade III), IDHmutant/ 1p/19q intact; oligodendroglioma (grade II) or anaplastic oligodendroglioma (grade III), IDH-mutant and 1p/19q co-deleted.

  individual cell type to become glioma cell of origin. Results from experimental models depend on a number of intrinsic and extrinsic factors. The cell type used in the study, the combination of the genetic lesions, the developmental stage of the experimental animal, the intrinsic inter-cellular heterogeneity of mice used in the study all contribute to the variation in results obtained. Majority of the mutational combinations results in histopathology of high grade gliomas. Systematic understanding of the minimum required mutations necessary to generate grade II glioma in specific cell type are still not clearly understood.

  existing within individual tumors. Single tumor mass can exist with intricate mosaicismtumor clones arise that can drift and branch during evolution of the tumor. Selective environmental cues can induce secondary mutations in the proliferating cells the frequency of which can change with time and space. For example, chemotherapy and/or radiotherapy can preferentially kill specific tumor clones and promote the expansion of treatment resistant clones that may carry a different genetic mutation providing survival advantage. Sampling of tumor fragments from 11 glioblastoma, spatially distinct in the tumor mass demonstrated the co-existence of transcriptional subtypes

  Introductionheterogeneity has been significantly boosted by emerging advances in single cell RNA sequencing (scRNA-seq). Advancement of single cell sequencing technologies has improved our understanding on cellular heterogeneity and complexity in glioma. Larger part of earlier research in low-grade glioma relies on tissue analysis to identify putative cellular subtypes through phenotypic characterization, or bulk transcriptomic analysis of tissue samples.Transcriptomic analysis of tumor tissue is insufficient in providing information specifically on tumor cells alone, as the RNA pool comprises the entire cell populations present in the tissues. There has been a lot of research carried out in the field of glioblastoma to identify the putative cancer stem cells (CSCs) using various surface markers, purifying those cells to perform dilution assays of neurosphere formation or xenograft transplantation to generate secondary tumors. Such functional studies have not been successful in low grade glioma to understand the biology of CSCs.

  glioma cells harboring ATRX mutations to exhibit longer telomeres than TERTp mutations suggesting ALT mechanisms. Genome wide DNA methylation analysis identified three subtypes of IDH mutated glioma-1) 1p/19q co-deleted, 2) non-co-deleted with G-CIMP (CpG island methylation phenotype) high and 3) non-co-deleted G-CIMP low. The G-CIMP low IDH1 non-co-deleted tumors represented an intermediate group of transition towards higher grade and were associated with upregulation of cell cycle genes such as CDK4 and CDKN2A as well as increased transcription of SOX2, a neural stem cell marker. Upon tumor recurrence G-CIMP high tumors shifts to a demethylated phenotype similar to G-CIMP low

Introduction 1 . 7 .

 17 DLGG models-in vitro and in vivo 1.7.

Tp53

  in the PDGF mouse model generated aggressive tumors characteristic of GBM. Deletion of P53 and Rbpj, a transcriptional co-activator of Notch signaling accelerated tumor growth with upregulation of ASCL1 and OLIG2, transcription factors involved in glioma proliferation and development. These results were also in accordance with the gene expression studies on Notch targets in REMBRANDT and TCGA data sets. Higher expression of HES5, HEY2, HEY1 and RBPJ correlated with better prognosis for patients in grade II and grade III astrocytoma(Giachino et al., 2015).The role of Notch1 in DLGG requires thorough investigation. As these initial evidences highlight the role as a tumor suppressor, it needs investigation on how Notch1 exerts its tumor suppressive functions in glioma cells and further to identify its interacting partners. As there are opposing oncogenic and tumor suppressive roles of Notch in primary and secondary GBM, the functional role of intrinsic genetic mutation on Notch needs to be explored. Notch Introduction mutations are frequently observed in oligodendroglioma. What could be possible role of Notch in grade II astrocytoma? Does it have an activating role in its progression? Better understanding on the role of Notch signaling pathway in DLGG could open new avenues for Notch targeted therapies.

  PhD project was to systematically characterize diffuse low-grade gliomas and to investigate the role of potential signaling pathways in the genesis of tumor subpopulations in DLGGs. In order to achieve this, my specific aims were Aim 1: To identify the potential tumor subpopulations in human diffuse low-grade glioma Aim 2: To characterize the identified tumor populations for expression of distinct transcription factors and activated signaling pathways. Aim 3: To investigate the potential of activated signaling pathways in determining the fate of tumor subpopulations in DLGGs To identify different subpopulations in DLGGs (aim 1), I performed immunostaining on cryopreserved OCT embedded resected human DLGG tissue sections with SOX9 and OLIG1 Context, Aims and Approaches

  primary cultures were transduced with Notch Intracellular domain (NICD) to activate the Context, Aims and Approaches signaling. I further performed qPCR on various markers associated with both SOX9 + and OLIG1 + cells. Interestingly, I observed that Notch activation upregulated SOX9 related gene expression and downregulated all OLIG1 + cells associated markers suggesting the deterministic role of notch signaling on the phenotype of the low-grade glioma (discussed in chapter 3.1) During my PhD, I have also contributed to a side project that is completed and published.

  . Also, these cellular subpopulations could have a spatial territory within a tumor as well as interchange their identity depending on the environmental cues required for their sustainability[START_REF] Minata | Phenotypic Plasticity of Invasive Edge Glioma Stem-like Cells in Response to Ionizing Radiation[END_REF]{Minata, #1906)). But such extensive and elaborate studies are very rare in the field of diffuse lowgrade glioma. While there has been slow but steady growth in the knowledge about genetic and transcriptomic profiles in DLGGs(Auvergne et al., 2013; Cooper et al., 2010; Noushmehr et al., 2010) (Johnson et al., 2014) (Wiestler et al., 2014) (Suzuki et al., 2015) (CancerGenome Atlas Research et al., 2015) (Bai et al., 2016; Ceccarelli et al., 2016), information at the cellular level remains largely elusive. A recent study using single cell RNA sequencing has shed some light in this regard, where in the authors have shown that both astrocytoma and oligodendroglioma is comprised of three tumoral subpopulationsdifferentiated astrocytic and oligodendrocytic cell types which are the major components along with a smaller population of cycling stem cells(Tirosh et al., 2016; Venteicher et al., 2017). While this information advanced our understanding about DLGG heterogeneity, there still remains many open questions. For instance, does the RNA or gene expression profiles reported in several studies co-relate with the information at protein expression, which ultimately determines the identity of the cells? What is the genesis of such cellular heterogeneity in DLGGs? Is it possible to alter the heterogeneity by externally manipulating gene expression or signaling pathways? Answering these questions is of highest prominence not only to understand the landscape of heterogeneity in DLGGs but most importantly for designing better therapeutics.In this article, using immunofluorescence on freshly resected human patient samples with IDH1 mutated diffuse low-grade glioma; we have identified and characterized the cellular subpopulations to give a detailed view on the identity of these cells. Our analyses revealed the presence of two major non-overlapping cell populations expressing Sox9 or Olig1 transcriptional factors, in both astrocytoma and oligodendroglioma. Strikingly, these two cell populations express a unique set of molecular markers including transcription factors and signaling molecules. In order to identify potential signaling mechanisms determining the phenotypes of these cells, we purified tumoral cells from freshly resected tumors and overexpressed Notch intracellular domain to upregulate Notch-Signaling cascade.Interestingly, activation of Notch signaling in DLGG cells downregulate oligodendrocyticlineage specific gene expressions and upregulate astrocytic-lineage gene expressions. This, signify the possible role of Notch in the generation of cell populations by regulating their phenotype in diffuse low-grade glioma.

  Very briefly, the coverslips containing control-YFP transduced and NICD overexpressed cells were placed in bathing (extracellular) solution composed of 147 mM NaCl; 5 mM KCl; 2 mM CaCl2; 1.5 mM MgCl2; 10 mM HEPES; 10 mM Glucose, pH 7.4. Recording pipettes filled with the solution containing 135 mM K-methane-sulfonate; 0.1 mM EGTA; 8 mM KCl; 10 mM HEPES; 2 mM MgATP; 0.5 mM NaGTP, pH 7.3 was sealed to the cell membrane. SK3 current was recorded by applying 600 ms electrical ramp from -80 mV holding potential to gradually increasing up to +60 mV in both control-YFP and NICD-YFP transduced cells. Ionomycin-induced and apamine-sensitive SK3 current densities were measured by adding 10 µM Ionomycin and 1 µM apamine to the bathing solution respectively. All recordings were made at room temperature using an Axopatch 200B amplifier and a Digidata 1322A A/D board (Molecular Devices) and acquired at 5 kHz.

Figure 1 :

 1 Figure 1: DLGG is composed of at least two non-overlapping subpopulations of cells. (A) Immunofluorescence analysis performed on an Oligodendroglioma and Astrocytoma tissue sections using SOX9 (green) and OLIG1 (red) transcriptional factors revealed the presence of two non-overlapping subpopulations of cells. White arrowheads mark the cells that express either SOX9 or OLIG1 alone. Scale bar=20 µm. Bar diagram reveals the percentage of SOX9 + cells (green), OLIG1 + cells (red) and percentage of cells double positive for SOX9 + and OLIG1 + (orange) among the total number of cells counted manually using Hoechst positive cells. (B) SOX9 + cells have distinct set of protein expression. Double staining of SOX9 on one oligodendroglioma with marker proteins such as APOE, KCNN3, CRYAB and ID4 showed a preferential expression of these proteins to SOX9 + cells. White arrowheads identify the SOX9 + cells positive for the marker expression. Yellow arrowheads and yellow arrow represent OLIG1 + cells negative for the marker proteins and vice versa respectively. Scale bar=20 µm. (C) Pie diagram represents the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure 2 :

 2 Figure 2: OLIG1 + cells express proteins associated to oligodendrocytes. (A) Immunofluorescence performed on one oligodendroglioma using PDGFRa and SOX8 revealed their close association with the OLIG1 + cells in DLGG tissue sections. GPR17 was expressed by both SOX9 + and OLIG1 + cells but with higher percentage in OLIG1 + cells. White arrowheads represent OLIG1 + cells expressing the marker proteins. Yellow arrowheads and yellow arrow represent OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure 3 :

 3 Figure 3: OLIG1 + cells express neural precursor cell markers. (A) Immunofluorescence performed on an oligodendroglioma displayed that both SOX9 + and OLIG1 + cells express SOX2 but MASH1 and SOX4 were particularly expressed by OLIG1 + cells. White arrowheads represent double positive cells. Yellow arrowheads and yellow arrow represent SOX9 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in

Figure 4 :

 4 Figure 4: SOX9 + cells specifically express/activate various signaling molecules and receptors. (A) In oligodendroglioma, double staining of SOX9 + cells with HEY1 and HEY2, the downstream effector proteins of Notch Signaling revealed specific expression in the SOX9 + cells. (B) Immunofluorescence of SOX9 + cells with BMP4 and its downstream effector pSMAD1/5 revealed cell type specific expression in SOX9 + cells in oligodendroglioma. (C) SOX9 + cells have distinct expression of p-ERK, downstream of MAPK pathway. White arrowheads represent double positive cells. Yellow arrowheads and yellow arrow represent OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (D) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure 5 :

 5 Figure 5: OLIG1 + cells specifically express/activate various receptors and IDH1. (A) OLIG1 + cells in an oligodendroglioma have distinct expression of EGFR and PTPRZ1 in these cells. Expression of wildtype IDH1 was closely associated to OLIG1 + cells. White arrowheads represent double positive cells in the tissue sections and pie chart indicates the percentage of the double positive cells in green and single positive SOX9 + or OLIG1 + cells in red. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure 6 :

 6 Figure 6: Notch 1 activation modifies DLGG cell phenotype and reduces the proliferation of cells. (A) QPCR analysis of 15 genes in O4 tumoral cells in 4 primary cultures after notch activation by transducing cells with control-YFP or NICD-YFP for 5 days. Genes labeled in blue and brown are SOX9 and OLIG1 associated markers respectively. Unpaired t-test is used for significance calculation. (B) QPCR analysis of 18 genes in LGG 275 cell line after notch activation by transducing cells with control-YFP or NICD-YFP for 5 days (N=5). Genes labeled in blue and brown are SOX9 and OLIG1 associated markers respectively. Unpaired t-test is used for significance calculation. (C) Immunofluorescence of upregulated NICD, HEY1, CRYAB and downregulated KI67 upon Notch-1 activation. Scale bar=10 µm. (D) QPCR analysis of 17 genes after Notch inhibition by treating cells with 2 pharmacological g-secretase inhibitors DAPT (10 µM) and LY411575

Figure 7 :Figure 8 :

 78 Figure 7: Notch-1 modifies the electrophysiological properties of LGG 275 cells. (A) Immunofluorescence of KCNN3 in control-YFP and NICD-YFP transduced cells showing its upregulation and localization in the cell membranes. The change in cellular morphology upon Notch activation is also visible from the images. Scale bar=10 µm. (B) SK3 channels electrical activity was studied using the whole-cell patch clamp technique under voltage clamp configuration. Representative current recorded by applying 600 ms electrical ramp from -80 mV holding potential to +60mV in control-YFP (top) and NICD-YFP transduced (bottom) cells. An increase in current density was observed in the presence of 10 µM Ionomycin (to increase intracellular Ca2+ level). This increase was specifically blocked after treating cells with 1 µM apamin (a specific SK channels blocker). (C) Mean ± S.E.M current densities obtained at +40 mV from current/voltage curves obtained after 500 ms voltage steps from -80 mV holding potential to +40 mV, every 10 mV. Ionomycine induced current and apamin-sensitive current densities were significantly higher in NICD transduced cells compared to control cells (n=6). * p<0.05; ** p<0.01

Figure S1 :

 S1 Figure S1: RNA levels in the Human Brain database (Ben Barres's lab) showing the specificity of cellular markers to astrocytic and oligodendrocytic lineages used in our study. Data obtained from(Zhang et al., 2016). Database-(http://www.brainrnaseq.org/)

Figure S3 :

 S3 Figure S3: SOX9 + cells have distinct set of protein expression. (A) Double staining of SOX9 on one astrocytoma with marker proteins (APOE, KCNN3, CRYAB and ID4) showed a preferential expression of these proteins in SOX9 + cells. White arrowheads identify the SOX9 + cells positive for the marker expression. Yellow arrowheads and yellow arrow represent OLIG1 + cells negative for the marker proteins and vice versa respectively. Yellow arrowheads represent OLIG1 + cells negative for the marker proteins and vice versa respectively. Scale bar=20 µm. (B) Pie diagram represents the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S4 :

 S4 Figure S4: OLIG1 + cells express proteins associated to oligodendrocytes. (A)Immunofluorescence performed on one astrocytoma using PDGFRa and SOX8 revealed their close association with the OLIG1 + cells in DLGG tissue sections. GPR17 was expressed by both SOX9 +

Figure S5 :

 S5 Figure S5: OLIG1 + cells express neural precursor cell markers. (A) Immunofluorescence performed on an astrocytoma displayed that both SOX9 + and OLIG1 + cells express SOX2 but MASH1 and SOX4 were particularly expressed by OLIG1 + cells. White arrowheads represent double positive cells. Yellow arrowheads and yellow arrow represent SOX9 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S6 :

 S6 Figure S6: SOX9 + cells specifically express/activate various signaling molecules and receptors. (A) In astrocytoma, double staining of SOX9 + cells with HEY1 and HEY2, the downstream effector proteins of Notch Signaling revealed specific expression in the SOX9 + cells. (B) Immunofluorescence of SOX9 + cells with BMP4 and its downstream effector pSMAD1/5 revealed cell type specific expression in SOX9 + cells in astrocytoma. (C) SOX9 + cells have distinct expression of p-ERK, downstream of MAPK pathway. White arrowheads represent double positive cells. Yellow arrowheads and yellow arrow represent OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (D) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S7 :

 S7 Figure S7: Expression profiles for BMP2/4 and NOGGIN in DLGG databases. (A) RNA levels for BMP2, BMP4 and NOGGIN in non tumoral brain, oligodendrogliomas, astrocytomas and oligoastrocytomas in Rembrandt (Madhavan et al., 2009) and Kamoun (Kamoun et al., 2016) databases. Used test are t tests with corrections for multiple testing (p-values with Bonferroni correction). The number of cases is indicated in brackets. (B) Pearson correlation matrix of mRNA expression of BMP2, BMP4 and NOGGIN in LGG-TCGA database reveals significant correlation.These histograms, scatter dot diagrams and correlation matrix were created with the database mining website GLIOVIS(Bowman et al., 2017)

Figure S9 :

 S9 Figure S9: OLIG1 + cells specifically express/activate various receptors and IDH1. (A) OLIG1 + cells in an astrocytoma have distinct expression of EGFR and PTPRZ1 compared to SOX9 + cells. Expression of wildtype IDH1 was closely associated to OLIG1 + cells. White arrowheads represent double positive cells in the tissue sections. Yellow arrowheads and yellow arrow represent SOX9 + /OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S10 :

 S10 Figure S10: Cell type specific expression of IDH1 in adult mice and human brain. Single cell transcriptomic data from adult mice and human brain reveals oligodendrocytic specific expression of wildtype IDH1. In mice, oligodendrocytic cells of different developmental stages express IDH1 with

Figure S11 :

 S11 Figure S11: Phenotypic characterization of tumoral O4 + cells isolated from glioma samples. (A) Bright field image of O4-purified tumoral human cells in culture. (B) Immunofluorescence for O4show that the vast majority of cells (>90%) express O4 but not ATRX and are thus tumoral. One example of rare O4 + cell maintaining expression of ATRX and so probably non-tumoral is presented to show the quality of staining (yellow arrow). (C) Immunofluorescence staining for IDH1R132H and absence of nuclear ATRX confirmed their tumoral nature of the culture. Tumoral cells detected with IDH1 R132H staining express SOX10 at low level in contrast to the rare IDH1 R132H -nontumoral cells, which were highly positive for SOX10 (yellow arrow). Tumoral cells express EGFR, the oligodendrocytic markers CNP and OLIG1 together with SOX9. Note that OLIG1 is localized both in the nucleus and cytoplasm. Scale bar=10 µm (D) Graphical representation of tumoral human O4-purified cells in culture with their phenotypes.

Figure S12 :

 S12 Figure S12: Phenotypic characterization of non-tumoral O4 + cells isolated from glioma patient samples. (A) Bright field image of highly branched non-tumoral cells isolated with O4 purification from a supratotal glioma resection with ATRX and IDH1 R132H mutations. (B) Immunofluorescence

Figure S13 :

 S13 Figure S13: Phenotypic characterization of the LGG 275 cell line. (A) Bright field image of LGG 275 cells. (B) Immunofluorescences for indicated makers. LGG275 express CNP, EGFR, OLIG1 and SOX9. The tumoral nature of these cells is indicated by the presence of IDH1 R132H and absence of ATRX. Note that these cells show different nuclei size and shape. Scale bar=10 µm

Figure S15 :

 S15 Figure S15: Database mining for CRYAB, BMP2 and HEY2 co-expression and HEY1/2 expression in different glioma grades. (A) Expression of CRYAB is positively correlated to HEY2 and BMP2 expression in the diffuse low-grade gliomas TCGA database. (B) Expression of HEY1 and HEY2 is reduced in high grade compared to low-grade gliomas in the TCGA database. Used test are t tests with corrections for multiple testing (p-values with Bonferroni correction). The number of cases

  Figure S2: DLGG is composed of at least two non-overlapping subpopulations of cells. (A) Immunofluorescence analysis performed on additional 2 Oligodendroglioma and 2 Astrocytoma tissue sections using SOX9 (green) and OLIG1 (red) transcriptional factors revealed the presence of two non-overlapping subpopulations of cells. White arrowheads mark the cells that express either SOX9 or OLIG1 alone. Scale bar=20µm. Bar diagram reveals the percentage of SOX9 + cells (green), OLIG1 + cells (red) and percentage of cells double positive for SOX9 + and OLIG1 + (orange) among the total number of cells counted manually using hoechst positive cells. (B) SOX9 + and OLIG1 + cells are tumoral with loss of ATRX expression and presence of IDH1R132H protein expression. Upper images: representative images of one astrocytoma tissue section showing the absence of nuclear expression of ATRX in majority of the SOX9 + and OLIG1 + cells. The white head arrows mark tumoral cells and yellow arrowheads mark non-tumoral cells that express nuclear ATRX. Lower images: representative images of oligodendroglioma sections double stained with IDH1R132H protein and SOX9 or OLIG1 revealed the tumoral nature of these cells. White arrowheads mark OLIG1 + cells expressing IDH1R132H protein and yellow arrowheads represent the SOX9 + or IDH1R132H single positive cells. Majority of the OLIG1 + cells express IDH1R132H protein while only a minor population of SOX9 + cells expressed the mutated protein. (C) Bar diagram represents the percentage of ATRX -/ IDH1R132H + tumor cells (green)in the tissue, percentage of SOX9 + or OLIG1 + cells (red) and percentage of SOX9 + or OLIG1 + cells that are mutated for ATRX or IDH1R132H (orange). Scale bar=20 µm.

Figure S3 :

 S3 Figure S3: SOX9 + cells have distinct set of protein expression. (A) Double staining of SOX9 on one astrocytoma with marker proteins (APOE, KCNN3, CRYAB and ID4) showed a preferential expression of these proteins in SOX9 + cells. White arrowheads identify the SOX9 + cells positive for the marker expression. Yellow arrowheads and yellow arrow represent OLIG1 + cells negative for the marker proteins and vice versa

Figure S4 :

 S4 Figure S4: OLIG1 + cells express proteins associated to oligodendrocytes. (A) Immunofluorescence performed on one astrocytoma using PDGFRa and SOX8 revealed their close association with the OLIG1 + cells in DLGG tissue sections. GPR17 was expressed by both SOX9 + and OLIG1 + cells but with higher percentage in OLIG1 + cells. White arrowheads represent OLIG1 + cells expressing the marker proteins. Yellow arrowheads and yellow arrow represent OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S5 :

 S5 Figure S5: OLIG1 + cells express neural precursor cell markers. (A) Immunofluorescence performed on an astrocytoma displayed that both SOX9 + and OLIG1 + cells express SOX2 but MASH1 and SOX4 were particularly expressed by OLIG1 + cells. White arrowheads represent double positive cells. Yellow arrowheads and yellow arrow represent SOX9 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S6 :

 S6 Figure S6: SOX9 + cells specifically express/activate various signaling molecules and receptors. (A) In astrocytoma, double staining of SOX9 + cells with HEY1 and HEY2, the downstream effector proteins of Notch Signaling revealed specific expression in the SOX9 + cells. (B) Immunofluorescence of SOX9 + cells with BMP4 and its downstream effector pSMAD1/5 revealed cell type specific expression in SOX9 + cells in astrocytoma. (C) SOX9 + cells have distinct expression of p-ERK, downstream of MAPK pathway. White arrowheads represent double positive cells. Yellow arrowheads and yellow arrow represent OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (D) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S7 :

 S7 Figure S7: Expression profiles for BMP2/4 and NOGGIN in DLGG databases.

  Figure S8: Expression profiles for BMP2/4 and NOGGIN in DLGG. (A) QPCR data showing increased expression of BMP2, BMP4 and NOGGIN in five IDH1R132H mutated DLGG tissues (4 oligodendrogliomas and 1 astrocytoma) compared to non-tumoral brain tissues. Tests used are two-tailed t-tests. (B) Pearson correlation matrix reveals that BMP2, BMP4 and NOGGIN are significantly correlated in their expression in these DLGG tissues. (C) Western blot analysis for BMP2 and BMP4 proteins in proteins extracted from IDH1-mutated grade II oligodendrogliomas (OII) and IDH1-mutated grade III or II astrocytomas (AIII, AII).The same amount of proteins (20 µg) was loaded in each lane.

Figure S9 :

 S9 Figure S9: OLIG1 + cells specifically express/activate various receptors and IDH1. (A) OLIG1 + cells in an astrocytoma have distinct expression of EGFR and PTPRZ1 compared to SOX9 + cells. Expression of wildtype IDH1 was closely associated to OLIG1 + cells. White arrowheads represent double positive cells in the tissue sections. Yellow arrowheads and yellow arrow represent SOX9 + /OLIG1 + and marker protein single positive cells respectively. Scale bar=20 µm. (B) Pie diagram reveals the percentage of double positive cells in green and single positive cells in red. Number in the pie diagram indicates the percentage of higher proportion of cells in tissues.

Figure S10 :

 S10 Figure S10: Cell type specific expression of IDH1 in adult mice and human brain.

Figure S11 :

 S11 Figure S11: Phenotypic characterization of tumoral O4 + cells isolated from glioma samples. (A) Bright field image of O4-purified tumoral human cells in culture. (B) Immunofluorescence for O4 show that the vast majority of cells (>90%) express O4 but not ATRX and are thus tumoral. One example of rare O4 + cell maintaining expression of ATRX and so probably non-tumoral is presented to show the quality of staining (yellow arrow). (C) Immunofluorescence staining for IDH1R132H and absence of nuclear ATRX confirmed their tumoral nature of the culture. Tumoral cells detected with IDH1 R132H staining express SOX10 at low level in contrast to the rare IDH1 R132H -non-tumoral cells, which were highly positive for SOX10 (yellow arrow). Tumoral cells express EGFR, the oligodendrocytic markers CNP and OLIG1 together with SOX9. Note that OLIG1 is localized both in the nucleus and cytoplasm. Scale bar=10 µm (D) Graphical representation of tumoral human O4-purified cells in culture with their phenotypes.

Figure S12 :

 S12 Figure S12: Phenotypic characterization of non-tumoral O4 + cells isolated from glioma patient samples. (A) Bright field image of highly branched non-tumoral cells isolated with O4 purification from a supratotal glioma resection with ATRX and IDH1 R132H mutations. (B) Immunofluorescence for O4 shows the very high expression of this antigen. The vast majority of cells (>90%) are O4 + . (C) Representative images of immunofluorescence performed on O4 purified cells. Absence of IDH1R132H protein expression and nuclear staining of ATRX reveal the non-tumoral nature of these cells.These cells are highly positive for oligodendrocytic markers such as CNP, OLIG1, and SOX10 and have small and perfectly round nuclei. In contrast, the vast majority of these cells (>90%) do not express EGFR, GFAP and SOX9. Two examples of very rare GFAP + SOX10 -and SOX9 + OLIG1 -cells are presented to show the quality of immunofluorescence (yellow arrows). Of note, non-tumoral cells isolated from glioma resections often-present highly fluorescent green and red auto fluorescent cytoplasmic

Figure S13 :

 S13 Figure S13: Phenotypic characterization of the LGG 275 cell line. (A) Bright field image of LGG 275 cells. (B) Immunofluorescences for indicated makers. LGG275 express CNP, EGFR, OLIG1 and SOX9. The tumoral nature of these cells is indicated by the presence of IDH1 R132H and absence of ATRX. Note that these cells show different nuclei size and shape. Scale bar=10 µm

Figure S15 :

 S15 Figure S15: Database mining for CRYAB, BMP2 and HEY2 co-expression and HEY1/2 expression in different glioma grades. (A) Expression of CRYAB is positively correlated to HEY2 and BMP2 expression in the diffuse low-grade gliomas TCGA database. (B) Expression of HEY1 and HEY2 is reduced in high grade compared to low-grade gliomas in the TCGA database. Used test are t tests with corrections for multiple testing (p-values with Bonferroni correction). The number of cases is indicated

Figure 1 .

 1 Figure 1. pSTAT3 stainings in diffuse low-grade glioma foci. (A) Example of a high cell density foci detected in a diffuse low-grade glioma. H&E: hematoxylin and eosin stainings. Scale bar 500 µm. (B) Representative stainings for pSTAT3 in diffuse low-grade gliomas. Left and right-hand images are taken outside and inside the foci, respectively. Images taken in an oligodendroglioma (upper images) and an astrocytoma (lower images) are presented. Arrows point to pSTAT3 + cells in each inset. Scale bars 150 µm. Quantification of pSTAT3 + cells detected in 5 fields (10,000 µm²) outside and inside the foci in 4 oligodendrogliomas and 4 astrocytomas are presented on the right-hand side. Test = Mann-Whitney tests n = 5, p value = 0.011 for oligodendrogliomas and astrocytomas. (C) Expression of pSTAT3 by tumoral cells. Representative photographs of double immunofluorescences for IDH1 R132H /pSTAT3 and ATRX/pSTAT3 in one grade II oligodendroglioma and one grade II astrocytoma, in and outside the foci. White arrows point to IDH1 R132H+ /pSTAT3 + (oligodendroglioma) and ATRX negative/pSTAT3 + (astrocytoma) cells. The yellow arrow on astrocytoma photograph indicates one example of an ATRX + cell to show the quality of the immunofluorescence. Right-hand histograms show the percentage of tumoral pSTAT3 + cells (e.g. pSTAT3 + cells which are positive for IDH1 R132H or negative for ATRX) outside and inside the foci assessed by IDH1 R132H /pSTAT3 and ATRX/pSTAT3 co-stainings in 4 oligodendrogliomas and 4 astrocytomas (5 fields (10,000 µm²) outside and inside the foci quantified per patient). Only cells with obvious nuclear pSTAT3 staining were counted.

Figure 2 .

 2 Figure 2. qPCR validation of differentially-expressed genes and expression in grade II and III gliomas. (A) qPCR quantification of indicated RNAs in foci and in the other part of the tumour (DLGG) in oligodendrogliomas and astrocytomas. Values represent fold change (foci area/non foci area) of indicated RNA expression normalized by RPLP0 quantification. n = 10 tumours. Test = Wilcoxon matched-pairs test. (B)Expression of indicated genes in grade II and grade III gliomas retrieved from the TCGA database. A similar analysis done for all identified genes is presented in TableS3. OII (Oligodendroglioma grade II, 108 patients). OIII (Oligodendroglioma grade III, 76 patients). AII (Astrocytoma grade II, 87 patients). AIII (Astrocytoma grade III, 98 patients). Tests = Kruskal-Wallis with a Dunn post-hoc test.

Figure 3 .

 3 Figure 3. Detection of ETNPPL protein in human cortex. (A) Immunofluorescence for ETNPPL (green) in human cortex sections. The two middle photographs are high magnification of red dotted-line square on the left-hand image. ETNPPL is detected in the cytoplasm (yellow arrow) or the nucleus (red arrow). The righthand image shows the absence of detection of ETNPPL when the antibody was pre-incubated with the ETNPPL peptide used to generate the antibody. Remaining green dots are likely to be autofluorescent lipofuscin which is often present in human brain samples. Scale bars = 20 µm. (B) Immunofluorescences for ETNPPL (green) and indicated proteins (red) in human cortex. ETNPPL is detected in the nucleus of cells expressing ALDH1L1, CHI3L1, GFAP and VIM (vimentin), identifying these cells as astrocytes. Arrows point to double positive cells. Scale bars = 10 µm.

Figure 4 .Figure 5 .Figure 6 .

 456 Figure 4. Detection of ETNPPL in gliomas. (A) WB detection of ETNPPL in proteins extracted from indicated gliomas. ETNPPL is detected as a single band with the predicted size (55 kDa). The uncropped image of the WB is presented on Supplemental Fig. 8A. Oligo II: grade II oligodendrogliomas, Astro II and III: grade II and III astrocytomas. GBM: IDH1 non-mutated glioblastomas. β-actin detection was used for normalization. Quantification for ETNPPL is presented on the right-hand side panel (4 astrocytomas IDH1 R132H-mutated and 6 glioblastomas). Test = Mann-Whitney test (**p = 0.01). (B) Immunohistochemistry for ETNPPL (brown) in one IDH1-mutated diffuse grade II astrocytoma. The protein is present either in the nucleus (red arrow) or in the cytoplasm (black arrow) of cells. Scale bars = 150 µm. Nuclei are stained with hematoxylin.

Figure 7 .

 7 Figure 7. Functional assessment of ETNPPL expression in glioblastoma cell lines. (A) WB for ETNPPL in proteins extracted from Gli4, Gli7 and LGG85 cells infected with control (luciferase) or ETNPPL induciblelentiviruses and cultured with and without doxycycline. The ETNPPL protein is only detected in ETNPPLinfected cells in the presence of doxycycline. β-actin detection is used as loading control. The uncropped image of the WB is presented on Supplemental Fig. 8B. (B) Immunofluorescence for ETNPPL in Gli7 cells infected with an ETNPPL lentivirus and cultured with and without doxycycline. ETNPPL (red) is strongly detected in the cell nuclei. Infected cells are detected by expression of the GFP (green) gene included in the lentiviral construct. (C) Representative experiment of the effect of ETNPPL overexpression on glioblastoma cell growth. Histograms show the relative number of Gli7 and LGG85 cells cultured for 8 days with and without doxycycline. Test = One-way ANOVA tests. n = 3 independent experiments. (D) Representative experiment of EdU incorporation in Gli7 cells. Histograms represent the % of EdU + cells obtained after 4 hours of incorporation in the presence or absence of doxycycline. test = Mann-Whitney test (*p = 0.024), n = 3 independent experiments.

  Figure S2

Analyses of 6 tumors ( 3

 63 oligodendroglioma and 3 astrocytoma) exhibited similar cellular architecture suggesting that it could be a global phenomenon. Further studies are required to explore the same in large number of tumor samples to confirm this. It is also interesting to observe how the cell types are localized within the tumor. Do the cells exist intertwined to each other or exist in preferential territories separated by unknown boundaries? Does one cell type has a preferential localization in the periphery than the tumor core and thereby possible differential interactions with vessels and white matter tracks? Do they differ in the migratory and malignant potential? Could it be possible that they switch between their phenotypes owing to the environmental cues? Analyzing SOX9/OLIG1 staining over a large number of samples General discussion and Perspectives and on large areas of tissues can give an idea on the localization of cells within the tumors and to identify their territories if any.

  Combining the results from my in vitro experiment, I propose that Notch signaling is the central player in regulating the phenotypes of the DLGG cellular subpopulations and BMP could act synergistically with Notch signaling in inducing astrocytic differentiation. How are Notch signaling activated? Which are the ligands involved? Do other cells in tumor microenvironment be involved in activating Notch signaling are important questions to be answered in the future. Conclusions

Figure 1 .

 1 Figure 1. eIF3e regulates HIF translation in glioblastoma cells. (A) Western blot analysis of HIF-1␣ and HIF-2␣ in GBM cell lines treated with control (siScr) and eIF3e (si3e) siRNAs, with or without a proteasome inhibitor treatment (MG132 at 5 M for 2 h) (i) and with or without a hypoxia mimetic treatment (CoCl 2 at 150 M for 12 h) (ii). Shown is a representative result from two to four experiments. (B) Annexin V/PI staining and flow cytometry analysis for GBM cells treated as in (A). Data are presented as mean values ± SEM of four independent experiments; * P < 0.05, ** P < 0.01, *** P < 0.001 (paired t-test). (C) Quantitative RT-qPCR using specific primers for HIF-1αand HIF-2α mRNAs extracted from U251 cells treated with control (siScr) or eIF3e (si3e) siRNAs. Data are plotted relatively to B2M mRNA amounts and are presented as mean values ± SEM of four to six independent experiments. NS: non-significant (Wilcoxon test). (D) RT-qPCR analysis using specific primers for HIF-1α and B2M mRNAs extracted from translationally inactive (NP) or active (including LP and HP) fractions obtained after fractionation on a sucrose gradient of cytoplasmic extracts of U251 cells treated with control (siScr) or eIF3e (si3e) siRNAs. Shown is a representative distribution of two independent experiments.

Figure 2 .

 2 Figure 2. eIF3e drives selective mRNA translation of mRNAs involved in GBM tumor progression and response to treatments. (A) Polysome profile of U251 cells treated with control (siScr) or eIF3e (si3e) siRNAs. mRNA was isolated from fractions containing three ribosomes (box) and analyzed in parallel with cytoplasmic mRNA using microarrays (see the 'Materials and Methods' section). The peaks corresponding to the 40S, 60S and 80S ribosomal subunits and polysomes are indicated, as well as NP, LP and HP fractions. (B) Microarray data analysis using a Venn diagram showing the overlap between cytosolic mRNAs and translationally regulated mRNAs. The number of eIF3e activated or repressed mRNAs in each group is indicated. (C) Validation of the genome-wide polysome profiling in (A) by RT-qPCR analysis from pooled NP and HP fractions using specific primers for the indicated mRNAs and quantification by analyzing the ratio HP/NP [error bars ± SEM of three experiments; * P < 0.05, *** P < 0.0005 (paired t-test)]. (D) Western blot analysis of the indicated proteins in U251 and LN18 cells treated with control (siScr) or eIF3e (si3e) siRNAs. (E) Ratio of Renilla/Firefly luciferase activities (Rluc/Fluc) (ii) determined using U251 cells treated with control (siScr) and eIF3e (si3e) siRNAs, followed by co-transfection with Rluc and Fluc mRNA reporters depicted in (i) [error bars ± SEM of three independent experiments; * P < 0.05 (paired t-test)].

Figure 5 .

 5 Figure 5. High eIF3e expression in GBM impacts GBM patient outcome. (A) eIF3e mRNA expression using TCGA data in normal tissue (n = 10) and GBM primary tumor (n = 529). The band inside the box shows the median and the whiskers show the upper and lower extremes (two-sided nonparametric Mann-Whitney test and Benjamini-Hochberg procedure was used for multiple comparisons). (B) GBM patient clustering with the top-ranked eIF3e-correlated genes (see Supplementary TableS2) (i). Kaplan-Meyer survival analysis from (ii). (C) Western blot analysis of eIF3a, eIF3e and eIF3d levels in protein extracts from diffuse low-grade gliomas (grade II) and high-grade GBMs (grade IV) (i). Protein levels in (i) from high-grade GBMs were normalized to GAPDH protein levels and plotted relatively to the levels of protein from the low-grade gliomas (ii). Data are presented as mean values ± SEM of two independent experiments; * P < 0.05, NS: non-significant (Wilcoxon test). (D) Representative IHC images for eIF3e expression in primary untreated tumors (i) and post-radiation recurrent tumors (ii) from matched GBM patients. Percentage of eIF3e positive-stained cells in primary untreated tumors and post-radiation recurrent tumors from matched GBM patients (n = 8; P < 0.05, Wilcoxon test) (iii).

Figure 6 .

 6 Figure 6. eIF3e expression in different GBM histological regions and in GSCs. (A) Relative mRNA expression for eIF3e in different tumor regions from the Ivy GBM database. Data are presented as mean values ± SEM; * P < 0.05, ** P < 0.01, *** P < 0.001, NS: non-significant (Benjamini-Hochberg test) (i). Representative IHC images for eIF3e expression in microvascular proliferating (ii) and pseudopalisading regions (iii). (B) Genome-wide transcriptome microarray analysis (GSE67089) showing that eIF3e was among the most upregulated translation factors in glioma spheres (i). mRNA expression analysis (GSE67089) of eIF3e in the mesenchymal (Mes) and the proneural (PN) subtypes of GSCs compared with normal neurosphere (ii). * P < 0.05 and *** P < 0.001, by one-way ANOVA followed by Dunnett's post-hoc test. n = 6forPN ,n = 3 for Mes and n = 1 for normal neurosphere.

1. Introduction 1.1. Central Nervous System: Cells and their functions

  IntroductionThe absence of IDH mutation has a heterogeneous outcome. Maximal surgical resection improves overall survival in DLGG patients irrespective of the molecular status[START_REF] Di Carlo | IDH wild-type WHO grade II diffuse low-grade gliomas. A heterogeneous family with different outcomes. Systematic review and meta-analysis[END_REF]. Not all IDH-wt have similar poor prognosis. Low-grade gliomas can be further stratified based on the additional mutations that they carry. Tumors with Epidermal Growth

	Factor Receptor (EGFR) amplification, BRAF, and H3 histone family 3A (H3F3A) mutations
	occur in a mutually exclusive manner. Myeloblastiosis (MYB) amplification is associated
	with favourable prognosis while tumors bearing EGFR amplification, H3F3A and Telomerase
	Reverse Transcriptase promoter (TERTp) mutations together are considered 'molecular high
	grade' with IDH-wt DLGG with a median OS of 1.23 years if otherwise OS can be obtained
	close to 7 years (Aibaidula et al., 2017).
	1.3.5.2.	Diffuse Astrocytoma

1.3.5.2.1. Epidemiology of diffuse astrocytoma (AII)

Patients with IDH1 mutant diffuse astrocytoma have a mean age of diagnosis of 36 years and a median overall survival of 9.3 years

Introduction 1.3.5.3. Diffuse Oligodendroglioma

	1.3.5.3.1. Epidemiology of diffuse oligodendroglioma
	Patients with IDH1 mutated oligodendroglioma have a median age of diagnosis of 44 years

1.3.6. Primary and secondary glioblastoma 1.3.6.1.

	. Gliomas with TERT mutation alone
	are primarily grade IV glioma and glioma with TERT and IDH mutation without 1p/19q co-
	deletion are very rare. TERT have a favorable prognosis in the presence of IDH mutation and
	1p/19q co-deletion. Regardless of the IDH mutation, TERT mutations are generally observed
	in older patients (Eckel-Passow et al., 2015).

  These mutations have their significant prognosis in determining the outcome of the patients when appearing alone or in combination with other mutations. A study in 2015 showed that idh1 mutations, 1p/19q codeletion and TERTp mutations could stratify tumors according to the age at diagnosis, survival probabilities and grades of tumors. Triple positive mutation group representing oligodendroglioma has better overall survival. These tumors seem to be "genomically silent"

as they seem to acquire fewer other mutations and respond better to chemotherapy and radiations. Tumors with idh1 mutations alone were observed in patients of youngest age group with a mean age of 37 years at diagnosis and had intermediate prognosis. Two-third of this group had astrocytoma of grade II or III mostly acquiring TP53 and ATRX mutations.

Introduction 1 .7.2. In vitro model systems

 1 Generation of a reliable in vivo mouse model of glioma requires to have a good understanding of various criteria-what are the minimum genetic aberrations required for the model of interest, which among them are the best combinations, which are the cells to be targeted, what

Introduction 1 .8. Phenotypic plasticity of glial cells

 1 Lineage conversions of glial cells have been demonstrated through various studies both in vivo and in vitro. Forced expression of lineage related transcription factors were sufficient enough to convert astrocytes to neurons or stem-like cells. These were developed as a new tool of regenerative medicine for brain repair in neurodegenerative diseases. Expression of proneural gene such as Neurogenin-2 and its combination with other transcription factors could directly reprogram astrocytes to various functional neurons such as dopaminergic, glutamatergic with active conductance in vitro[START_REF] Berninger | Functional properties of neurons derived from in vitro reprogrammed postnatal astroglia[END_REF] [START_REF] Heinrich | Directing astroglia from the cerebral cortex into subtype specific functional neurons[END_REF].

	Human astrocytes were dedifferentiated into stem/progenitor cells through ectopic expression
	of reprogramming factors SOX2, OCT4 and NANOG in specific culture conditions (Figure

12) (Corti, 2012 #2279}. The reprogrammed cells were able to function as multipotent cells giving rise to neurons, astrocytes and oligodendrocytes. These lineage conversions of astrocytes were also attempted in vivo within brain parenchyma to generate neurons.

Expression of single transcription factors such as SOX2, NEUROD1 or ASCL-1 under GFAP promoter generated functional neuroblasts that matured and integrated into neuronal circuits of adult mice brain

[START_REF] Niu | In vivo reprogramming of astrocytes to neuroblasts in the adult brain[END_REF]

(Su et al., 2014a)

[START_REF] Brulet | NEUROD1 Instructs Neuronal Conversion in Non-Reactive Astrocytes[END_REF]

  Rousseau, A., Nutt, C.L., Betensky, R.A., Iafrate, A.J., Han, M., Ligon, K.L., Rowitch, D.H., and Louis, D.N. (2006). Expression of oligodendroglial and astrocytic lineage markers in diffuse gliomas: use of YKL-40, ApoE, ASCL1, and NKX2-2. J Neuropathol Exp Neurol 65,

	1149-1156.
	Sabelstrom, H., Petri, R., Shchors, K., Jandial, R., Schmidt, C., Sacheva, R., Masic, S., Yuan,
	E., Fenster, T., Martinez, M., et al. (2019). Driving Neuronal Differentiation through
	Reversal of an ERK1/2-miR-124-SOX9 Axis Abrogates Glioblastoma Aggressiveness. Cell
	Rep 28, 2064-2079 e2011.
	Shih, H.P., Kopp, J.L., Sandhu, M., Dubois, C.L., Seymour, P.A., Grapin-Botton, A., and
	Sander, M. (2012). A Notch-dependent molecular circuitry initiates pancreatic endocrine and
	ductal cell differentiation. Development 139, 2488-2499.
	Trotter, J., and Schachner, M. (1989). Cells positive for the O4 surface antigen isolated by
	cell sorting are able to differentiate into astrocytes or oligodendrocytes. Brain Res Dev Brain
	Res 46, 115-122.
	Turcan, S., Rohle, D., Goenka, A., Walsh, L.A., Fang, F., Yilmaz, E., Campos, C., Fabius,
	A.W., Lu, C., Ward, P.S., et al. (2012). IDH1 mutation is sufficient to establish the glioma
	hypermethylator phenotype. Nature 483, 479-483.

Srikanth, M.,

Kim, J., Das, S., and Kessler, J.A. (2014)

. BMP signaling induces astrocytic differentiation of clinically derived oligodendroglioma propagating cells. Mol Cancer

Res 12, 283-294. Suzuki, H., Aoki, K., Chiba, K., Sato, Y., Shiozawa, Y., Shiraishi, Y., Shimamura, T., Niida, A., Motomura, K., Ohka, F., et al. (2015)

. Mutational landscape and clonal architecture in grade II and III gliomas. Nat Genet 47, 458-468. Szerlip, N.J., Pedraza, A., Chakravarty, D., Azim, M., McGuire, J., Fang, Y., Ozawa, T., Holland, E.C., Huse, J.T.,

Jhanwar, S., et al. (2012)

. Intratumoral heterogeneity of receptor tyrosine kinases EGFR and PDGFRA amplification in glioblastoma defines subpopulations with distinct growth factor response. Proc Natl Acad Sci U S A 109, 3041-3046. Tirosh, I.,

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. Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539, 309-313.

Supplementary

Table 2 :

 2 List of cellular markers and supporting references for their specific expression.

	Tumor Patient 1 LGG 236 Patient 2 LGG 253 Patient 3 LGG 39 Patient 4 LGG 234 Patient 5 LGG 244 Patient 6 LGG 188 LGG 270 LGG 289 LGG 312 LGG 318 LGG 307 LGG 335 LGG 338	Techniques IF IF IF IF IF IF Tumoral cells qPCR-YFP, NICD Tumoral cells qPCR-YFP, NICD, Cell characterizat ion Tumoral cells qPCR-YFP, NICD Tumoral cells qPCR-YFP, NICD Non-tumoral cells qPCR-YFP, NICD Non-tumoral cells qPCR-YFP, NICD Cell characterizat ion Non-tumoral cells qPCR-ion characterizat Cell YFP, NICD	Figure 1 1 1 1 1 1 6A, S11 6A, S11 6A, S11 6A, S11 S14A, S12 S14A, S12 S14A, S12	Age 49 26 32 40 42 38 47 31 26 52 30 41	Gender Diagnosis (subtype, grade) F Oligodendroglioma II IDH1R132H IDH1 mutation ATRX Preserved Co-1p/19q deletion deleted M Oligodendroglioma II IDH1R132H Preserved Co-deleted Oligodendroglioma II IDH1R132H Preserved Co-deleted M Astrocytoma Grade II IDH1R132H Loss No co-deletion M Astrocytoma II IDH1R132H Loss No co-deletion F Astrocytoma II IDH1R132H Loss No co-deletion M Astrocytoma II IDH1R132H Loss M Astrocytoma II IDH1R132H Loss No co-deletion F Astrocytoma II IDH1R132H Loss No co-deletion M Astrocytoma II IDH1R132G Loss No co-deletion F Oligodendroglioma II IDH1wt No Loss Co-deleted M Oligodendroglioma II IDH1R132H No Loss Co-deleted F Astrocytoma II IDH1R132H Loss
	LGG 275			40	F	Anaplastic Astrocytoma	IDH1R132H	Loss

Table 2 :

 2 List of cellular markers and supporting references for their specific expression.

	Patient 1 LGG 236 Patient 2 LGG 253 Patient 3 LGG 39 Patient 4 LGG 234 Patient 5 LGG 244 Patient 6 LGG 188 LGG 270 LGG 289 LGG 312 LGG 318 LGG 307 LGG 335 LGG 338	IF IF IF IF IF IF Tumoral cells qPCR-YFP, NICD Tumoral cells qPCR-YFP, NICD, Cell characterizat ion Tumoral cells qPCR-YFP, NICD Tumoral cells qPCR-YFP, NICD Non-tumoral cells qPCR-YFP, NICD Non-tumoral cells qPCR-YFP, NICD Cell characterizat ion Non-tumoral cells qPCR-ion characterizat Cell YFP, NICD	1 1 1 1 1 1 6A, S11 6A, S11 6A, S11 6A, S11 S14A, S12 S14A, S12 S14A, S12	49 26 32 40 42 38 47 31 26 52 30 41	F M M M F M M F M F M F	Oligodendroglioma II IDH1R132H Oligodendroglioma II IDH1R132H Oligodendroglioma II IDH1R132H Astrocytoma Grade II IDH1R132H Astrocytoma II IDH1R132H Astrocytoma II IDH1R132H Astrocytoma II IDH1R132H Astrocytoma II IDH1R132H Astrocytoma II IDH1R132H Astrocytoma II IDH1R132G Oligodendroglioma II IDH1wt Oligodendroglioma II IDH1R132H Astrocytoma II IDH1R132H	Preserved Co-deleted Preserved Co-deleted Preserved Co-deleted Loss No co-deletion Loss No co-deletion Loss No co-deletion Loss Loss No co-deletion Loss No co-deletion Loss No co-deletion No Loss Co-deleted No Loss Co-deleted Loss
	LGG 275			40	F	Anaplastic Astrocytoma	IDH1R132H	Loss

Table 1 .

 1 Identification of dysregulated genes in foci. Fold changes (DLGG/foci) are indicated. p-values (ANOVA unpaired tests, n = 8 cases) are indicated.

			DLGG	Foci	Fold Change
	Gene Symbol	Description	(log2)	(log2)	(DLGG/foci) p-value
	SFRP2	Secreted Frizzled Related Protein 2	6.51	5.5	2	0.0475
	CST3	Cystatin C	8.94	8.1	1.79	0.0277
	DAAM2	Dishevelled Associated Activator Of Morphogenesis 2	7.2	6.4	1.75	0.0253
	ETNPPL	Ethanolamine-Phosphate Phospho-Lyase	6.01	5.22	1.72	0.0096
	TMEM47	Transmembrane Protein 47	6.16	5.48	1.61	0.0126
	MLC1	Megalencephalic Leukoencephalopathy With Subcortical Cysts 1	6.86	6.23	1.54	0.0028
	KCNN3	Potassium Calcium-Activated Channel Subfamily N Member 3	6.42	5.8	1.54	0.0377
	ADCYAP1R1	Adenylate Cyclase Activating Polypeptide 1 (Pituitary) Receptor Type I	7.28	6.72	1.47	0.0116
	GJA1	Gap Junction Protein Alpha 1	5.79	5.27	1.43	0.0223
	EZR	Ezrin	6.98	6.46	1.43	0.0048
	ALDOC	Aldolase, Fructose-Bisphosphate C	7.81	7.36	1.37	0.0107
	ATP1A2	ATPase Na + /K + Transporting Subunit Alpha 2	6.88	6.47	1.33	0.0072
	SLC1A3	Solute Carrier Family 1 Member 3	5.96	5.57	1.32	0.0273

Table S1

 S1 Patients description (Histological and molecular features of the ten patients used for bioinformatics and foci studies)

	Age at surgery	Sex	Histological subtype	1p19q status	IDH mutation	ATRX	Ki67 within foci
	yo	F	Astrocytoma	1p no loss 19q partial loss	c.G395A Arg132His	loss	10%
	yo	F	Astrocytoma	No loss	c.G395A Arg132His	loss	5%
	yo	M	Astrocytoma	No loss	c.G395A Arg132His	loss	4%
	yo	F	Astrocytoma	1p no loss 19q partial loss	c.G395A Arg132His	loss	15%
	yo	M	Astrocytoma	No loss	c.G395A Arg132His	loss	8%
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	20%
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	20% focally
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	3%
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	10%
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	15%
				Patients description
	(Histological and molecular features of the patients used for histological controls and DLGG comparison to foci)
	Age at surgery	Sex Histological subtype	1p19q status	IDH mutation	ATRX	Figure
	yo	F	Glioblastoma	not available	not available	maintained	4B
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	5A-C
	yo	F	Astrocytoma	No loss	c.G395A Arg132His	loss	5B-C
	yo	M	Astrocytoma	No loss	c.G395A Arg132His	loss	5B-C
	yo	M	Astrocytoma	No loss	c.G395A Arg132His	loss	5D
	yo	F	Astrocytoma	No loss	c.G395A Arg132His	loss	5D
	yo	F	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	Sup 6A-B
	yo	M	Oligodendroglioma	Total loss	c.G395A Arg132His	maintained	Sup 7C-D

Table S2

 S2

				Antibodies description
	Antibody		Manufacturer & Clone	Host Species	Dilution
	Actine		Cell Signalling -8H10D10		Mouse	1/6,000 for WB
	ALDH1L1		Abcam ab56777			Mouse	1/50
	ATRX		Santa Cruz -D5 Sigma HPA001906			Mouse Rabbit	1/15 1/500
	CHI3L1		Santa Cruz -S18			Goat	1/50
	ETNPPL	Sigma HPA044546 Atlas Antibodies HPA072938		Rabbit Rabbit	1/200 & 1/1,000 for WB 1/1,000 & 0.4µg/mL for WB
	GFAP		Pharmingen -1B4			Mouse	1/50
	IDH1 R132H		Dianova -H09			Mouse	1/50
	Vimentin		Dako -V9			Mouse	1/1,000
	pSTAT3 -Tyr705		Cell Signalling -D3A7		Rabbit	1/200
	Peptide		Manufacturer			Amino Acid Sequence	Dilution
	ETNPPL		Novus -NBP1-91655PEP	VLKIKPPMCFTEEDAKFMVDQLDRILTVLEEAMGTKTE SVTSENTPCKTKMLKEAHIELLRDSTTDSKENPSRK	10 :1
					Primers
	Genes chosen to be assessed by RT-qPCR	Forward Primer		Reverse Primer	Amplicon size (bp)	Melting temperature
	ALDOC		ACTCCATACCACAGCCCTTG	CAGCAATGAGAGAGGGGAAG	149	60°C
	CST3		CCAGCAACGACATGTACCAC	CCTTTTCAGATGTGGCTGGT	170	60°C
	ETNPPL		GCCGATGGACCTCATAGAAA	TTTCGGTTTTGGTTCCCATA	136	60°C
	EZR		AGATCTGGGCAATGGATCTG	GCTGTCCTTTGCTGTGATGA	137	60°C
	MLC1		TGCAGGACAGATCAGGTCAG AACAGCGGAGATGGAGAAGA	132	60°C
	SFRP2		CTTGGGTCTGGTTGGTTGTT	GGGCCACAGAGAAAATTGAA	152	60°C
	SLC1A3		TAGTCCCGGTTTTGCATTTC	AATCTTGGCACACCAGAAGC	103	60°C
	RPLP0		GCAATGTTGCCAGTGTCTGT	GCCTTGACCTTTTCAGCAAG	142	60°C

Table S3

 S3 Differential expression (grade III/II) from The Cancer Genome Atlas (TCGA) database of dysregulated genes identified in foci Heterogeneity in cancer is the bottleneck for developing effective therapeutic strategies. Several models are put forth to explain the heterogeneity within the tumor, one among them being the clonal evolution model that explain how diverse phenotypes arise within tumor through multistep tumorigenic process. During the evolution, cells acquire and accumulate mutations that provide survival advantages and dominance resulting in their expansion. An alternative hypothesis is the classical CSC model placing cancer stem cells at the apex of cellular hierarchy. CSCs undergo asymmetric division giving rise to both stem cells as well as differentiated cells with limited tumorigenic and metastatic potential. The phenotypic switch from CSC to differentiated non-CSC state was considered a unidirectional process until evidences for cellular plasticity became prominent. Plasticity indicates that committed, non-CSCs can undergo dedifferentiation process and enters a stem cell state. There are several examples of cellular plasticity and phenotypic switch identified in several cancer models. The plasticity can be acquired through the genetic variations or from microenvironmental cues. In glioblastoma, recurred tumor have shown the phenotypic shift from proneural to aggressive mesenchymal phenotypic shift after chemo and radiotherapy. In general, cellular

	General discussion and Perspectives
	4. General discussion and perspectives
	Gene Symbol ADCYAP1R1 Adenylate Cyclase Activating Polypeptide 1 (Pituitary) Receptor Type I Description ALDOC Aldolase, Fructose-Bisphosphate C ATP1A2 ATPase Na+/K+ Transporting Subunit Alpha 2 CST3 Cystatin C DAAM2 Dishevelled Associated Activator Of Morphogenesis 2 ETNPPL Ethanolamine-Phosphate Phospho-Lyase EZR Ezrin GJA1 Gap Junction Protein Alpha 1 KCNN3 Potassium Calcium-Activated Channel Subfamily N Member 3 MLC1 Megalencephalic Leukoencephalopathy With Subcortical Cysts 1 SFRP2 Secreted Frizzled Related Protein 2 SLC1A3 Solute Carrier Family 1 Member 3 TMEM47 Transmembrane Protein 47	OII vs OIII Fold Change p-value 1,68 0.0005 1,40 0.0002 1,52 0.0012 1,12 ns 2,00 < 0.0001 2,40 0.0003 1,41 0.0031 1,91 0.0010 1,67 0.0039 1,73 < 0.0001 4,43 < 0.0001 1,47 0.0002 1,79 0.0001	AII vs AIII Fold Change p-value 1,41 0.0363 1,44 0.0031 1,69 0.0013 1,24 0.0477 1,56 0.0008 2,45 < 0.0001 1,17 ns 1,67 0.0001 1,25 ns 1,47 < 0.0001 2,95 < 0.0001 1,32 0.0015 1,52 < 0.0001

Table 1 .

 1 qPCR primer sequences

	Targets	Forward primer (5 ′ -3 ′ )	Reverse primer (5 ′ -3 ′ )
	B2M	ACCCCCACTGAAAAAGATGA	ATCTTCAAACCTCCATGATG
	Int6/eIF3e	TTCTTCAATCACCCCAAAGG	TAGAACCTGCCGACGTTTTC
	GADD45␣	GAGAGCAGAAGACCGAAAGGA	CACAACACCACGTTATCGGG
	UBE2V1	CGGGCTCGGGAGTAAAAGTC	CCCCAGCTAACTGTGCCATC
	HIF-1␣	TTTACCATGCCCCAGATTCAG	GGTGGACTTTGTCTAGTGCTTCCA
	HIF-2␣	CCACCAGCTTCACTCTCTCC	TCAGAAAAAGGCCACTGCTT
	FAS	TCTGGTTCTTACGTCTGTTGC	CTGTGCAGTCCCTAGCTTTCC
	CDC45	GCCATGGTGATGTTTGAGCT	TGTGTTCTCCTCATCCTCGT
	GAS5	TGAAGTCCTAAAGAGCAAGCC	ACCAGGAGCAGAACCATTAAG
	at 100 g/ml (FITC Annexin V/Dead Cell Apoptosis Kit
	with FITC Annexin V and PI; Invitrogen Life Technologies,
	Carlsbad, CA, USA) during 15 min at room temperature in
	the dark. 400 l of Annexin-binding buffer 5X were then
	added after washes with PBS-bovine serum albumin 1%.
	Labeled cells were preserved on ice and run on a flow cy-
	tometer (BD Accuri™ C6, BD Biosciences, Franklin Lakes,
	NJ, USA).

Polysome profiling and isolation of total, non-polysomal, light polysomal and heavy polysomal mRNA fractions

	Cells were incubated for 15 min at 37 • C with 100 g/ml
	cycloheximide (CHX), washed in PBS, lysed in hypotonic
	polysome lysis buffer (5 mM Tris-HCl, pH 7.5, 2.5 mM
	MgCl 2 , 1.5 mM KCl, 100 g/ml CHX, 2 mM DTT, 40
	U/l RNAse OUT, 10% Triton X-100, 10% sodium de-
	oxycholate) on ice, mixed by vortexing and centrifuged at
	1400 rpm for 5 min. Lysates were layered onto 15-50%
	sucrose gradients for fractionation (2 h at 39 000 rpm in
	a Beckman SW40.1 rotor and L8 ultracentrifuge at 4

• C).

  /glioblastoma.alleninstitute.org/). Gene expression in major anatomic structures of glioblastoma (leading edge, infiltrating tumor, cellular tumor, perinecrotic zone, pseudopalisading, hyperplastic blood vessels and microvascular area) was quantified by RNA sequencing in the Anatomic Structures RNA-Seq Study. The Ivy GAP cohort is comprised of 42 tumors.

		M O ,U S A )a t1 /100)]. Cell extracts were incubated for 1
		h at room temperature with DNase I (Thermo Scientific
		EN0521) and precleared with protein-Sepharose beads for
		1ha t4 • C. DDX3X (Santa Cruz, sc-365768) and IgG (In-
		vitrogen, 026502) antibodies were incubated with 20 lo f
		slurry beads (washed and equilibrated in cell lysis buffer) for
		1hat4 • C. Beads were incubated with 1 mg of cell extracts
		overnight at 4 • C. Beads were washed four times with cell ly-
		sis buffer and eluted in NT2 buffer [50 mM Tris, pH 7.4, 1
		mM MgCl 2 , 0.05% NP-40, 0.1% SDS and 30 g proteinase
		K (Qiagen, Venlo, Limburg, The Netherlands)]. RNAs are
		then extracted by phenol/chloroform and analyzed by RT-
		qPCR.
		In vitro transcription
	• C for epitope retrieval.	RNAs used in RNA chromatography experiments were
	EnVision™ FLEX Peroxidase-Blocking Reagent was used	transcribed using the MEGAscript Kit (Invitrogen
	for blocking (provided in the K8000 kit, Dako, Ely, UK)	AM1333) as per manufacturer's instructions. 7.5 mM
	for 5 min. Sections were incubated for 1 h with diluted 1/50	ATP/CTP/GTP, 6.75 mM UTP and 0.75 mM biotinylated
	(diluted in EnVision™ FLEX Antibody Diluent) human eIF3e-specific primary antibody, HPA 023973 (Sigma, St	UTP (Biotin-16-UTP, Lucigen BU6105H) were used. For luciferase reporter mRNAs, m 7 G-cap was added using
	Louis, MO, USA), and washed with PBS-Tween 0.3%. Sec-	the Vaccinia capping system kit (M208S NEB) according
	tions were incubated with secondary antibody-HRP (En-	to the manufacturer's instructions. To generate the DNA
	Vision™ FLEX/HRP, K8000 kit, Dako, Ely, UK) for 20	templates to synthetize the luciferase reporter mRNAs,
	min and after washes with PBS-Tween 0.3%, EnVision™	oligonucleotides CDC45, FAS and GADD45␣ were ampli-
	FLEX system (DAB+ Chromogen, K8000 kit, Dako, Ely,	fied by PCR using the following primers. For CDC45, PCR
	UK) was used for signal visualization according to the man-	products were used as template for in vitro transcription.
	ufacturer's instructions and we counterstained sections with	For GADD45␣ and FAS, PCR products were cloned in the
	hematoxylin (EnVision™ FLEX Hematoxylin, provided in	pSC-B-amp/kan plasmid from the Strataclone Blunt PCR
	the K8000 kit, Dako, Ely, UK). After dehydration, slides were mounted with EUKITT ® mounting medium. The	Cloning Kit, and then digested by, respectively, BamHI and XhoI (restriction sites for transcription run-off) and
	levels of cytoplasmic eIF3e staining were scored by two	purified. All oligonucleotide sequences are available in the
	anatomopathologists using a 4-point score intensity to dis-	following table (bold: T7 promoter). For GADD45␣,T 7
	tinguish between 'high' (2 or 3 points) and 'low' (0 or 1	sequence used was in pSC-B-amp/kan plasmid.
	point) eIF3e staining levels. Patient survival between high and low eIF3e-stained glioblastomas was measured using	Name	Sequence
	the log-rank test and the Gehan-Breslow-Wilcoxon test.	GADD45␣	FW: GGAGAGCGGGGCCCTTTGTC RV:
			CTGGATCATAAACTTTCGAAGTCATATT
	Immunoprecipitation	CDC45	GCAAACTGCAGGTCGCCC FW: TAATACGACTCACTATAGGGAAAGA
	U251 cells were lysed in lysis buffer [20 mM Tris-HCl, pH 8,		AAGGAAGGCTGGGAACTAA RV: CTGGATCATAAACTTTCGAAGTCATAGC
	0.5% NP-40, 450 mM NaCl, 0.5% Triton, 2% glycerol com-		CACGGCGGCCGGACG
	plemented by protease inhibitors (Sigma-Aldrich, St Louis, MO ,USA)a t1/100)]. Cell extracts were incubated for 1 h at room temperature with Benzonase (Millipore E1014) and DNase I (Thermo Scientific EN0521; see Supplementary	FA S	F W: TAATACGACTCACTATAGGGATCAA TGGAGCCCTCCCCAAC RV: CTGGATCATAAACTTTCGAAGTCATGGT TGTTGAGCAATCCTCCGAA
	Figure S3) and precleared with protein-Sepharose beads for
	1ha t4 • C. DDX3X (Santa Cruz, sc-365768) and IgG (In-vitrogen, 026502) antibodies were incubated with 20 lo f	In cellulo luciferase activity analysis
	slurry beads (washed and equilibrated in cell lysis buffer) for 1 h at 4 • C. Beads were incubated with 1 mg of cell ex-tracts overnight at 4 • C. Beads were washed four times with	U251 cells transfected with luciferase Renilla and Firefly re-porter mRNAs were harvested in 100 l of Passive Lysis Buffer (Promega). 10 l of this extract were analyzed with
	cell lysis buffer and co-immunoprecipitated proteins were	the luciferase assay.
	analyzed by western blot.
	RNA immunoprecipitation
	U251 cells were lysed in lysis buffer [20 mM Tris-HCl, pH 8,
	0.5% NP-40, 450 mM NaCl, 0.5% Triton, 2% glycerol com-
	plemented by protease inhibitors (Sigma-Aldrich, St Louis,

RNA chromatography

200 g of the U251 cells were lysed in 500 loflysisbuffer

 pH 8, 150

mM NaCl, 2 mM EDTA complemented by protease inhibitors (Sigma-Aldrich, St Louis, MO, USA) at 1/100]. Cells extracts

Ivy GAP

Gene expression in the various anatomical regions of glioblastoma tumors was analyzed using the Ivy Glioblastoma Atlas Project (GAP; http: /

SCIENTIFIC REPORTS |(2020) 10:5504 | https://doi.org/10.1038/s41598-020-62145-1

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Acknowledgements

Acknowledgements

As I come closer to completion of the four yearlong PhD life, it cannot be wrapped-up Acknowledgements At this point I also remember and thank Bernard Rothhut who have been my co-supervisor in the first year for all the help he extended during my initial days in the lab.

Nicolas, you have been a great friend and an inspiration during my PhD life. For all the help Acknowledgements independently use Gallios machine and its analysis. You have always been ready to help whenever I had issues with sorting.

Acknowledgements

.............................................................................................................................

Table of contents .................................................................................................................................. Acknowledgements This work was supported by grants from ARC, INCA-GSO, and ARTC-SUD. M. Augustus was supported by University of Montpellier, ARC and ARTC-SUD. We thank Amélie Sarrazin and Christophe Duperray from MRI RIO biocampus facilities for their technical assistance as well as RHEM facility and CHU of Montpellier, Centre de Ressources Biologiques du CHU de Montpellier (CRB), Collection Neurologie, F-34285 Montpellier, France. We thank A. Monteil and C. Lemmers from the Vectorology facility, PVM, Biocampus Montpellier, CNRS UMS3426 for producing lentiviruses used in the study.

Acknowledgements

This work was supported by grants from ARC, INCA-GSO, ARTC-SUD. N. Leventoux, was supported by an ARTC-SUD fellowship. We thank Marie-Pierre Blanchard, Amélie Sarrazin and Christophe Duperray from MRI RIO biocampus facilities for their technical assistance as well as RHEM facility and CHU of Montpellier, Centre de Ressources Biologiques du CHU de Montpellier (CRB), Collection Neurologie, F-34285 Montpellier, France. Affymetrix microarrays were processed in the Microarray Core Facility (V. Pantesco) and the Platform Bioinformatics and Biomarkers (Bio2M) at the Institute of Regenerative Medicine and Biotherapies -Montpellier Hospital. We also want to thank: Professor Steven Sloan who kindly authorized us to use the ETNPPL graph on supplemental Fig. 4C from 18 and Inger Åhlén who authorized us to use the ETNPPL stainings on supplemental Fig. 4E -Image credit: Human Protein Atlas, www.proteinatlas.org, Image available at the following URL: v18. proteinatlas.org/humancell from 39 .

ACKNOWLEDGEMENTS

We thank Marie Tosolini and Frederic Pont from CRCT Technology Cluster for initial bioinformatic analysis, GeT-Biopuces core of INSA Toulouse for assistance with the polysome profiling microarray technology, D. da Mota and F. Arnauduc for assistance with IHC and J.P. Hugnot for providing GBM samples. C. Oertlin and O. Larsson at Karolinska Institutet helped with anota2seq analysis. Author contributions: S.M. and N.S. conceived the project. S.M., N.S., C.S. and A.C. designed and supervised the experiments. J.B. and J.S. performed most of the experiments, together with A.C. M.A. prepared the GBM protein extracts. A.C., J.S. and J.B. made the figures. J.G. performed statistical analysis. S.E., M.C.-S. and E.U.-C. performed and analyzed ISH. E.C.J.-M., C.T., C.S. and E.U.-C. contributed with helpful discussion. E.D. performed bioinformatics analysis. S.M. and N.S. wrote the manuscript with input from all the authors. FUNDING Institut National de la Santé et de la Recherche Médicale (INSERM); Université Toulouse III--Paul Sabatier; Centre National de la Recherche Scientifique (CNRS); Ligue Contre le Cancer (LNCC) [to J.S.]; Labex TOUCAN [ANR11-LABX]; Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation (MENRT) [to J.B.].

Data obtained from (Zhang et al., 2016). Database-(http://www.brainrnaseq.org/)

DATA AVAILABILITY

The polysome profiling has been deposited in the Gene Expression Omnibus (GEO) under accession GSE157608.

Context, Aims and Approaches

Chapter 2:

Context, aims and experimental approaches of my thesis

Results

Chapter 3: Results

Abstract

IDH1-mutated gliomas are slow growing brain tumors that progress into high-grade gliomas. Sc-RNA sequencing analyses have revealed tumoral cell heterogeneity in these tumors. The molecular mechanisms underlying the formation of this cellular diversity is ill defined. Here we investigated the composition of oligodendroglioma and astrocytoma tumors using cellular markers. We found largely two non-overlapping population of tumoral cells expressing the transcription factors Sox9 and Olig1 respectively. Sox9 cells stained for APOE, CRYAB, KCNN3, and ID4 while Olig1 cells stained for EGFR, IDH1, PTPRZ1, PDGFRA, and SOX4. Both cells expressed GPR17 but the signal was higher in Olig1 cells. These two subpopulations appear to have distinct Notch, BMP, and MAPK active pathways as stainings for Hey1, Hey2, p-SMAD1/5 and p-ERK were higher in Sox9 + cells. Using diffuse IDH1mutated low-grade primary glioma cells and cell line as well as non tumoral O4 + purified human oligodendrocyte cells, we found that activation of Notch and BMP reduce several oligodendrocytic markers and IDH1 expression while upregulating KCNN3 and CRYAB.

Supplementary data

Supplementary Table 1

Supplementary data

Supplementary

Competing interests

The authors declare no competing interests.

SUPPLEMENTARY INFORMATION

Supplement figure legends

Supplement table legends