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2017 TRANSCRIPTIONAL REGULATION OF NEURONAL MIGRATION AND CELL FATE SPECIFICATION IN THE NEOCORTEX

Adnani, Lata

Adnani, L. (2017). TRANSCRIPTIONAL REGULATION OF NEURONAL MIGRATION AND CELL FATE SPECIFICATION IN THE NEOCORTEX (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/28505 http://hdl.handle.net/11023/3979 doctoral thesis

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TRANSCRIPTIONAL REGULATION OF NEURONAL MIGRATION AND CELL FATE SPECIFICATION IN THE NEOCORTEX

LATA HARISH ADNANI

A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF BIOCHEMISTRY AND MOLECULAR BIOLOGY

CALGARY, ALBERTA JULY 2017

Abstract

The events that lead to the generation of a functional neocortex are tightly regulated and require the coordination of multiple events, including progenitor proliferation and maturation, neuronal differentiation and neuronal migration. I began my PhD studies by investigating the role of the zinc finger gene Zac1 in neocortical development. Zac1 was initially identified in the

Schuurmans’ lab in a subtractive screen designed to isolate downstream effectors of the proneural gene Neurog2, which is a critical regulator of neocortical development. Previous studies had identified a role for Zac1 in the developing retina and cerebellum. I hypothesized that

Zac1 would have essential roles in regulating the key events during the development of a functional neocortex. We tested the sufficiency of Zac1 in progenitor cell proliferation, progenitor cell maturation, neuronal differentiation and neuronal differentiation. We have demonstrated that Zac1 functions in regulating the radial glial cell to intermediate neuronal precurssor transition, neuronal differentiation and neuronal migration in the embryonic neocortex, acting in part through the regulation of Pac1 (Chapter 2). In the next stage of my PhD project, I tested the requirement and sufficiency of of two other members of the Plag family of transcription factors, Plag1 and Plagl2 in the developing neocortex (Chapter 3). Previously, it was established that Plag1 and Plagl2 (as well as Zac1) are associated with intrauterine growth restriction (IUGR) and intellectual disabilities. I found that Plag1 and Plagl2 have complementary roles in maintaining the ventral and dorsal boundaries of gene expression in the developing telencephalon, respectively, and that Plag1 is required while Plagl2 is sufficient to induce neocortical progenitor proliferation. Finally, in Chapter 4, I switched gears and focused my study on a disease of the neocortex, which is oligodendroglioma (ODG). My goal was to elucidate how ODG cells influence the behavior of mouse neural stem cells (mNSCs), and I

i hypothesized that the communication between ODG cells and mNSCs was , in part, EV dependent. I was able to show that ODG cells secrete factors that have dosage-specific effects on the growth of normal neural cells. In particular I demonstrated that ODG cells communicate with mNSCs by secreting EVs that carry several signaling molecules as cargo, including EGF, which acts in a dose-dependent manner to influence mNSC proliferation. I also demonstrated that inhibition of EV secretion by blocking the nSMase pathway increases ODG ‘tumoursphere’ number and size, while ectopic expression of this pathway lead to decrease in the generation of

‘tumoursphere’.

Taken together, through my PhD work new molecular insights into how neocortical development is regulated have been gained, and an onset to understanding one of the means of a disease to influence the behavior of mNSCs in a non-cell autonomous manner have been studied.

These studies bring us closer to understanding the molecular mechanisms that underlie normal neocortical development, and possibly open up new avenues for testing various biomarkers and therapies for ODG.

ii Acknowledgements

I would like to thank my supervisor, Dr. Carol Schuurmans for her support and guidance during my PhD program. Her work ethic is inspiring and I always will look up to her as my mentor in academia. It was because of her guidance that I not only learnt a lot of different techniques in the lab but also learnt to give decent oral presentations. I thank you, Carol, for igniting my passion in Neuroscience.

I would like to thank all the lab members of the Schuurmans’ laboratory: Dr. Dawn Zinyk, from whom I have learnt a lot of techniques, including cloning, PCR, and animal handling. Thank you Dawn for always having solutions to my silliest to toughest of questions. Natalia Klenin, for being there whenever I needed help with anything. Dr. Rajiv Dixit, for helping me with cell counts, in utero electroporations and suggesting valuable ideas to my projects. Sisu Han, for interesting scientific discussions. Nobuhiko Tachibana and Daniel Dennis for helping with and discussing innumerable scientific ideas. Anjali Balakrishnan, for helping me with my qPCR data. Dr. Yacine Touahri, for providing insights and suggestions on my projects, for helping me with the glucose uptake assay for my ODG-EV project, sportingly losing in some of our foosball matches and for providing words of support in the last month of my PhD program. Tooka Aavani Collette and Dario Collete for being my source of fun and joy in the lab. Thank you Tooka for being my partner in crime in our ‘madness’ and awesome times. I would like to thank the current summer students in the Schuurmans’ laboratory, especially Boris Kan, who helped me with measuring sphere sizes for my ODG-EV project. I would also like to thank the past lab members of the Schuurmans’ laboratory, Dr. Grey Wilkinson and Dr. Saiqun Li for introducing me to various techniques such as cell culture and in utero electroporation respectively. Mary Chute for helping me when I needed and Amy Chen for helping me with my Plag project as a summer student in the lab.

I would like to thank my committee members, Dr. Sarah Childs, Dr. Deborah Kurrasch and Dr. Jennifer Chan for their generous help, guidance and suggestions throughout my PhD program. Also, thank you Dr. Jennifer Chan for agreeing to be my co-supervisor when we moved to Sunnybrook Research Institute in Toronto. Finally, I would like to thank my internal examiner, Dr. Patrick Whelan for agreeing to be on my PhD examining committee and my external examiner, Dr. Johan Holmberg for traveling all the way from Sweden to be a part of my defense examining committee.

I would like to thank everyone from the ACHRI/GDRG research group for their valuable insights at every one of my research in progress sessions. It shaped my way of thinking and presenting my data dramatically.

I would like to thank ACHRI training scholarship for awarding me a stipend for two years during my PhD program.

I would like to thank members of the Chan lab and my friends, Christian, Myra and Dan all of whom helped my transition from mouse work to human cell culture work be as smooth as possible. Thank you all very much.

iii

I would also like to thank my friends at the University of Calgary including, Charlene, Rasha, Michaela, Candace, Sherry, Elizabeth, Hayley, Ramy and Jessica; and my friends at Sunnybrook Health Sciences Center including, Dominica for being an integral part of my daily fun times. Thank you Dom for being there, during my highs and lows.

I started my journey in Canada in 2011 with an intention of completing my Masters in Science and having no idea that I would be drawn to perusing my PhD here. Calgary will always be close to my heart as I made some wonderful friends there. Thank you so much Amrita, Sowmya and Shankha for making every day in Calgary a fun-filled one. Amrita and Sowmya, without your constant support and companionship, this journey would not have been a memorable one. Thank you very much for being there with me during my thick and thin times. After our lab moved to Sunnybrook Research Institute in Toronto, I was warmly welcomed by one of my dearest friends. Thank you very much Gurnita for being there and helping me around this big city. I will cherish our tea times always and the time spent in Toronto would not have been even half as joyous without you. These lovely people that I call close friends, have become a part of my family, and I am utterly grateful for that.

Finally, I would like to dedicate my thesis to my parents, Mrs. Rachna Adnani and Mr. Harish Adnani, and my sister, Jaya Adnani Kanjani. Maa and papa you’ll are my pillars of strength and it is because of your confidence in me that I have been able to complete my PhD successfully. Without your words of encouragement and unconditional love and support, this would not have been possible. I am very proud to be your daughter and only hope that I can make you both half as proud of being my parents. Jaya and Vishal, thank you very much for your kind words of support always. I would like to thank my grandmother, Mrs. Rajkumari Adnani, for her constant supply of wisdom. I would also like to thank my grandfather, late Mr. Hundaldas Adnani. Your words of wisdom and light guide me every day, and I like to believe that it is your blessings that has gotten me this far -I miss you a lot daddy. Finally, I would like to thank my maternal grandparents, Mrs. Jyoti Gurdasani and late Mr. Pahoomal Gurdasani. I hope attaining a doctoral degree has fulfilled your desire of having one of your grandchildren being a doctor. Words seem insufficient to express my gratitude towards my family but thank you all so much for everything.

I am a firm believer in the existence of a “supreme” and so truly believe that my path, family and friends are all “his” blessings. This journey has been an adventure and makes me want to believe that it is only the beginning. I owe what has been and what will be to my Supreme. I also owe what I am to my Gurus for guiding me in every phase of my life. I am what I am by their blessings and grace.

Table of contents

Abstract………………………………………………………………………………...... i Acknowledgements……………………………………………………………………….... iii Table of contents………………………………………………………………………….... v List of Tables………………………………………………………………………….…… ix List of figures…………………………………………………………………………...... x List of symbols, abbreviations and Nomenclature………………………………...……….. xii Contribution of authors……………………………………………………...…..…………. xvi Other co-authored publication from my PhD work…………………………….…...... xvii

Chapter1. Introduction 1.1. General introduction to the mature neocortex ………………………………………... 1 1.2. Embryonic development of the neocortex : neurogenesis…………………………...... 2 1.2.1 Neocortical progenitor pools…………………………………………………. 2 1.2.2. Sequential production of cortical projection neurons……………………...... 4 1.2.3. RGC and INP contribution to the generation of different neocortical layers………………………………………………………………..……...... 5 1.2.4. Regional identity and the specification of neuronal identity………………... 6 1.2.5. Transcriptional derepression circuit that specifies laminar fates……………. 7 1.3. Neuronal migration in the neocortex...... ………………………………………..... 8 1.3.1. Early-born neuronal migration ...……………………………………………. 8 1.3.2. Late-born neuronal migration……………………………………………...... 9 1.3.3. Molecular regulation of migration………………………………………...... 10 1.4. Embryonic development of the neocortex : gliogenesis………………………………. 11 1.4.1. Switch from neurogenesis to gliogenesis……………………………………. 12 1.4.2 Generation of astrocytes in the neocortex……………………………………. 12 1.4.3. Generation of oligodendrocytes in the neocortex.….…..….….….….……… 13 1.5 Introduction to Plag family transcription factors.….….….……………………………. 13 1.5.1. Plag gene family function in cancer.….…..…...….….….….……………….. 14 1.5.2. Control of Zac1 expression………………………………………………….. 14 1.5.3. Transcriptional activities of Plag family proteins…………………………… 15 1.5.4. Plag gene family expression….….….….….….….….……………………… 17 1.5.5. Plag gene family function in neural development….….….….….….….….…18 1.6 An introduction to glioma……………………………………………………………... 19 1.6.1. General introduction to glioma subtypes……………………………………. 19 1.6.2. Molecular features of ODG………………………………………………..... 19 1.6.3. Molecular features of GBM………………………………………………..... 20 1.7 An introduction to extracellular vesicles (EVs)……………………………………...... 21 1.7.1 General introduction to EVs……………………………….…...... 21 1.7.2 Biosynthesis of exosomes. ………………………………………………...... 22 1.7.3 Rab GTPases in exosomal secretion. …………………………………….….. 23 1.7.4. EV function in the nervous system. ……………………………………….... 24 1.7.5. EV functions in brain cancer……………………………………………….... 24 1.8 Summary, hypothesis and rationale…………………………………………………...... 25

v 1.9 Figures and figure legends…………………………………………………………...... 27

Chapter 2. Zac1 regulates the differentiation and migration of neocortical neurons via Pac1

2.1 Abstract……………………………………………………………………………….... 50 2.2 Significance statement………………………………………………………………..... 51 2.3 Introduction…………………………………………………………………………...... 52 2.4 Materials and methods………………………………………………………………..... 53 2.4.1 Animals……………………………………………………………...... 53 2.4.2 Constructs used for in utero electroporation………………………………...... 53 2.4.3 In utero electroporation……………………………………………………..…. 54 2.4.4 RNA extraction, cDNA synthesis and quantitative real time PCR (qRT-PCR)...... 54 2.4.5 Tissue processing and immunolabelling………………………………………. 55 2.4.6 BrDU and EDU labelling…………………………………………………….... 56 2.4.7 Biphoton time lapse videomicroscopy……………………………………….... 57 2.4.8 RNA in situ hybridization …………………………………………………….. 58 2.4.9 Imaging, tracing, quantitation and statistics………………………………….... 58 2.5 Results ………………………………………………………………………………..... 58 2.5.1 Overexpression of Zac1 in neocortical progenitors perturbs late-born neuronal migration…………………………………………………………….. 58 2.5.2 Zac1 misexpression delays progenitor cell maturation and neuronal differentiation...... 60 2.5.3 Zac1-overexpression reduces the expression of neuronal differentiation markers…...... 62 2.5.4 Zac1-overexpressing cells exhibit decreased migratory velocities and increased pause time …………………………………………………………... 63 2.5.5 Zac1-overexpressing neurons exhibit aberrant morphologies…………….…… 65 2.5.6 Neuronal migration is perturbed in Zac1 mutant neocortices…………………. 67 2.5.7 Zac1 mutant neocortical neurons have aberrant morphologies……………...... 69 2.5.7 Zac1 regulates neuronal migration via Pac1…………………………….….…. 71 2.5.8 Pac1 partially rescues migration defects associated with Zac1 knock-down..... 73 2.6 Discussion………………………………………………………………….….….……. 74 2.6.1 Zac1 and the regulation of cortical progenitor cell proliferation…………....… 75 2.6.2 Zac1 blocks progenitor cell maturation and neuronal differentiation……….… 77 2.6.3 Zac1 regulates neocortical neuronal migration via Pac1…………………….... 77 2.7 Figures and figure legends……………………………………………...... ………….. 80

Chapter 3. Plag1 and Plagl2 have overlapping and distinct functions in telencephalic development 3.1 Abstract …………….………………………………..……………………...... 101 3.2 Summary statement …………….……………………………….……....……...... 101 3.3 Introduction………………………………………………………………….….…….... 101

vi 3.4 Materials and methods…………………………………………………………………. 104 3.4.1 Animals………………………………………………………………………... 104 3.4.2 Tissue processing and cryostat sectioning………………………………...... 105 3.4.3 Immunohistochemistry……………………………………………..………..… 105 3.4.4 RNA in situ hybridization…………………………………………..…………. 106 3.4.5 X-Gal staining………………………………………………………….…...…. 106 3.4.6 In utero electroporation……………………………………………....……...… 107 3.4.7 RT-qPCR…………………………..…………………………………....……... 107 3.4.8 Imaging, quantitation and statistics …………………………………….…...… 108 3.5 Results ……………………………………………………………………………….… 108 3.5.1 Plag1 and Plagl2 do not cross-regulate each other at the level of transcription…………………………………………………………………… 108 3.5.2 Plag1 and Plagl2 act redundantly to control embryonic survival…...... 110 3.5.3 Plag1 sets the dorsal border of ventral telencephalic gene expression…….….. 111 3.5.4 Plagl2 sets the ventral border of dorsal telencephalic gene expression …….… 113 3.5.5 Plag1 is required to regulate the proliferation of early embryonic neocortical progenitors…………………………………………………………………….. 114 3.5.6 Plagl2 is sufficient to alter the proliferation of neocortical progenitors…….… 115 3.6 Discussion…………………………………………………………………………….... 116 3.7 Figures and figure legends…………………………………………………………...… 121

Chapter 4. Glioma cells secrete extracellular vesicles carrying EGF and have dose-dependent effects on neural stem cells

4.1 Abstract………………………………………………………………………………… 130 4.2 Significance statement...... 131 4.3 Introduction……………………………………………...…...... 131 4.4 Materials and methods………………………………………………………….…….... 132 4.4.1 Animals…………………………………………………...……………....….... 133 4.4.2 STR matching………………………………………………………………..… 133 4.4.3 Patient-derived tumor tissues…………………………………………….…..... 133 4.4.4 BT088 cell line maintainence, CM and EV collection……………………..….. 133 4.4.5 mNSC derivation and culture…………………………………………….……. 134 4.4.6 Transwell (Boyden) chamber assay……………………………………….….... 135 4.4.7 Western blotting and silver staining……………………………………….…... 135 4.4.8 ELISA…………………………………………………………………….……. 135 4.4.9 Mass spectrometry…………………………………………………………...... 136 4.4.10 Nucleofection ………………………………………………………………... 136 4.4.11 Pellet assay………………………………………………………………...... 137 4.4.12 In utero Electroporation…………………………………………..….………. 138 4.4.13 Tissue processing and immunostaining…………………………………...….. 138 4.4.14 Imaging and statistical analysis…………………………...……………….…. 139 4.5 Results………………………………………………………………………...... …. 139 4.5.1 BT088 cells act in a contact-independent fashion to influence the proliferation of neural stem cells……………………………...... 139 4.5.2 BT088 cells secrete bioactive molecules that have dosage-specific effects on

vii neural stem cell self-renewal, proliferation and survival……………...…….... 141 4.5.3 BT088 cells secrete bioactive molecules in their EVs…………………...……. 142 4.5.4 BT088 CM effects are EV mediated…………………………………………... 144 4.5.5 Proteome of BT088 EVs includes exosome markers and many signalling molecules…………………………………………………………………..….. 145 4.5.6 Activation of RTK signaling induces gliogenesis in a non-cell autonomous fashion...... 145 4.5.7 EGF is secreted in BT088 EVs and mNSCs express Egfr and downstream signaling molecules……………………………………………………….….... 148 4.5.8 EGF has dose-sensitive effects on neural stem cells……………………….….. 149 4.5.9 EGF effects on neural stem cells are sensitive to glucose levels…………….. 150 4.5.10 Altering exosome secretion influences the survival of BT88 cells in vitro...... 151 4.6 Discussion……………………………………………………………..…...... 152 4.7 Figures and figure legends………………………………………..….….…..……...….. 157 4.8 Tables……………………………………………………………………………….….. 171

Chapter 5. Final Discussion 5.1 Summary of findings…………………………………………………………….…….. 179 5.1.1 Zac1 regulates neocortical neuronal migration via Pac1 signaling …………… 179 5.1.2 Plag1 and Plagl2 proto-oncogenes have distinct functions in the neocortical development …………………………………………………………………... 181 5.1.3 Oligodendroglioma cells secrete bioactive EVs that influence the proliferation of NSCs………………………………..…..…..….….…………. 182 5.2 Biological and clinical implications of findings……………………………………….. 183 5.2.1 Plag family genes and intra uterine growth restriction (IUGR) ………………. 183 5.2.2 Zac1 and transient neonatal diabetes mellitus (TNDM) ……….…………...... 184 5.2.3 Plag family genes and intellectual disabilities………………………...………. 184 5.2.4 Targeting EVs for the treatment of gliomas………………………….…….….. 186 5.3 Future perspectives………………………………………………………....………….. 186 5.3.1 To elucidate which downstream effectors of Plag genes regulate cell fate decisions………………………………………………………………….……. 186 5.3.2 To understand how mNSCs interact with ODG cells…………….…….……… 189 5.4 Concluding remarks………………………………………………………………….… 190 5.5 Figures and figure legends………………………………………………….……….…. 191

References

viii List of Tables

Table 4.1 General summary of the signaling pathways enriched in BT088 secretome....… 169

Table 4.2 Relative glucose consumption of the mNSCs ………………………..…...... 175

ix List of Figures and Illustrations

Figure 1.1 Neocortical Anatomy…………………………………………………...…...... 26

Figure 1.2 Interkinetic nuclear migration (INNM)……………………………...……...... 28

Figure 1.3 Different Modes of cell division……………………………………...……...... 30

Figure 1.4 Sites of origin of Cajal-Retzius neurons………………………………...... …… 32

Figure 1.5 Sequential generation of cortical neurons…………………………….…..…… 34

Figure 1.6 Sites of origin of cortical interneurons……………………………………..….. 36

Figure 1.7 A postmitotic derepression circuit specifies laminar fates………………..…… 38

Figure 1.8 Neural stem cell multipotency……………………………………………….… 40

Figure 1.9 Specification of a cortical astrocytic fate……………………………………… 42

Figure 1.10 Sites of origin of cortical oligodendrocytes……………………...…………… 44

Figure 1.11 Members of the Plag gene family: Plagl1 (Zac1), Plagl1 and Plagl2…..…… 46

Figure 2.1 Zac1 overexpression perturbs cell migration during later stages of

corticogenesis…...... 79

Figure 2.2 Zac1 overexpression delays progenitor cell maturation and neuronal

differentiation...... 81

Figure 2.3 Zac1 overexpression blocks neuronal differentiation………………...... …… 83

Figure 2.4 Altered migratory properties of Zac1 over-expressing cortical cells……...... 85

Figure 2.5 Zac1 over-expression alters the morphology of migrating neurons……...... 87

Figure 2.6 Loss of Zac1 does not alter progenitor cell dynamics…………………….....… 89

Figure 2.7 Aberrant distribution of laminar markers in Zac1 mutant cortices……….….... 91

Figure 2.8 Aberrant morphology of migrating neurons in Zac1 mutant cortices…….....… 93

x Figure 2.9 Zac1 regulates neuronal migration by regulating Pac1 transcription in the developing neocortex…………...…………………………………………………...... …… 95

Figure 2.10 Zac1 regulates neuronal migration via Pac1 in the developing neocortex…… 97

Figure 3.1 Plag1 and Plagl2 have similar patterns of telencephalic gene expression and function redundantly to regulate embryonic development………………………………… 120

Figure 3.2 Plag1 and Plagl2 are required to pattern the embryonic telencephalon……...... 122

Figure 3.3 Plag1 is required to regulate proliferation in the early embryonic

Telencephalon...... 124

Figure 3.4 Plagl2 is sufficient to alter the proliferation and differentiation of neocortical

progenitors………………………………………………………………..….… 126

Figure 4.1 Short tandem repeat matching of DNA samples purified from patient 9672 having

ODG and BT088 cells………………………………………………….……… 155

Figure 4.2 BT088 conditioned media (088-CM) influences E13.5 mNSC growth……….. 157

Figure 4.3 BT088 cells secrete bioactive EVs…………………………………………….. 159

Figure 4.4 Molecular profiling of BT088 derived EVs…………………………………… 161

Figure 4.5 BT088 derived EVs express EGF and effects of EGF on mNSCs in vitro….… 163

Figure 4.6 Increased glucose rescues high EGF toxicity of mNSCs…………………….. 165

Figure 4.7 Loss of nSMase pathway in BT088 cells induces cell proliferation………...… 167

Figure 5.1 Alkaline phosphatase activity induced by Plagl2 misexpression in the

neocortex...... 189

Figure 5.2 Zac1-Neurog2 interactions……………………………………………...... … 191

Figure 5.3 Etv5 mutants are smaller at P21 and have smaller hippocampus…………....… 193

xi List of Symbols, Abbreviations and Nomenclature

Symbol Definition

88-CM BT088-conditioned media ACVR1 Activin receptor 1 Adcyap Adenylyl cyclase-activating peptide AEP Anterior entopeduncular area ANR Anterior neural ridge AS Asparagine synthetase Ascl1 Achaete scute like 1 aSMase Acid sphingomyelinase ANOVA One-way analysis of variance BF1 Brain factor 1 BFP Blue fluorescent protein BMP Bone morphogenetic proteins B-catenin beta catenin Bcll 1b B cell CLL/lymphoma 11B Bcl6 B cell leukemia/lymphoma 6 BDNF Brain-derived neurotrophic factor Βgal β-galactosidase bHLH basic helix-loop-helix BrdU bromodeoxyuridine C-terminal carboxy terminal cDNA coding DNA Cdh9 Cadherin 9 CARM1 Co-activator associated arginine methytransferase CGE Caudal ganglionic eminence Cited2 Carboxy-terminal domain, 2 CNS Central nervous system CNTF Ciliary neurotrophic factor CoP Commissural plate CoupTF1 Coup transcription factor 1 CP Cortical plate CR Cajal-Retzius CREB Cyclic AMP response element-binding protein CT1 Cardiotrophin-1 Ctip2 Chicken ovalbumin upstream promoter transcription factor-interacting protein 2 Ctx Neocortex Cux1/2 Cut like homeobox 1/2 Cx Neocortex DAPI 4',6-diamidino-2-phenylindole DCC Deleted in colorectal cancer Dig Digoxygenin

xii DIPG Diffuse intrinsic pontine gliomas DIV Days in vitro Dkk1 Dickkopf1 E Embryonic day EAAT2 Expression of excitatory amino acid transporter 2 EDTA Ethylene diamine tetra-acetic acid EGF Epidermal growth factor EGFR Epidermal growth factor receptor EGFRvIII Epidermal growth factor receptor variant III Emx2 Empty spiracles homeobox 2 ESCRT Endosomal sorting complex required for transport Etv5 Ets variant 5 EV Extracellular vesicles FGF Fibroblast growth factor Foxg1 Forkhead box g1 Foxh 1 Forkhead box h1 FUBP1 Far upstream element binding protein 1 Fzd Frizzled G1 Gap phase 1 G2 Gap phase 2 GABA γ-aminobutyric acid GABA+ GABAergic GBM Glioblastoma multiforme G-CIMP Glioma-CpG island methylator phenotype GFP Green fluorescent protein Gli3 GLI-Kruppel family member GLI3 GLT1 Glutamate transporter1 Glu+ Glutamatergic H3 histone 3 H&E Hematoxylin and eosin Hesx1 Homeobox gene expressed in ES cells HEK Human embryonic kidney cells Id Inhibitor of Differentiation IDH Isocitrate dehydrogenase IGF Insulin-like growth factor ILV Intraluminal vesicles INPs Intermediate neuronal progenitors IRES Internal ribosome entry site IUGR Intra uterine growth restriction IZ Intermediate zone JAK Janus kinase K Lysine LAMP1/2 Lysosomal –associated membrane proteins1/2 Lef1 Lymphoid enhancer binding factor 1 LGE Lateral ganglionic eminence LIF Leukemia inhibitory factor

xiii Lot1 Lost on transformation, 1 MAPK Mitogen-activated protein kinase MBP Myelin basic protein M-Dia mammalian Diaphanous MGE Medial ganglionic eminence MGMT O6-methylguanine DNA methyltransferase mNSCs mouse neural stem cells M-phase Mitosis-phase mRNA messenger RNA MTOC Microtubule-organizing center MV Microvesicles MVB Multivesicular bodies NICD Notch intracellular domain Neurod Neurogenic differentiation Neurog2 Neurogenin 2 NF1 Neurofibromin 1 NF1 Neurofibromatosis type 1 (in glioma section) NFIA Nuclear factor I/A NICD Notch intracellular domain NOS Not otherwise specified Nr2f1 Nuclear receptor subfamily 2 group F member 1 nSMase neutral sphingomyelinase ODG Oligodendroglioma OLC Oligodendroglia-like cells OPCs Oligodendrocyte precursor cells oRGCs outer RGCs Otx1/2 Orthodenticle homeobox 1/2 P Postnatal day Pac1 Type1 receptor for PACAP PACAP Pituitary adenylyl cyclase-activating peptide Pax6 Paired box 6 PcG Polycomb group PDGFRa Platelet derived growth factor PFA paraformaldehyde pHH3 phospho-histone H3 PI3K phosphatidylinositol 3-kinase Plag1 Pleiomorphic adenoma gene 1 Plagl1 Pleiomorphic adenoma gene like 1 Plagl2 Pleiomorphic adenoma gene like 2 PLP Proteolipid protein PM Plasma membrane PNS Perepheral nervous system PP Preplate PPMID Magnesium dependent protein phosphatase 1D Ptch1 Patched 1 RGCs Radial glial cells

xiv RNA Ribonucleic acid RTK Receptor tyrosine kinase Satb2 Special AT-rich sequence binding protein 2 Sfrp2 Secreted frizzled related protein 2 Shh Sonic hedgehog SMAD Sma and Mad Related Family Sox SRY-box Sp8 Trans-acting transcription factor 8 SP Subplate SRY Sex determining region Y STAM Signal transducing adaptor molecule STAT Signal transducer and activator of transcription STRs Short tandem repeats Svet1 Subventricular expressed transcript 1 SVZ Sub-ventricular zone TCF12 transcription factor 12 TERT Telomerase reverse transcriptase TGF Transforming growth factor TH Thyroid hormone Tlx Tailless T-N Tumor-Neural VZ Ventricular zone WB Western blot WHO World health organization WNTs Wingless-type MMTV integration site family signals YAP Yes-associated protein Zac1 Zinc-finger protein regulator of apoptosis and cell-cycle arrest

xv Contribution of Authors

Chapter 2: *Adnani L, *Langevin LM, Gautier E, Parsons K, Li S, Dixit R, Kaushik G, Wilkinson G, Wilson R, Childs S, Nguyen MD, Journot L, Dehay C, Schuurmans C. Zac1 regulates the differentiation and migration of neocortical neurons in part via Pac1. J Neuroscience. 30 September 2015, 35(39): 13430-13447; doi: 10.1523/JNEUROSCI.0777- 15.2015

The project was initiated by Lisa Marie Langevin during her PhD program. However, after her graduation, I took over the project, and repeated most of her experiments to validate the data, and I studied migration of cortical neurons and added the migration rescue experiments to complete the story (Fig. 1, 2, 3, 5, 6, 7, 8, 9). Elodie Gautier and Dr. Collet Dehay did the time lapse imaging of Zac1 misexpressed neurons and compared it with control, pCIG2 (Fig. 4). Kari Parsons and Dr. Minh Dang Nguyen helped me acquire some preliminary data and taught me how to use the confocal microscope. Saiqun Li and Rajiv Dixit helped me with a few in utero electroporations. Gaurav Kaushik and Grey Wilkinson helped with qPCR. Dr. Richard Wilson provided us with the PACAP inhibitor and provided us with P4 Pac1 knock out mice. Dr. Sarah Childs provided financial and intellectual support. Dr. Laurent Journot provided us with the Zac1+m/- mice.

Chapter 3: Adnani L, Dixit R, Chen X, Balakrishnan A, Logan CC, Schuurmans C. Plag1 and Plagl2 have overlapping and distinct functions in telencephalic development. Under review, Biology Open.

The project was initiated by me with the intellectual guidance and financial support of Dr. Carol Schuurmans and Dr. Cairine Logan. I performed most experiments with help from Xingu (Amy) Chen and Rajiv Dixit with sectioning, staining and counting. Anjali Balakrishnan performed the qPCR. Dr. Logan supervised Amy’s part of the project in Calgary.

Chapter 4: Adnani L, El-Sehemy A, Kan B, Olender T, Dixit R, Chen M, Comanita LC, Touahri Y, Briggs S, Carincross G, Beattie T, Brand M, Wallace W, Chan JA, Schuurmans C. Glioma cells secrete extracellular vesicles carrying EGF and have dose-dependent effects on neural stem cells. In preparation.

This project was designed and initiated by me with the guidance and support from Dr. Carol Schuurmans and Dr. Jennifer Chan. I performed most of the experiments with the following exceptions. Thomas Olender and Dr. Marjorie Brand performed the mass spectrometry analyses in Fig. 4. Ahmed El-Sehemey and Dr. Valarie Wallace performed the xenografting experiments. Boris Kan assisted with measuring sphere sizes. Rajiv Dixit performed in utero electroporations. Myra Chen performed immunostaining of human ODG tissues. Experiments not included in the thesis but that will be in the manuscript were contributed by the following people. Cre Comanita in Valerie Wallace’s lab performed subretinal injections of BT088 cells transfected with Cre. Yacine Touahri assisted with the glucose uptake assay. Sophie Briggs and Dr. Tara Beattie sent us the conditioned media from six other GBM cell lines.

xvi Other co-authored publications from my PhD work

Published and In Press:

1) Adnani L, Han S, Li S, Mattar P, Schuurmans C. Mechanisms of cortical differentiation. International Review of Cell and Molecular Biology. In press. I contributed to a significant amount of writing and making schematics for this review article.

2) Dennis D*, Wilkinson G*, Li S*, Dixit R, Adnani L, Balakrishnan A, Han S, Kovach C, Gruenig N, Kurrasch D, Dyck R, SchuurmansC. Neurog2 and Ascl1 together regulate a postmitotic derepression circuit to govern laminar fate specification in the murine neocortex. 2017. Proc Natl Acad Sci U S A. 2017 Jun 5. pii: 201701495. doi: 10.1073/pnas.1701495114. I performed in utero electroporations at E12.5-E13.5 of the different constructs and analyzed the data post harvesting, sectioning, staining, imaging and counting cells.

3) Touahri Y, Adnani L, Mattar P, Markham K, Klenin N, Schuurmans C Non-isotopic RNA In Situ Hybridization on Embryonic Sections. Curr Protoc Neurosci. 2015 Jan 5;70:1.22.1- 25. doi:10.1002/0471142301.ns0122s70. PMID: 25559002 I contributed in part to writing the manuscript and I made all the figures.

4) Wilkinson G*, Dixit R*, Cancino GI, Shaker T, Adnani L, Li S, Dennis D, Kurrasch D, Chan JA, Olson EC, Kaplan DR, Zimmer C, Schuurmans C. Neurog1 and Neurog2 control two waves of neuronal differentiation in the piriform cortex. J Neurosci. 2014 Jan 8;34(2):539-53. *Authors contributed equally to this publication. I contributed by performing in situ hybridization for the project.

Under revision/review:

1) Wilkinson G*, Li S*, Han S, Adnani L, Zinyk D, Ilnytskyy Y, Brooks M, Raharjo E, Dixit R, Malik F, Wu W, Rahmani W, Chan JA, Kurrasch D, Swaroop A, Kovalchuk I, Biernaskie J, Schuurmans C. Proneural genes mediate multilineage priming in the neocortex. In revision.

I performed in utero electroporations at E12.5-E13.5 of the different constructs and analyzed the data post harvesting, sectioning, staining and imaging and counting the cells.

2) Marsters CM, Malik F, Adnani L, Klenin N, Dixit R, Schuurmans C, Pittman QJ, Kurrasch DM. Microglia sever radial glia processes to influence the development of hypothalamic energy balance centers. Under revision for Nature Neuroscience.

I contributed by performing in utero electroporations for the project.

xvii 3) Ahmad ST, Rogers AD, Chen MJ, Dixit R, Adnani L, Frankiw LS, Lawn SO, Alshehri M, Wu W, Chittaranjan S, Robbins SM, Marra MA, Cairncross G, Schuurmans C, Chan J. Capicua regulates neural progenitor cell proliferation and oligodendrocyte differentiation. Under review at Nature Communications. I contributed by performing in situ hybridization for the project.

4) Tachibana N, Dixit R, Adnani L, Cantrup R, Touahri Y, Aavani T, Kurek K, Wong RO, Logan CC, C Kurek K, Schuurmans C. Generation of an animal model of hamartoma tumour syndrome in the central nervous system. Under review at Disease Models & Mechanisms. I contributed by helping in the systemic injections of the different drugs into the mice.

In preparation:

1) Touahri Y, Tachibana N, Adnani L, Chute M, Dixit R, Reisenhofer M, Ma L, Zinyk D, Enzmann V, Biernaskie J, Journot L, Sauve Y, Schuurmans C. Zac1 prevents injury- independent activation of Muller glia in the retina.

I contributed by maintaining the Zac1 mice line, and assisted in some of the genotyping, sectioning and imminostaining the retinal tissues.

xviii CHAPTER 1. INTRODUCTION

1.1. General introduction to the mature neocortex

The neocortex is a mammalian-specific brain region that subserves several higher cognitive functions, including language, intellect and sensory processing. In most rodents, the neocortical surface is smooth, whereas in primates, it is folded into sulci and gyri, which increases the surface area. However, despite these differences, neocortices of all mammals have the same organization and are divided into six neuronal layers in the radial axis. They are also all populated by the same two neuronal cell types: inhibitory GABAergic interneurons and excitatory, glutamatergic, projection neurons (Figure 1.1). The glutamatergic projection neurons are divided into the following six layers. Layer I neurons are called Cajal-Retzius (CR) cells, and they secrete Reelin, which guides the migration of neurons into the other layers [1]. Layer II (external granular layer) and layer III (external pyramidal layer) are together called the supragranular layers, and they primarily send projections to the contralateral hemisphere or they form intra-hemispheral connections. Layer IV (internal granular layer) neurons receive afferent input from the thalamus

(i.e., thalamocortical afferants). Layer V (internal pyramidal layer) and layer VI (multiform layer) are together called the infragranular layers, and they both project subcortically and are therefore known as corticofugal neurons. However, while layer V neurons innervate the basal ganglia, brain stem, spinal cord and other subcerebral regions, these layer neurons are known as subcerebral neurons, layer VI neurons target the thalamus and are known as corticothalamic neurons (Figure

1.1). Therefore, the neuronal projection areas are dependent on where the neurons are positioned in the cortex. Finally, interspersed among these defined layers of gluatamatergic neurons are

GABAergic interneurons, which are more sparsely distributed.

1.2. Embryonic development of the neocortex : neurogenesis

1.2.1 Neocortical progenitor pools. Cortical progenitors undergo three stages of maturation during development. Prior to the onset of neurogenesis (~E8.5-E10.5), cortical progenitors are known as neuroepithelial cells, and they are organized in a single cell layer that is a pseudostratified neuroepithelium [2]. The cortical neuroepithelium appears stratified because the nuclei of the polarized neuroepithelial cells undergo interkinetic nuclear migration, migrating up and down along the apicobasal axis of the neuroepithelium while maintaining basal and apical attachments to the pial and ventricular surfaces, respectively [3, 4] (Figure 1.2). These interkinetic nuclear movements occur in a cell cycle-dependent fashion. That is, nuclei that are in S-phase of the cell cycle, when DNA is synthesized, move up to the basal surface of the neuroepithelium, while nuclei in gap phase 2 (G2) and mitosis (M-phase) migrate down to the apical surface. Nuclei in gap phase 1 (G1), which separates M- and S-phases, lie in the center of the neuroepithelium

(Figure 1.2). Notably, at these early developmental stages, neuroepithelial cells primarily undergo symmetric proliferative divisions, which serve to expand the progenitor pool [5, 6].

With the onset of neuronal differentiation, which begins at ~E10.5, cortical neuroepithelial cells begin to transform into radial glial cells (RGCs), which have neuroepithelial and astroglial properties [7-9]. RGCs are also radially polarized cells that have their cell bodies in the ventricular zone (VZ) and send projections to contact the apical and basal surfaces of the neuroepithelium.

RGCs are distinguished from neuroepithelial cells in that they begin to express several glial markers (e.g., BLBP, RC2, GLAST, etc) [7-11]. RGCs also change their mode of cell division, primarily undergoing asymmetric differentiative divisions, giving rise to one RGC to renew the progenitor pool, and one neuronal daughter [12, 13]. As the neuronal daughter exits the cell cycle, it loses its apical process so that it can migrate to its appropriate layer [14] (Figure 1.3). Notably,

the basal processes of RGCs, which contact the pial surface, serve as a scaffold to guide the radial migration of newborn glutamatergic neurons to their final destinations in the cortical plate [14-

17]. While RGCs are thought to maintain contacts with the pial and ventricular surfaces, recently a new population of outer RGCs (oRGCs) has been identified, which lose their ventricular attachment and are located outside the VZ [18-21].

Later in development (~E11.5), RGCs give rise to a secondary pool of progenitors that are called intermediate neuronal progenitors (INPs). INPs lose their apical contacts and migrate in a basal direction to form the sub-ventricular zone (SVZ) [22, 23]. INPs divide less, usually only 1-

2 times, and primarily undergo symmetric differentiative divisions to generate two neuronal daughters [24, 25]. Differentiating INPs are known to give rise to upper-layer neurons [26-28], although there is some evidence that some deep-layer neurons are also derived from INPs [29].

However, these INPs might actually be the oRGCs described above.

The regulation of progenitor cell maturation (i.e., the RGC to INP transition) is a key determinant of neuronal number and identity. Transcription factors that have been implicated in regulating this transition include Pax6, Tbr2, Insm1 and Neurog2. During neurogenesis, RGCs express the homeodomain transcription factor Pax6 [30]. Later on, when RGCs differentiate into

INPs, Pax6 expression is turned off and expression of the T-box transcription factor Tbr2 is initiated in INPs [31, 32]. Pax6 and Tbr2 are essential for regulating RGC [33, 34] and INP [35,

36] identities, respectively. Pax6 promotes the RGC to INP transition by inducing transcription of

Tbr2 [30, 37]. Neurogenin2 (Neurog2) is a proneural basic-helix-loop-helix (bHLH) transcription factor that is also necessary and sufficient to regulate the RGC to INP transition [23, 38-40]. Tbr2 is also a Neurog2 transcriptional target [39], providing a mechanism by which Neurog2 can induce an INP cell fate. Neurog2 is also known to indirectly suppress Pax6, and consequently a RGC

identity, via inducing the expression of Tbr2, an INP determinant [40]. Another transcription factor that promotes the transition from RGC to INP is Insm1, which is a zinc finger protein that is regulated by Neurog2 [25]. However, whereas Neurog2 induces precocious neurogenesis when misexpressed in cortical progenitors [41, 42], neither Tbr2 nor Insm1 can induce INP differentiation into neurons [25, 36, 40]. Thus, other downstream effectors of Neurog2 must promote the transition of INPs to differentiated neurons (e.g., NeuroD1 and NeuroD4) [65].

1.2.2. Sequential production of cortical projection neurons. The excitatory projection neurons that form the six neocortical layers arise from dorsal telencephalic (cortical or pallial) progenitors over eleven cell divisions between embryonic day (E) 10 and E17 [43-46]. The first neurons to be born are the Cajal-Retzius neurons, which arise from progenitors in the pallial margins, including the cortical hem, pallial septum and anti-hem [47] (Figure 1.4). Cajal-Retzius neurons will populate layer I, which is also known as the marginal zone (MZ). After layer I neurons are born, the next neuronal population to differentiate are the presumptive layer VII or subplate

(SP) neurons, which is a transient population of neurons in most species [48]. Together, the MZ and SP neurons make up what is called the preplate (PP) at E12.5. As neurogenesis continues, the

PP is split into an overlying MZ and an underlying SP by the migration of layer VI neurons into the middle of the PP. After the differentiation of layer VI neurons, neurogenesis occurs in an inside-out pattern, with deeper layer neurons being born first followed by the generation of upper layer neurons (i.e., layer VI, then V, then IV, then II/III, which are fused in mouse) [43].

Neurogenesis is complete by E17 in mouse, while neuronal migration continues until approximately postnatal day (P) 7 (Figure 1.5).

1.2.3. RGC and INP contribution to the generation of different neocortical layers. The generation of different neurons at different times suggests that the neuronal progenitors of the neocortex undergo temporal identity transitions over time. The traditional view is that deep layer neurons are derived from VZ –RGC progenitors, whereas upper layer neurons are derived from

SVZ-INPs [26] (Figure 1.5A). One piece of correlative evidence is that genes that are expressed in SVZ INPs, such as non-coding RNA Subventricular expressed transcript 1 (Svet1), Cut like homeobox 1/2 (Cux1/2), Tbr2, Special AT-rich sequence binding protein 2 (Satb2), Neurogenic differentiation 6 (Neurod6 - also known as Nex) are also expressed in upper layer neurons [26-28,

35, 36] [49] [50]. Conversely, Neurog1, Neurog2, Orthodenticle homeobox 1 (Otx1) and Fezf2 are expressed in VZ progenitors, and are required to specify a deep-layer fate [40, 41, 51-56]. More recently, however, lineage tracing and cell transplantation experiments suggest that some VZ

RGCs give rise to upper layer neurons [57], while a subset of SVZ INPs give rise to lower layer neurons (although these may be oRGCs) [32]. For instance, lineage tracing experiments in the

Fezf2-Cre mice have indicated the sequential generation of cortical neurons owing to the multipotency of the cortical progenitors [58]. Initial lineage tracing studies using Cux2-Cre mice supported the idea that a subset of RGCs which express Cux2 are fated to generate upper layer, layers II/III neurons [57]. However, more recently, studies have implicated the fact that RGCs are in fact multipotent and capable of generating both, deeper and upper layer neurons [58, 59]. Other transcription factors such as Pax6 and the orphan nuclear receptor Tailless (Tlx - also known as

Nr2e1), have been implicated in the expansion of the progenitor pool of the SVZ [52, 60]. While neurons in the lower layers remain unperturbed, there is a marked reduction in the generation of neurons in the upper layers in the Pax6 and Tlx single and double mutants [27, 52, 60-62]. It is

interesting to note that the INPs which express Tbr2 have the potential to generate both upper and lower layer neurons [32, 63].

1.2.4. Regional identity and the specification of neuronal identity. Neuronal fate specification is directly tied to regional identity in the telencephalon. Specifically, progenitors in the dorsal telencephalon give rise to glutamatergic excitatory projection neurons, while progenitors in the ventral telencephalon give rise to GABAergic interneurons (Figure 1.6). Interestingly,

GABAergic interneurons have been identified to be excitatory developmentally due to increased intracellular chloride concentrations which depolarize neurons. However, in an adult brain, the levels of chloride decreases rendering GABAergic interneurons as inhibitory. Genes involved in the specification of dorsal-ventral regional identities and neuronal fates include Pax6 and Emx2, which encode homeodomain transcription factors and are considered cortical selector genes [64-

66]. Pax6 and Emx2 are together required to specify a dorsal telencephalic identity, and the loss of both of these genes results in the formation of a telencephalon that is purely ventral in character

(i.e., only GABAergic neurons generated) [65]. Another important set of genes that specify dorsal- ventral identities are the proneural basic-helix-loop-helix (bHLH) transcription factors Neurog1 and Neurog2, which specify a dorsal telencephalic identity [51, 52]. Specifically, Neurog1 and

Neurog2 are required to specify a glutamatergic neuronal identity in early- but not late-born neocortical neurons [52], whereas Pax6 and the nuclear receptor Tlx specify the dorsal regional identities and glutamatergic neurotransmitter fates of mid- to late-born neurons [52].

GABAergic inhibitory interneurons are generated from subcortical progenitors in the ventral telencephalon, starting at E10.5 [67, 68]. A subset of these ventrally-derived GABAergic neurons, specifically those generated in the medial (MGE) and caudal (CGE) ganglionic

eminences, migrate tangentially into the neocortex in three streams (PP, SVZ/intermediate zone

(IZ) border and MZ), before migrating radially to ultimately end up in the same layer as glutamatergic projection neurons born on the same day [69-78] (Figure 1.6). The homeodomain transcription factors Dlx1 and Dlx2 are required to establish a ventral telencephalic identity, and in the absence of these genes, most, if not all, GABAergic interneurons are missing in the neocortex [74]. In addition, the proneural bHLH gene Ascl1 is required and sufficient to specify a ventral telencephalic identity and a GABAergic neuronal phenotype [68, 79].

1.2.5. Transcriptional derepression circuit that specifies laminar fates. Several transcription factors play critical roles in the generation of neurons specific to each layer. Several studies have identified a cortical de-repression circuit that operates in post-mitotic neurons that specifies laminar fates, indicating that this fate choice is determined post differentiation (Figure

1.7). Layer VI corticothalamic neurons express T-box brain factor 1 (Tbr1) [80-83]. Tbr1 knock out animals have reduced expression of other layer VI markers, including B cell leukemia/lymphoma 6 (Bcl6) and Cadherin 9 (Cdh9), and instead ectopically express layer V markers, such as Fezf2 and Chicken ovalbumin upstream promoter transcription factor-interacting protein 2 (Ctip2) (also known as B cell CLL/lymphoma 11B, or Bcl11b) in layer VI [82, 83]. In addition, in Tbr1 mutants, layer VI neurons no longer extend their axons to the thalamus but instead aberrantly project their axons to subcerebral targets such as the pons and hypothalamus [81, 82].

To carry out its repressive functions, Tbr1 has been shown to directly bind to the upstream regulatory region for the subcerebral layer V neuronal marker, Fezf2, which is required to specify a layer V identity [81, 82]. Tbr1 is also required to induce the expression of Sex determining region

Y-box 5 (Sox5) [83]. Like Tbr1, Sox5 is also an essential determinant of layer VI and is expressed

in layer VI, the SP and in a few layer V neurons [84, 85]. Down regulation of Sox5 in mice phenocopies Tbr1 mutants, as Sox5 mutants also display ectopic Fezf2 and Ctip2 expression in layer VI and the SP, and their layer VI axons aberrantly invade the hypothalamus [84, 85].

Fezf2 and Ctip2 are zinc finger transcriptional determinants of layer V [56, 86, 87].

Expression of Fezf2 is maintained in Ctip2 mutants, but layer V axons fail to innervate the corticospinal tract [86, 88]. Fezf2 is thought to be required to specify early born neuronal identities at the progenitor and post-mitotic level, as it is expressed in layer V and in RGCs during the generation of layer V neurons [55, 56, 87]. In Fezf2 mutants, Ctip2 is downregulated, and layer V neurons ectopically express Satb2, which specifies a layer II/III fate, and Tbr1 is ectopically expressed in layer V [56, 82, 86, 87]. This leads to layer V neurons aberrantly projecting their axons across the corpus callosum and into the thalamus. Interestingly, Tbr1 deletion in Fezf2 mutants (Tbr1-/-;Fezf2-/- double mutants) restores Ctip2 expression and typical subcerebral axonal projections [82]. Therefore, both Fezf2 and Ctip2 are repressed by Tbr1.

Satb2 is a chromatin remodeler that is specifies a layer II/III identity, promoting axon projections across the corpus callosum [89, 90]. In Satb2 mutants, Ctip2 is ectopically expressed in layers II/III, and these neurons extend their axons subcortically [89, 91]. Satb2 has been shown to bind to Ctip2 regulatory elements and repress its expression [89]. Satb2 also induces the expression of Tbr1, and overexpression of Tbr1 in Satb2 mutants alleviates the defective axonal projections observed in Satb2 mutants [92].

1.3. Neuronal migration in the neocortex

1.3.1. Early-born neuronal migration. Time lapse studies have established two modes of radial migration in the developing neocortex; nuclear/somal translocation and glial-guided

locomotion [93, 94] (Figure 1.5A). During early neocortical development, when the PP is forming, newborn cortical neurons translocate to their destinations independent of a RGC glial guide [16,

93]. Translocation of the cell body occurs after the leading process of the neuron adheres to the pial surface, while the smaller trailing process has lost its connections to the ventricular surface

[93, 95-100]. In general, the speed of translocation is constant, without any interruptions [93].

1.3.2. Late-born neuronal migration. As differentiation proceeds and the different cortical layers form, newborn neurons use glial-guided migration to exit the VZ, first entering the SVZ, then the IZ and finally the cortical plate (CP) (Figure 1.5A). Newborn neurons arising at the ventricular surface rapidly acquire a bipolar phenotype, with the leading process thicker than the trailing process. Importantly, upon differentiation from an RGC, the leading process of the neuron loses its basal contact with the pial surface, and instead makes contacts with the RGC process itself, which serves as a glial guide. Newborn neurons migrate along the RGC out of the VZ and into the SVZ, where they shift to a multipolar morphology, halting their directed migration as they undergo a waiting period, during which time they can disperse radially and tangentially or remain in the same position [24, 101]. The multipolar neurons then re-polarize, attaching again to their radial glial guides, and continuing their radial migration. Strikingly, at this stage, a large number of pyramidal neurons undergo a transient reversal in direction, migrating in a retrograde fashion towards the ventricular surface, before turning around and heading in the correct direction towards the cortical plate [24]. Through extension and retraction, the neuronal process directs the neuronal soma to move along the RGC process towards the pial surface. Locomotion does not occur at a constant speed, as neurons undergo ‘waiting periods’ during which time migration is stalled [93].

Once locomoting neurons reach their destination, they shift their mode of migration to

translocation to rapidly move to their final position [93]. Once neurons reach the cortical plate, they develop a multi-branched leading process.

1.3.3. Molecular regulation of migration. One of the factors important in neuronal migration is the organization of microtubules [102-106]. In migrating neurons, the centrosome, which is a microtubule-organizing center (MTOC), nucleates a network of microtubules to surround the nucleus, creating a nuclear cage [107, 108]. As neurons migrate, the leading process dilates and the dilation is invaded by the centrosome followed by the Golgi apparatus, mitochondria and rough endoplasmic reticulum [102]. Following the centrosome movement, the nuclear-microtubule cage enters the swelling (by assistance of myosinII) since one of the ends of the microtubules is tethered to the centrosome (Figure 1.5J) [102, 107, 109]. The Golgi apparatus is closely associated with the centrosome [110] and also moves away from the nucleus, with the

Golgi/centrosome complex pulling on microtubules to initiate nucleokinesis. The positioning of the Golgi apparatus is dynamically regulated during the tangential migration of MGE interneurons, although the functional significance of this is unknown [110, 111]. The endoplasmic reticulum

(ER) is also specifically localized in migrating cortical neurons, localizing to perinuclear regions and throughout the leading process [112].

Actin polymerization is also one of the key regulators in maintaining correct neuronal migration. Actin polymerization includes actin nucleation, extension and capping of growing ends.

During neuronal migration, the actin cytoskeleton (F-actin) and its binding proteins play a critical role in moving the leading process forward by the assembly/disassembly of F-actin [113]. The molecular mechanisms underlying this process are well studied [114]. Important mediators of changes in the actin cytoskeleton and hence neocortical neuronal migration include members of

the Rho-family of GTPases, such as RhoA, Rac1 [115-118] and Cdc42 [119-121]. Actin binding proteins such as Arp2/3, mammalian Diaphanous (mDia) and Spire are also involved in regulating actin polymerization by severing and capping actin filaments [122, 123]. Cdc42 activates the

Arp2/3 complex which in turn induces actin polymerization by de novo nucleation which leads to branching of actin filaments [124, 125]. This activation of Arp2/3 by Cdc42 also promotes F-actin to develop filopodia [124]; activation of Arp2/3 by Rac1 on the other hand promotes formation of lamellipodia in motile cells [126, 127]. Another actin-binding protein called cofilin is known to regulate actin depolymerization by binding to F-actin and causing disassembly. Cofilin is also involved in formation of lamellipodia [128]. Therefore, in order to propel the nucleus and hence the soma forward, traction and propulsion are required. The microtubule nuclear cage and its adherence to the centrosome provides traction while contractile locomotive forces are provided by actin-myosinII interactions at the rear of the nucleus.

Intrinsic and extrinsic factors also regulate radial migration during development. Proneural genes such as Neurog2 and Ascl1 control migration by regulating the transcription of Rnd2 and

Rnd3, respectively, each encoding small GTP-binding proteins. Rnd2 controls the multipolar to bipolar transition as well as the extension of the leading process [129]. Rnd3 also regulates glial- guided locomotion [130]. Both of these small GTP-binding proteins play such crucial roles by inhibiting RhoA signaling. Extrinsic factors are also known to impact radial migration in the neocortex. Evidence for such extrinsic factors include guidance molecules such as semaphorin

(Sema3a-PlexinB2) [131-133] and Netrin-Unc5D signaling molecules [134].

1.4. Embryonic development of the neocortex : gliogenesis

1.4.1. Switch from neurogenesis to gliogenesis. During neocortical development, progenitor cells in the dorsal telencephalon sequentially generate neurons (E10-17), followed by astrocytes (E18) and finally oligodendrocytes (postnatally) (Figure 1.8) [135, 136]. Remarkably, this developmental pattern can be recapitulated in vitro by culturing dissociated cortical cells taken from different embryonic stages [136-139]. These studies highlight the importance of intrinsic cues (i.e., gene expression profiles and epigenetic modifications) in regulating the timing of the switch from neurogenesis to gliogenesis (discussed further below). However, cell-extrinsic cues also contribute to this precisely timed process [136] (Figure 1.9). Evidence that environmental cues regulate the switch from neurogenesis to astrocyte differentiation comes from experiments in which embryonic cortical progenitors cultured on embryonic cortical slices were shown to differentiate into neurons, while cortical progenitors cultured on postnatal cortical slides differentiated into astrocytes [136, 140].

1.4.2 Generation of astrocytes in the neocortex. In the neocortex, neurogenesis ends at

E17, but the first astrocytes are observed around E15.5, indicating that there is some overlap in the period of neurogenesis and gliogenesis [141-145]. Astrocytes continue to be generated postnatally and through out adulthood of the rodents. Astrocytes arise from two different progenitor pools in the neocortex; RGCs in the VZ and postnatal subependymal cells in the SVZ, with the bulk of the astrocytes arising from the subependyma three weeks postnatally [141-143, 146]. The astrocyte pool is further expanded by symmetric divisions, with newly generated cells integrating into functional networks of pre-existing astrocytes [144]. Interestingly, the bulk of astrocytes are also generated in the month after birth in humans [147].

1.4.3. Generation of oligodendrocytes in the neocortex. Similar to GABAergic interneurons, oligodendrocyte precursor cells (OPCs) are born in the ventral telencephalon during the embryonic period and migrate tangentially to populate dorsal telencephalic cortical domains

(Figure 1.10). There are two waves of OPC generation in the ventral telencephalon; the first wave of OPCs are born in the MGE and anterior entopeduncular area (AEP) at E11.5, arising from

Nkx2.1+ progenitor cells [148, 149], while the second wave arises from Gsh1+ (also known as

Gsx2) progenitor cells in the lateral ganglionic eminence (LGE) beginning at E15 (Figure 1.10)

[150]. Most OPCs generated from the first wave undergo apoptosis, while 50% of the OPCs generated by Gsh1+ progenitor cells die by P10 [150]. Later, in the early postnatal period, OPCs are generated from Emx1+ progenitor cells in the dorsal telencephalon, which become the predominant source of oligodendrocytes in the adult neocortex [150, 151]. The Emx1+ progenitor derived oligodendrocytes continue to be generated through out the postnatal and adulthood of the murine neocortex. While the functional significance of each of these OPC pools has yet to be fully elucidated, a recent study has indicated that oligodendrocytes from dorsal and ventral sources preferentially myelinate different neuronal populations [152].

During development, neonatal OPCs can either divide symmetrically to expand the population (generating two OPCs), differentiate (generating two oligodendrocytes), or divide asymmetrically to generate one OPC and one oligodendrocyte [153, 154]. OPCs also persist in the adult brain, proliferating and differentiating to replace dying oligodendrocytes on a continual basis so as to maintain the same cellular density [155, 156].

1.5 Introduction to Plag family transcription factors

1.5.1. Plag gene family function in cancer. The pleiomorphic adenoma gene (Plag) family is made up of three genes: Plag-like1 (Plagl1/Zac1/Lot1), Plag1, and Plag-like2 (Plagl2) (Figure

1.11). Plagl1 is the official name for a gene that has also been named Zac1, which stands for zinc finger protein that regulates apoptosis and cell cycle arrest, and Lot1, which stands for lost-on- transformation; both names reflecting the known growth suppressive functions of this gene [157-

162]. Zac1/Plagl1 is a tumor suppressor gene that is located on human chromosome 6q24-15, a locus that is silenced in multiple carcinomas (e.g. head and neck, ovarian, breast, kidney, pituitary)

[1, 159, 162-178]. Consistent with its growth suppressive functions in cancer, Zac1 causes cell cycle arrest and apoptosis when over-expressed in epithelial cell lines [162-164, 166-179].

In contrast to Zac1, Plag1 and Plagl2 are proto-oncogenes [161]. Plag1 is amplified in pleiomorphic adenomas of the salivary gland [180-187], lipoblastomas [188-192], hepatoblastomas [193] and some leukemias [194, 195]. The misexpression of Plag1 in these cancers is due to chromosomal translocations that place Plag1 under the control of regulatory elements for ubiquitously expressed genes, such as elongation factor SII gene [196], Ctnnb1 (β- catenin) [197] and leukemia inhibitory factor receptor [198]. Plagl2 is similarly amplified in a set of cancers, including glioblastomas [199] and acute myeloid leukemia [194]. Consistent with their roles as oncogenes, Plag1 and Plagl2 promote proliferation, anchorage-independent growth, loss of contact inhibition and tumor formation in nude mice [161, 194, 199-203]. Importantly, Plagl2 is not oncogenic in all contexts as it has a pro-apoptotic response to hypoxia and other cellular stresses [204-207].

1.5.2. Control of Zac1 expression. Zac1 expression is tightly regulated by a process known as imprinting, with transcription from the maternal allele silenced via CpG methylation [165, 173-

176, 178, 208-210]. Consequently, Zac1 is only expressed from the paternal allele. Maintaining precise Zac1 expression levels is important, as tumor formation results from promoter hypermethylation (i.e., reduced Zac1 expression), while hypomethylation (i.e., increased Zac1 expression) results in intrauterine growth restriction (IUGR) and transient neonatal diabetes mellitus (TNDM) [173, 175, 176, 179, 208, 211-217].

1.5.3. Transcriptional activities of Plag family proteins. All three members of the Plag gene family encode zinc finger transcription factors that share homology chiefly in their zinc (Zn) finger domains, which are located in their amino termini, whereas the carboxyl terminal regions of the three proteins are quite diverse [218]. Zac1 and Plag1 contain seven C2H2 zinc finger domains, while Plagl2 contains six C2H2 domains. All three Plag proteins can function as transcriptional activators or repressors. Plag1/Plagl2 bind a similar core GRGGC site followed by a 6-8 nucleotide stretch and then a G-cluster (RGGK) [219]. Plag1/Plagl2 transcriptional activities are regulated by post-translational modifications such as being repressed by sumoylation while activated by acetylation [220-223]. In contrast, Zac1 transcriptional activities are dictated by whether it binds DNA as a monomer or dimer and on its recognition site [179]. Zac1 transactivates genes when bound as a monomer to G4C4 or GC2GC2G sites, or when bound as a dimer to G4N6G4 sites, whereas Zac1 monomers repress transcription from G4N6G4 sites [219, 224, 225].

Several transcriptional targets of the Plag family transcription factors have been identified.

Plag1 and Plagl2 regulate the expression of IgfII (Insulin-like Growth Factor), which accounts at least in part for their abilities to stimulate cell proliferation [162, 219, 226, 227]. In addition,

Plag1/Plagl2 promote tumorigenesis by initiating the transcription of several Wnt pathway genes

[228-230]. For instance, Plagl2 has been shown to regulate the expression of Wnt6, Fzd2 and Fzd9

to maintain cells in a proliferative state [199]. Likewise, Plag1 misexpression in pleiomorphic adenomas causes an upregulation of canonical Wnt signaling [203, 227]. Plag1 was also found to regulate several cell division and cell cycle-related genes, such as cyclin D3 and cyclinD1, as well as apoptosis-related genes, such as caspase-8 [231]. A crosstalk between TGFβ1 and ERK1/2 signaling is facilitated in part via Plag1. First, Plag1 expression is induced in response to TGFβ1 signaling, and second, Plag1 is required to maintain activation of the ERK pathway in response to

TGFβ1 [232]. Interestingly, microarray analysis of Plag1 in HEK293 cells indicated regulation of

Zac1 by Plag1 [231].

Several transcriptional targets of Zac1 have also been identified. One of the ways in which

Zac1 was initially identified is based on its ability to activate the transcription of Adcyap1r1, which is more commonly known as Pac1 [233, 234]. Pac1 is a type1 receptor for Pituitary adenylyl cyclase-activating peptide (PACAP or Adcyap). Pac1 function has been studied in the cortex and has been shown to regulate progenitor proliferation. It acts as an anti-mitogenic signal by repressing cAMP which elicits a p-CREB response leading to a blockade in mitosis [235].

However, recently it has been shown that Pac1 is regulated temporally during cortical development. This study shows that at early developmental stages (E9.5-E10.5), Pac1 is mitogenic without affecting cell survival and becomes anti-mitogenic by E14.5 [236]. Zac1 is also known to regulate astroglial differentiation in neural stem cells of the developing and adult brain via the

Jak/Stat3 signaling pathway [237]. Recently, it has been found that Zac1 binds to the promoter region of the paternally imprinted gene, Tcf4 and regulates the G1- to S-phase cell cycle transition by indirectly regulating the cyclin dependent kinase inhibitor, p57kip1 [238]. Apart from Tcf4, Zac1 regulates the expression of several other imprinted genes, such as Dlk1, IgfII, and Cdkn1c [112].

Finally, a recent study has found that Zac1 misexpression in neural progenitors results in the

aberrant expression of non-neural lineage genes, and of pluripotency genes, implicating this factor in key cell fate decisions [239].

Therefore, despite having distinct functions in tumor cells and cell cycle control, all three

Plag transcription factors have at least one common transcriptional target, IgfII.

1.5.4. Plag gene family expression. All three Plag genes are expressed in several lineages in the developing embryo as well as in some adult tissues [158, 233, 240, 241]. While each of the

Plag genes has a unique expression profile, the three genes are also co-expressed in certain lineages/tissues [158, 233]. In the developing central (CNS) and peripheral (PNS) nervous systems, Zac1 is expressed in a regionalized fashion whereas Plag1 and Plagl2 are more uniformly expressed in neural progenitors [158] [1, 184, 242, 243]. Interestingly, all three Plag genes are expressed at higher levels in neural progenitors than in post-mitotic neurons [233].

All three Plag genes are expressed in the developing neocortex, which was the focus of my studies. At E12.5, when the first neocortical neurons have differentiated and formed a PP overlying the VZ, Zac1 is highly expressed in VZ progenitors and not in postmitotic PP neurons [158]. By

E16.5, Zac1 expression is also detected in some deep layer neurons. At E15.5 and postnatal day

(P) 0, during the latter half of cortical neurogenesis, high Zac1 transcript levels are detected in the cortical VZ, while low Zac1 expression is detected in the SVZ and in a band of neurons in the lower cortical plate. Plag1 also displays a somewhat regionalized pattern of expression in the telencephalon, with higher expression in dorsal telencephalic vs ventral telencephalic progenitors

[158]. Plagl2 on the other hand, was found to be expressed uniformly throughout the telencephalic

VZ, including in the dorsal (i.e., cortical) and ventral (i.e., LGE, MGE, CGE) telencephalic VZ

[158]. Expression of both Plag1 and Plagl2 is uniform in the dorsal and ventral VZ at P0, however,

expression of Plag1 declined drastically by P0 [158], a stage that marks the end of neurogenesis and onset of giogenesis. The expression of all three Plag genes in neocortical progenitors thus suggests that they may play an important role during neuronal fate decisions during neocortical development.

1.5.5. Plag gene family function in neural development. Knock-out mice have been generated by gene targeting for each of the three Plag family genes. Plag1 null mice (Plag1-/-) are viable after birth, but are growth retarded and have reduced fertility [240]. Despite their growth defects, and the known ability of Plag1 to regulate expression of the Igf2 growth factor [162], Igf2 expression levels are unperturbed in Plag1 null mice [240]. Therefore, the underlying molecular mechanisms that lead to growth perturbation in Plag1 null embryos remains unknown. Likewise,

Plagl2-/- neonates also weigh less relative to their littermates at birth [241]. However, unlike Plag1-

/- mutants, Plagl2-/- pups display postnatal lethality, dying shortly after birth due to starvation and nutrient malabsorption [241]. In the neonatal Plagl2-/- liver, the starvation response factor asparagine synthetase (AS) is expressed at high levels [244], whereas Igf1 levels are low, indicative of a loss of nutrients [245]. Neither Plag1 nor Plagl2 have any known functions in the developing nervous system, despite their expression in these tissues. In contrast, a developmental role for Zac1 has been identified in the retina and cerebellum [159] [246, 247]. In the retina, Zac1 negatively controls the number of amacrine cells and rods generated during development [159].

While Zac1 functions as a direct negative regulator of a rod cell fate, amacrine cell production is regulated by Zac1 indirectly (i.e., non-cell autonomously) via regulating the expression of TGFβII

[159]. TGFβII then acts in a negative feedback pathway to limit amacrine cell production [159].

In the developing murine cerebellum Zac1 was shown to be required for the development of certain

neuronal subtypes and nuclei [247]. Taken together these findings demonstrated that Zac1 does indeed have a function in the developing nervous system [247].

1.6. An introduction to glioma

For chapter 4 of my thesis, I focused on studying the non-autonomous interactions of oligodendroglioma cells with mNSCs. In the following section, a general introduction on glioma and oligodendroglioma is described.

1.6.1. General introduction to glioma subtypes. Gliomas are glial cell-derived brain tumours that are generally classified as astrocytomas (e.g., glioblastoma - GBM) or oligodendrogliomas (ODG). Histopathologically, these two types of gliomas are characterized based on their morphological resemblance with the normal cells in the brain, having astrocytic or oligodendroglial features, respectively. Furthermore, the World Health Organization (WHO) has categorized gliomas as low grade (grade I-II) and high grade (grades II-IV). Low grade gliomas are non-anaplastic, which means that they are well differentiated and benign, while high grade gliomas are anaplastic and malignant. These original WHO grade classifications were almost entirely dependent on histological characteristics of glioma. More recently, genetic and molecular differences in the otherwise histologically similar glioma samples were identified [248], enabling the classification of brain tumors based also on their genetic profiles [249, 250]. Although histological and genetic analyses are both required to confirm a diagnosis of tumor type, in 2016

WHO has emphasized the importance of genotype over histology.

1.6.2. Molecular features of ODG. ODG accounts for approximately 6% of all gliomas.

ODGs develop in early adulthood, and even though they are slowly growing tumours, they are

ultimately fatal [251]. ODGs tend to localize to the cerebral cortex and they contain cells that look like oligodendrocyte precursor cells (OPCs), expressing Olig2, Pdgfra and NG2 [251], while not expressing mature oligodendrocyte cell markers such as myelin basic protein (MBP), Proteolipid protein (PLP) and myelin-associated glycoprotein [252]. Not only do ODGs resemble OPCs, there is also evidence that they arise from OPCs [253, 254].

ODG has a very specific genetic signature as it is associated with 1p19q codeletion and

IDH1/2 mutation [255, 256]. The 1p19q codeletion is caused by an uneven translocation t(1;19)(q10;p10) [257, 258]. Mutations in IDH1 are in codon 132 and mutations in IDH2 are in codon 172). Another genetic anomaly that is linked to ODG is mutation of the CIC gene. CIC is the drosophila homologue of capicua which is a transcriptional repressor [259]. In addition,

Telomerase reverse transcriptase- (TERT) promoter mutations are also commonly (>95% of ODG cases) associated with ODG, leading to the activation of reverse transcriptase activity of telomerase [260]. Mutation of the far upstream element binding protein 1 (FUBP1) which is a known regulator of MYC is also found in commonly in the oligodendroglial tumors [259].

Furthermore, less aggressive ODG is characterized by mutations in NOTCH1 (development regulator gene), SETD2 (epigenetic regulator gene) and PIK3CA (PI3K pathway gene) [250, 261].

However, more aggressive ODGs are characterized by 1p19q codeletion [262], upregulation of transcription factor 12 (TCF12) [263] and MYC signalling [264].

1.6.3. Molecular features of adult GBM. GBMs are the most common type of astrocytoma and the most common glioma. Unlike ODG, GBM progresses rapidly, and these malignant tumors are also ultimately fatal. GBMs have been divided into three classes based on gene expression patterns: classical, proneural, and mesenchymal [265]. Classical GBMs often have mutations

resulting in EGFR activation, including a constitutively active deletion mutation known as

EGFRviii [266], which is one of the oncogenes found in EVs [267]. Classical GBMs have a molecular profile associated with the activation of Notch (NOTCH3, JAG1) and sonic hedgehog

(SMO, GLI2) signaling [266]. Proneural GBMs most often have constitutively active PDGFRA signaling, which is a pro-OPC pathway that results in the expression of several OPC genes, such as NKX2.2, OLIG2, and +ASCL1 [266, 268]. Mesenchymal GBMs have mutations in NF1 and express a distinct set of markers [266, 268, 269].

1.7 An introduction to extracellular vesicles (EVs)

For chapter 4 of my thesis, I focused on studying the non-autonomous interactions of oligodendroglioma cells with mNSCs. In the following section, a brief introduction on EVs,

EV biosynthesis and release mechanisms, EV roles identified in the developing CNS and cancer have been outlined. It is interesting to note that cancer cells and various cell types in the neocortex have been shown to secrete EVs and communicate with each other.

1.7.1 General introduction to EVs. One way that cells can communicate with their neighbors is through the secretion of extracellular vesicles (EVs), which are lipid bilayer-enclosed vesicles that are packaged with protein, RNA and/or DNA [270, 271] (Figure 4.3A). The two main types of EVs are microvesicles (MVs), which are shed by budding from the plasma membrane, and exosomes, which are secreted from endosomes [271]. These two classes of EVs are quite different in size, with MVs in the 100nm to 1µm in diameter range, and exosomes in the 30-100nm in diameter range [271]. Another EV subtype that are even larger in size (0.8-5µm) are apoptotic bodies, which are shed from apoptotic cells and phagocytosed by phagosomes in the extracellular space [272].

1.7.2 Biosynthesis of exosomes. The biogenesis of EVs is vesicle-dependent. The biogenesis of exosomes begins with endosomes that start to accumulate intraluminal vesicles

(ILVs) during their transition from early endosomes to late endosomes [273]. ILVs are generated due to the inward budding of early endosomes. These late endosomes are multivesicular are hence termed multivesicular bodies (MVBs). MVBs may either fuse with lysosomes, which leads to degradation of their contents, or fuse with the plasma membrane (PM), and shed off into the extracellular space. MVBs that shed express several late endosomal markers such as the tetraspanins CD63, CD9 and CD81, with CD63 expressed in EVs of all sizes and CD81 only in the smallest exosomes [271].

The most studied pathway for MVB and ILV formation is called the endosomal sorting complex required for transport (ESCRT). The ESCRT complex contains approximately thirty proteins that are packaged into four complexes called ESCRT-0, -I, -II and –III, and these complexes have additional associated proteins (eg. ALIX) [274]. ESCRT-0 recognizes transmembrane proteins that are ubiquitinated and isolates them into the endosomal membrane,

ESCRT-I/II are required for inward budding of sorted cargo, and ESCRT-III is essential for budding off of the vesicle [274]. ESCRT-0 is comprised of the hepatocyte growth factor –regulated tyrosine kinase substrate (HRS, also refered to as HGS) which recognizes monoubiquitinated molecules. TSG101 of ESCRT-I is recruited by HRS, which in turn associates with ALIX of

ESCRT-II complex and recruits the ESCRT-III complex. Notably, MVBs and ILVs can form in the absence of the ESCRT pathway, so biogenesis of EVs can occur via ESCRT dependent or independent pathways.[275].

ESCRT-independent mechanisms of EV biogenesis has also been extensively studied. The

MVB membrane is composed of lipids generated by two lipid metabolizing enzymes; neutral sphingomyelinase (nSMase) which hydrolyses sphingomyelin to ceramide, and phospholipase D2 which hydrolyses phosphotidylcholine into phosphatidic acid [276, 277]. Blocking nSMase activity with a pharmacological inhibitor (GW4869) inhibits exosomal release, indicating that packaging into ILVs is ceramide dependent and ESCRT independent [277]. In contrast, larger microvesicles are derived from shedding of membrane-enclosed vesicles from the plasma membrane, and their biogenesis is dependent on enzymes such as acidic sphingomyelinases

(aSmase)[278].

1.7.3 Rab GTPases in exosomal secretion. The content of EVs can be delivered to neighboring cells upon secretion from the cell of origin. The Rab protein family of GTPases, including RAB9A, 5A, 2B, 11, 35, and 27A/B, play a critical role in exosome secretion, showing cell type specificity, and participating in the docking of MVBs to the plasma membrane [279-282].

The Rab proteins do have some specific functions. For example, RAB11 is associated with recycling of endosomes, RAB35 is associated with early endosome sorting, and RAB27A/B is associated with late endosome and lysosome organelles [283]. To illustrate the importance of the

Rab proteins and their cell type-specificity, exosome secretion was reduced significantly upon deletion of Rab27A in several tumor cell lines [284-287]. In contrast, exosome secretion in MDA-

MB-231 breast cancer cells was not perturbed upon deletion of RAB27A although it was if both

RAB27A and RAB27B were depleted [288]. Efforts to interfere with EV secretion must therefore take into account the cell type to be used.

1.7.4. EV function in the nervous system. There are now several studies demonstrating that neurons secrete EVs. As an example, when neurons when cultured in vitro can be stimulated to secrete EVs by the addition of GABA+ receptor inhibitors (AMPA, NMDA) or the addition of excitation molecules such as Ca2+ ionophores [289, 290]. EVs derived from excited neurons are then taken up by the surrounding neurons [291]. In another study, purified exosomes from cultured primary mouse cortical neurons contained miR-124a, which was taken up by the surrounding astrocytes, inducing the expression of excitatory amino acid transporter 2 (EAAT2), which is an essential component of glutamate uptake in the brain [292].

Oligodendrocytes have also been shown to release EVs at periaxonal sites, and these EVs contain proteins such as PLP and myelin associated proteins that protect against oxidative stress

[281, 293, 294]. Similarly, Schwann cells in the peripheral nervous system (PNS) secrete exosomes that enhance axonal regeneration and repair after a sciatic nerve crush injury [295]. In another study, EVs secreted from oligodendrocytes are taken up by neurons and microglia [281], and one study has suggested that microglia taking up the EV cargo are simply removing waste products from the neurons [296]. Finally, astrocytes have been shown to secrete EVs in an aSMase- dependent fashion [278].

1.7.5. EV functions in brain cancer. Cancer cells are well known to release EVs, and this secretion appears to be at levels higher than observed in normal cells, and often tumour EVs have different cargo than the non-transformed cells from which they are derived. The difference can lie in the amount of cargo, and the presence of transforming protein(s), RNA and/or DNA. EVs secreted from the cancer cells are often called oncosomes, and when they are taken up by the neighboring ‘normal’ cells, they can transfer oncogenic activity [297]. Oncogenes that are

transferred include epidermal growth factor variant III (EGFRvIII), tumor suppressors, histones and miRNAs [267]. For example, GBMs secrete EVs that can alter the proliferation, motility and survival rates of neighboring cells [297]. For example, uptake of EGFRvIII in neighbouring

‘normal’ cells results in activation of receptor tyrosine kinase (RTK) signaling, with activation of

ERK and AKT pathways [267]. GBM cells also secrete EVs that carry mir-1, a tumor suppressor that silences annexin A2 mRNA, the protein product of which is oncogenic [298].

1.8 Summary, hypothesis and rationale

The neocortex, which is the most recently evolved region of the brain, is constructed in a highly ordered and specific fashion. It is comprised of six distinct neuronal layers, each made up of neurons with unique morphologies, axonal projection patterns, gene expression profiles, and specialized functions. During my thesis studies, my goal was to decipher how neuronal cell fate specification and neuronal migration are regulated at the molecular level in the developing neocortex. Specifically, I examined the role of the three pleiomorphic adenoma genes (Plag), which encode for a small family of zinc finger transcription factors, in neocortical development.

In cancer cells, Plag-like1 (Plagl1, also known as Zac1) is a tumor suppressor gene that normally promotes cell cycle exit and apoptosis, while Plag1 and Plag-like2 (Plagl2) are proto-oncogenes, which when activated, promote uncontrolled cell proliferation. My general hypothesis was that the three Plag genes, all of which are expressed in neocortical progenitors, control the decisions by progenitors to proliferate or differentiate, thereby influencing the timing of neuronal differentiation and subsequent neuronal migration. Indeed, I showed that Zac1 is a critical regulator of neuronal migration in the developing neocortex (Chapter 2). I also showed that

Plag1 and Plagl2 regulate telencephalic patterning and proliferation (Chapter 3). In my final

chapter I switched my focus to studying how the proliferation of cortical progenitors is regulated in a tumour setting. My general hypothesis was that tumour cells secrete factors that influence the brain, and I focused on how these factors influence dividing neocortical progenitor cells. I found that an oligodendroglioma cell line secretes EVs that act in a dosage-dependent fashion to control the proliferation of neocortical progenitors, and I identified EGF as one of the responsible factors (Chapter 4).

1.9 Figures and Figure legends

Figure 1.1. Neocortical Anatomy. (A) Schematic of the adult neocortex. The germinal zone contains ependymal (grey) and subependymal (purple) cells. The intermediate zone (blue) contains white matter tracts. The subplate (layer VII) is a transient neuronal layer in rodents (white neurons) that persists into adulthood in some species. Layer VI multiform neurons (green) send subcortical projections to the thalamus (grey arrow). Layer V internal pyramidal cells (yellow) send projections to subcortical targets including the basal ganglia, brain stem and spinal cord (yellow arrow). Spiny stellate and pyramidal neurons make up the internal granular layer IV (blue), which receives sensory information from the thalamus (grey arrow). Neurons in layers II external granular neurons and layer III external pyramidal neurons are intermingled in rodents (orange and pink cells), and send out commissural projections to the anterior commissure and corpus callosum

(black arrow). Layer I consists of CR cells (white), which secrete reelin (black dashed lines across the layers). (B) Rodent (top) and human (bottom) neocortices are subdivided in the tangential plane into primary sensory areas, including auditory (blue), visual (green), somatosensory (pink) and motor (red) regions.

Figure 1.2: Interkinetic nuclear migration (INNM). The RGCs undergo IKNM reaching the basal region in S-phase and apical region at M-phase, when it produces a neuron and a RGC by asymmetric cell division.

Figure 1.3: Different Modes of cell division. Symmetric/Proliferative divisions generate 2 daughter progenitor cells. Asymmetric divisions generate a daughter neuron and a daughter progenitor cell. Symmetric neurogenic divisions produce 2 postmitotic neurons from a single progenitor cell.

Figure 1.4: Sites of origin of Cajal-Retzius neurons. CR neurons have three sites of origin in the cortical margins, including the pallial septum (A), the cortical hem (red) and antihem (blue)

(B). CR neurons also arise from the thalamic eminence (not diagramed).

Figure 1.5: Sequential generation of cortical neurons. (A) At E10.5, radial glial cells (RGCs)

(diamond shaped grey cells) differentiate into the first pool of cortical neurons to form the preplate

(PP) (light grey). By ~E11.5, RGCs start producing a second pool of progenitors termed intermediate neuronal precursors (INPs) (purple). At this stage, RGCs also divide asymmetrically to generate one RGC and one layer VI neuron (green). Layer VI neurons split the PP into a lower subplate (white) and an upper MZ (layer I) (white). From here on the neurons are generated in an inside out fashion such that layer V neurons (yellow) are born next, followed by neurons of layers

IV (blue) and layer III/II (pink and orange). The red arrows indicate the possibility of generation of upper later neurons from RGCs and INPs. The red arrows also show the mode of neuronal cell migration in the developing neocortex. (B and C) The inside out generation of neurons is schematized, where upper layers consist of neurons from layers IV and II/III, while deep layers consist of neurons from layers VI and V.

Figure 1.6. Sites of origin of cortical interneurons. (A,B) Neocortical interneurons arise from the MGE and CGE, whereas the POA gives rise to hippocampal interneurons. Ventrally-derived interneurons migrate tangentially to enter the neocortex (B). MGE, medial ganglionic eminence;

CGE, caudal ganglionic eminence; POA, preoptic area.

Figure 1.7. A postmitotic derepression circuit specifies laminar fates. Cortical laminar identity is specified by a derepression circuit of layer-specific transcription factors. Pax6 is expressed in radial glial cells (RGCs) and Tbr2 is expressed in intermediate neuronal progenitors (INPs). Sox5 and Tbr1 are expressed at high levels in layer VI, where they repress Fezf2 and Ctip2 expression, specifying a layer VI corticothalamic projection neuron identity. In layer V, the lack of expression of Sox5 and Tbr1 allows Fezf2 and Ctip2 to be expressed. Conversely, Fezf2 and Ctip2 repress the expression of Tbr1 to suppress a layer VI identity and induce the differentiation of layer V subcerebral projection neurons. Fezf2 also repress Sabt2 expression, which promotes a layer II/III identity. In layer II/III, Satb2 escapes from the repression of Fezf2 and is highly expressed. Satb2 binds to the Ctip2 locus to repress expression of Ctip2 and specifies a callosal projection neuron identity in layer II-III.

Figure 1.8. Neural stem cell multipotency. (A) Cortical progenitors have the ability to generate different cell types at different stages of development, passing through an intermediate progenitor and then committed precursor stage. (B) Between E10.5-E17, neural stem cells (NSCs) (grey) generate neurons (green). Also embryonically, at E15.5, NSCs begin differentiating into astrocyte precursor cells (blue). Finally, when the pups are born (P0), NSCs start generating oligodendrocyte precursor cells (OPCs), which differentiate into oligodendrocytes (red).

Figure 1.9. Specification of a cortical astrocytic fate. Multiple extrinsic signals and intrinsic factors act in a coordinated fashion to specify an astrocyte identity. The major pathways are summarized here.

Figure 1.10. Sites of origin of cortical oligodendrocytes. (A) During the embryonic period, oligodendrocyte precursor cells (OPCs) arise in the MGE (E11.5) and then the LGE (E16.5), followed by a third wave of OPC differentiation from dorsal cortical domains after P0. (B) The different temporal waves of OPC genesis are schematized.

Figure 1.11. Members of the Plag gene family: Plagl1 (Zac1), Plagl1 and Plagl2. Members of the Plag gene family. The loci (in humans) for each gene is mentioned in brackets. Plag-l1 is

4.7kb, Plag1 is 7.3kb and Plag-l2 is 496bp in length in humans. In mice, Plag-l1 is present in chromosome 10, while chromosomes 4 and 2 contain mPlag1 and mPlag-l1, respectively.

CHAPTER 2: Zac1 regulates the differentiation and migration of neocortical neurons via Pac1

Lata Adnani, Lisa Marie Langevin, Elodie Gautier, Rajiv Dixit, Kari Parsons, Saiqun Li, Gaurav Kaushik, Grey Wilkinson, Richard Wilson, Sarah Childs, Minh Dang Nguyen, Laurent Journot, Colette Dehay, Carol Schuurmans

2.1 ABSTRACT

Imprinted genes are dosage sensitive, and their dysregulated expression is linked to disorders of growth and proliferation, including fetal and postnatal growth restriction. Common sequelae of growth disorders include neurodevelopmental defects, some of which are indirectly related to placental insufficiency. However, several growth-associated imprinted genes are also expressed in the embryonic CNS, where their aberrant expression may more directly impact neurodevelopment.

To test whether growth-associated genes influence neural lineage progression, we focused on the maternally imprinted gene, Zac1. In humans, either loss- or gain- of ZAC1 expression is associated with reduced growth rates and intellectual disability. To test whether increased Zac1 expression directly perturbs neurodevelopment, we misexpressed Zac1 in murine neocortical progenitors. The effects were striking; Zac1 delayed the transition of apical radial glial cells to basal intermediate neuronal progenitors, and postponed their subsequent differentiation into neurons. Zac1 misexpression also blocked neuronal migration, with Zac1-overexpressing neurons pausing more frequently and forming fewer neurite branches during the period when locomoting neurons undergo dynamic morphological transitions. Similar, albeit less striking, neuronal migration and morphological defects were observed upon Zac1 knock-down, indicating that Zac1 levels must be precisely regulated. Finally, Zac1 controlled neuronal migration by regulating Pac1 transcription, a receptor for the neuropeptide PACAP. Pac1 and Zac1 loss and gain-of-function presented as phenocopies, and overexpression of Pac1 rescued the Zac1 knock-down neuronal migration phenotype. Dysregulated Zac1 expression thus has striking consequences on neocortical development, suggesting that misexpression of this transcription factor in the brain in certain growth disorders may contribute to neurocognitive deficits.

2.2 SIGNIFICANCE STATEMENT

Altered expression of imprinted genes is linked to cognitive dysfunction and neuropsychological disorders such as Angelman and Prader-Willi syndromes, and autism spectrum disorder. Mouse models have also revealed the importance of imprinting for brain development, with chimeras generated with parthenogenetic (two maternal chromosomes) or androgenetic (two paternal chromosomes) cells displaying altered brain sizes and cellular defects. Despite these striking phenotypes, only a handful of imprinted genes are known or suspected to regulate brain development (e.g., Dlk1, Peg3, Ube3a, necdin, Grb10). Herein we show that the maternally imprinted gene, Zac1 is a critical regulator of neocortical development. Our studies are relevant as loss of 6q24 maternal imprinting in humans results in elevated ZAC1 expression, which has been associated with neurocognitive defects.

2.3 INTRODUCTION

Development of a functional nervous system requires that appropriate numbers of the correct types of neurons first differentiate, and then migrate to their proper destinations where they establish specific synaptic connections. Long-term cognitive and behavioural deficits can arise when neurogenesis, neuronal migration or circuit formation are disrupted. Infants with intrauterine growth restriction (IUGR), defined as birth weights below the 10th percentile for gestational age

[299], have an increased risk of long-term neurological disabilities [300-302]. While IUGR-linked neurodevelopmental defects can be a secondary consequence of reduced nutrient/oxygen levels during pregnancy from placental insufficiency, several genes associated with IUGR are also expressed in the embryonic CNS, where their dysregulated expression may more directly impact nervous system development. Included in this category are imprinted genes, which are expressed in a parent-of-origin specific manner, and are emerging as key regulators of both intrauterine growth and brain development [303, 304].

Zac1, also known as pleiomorphic adenoma gene like 1 (Plagl1), is a maternally imprinted gene that encodes a seven-C2H2 zinc finger protein [1]. Human ZAC1 is located on chromosome

6q24-25, a locus silenced in multiple carcinomas, including head and neck, ovarian, and pituitary tumors [1]. The ZAC1 maternal imprint is established during oogenesis by methylation of an imprinting control region (ICR), which silences transcription from a maternal P1 promoter [178].

Loss of 6q24 maternal imprinting, resulting in biallelic expression, occurs in 70% of infants with transient neonatal diabetes mellitus (TNDM), a disorder associated with growth retardation [305,

306]. In contrast, ICR hyper-methylation reduces ZAC1 expression in ovarian tumor cells [179].

Reduced ZAC1 expression is also associated with growth restriction, developmental delay and intellectual disability (e.g., Decipher ID: 248227, 294593).

In mouse models, Zac1 regulates embryonic growth [157], as well as keratinocyte [307], heart [225, 308], pancreatic islet [309], cerebellar [247] and retinal [159, 246] development. We identified Zac1 in a subtractive screen designed to identify new regulators of neocortical neurogenesis [310]. Here, we asked whether altered Zac1 expression in the embryonic neocortex, the seat of higher order cognitive functioning, could give rise to morphological defects that may result in neurocognitive deficits [300-302]. Misexpression of Zac1 in neocortical progenitors inhibited progenitor maturation, while delaying neuronal differentiation and migration. The effects of Zac1 on neuronal migration were in part mediated by Pac1 (Pituitary adenylate cyclase- activating polypeptide type I receptor), a Zac1 transcriptional target [233, 311] that controls neocortical progenitor proliferation [235, 236]. We have thus identified a novel Zac1-Pac1 regulatory pathway that controls progenitor maturation, neuronal differentiation and migration in the developing neocortex.

2.4 MATERIALS AND METHODS

2.4.1. Animals. Embryos were staged using the morning of the vaginal plug as embryonic day (E)

0.5. CD1 mice (Charles River Laboratories, Senneville, QC) were used for in utero electroporation experiments. Zac1 null mutant embryos were obtained by crossing Zac1+/- males with C57/Bl6 wild-type females. The resulting Zac1+m/- embryos, which obtained their wild-type allele from the dam, were the equivalent of Zac1 null mutants due to imprinting of the maternal Zac1 allele.

Genotyping Zac1 mutant and wild-type alleles was performed as described [159].

2.4.2. Constructs used for in utero electroporation. For gain-of-function experiments, Zac1 and

Pac1 were cloned into pCIG2 [312], a bicistronic expression vector containing a β−actin

promoter/CMV enhancer and an internal ribosome entry site (IRES)-EGFP cassette [312]. For knock-down experiments, shRNAs were obtained from ORIGENE (Rockville, MD): HuSH shRNA TG502444 mus musculus Plagl1 (Zac1) in pGFP-V-RS; HuSH shRNA TG500044 mus musculus Adcyap1r1 in pGFP-V-RS. To identify which of the four shRNAs was most effective,

NIH-3T3 cells were transfected with pCIG2-Zac1 or pCIG2-Pac1 either alone or together with individual shRNAs and Western blots were performed 24 hr later (as in [313]). The scrambled shRNA was from ORIGENE (TR30013). EGFP-CentII [107] and pEF/Myc/ER/GFP vectors

(Invitrogen, Carlsbad, CA) were modified to incorporate RFP and mCherry reporters, as previously described [112].

2.4.3. In utero electroporation. In utero electroporation was performed as described [314].

Briefly, endotoxin-free DNA was prepared according to the manufacturer’s instructions (Qiagen,

Mississauga, ON) and injected at 1.5 g/l into the telencephalic vesicles of embryos in time-staged pregnant females anaesthetized under inhalable isofluorane (5L/min) using a Femtojet microinjector apparatus (VWR CanLab, Mississauga, ON) and 3-axis coarse manipulator (Carl

Zeiss Canada, North York, ON). This was followed by seven 50 V pulses at 750 msec intervals applied by tweezer-style electrodes (5 mm for E12.5 and 7 mm for E14.5; Protech International,

Monroe, NC) using a BTX square wave electroporator (BTX, VWR CanLab). The uterus was replaced in the body cavity, the peritoneum was sutured and the skin stapled, and normal embryonic development proceeded until the time of harvesting.

2.4.4. RNA extraction, cDNA synthesis and quantitative real time PCR (qRT-PCR). RNA was extracted from E18.5 wild type and Zac1 mutant cortices, and from microdissected

E13.5→E14.5 cortical tissue electroporated with pCIG2 or pCIG2-Zac1 using an RNeasy® Mini

Kit (Qiagen, Mississauga, ON) according to the manufacturer’s instructions. First strand cDNA was synthesized using the Quantitect Reverse Transcription kit (Qiagen) according to the manufacturer’s instructions. qRT-PCR was performed using an Opticon 2 DNA engine (Biorad

Laboratories Canada, Mississauga, ON) using a Quantifast™ SYBR® Green kit (Qiagen). For every primer pair, three different cDNA dilutions were tested with the following cycle conditions: one cycle of 95°C/4', 40 cycles of 95°C/1', 55°C to 67°C/1', 72°C/1'30'', and one cycle of 72°C/10'.

The annealing temperature was optimized for each primer pair using a temperature gradient, selecting conditions that yielded >95% amplification efficiencies. Normalization was achieved using Hprt (Hypoxanthine phosphoribosyl-transferase 1) and B2m (Beta-2 microglobulin) as reference genes. Pac1 forward: TACTCCAGATGTGGTTCCAGGC; reverse:

AGTGAGGTCCGTGGGGTTTATC (66°C annealing); B2M forward:

CCTGGTCTTTCTGGTGCTTGTC; reverse: CAGTATGTTCGGCTTCCCATTC (63°C annealing); HPRT forward: AGCTACTGTAATGATCAGTCAACG; reverse:

AGAGGTCCTTTTCACCAGCA (58.3°C annealing); Zac1 forward:

AATGTGGCAAGTCCTTCGTCAC; reverse: TGGTTCTTCAGGTGGTCCTTCC (67°C annealing).

2.4.5. Tissue processing and immunolabeling. Dissected brains were fixed overnight at 4°C in

4% paraformaldehyde (PFA)/1X phosphate buffered saline (PBS). Brains were rinsed 3 x 10 min in 1X PBS and transferred to 20% sucrose/1X PBS overnight at 4°C. Cryopreserved brains were then embedded in O.C.T™ (Tissue-Tek®, Sakura Finetek U.S.A. Inc., Torrance, CA) and stored at -80°C before cutting 10 micron cryosections. For immunolabeling, sections were blocked 1 hr

in 10% normal goat serum in 1X TBST (Tris Buffered Saline: 25 mM Tris, 0.14 M NaCl, 0.1%

Triton X-100) at room temperature. Primary antibodies were diluted in blocking solution and incubated on slides overnight at 4ºC. Slides were washed 3x10 min in TBST before incubating in secondary antibody diluted in TBST for 1 hr at room temperature. Nuclei were counterstained in

DAPI (4',6-diamidino-2-phenylindole, Santa Cruz, Santa Cruz, CA) diluted 1/10,000 in 1X PBS for 5 min and then destained with 3x5 min PBS washes before mounting in AquaPolymount

(Polysciences, Inc., Warrington PA). Primary antibodies included: mouse anti-BrdU (1/200,

Roche Diagnostics GmbH, Mannheim, Germany), rabbit anti-GFP (1/500, Chemicon, Temecula

CA), rabbit anti-Pax6 (1/500, Covance, Laval, QC), rabbit anti-Cux1 (anti-CDP, 1/500, Santa

Cruz), mouse anti-Tuj1 (Neuronal class III β-tubulin, 1/500, Covance, Laval, QC), rabbit anti-

Tbr1 (1/3000, Chemicon), rabbit anti-Tbr2 (1/500, Abcam, Cambridge MA), rabbit anti-phospho- histone H3 (pHH3; 1/1000, Upstate Biotechnology, Lake Placid, NY), mouse anti-NeuN (1/500,

Chemicon), goat anti-Beta3 (1/300, Santa Cruz), rat anti-Ctip2 (1/100, Abcam, Cambridge MA),

Rabbit anti-Ki67 (1:200, Abcam, Cambridge MA) and rabbit anti-Zac1 [1/1000; [315]]. Secondary antibodies were conjugated to Alexa488 (1/500, Molecular Probes, Eugene, Oregon) or Cy3

(1/500, Jackson Immunoresearch, West Grove, PA).

2.4.6. BrdU and EdU labeling. For birthdating and proliferation studies, 100 µg/g body weight

BrdU (Sigma, Oakville, ON) was injected intraperitoneally at E14.5. For BrdU immunolabeling, sections were treated with 2N HCl for 25 min at 37°C prior to processing [38]. Cell proliferation was assayed via EdU staining, using the Click-iT™ EdU Alexa-Fluor® 594 kit (Invitrogen).

200µL of 1µg/µL EdU (5-ethynyl-2’-deoxyuridine) dissolved in PBS was injected subcutaneously into pregnant dams 30 min prior to sacrifice. For gain-of-function studies, sections were first

stained with αGFP and post-fixed for 1 hr in 4%PFA /1XPBS at 4°C. Slides were the rinsed 3x10 min in 5% BSA (bovine serum albumin) /1XPBS and then stained for EdU as per the manufacturer’s instructions. Slides were rinsed 3x5 min in 1XPBS, counterstained with DAPI and mounted using Aqua Polymount.

2.4.7. Biphoton time lapse videomicroscopy. E15.5 cortices were dissected and electroporated with pCIG2 (control) or pCIG2-Zac1 expression constructs. Briefly, 1.5 mL of plasmid at 1-2

µg/µl was mixed with Fast Green (0.01 mg/ml; Sigma) and injected into the lateral ventricles of whole heads using a Hamilton syringe. Gold electrodes (Genetrode BTX Model 514, Harvard

Apparatus) were used to deliver five pulses of 30V, 50 ms on/1000 ms off. The anode was oriented dorsally and the cathode ventrally. Cortices were then sliced and maintained in culture for 4 days

(37°C, 7.5% CO2) as 150 µm organotypic slices. Biphoton time lapse videomicroscopy was performed on 24 recorded positions in both hemispheres of 12 brain slices (2 from each brain, n=3 for each construct) over 3 days beginning 30h post-electroporation. One image was taken per hour on 100 µm with 20 z-slices. A total of 195 control neurons (pCIG2) and 133 Zac1-transfected neurons were traced. Migration parameters extracted for each neuron included time of departure and arrival (number of hours after electroporation), migration duration (T, in hour), distance (D, in µm) and velocity (µm/h = D / T), number and duration of pauses during saltatory locomotion.

A pause was defined as non-significant movement (< 3.5µm) during at least two consecutive hours.

Migration parameters were calculated for each neuron on a fragmented track. The neocortex thickness was subdivided into 20 bins parallel to the ventricular border, and the values were calculated for movements made in each bin. As neurons can begin and finish their track in different

bins, only bins with at least half of the population making a part of their tracks in a bin were taken into account.

2.4.8. RNA in situ hybridization. RNA in situ hybridization was performed as previously described [316]. The Zac1 digoxygenin-labeled riboprobe was generated as in [158].

2.4.9. Imaging, tracing, quantitation and statistics. Images were captured with a QImaging

RETIGA 2000R or QImaging RETIGA EX digital camera and a Leica DMRXA2 optical microscope using OpenLab5 software (Improvision; Waltham MA). Confocal images were acquired using a Nikon C1si Spectral confocal microscope. The lasers used to detect DAPI, GFP and TxRed were excited at 405nm, 488nm and 561nm respectively with a 400-750nm detectable emission range. Using these images, neurons were traced with the paint tool in Photoshop CS6 (64 bit). Cell counts were performed on a minimum of three embryos per genotype or treatment group, and a minimum of three cortical sections from each embryo. Statistical significance was calculated using a student’s t test when comparing two values, while three or more values were compared using a two-way ANOVA with a Bonferonni correction unless indicated. Graphs and statistics were generated using GraphPad Prism Software (GraphPad Inc., La Jolla, CA). Error bars represent s.e.m.. p values denoted as follows: < 0.05 *, < 0.01 **, < 0.005 ***.

2.5. RESULTS

2.5.1. Overexpression of Zac1 in neocortical progenitors perturbs late-born neuronal migration

Previous analyses revealed that Zac1 is expressed in a regionalized fashion in the developing nervous system, including in the telencephalon, the anlage of the neocortex [158]. To better understand how Zac1 might function during neocortical development, we assessed its expression in this region of the embryonic neural tube in more detail. At embryonic day (E) 12.5, Zac1 transcripts were detected at high levels in dorsal telencephalic (neocortical) progenitor cells in the ventricular zone (VZ), and at lower levels in the ventral telencephalic VZ (Figure 2.1A,A'). At

E15.5, Zac1 continued to be expressed in neocortical VZ progenitors, as well as in deep layers of the developing cortical plate (Figure 2.1B,B'). A similar spatiotemporal distribution was observed using Zac1-specific antisera; at E12.5 (Figure 2.1C,C') and E14.5 (Figure 2.1D,D'), Zac1 protein was detected in most neocortical VZ progenitors, but not in postmitotic Tuj1+ neurons. By E16.5

(Figure 2.1E,E',E'') and at E18.5 (Figure 2.1F,F',F''), Zac1 protein continued to be widely expressed in the neocortical VZ, and could now be detected in a small number of subventricular zone (SVZ) cells and deep layer neurons. Zac1 is thus primarily expressed in neocortical VZ progenitors and in a smaller number of SVZ progenitors and deep-layer postmitotic neurons.

To mimic the upregulation of Zac1 expression associated with loss of the maternal imprint in TNDM, a bicistronic pCIG2-Zac1 expression vector containing an IRES-EGFP cassette, or an empty vector pCIG2 control, were introduced into E12.5 and E14.5 neocortical progenitors via in utero electroporation. The positions of GFP+ electroporated cells were then assessed at E18.5.

Control and Zac1 E12.5→E18.5 electroporations looked similar, with most GFP+ electroporated cells concentrated in deep neocortical layers (n=3; p>0.05 comparing all layers; Figure 2.1G-I), in accordance with the E12.5 birthdate of layer VI neurons [43, 44]. In contrast, a striking migratory block was observed in E14.5→E18.5 Zac1 electroporations, with Zac1-overexpressing cells aggregating in the intermediate zones (IZ) (n=6; p<0.01) instead of migrating into upper (n=6;

p<0.005) layers of the cortical plate (CP) (Figure 2.1J-L). Overexpression of Zac1 thus strongly perturbs cellular migration at later stages of neocortical development, either because overexpressing cells fail to differentiate, and/or because Zac1 impairs neuronal migration, which we addressed further below.

2.5.2. Zac1 misexpression delays progenitor cell maturation and neuronal differentiation

To further dissect the effects of Zac1 overexpression on neocortical progenitors, we focused on E14.5 electroporations, when Zac1-induced migratory defects were most profound. At E14.5,

Pax6+ radial glial cell (RGC) progenitors in the VZ give rise to Tbr2+ intermediate neuronal progenitors (INPs) in the SVZ, which divide once or twice before differentiating into Tbr1+ neurons [24] (Figure 2.2A). To test whether Zac1 overexpression perturbed the RGC to INP transition, we performed shorter E14.5→E15.5 electroporations. By 24 hrs post-electroporation, the vast majority of pCIG2-transfected GFP+ progenitors migrated to the upper VZ/SVZ, in transition to becoming an INP (Figure 2.2B,D). In contrast, more Zac1-transfected cells remained in the lower VZ (n=3; p<0.005), and many fewer cells reached the SVZ (n=3; p<0.005; Figure

2.2C,D), consistent with a possible block in the RGC to INP transition.

A distinguishing feature of RGC progenitors is their cell cycle-dependent interkinetic nuclear movements, with nuclei in G2/M-phase of the cell cycle dividing at the apical surface, whereas INP mitoses occur in basal positions. To determine whether Zac1 influenced the apical to basal mitotic transition, we examined the expression of phosphorylated histone H3 (pHH3), a

G2/M-phase marker (Figure 2.2E-G). In E14.5→E15.5 transfections, of the Zac1-transfected

(GFP+) cells that co-expressed pHH3, most divided in apical regions of the VZ (n=3; p<0.005), while fewer divided basally compared to control pCIG2-transfections (n=3; p<0.005; Figure

2.2G). This data is consistent with the idea that Zac1 maintains a RGC identity while blocking the transition to an INP fate. To provide further support for this conclusion, we examined the expression of Pax6 and Tbr2, which are specifically expressed in, and are essential determinants of, RGC and INP progenitor cell fates, respectively [31, 36]. At 24 hours post-E14.5 electroporation, significantly more Zac1-misexpressing cells versus control-transfected cells expressed Pax6 (n=3; p<0.01; Figure 2.2H-J). Concomitantly, fewer Zac1-transfected cells expressed Tbr2 (n=3; p<0.005; Figure 2.2K-M). Zac1-misexpression thus blocks the maturation of cortical progenitors from an apical Pax6+ RGC identity to a basal Tbr2+ INP fate.

The delay in progenitor cell maturation associated with Zac1-overexpression suggested that this transcription factor may also block neuronal differentiation. To assess the effects of Zac1 on neuronal differentiation, we examined the expression of Tbr1 (Figure 2.2N-P), a T-box transcription factor that is expressed at high and low levels, respectively in deep- and upper-layer cortical neurons [31]. In E14.5→E15.5 electroporations, the number of Zac1-transfected cells that expressed Tbr1 was reduced compared to control transfections (n=3; p<0.05; Figure 2.2P). These data suggest that Zac1 does indeed block neuronal differentiation in the neocortex. However, these results were somewhat unexpected, as Zac1 promotes cell cycle exit when misexpressed in cell lines [238, 315] or in the retina [159], and exit from the cell cycle is a hallmark feature of neuronal differentiation. To test whether Zac1 influenced the proliferative capacity of E14.5 cortical progenitor cells, we performed a 30 min pulse-label with the thymidine analog EdU (Figure 2.2Q-

S). In E14.5→E15.5 electroporations of Zac1, fewer GFP+EdU+/GFP+ proliferating S-phase progenitors were detected compared to pCIG2 control transfections (n=3; p<0.05). To confirm that

Zac1-misexpressing cells exited the cell cycle at a higher frequency, we administered BrdU immediately after electroporation of pCIG2 or Zac1 at E14.5. At E15.5, 24 hr post- electroporation,

embryos were harvested and quantified based on the number of electroporated GFP+ cells that incorporated BrdU while also expressing Ki67 (Figure 2.2T-V). This value gave us a measure of the number of GFP+ cells that were proliferating at the time of electroporation and also remained in the cell cycle 24 hr later. The number of cells that remained in the cell cycle 24 hr post- electroporation was reduced when Zac1 was overexpressed (n=3) compared to pCIG2 n=3 ; p<0.05; Figure 2.2V). Zac1 thus promotes cell cycle exit in cortical progenitors, even though it does not initiate the expression of neuronal differentiation markers such as Tbr1.

2.5.3. Zac1-overexpression reduces the expression of neuronal differentiation markers

To test whether Zac1 overexpression blocked as opposed to delayed the expression of neuronal differentiation markers, we extended the time after which E14.5 electroporated brains were analysed to E18.5 (Figure 2.3A-P). Four days post-electroporation, NeuN (neuronal nuclear antigen), which is a late neuronal marker, was expressed in comparatively fewer Zac1- versus control-transfected cells (n=3; p<0.005; Figure 2.3A-C), particularly in the GZ (n=3; p<0.01;

Figure 2.3D). Notably, the overall number of GFP+NeuN+ cells was low even in control transfections as NeuN was not expressed at high levels in upper layers of the neocortex. We thus also examined the effects of Zac1 misexpression on the differentiation of deep layer (Ctip2) and upper layer (Cux1 and Beta3) neurons using cell type-specific markers. Ctip2 is expressed in layer

V neurons, most of which differentiate before E14.5. Accordingly, less than 6.0±0.8% of GFP+ neurons in pCIG2 control electroporations expressed Ctip2 (Figure 2.3E,G), and even fewer

GFP+Ctip2+ neurons were observed upon Zac1 overexpression (n=3; p<0.01), particularly in deep layers of the CP (n=3; p<0.005; Figure 2.3H). Consistent with the idea that E14.5 progenitors preferentially differentiate into upper layer neurons, many more control transfected cells expressed

Cux1 (Figure 2.3I,K) and Beta3 (Figure 2.3M,O); markers for upper layers II-IV and II-V, respectively. Zac1 misexpression reduced the number of progenitors that differentiated into both

Cux1+ (n=3; p<0.005; Figure 2.3I-K) and Beta3+ (n=3; p<0.05; Figure 2.3M-O) neurons, particularly in upper neocortical layers (Cux1: n=3; p<0.005; Figure 2.3L; Beta3: n=3; p<0.005;

Figure 2.3P). More Cux1+ and Beta3+ neurons were also observed in the IZ upon Zac1 misexpression (n=3 for both; p<0.005 for Cux1; Figure 2.3L; and p<0.005 for Beta3; Figure 2.3P), suggesting that some neurons differentiate when Zac1 is overexpressed, but these neurons fail to migrate to their correct position in the cortical plate.

Taken together, these data suggest that there is a block in neuronal differentiation in a subset of Zac1 overexpressing progenitors, while many of the neurons that differentiate fail to migrate to their correct location in the cortical plate.

2.5.4. Zac1-overexpressing cells exhibit decreased migratory velocities and increased pause time

Defects in the migration of Zac1-overexpressing neurons were evident 96 hr post- transfection of E14.5 cortical progenitors (Figure 2.1J-L). To better assess the effects of Zac1 misexpression on the migratory behaviour of differentiating neurons, we used time-lapse biphoton laser scanning microscopy to image transfected cells in real time following ex utero electroporation of E15.5 cortical slices. Recordings were initiated 30 hr-post electroporation and were continued over three days with one image taken per hour. In total, 133 control (n=3) and 195 (n=3) Zac1- misexpressing cells were traced through 71 positions along the radial cortical axis, with videomicroscopy ending at 101 hrs post-electroporation (Figure 2.4A,B). Newly born neurons generated at E15.5 were expected to exit the GZ within 48 hours [317], however, a large proportion

(63.7% by 72 hr) of Zac1-electroporated cells did not exit the GZ until 72 hours post-transfection as compared to controls (66.3% by 60 hr) (Figure 2.4C,D). Thus, on average, the peak departure time, defined as the time when neurons left the GZ and entered the IZ (Figure 2.4C), occurred significantly later in Zac1-misexpressing cells compared to controls (p<0.005; Figure 2.4D,E). As migration proceeded, a large subset of control cells (32.8%) managed to arrive at the cortical plate within 56 hours post-transfection, whereas most Zac1-overexpressing cells (53.1%) took in excess of 80 hours to complete this phase of migration (Figure 2.4F,G). Accordingly, the peak arrival time of Zac1-misexpressing cells in the cortical plate was delayed (p<0.005; Figure 2.4H), and the overall distance migrated was reduced from 79.6±1.7 µm for control cells to 62.8±1.2 µm for

Zac1-transfected cells (p<0.005; Figure 2.4I,J). Zac1 overexpression also impacted migration velocity, with Zac1-transfected cells (43.9%) averaging a velocity of approximately 7.5±0.3

µm/hr, compared to control cells, which migrated on average at 9.3±0.3 µm/hr (p<0.005; Figure

2.4K,L).

Locomotion is a saltatory, discontinuous process whereby neurons undergo periods of active movement interspersed by pauses [93, 318]. Zac1 misexpressing cells paused more often (25.0% of cells paused two or more times) during migration when compared to the migratory progress of control cells (12.3% paused two or more times) (p<0.005; Figure 2.4M,N), and the length of their pauses was longer compared to control transfected cells (p<0.01; Figure 2.4O,P). The motility index, defined as the migration capacity of each cell without considering pauses, was also reduced in Zac1-misexpressing cells (Zac1: 11.1±0.3 µm/hr versus pCIG2: 11.9±0.2 µm/hr).

Taken together, these data indicate that Zac1 overexpression in neocortical progenitors reduces migratory velocity and increases pause time and frequency.

2.5.5. Zac1-overexpressing neurons exhibit aberrant morphologies

Cortical neurons undergo a series of morphological transitions as they differentiate and migrate, the perturbation of which can block radial migration. To examine whether Zac1 misexpression influenced the morphology of migrating neurons, we used spectral confocal microscopy to image transfected neurons following E14.5→E18.5 electroporations of pCIG2 and

Zac1 (Figure 2.5A-I). Cortical neurons born at E14.5 use glial-guided locomotion to migrate, with their leading process contacting RGCs, which serve as glial guides. As differentiating neurons exit the germinal zone, they initially stall in the upper SVZ and IZ, where they acquire a transient multipolar morphology that is associated with the dynamic extension and retraction of neurites

[24, 101]. This is followed by the acquisition of a motile, bipolar morphology, with neurons extending a leading process towards the pial surface and a smaller lagging process oriented towards the ventricle [24, 93]. As the waiting or pause period was increased after Zac1 misexpression, we questioned whether the multipolar to bipolar transition was disrupted. We first traced 82 pCIG2-transfected and 137 Zac1-transfected Tuj1+ neurons in the IZ (n=3). In both pCIG2 and Zac1 electroporations, many Tuj1+ neurons in the IZ had a multipolar phenotype

(34.4±6.7% for pCIG2 and 36.4±5.5% for Zac1), but the vast majority of neurons had transited to typical uni- or bi-polar neuronal morphologies (65.6±6.7% for pCIG2 and 53.6±4.6% for Zac1), with processes extending toward the apical (ventricular) and basal (pial) surfaces (Figure

2.5A,A',E,F). However, while most pCIG2-transfected neurons extended neurites (99.8±0.2%),

10.4±2.6% of Zac1 overexpressing neurons in the IZ lacked any detectable processes, instead acquiring an amorphous cell shape (p<0.01; Figure 2.5B,B',G). Zac1 overexpression thus perturbs the ability of cortical neurons to extend processes in the IZ (Figure 2.5G).

Once locomoting neurons reach their destination in the CP, their leading process extends multiple branches that attach to the pial surface, providing traction for the rapid pulling of neurons into their final laminar position in a process known as somal translocation [93]. To determine whether Zac1 misexpression perturbed these late morphological changes, we examined the morphology of neurons in upper layer II/III of the CP, tracing 101 pCIG2-transfected and 121

Zac1-transfected Tuj1+ neurons. In E14.5→E18.5 pCIG2 control electroporations, almost all

(98.9%) of the GFP+Tuj1+ neurons had two or more secondary branches extending out of the leading process (Figure 2.5C,C',H,I). In contrast, when Zac1 was overexpressed, only 44.9% of

GFP+Tuj1+ neurons elaborated branches in the CP (Figure 2.5D,D',H,I). Zac1 overexpression thus prevents neurite branching, most notably in the CP, likely interfering with the final somal translocation of migrating neurons.

Concomitant with the dynamic changes in neurite branching patterns, intracellular organelles also undergo active movements in migrating neurons. The centrosome, which is located basal to the nucleus in a migrating neuron, first translocates into a swelling within the leading process, followed by the endoplasmic reticulum (ER). The centrosome then pulls the nuclear cage upward and the saltatory migratory movements are repeated (Figure 2.5J). To examine whether organelle movements were disrupted upon Zac1 misexpression, we labelled the centrosome and ER by co- electroporating RFP-CENT2 [319] and pEF/Myc/ER/mCherry [112], respectively. In control pCIG2-transfected neurons, the centrosome (Figure 2.5K,K') and ER membranes (Figure

2.5M,M') were located on the basal side of the nucleus, and were clearly in the process of translocating into the leading process. In contrast, in Zac1-overexpressing neurons, especially those with an amorphous shape, the centrosome (Figure 2.5L,L') and ER membranes (Figure

2.5N,N') remained on the apical side of the nucleus. These data suggest that organelle movements

are perturbed in neurons that overexpress Zac1, likely contributing to the aberrant morphological transitions and migratory patterns of these neurons.

2.5.6. Neuronal migration is perturbed in Zac1 mutant neocortices

ZAC1 is a critical developmental gene in humans, as both the increase and decrease in ZAC1 expression in humans is associated with intellectual disability and smaller size for gestational age

(e.g., Decipher ID 248227, 251465) [305, 306]. Growth restriction is also observed in Zac1 mutant mice [157]. To determine whether the loss of Zac1 expression also influenced neocortical development, we examined Zac1 mutant mice. Zac1 is a maternally imprinted gene [209, 211].

Consequently, crosses between Zac1+/- males and wild-type C57BL/6 females yield Zac1+m/- heterozygotes with a silenced, maternal wild-type allele; these embryos are effectively null for

Zac1 and are hereafter designated as Zac1 mutants. We first examined Zac1 mutant neocortices at

E14.5 to determine whether proliferation and progenitor cell dynamics were altered. Following a

30 minute exposure to BrdU, similar numbers of progenitors were labeled in E14.5 Zac1 mutant and wild-type cortices (Figure 2.6A-D,I). In addition, there were no differences in the numbers of

Pax6+ RGCs (Figure 2.6A,B,E) and Tbr2+ INPs (Figure 2.6C,D,G) in E14.5 Zac1 mutants, nor in the numbers of progenitors that co-expressed Pax6/BrdU (Figure 2.6F) or Tbr2/BrdU (Figure

2.6H). To provide further support for the lack of an effect of the Zac1 mutation on progenitor cell maturation, we also analyzed progenitor populations at E15.5, 24 hr post-BrdU injection at E14.5.

The ratios of Pax6/BrdU (Figure 2.6J,K,N) and Tbr2/BrdU (Figure 2.6L,M,O) co-expression, as well as the total BrdU counts (Figure 2.6P), were not significantly different in E15.5 wild-type and

Zac1 mutants. Thus, the loss of Zac1 does not alter the transition of cortical progenitors from

Pax6+BrdU+ RGCs to Tbr2+Brdu+ INPs. Thus, while Zac1 is sufficient to block the RGC to INP transition and promote cell cycle exit, it is not required for these events.

We next examined whether the loss of Zac1 influenced neocortical neuronal migration. The majority of Zac1 mutant pups die within 24 hr after birth [157, 159], precluding us from examining mature laminar patterns in Zac1 mutants at postnatal day (P) 7, when migration is normally complete. Nevertheless, we were able to analyse the initial partitioning of neurons into upper- and deep-layers of the cortex at E18.5 by BrdU birthdating. BrdU was administered at E14.5, when upper-layer II-IV neurons are generated [43, 44]. The laminar positions of darkly-labelled nuclei, corresponding to neurons derived from progenitors that underwent their last round of cell division immediately after labelling, were assessed at E18.5 (Figure 2.7A-C). Cortical sections were subdivided into 13 ten µm bins, which were assigned to the VZ, IZ, deep- or upper- CP layers based on differences in the size and distribution of DAPI+ nuclei, and pairwise comparisons were made between wild-type and Zac1 mutants. In wild-type cortices, the majority of labelled neurons were found in bins in upper layers II-IV (Figure 2.7A-A'',C). In contrast, in Zac1 mutants, fewer darkly stained nuclei were present in the upper-most cortical layers (n=3; p<0.05; t-tests to compare bins; Figure 2.7B-B'',C). Instead, a subset of the post-mitotic cells labelled at E14.5 in

Zac1 mutants aberrantly accumulated in the upper GZ (n=3; p<0.05) and IZ (n=3; p<0.001; Figure

2.7B-B'',C). As progenitor cell maturation and neuronal differentiation were not notably different in Zac1 mutants, these data suggested that some neurons born at E14.5 fail to migrate into the upper CP in the absence of Zac1, instead aggregating in deep positions in the GZ/IZ.

To confirm that the aberrantly aggregating cells in Zac1 mutants were indeed neurons, we also examined the expression of layer-specific markers in E18.5 cortices. The total number of neurons expressing two upper-layer markers; Beta3 (Figure 2.7D-F), a basic-helix-loop-helix

transcription factor expressed in layers II-V [320] and Cux1 (Figure 2.7H-J), a Cut-like homeobox

1 transcription factor expressed in layers II-IV, were the same in E18.5 wild-type and Zac1 mutant cortices. However, the distribution of Beta3 (Figure 2.7G) and Cux1+ (Figure 2.7K) neurons was altered in E18.5 Zac1 mutants, with more of these neurons aberrantly aggregating in the GZ and

IZ (n=3; p<0.05 for both Beta3 and Cux1 using t-tests to compare bins; Figure 7G,K). Cux1 was also found to be ectopically located in the deep regions of Zac1 mutants (n=3; p<0.05; Figure

2.6K). In contrast, Ctip2 (Bcl11b), a layer V-specific transcription factor [86], was expressed in similar numbers of neurons and in a similar distribution throughout the cortical layers in both

E18.5 wild-type and Zac1 mutant cortices (Figure 2.7L-O).

Thus, a small subset of late-born Zac1 mutant neurons fail to migrate to their appropriate upper layers based on birthdating and laminar markers. Notably, these defects were overcome by

P4, when cell counts revealed no differences in the number or distribution of upper-layer neurons in the Zac1 mutants that survived (data not shown). There is thus a delay, rather than a block, in upper layer neuronal migration in Zac1 mutant neocortices.

2.5.7. Zac1 mutant neocortical neurons have aberrant morphologies

To further substantiate the requirement for Zac1 in regulating the migration of upper layer neurons, and to examine underlying causes, we performed two electroporation assays. First, we performed knock-down experiments. A highly efficient Zac1-shRNA construct (Zac1-sh(3); hereafter designated Zac1-shRNA) was identified by transfecting NIH-3T3 cells with 4-shRNA constructs carrying different Zac1 target sequences (Figure 2.8A). We then electroporated Zac1- shRNA or a scrambled shRNA control construct into E14.5 cortices and examined the distribution of electroporated cells at E18.5. Knock-down of Zac1 had a striking effect on cell migration, with

the vast majority of GFP+ electroporated cells failing to migrate out of the GZ (n=3; p<0.005) and not reaching the IZ (n=3; p<0.005) and upper layers (n=3; p<0.005) of the neocortex (Figure 2.8B-

D). To confirm that Zac1-shRNA did not have off-target effects, we repeated the E14.5→E18.5 electroporations of sh-scrambled and sh-Zac1 constructs in Zac1 mutant cortices; neither shRNA construct blocked neuronal migration in Zac1 mutants (Figure 2.8E,F), indicating that Zac1- shRNA-induced migration errors are not off-target effects or an electroporation artefact. To assess whether a subset of neurons failed to migrate in Zac1 mutant cortices, we used a second electroporation assay, introducing pCIG2 into E14.5 Zac1 mutants and wild-type littermates, and analysing the distribution of GFP+ cells at E18.5. In Zac1 mutants, significantly more GFP+ cells were found in deep cortical layers compared to wild-type controls (n=5 for Zac1 mutants and n=6 for wild type littermates; p<0.05; Figure 2.8G-I). There are thus subtle migratory defects in Zac1 genetic mutants.

Next, to study the underlying cause of the migration defects in Zac1 mutants in more detail, we examined the morphologies of pCIG2-transfected GFP+Tuj1+ neurons in the IZ and upper CP, comparing to littermate controls. Within the IZ, there were no differences in the number of

GFP+Tuj1+ multipolar neurons (Figure 2.8J,J',K,K',N) or neurite-bearing neurons (Figure

2.8L,L',M,M',O) in wild-type (n=86) and Zac1 mutant cortices (n=71). However, many fewer branches were seen in the pCIG2-transfected GFP+Tuj1+ neurons in Zac1 mutant (n=100; p<0.005;

Figure 2.8M,M'',P) versus wild-type embryos (n=82; Figure 2.8L,L'',P) in the cortical plate.

Combined, these data suggest that neuronal migration is perturbed when Zac1 is knocked down and to a lesser extent when it is knocked out. However, there was a similar reduction in the branching of upper layer neurons in both genetic null mice and in transient knock-down experiments, suggesting that Zac1 is absolutely required for this branching process, with no

compensatory mechanisms in place. Given that similar branching defects were observed whether

Zac1 was over- or under-expressed, we can conclude that Zac1 is a dosage sensitive gene, similar to other imprinted genes.

2.5.7. Zac1 regulates neuronal migration via Pac1

As Zac1 functions as a transcriptional activator or repressor [219, 224], its effects on neuronal migration are likely mediated by downstream effectors. Several Zac1 transcriptional targets have been identified, including Pac1 [233, 311], which encodes a receptor for the neuropeptide PACAP. We focused on Pac1 as a potential downstream effector of Zac1 as Pac1 is expressed at high levels in the neocortical VZ, and to a lesser extent in the cortical plate [235, 236], similar to the Zac1 expression profile (Figure 2.1A-F). Moreover, PACAP promotes cell cycle exit in cortical progenitors after E13.5 [235], mimicking the effects we observed upon Zac1- overexpression, although the authors did not examine whether Pac1 also influenced neuronal migration.

To determine whether Pac1 may be a downstream Zac1 effector in the developing neocortex, we first asked whether Zac1 regulated Pac1 expression levels in this region of the neural tube.

Pac1 transcript levels were quantitated by qPCR in E18.5 microdissected wild-type (n=4) and

Zac1 mutant (n=4) neocortices, revealing a 1.2-fold decrease in Zac1 mutants relative to wild-type

(Figure 2.9A,B). Next, to test whether Zac1 was sufficient to induce Pac1 expression in neocortical cells, pCIG2 control (n=6) and pCIG2-Zac1 (n=6) expression vectors were electroporated into

E13.5 cortices and GFP+ electroporated patches in the dorsal telencephalon were micro-dissected

24 hr later (Figure 2.9C,D). Zac1 was upregulated 4.2-fold in Zac1-transfected cortical cells compared to control transfections, resulting in a 3.3-fold increase in Pac1 transcript levels (Figure

2.9D). Zac1 is thus required and sufficient to regulate Pac1 transcript levels in neocortical progenitors.

If Zac1 acts via Pac1 to regulate neuronal migration, we predicted that we would obtain the same perturbation of neuronal migration when Pac1 was either over-expressed or knocked down.

To test this hypothesis, we first electroporated pCIG2 control and pCIG2-Pac1 expression vectors into E14.5 neocortices and harvested the embryos at E18.5 (Figure 2.9E,F). In control electroporations, most GFP+ cells had migrated to upper regions of the CP (Figure 2.9E,G), whereas misexpression of Pac1 led to the accumulation of more GFP+ cells in the IZ (n=3; p<0.01) and fewer cells reached upper layers of the CP (n=3; p<0.005; Figure 2.9F,G). Pac1 misexpression therefore phenocopies the migration defects observed when Zac1 is misexpressed in E14.5 cortical progenitors (Figure 2.1J-L). Next, to investigate whether Pac1 loss-of-function phenocopied Zac1 loss-of-function, we knocked Pac1 down using shRNA, targeting E14.5 cortical progenitors and examining the positions of electroporated cells at E18.5. Relative to control electroporations

(Figure 2.9H,J), more GFP+ cells electroporated with shPac1 were ectopically located in the IZ

(n=3; p<0.005) and fewer GFP+ cells reached upper layers of the CP (n=3; p<0.005; Figure 2.9I,J).

Both the loss and gain of Pac1 function thus perturbs neuronal migration, similar to the phenotypes observed when Zac1 levels are manipulated.

As a final comparative measure of Zac1 and Pac1 functions, we examined the morphologies of cortical neurons following the overexpression or knockdown of Pac1. Similar to Zac1, overexpression of Pac1 increased the number of GFP+Tuj1+ neurons that lacked neurites, with

9.6% of Pac1-transfected neurons acquiring an amorphous shape in the IZ (n=93; p<0.005; Figure

2.9K,K',L,L',P). Also similar to Zac1, Pac1 did not affect the multipolar to unipolar/bipolar ratio of the neurons that did extend neurites (Figure 2.9O,Q). However, of the few GFP+Tuj1+ neurons

that did reach the CP after Pac1 overexpression, there was a reduction in the average number of neurite branches that were extended (n=23; p<0.005; Figure 2.9R), similar to the Zac1 gain-of- function phenotype. Conversely, when Pac1 was knocked down by electroporating shPac1 into

E14.5 cortical progenitors (Figure 2.9S-V), more GFP+Tuj1+ neurons acquired a multipolar shape compared to control transfections (n=87 for shPac1 vs n=63 for sh-scrambled; p<0.05; Figure

2.9U), whereas fewer were bipolar (p<0.05; Figure 2.9V). Pac1 is thus required for the multipolar to bipolar transition of locomoting neurons (Figure 2.9U,V).

Taken together, these data indicate that Pac1 transcription is regulated by Zac1 in the neocortex, and suggest that Pac1 is necessary and sufficient downstream of Zac1 to control the migratory behaviour and morphologies of neocortical neurons.

2.5.8. Pac1 partially rescues migration defects associated with Zac1 knock-down

To provide additional support for the idea that Pac1 is a downstream effector of Zac1 in the developing neocortex, we performed rescue experiments. For this purpose, we first conducted

E14.5→E18.5 electroporations of pCIG2, pCIG2-Zac1, pCIG2-Pac1, sh-scrambled, shZac1, and shPac1 constructs, confirming that the gain or loss of both Zac1 and Pac1 perturbed migration

(Figure 2.10B-G), and providing a comparative baseline for co-electroporation experiments. To provide a single measure of migration that could be compared between single and double electroporations, we calculated a migration index, dividing the cortex into 7 bins of equal size, with the top-most bin, where cells had migrated the furthest, given a value of 7, and the lowest- bin, where cells had migrated the least, assigned a value of 1 (Figure 2.10A). The percentage of

GFP+ cells within each bin was then multiplied by the assigned bin value, and all numbers were added together. Using this strategy, the migration indices of pCIG2 (n=4) and scrambled shRNA

(n=3) control transfections were 4.3±0.2% and 5.0±0.1%, respectively (Figure 2.10 B,E,J). In contrast, migration indices for pCIG2-Zac1 (3.3±1.5; n=3; p<0.001) and pCIG2-Pac1 (3.4±0.1%; n=3; p<0.01; Figure 2.10C,D,J ) were considerably lower than for pCIG2, while shPac1

(2.8±0.1%; n=4; p<0.001) and shZac1 (2.7±0.1%; n=3; p<0.001; Figure 2.10F,G,J) were considerably lower than the scrambled shRNA control, as expected. We were thus able to use this migration index to compare the migratory effects of several constructs at once.

To determine whether Pac1 was an essential Zac1 effector, we first asked whether Zac1 perturbed neuronal migration when Pac1 was knocked down. The migration index for pCIG2-

Zac1+shPac1 was 2.6±0.1% (n=6; Figure 2.10H,J), even lower than that observed for the gain-of- function of Zac1 (p<0.01). Thus, Zac1 gain-of-function perturbs radial migration even when Pac1 is knocked down, suggesting that Zac1 must control the expression of other migratory factors in addition to Pac1. We next asked the converse question; whether Zac1 is required to initiate Pac1 expression for normal migration to occur. Indeed, by knocking down Zac1 and adding back Pac1, a rescue of neuronal migration defects was observed, with a resulting migration index of 4.2±0.1% that was not significantly different than values observed in control electroporations (n=3; p>0.05;

Figure 2.10I,J). Given that the Zac1 knock-down no longer perturbs migration when Pac1 is overexpressed, we suggest that Pac1 is indeed a critical downstream effector of Zac1. Taken together, these data support the notion that Zac1 modulates neuronal migration at least in part by regulating the expression of Pac1, although other downstream effectors are also likely involved.

2.6. DISCUSSION

Zac1 is a maternally-imprinted, dosage-sensitive gene, and an increase or decrease in its expression is associated with developmental growth restriction and intellectual deficits in humans.

We therefore investigated whether alterations in Zac1 expression in the developing murine neocortex, which is the seat of higher order cognitive functioning, would influence brain development. Striking defects in progenitor cell maturation, neuronal differentiation, neuronal morphology and neuronal migration were observed upon over-expression of Zac1 in neocortical progenitors. Defects in neuronal migration were also observed in Zac1 loss-of-function models, albeit to a lesser extent. Mechanistically, we attribute Zac1’s ability to control neocortical neuronal migration to its regulation of Pac1, a receptor for the neuropeptide PACAP that is known to regulate neocortical progenitor proliferation [235]. We have thus uncovered a novel Zac1-Pac1 regulatory circuit that plays an essential role in regulating progenitor proliferation, neuronal differentiation and migration in the developing neocortex. Many of our conclusions are based on gain-of-function experiments, which can in some instances induce experimental artifacts.

However, Zac1 misexpression upregulates Pac1 expression, a known Zac1 transcriptional target, and Zac1 and Pac1 have similar gain-of-function phenotypes, thus supporting the specificity of our gain-of-function data. Moreover, as our goal was to mimic the increase in Zac1 expression observed in human TNDM, it was necessary to use a gain of function approach.

2.6.1. Zac1 and the regulation of cortical progenitor cell proliferation

We found that Zac1 misexpression reduces EdU incorporation in the neocortex, and that fewer Zac1-overexpressing cells re-enter S-phase of the cell cycle. This is similar to our findings in the embryonic retina, where Zac1 misexpression also reduced S-phase progenitors [159]. Zac1 similarly induces cell cycle arrest in epithelial cell lines, while conversely, Zac1 expression is lost in several carcinomas that display an increased proliferative potential [1]. It is currently unknown how Zac1 regulates cell cycle exit, either in the developing CNS or in tumorigenic cells, but it is

thought to function independently of Kip-family cyclin dependent kinase inhibitors and

Retinoblastoma [315]. We found that Zac1 promotes Pac1 expression in cortical progenitors, while Pac1 transcript levels were also reduced in Zac1 mutant cortices, although to a lesser extent.

PACAP has anti-proliferative properties in the developing neocortex, reducing the number of progenitors entering S-phase of the cell cycle at E13.5 and later [235]. The ability of Zac1 to reduce proliferation is therefore likely related to its ability to increase Pac1 transcription. A similar model was proposed based on analyses of Suz12 null cortices, which also display a reduction in cortical proliferation [321]. Suz12 encodes a component of a polycomb repressive complex 2 that regulates the expression of imprinted genes, such as Zac1. Accordingly, Zac1 expression levels are upregulated in Suz12 mutant cortices, as are the expression levels of Pac1 [321]. Zac1 in turn has been shown to regulate the expression of a number of imprinted genes, including Igf2, Dlk1 and

H19, all of which are associated with growth control and proliferation [157]. Future studies will be required to see if these genes are also regulated by Zac1 in the neocortex, accounting for the reduced proliferative capacity of Zac1-overexpressing cells. However, based on our studies, we can conclude that a Zac1-Pac1 transcriptional pathway is a key regulator of progenitor cell proliferation in the developing neocortex.

Although we found that Zac1 can promote cell cycle exit, it was recently shown that Zac1 can enhance the tumorigenicity of a glioma cell line, in contrast to its original identification as a tumor suppressor gene [322]. This is perhaps not unexpected given that members of several gene families, including the Runx transcription factors [323], Pten phosphatase [324, 325] and TGFβ signaling molecules [326], are lineage-specific oncogenes or tumor suppressors, depending on the time and tissue in which they are expressed. Zac1 function is thus clearly context-specific.

2.6.2. Zac1 blocks progenitor cell maturation and neuronal differentiation

We found that Zac1 misexpression blocks the apical to basal transition of neocortical progenitors, leading to the sustained expression of Pax6 and a reduction in Tbr2 expression. Furthermore, neuronal differentiation was delayed, but not completely blocked, by the overexpression of Zac1 in neocortical progenitors. The ability of Zac1 to block neocortical cells as early apical progenitors is consistent with a recent study in a glioma cell line, where Zac1 promoted the expression of nestin, a marker of apical radial glia, and blocked neuronal differentiation [322]. However, it is not clear whether Zac1 is a direct transcriptional regulator of apical progenitor genes, such as

Nestin or Pax6, or whether it alters the expression of other genes that block progenitor cell maturation and neuronal differentiation (e.g., Pac1). Interestingly, Zac1 and Pax6 expression have very similar expression domains in the embryonic telencephalon, consistent with a potential regulatory interaction [158]. Interestingly, Pax6 expression was reduced in the embryonic pancreas of a transgenic mouse engineered to overexpress a locus associated with TNDM, which included

ZAC1 [327], suggesting a repressive interaction between Zac1 and Pax6. Indeed, Zac1 is known to function both as a transcriptional activator and repressor [224, 328]. Further studies are required to explore potential regulatory interactions between Zac1 and Pax6.

2.6.3. Zac1 regulates neocortical neuronal migration via Pac1

We found that Zac1 misexpression at E12.5 did not perturb neuronal migration, whereas misexpression of Zac1 at E14.5 prevented neurons from migrating out of the GZ and IZ and into the CP. Other studies have identified two temporal phases of neuronal migration; an early-period of somal translocation that occurs before E14.5 and a later period of glial-guided locomotion that primarily occurs after E14.5 [93]. Based on the timing of its effects, Zac1 overexpression

influences the latter period of locomotion. Indeed, several of the changes that locomoting neurons undergo were perturbed when Zac1 was overexpressed, including an increase in the length and number of pauses, and reduced neuronal branching in the IZ, where a multipolar shape is associated with the waiting period. Zac1 overexpressing neurons also displayed decreased branching patterns in the upper cortical plate, where the final movement of neurons into their laminar position depends on somal translocation, with the force required for movement generated by the branching of the primary dendrites and their attachment to the pial surface.

Analyses of Zac1 mutant cortices also revealed defects in neocortical neuronal migration, albeit less severe than in our gain-of-function models. Consistent with this observation, we previously identified a role for Zac1 in mediating neuronal migration in the developing retina

[159]. In addition, in the Zac1 mutant cerebellum, fewer neurons are found in medial cerebellar nuclei, and fewer Golgi cells populate cerebellar lobule IX, possibly also reflecting a neuronal migration defect [247]. Consistent with the idea that Zac1 may mediate its effects on neuronal migration through Pac1 signaling, PACAP reduces the rate of granule cell migration in culture

[329]. Taken together, our data suggest that neuronal migration may be regulated by different signaling pathways early and late in corticogenesis.

Several Zac1 transcriptional targets have been identified, including Tcf4 [238], Pparg1

[330], Cdkn1a [331], Rasgfr1 [332], Glut4 [308], and Pac1 [233, 311]. We focused on Pac1 as a potential downstream effector of Zac1 for several reasons. Firstly, the over-expression of Pac1 signaling molecules in humans has been associated with developmental brain disorders [329].

Secondly, previous time lapse video microscopy studies have shown that PACAP1-38, a Pac1 agonist, delays the migration of cerebellar granule cells [329]. In contrast, PACAP6-38, a Pac1 antagonist, has no effect [329], and the overall laminar organization of the cerebellum is normal

in PACAP mutant mice, indicating that this neuropeptide is sufficient, but not required to regulate the migration of cerebellar granule cells [333]. In contrast, in this study we observe neuronal migration defects following Pac1 gain- and loss-of-function in the neocortex, suggesting that precise levels of signalling through this receptor is required for normal migration of neocortical neurons. Notably, Pac1 perturbations phenocopied those observed when Zac1 expression was altered, and misepxression of Pac1 could rescue the Zac1 knock-down migratory phenotype, suggesting that these genes act in the same genetic pathway. Conversely, when Zac1 was overexpressed and Pac1 was knocked down, migratory defects were not rescued, suggesting that

Zac1 induces the expression of other downstream genes that perturb migration. Future experiments will be required to identify the exact nature of these genes and the underlying regulatory interactions.

Taken together, these data increase our understanding of the pathways that regulate the morphogenetic changes associated with neuronal differentiation and migration in the neocortex.

2.7. FIGURE LEGENDS

Figure 2.1. Zac1 overexpression perturbs cell migration during later stages of corticogenesis

(A,B) Zac1 transcript distribution in E12.5 (A,A') and E15.5 (B,B') telencephalon. A' and B' are high magnification images of A and B, respectively. (C-F) Distribution of Zac1 (red, C-F'') and

Tuj1 (green, C-D) protein in the E12.5 (C,C'), E14.5 (D,D'), E16.5 (E-E'') and E18.5 (F-F'') neocortex. C'-F' are higher magnification images of C–F, respectively. Arrowheads in E and F mark CP expression. Comparison of E12.5→E18.5 (G-I) and E14.5→E18.5 (J-L) electroporations of pCIG2 control (G,J) and pCIG2-Zac1 (H,K) analyzed for the distribution of GFP+ cells/zone

(I,L). DL, deep layer; iz, intermediate zone; LGE, lateral ganglionic eminence; MGE, medial ganglionic eminence; Ncx, neocortex; PP, preplate; UL, upper layer; SVZ, subventricular zone;

VZ, ventricular zone, GZ, germinal zone.

Figure 2.2. Zac1 overexpression delays progenitor cell maturation and neuronal differentiation. (A) Schematic illustration of cells transitioning from Pax6+ RGCs to Tbr2+ INPs to Tbr1+ differentiated neurons. (B-S) E14.5→E15.5 electroporations of pCIG2 control

(B,E,H,K,N,Q) and pCIG2-Zac1 (C,F,I,L,O,R) co-stained for GFP and pHH3 (E,E',F,F'), GFP and

Pax6 (H,H',I,I'), GFP and Tbr2 (K,K',L,L'), GFP and Tbr1 (N,N',O,O') and GFP and EdU

(Q,Q',R,R'). E',F',H',I',K',L',N',O',R',Q' are high magnification images of boxed regions in

E,F,H,I,K,L,N,O,R,Q, respectively. Arrowheads in E',F',H',I',K',L',Q' mark double positive cells.

Quantitation of GFP+ cells/zone (D), %pHH3+GFP+ mitotic cells in apical and basal regions of the cortex (G), %Pax6+GFP+/GFP+ cells (J), %Tbr2+GFP+/GFP+ cells (M), %Tbr1+GFP+/GFP+ cells

(P), and %EdU+ GFP+/GFP+ cells (S) following the electroporation of pCIG2 (white bars, n=3) and pCIG2-Zac1 (blue bars, n=3). (T-V) E14.5→E15.5 electroporations of pCIG2 control (T) and pCIG2-Zac1 (U) co-stained for GFP (green), Ki67 (blue) and BrdU (red) after a 24 hr BrdU pulse.

Quantitation of %Ki67+BrdU+GFP+/GFP+BrdU+ cells (V). Arrowheads in T,U point to BrdU+ proliferating cells that have been electroporated (GFP+) and have remained in the cell cycle

(Ki67+). DAPI labeling is in blue for B-R'. IZ, intermediate zone; SVZ, subventricular zone; VZ, ventricular zone; CP, cortical plate.

Figure 2.3. Zac1 overexpression blocks neuronal differentiation. (A-P) E14.5→E18.5 electroporations of pCIG2 control (A,E,I,M) and pCIG2-Zac1 (B,F,J,N) analyzed for the expression of GFP and NeuN (A,B), GFP and Ctip2 (E,F), GFP and Cux1 (I,J), and GFP and Beta3

(M,N). Insets to the right are high magnification images of boxed regions in the IZ and CP in

A,B,E,F,I,J,M,N, and arrowheads mark double positive cells. Quantitation of %NeuN+GFP+/GFP+ cells in total (C) and per zone (D), Ctip2+ GFP+/GFP+ cells in total (G) and per zone (H), Cux1+

GFP+/GFP+ cells in total (K) and per zone (L), and Beta3+ GFP+/GFP+ cells in total (O) and per zone (P) following the electroporation of pCIG2 (white bars, n=3) and pCIG2-Zac1 (blue bars, n=3). IZ, intermediate zone; GZ, germinal zone; CP, cortical plate; DL, deep layer; UL, upper layer.

Figure 2.4. Altered migratory properties of Zac1 over-expressing cortical cells. (A-P)

Biphoton time-lapse microscopy of E15.5 cortical slice cultures electroporated with pCIG2 and pCIG2-Zac1. (A,B) Photomicrographs of GFP+ cells imaged 30 hr post-electroporation of pCIG2

(A) and pCIG2-Zac1 (B). (C-E) Measurement of departure time defined as hrs post-transfection when GFP+ cells left the GZ and entered the IZ (C). Departure times for 195 pCIG2 (white bars) and 133 pCIG2-Zac1 (blue bars) transfected cells were recorded individually (D) and averaged

(E). (F-H) Measurement of arrival time defined as hrs post-transfection when GFP+ entered the cortical plate (F). Arrival times for 195 pCIG2 (white bars) and 133 pCIG2-Zac1 (blue bars) transfected cells were recorded individually (G) and averaged (H). (I,J) Measurement of total distance (m) migrated for 195 pCIG2- (white bars) and 133 pCIG2-Zac1- (blue bars) transfected cells recorded individually (I) and averaged (J). (K,L) Measurement of migration velocity (m/hr) migrated for 195 pCIG2- (white bars) and 133 pCIG2-Zac1- (blue bars) transfected cells recorded individually (K) and averaged (L). (M,N) Quantitation of pauses in migration defined as any movement < 3.5µm over two consecutive hours of recording for 195 pCIG2- (white bars) and 133 pCIG2-Zac1 (blue bars) individual transfected cells (M) and averaged (N). (O,P) Quantitation of pause duration in hours for 195 pCIG2- (white bars) and 133 pCIG2-Zac1- (blue bars) individual transfected cells (O) and averaged (P). CP, cortical plate; GZ, germinal zone; hr, hours; IZ, intermediate zone.

Figure 2.5. Zac1 over-expression alters the morphology of migrating neurons. (A-D)

E14.5→E18.5 electroporations of pCIG2 (A,C; white bars) and pCIG2-Zac1 (B,D; blue bars).

GFP+Tuj1+ neurons (A-D) were traced (A'-D') in the IZ (A',B') and CP (C',D') from pCIG2 (n=82 in IZ; n=101 in CP) and pCIG2-Zac1 (n=137 in IZ; n=121 in CP) electroporations. (E-I)

Quantitation of % multipolar neurons in the IZ (E), % uni-/bipolar neurons in the IZ (F), % neurons with neurites in the IZ (G), number of branches per neuron in the CP (H) and average number of branches in the CP (I). (J) Schematic illustration of glial guided locomotion; saltatory movements begin with the centrosome, which is in front of the nucleus, and sends out microtubules to form a fork/cage around the nucleus (i). The leading process of the migrating neuron dilates and the centrosome enters (ii). Other organelles such as the Golgi apparatus and endoplasmic reticulum enter the dilated leading process (iii). Finally, microtubules attached to centrosome pull the nucleus into the dilation (iv). (K-N) E14.5→E18.5 co-electroporations of pCIG2 (K,K',M,M') or pCIG2-

Zac1 (L,L',N,N') with RFP-CENT2 (K,K',L,L') or pEF/Myc/ER/mCherry (M,M',N,N'). GFP+ cells were traced in K'-N' to highlight the position of the organelles within the transfected cells. IZ, intermediate zone; CP, cortical plate; ns, not significant; ER, endoplasmic reticulum.

Figure 2.6. Loss of Zac1 does not alter progenitor cell dynamics. (A-I) Analysis of Pax6/BrdU

(A,B) and Tbr2/Brdu (C,D) co-expression in E14.5 wild-type and Zac1 mutant (B) cortices after a

30 min BrdU pulse. DAPI labelling is blue counterstain. Quantitation of total number of Pax6+ cells (E), %Pax6+BrdU+/BrdU+ cells (F), total number of Tbr2+ cells (G), %Tbr2+BrdU+/BrdU+ cells (H) and total BrdU+ cells (I) in wild-type (n=3; white bars) and Zac1 mutants (n=3; blue bars). (J-P) Analysis of Pax6/BrdU (J,K) and Tbr2/Brdu (L,M) co-expression in E15.5 wild-type

(L) and Zac1 mutant (M) cortices after a 24 hr BrdU pulse. DAPI labelling is blue counterstain.

Quantitation of the %Pax6+BrdU+/BrdU+ cells (N), %Tbr2+BrdU+/BrdU+ cells (O) and total BrdU+ cells (P) in wild-type (n=3; white bars) and Zac1 mutants (n=3; blue bars).

Figure 2.7. Aberrant distribution of laminar markers in Zac1 mutant cortices. (A-C)

E14.5→E18.5 BrdU birthdating in wild-type (A-A'') and Zac1 mutant (B-B'') cortices. Distribution of BrdU-labeled cortical neurons divided into 13 bins corresponding to upper CP layers (bins 10-

13), deep CP layers (bins 5-9), IZ (bins 3-4) and GZ (bins 1-2) in wild-type (white bars; n=3) and

Zac1 mutant (blue bars; n=3) cortices (C). (D-N) E18.5 wild-type (D,D',H,H',L,L') and Zac1 mutant (E,E',I,I',M,M') cortices immunostained for Beta3 (D,D',E,E'), Cux1 (H,H',I,I') and Ctip2

(L,L',M,M'). DAPI-labeling is blue counterstain. Quantitation of %Beta3+/DAPI+ cells in total (F) and in each layer (G), %Cux1+/DAPI+ cells in total (J) and in each layer (K), and %Ctip2+/DAPI+ cells in total (N) and in each layer (O) for wild-type (n=3; white bars) and Zac1 mutants (n=3; blue bars). GZ, germinal zone; DL, deep layer; IZ, intermediate zone; UL, upper layer.

Figure 2.8. Aberrant morphology of migrating neurons in Zac1 mutant cortices. (A) Western blot analysis of Zac1 and β-actin protein levels in NIH-3T3 cells co-transfected with pCIG2-Zac1 along with different shRNA constructs. (B-D) E14.5→E18.5 electroporations of sh-scrambled control (B) and shZac1 vectors (C) in wild-type CD1 timed pregnant females. Quantitation of

%GFP+ cells/layer for sh-scrambled (n=3; white bars) and shZac1 (n=3; blue bars) (D). (E,F)

E14.5→E18.5 electroporations of Zac1 mutant cortices with sh-scrambled and sh-Zac1 constructs.

(G-I) E14.5→E18.5 electroporation of pCIG2 in wild-type (G) and Zac1 mutant (H) cortices.

Quantitation of %GFP+ cells in each layer for wild-type (n=3; white bars) and Zac1 mutant (n=3; blue bars) cortices (I). (J-P) E14.5→E18.5 electroporation of pCIG2 in wild-type (J,L) and Zac1 mutant (K,M) cortices, with images taken in the IZ (J,K) and CP (L,M). GFP+Tuj1+ neurons in wild-type IZ (J') and CP (L') and in Zac1+m/- IZ (K') and CP (M') were traced. Quantitation of % multipolar neurons in IZ of wild-type (n=86; white bars) and Zac1 mutant (n=71; blue bars) cortices (N). Quantitation of % neurons with neurites in the IZ of wild-type (n=86; white bars) and

Zac1 mutant (n=71; blue bars) cortices (O).Quantitation of the number of branches in the CP of wild-type (n=82; white bars) and Zac1 mutant (n=100; blue bars) cortices (P). GZ, germinal zone;

DL, deep layer; IZ, intermediate zone; UL, upper layer; CP, cortical plate.

Figure 2.9. Zac1 regulates neuronal migration by regulating Pac1 transcription in the developing neocortex. (A-D) Schematic of the experimental design to test whether Zac1 regulates the expression of Pac1 in E15.5 Zac1+m/- cortices (A) and in E13.5→E14.5 Zac1 gain-of-function assays (C). Quantitation of qPCR data, showing reduced Pac1 transcript levels in Zac1+m/- cortices

(n=4 for both wild-type, white bars and Zac1 mutant, blue bars; B) and increased Pac1 transcript levels after Zac1 misexpression (n=6 for both pCIG2, white bars and pCIG2-Zac1, blue bars; D).

(E-G) E14.5→E18.5 electroporations of pCIG2 (E) and pCIG2-Pac1 (F). Quantitation of % GFP+ cells in each layer for pCIG2 control (n=3; white bar) and pCIG2-Pac1 (n=3; blue bar) (G). (H-J)

E14.5→E18.5 electroporations of sh-scrambled (H) and shPac1 (I). Quantitation of % GFP+ cells in each layer for pCIG2 control (n=3; white bar) and shPac1 (n=3; blue bar) (J). (K-R)

E14.5→E18.5 electroporations of pCIG2 (K,M) and pCIG2-Pac1 (L,N), showing co- immunolabeling of GFP (green) and Tuj1 (red). Blue is DAPI counterstain. Tracing of GFP+Tuj1+ neurons in the IZ from pCIG2 control (n=82; K') and pCIG2-Pac1 (n=93; L') electroporations.

Quantitation of % multipolar cells (O), % cells with neurites (P) and % uni- or bipolar neurons (Q) for pCIG2 control (n=3; white bars) and pCIG2-Pac1 (n=3; blue bars). Tracing of GFP+Tuj1+ neurons in the CP from pCIG2 control (n=101; M') and pCIG2-Pac1 (n=23; N') electroporations.

Quantitation of average number of branches per neuron in the CP (R). (S-V) E14.5→E18.5 electroporations of sh-scrambled (S) and shPac1 (T), showing co-immunolabeling of GFP (green) and Tuj1 (red). Blue is DAPI counterstain. Tracing of GFP+Tuj1+ neurons in the IZ from pCIG2 control (n=82; S') and shPac1 (n=87; T'). Quantitation of % multipolar neurons (U) and % uni- or bipolar neurons (V) for sh-scrambled (n=3; white bars) and shZac1 (n=3; blue bars). GZ, germinal zone; DL, deep layer; IZ, intermediate zone; UL, upper layer; CP, cortical plate.

Figure 2.10. Zac1 regulates neuronal migration via Pac1 in the developing neocortex. (A)

Schematic representation of method used to calculate migration index. (B-F) E14.5→E18.5 electroporations of pCIG2 (B), pCIG2-Zac1 (C), pCIG2-Pac1 (D), sh-scrambled (E), shZac1 (F), shPac1 (G), pCIG2-Zac1+shPac1 (H) and shZac1+pCIG2-Pac1 (I). (J) Quantitation of migration indices for all electroporations. (K) Summary of regulatory interactions between Zac1 and Pac1.

Zac1 gain-of-function perturbs radial migration even when Pac1 is knocked down, suggesting that

Zac1 controls the expression of other migratory factors. Zac1 knock-down no longer perturbs migration when Pac1 is over-expressed, suggesting that Pac1 is the most critical regulator of migration downstream of Zac1. (L) Summary of Zac1’s role in guiding neuronal migration in the developing neocortex. At the end of glial guided locomotion (steps i-iv), neurons detach from the radial glial scaffold and the leading process extends multiple branches that arborize to the pial surface (step v in pCIG2 control). In neurons in which Zac1 expression is deregulated, branching of the leading process does not occur at the end of terminal translocation (step v; + or – Zac1). GZ, germinal zone; DL, deep layer; IZ, intermediate zone; UL, upper layer.

CHAPTER 3: Plag1 and Plagl2 have overlapping and distinct functions in telencephalic development

Lata Adnani, Rajiv Dixit, Xingyu Chen, Anjali Balakrishnan, Cairine Logan, Carol Schuurmans

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3.1 ABSTRACT

The Plag gene family contains three genes; Plagl1/Zac1, which functions as a tumour suppressor gene, and Plag1 and Plagl2, which are oncogenes. All three genes are known to be expressed in embryonic neural progenitor cells, and Plagl1/Zac1 was shown to regulate progenitor proliferation, differentiation and migration in the neocortex. Here we examined the functions of

Plag1 and Plagl2 in the embryonic telencephalon. To test whether Plag1 and/or Plagl2 play essential and/or redundant roles, we first attempted but were unable to generate E12.5

Plag1;Plagl2 double mutant embryos, indicating that at least one Plag1 or Plagl2 gene copy is required for embryonic survival. We therefore focused on E12.5 Plag1 and Plagl2 single mutants, revealing complementary patterning defects, with Plag1 required to set the dorsal boundary of ventral telencephalic gene expression, and Plagl2 required to set the ventral border of dorsal telencephalic gene expression. Complementary functions were also observed with respect to proliferation, with Plag1 required to maintain the proliferation of neocortical progenitors, while

Plagl2 is sufficient to promote proliferation. Taken together these studies indicate that the Plag genes are essential regulators of CNS development, and demonstrate that while Plag1 and Plagl2 functions are similar, they do not entirely overlap.

3.2 SUMMARY STATEMENT

Plag1 and Plagl2 are proto-oncogenes that have been studied extensively in cancer. Here we provide the first report of a role for these genes in the developing central nervous system.

3.3 INTRODUCTION

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The Pleomorphic adenoma gene (Plag) family includes three genes: Plag-like 1 (Plagl1; also known as Zac1), Plag1, and Plagl2. Plag genes encode C2H2 Zn-finger transcription factors that are key regulators of tumorigenesis [1, 241]. Zac1 was initially identified as a gene lost on transformation (Lot1) in a spontaneously transformed cell line [243]. Human ZAC1 was subsequently found to be located on 6q24-25, a locus silenced in multiple carcinomas, including head and neck, ovarian, breast, kidney, and pituitary tumors [164, 166-171, 179, 196, 198, 219,

242, 243, 334]. Consistent with a role as a tumor suppressor gene, Zac1 promotes cell cycle exit and apoptosis in vitro in various cell lines [172, 219, 315, 335] as well as in vivo in the developing nervous system [159, 239, 336].

In contrast to Zac1, Plag1 and Plagl2 function as proto-oncogenes [161]. Plag1 has been shown to be amplified in pleiomorphic adenomas of the salivary gland [180, 181, 183-187], lipoblastomas [188-192], hepatoblastomas [193] and some leukemias [194, 195]. The misexpression of Plag1 in these cancers is due to chromosomal translocations that place Plag1 under the control of regulatory elements for ubiquitously expressed genes, such as elongation factor SII gene [196], Ctnnb1 (β-catenin) [197] and leukemia inhibitory factor receptor [198].

Plagl2 is similarly amplified in a number of cancers, including glioblastomas [199] and acute myeloid leukemia [194]. Consistent with their roles as oncogenes, Plag1 and Plagl2 promote proliferation, anchorage-independent growth, loss of contact inhibition and tumor formation in mice [161, 194, 199, 201-203, 337]. However, Plagl2 is not oncogenic in all contexts as it is pro- apoptotic in response to hypoxia and other cellular stresses [204-207, 338].

All three members of the Plag gene family encode zinc finger transcription factors that share homology chiefly in their amino terminal zinc (Zn) finger domains, whereas the carboxyl terminal regions of the three proteins are quite diverse [218]. Several transcriptional targets of the

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Plag family transcription factors have been identified. For example, Plag1 and Plagl2 are known to regulate the expression of Insulin-like Growth Factor 2 (Igf2), which accounts at least in part for their abilities to stimulate cell proliferation [162, 219, 226, 227]. In addition, Plag1/Plagl2 promote tumorigenesis by initiating the transcription of several Wnt pathway genes. For instance,

Plagl2 has been shown to regulate expression of Wnt6, Fzd2 and Fzd9 to maintain cells in a proliferative state [199]. Likewise, Plag1 misexpression in pleiomorphic adenomas results in an upregulation of canonical Wnt signaling [203, 227]. Finally, Plag1 was also found to regulate several cell division and cell cycle-related genes, such as cyclin D3 and cyclinD1, as well as apoptosis-related genes, such as caspase-8 [231].

Despite extensive knowledge of Plag gene function in cancer, their roles during normal development have only recently been examined. Zac1, Plag1 and Plagl2 all function to regulate embryonic growth [157, 240, 241]. Zac1 also controls development of keratinocytes [307], heart

[225, 308] and pancreatic islets [309], while Plagl2 functions to control the development of enterocytes [241]. All three Plag genes are known to be expressed in several lineages in the developing embryo as well as in some adult tissues [158, 233, 240, 241]. While each of the Plag genes has a unique expression profile, the three genes are co-expressed in certain lineages/tissues

[158, 233]. For example, Zac1 is expressed in a regionalized fashion in neural progenitor cells in the developing central (CNS) and peripheral (PNS) nervous systems, whereas Plag1 and Plagl2 are more uniformly expressed in CNS and PNS neural progenitors [1, 158, 184, 242]. Interestingly, all three Plag genes are co-expressed at higher levels in neural progenitors than in post-mitotic neurons [158, 233].

Plag1 null mice (Plag1KI/KI), although viable, are growth retarded and have reduced fertility [240]. However, despite their growth defects and the known ability of Plag1 to regulate

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expression of the Igf2 growth factor [162], Igf2 expression levels were found to be unperturbed in

Plag1 null mice [240]. Thus, the underlying molecular mechanisms that lead to growth perturbation in Plag1 null embryos remains unknown. Likewise, Plagl2KI/KI neonates also weigh less relative to their littermates at birth [241]. However, unlike Plag1KI/KI mutants, Plagl2KI/KI pups display postnatal lethality, dying shortly after birth due to starvation and nutrient malabsorption

[241]. In the neonatal Plagl2KI/KI liver, the starvation response factor asparagine synthetase (AS) is expressed at high levels [241], whereas Igf1 levels are low, indicative of a loss of nutrients.

In the CNS, multiple developmental roles for Zac1 have been deciphered, including in the retina, cerebellum and neocortex [159, 239, 246, 247, 336]. However, to date, neither Plag1 nor

Plagl2 have any known functions in the developing CNS. Here, given their overlapping expression with Zac1, we asked whether Plag1 and Plagl2, also function during neocortical development and reveal novel complementary roles for these genes in both telencephalic patterning and in regulating neocortical progenitor cell proliferation.

3.4 MATERIALS AND METHODS

3.4.1. Animals. The use of animals was vetted and approved by the University of Calgary and then the Sunnybrook Research Institute Animal Care Committees in agreement with the Guidelines of the Canadian Council of Animal Care (CCAC). The generation of Plag1lacZKI [240] and

Plagl2lacZKI [241] mice was previously reported, and we maintained these alleles on a CD1 background.

For Plag1 genotyping we used the following cycles: 95 ˚C 4 min, 40x (95 ˚C 1 min, 55 ˚C

1 min, 72 ˚C 1.5 min), 72 ˚C 10 min. Plag1 genotyping primers for the wild-type allele were:

Plag1 WT forward primer: 5'- CGGAAAGACCATCTGAAGAATCAC -3'. Plag1 WT reverse

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primer: 5'- CGTTCGCAGTGCTCACATTG -3'. Plag1 genotyping primers for the mutant allele were: Plag1 mutant forward primer: 5'- CGGAAAGACCATCTGAAGAATCAC -3'. Plag1 mutant reverse primer: 5'-AATGTGAGCGAGTAACAACCCG-3'.

For Plagl2 genotyping we used the following cycles: Mutant: 95 ˚C 4 min, 35x (95 ˚C 1 min, 62 ˚C 1 min, 72 ˚C 1.5 min), 72 ˚C 10 min. Wild-type: 95 ˚C 4 min, 40x (95 ˚C 1 min, 59 ˚C

1 min, 72 ˚C 1.5 min), 72 ˚C 10 min. Plagl2 genotyping primers for the wild-type allele were:

Plagl2WT forward primer: 5'- TGTATGGTGCCCACATCCCTAC -3'. Plagl2WT reverse primer:

5'- GGAAAAGTCCACATTAGCAGCG -3'. Plagl2 genotyping primers for the mutant allele were: Plagl2 MUT forward primer: 5'- CAGTTCAACATCAGCCGCTACAG -3'. Plagl2 MUT reverse primer: 5'- GGTGGACAGTGGACATTTATCAAGG -3'.

3.4.2. Tissue processing and cryostat sectioning. Embryos were dissected at E12.5 for all loss- of-function studies and at E13.5 for gain-of-function studies. Embryos were fixed overnight at 4°C in 4% paraformaldehyde (PFA) diluted in phosphate buffered saline (PBS) at pH 7.5. To remove the fixative, embryos were washed three times for 10 min in PBS, and then transferred to 20% sucrose/ 1 x PBS overnight. For cyrosectioning, the brains were embedded in optimal cutting temperature (OCT) compound and stored at -80°C. Blocks were then sectioned at 10 µm on a cryostat for immunostaining and RNA in situ hybridisation.

3.4.3. Immunohistochemistry. For immunostaining, sections were blocked in 10% Horse Serum,

0.1% Triton-X100 in PBS (PBT) at pH 7.5 for 1 hr. Primary antibodies were then diluted in blocking solution and the sections were incubated overnight at 4°C. Primary antibodies included rabbit anti-Tbr1 (1:800, Chemicon; Etobicoke, ON), rabbit anti-GFP (1:500, Chemicon, Temecula 105

CA), goat-anti-GFP (1:1000, Abcam) rabbit anti-Pax6 (1:500, Convance), rabbit anti-Tbr2 (1:500,

Abcam), rabbit anti-phospho-histone H3 (pHH3; 1:500; Millipore Biotechnology), and rat anti-

BrdU (1:20, Serotec). After incubating in primary antibody, the slides were washed three times in

PBT and then incubated for 1hr at room temperature in secondary antibodies. Secondary antibodies were conjugated to Alexa568 (1:500; Molecular Probes) or Alexa488 (1:500; Molecular Probes).

After incubation with secondary antibodies, the slides were washed three times in PBS and then stained with DAPI (1/10,000 for 5 min) and washed an additional three times. Slides were mounted in Aquapolymount for imaging.

3.4.4. RNA in situ hybridisation. RNA in situ hybridisation was performed on 10 mm cryosections using a previously described protocol [316]. Riboprobes were described in the following publications; Plag1 and Plagl2 [158], Lhx2 [344], Dlx1 [74], Ascl1 [354], and Neurog2

[355].

3.4.5. X-Gal staining. Slides were washed with DEPC phosphate buffered saline (PBS) pH7.5 for

5 min three times. Sections were fixed in fixing solution (0.2% glutaraldehyde, 2% formaldehyde,

5mM EGTA pH7.3, 2mM magnesium chloride and 0.1M sodium phosphate pH7.3 in PBS) for 15 min at room temperature. The slides were then washed with washing solution (0.02% NP40, 2mM

MgCl2 in PBS) for 10 min, three times. The slides were immersed in prewarmed staining solution

(20mg/ml X-gal-Sigma B4252 dissolved in DMSO, 5mM K3Fe(CN)6, 5mM K4Fe(CN)6, 2mM

MgCl2, 0.02% NP40 in PBS) and incubated in a 37C water bath for 4h to overnight protected from light. The tissues were dehydrated in 95% and 100% EtOH, and Xylene at room temperature. After

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the slides were dry, ~4 drops of permount was added per slide and mounted with a coverslip for imaging.

3.4.6. In utero electroporation. We performed in utero electroporation as previously described

[314, 317]. Briefly, we introduced 3 µg/µl of a pCIG2 control vector, which expresses GFP, or 3

µg/µl of pCIG2-Plag1 or pCIG2-Plagl2, which express the gene of interest and GFP, into E12.5 telencephalic vesicles using borosilicate needles and a Femtojet microinjector. Using a BTX electroporator, we applied 7 pulses of 55 mV within a 7 sec interval to the uterus with the paddles flanking the head of the embryo. The uterus was then put back and embryos were allowed to develop until E13.5. pCIG2-Plag1 was generated by PCR amplification of Plag1 from IMAGE clone ID 6328180 using the following primers: Plag1L:

AATCTAGAGATGGCCACTGTCATTCCTGG; Plag1R: AATCTAGAGGCTACACAAGCA

CCTCGGGT. The amplified Plag1 cDNA was cloned as a blunted XbaI fragment into the blunted

EcoRI site of pCIG2. pCIG2-Plagl2 was generated by PCR amplification of Plagl2 from IMAGE clone ID 6405960 using the following primers: Plagl2L: AATCTAGACATGACCACATTTTT

CACCAG; Plagl2R: AATCTAGACTGAGTTGGGGGACCTTCAT. The amplified Plagl2 cDNA was cloned was cloned directionally as an EcoRI fragment into the EcoRI site of pCIG2.

3.4.7. RT-qPCR. We microdissected the dorsal telencephalon from E12.5 embryos as described.

RNA was extracted with TRIzol reagent following the instructions of the manufacturer (Thermo

Fisher Scientific Cat#15596026). cDNA was synthesized and RT-qPCR was performed using a

RT2 primer assay kit (Qiagen 330001) according to the manufacturer’s instructions. The following

RT2 qPCR primers were obtained from Qiagen: Gapdh (PPM02946E), B2m (PPM03562A), Hrpt

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(PPM03559F), Plag1 (PPM30678A) and Plagl2 (PPM30603B). qPCR was performed with cortices from three embryos of each genotype and with three technical replicates for each biological replicate. We used the delta-delta Ct method to calculate relative expression levels, using three housekeeping genes to normalize (Gapdh, B2M, Hrpt).

3.4.8. Imaging, quantitation and statistics. We captured images using using OpenLab5 software

(Improvision) and a QImaging RETIGA EX digital camera for bright-field images and a Leica

DMRXA2 optical microscope for fluorescence imaging. Images were processes in Photoshop CS6

(64 bit; Adobe Systems) and quantification was performed from these images. For quantification we used a minimum of three embryos, and three sections per embryo. Calculation of statistical significance involved a one-way ANOVA with a Tukey correction for multiple comparisions.

Graphs and statistical values were generated using GraphPad Prism software. The error bars are standard error of the mean (s.e.m). p values are: *p < 0.05, **p < 0.01, and ***p < 0.005.

3.5 RESULTS

3.5.1. Plag1 and Plagl2 do not cross-regulate each other at the level of transcription

Plag1 and Plagl2 have similar amino acid sequences, sharing 79% identity in their N- termini and 35% in their C-termini [338]. They also share several transcriptional targets, including the growth factor Igf2 [1]. In addition, Plag1 and Plagl2 have both been characterized as growth regulators and proto-oncogenes [1, 194, 338]. Here we set out to determine whether they also have overlapping, possibly redundant roles in the developing CNS.

To better understand how Plag1 and Plagl2 function in the developing telencephalon, we first examined their expression profiles at embryonic day (E) 12.5, when the first neurons have

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begun to differentiate in both dorsal and ventral domains. As previously reported [158], Plag1

(Figure 3.1A) and Plagl2 (Figure 3.1B) were expressed in E12.5 telencephalic progenitors throughout the dorsal and ventral ventricular zones (VZ) in a highly similar fashion. Similarly, X- gal staining of coronal sections through E12.5 Plag1lacZKI/+ [240] (Figure 3.1C) and Plagl2lacZKI/+

[241] (Figure 3.1D) brains, revealed that lacZ had a similar distribution throughout the telencephalic VZ in both genotypes. Plag1 and Plagl2 are thus expressed similarly in the early embryonic telencephalic VZ, an expression profile that we previously demonstrated persists into the late embryonic period [158].

In several instances, highly related genes in the same family are not only expressed in the same CNS domains, but also display cross-regulatory interactions. For example, the highly similar proneural genes Neurog1 and Neurog2 are largely co-expressed in the early embryonic dorsal telencephalon [38], and Neurog2 is required to initiate Neurog1 expression in the dorsomedial cortex [51]. To determine whether there are similar cross-regulatory interactions between Plag1 and Plagl2, we asked whether when one gene is mutated, expression of the other was altered. By

RNA in situ hybridisation, we observed a similar distribution of Plagl2 transcripts in the telencephalic VZ of E12.5 Plag1lacZKI/KI homozygous mutants as seen in wild-type brains (Figure

3.1E,F). The converse was also true, as Plag1 transcripts were maintained in the telencephalic VZ of E12.5 Plagl2lacZKI/KI homozygous mutants in a similar pattern as in wild-type brains (Figure

3.1G,H).

To validate that there were no differences in Plag1 and Plagl2 transcript levels in homozygous mutants for the other Plag gene, we microdissected out neocortical tissue at E12.5 and performed RT-qPCR (Figure 3.1I). As expected, Plag1 transcripts were lost in Plag1lacZKI/KI cortices, whereas Plag1 transcript levels were at the same relative level in wild-type controls and

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in E12.5 Plagl2lacZKI/KI homozygous mutant neocortices (Figure 3.1J). Similarly, Plagl2 transcripts were lost in neocortical tissue from Plagl2lacZKI/KI homozygous mutants, whereas Plagl2 transcripts were expressed at wild-type levels in E12.5 Plag1lacZKI/KI cortices (Figure 3.1J').

Thus, we do not see any evidence of cross-regulatory transcriptional interactions between

Plag1 and Plagl2, or dosage compensation mechanisms that balance the overall reduction in Plag gene dosage, at least at E12.5, which is the stage that we focused on for the remainder of this study.

3.5.2. Plag1 and Plagl2 act redundantly to control embryonic survival

Previous reports have suggested that Plag1lacZKI/KI null mice are viable after birth, but are growth retarded and have reduced fertility [240]. Likewise, Plagl2lacZKI/KI neonates weigh less relative to their littermates at birth [241]. However, unlike Plag1lacZKI/KI mutants, Plagl2KI/KI pups display postnatal lethality, dying shortly after birth due to starvation and nutrient malabsorption

[241]. To determine whether Plag1 and Plagl2 function redundantly or have distinct functions in the embryonic telencephalon, we set out to generate double mutants by setting up double heterozygous intercrosses between Plag1lacZKI/+ and Plagl2lacZKI/+ mice (hereafter designated

Plag1KI and Plagl2KI). We collected seventeen litters at E12.5 for a total of 120 live embryos and compared the acquired genotypes to the expected genotypes using a Mendelian Punnett square diagram for a dihybrid cross (Figure 3.1L). If there was no embryonic lethality, we expected

Mendelian ratios for each possible genotype after double heterozygous intercrosses. Of the 120 embryos genotyped, significantly under-represented genotypes included Plag1+/+;Plagl2KI/KI,

Plag1KI/+;Plagl2KI/KI and Plag1KI/KI;Plagl2KI/KI (Figure 3.1M).

As we did not collect any double mutant embryos, our data suggests that Plag1 and Plagl2 function redundantly to control embryonic survival. Moreover, the Plagl2KI/KI genotype has an

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early embryonic lethal phenotype. This finding was somewhat surprising given that Plagl2KI/KI mutant embryos were previously reported to survive postnatally [241]. Differences between the two studies are likely related to our use of a different genetic background (i.e., CD1) compared to

129/SvJ background used by Van Dyck et al. (2007a).

3.5.3. Plag1 sets the dorsal border of ventral telencephalic gene expression

Neuronal fate specification is directly linked to dorsoventral regional identity in the telencephalon, with progenitors in the dorsal telencephalon giving rise to glutamatergic excitatory projection neurons, while ventral progenitors give rise to GABAergic inhibitory interneurons [338,

339]. Given that Plag1 and Plagl2 were expressed in both dorsal and ventral telencephalic progenitors, we first asked whether the Plag genes acted upstream of regional patterning genes.

Genes involved in the initial patterning of telencephalic domains are expressed in a regionalized manner and are enriched in or restricted to either dorsal or ventral telencephalic progenitors, with very precise dorsoventral boundaries [340]. Mutation of these patterning genes can disrupt the positioning of the border between the dorsal and ventral VZ (eg. Gsh2 mutants have an altered dorsoventral boundary; [341, 342]), and/or alter the phenotype of the resultant neurons.

To assess the roles of the Plag genes in dorsoventral patterning, we focused on Plag1 and

Plagl2 single mutants as we were not able to generate E12.5 Plag1;Plagl2 double mutants. In addition, to determine whether there was a gene dosage effect, we assessed E12.5 compound mutants with only one Plag gene copy, including Plag1KI/KI;Plagl2KI/+ and Plag1KI/+;Plagl2KI/KI embryos. In these embryos, we compared the position of the border of high dorsal or ventral gene expression (red arrowheads; Figure 3.2) to a morphological landmark, the corticostriatal angle

(black arrowheads; Figure 3.2). We first examined the expression of Ascl1, a proneural gene

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encoding a basic-helix-loop-helix (bHLH) transcription factor that is required for ventral telencephalic development [79]. At E12.5, Ascl1 was expressed at high levels in the ventral telencephalic VZ, including in both the lateral (LGE) and medial (MGE) ganglionic eminences

(Figure 3.2A), as previously reported [79]. Ascl1 transcripts were also enriched in the cortical hem, while lower levels of Ascl1 transcripts were detected in the dorsal telencephalic VZ (Figure 3.2A).

We also examined the position of the border of high and low Ascl1 expression in the ventral telencephalon, revealing a gap between this border and the corticostriatal angle in E12.5 wild-type brains in a region known as the dorsal LGE (dLGE) [343] (Figure 3.2A). Strikingly, in both E12.5

Plag1KI/KI (Figure 3.2B) and Plag1KI/KI;Plagl2KI/+ (Figure 3.2C) brains, the high Ascl1 expression domain shifted dorsally to meet the corticostriatal angle, filling in the VZ of the dLGE. In contrast, in E12.5 Plagl2KI/KI (Figure 3.2D) and Plag1KI/+;Plagl2KI/KI (Figure 3.2E) cortices, the gap between high ventral Ascl1 expression and the corticostriatal angle was maintained.

We also examined the expression of Dlx1, a homeodomain transcription factor that acts with the related gene Dlx2 to establish a ventral telencephalic identity, with the absence of these genes, resulting in the loss of most if not all, GABAergic interneurons [74]. In E12.5 wild-type brains, Dlx1 was expressed at high levels throughout the VZ of the LGE and MGE, except in a small gap in the dLGE (Figure 3.2F) [51]. In E12.5 Plag1KI/KI (Figure 3.2G) and

Plag1KI/KI;Plagl2KI/+ (Figure 3.2H) brains, Dlx1 expression directly abutted the corticostriatal angle. In contrast, in E12.5 Plagl2KI/KI (Figure 3.2I) and Plag1KI/+;Plagl2KI/KI (Figure 3.2J) cortices, the normal gap in Dlx1 expression in the dLGE was maintained.

Taken together, these data indicate that Plag1 is required to maintain dorsal boundaries of ventral gene expression in the E12.5 telencephalon. Furthermore, they suggest that there is not a further worsening of this phenotype when an additional Plagl2 allele is mutated.

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3.5.4. Plagl2 sets the ventral border of dorsal telencephalic gene expression

We next examined the expression of dorsally-restricted genes in our series of E12.5 Plag1 and Plagl2 mutants. The proneural gene Neurog2, which also encodes a bHLH transcription factor, is required to specify a dorsal telencephalic identity [51]. In the E12.5 wild-type telencephalon,

Neurog2 was exclusively expressed in the dorsal VZ, with the ventral border of expression just passing the corticostriatal angle into a region of the telencephalon known as the ventral pallium

(Figure 3.2K). A similar pattern of Neurog2 expression was observed in E12.5 Plag1KI/KI (Figure

3.2L) and Plag1KI/KI;Plagl2KI/+ (Figure 3.2M) brains, with Neurog2 expression extending slightly past the morphological crease into the ventral pallium. In contrast, Neurog2 expression extended well past the ventral pallium into the dLGE in E12.5 Plagl2KI/KI (Figure 3.2N) and

Plag1KI/+;Plagl2KI/KI (Figure 3.2O) cortices, suggesting that there has been a ventral expansion of the expression domains of dorsal markers.

Finally, we examined the expression of Lhx2, which encodes a homeodomain transcription factor that acts as a cortical selector gene [344, 345]. In wild-type E12.5 cortices, Lhx2 was expressed throughout the telencephalic VZ, but in a graded fashion, with higher levels in dorsomedial domains, and lower levels in the lateral and ventral telencephalon (Figure 3.2U). A similar pattern of expression was seen in all genotypes, including in E12.5 Plag1KI/KI (Figure

3.2V), Plag1KI/KI;Plagl2KI/+ (Figure 3.2W) Plagl2KI/KI (Figure 3.2X) and Plag1KI/+;Plagl2KI/KI

(Figure 3.2Y) brains. Plag genes are thus not required to control the expression of Lhx2, which is expressed in both dorsal and ventral domains of the telencephalon.

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3.5.5. Plag1 is required to regulate the proliferation of early embryonic neocortical progenitors

To further assess the functions of the Plag genes in the developing telencephalon, we focused on dorsal domains, which gives rise to the neocortex. At E12.5, Plag1 and Plagl2 are both expressed in the neocortical VZ, which is comprised of radial glial cells (RGCs). RGCs serve as progenitors for early-born, deep-layer neurons, and also give rise to intermediate neuronal progenitors (INPs) that will form a subventricular zone (SVZ) and differentiate into later-born upper-layer neurons (reviewed in [346]). We asked whether Plag1 and Plagl2 are required for the proliferation and/or differentiation of neocortical progenitors by characterizing E12.5 mutants, focusing on single mutants as compound mutants did not appear to have more severe defects in patterning.

To determine whether Plag1 and Plagl2 were required to regulate the proliferation of neocortical progenitors, we administered BrdU 30 min prior to sacrifice to label progenitor cells in S-phase of the cell cycle. In E12.5 wild-type (Figure 3.3A), Plag1KI/KI (Figure 3.3B) and

Plagl2KI/KI (Figure 3.3C) cortices, BrdU was detected in an abventricular band where S-phase progenitors accumulate due to interkinetic nuclear migration. Quantitation revealed that there was a 1.67-fold reduction in the percentage of S-phase progenitors in the Plag1KI/KI cortex (n=3; p<0.01), whereas there was no change in the BrdU labeling index in the Plagl2KI/KI cortex (Figure

3.3D). Similarly, labeling G2/M-phase progenitors with phospho-histone H3 (pHH3), which marks mitotic cells near the apical surface in E12.5 wild-type (Figure 3.3E), Plag1KI/KI (Figure

3.3F) and Plagl2KI/KI (Figure 3.3G) cortices, revealed a 3-fold reduction in pHH3+ cells in Plag1 mutants (Figure 3.3H). Taken together, these data suggest that Plag1, and not Plagl2, is required for the proliferation of neocortical progenitors.

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We next assessed changes in the expression of progenitor cell markers in E12.5 wild-type

(Figure 3.3I,M), Plag1KI/KI (Figure 3.3J,N) and Plagl2KI/KI (Figure 3.3K,O) cortices, using Pax6 to label RGCs [33] and the T-box transcription factor Tbr2 to label INPs [35, 36]. Pax6 labeled the same number of RGC progenitors in the VZ in all genotypes (Figure 3.3I-L), while Tbr2 labeled the same number of INPs (Figure 3.3M-P). The decrease in VZ proliferation in Plag1 mutants was therefore not translated into an overall change in progenitor cell number, at least by E12.5. Finally, we asked whether Plag1 and/or Plagl2 regulated the differentiation of neocortical progenitors by examining the expression of Tbr1, a marker of early-born, deep-layer neurons [80]. There was a small but significant increase in the number of early-born neurons generated in E12.5 Plag1KI/KI mutants compared to wild-type and Plagl2KI/KI cortices (Figure 3.3Q-T). Notably, the differences in proliferation and differentiation observed in Plag1KI/KI mutants did not translate into alterations in the total number of DAPI+ nuclei in the E12.5 neocortex (wild-type: 1393±76.4; Plag1KI/KI:

1188±68.8; Plagl2KI/KI: 1427±80.0; n=3 for each genotype).

Taken together we can conclude that Plag1 is required to maintain the balanced choice between proliferation and differentiation in the E12.5 neocortex, suggesting that Plagl2, which is not mutated in Plag1KI/KI embryos, is not sufficient to rescue this phenotype. In contrast, Plagl2 is not required for the proliferation or differentiation of neocortical progenitors, possibly because

Plag1 compensates to some extent for its functions.

3.5.6. Plagl2 is sufficient to alter the proliferation of neocortical progenitors

Plag1 and Plagl2 are both proto-oncogenes, promoting cell proliferation in a malignant context [1, 241]. We therefore asked whether the overexpression of these factors in non- transformed, embryonic neural progenitors could similarly promote proliferation, and/or alter

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differentiation. For this purpose, we used in utero electroporation to introduce Plag1 and/or Plagl2 expression constructs containing an IRES-GFP cassette into dorsal telencephalic progenitors at

E12.5, or an empty vector control expressing GFP only. Embryos were harvested 24 hr post- electroporation and transfected cells were identified using GFP epifluorescence (Figure 3.4A).

We first asked whether Plagl1 and/or Plagl2 could promote ectopic proliferation by assessing the incorporation of BrdU administered 30 min before embryo collection. Relative to control E12.5→E13.5 electoporations, Plagl2 (and not Plag1) was sufficient to increase the number of cells taking up BrdU (i.e., BrdU+GFP+/GFP+ cells; n=3; p<0.05; Figure 3.4B-E).

Similarly, Plagl2 misexpression increased the number of cortical progenitors expressing pHH3, a

G2/M-phase marker (n=3; p<0.001; Figure 3.4F-I), whereas Plag1 did not alter the pHH3+GFP+/GFP+ ratio. However, this increase in proliferation did not translate into an increase in RGC progenitor cells, as the ratio of Pax6+GFP+/GFP+ cells was not altered by either Plag1 or

Plagl2 (n=3 each; Figure 3.4J-M). Moreover, there was a decrease, rather than increase, in the number of Tbr2+GFP+/GFP+ INPs generated after the misexpression of both Plag1 (n=3; p<0.05) and Plagl2 (n=3; p<0.01) (Figure 3.4N-Q). Finally, Plagl2 also increased the number of cortical progenitors that underwent neuronal differentiation, as assessed by the increase in number of

Tbr1+GFP+/GFP+ neurons (n=3; p<0.05, whereas Plag1 did not alter neurogenesis (Figure 3.4R-

U).

In summary, Plagl2 but not Plag1 is sufficient to induce the proliferation of neocortical progenitors, as well as to promote the differentiation of these progenitors into neurons.

3.6 DISCUSSION

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In this study we investigated the function of the proto-oncogenes Plag1 and Plagl2 in the developing CNS. Our goal was to generate double mutants to assess genetic redundancy in the

CNS, but no live double mutant embryos were collected at E12.5, indicating that these genes can compensate for one another with respect to overall embryonic growth and survival, and that at least one gene copy of either Plag1 or Plagl2 is required. Furthermore, we found that the Plagl2 genotype was lethal on a CD1 background, with a reduced number of single mutant embryos obtained at E12.5, restricting our analyses of neocortical development to this early embryonic stage. Our analysis of E12.5 mutants revealed complementary patterning defects in the telencephalon, with Plag1 required to set the dorsal boundary of ventral gene expression, and

Plagl2 required to set the ventral boundary of dorsal gene expression. We also found that only

Plag1 is essential for neocortical progenitor proliferation and differentiation, consistent with its known roles as a growth regulator, whereas our gain-of-function studies revealed that only Plagl2 was sufficient to promote the proliferation of neocortical progenitors. Thus, despite their related structures and roles as oncogenes, there are key differences in how Plag1 and Plagl2 normally function in vivo. We discuss the potential reasons for these differences below, and compare Plag1 and Plagl2 functions to Plagl1 (also known as Zac1), the third member of this gene family.

All three of the Plag proteins transactivate some common transcriptional targets, including several imprinted genes (e.g., Dlk1, Igf2) [157, 193, 227, 231, 337], despite Plag1 and Plagl2 recognizing a distinct binding site (GRGGCN6-8G3) [161, 162, 218] compared to Zac1 (G4C4,

G4N6G4 or GC2GC2G) [219, 224, 225]. Given the similar transcriptional targets, it is surprising that Plag1 and Plagl2 act as proto-oncogenes, while Zac1 is a tumour suppressor gene. Moreover,

Zac1 misexpression was previously shown to reduce proliferation in the neocortex [239, 336],

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whereas in this study we showed that Plagl2 was sufficient and Plag1 required to promote proliferation.

One possible reason for these functional differences despite overlapping transcriptional targets is that Zac1 can function as a transcriptional activator or repressor [219, 224, 225]. When

Zac1 binds as a monomer, it transactivates G4C4 and GC2GC2G sites and represses transcription from G4N6G4 sites, while dimer binding to G4N6G4 leads to transactivation [224, 225]. Zac1 transcriptional activity is also modulated by interactions with nuclear importers [347], other transcription factors [225], and histone acetyltransferases (HAT) [348]. Zac1 can also act in a non-

DNA binding-dependent manner, functioning as a co-activator or co-repressor of other transcriptional regulators (e.g., p53, nuclear receptors; [218, 224, 225, 349-352]).

In addition to sharing some common targets, the three transcription factors must also transactivate distinct genes in the developing neocortex. Further studies will be required to find out what these targets are for Plag1 and Plagl2, but a recent study has begun to shed light on the transcriptional targets of Zac1 [353]. In this study, Zac1 misexpression was shown to upregulate the expression of several imprinted genes, consistent with the finding that Zac1 is part of an imprinted gene network [157]. Zac1 also induced the expression of negative regulators of the cell cycle, such as the cyclin dependent kinase inhibitors p57 (which is imprinted) and p27, consistent with the ability of Zac1 to promote cell cycle exit [353]. Finally, Zac1 misexpression also induced the ectopic expression of several genes not normally expressed in neural lineages, as well as genes associated with pluripotency, suggesting that one function of Zac1 is to promote a pluripotent state

[353]. It will be of interest in the future to see whether Plag1 and Plagl2 also have a similar role in maintaining pluripotency.

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We found that Plag1 is required to regulate cell proliferation in the neocortex, which is of particular interest as several genome wide association studies (GWAS) have indicated that a SNP in Plag1 is in one of 27 loci that correlate with height in humans [225], and additional studies have found correlations with stature or size in various livestock species, including cattle, pigs and horses

[338]. While these are association studies, the underlying assumption is that Plag1 is an important regulator of growth. Interestingly, in our gain-of-function studies, Plag1 was not sufficient to promote proliferation in neocortical progenitors, possibly because it acts in concert with other factors to carry out its growth regulatory role. Igf2 is a downstream transcriptional target of Plag1 that has been implicated in growth control [162], and it may be that Plag1 is not sufficient on its own to turn on this transcriptional target in the embryonic neocortex. Another possibility is that

Plag1 is sumoylated in the embryonic neocortex, as this post-translational modification has been shown to repress the ability of Plag1 to transactivate downstream targets [222].

In our study we found that Plagl2 is sufficient but not necessary to promote the proliferation of neocortical progenitor cells. This data is consistent with a previous report showing that misexpression of Plagl2 in p53-/- adult neural stem cells promotes a proliferative phenotype when these cells are cultured in vitro [199]. Moreover, we found that more neurons were generated upon the misexpression of Plagl2, possibly because there were more progenitors to differentiate.

This finding is in direct opposition to the finding that Plagl2 blocks neuronal differentiation in glioma cells [199]. These results suggest that Plagl2 functions are context-dependent. Indeed,

Plagl2 is not oncogenic in all contexts (e.g., pro-apoptotic in response to hypoxia and other cellular stresses [204-207]). One reason why Plagl2 functions may change in different contexts is that its transcriptional activity is also regulated by post-translational modifications, including sumoylation and acetylation [220-223]. Under the right conditions, Plagl2 may promote neocortical progenitor

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proliferation possibly via its capacity to initiate the transcription of Wnt pathway genes [199], a key proliferative signal in the neocortex [199].

In summary, our study reveals that Plag1 and Plagl2 are not only important regulators of tumorigenesis, but also play important redundant as well as complementary roles in normal CNS development. Both genes function redundantly to control embryonic survival. In addition, they have complementary patterning defects in the telencephalon, with Plag1 required to set the dorsal boundary of ventral gene expression, and Plagl2 required to set the ventral boundary of dorsal gene expression. Complementary functions were also observed with respect to proliferation, with

Plag1 required to maintain the proliferation of neocortical progenitors, while Plagl2 is sufficient to promote proliferation.

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3.7. FIGURE LEGENDS

Figure 3.1. Plag1 and Plagl2 have similar patterns of telencephalic gene expression and function redundantly to regulate embryonic development. (A,B) Expression of Plag1 (A) and

Plagl2 (B) in E12.5 wild-type embryos. (C,D) X-gal staining of E12.5 PlagllacZKI/+ (C) and

Plagl2lacZKI/+ (D) brains. (E-H) Expression of Plagl2 (E,F) and Plag1 (G,H) in wild-type (E,G),

Plag1lacZKI/KI (F) and Plagl2lacZKI/KI (H) brains. (I-J') Schematic representation of RT-qPCR experiment (I). Analysis of Plag1 (J) and Plagl2 (J') transcript levels in E12.5 wild-type, Plag1KI/KI and Plagl2KI/KI cortices. (L,M) Punette square analysis of the ratios of genotypes acquired from

Plag1KI/+;Plagl2KI/+ heterozygous intercrosses (L). Graphical representation of the expected (black bars) and observed (blue bars) numbers of embryos with each genotype (M). cx, neocortex; lge, lateral ganglionic eminence; mge, medial ganglionic eminence; oe, olfactory epithelium; re, retina.

Scale bars, 250 µm.

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Figure 3.2. Plag1 and Plagl2 are required to pattern the embryonic telencephalon. (A-Y)

Expression of Ascl1 (A-E), Dlx1 (F-J), Neurog2 (K-O), and Lhx2 (P-T) in E12.5 wild-type

(A,F,K,P), Plag1KI/KI (B,G,L,Q), Plag1KI/KI;Plagl2KI/+ (C,H,M,R) Plagl2KI/KI (D,I,N,S) and

Plag1KI/+;Plagl2KI/KI (E,J,O,T) brains. Black or white arrowheads mark the corticostriatal angle.

Red arrowheads in A-J mark the dorsal limit of high ventral gene expression. Red arrowheads in

K-Y mark the ventral limit of high dorsal gene expression. ch, cortical hem; cx, neocortex; lge, lateral ganglionic eminence; mge, medial ganglionic eminence; oe, olfactory epithelium; re, retina. Scale bars, 250 µm.

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Figure 3.3. Plag1 is required to regulate proliferation in the early embryonic telencephalon.

(A-T) Analysis of the expression of BrdU (A-C), pHH3 (E-G), Pax6 (I-K), Tbr2 (M-O) and Tbr1

(Q-S) in E12.5 wild-type (A,E,I,M,Q), Plag1KI/KI (B,F,J,N,R) and Plagl2KI/KI (C,G,K,O,S) cortices.

Quantification of the percentage of DAPI+ cells expressing BrdU (D), pHH3 (H), Pax6 (L), Tbr2

(P) and Tbr1 (T). Error bars are s.e.m.. pp, preplate; vz, ventricular zone. Scale bars, 125 µm.

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Figure 3.4. Plagl2 is sufficient to alter the proliferation and differentiation of neocortical progenitors. (A) Schematic representation of gain-of-function experiment using in utero electroporation. (B-U) E12.5 to E13.5 electroporations of pCIG2 (B,F,J,N,R), Plag1

(C,G,K,O,S) and Plagl2 (D,H,L,P,T) analysed for the expression of BrdU (B-E), pHH3 (F-I),

Pax6 (J-M), Tbr2 (N-Q) and Tbr1 (R-U). Error bars are s.e.m.. pp, preplate; vz, ventricular zone.

Scale bars, 125 µm.

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CHAPTER 4: Glioma cells secrete extracellular vesicles carrying EGF and have dose- dependent effects on neural stem cells

Lata Adnani, Ahmed El-Sehemy, Boris Kan, Thomas Olender, Rajiv Dixit, Lacrimioara C Comanita, Myra Chen, Yacine Touahri, Sophie Briggs, Greg Cairncross, Tara L Beattie, Marjorie Brand, Valerie A Wallace, Jennifer A Chan, Carol Schuurmans

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4.1 ABSTRACT

Oligodendroglioma (ODG) is characterized by a 1p19q co-deletion and CIC, FUBP1 and

IDH1/2 mutations. The identification of these driver mutations has brought hope for the development of therapies, but drugs that block glioma growth in vitro often fail in the clinic. One reason is that these drugs fail to target key interactions between tumour cells and other cells in the environment. We set out to determine whether ODGs interact with neural stem cells by working with BT088 cells derived from an ODG tumour. We revealed that BT088 cells secrete factors that have dose-dependent effects on mNSC proliferation; stimulatory at low levels and inhibitory at high levels. Moreover, we found that BT088 cells secrete bioactive molecules in extracellular vesicles (EVs), and that the EV factors are responsible for the effects on mNSC proliferation. Characterization of the BT088 secretome revealed that it is enriched in several signaling molecules. We focused on receptor tyrosine kinase signaling, and demonstrated that this pathway can influence neural cells non-cell autonomously both in a mouse model of glioma and in human ODG tumours. To begin to identify the dose-responsive factors, we focused on

EGF, which we showed is stimulatory at high levels and inhibitory at low levels. Furthermore, we found that the effects of EGF are modulated by glucose, with high glucose having neuroprotective effects. Finally, we manipulated EV production by blocking or overexpressing

Smpd3 in BT088 cells directly, and showed that removal of EVs stimulates tumour cell growth, whereas the increased production of EVs inhibits growth. Xenografting experiments are currently in progress to test the effects of these manipulations in vivo. In summary, we demonstrated that ODG cells communicate with neural cells non-cell autonomously, and implicated the secretion of growth factors such as EGF into EVs as one of the responsible mechanisms.

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4.2 SIGNIFICANCE STATEMENT

Gliomas are brain cancers comprised of cells having glial characteristics. According to the most recent WHO classification, gliomas are categorized based on not only their morphologies but also their molecular and genetic hallmarks. While glioblastoma multiforme (GBM) is comprised of proneural, neural, mesenchymal and classical tumor forms, oligodendroglioma (ODG) and astrocytoma are comprised of cells which are characteristic of oligodendrocyte precursor cells (OPCs) or astrocyte precursor cells (APCs) respectively. ODG has been shown to be classified as WHO grade II (less aggressive) and WHO grade III

(aggressive). Usually, grade II cancers progress into grade III leading to unfavorable patient prognosis.

Since several drugs that have been used to target glioma have not been very efficient, in this study we undertook a novel approach to tease apart some of the events that lead to ODG and neural stem cell (NSCs) communication. Specifically, we studied how ODG cells communicate with mNSCs and influence the nNSC growth in vitro and in vivo.

4.3 INTRODUCTION

Gliomas are glial cell-derived brain tumours that are classified as astrocytomas (e.g., glioblastoma - GBM) or oligodendrogliomas (ODG), which differ from one another with respect to their genetic mutations, cellular makeup and locations. In general, gliomas are composed of a mixture of malignant glial cells, or tumour cells, as well as non-malignant glial cells and neurons

(neural cells), and a variety of other inflammatory and vascular cells (stromal cells). The composition of the tumour mass changes over time, as proliferating tumour stem and progenitor cells undergo lineage progression and differentiation, and the molecular identity of the tumour cells can also evolve, with proneural signatures often resolving into more mesenchymal, aggressive tumour phenotypes [297]. Accordingly, single cell analyses revealed that cells with different subtype-specific gene expression signatures are found within individual tumours in

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different proportions [356].

Homotypic and heterotypic cell interactions are important factors in the tumour microenvironment and in tumour progression. Indeed, human glioma cells secrete factors that confer a proliferative and self-renewal advantage onto ‘normal’ neural stem cells [357]. One mode of intercellular communication involves the trafficking of extracellular vesicles (EVs) – secreted membrane-enclosed structures that deliver protein and nucleic acid cargo to neighboring cells

[270, 271]. A previous study found that the oncogene EGFRviii, a constitutively active EGF receptor identified in various gliomas [267], transported by GBM host cells into EVs that are then delivered to neighboring cells, altering the signaling and proliferative behavior of these recipient cells [267]. Other studies have observed EV-mediated transfer of DNA fragments containing oncogenic DNA fragments [358], or the delivery of pre-miRNAs and components of the RISC- loading complex, which both affect the behavior of recipient cells in the tumour mass.

We set out to examine the role of EV-mediated transfer in gliomagenesis in more detail by taking advantage of a brain tumour initiating cell (BTIC) line derived from an ODG tumour [359].

ODG is characterized by a 1p/19q chromosomal co-deletion, IDH1/2 mutations [259, 360].

Capicua (CIC), which is located at chr19q13.2, is mutated in most ODGs [259, 360]. Our goal was to determine whether glioma cells secrete factors that influence the behavior of neural stem cells

(NSCs), and we found a dosage-sensitive response, identifying EGF as an EV-secreted factor that promotes NSC proliferation at low doses and inhibits NSC proliferation at higher doses.

Furthermore, we found that altering EV secretion changes the survival of BTICs, and xenografting is currently in progress to test whether this altered survival influences gliomagenesis in vivo.

4.4 MATERIALS AND METHODS

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4.4.1 Animals. Embryos were staged using the morning of the vaginal plug as embryonic day (E)

0.5. CD1 mice (Charles River Laboratories, Senneville, QC) were used for the preparation of mNSCs and for in utero electroporation experiments. The use of animals was approved by

HERBA, Alberta according to the ethics approval # HREBA.CC-16-0787_REN1.

4.4.2 STR matching. Genomic DNA was isolated from the patient 9672 and from the BT088 cell line that were derived from this patient’s tumour and resuspended at 10-50 ng/ul. STR matching was performed at the Center for Applied Genomics at the Hospital for Sick Children, Toronto using a 16 panel Identifiler panel.

4.4.3 Patient-derived tumor tissues. Formalin-fixed paraffin embedded tissues from oligodendroglioma were obtained from pathology archives at the Calgary Laboratory Services and the Clark Smith Brain Tumor Bank at the University of Calgary [359]. The use of these tissues was approved by Calgary Laboratory Services and the Calgary Health Region Ethics Board (U of

C Conjoint Health Research Ethics Board #2875 to JAC and #24993 to CS).

4.4.4 BT088 cell line maintenance, CM and EV collection. Derivation of the BT088 cell line was previously described [359]. BT088 cells were maintained in Human NeurocultTM NS-A proliferation kit from Stem Cell Technologies (cat# 05751) in combination with epidermal growth factor (hEGF, 20ng/ml, Wisent), fibroblast growth factor (hFGF2, 20ng/ml, Wisent), Heparin solution (0.0002% Heparin (w/v); Stem Cell Technologies, Cat#07980), Penicillin/streptomycin

(Wisent, 0.1%) and Amphotericin B (ThermoFisher Scientific #15290026, 40 ng/mL). BT088 133

cells were passaged every three days using ACCUTASETM (Stem Cell Technologies, Cat# 07920).

To collect CM, BT088 cells were seeded at 1x106 cells in 13ml DMEM media in a T75 flask and incubated for 24 hours before harvesting. DMEM media consisted of DMEM (ThermoFisher

Scientific #11965-092) : F12 (ThermoFisher Scientific #31765-035) (3:1), hFGF2 (40ng/ml), hEGF (50ng/ml), B27 supplement (ThermoFisher Scientific #17504044, 2%),

Penicillin/streptomycin (0.1%), Amphotericin B (40 ng/mL), Cyclopamine (Sigma #C4116, 0.5

µM) and Heparin solution (0.0002% Heparin (w/v); equals 2 µg/mL). After 24 hr, BT088-CM was centrifuged at 300 x g for 5 min to remove cells. The supernatant (BT088-CM) was collected and ultra-centrifuged at 10,000 rcf for 10 min at 4°C to pellet down cell debris. To collect BT088-CM minus EVs, the supernatant was further centrifuged at 100,000 rcf for 2 hr at 4°C. To collect BT088

EVs, the supernatant was discarded and the pellet was suspended in equal volume of DPBS

(ThermoFisher Scientific # 14190144) and centrifuged for and additional 1 hr at 100,000 rcf at

4°C (to pellet purified EVs).

4.4.5 mNSC derivation and culture. mNSCs were harvested from the dorsal telencephalon of

E13.5 CD1 embryos and the cells were dissociated in 0.125% trypsin (ThermoFisher Scientific

#15090046) at 37°C for 8 min. Trypsinization was stopped by the addition of 20% FBS. Cells were then spun at 520 rcf, resuspended in 1ml DMEM media and counted using the heamocytometer for Trypan blue negative cells. Cells were seeded at 8000 cells/ml in fresh

DMEM media or in BT088-CM at different concentrations diluted in fresh media (100%, 75%,

50%, 25%).

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4.4.6 Transwell (Boyden) chamber assay. The transwell chamber was set up as in [281]. Briefly, mNSCs were plated at 8000 cells/ml in a 2.7ml volume in a six well companion plate (BD Falcon

#353502). The insert was placed on top and contained either 1.5 ml of DMEM media, BT088 cells, or BT088-CM (six well cell culture inserts, BD Falcon #353102). mNSCs and BT088 cells were plated in a 1:1 ratio.

4.5.7 Western blotting and Silver staining. Cells were collected and lysed in RIPA buffer with protease (1X protease inhibitor complete, 1 mM PMSF) and phosphatase (50 mM NaF, 1 mM

NaOV) inhibitors. 10 µg of lysate was run on 10 % SDS-PAGE gels for Western blot analysis as described previously [313]. Primary antibodies included: pErk (1:1000, Cell Signaling #9106),

Erk (1:1000, Cell Signaling #9102), Etv5 (1:1000, Abcam ab102010), Egfr (1:1000, Abcam ab52894), flotillin (1:1000, cell signalling #3253), CD63 (1:1000, BD Pharmingen #556019), CD9

(1:1000, Santa Crutz sc9148), nSMase2 (1:1000, Abcam ab85017) and β-actin (1:10000, Abcam

#8227). Densitometries were calculated using UN-SCAN-IT gel densitometry software (Silk

Scientific). The average values of normalized expression levels were plotted. Silver staining was performed as per the manufacturer’s instructions (BioRad Dodeca Silver Stain Kit Catalog# 161-

0481).

4.4.8 ELISA. EVs were collected from BT088 cells and other glioma cell lines as described above.

A human EGF ELISA was performed on 420 µg of protein as per the manufacturer’s instructions

(R&D systems catalogue # DEG00).

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4.4.9 Mass Spectrometry. EVs were lysed in RIPA buffer and 10 ug of protein was run on an

10% SDS-PAGE gel. The gel was silver stained, and 9 blocks of gel in different size ranges were cut out and trypsin digested as described [386]. Proteins were analyzed by liquid chromatography

(LC)-tandem MS (MS/MS) on a linear trap quadrupole (LTQ)-Orbitrap XL mass spectrometer with a nanospray source and Surveyor high-performance liquid chromatography (HPLC) as described [386]. Scaffold data analysis was performed by applying NCBI annotations to all proteins, removing all proeins that matched the search term “keratin” and which did not have

“Homo sapiens” under the taxonomy heading. Protein filtering thresholds were set at 99.0%, with a minimum number of 2 peptides and a peptide threshold of 95%. Remaining proteins were then exported to Excel for analysis of “Extracellular Vesicles” and “Signaling pathways”. Applied Top3

TIC calculations based on [387]. Cytoscape analysis was performed on the Extracellular vesicle sample analsyis, separa.

4.4.10 Nucleofection. 3X106 BT088 cells were suspended in 15 µl of P3 nucleofector reagent along with the total DNA concentration of ~8 µg. The P3 reagent suspended cells were placed into nucleofector strips and inserted into a 4D nucleofector (Lonza) with the program, DS113. DNA constructs to be nucleofected were generated as follows: The IRES GFP + PiggyBac shRNA construct (SB #PBSI505A-1) was cut with BamH1 and EcoR1. To generate shSmpd3, 5ʹ P-

GATCCCCCTCATCTTCCCATGTTACTTCAAGAGAGTAACATGGGAAGATGAGGGACG

CGTG 3ʹ (sense) and 5’ P AATTCACGCGTCCCTCATCTTCCCATGTTACTCTCTTGAAG

TAACATGGGAAGATGAGGGG 3’ (antisense); and for shScrambled, 5’ P – 136

GATCCATTCACTTATCCGCCTCTCCTTCAAGAGAGGAGAGGCGGATAAGTGAATCTC

GAGG 3’ (sense), and 5’ P – GAATTCCTCGAGATTCACTTATCCGCCTCTCCTCTCTTG

AAGGAGAGGCGGATAAGTGAATG 3’ (antisense) oligonucleotides were cloned into the cut

PiggyBac shRNA vector. For the shScrambled construct, we used an online program, Genescript, to generate a specific scrambled sequence for the shSmpd3 that we used. Likewise, we cloned the

Smpd3 gain of function construct by modifying the EF1 alpha promoter of the GFP+ PiggyBac

IRES vector (SB # PB530A-2) to a caags promoter (obtained from Dr. Jennifer Chan), then digesting it with SwaI. The Smpd3 CDS insert was isolated from pCMV-Sport6 vector (image clone #6399438) post cutting it with Sal1/Xho1 and blunt ending it. The insert was ligated into the predigested vector. The Cre expression vector used was Caags-PiggyBac. Each PiggyBac vector was nucleofected with Super PiggyBac Transposase expression vector (SBI, Cat#PB210PA-1) in

1 : 0.5 , PiggyBac : transposase ratio in order to ensure genome integration of the PiggyBac vector.

4.4.11 Pellet assay. Pellet assay was performed as in [388]. Briefly, BT088 cells nucleofected with a GFP+ Cre driver was mixed with NIH3T3 cells transfected with BFPloxPDsRed in a 5:1 ratio (Cre:reporter). The cells were centrifuged and the pellet was placed on the cell culture membrane. The membrane was allowed to float on the DMEM media in a 6-chamber dish. The cells were incubated at 37C for 3DIV after which the membrane was embedded in a cryopreservative, OCT, and frozen gradually on dry ice. 10um thick sections were obtained by sectioning the OCT block. The slides were them imaged at 10X.

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4.4.12 In utero electroporation. In utero electroporation was performed as described [314].

Briefly, 1.5 µg/µl DNA was prepared using Qiagen columns according to the manufacturer’s instructions (Qiagen, Mississauga, ON). DNA was injected using a Femtojet microinjector apparatus (VWR CanLab, Mississauga, ON) and 3-axis coarse manipulator (Carl Zeiss Canada,

North York, ON) into E12.5 telencephalic vesicles of embryos that were still in the uterus of pregnant females anaesthetized with inhalable isofluorane (5L/min). Electroporation was performed using seven 50 V pulses at 750 msec intervals applied by 5 mm tweezer-style electrodes

(Protech International, Monroe, NC) using a BTX square wave electroporator (BTX, VWR

CanLab). After electroporation, the uterus was replaced, the peritoneum and skin were sutured and embryos were harvested three days later at E15.5. cDNAs were cloned into pCIG2 as described, and included BRAFV600E (Addgene plasmid 15269), MekCA and Egfvriii [368].

4.4.13 Tissue Processing and Immunostaining. Brains were dissected in phosphate-buffered saline (PBS) and immediately fixed in 4% paraformaldehyde (PFA) in PBS overnight at 4°C. The tissue was washed 3 x 10 min in PBS and then immersed in 20% sucrose in PBX overnight at 4°C.

Brains were then embedded in OCT and 10 µm cryosections were collected on Superfrost Plus

(Fisher) slides. Sections were blocked in 10% horse serum in PBS with 0.1% triton x-100 (PBT) for 1 hr at room temperature and then incubated in primary antibodies: (rabbit anti-Sox9: 1/500,

Millipore; rabbit anti-pERK: 1/500, Cell Signaling; IDHMR132H (1:500), overnight at 4°C.

Sections were washed 3 x 10 min in PBT and then incubated in secondary antibody conjugated to or Alexa 568 (1/500; Molecular Probes). Sections were washed 3 x 10 min in PBS and then mounted with AquaPolymount (Polysciences).

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4.4.14 Imaging and statistical analysis. Images were obtained from DFC3000G camera or

DFC9000 GT sCMOS camera compatible with Leica DM IL LED or Leica DMi8 microscopes respectively. Images were captured using the Leica specific software, Las X.

Neurosphere/tumorsphere and trypan blue cell counts were performed using the DM IL LED microscope. Sphere sizes were measured using the ruler measurement tool in Adobe Photoshop

CS6 (64 bit). In order to generate minimum three biological replicates, experiments were set up and cell counts were performed on three separate days and cells were plated at clonal densities as technical triplicates. Statistical analysis and graphs were generated using the Prism software

(GraphPad Prism 6 software). In order to compare two groups, standard student’s t-test was used, while comparing groups more than two, One way ANOVA with Tukey post corrections was used.

Error bars are representative of the p-values, *p < 0.05, **p < 0.01, and ***p < 0.005.

4.5 RESULTS

4.5.1 BT088 cells act in a contact-independent fashion to influence the proliferation of neural stem cells

BT088 cells are a line of brain tumour initiating cells (BTICs) that were first established from an oligodendroglioma tumour resected from a patient in 2010 [359]. These cells grow well in vitro, maintaining their self-renewal capacity, and giving rise to tumours when xenografted into nude mice [359]. We confirmed the identity of the BT088 cell line by STR matching. (Figure

4.1A,B). Several studies have demonstrated that glioma cells can alter the behaviour of other cells in the microenvironment. For example, GBM cells have chemoattractant properties on host neural cells, which are attracted to migrate into the tumour mass [361, 362]. Moreover, conditioned media 139

(CM) from a GBM cell line has been shown to stimulate the self-renewal and proliferative capacity of NSCs in vitro [357]. To determine whether BT088 cells could similarly influence the proliferation or survival of other cells in the glioma microenvironment, we focused on interactions between these tumour cells and NSCs.

To first determine whether BT088 cells had contact-dependent or -independent effects on mNSCs, we used a transwell chamber assay, separating the two cell types with a porous (1 µm thick) membrane that allows for the transfer of macromolecules but not cells (Figure 4.2A). For this assay, mNSCs were isolated from the E13.5 dorsal telencephalon, which is the anlage of the neocortex, a site where oligodendroglioma tumours can develop. BT088 cells were placed in the upper chamber and mNSCs in the bottom chamber, and after 7 days in vitro (DIV), we monitored the formation of mNSC neurospheres (Figure 4.2A). mNSCs were plated at clonal density (8000 cells/ml) so that each sphere was derived from a single cell, allowing neurosphere number to be used as a measure of self-renewal [363]. We also did not move the plates during the 7 day culture period to reduce the risk of aggregation [363]. By following these rules, we found that mNSCs continuously exposed to secreted factors from BT088 cells formed 1.69-fold fewer neurospheres than mNSCs exposed to fresh media in the upper chamber (n=3; p<0.05; Figure 4.2C-F). BT088 tumour cells thus secrete a factor that is inhibitory to mNSC self-renewal and proliferation (Figure

4.2G).

As an additional control, we collected CM from BT088 cells 24 hrs after plating 106 cells in fresh media. The BT088 CM was placed in the upper chamber over mNSCs plated in fresh media in the lower chamber (Figure 4.2A). Due to the free diffusion of most macromolecules, and the volume differences between the upper (1.5ml) and lower (2.7ml) chambers, this amounted to

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the exposure of mNSCs to the equivalent of 35% CM. After 7 DIV, there was a 1.87-fold increase in the number of neurospheres generated in the lower chamber (n=3; p<0.001; Figure 4.2C-F). Of note, this experiment differed from the exposure of mNSCs to BT088 cells since the cells continuously produce and secrete factors, whereas the CM provides a limited source of factors.

BT088 cells thus influence the proliferation of mNSCs, but this effect appears to be dosage sensitive, with stimulatory effects at low concentrations and inhibitory effects at high concentrations (Figure 4.2G). We set out to examine this dosage sensitivity in more detail.

4.5.2 BT088 cells secrete bioactive molecules that have dosage-specific effects on neural stem cell self-renewal, proliferation and survival

To begin to distinguish between the opposing effects of the BT088 cells and the BT088

CM in the transwell chamber assay, and possible dosage effects, we performed a second assay in which we directly exposed mNSCs to four different concentrations of CM (25%, 50%, 75%, 100%;

Figure 4.2B). CM was collected 24 hrs after plating 106 BT088 cells in fresh media, as described above. We first assessed mNSC self-renewal by monitoring neurosphere formation, counting the number of spheres that formed in each concentration of CM, and normalizing to the number of spheres observed in fresh media (Figure 4.2H-M). Strikingly, while the total number of neurospheres increased 1.42-fold when mNSCs were grown in 25% CM (n=3; p<0.001), as the concentration of CM increased, total sphere number declined, with significant reductions observed in 75% CM (1.70-fold decrease; n=3; ;<0.001) and 100% CM (10.41-fold decrease; n=3; p<0.001;

Figure 4.2H-M).

Neurospheres are a mixture of stem cells, proliferating progenitors, and differentiated neural cells, and the size of the sphere can be used as an indication of the proliferative potential of

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the progenitor pool [363]. We thus assessed sphere size 7 days after culturing mNSCs in different concentrations of BT088 CM. While the spheres grown in 25% CM were not significantly larger than those grown in fresh media, sphere size declined significantly in 50% (1.36-fold decrease; n=3; p<0.001), 75% (2.35-fold decrease; n=3; p<0.001), and 100% (2.77-fold decrease; n=3; p<0.001) CM, indicating that the proliferative potential of these cells had declined (Figure 4.2N).

When the neurospheres were dissociated and a viable cell count was performed using trypan blue exclusion, there was a 1.55-fold relative increase in viable cell number in mNSCs grown in 25%

CM compared to fresh media (n=3; p<0.001), indicating that BT088 CM confers a proliferative and/or survival advantage at low concentrations (Figure 4.2O). In contrast, the number of live cells declined precipitously in 50% CM (3.12-fold decrease; n=3; p<0.001) and 75% CM (25.64-fold decrease; n=3; p<0.001; Figure 4.2O), and in 100% CM, the vast majority if not all cells were necrotic, so viable cells were not counted (Figure 4.2O). Conversely, the percentage of dying cells increased 3.57-fold in 75% CM (n=3; p<0.001; Figure 4.2P).

Taken together, these data indicate that BT088 CM has a biphasic effect on the self- renewal, proliferation and survival of mNSCs, with low levels of CM stimulatory and higher levels inhibitory.

4.5.3 BT088 cells secrete bioactive molecules in EVs

One mode of intercellular communication involves the trafficking of extracellular vesicles

(EVs), which are secreted membrane-enclosed structures that deliver protein and nucleic acid cargo to neighboring cells (Figure 4.3A) [270, 271]. Previous studies have shown that EV- mediated uptake of oncogenes by host cells contributes to aberrant growth factor signaling,

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proliferation and angiogenesis [267, 358, 364]. We thus asked whether BT088 cells secrete bioactive cargo in EVs.

To first determine whether BT088 cells secrete EVs, we collected CM 24 hr post-plating, as described above, and performed a sequential centrifugation purification protocol [271]. Using electron microscopy to visualize the vesicles, we revealed that they were enclosed in a characteristic lipid bilayer, and the vesicles ranged in size from 40 nm to over 700 nm (Figure

4.3B). EVs range in size from 30-150 nm (exosomes) up to 1000 nm (microvesicles, MVs) [271], so these particles were within the expected size range. We further validated that these vesicles were indeed EVs by examining the expression of a series of markers that have been associated with EVs, including flotillin and the tetraspanins CD63 and CD9 [271]. By Western blot, we detected flotillin, CD63 and CD9 in BT088 EVs and in total cell lysates from these cells, whereas these proteins were not detected (CD63, CD9), or detected at low levels (flotillin) in mNSCs

(Figure 4.3C). We thus have good evidence that BT088 cells do indeed secrete EVs.

We next asked whether the EVs secreted from BT088 cells carried bioactive cargo by adopting a Cre-based fluorescent reporter assay that was previously used to monitor the transfer of bioactive materials from EV-producing breast cancer and immune cells to recipient cells [365,

366]. BT088 cells were stably transduced with Cre recombinase and a GFP reporter using a piggybac transposon, while a recipient NIH-3T3 cell line was transduced with a dual-Cre-reporter that drives BFP expression in the absence of recombination and RFP expression after cre-mediated excision of a floxed stop cassette (Figure 4.3D,E). The two cell types were aggregated together in a 5:1 ratio (BT088:NIH-3T3) and cultured as a cell pellet for 3 DIV before examining the expression of the Cre reporter. After 3 DIV, RFP+ cells that were not also GFP+ (i.e., not arising from cell fusion) were detected, indicative of the transfer of Cre mRNA or protein to the recipient 143

cells (Figure 4.3F-F'''). We thus have evidence that bioactive cargo is secreted in the EVs found in

BT088 CM and that this cargo is transferred to neighboring cells.

4.5.4 BT088 CM effects are EV-mediated

We next asked whether the bioactive factors in the BT088 CM that influence mNSC self- renewal and proliferation were packaged in EVs. For this purpose, we again collected CM from

BT088 cells 24 hr after plating 106 cells, but this time, before exposing mNSCs to the CM, we first removed the EVs by sequential centrifugation. mNSCs were grown in BT088 CM-EVs for 7 DIV, and then neurosphere numbers were assessed (Figure 4.3G-L). Strikingly, removal of EVs blocked the stimulatory effects of the CM on mNSC proliferation, which generated the same number of neurospheres as mNSCs cultured in fresh media (Figure 4.2L). Moreover, the removal of EVs from the CM completely abolished the inhibitory effects of 75% and 100% CM, and instead, high concentrations of the CM-EVs increased neurosphere number (75% CM-EVs: 1.57-fold increase; n=3; p<0.001; 100%CM-EVs: 1.30-fold increase; n=3; p<0.01; Figure 4.3L). These data suggest that there are factors in the BT088 CM that can stimulate mNSC self-renewal, but these effects are blocked by inhibitory factors secreted in the EVs.

To assess whether the removal of EV factors also altered mNSC proliferation, we first assayed sphere size, which can be used as a surrogate measure of proliferation. The size of mNSC spheres grown in fresh media or 25%-100% CM-EVs were all the same, indicating that the removal of EVs blocked the inhibitory effects of high levels of BT088 CM on mNSC proliferation (Figure

4.3M). We also used the trypan blue exclusion assay to assess live cell number (Figure 4.3N). The stimulatory effects of 25% CM on mNSC proliferation was lost when EVs were removed, as were the inhibitory effects of 75% CM and 100% CM, with viable cell number not statistically different

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in any condition (Figure 4.3N). Finally, the dose-specific effects of the CM on cell death was lost upon the removal of EVs, with no differences observed in the number of dead cells in any condition

(Figure 4.3O). Taken together, these studies confirm that the dosage-specific effects of the BT088

CM are EV-mediated.

4.5.5 Proteome of BT088 EVs includes exosome markers and many signaling molecules

To identify bioactive factor(s) in BT088-secreted EVs, we performed a proteomics analysis. CM was collected from BT088 cells 24 hr post-plating, and EVs were removed by sequential centrifugation, as described above. EVs were lysed and their contents run on an SDS-

PAGE gel, which was silver stained to visualize proteins in different size ranges (Figure 4.4A).

The gel was cut into nine blocks encompassing proteins of different sizes, and subjected to

MS/MS. 1294 proteins were identified in total, revealing the complexity of the BT088 EV proteome (Table 4.1). Cytoscape was used to examine biological pathways. Exosome pathway components were first extracted, revealing a subnetwork of proteins involved in EV biosynthesis and secretion, including ESCRT-dependent and independent pathways (Figure 4.4B,C). Further analysis of GO terms identified multiple signaling pathways that were enriched in BT088 EVs, including receptor tyrosine kinase (RTK), Akt, Jak/Stat, mTOR, p53, TGF, Thyroid hormone, Wnt and CREB signaling pathways (Figure 4.4D). Interestingly, misexpression of hyperactivated forms of Ras, Mek and Akt in the embryonic and early postnatal brain can induce a glioblastoma-like phenotype in vivo [367-370]. We thus focused on RTK signaling, asking whether this signaling pathway can act non cell autonomously to influence mNSC behaviour.

4.5.6 Activation of RTK signaling induces gliogenesis in a non-cell autonomous fashion

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We reasoned that if RTK signaling underlies the non-cell autonomous effects of BT088

EVs on mNSC self-renewal and proliferation, then we should be able to see non-cell autonomous effects on neighboring neural cells when this pathway is ectopically activated in vivo. A major downstream effector of RTK signaling is the RAS→RAF→MEK→ERK signal transduction cascade, which drives cellular proliferation in both cancer and development. Most glial brain tumors, specifically, GBMs have activated RAS/ERK signaling due to mutations in receptor tyrosine kinases (RTKs), or in the Ras-GAP Neurofibromin (NF1), a negative regulator of RTK signaling, or in BRAF and other downstream effectors [249, 371-373]. Interestingly, one of the downstream effector of the RAS signaling pathway is CIC, which is commonly mutated in ODG.

We found several RTK effector molecules in the BT088 EVs, including HRAS, KRAS, MAPK3, and GRB2, suggesting that these tumour cells may be able to activate RAS/ERK signaling in neighboring neural cells.

GBMs can be modeled in the murine brain by ectopically activating oncogenic Ras signaling in neural progenitors, either misexpressing activated components of this pathway alone at embryonic and early postnatal stages [368, 369], or together with other genetic hits in the adult brain [367]. To simplify, we tested whether RTK signaling could act non-cell autonomously in the embryonic brain, at a stage when activation of Ras alone can induce gliomagenesis [368]. To test this model, we used in utero electroporation to introduce activated components of RTK signaling in the E12.5 murine brain in vivo, misexpressing Egfrviii (Figure 4.4E,E', E''), an activated EGF receptor that is found in several gliomas [267], RasV12 (Figure 4.4F,F', F''), a constitutively active

(CA) form of RAS [374], and bRafv600e (Figure 4.4G,G', G''), a CA-Raf that is highly mutated in gliomas [375]. Note that misexpression of RasV12, bRafV600E, and MekCA mimics the overactivity of the RAS/ERK pathway observed in gliomas, and we previously showed that 146

activation of this pathway induces a proliferative, glioblast fate, but here we asked whether these effects were non-cell autonomous. To monitor gliogenesis, we examined the expression of Sox9, which is required to specify a glial identity [376, 377]. In pCIG2 control electroporations, Sox9 was expressed in VZ progenitors and only in a few scattered cells outside the VZ (Figure 4.4D,D').

In contrast, misexpression of EGFRviii (Figure 4.4E,E'), Rasv12 (Figure 4.4F,F') and bRafv600e

(Figure 4.4G,G') all induced ectopic Sox9 expression outside of the VZ, with the loss of apical ventricular contacts a known feature of glial precursors [378]. Moreover, upon close inspection it was evident that Sox9 was expressed in GFP+ electroporated cells and in GFP-negative cells surrounding the transfected patch. This data provides support for the idea that activation of

RAS/ERK signaling can have non-cell autonomous effects on cell fate in vivo.

In another assay to test non-cell autonomy, we analyzed human patient derived ODG samples to see whether there was any evidence of the non-cell autonomous activation of RTK signaling in neighboring, non-transformed cells. In general, ODG tumours do not have mutations traditionally observed in GBM, which have amplifications or activating mutations in RTKS (e.g.,

EGFR, PDGFRA, MET) or a loss of NF1 [249, 265, 371-373], all of which activate downstream

RAS/ERK signaling. Nevertheless, in our profiling of the EV content of BT088 cells, we did observe several RTK signaling molecules, prompting us to ask whether there was any evidence of the non-cell autonomous transfer of these signaling molecules to activate ERK signaling in neighboring, non-transformed cells.

To identify ODG cells and distinguish them from ‘normal’ neural cells, we stained for

IDHMR132H as this antibody recognizes a mutant form of IDH that is only present in ODG tumour cells. As a corollary, the non-transformed neural cells do not express IDHMR132H, and

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we asked whether these ‘normal’ cells expressed an activated form of ERK1/2 phosphorylated on

T202/Y204 (i.e., pERK), which is a readout of RTK signaling (Figure 4.4H-Iʹʹʹ). Interestingly, while pERK expression was not widespread, as expected of this tumour type, ‘normal’

IDHMR132H-negative cells expressed pERK in many cases (white arrows in Figure 4.4Iʹ-Iʹʹʹ).

Taken together, this data supports the non-autonomous response of neighboring neural cells to the

ODG tumour cells.

4.5.7 EGF is secreted in BT088 EVs and mNSCs express Egfr and downstream signaling molecules

One of the striking features of the BT088 CM was that it had dose-dependent effects, inducing proliferation at low levels (25%) and inhibiting growth at higher levels. To try and identify which factor might be responsible for this dose-dependency, we searched the literature and found evidence that EGF has previously been shown to stimulate breast cancer proliferation at low levels whereas it blocked proliferation at higher levels [379]. Moreover, in GBMs, a constitutively active form of the EGF receptor (EGFRvIII) is packaged in EVs and has an oncogenic effect upon transfer to recipient cells [267], consistent with the idea that this signaling pathway can influence ‘non-transformed’ neighboring cells (Figure 4.5A). However, EGFRvIII is not a common mutation in ODG, prompting us to ask whether the EGF ligand was instead packaged in ODG EVs.

Because the processed form of EGF is very small (~6kDa), it was not detected in our MS data set (Figure 4.4A-C). To detect EGF, we therefore performed an EGF ELISA on BT088 cell free extracts, and on extracts of the purified EVs from this cell line (Figure 4.5B). Within BT088 cell lysates, EGF protein was detected at 69.98±3.38 pg/µl, while in the BT088-derived EVs, the 148

concentration of EGF was 52.71±16.77 pg/µl (Figure 4.5B). EGF is thus produced by BT088 cells, and this protein is packaged in EVs.

If the 25% CM influenced neighboring neural cells through the transfer of EGF and possibly other RTK signaling molecules, we reasoned that we may see the activation of this signaling pathway in mNSCs exposed to 25% CM. To test this idea, we examined the expression of downstream effectors of the RAS/ERK pathway (i.e., Erk, pErk, Etv5) in E13.5 mNSCs exposed to 25% BT088 CM for 7 DIV, as well as determining whether the Egfr receptor was expressed in these cells (Figure 4.5C-H). While we did not find a significant overall change in the expression of Erk, pErk, Etv5 or EGFR in mNSCs exposed to fresh media or 25% CM, it may be that we would see changes if this experiment were performed more acutely (i.e., after 24 or 48 hr), rather than after 7 DIV (n=3, p>0.1).

4.5.8 EGF has dosage-sensitive effects on neural stem cells

As mentioned above, it has been previously shown in breast cancer cells that high EGF levels induce cell toxicity [379]. Therefore, we asked whether the cell toxicity that we observed in mNSCs exposed to higher levels of 088-CM was due to exposure to higher levels of EV packaged

EGF. To address the sensitivity of mNSCs to EGF dosage, we cultured mNSCs in media containing different concentrations of EGF (0, 10, 20, 50, 100, 150 ng/ml) for 7 DIV (Figure 4.

5I-R). As EGF concentrations increased, there was an overall decline in the number of neurospheres generated (Figure 4.5P; n=3 for each condition; 10ng, p<0.01; 20ng, p<0.01; 50ng, p<0.005; 100ng, p<0.005; 150ng, p<0.005). An even more dramatic change was seen when counting live cells using trypan blue exclusion, with the higher concentrations of EGF clearly toxic to the cells (Figure 4.5Q; n=3 for each condition; 2ng, p<0.05; 100ng, p<0.05; 150ng, p<0.005).

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In addition, a corresponding increase in cell death was observed when EGF concentrations were increased (Figure 4.5R; n=3 for each condition). Taken together, these results suggest that EGF is stimulatory at lower concentrations, promoting the proliferation of mNSCs, whereas EGF has toxic effects at higher concentrations.

4.5.9 EGF effects on neural stem cells are sensitive to glucose levels

In a previous study in breast cancer cells, it was shown that the toxicity of EGF at higher concentrations was rescued if glucose levels were increased [379]. To determine whether a similar protective effect of glucose was observed in neural cells, we cultured mNSCs in different EGF (0-

150ng/ml) and glucose (5mM, 15mM, 25mM) concentrations over a period of 7 DIV (Figure 4.6A-

Cʹʹʹʹʹʹ). Interestingly, while there was a decline in neurosphere number at the higher concentrations of EGF, glucose levels did not significantly alter sphere number (Figure 4.6D; n=3 for each condition). In contrast, using a trypan blue exclusion assay to count live cells revealed that the live cell number began to decline when EGF levels were at 20 ng/ml and higher, and that this toxic effect was rescued at the higher concentrations of glucose (Figure 4.6E; n=3 for each condition).

Sphere size was also used as a measure of proliferation, and it was found that there was an increase in sphere size with increasing amounts of EGF in every glucose level (5mM, 15mM, 25mM, Figure

4.6 F,G,H, respectively; n=3 for each condition; p<0.005), but this size increase plateaued at about

20-50 ng/ml EGF, and the sizes began to taper off afterwards. Similarly, the effects of glucose on neurosphere size at each EGF concentration (2, 10, 20, 50, 100, 150 ng/ml; Figure 4.6I-O, respectively) was further enhanced at the higher levels of glucose (15 and 20 mM; n=3 for each condition; p<0.005). Taken together this data suggests that the EGF response by mNSCs is regulated by glucose concentration, with toxicity reduced when glucose concentrations are higher.

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EGF has also been shown to increase glucose consumption [379], so we assessed the glucose consumption rate of mNSCs, comparing glucose levels after 48 hr and 6 days in culture with different concentrations of BT088 CM (Table 4.2). We calculated glucose consumption by subtracting the starting (48 hr) and ending (6 DIV) levels of glucose, and then divided by the final number of cells to get a sense of the amount of glucose consumed by individual cells. There was a striking increase in glucose consumption at the higher levels of CM (75% and 100%), suggesting that EGF along with possibly other factors in the CM are promoting a large increase in the amount of glucose taken up by each cell (Table 4.2). How this increase in consumption relates to the toxicity of the CM remains to be determined.

Taken together, our data suggests mNSC growth is influenced by both, EGF and glucose concentrations, such that, high EGF leads to cell toxicity that is rescued by higher glucose concentrations.

4.5.10 Altering exosome secretion influences the survival of BT088 cells in vitro

Exosomes are generated through several biogenetic pathways, the major ones including neutral sphingomyelinases (nSmase), which hydrolyse sphingomyelin to ceramide [380], and endosomal sorting complex required for transport (ESCRT) [271]. In contrast, the larger MVs are derived from the shedding of membrane-enclosed vesicles from the plasma membrane, and their biogenesis is dependent on other enzymes such as acidic sphingomyelinases (aSmase), and other effectors [278]. We assessed whether BT088 cell-cell interactions may depend on the nSMase pathway of exosome secretion. We first showed by Western blotting that BT088 cells express nSMase2, which is encoded by Smpd3 [381] (Figure 4.7A). We then used a transposase-based approach to knockdown Smpd3 by stable integration of an shSmpd3IRESGFP cassette into the

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host genome, confirming Smpd3 knockdown in HEK293 cells (Figure 4.7B). Notably, the knockdown of Smpd3 has previously been shown to reduce EV secretion [380].

We next generated stable BT088 cell lines that were nucleofected with shSmpd3 or a shScrambled control vector, and plated these cells at clonal densities. After 10 DIV, we counted tumourspheres (Figure 4.7C,C',D,D'), revealing that the knockdown of Smpd3 led to a significant increase in the number (1.97 fold increase, n=3; p<0.001; Figure 4.7E) and size (1.23 fold increase; p <0.001; Figure 4.7F). To confirm that the knockdown of Smpd3 was stimulatory for the growth of BT088 cells, we also inhibited the nSMase2 pathway pharmacologically using the drug,

GW4869 [277] (Figure 4.7G-I). We obtained the same phenotype as seen by blocking nSMase2 genetically, which was an increase in the number (1.65-fold increase, p<0.001; n=3; Figure 4.7J) and size (1.1-fold increase, p<0.001; n=3; Figure 4.7K) of tumorspheres. The converse was true when we overexpressed Smpd3 to increase the production of EVs [380]. In BT088 cells nucleofected with a Smpd3 gain-of-function piggybac construct, there was a sharp decline in the number of tumourspheres generated after 10 DIV (Figure 4.7L-Nʹ).

Taken together, our findings suggest that blocking the nSMase pathway genetically or pharmacologically increases the proliferation of ‘tumorspheres’, while an increase in the nSMase expression, inhibits cell proliferation in the BT088 cells. Future studies are aimed at xenografting these cell lines into the adult mouse brain to see whether altering exosome secretion alters tumour formation in vivo.

4.6 DISCUSSION

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EVs regulate diverse biological processes, establishing morphogenetic gradients and modulating signal transduction [382]. Specifically, tumour-derived EVs have the capacity to alter stromal and neural cells in other malignancies [383]. For instance, when human NSCs (hNSCs) are cultured in GBM conditioned media, they increased their rate of proliferation and elevate the expression of other signaling molecules (e.g., EGF, EGFR, VEGF, VEGFR, PDGF, PDGFR)

[357]. In our study, we demonstrated that bioactive EVs are secreted from the ODG cell line,

BT088, and showed that these EVs can alter the proliferative capacity of mNSCs in a dose- dependent fashion; at lower concentrations, BT088-derived EVs promote the proliferation of mNSCs, while at higher concentrations, BT088-derived EVs are toxic to mNSCs. We investigated the underlying mechanisms and identified EGF as at least one EV enclosed dose-responsive factor, revealing further that the response of mNSCs to EGF is glucose sensitive. Taken together these studies reveal the importance of EVs as a target for brain tumours, as these secreted vesicles contain cargo that can influence the behaviour of surrounding ‘normal’ neural cells and possibly other stromal cells. Since, we have studied just one ODG cell line, BT088, to understand the tumor- neural interactions, using another ODG cell line, BT054, or any other GBM cell line to study similar interactions should be perused to fully understand the tumor-neural interactions. Another caveat to our study is that we used mNSCs to study the effects of ODG secretome. Although, mNSCs are a useful tool to establish key experiments, they are not the ideal cell type to recapitulate the in vivo conditions. Therefore, we have initiated direct differentiation of hNSCs to astrocytes and oligodendrocytes to study effects of the ODG secretome in a more glial environment, which is more comparable to in vivo environment. However, we discuss the impact of our studies below.

In vitro screens have identified many drugs that have activity against glioma cells, but when these drugs are tested in vivo, they often do not have the same results. The discrepancy 153

between in vitro and in vivo data likely reflects the inability to faithfully recapitulate in vivo cellular interactions between cancer cells and other cells in the microenvironment in a dish [384]. Thus, even though many driver mutations have been identified in many types of tumours, we know very little about how these mutated cells interact with other cells in the environment. EVs are an emerging area of focus, not only because they may be a therapeutic target, but also because they may even serve as a biomarker for disease progression. Indeed, gliomas secrete EVs into the bloodstream, and these EVs carry oncogenes such as EGFRvIII [267]. Moreover, the content of glioma EVs changes as GBMs undergo a proneural to mesenchymal transition, providing a window to what is going on within the tumour [297]. One possibility from a diagnostic perspective is that monitoring EVs in the serum may provide a non-invasive way to determine whether therapeutics are effectively targeting glioma cells.

We demonstrated that BT088 EVs have non-cell autonomous effects on mNSC proliferation, and we then used a proteomic analysis to identify candidate factors that mediate these effects. We detected several molecules in BT088 EVs that are involved in RTK signaling, including HRAS, KRAS, MAPK3, GRB2 and CDC42. To determine whether the activation of

RTK signaling could have non-cell autonomous effects in vivo, we performed two assays. First, gliomas can be modeled in animal models in vivo by misexpressing EGFRvIII-, RasV12- or bRafV600E in neural stem cells in the brain [368, 369]. We used this assay to show that misexpression of EGFRvIII-, RasV12- and bRafV600E in the embryonic neocortex gave rise to the non-cell autonomous, ectopic expression of Sox9, which is a glioblast marker in vivo [368]. In addition, we showed that there is pERK activation in non-IDHMR132H+ cells in ODG tumour samples from patients, indicating that tumour cells can upregulate RAS/ERK signaling in their neighbors. One of the RTK signaling molecules that we found in BT088 EVs that may mediate 154

these effects is EGF. Moreover, we found a dose dependent response of mNSCs to increasing

EGF concentrations as was seen with MDA-468 breast cancer cells [379]. However, it is likely that ODG cells secrete other factors involved in the effect of the derivative EVs on mNSCs, and further analyses of the EV proteome may identify additional bioactive molecules.

Recent reports have indicated the inverse relationship between blood glucose levels and brain cancer risk [379, 385]. These reports have suggested that increasing glucose consumption does not lead to favorable patient outcomes with glioma [385]. From our study, we found that the relative glucose consumption of mNSCs in 088-CM increased when mNSCs were exposed to the higher toxic levels of 088-CM. We further found that an increase of glucose in the culture media with increasing EGF levels protected against EGF cell toxicity, and that the proliferation of mNSCs increased with increasing glucose levels. All of these data are indeed suggestive that ODG tumorigenicity is also inversely proportional to glucose consumption, which will be an area of focus in the future.

Finally, tumour-tumour cell interactions may also underlie, in part, the molecular and cellular heterogeneity of tumour cells, and their progression from lower to higher grade, or the transition from proneural to mesenchymal phenotypes [297]. Indeed, when we knocked down

Smpd3 to reduce EV production, we saw a dramatic increase in the proliferation of BT088 cells, suggesting that these cells secrete EVs that block their growth. Interestingly, previous attempts to block EV secretion in glioma cells were not successful as the genetic deletion of aSmase [278], or nSmase [278], or inhibition of Rab27A/B [282] did not block the vesiculation of brain tumour cells.

In contrast, in our hands, either knocking down Smpd3 genetically or pharmacologically, we influenced the proliferative behavior of BT088 cells, suggesting that our blockade was successful.

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Moreover, GW4869 decreased protein content, indicating that an EV blockade occurred. We also observed the converse, which is that the overexpression of Smpd3 blocked BT088 cell growth, suggesting that targeting this pathway may be a novel therapeutic approach. Our future xenografting experiments should help to determine whether Smpd3 misexpressio would be useful in vivo.

In summary, by profiling the ODG vesiculome in BT088 cells, we have built the foundation for translating our findings to identifying biomarkers and intervention strategies in the future.

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4.7 FIGURES AND FIGURE LEGENDS

Figure 4.1 Validation of BT088 cell line. (A,B) Short tandem repeat matching using a 16-panel

Identifiler panel to compare DNA samples purified from an ODG tumour sample from patient germline 9672 (A) and from BT088 cells (B). Red circles highlight loss of hetrozygosity at loci at D18551, D2S1338 and FGA markers in allele 2 between the patient and BT088 DNA samples.

This is a feature of cancer. The matching (without gains of new repeats) confirms that the line was derived from this patient.

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Figure 4.2 Dose-dependent effects of BT088 conditioned media. (A,B) Schematic representation of transwell chamber assay (Experiment #1) and conditioned media (CM) assay

(Experiment #2) that were used to examine the non-cell autonomous effects of BT088 cells on mNSCs. (C-G) Boyden chamber assay with mNSCs in bottom chamber and either fresh media

C), BT088 cells (D) or B088 CM in the top chamber (E). Quantitation of the fold change in neurosphere numbers when mNSCs were co-cultured after DIV (F). Summary of the effect of

088-CM on mNSCs (G). (H-P) mNSCs grown in fresh media (H), 25% 088-CM (I), 50% 088-

CM (J), 75% 088-CM (K) and 100% 088-CM (L) for 7DIV. Quantitation of the fold change in neurosphere numbers compared to fresh media after 7 DIV (M). Quantitation of sphere diameter after 7DIV (N). Quantitation of fold change in live cell numbers when mNSCs were cultured in different conditions for 7DIV (O). Quantitation of the fold change in cell death percentage when mNSCs were cultured in different conditions for 7DIV (P). CM, conditioned media; DIV, days in vitro; mNSCs, mouse neural stem cells; cx, neocortex; lge, lateral ganglionic eminence; mge, medial ganglionic eminence.

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Figure 4.3 BT088 cells secrete bioactive EVs. (A)Schematic of endosomal secretion of EVs.

(B) Electron microscopy of EVs purified from BT088 cells 24h post culture. (C) Western blots of EV enriched proteins such as flotillin, CD63 and CD9 along with β-actin in the BT088-EV lysate, BT088 whole cell lysate and mNSC whole cell lysate. (D-F''') Schematic of the pellet assay involving the aggregation of Cre-transfected GFP+ BT088 cells mixed in a 1:1 ratio with

NIH3T3 cells transfected with a dual BFPloxPDsRed reporter (D,E). Analysis of GFP, BFP and dsRed expression in pellets after 3 DIV (F-Fʹʹʹ). (G-O) CM-EV assay, showing effects on mNSCs cultured in fresh media (G), 25% 088-CM minus EVs (H), 50% 088-CM minus EVs (I),

75% 088-CM minus EVs (J), 100% 088-CM minus EVs (K). Quantitation of the fold change in neurosphere numbers after 7 DIV (L). Quantitation of the fold change in live cell numbers after

7DIV (M). Quantitation of the fold change in cell death when mNSCs after 7DIV (N).

Quantitation of diameter of the neurospheres when mNSCs after 7DIV (O). (P) Summary of the effect of mNSC growth in 088-CM minus EVs. (Q) Schematic of one of the modes of communication of BT088 cells with mNSCs. CM, conditioned media; mNSCS, mouse neural stem cells; N, nucleus; ER, endoplasmic reticulum; EE, early endosome; LE, late endosome; LY, lysosome; MVBs multivesicular bodies; EVs, extracellular vesicles; Ne, neurons; OL, oligodendrocytes; AS, astrocytes; EC, endothelial cells; TC, tumor cells.

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Figure 4.4 Molecular profiling of BT088 derived EVs and analysis of the non-cell autonomy of RTK signaling. (A-C) Silver staining of BT088 derived EV samples run on a SDS-PAGE gel

(A). Blue boxes indicate the band-regions that were cut to generate 9 samples for MS/MS analysis. Cytoscape of all proteins enriched in BT088 EVs, with proteins associated with extracellular exosomes pulled out to the left (B). Enlargement of proteins cluster enriched in EVs

(B'). List of enriched signaling pathways identified in BT088-derived EVs (C). (D-Gʹʹ) In utero electroporation of pCIG2 (D,Dʹ,D''), EGFRviii (E,Eʹ,E''), RasV12 (F,Fʹ,F''), bRaf-b600E

(G,Gʹ,G''), showing GFP+ electroporated cells in green (D'-G') and Sox9+ gliobasts in red (D''-

G''). (H-Iʹʹʹ) Sections of ODG tumour labeled with secondary antibodies only as a negative control (H'-Hʹʹʹ) and with pERK (I') and IDHMR132H (I'') and a merged image (I'''). DAPI staining is shown in H and I. White arrows in Eʹ, Eʹʹ, Eʹʹʹ, Fʹ, Fʹʹ, Fʹʹʹ, Gʹ, Gʹʹ, Gʹʹʹ indicate Sox9+

GFP- cells.White arrows in Iʹ, Iʹʹ, Iʹʹʹ indicate pERK+ IDHMR132H- cells. Ctx, neocortex.

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Figure 4.5 EGF has dosage specific effects on mNSCs. (A) Schematic of EGF signaling pathway. (B) ELISA analysis of EGF levels in BT088 cells and derived EVs. (C-H) Western blot anlaysis of Erk and pErk (C), and Egfr and Etv5 (F). Densitometry analysis of protein levels for

Erk (D), pErk (E), Etv5 (G), and Egfr (H). (I-R) mNSCs cultured in 0ng/ml EGF (I), 2ng/ml

EGF (J), 10ng/ml EGF (K), 20ng/ml EGF (L), 50ng/ml EGF (M) and 100ng/ml EGF (N),

150ng.ml EGF (O) for 7 DIV. Quantitation of the fold change in the neurosphere numbers (P).

Quantitation of the fold change in the live cell numbers (Q). Quantitation of the fold change in the dead cell numbers (R). mNSCS, mouse neural stem cells.

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Figure 4.6 Increased glucose levels rescue high EGF toxicity of mNSCs. (A-Aʹʹʹʹʹʹ) mNSC grown in 5mM glucose at 0ng/ml EGF (A), 2ng/ml (Aʹ), 10ng/ml (Aʹʹ), 20ng/ml (Aʹʹʹ), 50ng/ml

(Aʹʹʹʹ), 100ng/ml (Aʹʹʹʹʹ), and 150ng/ml (Aʹʹʹʹʹʹ). (B-Bʹʹʹʹʹʹ) mNSC grown in 15mM glucose at

0ng/ml EGF (B), 2ng/ml (Bʹ), 10ng/ml (Bʹʹ), 20ng/ml (Bʹʹʹ), 50ng/ml (Bʹʹʹʹ), 100ng/ml (Bʹʹʹʹʹ), and 150ng/ml (Bʹʹʹʹʹʹ). (C-Cʹʹʹʹʹʹ) mNSC grown in 25mM glucose at 0ng/ml EGF (C), 2ng/ml

(Cʹ), 10ng/ml (Cʹʹ), 20ng/ml (Cʹʹʹ), 50ng/ml (Cʹʹʹʹ), 100ng/ml (Cʹʹʹʹʹ), and 150ng/ml (Cʹʹʹʹʹʹ). (D)

Quantitation of fold change in neurosphere numbers in different EGF and glucose levels (5mM glucose (black line; 15mM glucose, blue line; 25mM glucose, red line). (E) Quantitation of fold change in live cell numbers when mNSCs in different EGF and glucose levels (5mM glucose, black line; 15mM glucose, blue line; 25mM glucose, red line). (F-H) Sphere size comparing the various EGF concentrations with 5mM glucose (F), 15mM glucose (G), 25mM glucose (H).

(0ng/ml, white circles; 2ng/ml grey circles; 10ng/ml, cyan circles; 20ng/ml, blue circles;

50ng/ml, red circles; 100ng/ml, yellow circles; 150ng/ml, green circles). (I-O) Sphere sizes comparing the three glucose concentrations with 0ng/ml EGF (I), 2ng/ml (J), 10ng/ml (K),

20ng/ml (L), 50ng/ml (M), 100ng/ml (N), 150ng/ml (O), 5mM glucose (white circles; 15mM glucose, red circles; 25mM glucose, blue circles).

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Figure 4.7 Altering nSMase activity in BT088 cells influences tumour cell proliferation.

(A,B) Smpd3 is expressed in BT088 cells and in mNSCs (A). shSmpd3 efficiently knocks down

Smpd3 in HEK cells (B). (C-F) Nucleofection of BT088 cells with shScr (C,Cʹ), and shSmpd3

(D,Dʹ). Quantitation of GFP+ tumorsphere numbers (E) and sphere diameter (m) (F) after 10

DIV. BCA assay to measure protein concentration of EVs derived from a 48h CM of BT088 cells with GW4869 (G). (H-K) BT088 cells treated with DMSO as control (H) and 10ug

GW4869 (I) for 5 DIV. Quantitation of the number of tumorspheres (J) and the size of tumorspheres (um) (K) generated after 5DIV. (L-N) Smpd3 gain of function induces increase in

Smpd3 expression in the BT088 cells (L). BT088 cells nucleofected with GFP ctrl (M,Mʹ) and

Smpd3 (N,Nʹ) after 5DIV. mNSC, mouse neural stem cells; HEK, human embryonic kidney cells; ctrl, control; BF, bright field.

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4.8 Tables

Table 4.1 General summary of the signaling pathways enriched in the BT088 secretome.

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GeneSet / Nodes / Proteins in Network Pathways Detected in Network

Akt Signaling Pathway

PI3K-Akt PRKCA,JAK1,RPS6,HSP90B1,RHEB,HSP90AB1,HSP90AA1,PPP2R1A,GRB2,R signaling AC1,HRAS,PPP2CA,GNB2,GNB1,GNB4,YWHAE,YWHAB,YWHAQ,YWHAG, pathway(K) YWHAH,YWHAZ,MAPK3,KRAS

Class I PI3K PRKACA,PRKDC,SFN,HSP90AA1,SRC,YWHAE,YWHAB,YWHAQ,YWHAG, signaling events YWHAH,YWHAZ mediated by Akt(N)

CREB Pathway

transcription PRKCA,GRB2,HRAS,GNAS,MAPK3 factor creb and its extracellular signals(B)

ESCRT- independent pathway

Sphingolipid PRKCA,ROCK2,FYN,PPP2R1A,RAC1,HRAS,RHOA,GNAI2,PPP2CA,MAPK3, signaling BAX,KRAS pathway(K)

ESCRT- dependent pathway

Syndecan-1- PRKACA,CASK,SDCBP,MAPK3 mediated signaling events(N)

Syndecan-2- PRKACA,RACK1,SRC,EZR,HRAS,RHOA,CASK,SDCBP,MAPK3,BAX mediated signaling events(N)

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Jak-Stat Signaling Pathway

stat3 signaling JAK1,MAPK3 pathway(B)

mTOR Signaling Pathway

mTOR signaling PRKCA,RPS6,RHEB,ATP6V1E1,ATP6V1C1,GRB2,HRAS,SEC13,RHOA,ATP6 pathway(K) V1A,ATP6V1H,MAPK3,KRAS

mTOR signaling PRKCA,SFN,EEF2,RHEB,EIF4A1,HRAS,YWHAE,YWHAB,YWHAQ,YWHAG, pathway(N) YWHAH,YWHAZ,MAPK3,KRAS

p53 Signaling Pathway

p53 pathway(N) RPL5,RPL23,RPL11,CSNK1A1,CSE1L,CSNK1E,PPP2CA

RTK Signaling Pathway

ErbB1 CYFIP2,NCKAP1,PRKCA,SFN,ARF4,ABI1,RPS6,ARPC4,ARPC2,ARPC3,RAB5 downstream A,ACTR3,ACTR2,SRC,CDC42,PPP2R1A,GRB2,RAC1,HRAS,PPP2CA,PEBP1, signaling(N) YWHAE,YWHAB,YWHAQ,YWHAG,YWHAH,YWHAZ,MAPK3,KRAS

Signaling by PSMD6,PRKACG,PSMD2,PSMD3,PSMD1,PRKACA,PRKCA,PSME3,UBA52,J EGFR(R) AK1,PSMA5,PSMA6,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5, PSMB3,PSMB1,PSMC5,PSMC6,PSMC3,PSMC1,PSMC2,CUL3,SPTB,SRC,CDC 42,FYN,SPTBN1,SPTBN2,GRB2,SPTAN1,HRAS,PEBP1,PSMD11,PSMD13,YW HAB,MAPK3,KRAS

ErbB2/ErbB3 PRKACA,SRC,CDC42,GRB2,RAC1,HRAS,MAPK3,KRAS signaling events(N)

EGF receptor PRKCA,GRB2,RAC1,HRAS,PPP2CA,PEBP1,YWHAE,YWHAB,YWHAQ,YWH signaling AG,YWHAH,YWHAZ,MAPK3,KRAS pathway(P)

Signaling by PRKCA,UBA52,CUL5,HSP90AA1,SRC,STUB1,GRB2,HRAS,RHOA,KRAS ERBB2(R)

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EGF receptor SRC,TLN1,GRB2,HRAS,MAPK3,KRAS (ErbB1) signaling pathway(N)

Internalization RAB5A,SRC,CDC42,GRB2,HRAS,KRAS of ErbB1(N)

EGFR tyrosine PRKCA,JAK1,RPS6,SRC,GRB2,HRAS,MAPK3,BAX,KRAS kinase inhibitor resistance(K)

egf signaling PRKCA,GRB2,HRAS,MAPK3 pathway(B)

FGF signaling PRKCA,PPP2R1A,GRB2,RAC1,HRAS,PPP2CA,PEBP1,YWHAE,YWHAB,YW pathway(P) HAQ,YWHAG,YWHAH,YWHAZ,MAPK3,KRAS

Signaling by UBA52,SRC,PPP2R1A,GRB2,HRAS,PPP2CA,MAPK3,KRAS FGFR1(R)

Signaling by UBA52,SRC,PPP2R1A,GRB2,HRAS,PPP2CA,NCBP1,MAPK3,KRAS FGFR2(R)

Signaling by UBA52,SRC,PPP2R1A,GRB2,HRAS,PPP2CA,MAPK3,KRAS FGFR3(R)

Signaling by UBA52,SRC,PPP2R1A,GRB2,HRAS,PPP2CA,MAPK3,KRAS FGFR4(R)

Signaling by PSMD6,PSMD2,PSMD3,PSMD1,PSME3,UBA52,PRKAG1,JAK1,PSMA5,PSMA Insulin 6,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5,PSMB3,PSMB1,PSM receptor(R) C5,PSMC6,PSMC3,PSMC1,PSMC2,RPS6,CUL3,RHEB,SPTB,PPM1A,FYN,ATP 6V1E1,SPTBN1,ATP6V1C1,SPTBN2,GRB2,SPTAN1,HRAS,PEBP1,ATP6V1A, PSMD11,PSMD13,ATP6V1H,YWHAB,MAPK3,KRAS

Signaling by PSMD6,PSMD2,PSMD3,PSMD1,PSME3,UBA52,PRKAG1,JAK1,PSMA5,PSMA Type 1 Insulin- 6,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5,PSMB3,PSMB1,PSM like Growth C5,PSMC6,PSMC3,PSMC1,PSMC2,RPS6,CUL3,RHEB,SPTB,PPM1A,FYN,SPT Factor 1 BN1,SPTBN2,GRB2,SPTAN1,HRAS,PEBP1,PSMD11,PSMD13,YWHAB,MAPK Receptor 3,KRAS (IGF1R)(R)

Insulin signaling PRKACG,PRKACA,FASN,PRKAG1,EXOC7,PPP1CB,PPP1CC,RPS6,RHEB,CR pathway(K) K,GRB2,HRAS,PPP1CA,ACACA,MAPK3,KRAS

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Insulin EXOC7,EXOC4,EXOC5,CRK,GRB2,HRAS Pathway(N)

MAPK PRKACG,STMN1,PRKACA,PRKCA,FLNA,FLNB,FLNC,RAP1B,RAP1A,PPM1 signaling A,CRK,CDC42,GRB2,RAC1,HRAS,HSPA8,HSPA2,HSPB1,MAPK3,KRAS pathway(K)

MAPK6/MAPK PSMD6,PRKACG,PSMD2,PSMD3,PSMD1,PRKACA,PSME3,UBA52,PSMA5,P 4 signaling(R) SMA6,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5,PSMB3,PSMB1 ,PSMC5,PSMC6,PSMC3,PSMC1,PSMC2,CDC42,XPO1,RAC1,PSMD11,PSMD1 3,HSPB1

p38 mapk CDC42,RAC1,HRAS,HSPB1,MAPK3 signaling pathway(B)

PDGFR-beta CYFIP2,NCKAP1,PRKCA,SFN,ABI1,RAP1B,RAP1A,RAB4A,ARPC4,ARPC2,A signaling RPC3,RAB5A,ACTR3,ACTR2,CRK,SRC,FYN,PPP2R1A,YES1,GRB2,RAC1,HR pathway(N) AS,RHOA,PPP2CA,ARHGDIA,YWHAE,YWHAB,YWHAQ,YWHAG,YWHAH, YWHAZ,DNM2,MAPK3,KRAS

Signaling by PSMD6,PRKACG,PSMD2,PSMD3,PSMD1,PRKACA,PRKCA,PSME3,UBA52,J PDGF(R) AK1,PSMA5,PSMA6,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5, PSMB3,PSMB1,PSMC5,PSMC6,PSMC3,PSMC1,PSMC2,CUL3,SPTB,CRK,SRC ,FYN,SPTBN1,SPTBN2,GRB2,SPTAN1,HRAS,PEBP1,PSMD11,PSMD13,YWH AB,MAPK3,KRAS

pdgf signaling PRKCA,GRB2,HRAS,MAPK3 pathway(B)

RAF/MAP PSMD6,PSMD2,PSMD3,PSMD1,PSME3,UBA52,JAK1,PSMA5,PSMA6,PSMA3, kinase PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5,PSMB3,PSMB1,PSMC5,PSMC cascade(R) 6,PSMC3,PSMC1,PSMC2,CUL3,SPTB,FYN,SPTBN1,SPTBN2,GRB2,SPTAN1, HRAS,PEBP1,PSMD11,PSMD13,YWHAB,MAPK3,KRAS

influence of ras RAC1,HRAS,RHOA,MAPK3 and rho proteins on g1 to s transition(B)

ras signaling CDC42,RAC1,HRAS,RHOA,MAPK3 pathway(B)

Signaling events PRKACA,PRKCA,ARF1,HSP90AB1,HSP90AA1,SRC,CDC42,FYN,GRB2,RHO mediated by A,CTNNA1,CTNNB1,VCL,DNM2,MAPK3

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VEGFR1 and VEGFR2(N)

VEGF signaling PRKCA,SRC,CDC42,RAC1,HRAS,HSPB1,MAPK3,KRAS pathway(K)

Signaling by CYFIP2,CYFIP1,NCKAP1,PSMD6,PSMD2,PSMD3,PSMD1,PRKCA,PSME3,UB VEGF(R) A52,JUP,JAK1,PSMA5,PSMA6,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB 4,PSMB5,PSMB3,PSMB1,PSMC5,PSMC6,PSMC3,PSMC1,ABI1,PSMC2,CTNN D1,CUL3,HSP90AA1,SPTB,CRK,SRC,ROCK2,CDC42,FYN,SPTBN1,SPTBN2, GRB2,RAC1,SPTAN1,HRAS,RHOA,CTNNA1,PEBP1,PSMD11,PSMD13,YWH AB,HSPB1,MAPK3,KRAS

VEGFR1 PRKACA,PRKCA,HSP90AA1,MAPK3 specific signals(N)

TGF Signaling Pathway

Signaling by UBA52,USP9X,PPP1CB,PPP1CC,PPM1A,STUB1,XPO1,RHOA,STRAP,PPP1CA TGF-beta Receptor Complex(R)

Thyroid Hormone signaling pathway

Thyroid PRKACG,PRKACA,PRKCA,NOTCH1,RHEB,SRC,PFKP,HRAS,CTNNB1,MAP hormone K3,KRAS signaling pathway(K)

WNT Signaling Pathway

Beta-catenin PSMD6,PSMD2,PSMD3,PSMD1,PRKCA,PSME3,UBA52,CLTC,PSMA5,PSMA6 independent ,PSMA3,PSMA4,PSMA2,PSMA7,PSMB6,PSMB4,PSMB5,PSMB3,PSMB1,PSM WNT C5,PSMC6,PSMC3,PSMC1,PSMC2,AP2M1,PFN1,AP2A1,AP2A2,RAC1,RHOA, signaling(R) CTNNB1,PSMD11,PSMD13,GNB1

Wnt signaling PRKACG,PRKACA,CSNK2A2,PRKCA,CSNK1A1,CUL1,ROCK2,CSNK1E,CSN pathway(K) K2B,RAC1,RHOA,CTNNB1

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Table 4.2. Summary of glucose consumption. Shown is the concentration of CM that mNSCs were exposed to, the number of live mNSCs after 7 DIV, the initial glucose concentration after

48 hr in vitro, the final glucose concentration after 7 DIV. Total glucose consumption was calculated by subtracting the final glucose concentration from the initial concentration. Relative glucose concentration was calculated by dividing total glucose consumption by cell number.

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CM Cell Initial Final Total glucose Relative glucose concentr number [glucose] [glucose] consumption consumption (nmol ation (x104) (nmol/µl) (nmol/µl) (nmol/6DIV) /104 cells)

0 173 979 424 555 3.20

25 240 1020 747 273 1.13

50 75 980 801 179 2.38

75 1 880 777 103 103

100 0.05 820 510 310 6200

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CHAPTER 5. GENERAL DISCUSSION

5.1 Summary of findings

My thesis work is divided into two parts. In the first two data chapters I studied development of the neocortex, while in the third data chapter I investigated the neocortex in a disease state; namely, oligodendroglioma (ODG). In the first two data chapters, I provided the first evidence that members of the Plag family of transcription factors play an important role in neocortical development, implicating Zac1 in the regulation of neuronal migration (Chapter 2) and Plag1 and Plagl2 in the control of regionalization and progenitor proliferation (Chapter 3).

In the last data chapter, I demonstrated that ODG cells act non cell autonomously to influence the behavior of NSCs, and showed that they do so through the secretion of EVs that contain many signaling molecules, including EGF. Furthermore I showed that ODG cells have a biphasic response to EGF, with an induction of proliferation at low levels and a suppression at higher levels, and I showed that this response is sensitive to glucose levels. I summarize my work below, and place it in the broader context of the field.

5.1.1. Zac1 regulates neocortical neuronal migration via Pac1 signaling. Zac1 was initially identified in the Schuurmans’ lab in a subtractive hybridization screen searching for downstream targets of the proneural gene Neurog2 that may function as novel cell fate determinants [310]. In Chapter 2, I performed gain- and loss-of-function analyses with Zac1. In gain of function studies, I demonstrated that Zac1 misexpression blocks the RGC to INP transition, and prevents neuronal differentiation [336], which was consistent with the findings of another group [239]. Furthermore, I demonstrated that the neurons that differentiated were delayed in their migration, in part due to the loss of neuronal polarity. In loss-of-function studies,

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while no defects were observed in progenitor maturation or neuronal differentiation, there were defects in the migration of Zac1 mutant and Zac1 knock-down neurons, and these defects correlated with morphological defects of the migrating neurons [336]. In particular, I observed reduced branching of neocortical dendrites in the cortical plate that likely interfered with the final somal translocation of these neurons as they migrated towards their laminar destinations.

Finally, I found that in the developing neocortex, Zac1 regulates its downstream transcriptional target Pac1, which is a G protein coupled receptor [233]. Furthermore, I demonstrated that up- and/or down-regulation of Pac1 yielded similar neuronal migration deficits. Taken together, these studies implicated Zac1 as a critical regulator of neuronal migration in the neocortex.

In addition to my findings in the neocortex, Zac1 regulates aspects of proliferation, apoptosis and migration in other regions of the CNS, including in the retina and cerebellum [159,

239, 246, 247, 336, 389]. In loss-of-function studies in the retina, Zac1 function fits more with its role as a tumour suppressor gene, as there is ectopic proliferation and a reduction in apoptosis that results in an overall increase in retinal cell number [159]. While Zac1 mutants did not display gross defects in proliferation or apoptosis in the developing neocortex, in gain-of- function studies both in the retina [159] and in the neocortex [336], Zac1 was shown to promote cell cycle exit. Future studies will be required to determine whether Zac1 carries out these functions through the same downstream determinants in both regions of the CNS. In the neocortex, a recent transcriptomic analysis of NSCs overexpressing Zac1 revealed that this transcription factor can induce the ectopic expression of non-neural lineage genes, and also induce the expression of markers of a pluripotent state [239]. In this regard it is interesting that

Plagl2, another member of this gene family, also promotes proliferation and possibly pluripotency when misexpressed in NSCs, as revealed by the induction of alkaline phosphatase 180

expression [199].

5.1.2. Plag1 and Plagl2 proto-oncogenes have distinct functions in neocortical development. In Chapter 3, I investigated the roles of Plag1 and Plagl2, two other members of the Plag family of transcription factors, in neocortical development. These two genes are known proto-oncogenes and are expressed quite ubiquitously in the developing CNS of murine embryos

[158]. I found that despite their structural and functional similarities and overlapping expression patterns, Plagl2 and Plag1 do not cross-regulate one another at the level of transcription

(Chapter 3). Moreover, I found that at least one copy of either Plag1 or Plagl2 is required for embryonic survival since double mutants do not survive the embryonic period (Chapter 3). I therefore focused my studies on single and compound single mutants, revealing that Plag1 and

Plagl2 play complementary roles in setting dorsal-ventral boundaries in the telencephalon; Plag1 is required to set the dorsal boundary of ventral telencephalic gene expression, while Plagl2 is required to set the ventral border of dorsal telencephalic gene expression (Chapter 3). Finally, with respect to the regulation of proliferation, which is what these genes do in cancer, I found that while Plag1 is required for the proliferation of neocortical progenitors, Plagl2 is sufficient to alter proliferation. Taken together these data suggest that Plag1 and Plagl2 have similar but still distinct functions in the developing neocortex.

Despite extensive knowledge of Plag gene function in cancer, our study is the first to show a role for Plag1 and Plagl2 in the developing nervous system. However, functions for all three Plag genes have been identified in other embryonic lineages. Zac1, Plag1 and Plagl2 all regulate embryonic growth [157, 240, 241]. Zac1 also controls development of keratinocytes

[307], heart [225, 308], and pancreatic islets [309], while Plagl2 functions in enterocytes [241].

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It is interesting that all three Plag genes are expressed in the neocortical VZ [158, 336], yet Zac1 promotes cell cycle exit while Plag1 and Plagl2 are required and sufficient to promote proliferation, respectively. Future studies will be required to tease apart these separate functions of the Plag genes, as described in more detail below.

5.1.3. Oligodendroglioma cells secrete bioactive EVs that influence the proliferation of

NSCs. In chapter 4, I set out to determine whether ODG cells secrete bioactive molecules that influence the behavior of mouse NSCs. I first confirmed that the BT088 ODG cell line that I used in my study was derived from the original patient [359], using STR matching to identify polymorphisms in 16 genetic markers. Apart from three of the loci that displayed loss of heterozygosity, the DNA from BT088 cells matched the original patient derived DNA. I then collected CM from these cells and demonstrated that it had dosage-specific effects on mNSC proliferation, promoting proliferation at low concentrations and blocking proliferation at high concentrations. These results suggested that BT088 cells secrete bioactive factor(s), and I demonstrated that these factors were secreted in EVs. While proteomic analyses revealed that

BT088 cells secrete many signaling molecules into EVs, I focused on RTK signaling, and in particular, EGF. I found that similar to breast cancer cells [379], mNSCs are sensitive to EGF levels, with lower levels stimulating growth and higher levels having a reduced capacity to promote growth. In part, these dose-dependent effects are due to the ability of EGF to induce glucose uptake, with the addition of glucose to the media increasing the growth stimulatory effects of EGF, as seen in breast cancer cells [379].

Next, I examined the consequence of inhibiting EV secretion on the growth of BT088 cells by inhibition of sphingomyelinase using sh-Smpd3 or a pharmacological inhibitor

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(GW4869). Strikingly, BT088 cells treated with GW4869 or shSmpd3 produced more, larger

‘tumuorspheres’, suggesting that BT088 EVs secrete factors that normally limit the growth of

BT088 cells themselves. This is similar to the effects of high levels of BT088 CM on mNSCs, which was also inhibitory. These unique tumour-tumour and tumour-neural cell interaction goes along with the idea that tumor cells are often competitive by nature and suggest that BT088 ODG cells secrete factors to inhibit the growth of their ‘own’-cell type and of adjacent cell types. The converse was also true, as BT088 cells nucleofected with a Smpd3 gain-of-function construct, which results in the production of more EVs, made fewer ‘tumourspheres’, suggesting that EV secretion is indeed toxic to the cell. We are currently performing xenografting experiments to assess the tumourigenicity of BT088 cells in which Smpd3 levels have been manipulated in vivo.

5. 2 BIOLOGICAL AND CLINICAL IMPLICATIONS OF FINDINGS

5.2.1. Plag family genes and intrauterine growth restriction (IUGR). IUGR, which occurs in 3-10% of the population, is a significant clinical problem, affecting fetal survival, embryonic and postnatal development, and life quality [390, 391]. Genes that are improperly imprinted in

IUGR placentae include ZAC1 and its co-regulated genes H19 and DLK1 [304]. IGF2, another imprinted gene, is also expressed at decreased levels in IUGR placentae, although not because of aberrant imprinting [221, 304]. In mice, null mutations in Zac1 [157], Igf2 [392] and Dlk1 [393] all lead to reduced birth weights and high perinatal death rates. Thus, expression levels of imprinted genes must be precisely regulated for normal embryonic growth to occur. While Plag1 and Plagl2 are not imprinted, they regulate the expression of some imprinted genes, as does Zac1

[157, 231, 337, 394]. Plag1 and Plagl2 mutant mice also display IUGR to some extent [157, 240,

241]. Understanding Plag gene function will thus be critical for understanding how embryonic

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growth is regulated. For instance, by performing a transcriptomic analysis of the Plag1 mutant neocortex, we may uncover transcriptional targets that also regulate body size and IUGR.

5.2.2. Zac1 and transient neonatal diabetes mellitus (TNDM). Loss of 6q24 maternal imprinting (where ZAC1 is located in humans) occurs in 70% of infants with transient neonatal diabetes mellitus (TNDM) [173-175, 217, 395]. Infants with TNDM fail to produce insulin and/or metabolize glucose. While TNDM usually resolves itself within 6 months, it is a risk factor for the development of type 2 diabetes later in life [395]. The importance of ZAC1 and a co-regulated gene HYMAI (hydatidiform mole–associated and imprinted transcript), a long non-coding RNA of unknown function, in the development of TNDM has been substantiated in a high copy transgenic mouse line carrying the human 6q24 locus [327] and in other mouse strains [309].

Interestingly, Zac1 is co-expressed in the neocortical VZ with Hymai [174]. Given the role of long non-coding RNAs in regulating transcription factors in cis- or trans-, future studies would be aimed at examining if Hymai regulates the expression and/or function of Zac1 in the developing neocortex. In the case of diabetes, it may be possible to target these genes for developing treatment strategies.

5.2.3. Plag family genes and intellectual deficits. Intellectual disability in humans are associated with reduced ZAC1 levels (e.g., Decipher IDs 248227, 294593), PLAG1 gain-of- function (e.g. Decipher IDs 261647, 262044), PLAG1 loss-of-function (269606, 327867), and

PLAGL2 gain-of-function (273429, 322433, 276162). Taken together, these data suggest that the aberrant expression of these genes may perturb brain development, which is consistent with my findings in mouse models. Neurodevelopmental disorders also occur in some infants with IUGR, and imprinted genes such as Zac1 are often aberrantly expressed in IUGR placentae [304].

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However, it is not known whether imprinting disorders also lead to the deregulated expression of

Zac1 in the embryonic CNS. However, IUGR can have long-term neurodevelopmental consequences. Imaging of IUGR infants revealed reduced size and cell number of the frontal neocortex and decreased topological complexity of both the white and grey matter [396-401]. By the age of 9-10, children have lower IQs and neurodevelopmental scores, which are based on parameters that include short term memory, attention abilities, executive functioning, language and coordination [300-302]. Notably, these functions are suggestive of frontal neocortex and hippocampus defects. IUGR is also linked to neuropsychological disorders, including attention deficit disorder and schizophrenia [402, 403].

Many imprinted genes are expressed in the embryonic CNS, where they may play a direct role in regulating neurogenesis, neuronal migration and/or circuit formation [303]. Altered expression of imprinted genes is linked to cognitive dysfunction and neuropsychological disorders in several disorders (e.g., Angelman, Prader-Willi syndromes, autism spectrum disorder [303,

404]). Mouse models have also revealed the importance of imprinting for brain development, with low contribution chimeras generated with parthenogenetic cells (i.e., containing two maternal chromosomes; resulting in increased paternal and decreased maternal imprinted gene expression) displaying increased body weights, a relative reduction in brain size and a biased contribution of parthenogenetic cells to the neocortex [405, 406]. This contrasts to chimeras generated with androgenetic cells (i.e., containing two paternal chromosomes), which have increased body weights, a relative reduction in brain size, and a biased contribution of cells to the hypothalamus.

Despite these striking phenotypes, only a handful of imprinted genes are known or suspected to regulate brain development [e.g. Dlk1, Peg3, Ube3a, necdin, Grb10; [303]]. Through my studies

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we have shown that Zac1 is a critical regulator of CNS development, and we suggest that its upregulation in the brains of some IUGR children may contribute to neurodevelopmental defects.

5.2.4. Targeting EVs for the treatment of glioma. Gliomas are primarily comprised of a heterogenous pool of cells which express glial markers. Many gliomas have the ability to transition from grade II to grade III tumors over time. One of the ways by which this may occur could be due to EV-mediated intercellular communication between ODG cells and neighboring neural cells or tumour cells. Surprisingly, we found that BT088 cells secrete EVs which contain material that is only stimulatory for cell growth at low levels, and inhibitory at high levels, both for neural cells and tumour cells. We implicate EGF as one of these dosage sensitive bioactive molecules, but future studies will focus more on the additional factors that were identified in the BT088 proteome.

Novel drugs that target these EV signals may be able to further reduce the proliferation of tumour cells, and/or induce their cell death. One factor that was particularly inhibitory to BT088 cell growth was the misexpression of Smpd3. If agonists of Smpd3 were identified, it is possible that they could inhibit ODG growth, both in vitro and in vivo. Future studies would be aimed in this direction.

5. 3 FUTURE PERSPECTIVES

5.3.1 To elucidate which downstream effectors of Plag genes regulate cell fate decisions. Although we identified Pac1 as a downstream effector of Zac1 in regulating neocortical neuronal migration, gene profiling studies from our lab (L Langevin, C Schuurmans, unpublished data) and another group [239] identified many other genes that might act as downstream effectors of Zac1. Many of these factors have not yet been studied in the developing nervous system, and future analyses of these factors may help to elucidate how Zac1 functions.

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For example, the findings by another group that Zac1 promotes the induction of pluripotency genes [239] suggests that Zac1 may be used as a reprogramming factor. One experiment would be to test whether the addition of Zac1 to the cocktail of Yamanaka factors (Klf4, c-Myc, Sox2,

Oct4) [407] would increase the efficiency of reprogramming fibroblasts to induced pluripotent stem cells (iPSCs). Notably, Plagl2 is also known to confer self renewing characteristics to cells where it is misexpressed [199], suggesting that it may also enhance iPSC production. Consistent with a role for Plagl2 in the induction of pluripotency, we found that Plagl2 overexpression in the E14.5 neocortex induces alkaline phosphatase (AP) expression, which is a marker of pluripotency (Figure 5.1).

Another question is how does Zac1 block neuronal differentiation? Work in our lab has shown that the proneural genes are essential determinants of a neuronal fate, and that the misexpression of these factors in neocortical progenitors induces neurogenesis [346]. In unpublished studies, we found that co-expression of Zac1 with Neurog2 blocks the ability of

Neurog2 to transactivate Neurod1, which is a downstream transcriptional target (Figure 5.2).

Furthermore, we found that Zac1 can bind Neurog2, at least in vitro, suggesting that Zac1 may be acting as a transcriptional co-repressor. Consistent with this idea, Zac1 is a known co-activator or co-repressor of other transcriptional regulators (e.g., p53, nuclear receptors; [218, 224, 225, 349-

352]).

Another area of investigation that I did not examine is whether Zac1 regulates glial differentiation. Indeed, a previous study showed that one of the downstream targets of Zac1 is

Socs3, which inhibits the Jak-Stat3 pathway, thus regulating the timing of astroglial differentiation embryonically and in the adult rodent brain [237]. That is, when Zac1 is overexpressed, astrocyte differentiation is delayed, and when Zac1 is knocked-down, astrocyte 187

differentiation occurs precociously [237]. In this regard, it is interesting to note that Etv5, which is a member of the FGF syn group of genes that has been implicated in gliogenesis [368], is also regulated by Zac1 [239]. Etv5 function has yet to be assessed in neocortical development, but my preliminary work suggests that Etv5 is an essential regulator of postnatal brain development, as

Etv5 mutants (Etv5fl/fl;NestinCre and Etv5fl/fl;Foxg1Cre) have normal sizes at birth, but are much smaller than littermate controls at P21 (Figure 5.3). An in-depth analysis of these mutants will be required to determine how Etv5 regulates brain size, and to see whether Etv5 is indeed required for gliogenesis in vivo.

Finally, we were unable to obtain double Plag1 KI/KI;Plagl2 KI/KI mutants as early as

E12.5 suggesting that double mutants die early embryonically, and that at least one copy of

Plag1 or Plagl2 is required for embryonic survival. Furthermore, of the 21 resorbed or dead embryos, I was able to genotype eight, and none of these dead embryos were Plag1 KI/KI;Plagl2

KI/KI double mutants, providing further support that this genotype is not viable. The next step would be to determine when in development these embryos die, as it would provide information about possible causal factors. Given the early lethality, one possibility is that the double mutants die because of defects in implantation that may be attributable to the aberrant development of the chorioallantoic placenta, which is established at approximately E9.5 [408]. I would therefore try to dissect double mutants at E9.5 and see if I can find any embryos that have implanted. If there are no implanted embryos, then I would suspect that there is peri-implantation lethality. One way to study embryos before implantation is to flush the uterus, and I would do so at various stages

(E3.5, E4.5, E5.5). I would then compare proliferation, size and number of blastomeres in the wild-type and mutant embryos, and also examine gene expression. Early peri-implantation death would be indicative of defects in proliferation, perhaps, that prevent the early blastula cleavages 188

[408].

Another intriguing line of investigation would be to see how Zac1 interacts genetically with Plag1 and Plagl2 by generating different combinations of double knock-outs (e.g., Zac1-/-

;Plag1-/- and Zac1-/-;Plagl2-/-). Even though Zac1 functions differently than Plag1 and Plagl2 in the developing neocortex, these three genes share common transcriptional targets, so it may be that they also act redundantly to carry out some functions.

5.3.2. To understand how the mNSCs interact with the ODG cells. In our study of how

ODG cells communicate with neighboring mNSCs via EVs, I primarily addressed tumour-neural cell interactions. I identified a candidate factor, EGF, which is carried as cargo by BT088 EVs, and showed that EGF has dose-specific effects on the growth and proliferation of mNSCs.

However, from the mass spectrometry analysis that we also performed on BT088-derived EVs, we identified several additional growth factors, including FGF, IGF, etc., that may also influence mNSCs. Future studies would be aimed at determining whether these growth factors also influence mNSC proliferation in a dose-dependent fashion.

The in vivo environment where BT088 cells shed their EVs is more complex and does not only contain neural stem cells but also other neural cells (neurons, astrocytes, oligodendrocytes) and stromal cells (eg., microglia, endothelial cells, macrophages), suggesting that EVs may also influence the behavior of these cells. To analyse tumour-neural and tumour-stromal cell interactions, I will examine the xenografted brains in which we have transplanted BT088 cells that generate EVs or BT088 cells in which Smpd3 has been knocked down and se whether there are changes in angiogenesis in the tumour, macrophage and microglia infiltration, and glial cell proliferation. In addition, we have only studied the effect of blocking Smpd3, but EVs are also

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generated by the ESCRT pathway, and the secretion of EVs can be blocked by targeting

Rab27a/b [271]. I would therefore also target these pathways in BT088 cells and see how this manipulation influences interactions with neural and non-neural cells in vitro and in vivo, as described above.

5.4 Concluding Remarks

In addition to playing a role in cancer, my work reveals an additional role for all three

Plag family transcription factors in neocortical development. While Zac1 is critical in regulating the RGC to INP transition and maintaining neocortical neuronal migration; Plag1 and Plagl2 regulate dorsoventral boundary formation and regulate proliferation. Taken together, these studies improve our understanding of how correct numbers of different cell types are generated in the embryonic neocortex and the underlying mechanisms that guides newborn neurons to their appropriate destinations. In addition, my study with the mode of ODG communication with surrounding mNSCs is first of its kind to show one of the ways by which ODG cells communicate with the neighboring non-tumor cells. I hope that my work has laid ground for more exciting discoveries such as blocking this mode of communication for more effective therapies to treat brain cancers grouped into WHO grade II/III ODG.

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5.5 Figures and Figure Legends

Figure 5.1. Alkaline phosphatase activity induced by Plagl2 misexpression in the neocortex.

(A-C) E14.5 to E18.5 in utero electroporation of Plagl2, showing DAPI stain (A). GFP expression (B) and alkaline phosphatase activity (C). Red arrowheads point to GFP+ alkaline phosphatase+ cells. AP, alkaline phosphatase; E, embryonic; cx, neocortex.

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Figure 5.2. Zac1-Neurog2 interactions. Zac1 and Neurog2 physically interact (co-IP). Zac1 promotes Neurog2-E47 interactions. Zac1 reduces Neurog2 transactivation of a NeuroD1 promoter.

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Figure 5.3. Etv5 mutants are smaller at P21 and have a smaller hippocampus. (A) Pictures of P21 animals with the following genotypes: Foxg1cre (i), Etv5fl/fl;Foxg1cre (ii), and Foxg1cre

(iii). (B-C) Coronal sections of P21 Foxg1cre (B) and Etv5fl/fl;Foxg1cre (C) brains. cx, neocortex; P, postnatal day; CA1 and CA3, subregions of hippocampus; DG, dentate gyrus region of hippocampus.

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