Mechanism of Microrna Mir-520G Pathogenesis in CNS-PNET

Mechanism of MicroRNA miR-520g Pathogenesis in CNS-PNET

J. H. David Shih

A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Department of Laboratory Medicine and Pathobiology University of Toronto

Mechanism of microRNA miR-520g pathogenesis in CNS-PNET

J. H. David Shih

Master of Science

Graduate Department of Laboratory Medicine and Pathobiology University of Toronto

2011 Abstract

We recently discovered a high-level amplicon spanning the chr19q13.41 microRNA cluster in

CNS Primitive Neuroectodermal Tumour, which results in striking upregulation of miR-520g.

Constitutive over-expression of miR-520g in untransformed human neural stem cells enhanced cell growth, restricted differentiation down the neuronal lineage, and promoted expression of neural stem/progenitor cell markers. We thus hypothesize that ectopic miR-520g expression promotes tumourigenesis in part by inhibiting cellular differentiation. Consistent with this proposition, miR-520g is silenced upon embryonic stem cell differentiation and its expression is absent from most adult tissues. Moreover, expression analysis of miR-520g overexpressing cells revealed significant dysregulation of developmental signalling pathways. Further efforts focused on elucidating mechanisms of miR-520g function led to the identification of a cell cycle inhibitor, p21, as an important candidate target. These findings collectively suggest that miR-

520g may modulate differentiation by regulating developmental signalling pathways and cell cycle exit of neural stem/progenitor cells.

Acknowledgments

I am thankful to my supervisor, Dr. Annie Huang, and my graduate committee members, Dr. Peter Dirks and Dr. Rod Bremner, whose encouragement, guidance, and support from the initial to the final stages of the project have provided a productive research environment and helped me develop an understanding of the subject. I am grateful for helpful discussions and feedbacks from Dr. Burton Yang and Dr. George M. Yousef on this thesis.

I wish to express my gratitude to past and present members of the Huang Lab – Daniel Picard, Dr. Limei Zhou, Mohamed Ahmed, Dr. Meihua Li, Dr. Yuntao Lu, and Kyle F. Lee – for their advice and support during the course of my research. I am also grateful for helpful discussions with and advices from members of other labs. I would like to thank: Stephen Mack, Dr. Paul A. Northcott, and Adrian Dubuc from Dr. Michael Taylor’s lab for advice on quantitative PCR and molecular cloning; Sameer Agnihotri and Dr. Joydeep Mukherjee from Dr. Abhijit Guha’s lab for advice on molecular cloning and immunoblotting; Micky Tsui from Dr. Herman Yeger’s lab for advice on cell culture; Arthur Ling from Dr. Stephen Girardin’s lab for advice on transfection and luciferase reporter assay; Dr. Kevin Donato and Dr. Melanie Gareau from Dr. Philip M. Sherman’s lab for advice on luciferase reporter assay; Jacky Chung from Dr. Meredith Irwin’s lab for advice on transfection; and Dr. Ian D. Clarke from Dr. Peter Dirks’s lab for advice on immunocytochemistry.

The progression of my project is also facilitated by the collaboration with and the generous sharing of equipment and reagents from other labs; I am grateful to: Dr. Peter Dirks, Dr. Paul Boutros, Dr. Herman Yeger, Dr. Meredith Irwin, Dr. Michael Taylor, Dr. Peter K. Kim, Dr. Jane McGlade, and Dr. Philip M. Sherman.

I would also like to acknowledge members of the open source community, whose ongoing contribution to bioinformatic tools have been instrumental in the analytical aspect of my research project. I owe my gratitude to a great number of developers, including the R development team, the Bioconductor development team, and authors of various packages therein.

This work was supported in part by the University of Toronto Fellowship, Ontario Graduate Scholarship, and the Hospital for Sick Children Research Training Competition.

iii

Table of Contents

List of Tables ...... vii

List of Figures...... viii

List of Appendices ...... ix

Abbreviations...... x

Chapter 1 Introduction...... 1

1.1 Overview ...... 2

1.2 Pediatric brain tumours...... 3

1.3 Mammalian central nervous system development ...... 3

1.3.1 Terminological premise ...... 3

1.3.2 Cellular players in neurogenesis ...... 4

1.3.3 Radial glial cells...... 4

1.3.4 Signalling pathways involved in neuroectodermal induction and neurogenesis .... 5

1.4 CNS-PNET and classification of pediatric embryonal brain tumours ...... 6

1.5 MicroRNA: its function and biogenesis...... 10

1.6 Chromosome 19 MicroRNA Cluster...... 12

1.6.1 Regulation of C19MC expression...... 12

1.6.2 C19MC dysregulation in cancer ...... 13

1.7 Project Objectives...... 13

Chapter 2 Materials and Methods...... 15

2.1 Cell cultures...... 16

2.2 Plasmids...... 16

2.3 Western Immunoblotting...... 17

2.4 Quantitative RT-PCR...... 18

2.5 Induction of apoptosis by serum starvation...... 18 iv

2.6 Retinoic acid induced differentiation of NCCIT cells...... 19

2.7 Transient transfections...... 19

2.8 Luciferase reporter assays...... 19

2.8.1 Rationale for luciferase reporter constructs and cell lines...... 20

2.8.2 Positive controls for luciferase reporter assay ...... 20

2.8.3 Optimized conditions for luciferase reporter assay ...... 21

2.9 Analyses of miRNA expression data...... 22

2.10 Expression array profiling...... 22

2.11 Expression data analysis...... 22

2.11.1 Normalization ...... 22

2.11.2 Differential expression...... 22

2.11.3 Enrichment analysis of tumour expression profiles...... 22

2.11.4 KEGG pathway enrichment analysis of PFSK and hNSC expression profiles .... 23

2.12 miRNA target prediction algorithms...... 23

Chapter 3 Results...... 24

3.1 Endogenous expression pattern of miR-520g...... 25

3.1.1 Rationale ...... 25

3.1.2 Change in miR-520g and C19MC microRNAs expression upon differentiation of human embryonic stem cells ...... 26

3.1.3 Endogenous expression pattern of miR-520g and C19MC microRNAs across normal tissues...... 28

3.1.4 miR-520g expression changes during retinoic-acid induced differentiation of NCCIT cells ...... 30

3.1.5 Summary...... 30

3.2 Pathways regulated by miR-520g...... 32

3.2.1 Rationale ...... 32

3.2.2 Target identification strategy I...... 37

3.2.3 Target identification strategy II ...... 41

3.2.4 Target identification strategy III ...... 42

3.2.5 Downstream validation of candidate target genes ...... 48

3.2.6 Specificity of miR-520g mediated repression...... 52

3.2.7 Summary...... 53

Chapter 4 Discussions and Future Directions...... 55

4.1 The role of miR-520g and other C19MC miRNAs in development ...... 56

4.2 Candidate genes and pathways that may be targeted by miR-520g ...... 58

4.3 Cell cycle inhibitor p21 is a potential miR-520g target ...... 59

4.4 Is p21 an important miR-520g target in CNS-PNET pathogenesis?...... 60

4.4.1 Functional studies of p21 as a miR-520g target...... 60

4.4.2 How does the targeting of p21 by miR-520g contribute to CNS-PNET pathogenesis? ...... 60

4.4.3 What other targets could contribute to pathogenesis? ...... 63

4.5 Limitations of current model systems ...... 64

4.6 Co-factors in miRNA-mediated post-transcriptional regulation ...... 65

4.7 Future candidate miRNA target screens and alternative strategies...... 66

4.7.1 Screening more genes with luciferase reporter assays...... 66

4.7.2 Assaying protein expression of target candidates using In-Cell Western...... 67

4.7.3 Enriching for miR-520g bound transcripts using immunoprecipitation with antibodies against Argonaute...... 67

4.8 Concluding remarks...... 68

References...... 69

Appendices...... 82

List of Tables

Table 3.I. Criteria for validating candidate miR-520g targets...... 34

Table 3.II. Common predicted miR-520g targets by TargetScan, PITA, and miRanda...... 44

Table 3.III. Luciferase reporter constructs...... 50

vii

List of Figures

Figure 1.1. Chromosome 19 MicroRNA Cluster...... 8

Figure 1.2. C19MC amplification identifies a unique subgroup of CNS-PNET...... 9

Figure 1.3. miRNA biogenesis...... 11

Figure 3.1. Expression profile of C19MC miRNA in differentiated and undifferentiated hESC. 27

Figure 3.2. Expression profile of C19MC miRNAs in normal tissues...... 29

Figure 3.3. Changes in miR-520g expression levels in NCCIT upon retinoic acid treatment. .... 31

Figure 3.4. Expression profile differences of miR-520g overexpressing cells...... 35

Figure 3.5. Approaches to validate miRNA target candidates...... 36

Figure 3.6. Enrichment analysis of dysregulated genes in C19MC amplified tumours...... 38

Figure 3.7. qRT-PCR of apoptosis genes in miR-520g overexpressing cells...... 40

Figure 3.8. KEGG Pathway enrichment analysis of miRNA-overpressing PFSK and hNSC expression profiles...... 42

Figure 3.9. Overlap of predicted targets by different algorithms...... 43

Figure 3.10. qRT-PCR of target candidates in PFSK-520g and hNSC-520g cells...... 47

Figure 3.11. Luciferase reporter assay...... 49

Figure 3.12. No luciferase reporters of putative miR-520g targets were repressed by miR-520g...... 51

Figure 3.13. Western blotting analyses to validate putative miR-520g targets ...... 54

viii

List of Appendices

Supplemental Table I. qRT-PCR primers for quantifying transcript levels of apoptosis genes... 82

Supplemental Table II. qRT-PCR primers for quantifying transcript levels of candidate targets.83

Supplemental Table III. Oligonucleotides used in preparing luciferase reporter constructs...... 84

Supplemental Figure 1. Determination of the minimum amount of the luciferase plasmid required in the transfection of HEK293TV...... 86

Supplemental Figure 2. Optimization of co-transfection to achieve luciferase activity repression in HEK293TV...... 87

Supplemental Figure 3. Optimization of transfections in NCCIT...... 88

Supplemental Figure 4. Validation of miR-520g transient transfection in NCCIT...... 89

Supplemental Figure 5. Optimization of co-transfection to achieve luciferase activity repression in NCCIT...... 90

Supplemental Figure 6. RNA secondary structures of the 3’UTR of luciferase reporter constructs...... 91

Supplemental Figure 7. miR-520g binding sites in the 3’UTR of p21 predicted by TargetScan. 92

Abbreviations bHLH basic helix-loop-helix BLBP Brain lipid-binding protein (FABP7) BMP Bone morphogenic protein bp base pair C19MC Chromosome 19 MicroRNA Cluster cDNA complementary DNA CNS central nervous system DNA deoxyribonucleic acid ESC embryonic stem cells GDF Growth and differentiation factor GFAP Glial fibrillary acid protein GLAST Glutamate/aspartate transporter (SLC1A3) Hes Hairy and enhancer of split family hNSC human neural stem cells miRNA microRNA mRNA messenger RNA NEP neuroepithelial progenitor PCR polymerase chain reaction PMSF phenylmethanesulfonyl fluoride PNET primitive neuroectodermal tumour qRT-PCR quantitative RT-PCR RA retinoic acid RISC RNA induced silencing complex RNA ribonucleic acid RT reverse transcription RT-PCR reverse transcription PCR Shh Sonic hedgehog TGF Transforming growth factor Wnt wingless-type MMTV integration site family

x 1

Chapter 1 Introduction

1.1 Overview

Primitive neuroectodermal tumours (PNET) represent the most common group of malignant pediatric brain tumours, and they pose great therapeutic challenges due to long-term consequences of damage from and broad diversity of response to treatment. Patient outcomes are improving as tumour classification evolves to reflect progress in elucidating common and distinct tumourigenic mechanisms in different brain tumour subclasses. A subclass of PNET that primarily occurs in the cerebrum, known as supratentorial- or CNS-PNET, is particularly aggressive and poorly studied, with high incidence of tumour reappearance and poor overall survival in response to conventional treatment (30-40%).1 In order to define the molecular pathways involved in CNS-PNET tumourigenesis, our lab has recently conducted a comprehensive analysis to characterize DNA copy number and gene expression changes of primary tumours.2 We have identified a non-constitutive chr19q13.41 focal amplicon in 25% of the CNS-PNET tumour samples. This region spans a cluster of miRNAs, known as the Chromosome 19 MicroRNA cluster (C19MC). The expression levels of a number of miRNAs therein were strikingly upregulated in tumours with the amplicon compared to those without. miR-520g is one of the most highly upregulated microRNA in C19MC amplified tumours, and demonstrated oncogenic activities in vitro and in vivo. Critically, overexpression of miR-520g inhibits differentiation of human neural stem cells (hNSCs). In this thesis, I will examine the role of miR-520g dysregulation in the pathogenesis of CNS-PNET.

Hypothesis

Ectopic overexpression of miR-520g contributes to tumourigenesis in part by restricting the neural differentiation of human neural stem cells.

Overall objective

To elucidate the role of ectopic miR-520g overexpression in the pathogenesis of CNS-PNET.

Specific Aims 1. To determine the endogenous expression pattern of miR-520g 2. To identify pathways and genes regulated by miR-520g

1.2 Pediatric brain tumours

Pediatric brain tumours are the most common solid cancer of childhood, and they are the leading cause of death in children, aside from trauma.3,4 The molecular features and etiological factors of pediatric brain tumours are distinct from their adult counterparts. Unlike adult brain tumours, childhood tumours of the brain are thought to arise from aberrations in normal CNS development.5 The molecular pathogenesis of pediatric brain tumours are poorly studied, due to the relative paucity of cases. The difficulty in treating pediatric brain tumours is further aggravated by two major challenges: the poor response rate of certain tumours to conventional therapy and the fragility of the developing brain.6 Significant progress has been made over years, largely focused on the optimization of chemotherapy and the delineation of prognostic factors.6,7 However, while the survival rates of some tumours have improved, these numbers are essentially unchanged for many brain tumour types.8-10 These challenges underscore the importance of understanding the biology of pediatric brain tumours and developing therapeutic strategies that specifically target the cause of the disease.

1.3 Mammalian central nervous system development

1.3.1 Terminological premise

Several definitions for “stem cell” and “progenitor” exist in the literature, explicitly stated or implicitly understood. In this thesis, I will use the definitions given by Malatesta et al.11 “Stem cells” are multipotent cells that can differentiate into most of the cell types in a given organ or tissue, and they can self-renew in vivo or in vitro for an indefinite number of times without any significant changes in its phenotype and differentiation capabilities, through symmetric or asymmetric divisions. “Progenitor cells” may also give rise to multiple lineages, but they undergo limited rounds of self-renewing divisions before significant phenotypic changes. Progenitor cells may give rise to stem cells, if the engendered cells fulfill the definition. By these definitions, I will reserve the term “stem cells” for cells that persist throughout the life of the organism, such as adult neural stem cells. In vitro cell cultures that fit the “stem cell” definition will also be referred to as such.

1.3.2 Cellular players in neurogenesis

During embryonic development, the neuroectoderm is induced to form the neural plate, which then folds to give rise to the neural tube. These structures are composed of a single layer of cells known as neuroepithelial progenitors (NEPs). Before the onset of neurogenesis, NEPs expand via symmetric divisions to form the neuroepithelium, which lines the lumen of the lateral ventricle. With the onset of neurogenesis, the neuroepithelium transform into a tissue with many cellular layers, eventually giving rise to all the neurons of the cerebral cortex. Cortical neurogenesis is essentially completed before birth, followed by gliogenesis (giving rise to astrocytes and oligodendrocytes), which largely occurs perinatally and postnatally. Neurogenesis is most well-studied in the cerebral cortex using rodent models. While the process is largely similar in most regions of the cerebrum, neurons can arise differently in specific regions of the brain, such as those derived from ganglionic eminences.11-14

During cortical neurogenesis, NEPs remain anchored to the ventricular (apical) surface and divide asymmetrically, engendering another NEP, in addition to a neuron or a secondary neural progenitor. Of the different types of secondary progenitors, radial glial cells also remain at the ventricular surface, where they divide to produce more radial glial cells, neurons, or further types of progenitors.11,12 On the other hand, basal progenitors (also known as intermediate neuronal progenitors) migrate basally to the subventricular zone where they divide symmetrically to produce neurons. Derived from different progenitors, earlier born neurons occupy deeper, more apical layers of the cortex, while later born neurons migrate further into basal regions.

NEPs and radial glial cells are collectively known as apical progenitors, and their cell cycle characteristics determine the layer distribution of the neurons.15 In mice, apical progenitors undergo about 11 cell cycles over a period of 6 days to give rise to cortical neurons.16,17 The number of neurons in and the thickness of each layer of the cortex are controlled by cell cycle exit of progenitors during neurogenesis.15

1.3.3 Radial glial cells

Radial glial cells were formerly thought to merely serve as a scaffold for neuronal migration, but are now recognized as the main proliferating population during neurogenesis.18 They were originally named for their molecular and cytological resemblance to astroglial-lineage cells. Apart from morphological features, radial glial cells cannot be distinguished from astrocytes by

antigenic markers, as they express markers typical of astrocytes, such as GLAST, BLBP, and GFAP.11 However, it has been demonstrated that radial glial cells can engender all the main lineages of the CNS: neurons, astrocytes, oligodendrocytes, ependymocytes, and adult neural stem cells.19-22 Indeed, radial glial cells are the main source of postmitotic neurons in the cerebral cortex, as determined by lineage-tracing studies in transgenic mice.21,23,24 Conversely, only modest portions of neurons derived from ganglionic eminences and interneurons in various regions appear to be produced by radial glial cells.21,24 Although radial glial cells can differentiate into various cell types, the majority of these progenitors are committed to neuronal or glial fates very early; the number of multipotent radial glial cells that exist throughout development are relatively few.11

Additionally, radial glial cells display antigenic similarities with various cultured neural stem cell, though it is unclear how in vitro conditions induce phenotypic changes in neural stem cell cultures.25 In particular, adherent neural stem cell cultures maintained with EGF and FGF2 resemble radial glial cells, irrespective of whether the cells were derived from embryonic stem cells (ESCs) or fetal or adult brain.26,27

1.3.4 Signalling pathways involved in neuroectodermal induction and neurogenesis

Studies on different organisms and mammalian ESC cultures have helped elucidate the signalling pathways involved in neuroectodermal induction during embryogenesis. The early events involve multiple pathways, including FGF2, BMP, Notch, Wnt, and Shh signalling pathways.28- 30 FGF signalling is one of the earliest steps involved in neural specification.28 The FGF pathway acts through the activation of the extracellular signal-regulated kinase (ERK1/2) cascade. Blockade of this cascade can completely abolish the neuroectodermal commitment of ESCs.31 After the formation of the primary germ layers during embryogenesis, the neighbouring mesoderm secretes BMP antagonist to inhibit BMP-SMAD* signalling in the ectoderm and thereby promote neuroectoderm formation.29 Further, transcriptional activation of Hes transcription factors by Notch signalling is required for forming boundaries and partitioning CNS

* The BMP pathway belongs to the TGF-b super family of signalling pathways, which also includes TGFB-b, Activin, Nodal, and GDF. Signalling through these pathways leads to the activation of SMAD1/5/8 or SMAD2/3.

compartments, since knockout of Hes genes lead to ectopic expression of proneural genes and loss of organizer activity.32 Similarly, positive and negative regulators of Wnt and Shh signalling establishes gradients required for tissue patterning.30,33 Above all, it is the coordinated interplay of a multitude of pathways that initiates neural specification and ensures proper patterning.

Neurogenesis is a complex process in which many pathways and players interact to influence cell-fate decisions, establish chromatin modifications, and modulate the transitions from multipotent progenitors to terminally differentiated cells.34 A family of complexes based on the Brg1 and Brm ATPases (BAF complexes) serves a central role in shaping the chromatin architecture and orchestrating the activity of transcription factors.34 BAF complexes can interact with different proteins during development by tailoring their subunit compositions to the needs of specific cell types. During neuronal development, BAF45a and BAF53a are assembled into the complex to form the neural progenitor specific BAF (npBAF). Replacing of these two subunits with BAF45b and BAF53b to form the neuronal specific BAF (nBAF) is an important transition in neuronal differentiation. npBAF interacts with negative regulators of neuronal differentiation such as Hes and RE1-silencing transcription factor (REST/NRSF) to suppress proneural genes and maintain progenitor cells. Conversely, nBAF associates with neurogenic transcription factors such as Neurogenin and NeuroD. Another prerequisite for neurons to terminally differentiate and mature is cell-cycle exit, and this process is regulated by several cyclin-dependent kinase inhibitors. Recently, various miRNAs have been reported to fine-tune neurogenesis at various steps including the switching of BAF subunits.35,36

1.4 CNS-PNET and classification of pediatric embryonal brain tumours

Pediatric brain tumours are mainly classified based on histological features and tumour location. Tumours are often named after the normal cell type which the tumour cells most resemble histologically, though the atypical appearance of cells in some tumours can make this comparison difficult.37 The actual cells of origin, however, have been identified only in few types brain tumours, as pre-malignant stages are difficult to recognize.37 For instance, transgenic mouse studies38,39 have identified cerebellar granule cells in the external granular layer as cells of origin for at least a subset of medulloblastoma tumours, particularly those with activation of the Shh pathway. Moreover, radial glial cells are believed to be the initiating cells for ependymomas, as the tumours exhibit patterns of gene expression that resemble those of radial glial cells in the

ependyma.40 Conversely, the cell of origin is unknown in CNS-PNET. Given that CNS-PNET display differentiation markers of all three major CNS cell types – neurons, astrocytes, and oligodendrocytes – they may derive from an early tri-potent progenitor, such as the radial glial cell. As neural stem cell cultures are also tri-potent, they may represent an attractive in vitro model for studying CNS-PNET tumourigenesis.

Medulloblastoma, ependymoma, pineoblastoma, atypical teratoid/rahbdoid tumours (ATRT), and CNS-PNET are collectively classified as embryonal brain tumours, owing to the similarity in their histological appearance of poorly differentiated cells.41,42 Although these tumours are often histologically indistinguishable, their molecular features are vastly distinct, underscoring the differences in their pathogenesis. For example, ATRT is characterized by a focal chr22 deletion, which disrupts the tumour suppressor gene INI1.43 Further, the expression profiles and genetic alterations in CNS-PNET are different from other PNET subclasses.44,45

Despite being classified as a separate entity from other PNET types, CNS-PNET still encompass a heterogeneous group of tumours, as revealed by DNA copy number and expression profiling.2 In order to improve clinical outcome, it would be important to refine the classification of CNS- PNET and determine common and distinct molecular pathways that contribute to the pathogenesis of this poorly studied tumour type. To this end, we have identified a recurrent genomic aberration in CNS-PNET, which leads to amplification of the C19MC locus (Figure 1.1). Tumours with this amplicon likely represent a group of tumours that share a common mechanism of oncogenesis, given their distinct histopathological features, expression signatures, and clinical outcomes (Figure 1.2). To understand how C19MC-amplified tumours commandeer normal CNS development, we set out to characterize the oncogenic function of the miRNAs in C19MC.

DPRX LILRP2

Chr.19q13.41-42 p12 q12

RP11-381E3 ┌MYADM ┌ NLRP12 ┌NDUFA3 ┌LILRA4

59.30 59.70Mb

C19MC 58,861 * * ~58, 983Mb miRNA clusters └MIR-512 -1 └ MIR-516 -1 └MIR-371 -3 └ MIR-520G └ MIR-517C 25kb

Figure 1.1. Chromosome 19 MicroRNA Cluster. The chr19q13.41 amplicon found in CNS-PNET tumours is schematized. The C19MC is situated within the amplicon and extends over ~100 kb, positioned upstream of the miR-371-373 cluster. Relative positions of C19MC (red), the MIR-371-373 cluster (green), and select coding genes within the amplicon are shown. Two C19MC miRNAs (marked by asterisks), miR-520g and miR-517c, are overexpressed in CNS-PNET and exhibit oncogenic activities in vitro and in vivo. All map positions are based on the hg18 build from the UCSC Genome Database (http://genome.ucsc.edu/). Figure adapted from Li et al.2

9 PNET18 PNET19 PNET45 PNET41 PNET31 PNET22 PNET44 PNET4 PNET7 PNET30 PNET36 PNET32 PNET6 PNET5 PNET42 PNET43 PNET3 PNET15 PNET39 PNET40 PNET2 PNET46 PNET16 PNET47 PNET48 PNET25 PNET24 PNET35 PNET17 PNET9 PNET37 PNET20 PNET34

feature p-value C19MC 0 Age < 4 0.026 PNET variant 0.00028 Metastasis 0.66

Yes No NA

1.0

C19MCamp negative C19MCamp positive 0.8

0.6 HR = 12.8 p = 3.3 x 10−05 n = 21 0.4 Survival

0.2

0.0 0 20406080100120 Months

Figure 1.2. C19MC amplification identifies a unique subgroup of CNS-PNET. C19MC amplification in CNS-PNET is associated with distinct histopathological features, a unique expression signature, and bleak patient survival, suggesting that it has an etiologic role in a subgroup of CNS-PNET. Upper panel: Unsupervised hierarchical clustering was performed using the expression profiles of CNS-PNET tumours. The dendrogram displaying the relationship between tumour samples is shown. Associations of C19MC amplification status with clinical and histopathological features (marked by red boxes) were tested using the two-sided Fisher’s exact test. Bottom panel: Patient survival was analyzed using the Cox proportional hazard regression model with the Efron method. P-values < 0.05 are considered statistically significant.

Presented results were published in Li et al.2 (The results of the survival analysis shown here were obtained using the statistical environment R, and the results shown in Li et al.2 were obtained using the SPSS software package.)

1.5 MicroRNA: its function and biogenesis

MicroRNAs are endogenous non-coding RNA of about 23 nucleotides in length that participate in post-transcriptional gene regulation by binding primarily to the 3’UTR of their target mRNA transcripts, ultimately resulting in the suppression – or in some cases, induction – of the protein level of the target.46,47 Recent studies have implicated miRNAs in the regulation of a variety of developmental pathways and the pathogenesis of a myriad of cancer types.48 As micro-managers in vertebrate development, miRNA orchestrate genes involved in the development of various organs and tissues; their deficiency leads to developmental arrest in mouse and zebrafish.49,50 As key players in tumourigenesis, miRNAs repress tumour suppressors and activate oncogenes in various cancers. Aberrant miRNA expression can be caused by different mechanisms, including DNA copy number abnormalities, genomic rearrangements, mutations, epigenetic alterations, and miRNA biogenesis defects.51

The biogenesis of miRNA involves a series of steps and a multitude of factors (Figure 1.3).52 First transcribed as one of several hairpins in a primary miRNA (pri-miRNA) transcript, precursor miRNAs (pre-miRNA) are excised by Drosha and DGCR8. A pre-miRNA may alternatively be derived from spliceosome processing of an intron within a protein-coding gene. Following nuclear export, the pre-miRNA is further processed by Dicer and TRBP into a short RNA duplex. One strand of the duplex, which represents the mature miRNA, is preferentially loaded into the microRNA RNA-induced Silencing Complex (miRISC), whereas the other strand (miRNA*) is degraded. This effector complex uses the miRNA sequence as a guide to recognize target transcript for post-transcriptional regulation. miRNA targeting typically leads to transcript degradation or translational inhibition,46 though translational activation and promoter activation53 have also been reported.47,54

As miRNA biogenesis is critically dependent on the activity of the aforementioned enzymes, the suppression of any of them leads to miRNA deficiency. The re-introduction of specific miRNAs in the context of biogenesis disruption, therefore, is a powerful method for determining the function of the miRNAs.55 This method can serve as an alternative to the loss-of-function approach of knocking down specific miRNAs (and their family members).

Figure 1.3. miRNA biogenesis. The primary miRNA is processed to produce the mature miRNA by a multitude of enzymes and factors, such as Drosha, DGCR8 and Dicer. Either strand of the miRNA duplex may be loaded onto the miRISC complex, in which an Ago family member is a core component. When both mature miRNA strands are stable, one strand is named miRNA-5p while the other miRNA-3p, as shown. If one of the strands is readily degraded, the unstable strand is designated as the star form (miRNA*). See text for details.

1.6 Chromosome 19 MicroRNA Cluster

The Chromosome 19 miRNA cluster (C19MC) is the largest human miRNA gene cluster.56 It maps to chr19q13.41 and extends over ~100 kb, located centrameric to the miR-371-373 cluster (Figure 1.1). C19MC harbours 46 pre-miRNA loci, which give rise to 53 validated mature miRNAs (miRBase release 15). In contrast, the miR-371-373 cluster encodes 3 pre-miRNAs and gives rise to 5 mature miRNAs. Several miRNAs from both clusters share sequence homology with those of the murine miR-290-295 cluster, which is also known as the Early Embryonic microRNAs Cluster (review in preparation).

First discovered by cloning and sequencing in placenta tissue, the C19MC cluster as a whole is highly primate specific, conserved in human, chimpanzee, rhesus monkey, and orangutan.57 The presence of long sequence stretches (400-700 nucleotides), repeated and interspersed throughout the region, suggest that the cluster evolved through duplication and mutation events unique to primates.57 Although the mature sequences of the C19MC miRNAs are highly similar, they generate 16 distinct seeds (nucleotides 2-8 of the mature miRNA).57

The biological function of C19MC is poorly understood. Recently, we have reported frequent amplification of this cluster in CNS-PNET and further demonstrated the in vitro and in vivo oncogenic function of miR-520g and miR-517c therein.2 Several other C19MC miRNAs have also been implicated in different cancers (review in preparation). It would thus be of interest to characterizing the cooperative effects of C19MC miRNAs.

1.6.1 Regulation of C19MC expression

The complex repeated structures of C19MC have not been well characterized, and it is unclear whether the miRNAs are derived from a single or several transcription units.56 It is also unclear whether the cluster is transcribed by RNA Polymerase II or III.56,58 A recent work suggest that C19MC may be regulated by an upstream CpG island, as treatment of gastric cancer cells with a demethylating agent induces upregulation of several miRNAs in the cluster.59 Further, this upstream region has been reported to be imprinted in the placenta, which provides further support for its promoter function.60 Another study have also found that treatment of DNA methylation inhibitor and histone deacetylase inhibitor results in upregulation of C19MC miRNAs and implicated the epigenetic modification of Alu repeats in regulating miR-512-5p of

C19MC.61 The observations that not all C19MC miRNAs are upregulated upon CpG demethylation or histone deacetylation59,61 suggest an additional layer of expression regulation, possibly through heterogeneous transcription from multiple polycistronic promoters or specific regulation of the biogenesis of individual miRNAs. Similarly, the high level focal amplification of C19MC does not result in overexpression of the entire cluster.2 In contrast, the downstream miR-371-373 cluster does not appear to be affected by CpG demethylation or focal amplification, which underscores the differences in transcriptional regulation of the two clusters.2,59

1.6.2 C19MC dysregulation in cancer

Many C19MC miRNAs are aberrantly expressed in cancer. Aside from focal amplification, the C19MC locus is also the target of chromosomal rearrangements involving 19q13.4, which are frequently observed in thyroid adenomas. 62-64 These rearrangements place the C19MC locus under the transcriptional control of the Pumilio Homolog 1 (PUM1) promoter.65 The resulting fusion transcript leads to the upregulation of C19MC miRNAs and miR-371-3. Several studies have also identified a recurrent t(11,19)(q13;q13.4) translocation in embryonal sarcoma,66,67 mesenchymal harmatoma67-70 and Peutz-Jeghers hamartoma.71 Interestingly, the breakpoint region on chr19 has been mapped immediately upstream of the C19MC locus.67,71 Despite search efforts for candidate protein-coding genes in this region, no targets have been discovered.67,71 It is likely C19MC is also the target of this recurrent translocation, which possibly places C19MC under the transcriptional control of the MALAT1 promoter. In support of this proposition, fusion of the MALAT1 promoter with another gene, TFEB, is thought to promote tumourigenesis in renal neoplasms via overexpression of TFEB.72 Further, recurrent chromosomal aberrations involving 19q13 have been reported in low-resolution spectral karyotyping studies of various other cancers, including malignant peripheral nerve sheath tumours,73 fibrosarcoma,74 ovarian cancer,75-77 and hematologic cancers.78,79 Taken together, C19MC activation by promoter substitution may represent a common mechanism in tumourigenesis.

1.7 Project Objectives

The function of the miRNAs in C19MC has been poorly studied. Our recently published work2 implicates two of the miRNAs therein, miR-517c and miR-520g, in CNS-PNET tumourigenesis. In the C19MC amplified tumours, miR-520g and miR-517c are two of the most highly

upregulated miRNAs in the cluster. They both exhibit oncogenic functions in vitro and in vivo, though the oncogenic phenotypes of miR-520g appear much more potent.

The aim of my research project is to elucidate the mechanism by which miR-520g promotes tumourigenesis.

In a collaborative work with Dr. Peter Dirks, we showed that miR-520g overexpressing hNSCs differentiate poorly.2 Compared to the control, miR-520g overexpressing hNSC continued to proliferate under differentiating conditions. Additionally, surface expression of Tubulin b-III, a neuronal marker, is concurrently reduced in miR-520g overexpressing hNSC. Taking these observations together, I hypothesize that:

Ectopic overexpression of miR-520g contributes to tumourigenesis in part by restricting the neural differentiation of human neural stem cells.

In order to gain insight into the function of miR-520g, I have analyzed its endogenous expression pattern and its expression changes upon cellular differentiation. I have then determined pathways that miR-520g regulate by examining the expression profiles of tumours and cell lines. Finally, I have sought to identify candidate miR-520g targets that contribute to tumourigenesis, using various approaches, including integration of computational predictions, detection of target expression changes, and validation of miRNA-target binding.

In this chapter, I have described the classification of pediatric brain tumours based on histological features and its limitations, thus emphasizing the need for understanding the molecular mechanism of tumourigenesis underlying different classes and subclasses of brain tumours. I have introduced the amplification of C19MC as mechanism of tumourigenesis for a group of CNS-PNET and outlined the approaches for elucidating the specific role of miR-520g. In chapter 2, I will describe the details of the experimental and analytical methods. In chapter 3, I will present the results of the experiments and analyses. In the final chapter, I will discuss the implications of the results and propose possible directions for future studies.

Chapter 2 Materials and Methods

2.1 Cell cultures

HEK293, HEK293TV, HeLa and NIH3T3 cells were maintained in DMEM supplemented with 10% FBS. PFSK cells were maintained in EMEM supplemented with 10% FBS and 1ä non- essential amino acids. Daoy cells were maintained in AMEM with 10% FBS. NCCIT cells were cultured in RPMI-1640 with 10% FBS. All culture media contain 100 U/mL penicillin and 100 mg/mL streptomycin, unless specified otherwise. Most cell culture media and reagents were obtained from Wisent (St. Bruno, QC, Canada); FBS was obtained from Thermo Scientific (Rockford, IL, USA). NCCIT, HEK293, HEK293TV, and HeLa cells were acquired from Dr. Herman Yeager’s, Dr. Peter K. Kim’s, Dr. Sam Benchimol, and Dr. Jane McGlade’s labs, respectively; the cell lines were verified to be free of mycoplasma by DAPI staining or established PCR methods.

Human NSCs (acquired from Dr. Peter Dirks) were maintained in NSC culture medium (Neurocult NS-A Basal Medium, 2 mM L-glutamine, 1ä hormone mix, 1ä B27 supplement, 75 mg/mL BSA, and 2 mg/mL heparin), further supplemented with 10 ng/mL epidermal growth factor (EGF) and 10 ng/mL basic fibroblast growth factor (bFGF) for propagation. The cells were induced to differentiate by either serum exposure (10% FBS) or growth factor (EGF and bFGF) withdrawal.2 Cell culture propagation and differentiation were performed by Dr. Ian D. Clarke.

Stable miRNA expression in various cell lines had been established using pcDNA (Invitrogen, Carlsbad, CA, USA) and pCDH (System Biosciences, Mountain View, CA, USA) backbone vectors as previously described, by Dr. Meihua Li and Daniel Picard.2

2.2 Plasmids

miR-520g and miR-517c expression plasmids (pcDNA and pCDH) had been previously generated.2 3’UTR fragments of candidate genes or putative binding sites alone were cloned into the dual-luciferase miRNA target expression plasmid pmirGLO (Promega, Madison, WI, USA). All generated plasmids were verified by restriction enzyme digestion and sequencing (Table 3.III). Restriction enzyme mapping, primer design, and sequence validation were facilitated by various programs in EMBOSS.80

Cloning of 3’UTR fragments of candidate genes into pmirGLO. A region of roughly 1 kb spanning the predicted miRNA binding sites in the 3’UTR of each candidate gene was selected for cloning. The selected regions were PCR amplified, digested overnight with XhoI and XbaI (Roche, Laval, QC, Canada), agarose gel electrophoresis purified (Qiagen Gel Extraction Kit or MP Biomedicals GeneClean II Kit), and ligated into the digested pmirGLO plasmid downstream of the Firefly luciferase gene, using T4 DNA ligase (New England Biolabs, Pickering, ON, Canada) at 16 ºC overnight. Ligated plasmids were transformed into DH5a competent cells by the calcium chloride method.

Cloning of putative miRNA binding sites into pmirGLO. Forward and reverse oligonucleotides corresponding to the putative miRNA binding site were synthesized (Sigma-Aldrich) with reverse-phase cartridge purification. The oligonucleotide mix was heated to 95 ºC and cooled to 20 ºC over a period of 1h in the Annealing Buffer (10 mM pH 8.0 Tris, 50 mM NaCl, 1 mD EDTA). Following annealing, the oligonucleotide duplexes (with overhangs) were ligated into pmirGLO plasmids previously digested with SacI and XbaI (Roche). An internal restriction, included in the oligonucleotide sequences, allowed colony screen by restriction enzyme digestion.

2.3 Western Immunoblotting

Whole cell lysates were prepared using Extraction Buffer C (EBC; 5 mM pH 8.0 Tris, 120 mM NaCl, 0.5% Nonidet P-40).81 Protease inhibitor cocktail (1 mg/mL aprotinin, 1 mg/mL leupeptin, 1 mg/mL pepstatin, and 0.5 mg/mL antipain), PMSF (1% v/v), and sodium metavanadate (1 mM) were added to the buffer immediately before use. Western immunoblotting assays were performed using standard protocol with 5% w/v nonfat dry milk and 0.05% Tween-20 in PBS. Rabbit polyclonal antibodies against p27/CDKN1B (#2552) and TGFBR3 (#2519), in addition to mouse monoclonal antibody against p21/CDKN1A (#2946), were purchased from Cell Signaling Technology (Danvers, MA, USA). Rabbit polyclonal anti-NPTX1 (ab75917) and mouse monoclonal anti-SMAD7 (ab87972) antibodies were purchased from Abcam (Cambridge, MA, USA). Polyclonal rabbit anti-actin (A2066) was obtained from Sigma Aldrich (St. Louis, MO, USA). Secondary horseradish peroxidase (HRP) linked donkey anti-rabbit and HRP linked sheep anti-mouse antibodies were from GE Healthcare (Baie d’Urfe, QC, Canada). Peroxidase

activities were assayed using Western Lightning Chemiluminescence Regents (PerkinElmer, Boston, MA, USA).

2.4 Quantitative RT-PCR

Total RNA was harvested from the cells using standard Trizol extraction (Invitrogen). For measuring levels of mature miRNA, cDNA of miRNAs and snRNAs were individually synthesized using RT primers specific for the mature sequences and the MultiScribe reverse transcriptase from Applied Biosystems (Streetsville, ON, Canada). Quantitative PCR was then performed using Taqman PCR reagents and miRNA PCR primers (Applied Biosystems). For measuring mRNA levels, cDNA was synthesized using random primers and Superscript II (Invitrogen), followed by PCR using SYBR Green PCR reagents and custom designed PCR primers (Sigma-Aldrich) using EPrimer3/Primer380,82 or PerlPrimer.83 Quantitative PCR reactions were carried out in the StepOne Plus PCR System (Applied Biosystems).

The PCR primers were designed (whenever possible) to either span an exon-exon junction or flank an intron such that they either only detect the transcript or yield different PCR products when amplifying from cDNA or genomic DNA. Primers were validated by establishing the range of linearity with respect to the template concentration, as previously described.84 All validated primers had amplification efficiencies (approximately 2.0) comparable to that of the control primers (RPLP0; 36B4). Primers resulting in multiple amplification products (as evidenced by the presence of multiple melting curve peaks) were re-designed or excluded. mRNA expression levels were calculated using the 2-DDCT method.85 Genes whose cycling thresholds were greater than 30 in all samples at all time points or under all conditions were excluded from downstream analysis, as their RNA levels could not be reliably detected by PCR.

2.5 Induction of apoptosis by serum starvation

Cells were first seeded under normal growth conditions (10% FBS), and starved 24h later by replacing the medium with low serum (0.1% FBS) medium following 3 PBS washes. The cells were starved for 48 and 72 hours before harvest.

2.6 Retinoic acid induced differentiation of NCCIT cells

All-trans retinoic acid (Sigma-Aldrich) treatment of NCCIT cells was used a model to determine miR-520g expression changes during neuroepithelial differentiation. The cells (normally grown as an adherent culture) were re-plated onto uncoated/untreated plates and incubated for 48 hours to allow spheroid formation. The spheroids were then treated with all-trans retinoic acid or vehicle (DMSO) for up to 3 weeks. Total RNA was extracted every 3 days. The level of miR- 520g was then determined using qRT-PCR.

2.7 Transient transfections

Transient transfections with plasmids were performed using FuGENE6 or 25kDa linear polyethyleneimine (PEI; from Polyscience, Warrington, PA, USA); transfections with oligonucleotides were performed using Lipofectamine 2000. Cells were seeded in antibiotic-free growth medium and transfected after 16~24 hours following manufacturers’ instructions. Briefly, the transfection reagent was added to serum free medium, and the mixture was incubated for 5 min at room temperature. Following addition of the plasmid and a 20-min incubation at room temperature, the cell cultures were treated with the complex. The cell seeding density and the ratio of transfection reagent to DNA were optimized so as to maximize the transfection efficiency of the GFP-encoding plasmid pCDH (in terms of the percentage of cells expressing GFP). NCCIT cells had a transfection efficiency exceeding 70% using PEI.

2.8 Luciferase reporter assays

Cells were transfected with the miR-520g expression vector, in addition to the luciferase reporter constructs, which encodes both Firefly and Renilla luciferase. 48h after transfection, the luciferase activities were determined using the Promega Dual-Luciferase Reporter Assay on a Lumat LB 9507 Single Tube Luminometer (Berthold, Oak Ridge, TN, USA). The Firefly luciferase activities were normalized internally to the Renilla luciferase activities and expressed relative to the matched sample transfected with control miRNA expression vector. The transfection reagent used was initially FuGENE6 (Roche) and was later switched to 25kDa linear polyethylenimine for improved transfection efficiency and reduced costs. The luciferase reporter assays were optimized with respect to the transfection efficiency and the ratio of the miRNA expression vector to the luciferase reporter construct transfected.

2.8.1 Rationale for luciferase reporter constructs and cell lines

Initially, luciferase reporter constructs were prepared to include as much of the 3’UTR of candidate target genes as technically possible (up to ~1 kb). Although this approach allows the miRNA binding site to be presented in its native sequence context, this approach may increase the stringency of the conditions for miRNA binding. For example, it has been reported that RNA binding proteins can block a miRNA binding site in the target transcript.86 It is also conceivable that nearby RNA binding proteins may regulate accessibility of the binding site, through physical occlusion, modifying the secondary structure of the 3’UTR, or interacting with the Argonaute protein.54 Cell types or conditions in which repressing co-factors are present or activating co- factors are absent would therefore not permit miRNA binding. In order to circumvent such complications and to avoid premature dismissal of candidates in the preliminary luciferase reporter screen, only the putative binding site of each candidate was cloned into the luciferase reporter vector. Mutated variants of these cloned were also constructed.

PFSK cells were first used for the reporter assays, since they are the only established CNS-PNET cell line. Due to the low transfection efficiency in PFSK cells, HEK293TV cells were used instead; however, non-specific squelching was observed in these cells. The assays were ultimately performed in NCCIT cells, whose transfection efficiency was higher than PFSK and in which squelching was minimal. Additionally, NCCIT cells endogenously express an appreciable level of miR-520g, which indicates that they may have the necessary co-factors for miR-520g function. In contrast, neither hNSC nor any of the PNET cell lines in the lab express miR-520g endogenously.

2.8.2 Positive controls for luciferase reporter assay

To rule out negative results in the luciferase reporter assay with confidence, a positive control is required; unfortunately, there are no known validated miR-520g targets to date. Some evidence from Liao et al.87 suggest that ABCG2 is a target of miR-520h (which is highly similar to miR- 520g). The authors, however, did not validate the predicted target binding site through mutagenesis. Nonetheless, in the absence of known targets, ABCG2 was selected as a positive control (pmirGLO-ABCG2-olg and pmirGLO-ABCG2-m1-olg). Included as a second positive control was a reporter construct containing a sequence complementary to the entire mature miR- 520g (pmirGLO-miR-520g-t). To determine whether the seed sequence (nucleotides 2-7) binding

paradigm holds for miR-520g, two variants of the second positive control were included. The two mutants harbour mutations that disrupt base-pairing with either the 5’ end or the 3’ end of the mature miR-520g (pmirGLO-miR-520g-t1m1 and pmirGLO-miR-520g-t1m2). The third set of positive controls consisted of constructs in which the seed match alone – or 2, 4, or 8 tandem copies thereof – is cloned downstream of the reporter (pmirGLO-miR-520g-s2, pmirGLO-miR- 520g-s4, and pmirGLO-miR-520g-s8). Mutated variants of these positive controls were also included (pmirGLO-miR-520g-s2m, pmirGLO-miR-520g-s4m, and pmirGLO-miR-520g-s8m).

2.8.3 Optimized conditions for luciferase reporter assay

Transfection in HEK293TV with PEI is optimal at an N/P ratio of roughly 40, as determined by GFP transfection efficiency (data not shown). The minimum amount of luciferase reporter plasmid required is 100 ng (Supplemental Figure 1). The pmirGLO-miR-520g-s4 positive control luciferase construct did not exhibit repression, in comparison to the pmirGLO control, at any ratio of miRNA expression plasmid to luciferase reporter plasmid (miRNA/luciferase ratio) tested (Supplemental Figure 2). Luciferase activity of the pmirGLO control is non-specifically repressed with increasing dose of the miRNA expression plasmid due to squelching (overloading of transcription and translation molecular machinery). As the pCDH backbone induces high level expression of many extraneous proteins, the miRNA expression plasmid was switched to pcDNA, which does not induce mammalian expression of any gene besides the neomycin resistance marker and the miRNA hairpin in mammalian cells. The squelching effect was alleviated to some extent, though miR-520g did not repress the expression of the luciferase reporter in pmirGLO-miR-520g-s4 in comparison to pmirGLO transfected cells at any tested dose (Supplemental Figure 2).

Transfection in NCCIT with PEI is optimal at an N/P ratio of roughly 40 (Supplemental Figure 3). However, at this N/P ratio, transfection exhibited toxicity, as determined by morphological features and Trypan Blue staining (not shown). Therefore, a lower N/P ratio of 15.5 is adopted, which still yields high luciferase signals. The minimum amount of luciferase reporter plasmid required is 250 ng (Supplemental Figure 3).

Expression of miR-520g post transfection in NCCIT was verified by qRT-PCR (Supplemental Figure 4). The pmirGLO-miR-520g-t positive control luciferase construct exhibited repression

in comparison to the pmirGLO control at a miRNA/luciferase ratio of 2 (600 ng of miR-520g expression vector to 300 ng of luciferase construct; Supplemental Figure 5).

2.9 Analyses of miRNA expression data

Expression data were retrieved from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). The miRNA expression profiles of human embryonic stem cells (hESC) and different normal tissues were retrieved from accessions GSE14473 and GSE11806, normalized, preprocessed, and re-annotated using more recent probe annotations. The miRNA expressions of undifferentiated and differentiated hESC were compared using heteroscedastic paired Student’s t-test.

2.10 Expression array profiling

The expression array profiles of tumour samples and cell lines have been published in Li et al.2 The data are deposited at GEO under the accession code GSE16988.

2.11 Expression data analysis

2.11.1 Normalization

Data analyses were performed with Illumina BeadStudio (v3.1.7) and Bioconductor packages (v2.3)88 in the R programming environment (v 2.7.1). The image data were analyzed using the BeadStudio, the output files of which were imported into the R using the lumi package (v1.8.3)89. Probe set signal intensities were averaged. Expression profiles were then log2 transformed and quantile normalized90 for downstream analyses.

2.11.2 Differential expression

Genes that are differentially expressed between tumour samples exhibiting and not exhibiting the chr19q amplicon were identified by unpaired, heteroscedastic, two-tailed Student’s t-tests, corrected for multiple testing using the false discovery rate (FDR) method. Comparisons of miRNA overexpressing and control cell lines were analyzed similarly.

2.11.3 Enrichment analysis of tumour expression profiles

The expression profiles of tumours with C19MC amplification were compared against those without. Genes that were declared significantly upregulated or downregulated were separately

subjected to gene ontology enrichment analysis using GoStat,91 restricting the search to biological processes.

2.11.4 KEGG pathway enrichment analysis of PFSK and hNSC expression profiles

Cells stably overexpressing miR-520g were compared to the parental background to identify significantly dysregulated genes, which were subsequently subjected to enrichment analysis by the hypergeometric test using gene annotations in the Kyto Encyclopedia of Genes and Genomes (KEGG) database. Custom R scripts and Bioconductor packages were used to retrieve the up-to- date annotation data from the KEGG database, compute pathway enrichment in significantly dysregulated genes based on the hypergeometric test, and adjust for multiple testing by the Bonferroni method.

2.12 miRNA target prediction algorithms

Three different prediction algorithms were used: miRanda92, TargetScan93, and PITA94. The predictions of the miRanda algorithm are based on sequence complementarity between the miRNA and the target site, binding energy of the miRNA-target duplex, and evolutionary conservation of the target site sequence. Although miRanda does not require target sites to have stringent pairing with the microRNA seed, it favours complementarity to the 5’ end of the miRNA, as it has been shown that 5’ pairing is more important than 3’ pairing.95 This algorithm yielded the most putative targets (2276) for miR-520g. The TargetScan algorithm, in contrast, imposes a stringent conserved seed pairing criterion on its predictions, which is possibly the reason why it has been accredited with a low false positive rate.46,96 With a stringent conserved seed pairing requirement, however, some potential targets targeted by “seedless” pairing may be overlooked. A more recent algorithm, PITA, introduces the site accessibility: whether the secondary RNA structure of the 3’UTR is conducive to miRNA binding. Additionally, since PITA does not consider site conservation, it may be a more appropriate algorithm for predicting targets of a poorly conserved miRNA such as miR-520g. Notwithstanding the limitations of each of these three algorithms, their consensus integrates various lines of computational evidence and may provide a bona fide candidate target list.

Chapter 3 Results

Data presented in this chapter have been published in part in:

Li, M., Lee, K.F., Lu, Y., Clarke, I., Shih, D., Eberhart, C., Collins, V.P., Van Meter, T., Picard, D., Zhou, L., Boutros, P.C., Modena, P., Liang, M.L., Scherer, S.W., Bouffet, E., Rutka, J.T., Pomeroy, S.L., Lau, C.C., Taylor, M.D., Gajjar, A., Dirks, P.B., Hawkins, C.E. & Huang, A. Frequent amplification of a chr19q13.41 microRNA polycistron in aggressive primitive neuroectodermal brain tumors. Cancer Cell 16, 533-46 (2009).

Data attribution

I generated date for figures 2C, 4A, 6A, and 7C of the publication, under the supervision of Dr. Paul Boutros and Dr. Annie Huang.

The retinoic acid differentiation experiment (Figure 3.3) was performed with the help of Mohamed Ahmed. Propagation and differentiation of hNSCs for experiments depicted in Figure 3.8 were done by Dr. Ian D. Clarke.

3.1 Endogenous expression pattern of miR-520g

3.1.1 Rationale

In the context of CNS-PNET, miR-520g is an oncogene.2 Its oncogenic function, however, appear to be highly dependent on cellular background. To gain some insight into the molecular environment in which miR-520g cooperate with other factors and act upon downstream targets, I examined the endogenous expression pattern of miR-520g, in order to better understand its physiological role. miR-520g exhibited cell-type specific and context dependent functions when it was introduced into different cells types, as shown in our recent work.2 Overexpression of miR-520g resulted in increased anchorage-independent growth in Daoy (medulloblastoma cell line), but not PFSK (CNS-PNET cell line) or NIH3T3 (mouse fibroblast) cells, as assessed by soft agar colony formation assay. Ectopic (flank) xenograft formation was enhanced for miR-520g overexpressing Daoy and NIH3T3, while poor tumour engraftment was observed in both miR- 520g overexpressing and control PFSK cells. In addition, while the growth curves of miR-520g overexpressing and control cells in the Daoy, PFSK, NIH3T3 and hNSC background were comparable under their respective normal growth conditions, miR-520g overexpressing hNSCs failed to growth arrest under differentiating conditions. Collectively, these observations suggest that miR-520g function likely require cooperating factors, which are not present in most cell types and contexts. In particular, the cellular effect of miR-520g is most potent under differentiation conditions. The last observation further suggest that miR-520g plays a role in stem/progenitor cell differentiation, a tightly controlled process involving many proteins and miRNAs that are induced and suppressed under complex temporal conditions. Insofar as miR- 520g function is strongly dependent on cell type and context, a key step toward understanding its function is to determine the tissues, cell types, and developmental stage in which miR-520g is expressed.

To this end, I have analyzed publically available miRNA expression profile data and investigated changes in miR-520g expression during cellular differentiation of an embryonal carcinoma cell line. The basic tenet of these analyses is that a gene must be expressed in order for it to exert its function in a given tissue. While expression does not necessarily imply function, the absence of

expression suggests that the gene may not be relevant in a given tissue under the assay conditions.

3.1.2 Change in miR-520g and C19MC microRNAs expression upon differentiation of human embryonic stem cells

Expression profile data retrieved from the GEO for human embryonic stem cells (hESCs) were analyzed to determine the changes in C19MC miRNA expression upon differentiation. In this dataset, a panel of 9 NIH-approved hESC lines was cultured under conditions for either maintenance of undifferentiated state or undirected differentiation into multiple lineages. (Refer to description for GEO accession GSE14473.) All of the C19MC miRNAs available on the platform exhibited significant downregulation upon differentiation of hESCs, as confirmed by the paired t-test after correction for multiple hypotheses testing (Figure 3.1). In particular, miR- 520g was significantly downregulated by 6.2 fold (q < 0.0001). This observation is consistent with results from a deep sequencing study of small RNA libraries generated from undifferentiated and differentiated hESCs (H1), in which the authors reported that miR-520g is silenced upon differentiation.97 Several other studies using different cell lines, differentiation protocols, and platforms have also found C19MC expression to be restricted to undifferentiated embryonic stem cells.98-100 These results indicate that miR-520g may function to maintain undifferentiated cellular states.

27 hsa-miR-517a hsa-miR-519c hsa-miR-520c hsa-miR-520d hsa-miR-526b hsa-miR-519b hsa-miR-519e hsa-miR-517c hsa-miR-520b hsa-miR-520g hsa-miR-498 hsa-miR-517b hsa-miR-527 hsa-miR-523 hsa-miR-520f hsa-miR-520e hsa-miR-520h hsa-miR-525 hsa-miR-518f hsa-miR-519d hsa-miR-518e hsa-miR-518b hsa-miR-524 hsa-miR-518c hsa-miR-520a hsa-miR-518d hsa-miR-522

Placental controls

Undifferentiated NTera2 Differentiated NTera2 BG01 BG02 BG03 H13 H14 H1 H7 Undifferentiated H9 HSF6 BG01 BG02 BG03 H13 H14 H1

Differentiated H7 H9 HSF6

0.0 15.0

Figure 3.1. Expression profile of C19MC miRNA in differentiated and undifferentiated hESC. The absolute probe signal for the C19MC miRNAs available on the array platform (Agilent-016436 Human miRNA Microarray 1.0) are shown for 9 different NIH-approved hESC. The cells were grown under normal growth conditions or differentiating conditions. Placental control and the embryonic carcinoma cell line NTera-2 were also included. The raw data were retrieved from GEO accession GSE14473. All miRNAs were significantly downregulated in hESCs grown under differentiating conditions compared to normal growth conditions (q < 0.05, after multiple hypothesis adjustment; heteroscedastic paired t-test).

3.1.3 Endogenous expression pattern of miR-520g and C19MC microRNAs across normal tissues

In order to identify tissues in which C19MC miRNA are expressed and thereby postulate their function, expression profiles of C19MC miRNAs across normal tissues were retrieved from the GEO database and analyzed. The results revealed that C19MC miRNAs are most highly expressed in primitive tissue types such as the placenta (Figure 3.2); their expression in the placenta is about ~1000 fold higher than compared to most other tissues. A few miRNAs are also expressed in other tissues, but most miRNAs are absent from differentiated tissues. These findings suggest that C19MC miRNAs play a role in development.

29 Placenta Testes Brain Breast Thymus Liver Ovary Skeletal Muscle Heart hsa-miR-517b hsa-miR-519d hsa-miR-518f hsa-miR-517a hsa-miR-519b hsa-miR-518d hsa-miR-519c hsa-miR-520d hsa-miR-518c hsa-miR-526b hsa-miR-498 hsa-miR-524 hsa-miR-518b hsa-miR-518e hsa-miR-520e hsa-miR-520f hsa-miR-523 hsa-miR-519e hsa-miR-525 hsa-miR-520h hsa-miR-522 hsa-miR-520a hsa-miR-520b hsa-miR-517c hsa-miR-520g hsa-miR-520c hsa-miR-527

-12.0 0.0 12.0

Figure 3.2. Expression profile of C19MC miRNAs in normal tissues. The expression profiles of the C19MC miRNAs available on the platform (Agilent-016436 Human miRNA Microarray 1.0) in different normal tissues are expressed relative to heart tissue. The heart tissue exhibited median expression level for miRNAs. The raw data were retrieved from GEO accession GSE11806.

3.1.4 miR-520g expression changes during retinoic-acid induced differentiation of NCCIT cells

As hNSCs do not express any miR-520g, it is not possible to study the endogenous function of miR-520g in these cells. NCCIT, an embryonal carcinoma cell line widely used for studying neuroepithelial differentiation, in contrast, does express miR-520g when grown under proliferative conditions. Retinoic acid (RA) treatment of NCCIT cells was therefore used as a model to determine the expression changes of miR-520g during neuroepithelial differentiation. The level of miR-520g in NCCIT was downregulated upon RA-induced differentiation compared to the vehicle control, as early as 3 days after treatment (Figure 3.3). This observation suggests that miR-520g may be involved in the maintenance of the undifferentiated state of NCCIT. At day 18, miR-520g is re-expressed, indicating that miR-520g may have additional functions late in neuroepithelial differentiation. The concurrent downregulation of SOX2, a pluripotency marker, confirms that the cells are differentiating in response to retinoic acid treatment.

3.1.5 Summary

C19MC miRNA expression in hESC is downregulated upon differentiation of hESC and they do not appear to be expressed in most adult tissues. These expression patterns suggest that C19MC miRNA may modulate cellular differentiation and may play a role in maintaining hESCs. Normal development likely requires the silencing of C19MC, and aberrant re-activation of C19MC in committed stem/progenitor cells may contribute to tumourigenesis, by allowing the over-expansion of the stem/progenitor cell pool. Various cancers, including CNS-PNET, may arise as a consequence of ectopic expression of C19MC miRNAs in different committed stem/progenitor cells.

miR−520g

1.5 Vehicle (DMSO) Retinoic acid

1.0

0.5 Relative expression Relative

* * * * * 0.0 d0 d3 d6 d9 d12 d15 d18

* * *

Figure 3.3. Changes in miR-520g expression levels in NCCIT upon retinoic acid treatment. (A) NCCIT cells were treated with retinoic acid or vehicle (DMSO) for 18 days. miR-520g expression was measured by qRT-PCR every three days. Expression levels were normalized to the U6 control and expressed relative to the paired vehicle treatment. (B) The loss of SOX2 expression upon treatment confirms that retinoic acid induced differentiation of NCCIT cells. Expression levels were normalized to the 36B4 control and expressed relative to the paired vehicle treatment. Bars represent means of triplicates ≤ SEM; * p < 0.05, Student’s t-test. Results are representative of two independent experiments.

3.2 Pathways regulated by miR-520g

3.2.1 Rationale

An important step toward understanding the function of a miRNA is identifying the specific targets that it regulates. miRNA target prediction has been the subject of much experimental and bioinformatic research efforts, which has revealed that miRNA target recognition is more complex than originally first determined in Drosophila.

The miRNA “seed”, encompassing nucleotides 2-7 in the 5’ region of the mature sequence, is important for miRNA binding to target transcript. In Drosophila, Lai et al.101 first observed that two 3’UTR motifs, the K box and the Brd box, mediate negative post-transcriptional repression, and these motifs are often perfectly complementary to the seed of targeting microRNAs. Mutations in the K box,102 the Brd box,103 and the seed104 all abrogate the post-transcriptional repression of the target transcript by the miRNA. Not all miRNAs, however, require seed complementary for target repression, as Lal et al.105 have recently shown that miR-24 regulate expression of targets through seedless but highly complementary sequences. Above all, miRNA targets can be predicted based on complementarity of the sequences of the miRNA and the target, though determinants outside of the seed sequence also contribute to target recognition.

Since miRNAs mediates its effect through complementary base pairing, computation target predictions largely use sequence and conservation information of mRNA transcripts and miRNAs. Based on computational analysis of evolutionarily conserved motifs in 3’UTRs, conserved microRNAs have been estimated to regulate at least 20% of human genes.106 Further, genome-wide statistical analyses revealed that conserved miRNA can potentially regulate a high number of targets.46,104,106 These estimates were based on evolutionary conservation, however; whether they apply to poorly conserved miRNAs remain unknown.

Given that miR-520g and many other C19MC miRNAs are poorly conserved and primate- specific, prediction algorithms using conservation as a criterion would dismiss potential primate- specific targets. Algorithms principally based on seed sequence match and/or binding energy, however, typically predict much larger set of candidate targets.46 In fact, target predictions without conservation requirement have a markedly higher false positive rate compared to

predictions with conservation requirement.46 Therefore, prediction algorithms without conservation requirement may not be suitable for an initial miRNA target screen.

While C19MC is primate-specific as a cluster, the seed sequences of C19MC miRNAs are similar to better conserved clusters such as miR-17-92, miR-302, and miR-371-373,107 which suggest that some of their targets may be overlapping. Prioritizing targets with putative binding sites that are conserved would thus, in theory, identify targets that are jointly targeted by conserved and non-conserved miRNAs with similar seed sequences and functions.† In this way, the number of false positive predicts may be reduced.

Even conservation-based algorithms have less than desirable accuracy rates, however. It has been observed that even one of most stringent algorithms, TargetScan,46 have an accuracy of less than 50% for conserved miRNAs,46,96 and may be even lower for non-conserved miRNAs. This low accuracy may be attributable to both the limitation of conservation and seed sequence based prediction, as well as the cellular and environmental context dependent actions of miRNAs. Indeed, the expression profile changes upon miR-520g overexpression were vastly different among Daoy, PFSK, and hNSC cell line: significantly dysregulated genes had very little overlap among the various cell line backgrounds (Figure 3.4). Further adding to the complexity of the puzzle, cumulating evidence suggest that miRNAs typically have modest but widespread repressive effects on the protein and/or RNA levels of its targets.108,109 A single miRNA may thus target a signalling pathway at multiple levels, in addition to fine-tuning multiple signalling pathways.

To address these issues, I used a combination of different approaches, in order to identify signalling pathways and genes targeted by miR-520g (Figure 3.5). In the first strategy, I compared expression profiles of tumours with C19MC amplification against those without and identified dysregulated biological processes. I then assessed whether the dysregulation may be attributable to miR-520g overexpression in the cell cultures. In the second strategy, I analyzed the expression profiles of miR-520g over-expressing cells and identified dysregulated pathways. Coupled with computational predictions based on multiple algorithms, I tested putative targets of

† Indeed, some of the promising predicted miR-520g targets are also targeted by better conserved miRNAs.

34 the dysregulated pathways. In the third strategy, I selected from the list of commonly predicted targets that were also downregulated in miR-520g over-expressing cells and have biological functions in development. Selected candidate genes from the above approaches were subsequently subject to downstream experimental validation by luciferase reporter assay and western immunoblotting. Above all, biologically relevant miR-520g targets must fulfill the criteria outlined in Table 3.I.

Table 3.I. Criteria for validating candidate miR-520g targets

Criteria Required Biological function explains miRNA overexpression phenotype: Yes Development TGF-beta signalling Cell cycle Apoptosis Binding site predicted by at least one of: Yes TargetScan, PITA, miRanda RNA expression downregulated upon miRNA overexpression Optional Luciferase reporter assay shows repression Yes Protein expression downregulated upon miRNA overexpression Yes Resulting phenotype can be rescued by re-introducing target protein Yes

Downregulated genes Upregulated genes

Daoy 0 PFSK Daoy 0 PFSK

56 79 74 72

4 0 0 14 0 0

2574 01370 2740 00 152

0 0 9 0 15 0 hNSC (+FBS) 1 3 hNSC (−EGF −bFGF) hNSC (+FBS) 1 1 hNSC (−EGF −bFGF)

343 190

hNSC (+FBS) 0 hNSC (−EGF −bFGF) hNSC (+FBS) 0 hNSC (−EGF −bFGF)

2250 128 2434 149

257 212 1 272 129 0

203 11911 401 214 536 306

5 4 8 70 3 50 hNSC (+EGF +bFGF) 0 10 Tumour hNSC (+EGF +bFGF) 0 13 Tumour

2 1

Figure 3.4. Expression profile differences of miR-520g overexpressing cells. Venn diagrams represent the degree of overlap between significantly dysregulated genes upon miR-520g overexpression in different cell lines and growth conditions. Genes significantly upregulated or downregulated in the comparison between cells stably transfected with miR-520g or the empty expression vector were identified by heteroscedatistic independent t-tests, with correction for multiple hypothesis testing by the false discovery rate method. Genes significantly upregulated or downregulated in tumours exhibiting the C19MC amplicon were also analyzed. The hNSCs were cultured in normal growth conditions (+EGF +bFGF) or two differentiating conditions (+FBS, serum exposure; or -EGF –bFGF, growth factor withdrawal).

Candidate

miRNA miRNA Biological Expression overexpression binding function

miRNA knockdown Protein RNA In vitro In silico

Endogenous Conservation coexpression Reporter assay Binding energy Ago IP ELISA RT-PCR Seed pairing

Western Expression array Site Target accessibility Immuno- histochemistry Expression Functional pattern

Figure 3.5. Approaches to validate miRNA target candidates. Flow chart outlines the different approaches to validate miRNA target candidates. A target should be coexpressed (at the RNA level) with the miRNA, and its expression (at the protein level and possibly at the RNA level) should change upon miRNA overexpression or knockdown, as measured by various molecular methods. The target must also be shown to be bound by the miRNA, typically by the luciferase reporter assay. Computation algorithms use a multitude of criteria for making target predictions. Further, as miRNAs generally target many transcripts, whether the biological function of the candidate is consistent with that of the miRNA should also be considered. Criteria are discussed in more detail in Kuhn et al.110

3.2.2 Target identification strategy I

Biological processes that are dysregulated by C19MC amplification were first identified by comparing tumours with C19MC amplification against those without. The genes involved in C19MC-disrupted biological processes were then tested in cell cultures, in order to determine whether their dysregulation in the tumours are specifically attributable to miR-520g action. Since this strategy does not pre-filter genes based on the presence of predicted miRNA binding sites, it bypasses the aforementioned limitations of stringent prediction algorithms. After genes dysregulated by miR-520g are identified, putative binding sites in these genes can then be determined by sensitive prediction algorithms. Two of such algorithms are RNA22111 and DIANA-MicroT112, which do not impose any cross-species conservation requirement. No candidate genes, however, were identified by this strategy, as detailed in the ensuing sections.

Determining processes disrupted by C19MC amplification by comparing expression profiles of tumours

To determine the effect of C19MC amplification and consequently the function of C19MC miRNAs, the expression profiles of tumours with C19MC amplification were compared against those without. Significantly dysregulated genes were then subjected to enrichment analysis. The results showed that the upregulated gene list was enriched for genes involved in developmental signalling pathways, such as genes of the Frizzled and Wingless family (Figure 3.6). Conversely, the downregulated genes are found to be involved in apoptosis significantly more often than expected by chance.

C19MC amp No C19MC amp

P-value

PNET42 PNET39 PNET40 PNET3 PNET5 PNET6 PNET15 PNET20 PNET24 PNET22 PNET48 PNET41 PNET43 PNET44 PNET45 PNET46 PNET47 PNET36 PNET37 PNET25 PNET30 PNET2 PNET4 PNET7 PNET9 PNET16 PNET17 PNET18 PNET19 PNET31 PNET32 PNET34 PNET35 (Fold change) FZD2 FZD7 FZD10 SFRP1 SFRP2 < 0.00001 WNT5A 2.7 ~ 13.8 WNT7A C8ORF4 CRABP1 IGF2BP2 PAK1 < 0.0005 LRP2 1.9 ~ 3.3 FZD3 STMN2 NR2F1 NKX2-2 NKX6-2 POU3F2 PBX2 LIN28B SALL4 IGF2BP3 LDB2 < 0.0005 MEIS1 PCDH18 1.5 ~ 12.5 CNTN2 DACH1 EBF3 FGF13 HES5 MSI1 PTCH1 RND1 SOX11 TUBB3 API5 BCL6 BAD < 0.001 CRYAB -1.3 ~ -8.3 CDKN1B BECN1 BCL2A1 TLR2 TRADD Apoptosis Survival and Self-renewal DAD1 < 0.0005 AIFM2 -1.1 ~ -3.0 CIDEB RELA MAP3K5 TAX1BP1 CDKN2C

-3.0 0.0 3.0

Figure 3.6. Enrichment analysis of dysregulated genes in C19MC amplified tumours. Heatmap represents the expression profile of select genes differentially expressed between C19MC amplified and non-amplified tumours (q < 0.05; heteroscedastic independent t-test, after multiple hypothesis correction). Upregulated genes are enriched for genes involved in developmental signalling; downregulated genes are enriched for genes involved in apoptosis. Data presented are published in Li et al.2

miR-520g may regulate the apoptosis pathway

As miR-520g (in addition to miR-517c) is one of the most highly upregulated miRNA in C19MC, much of the difference in gene expression for C19MC amplified tumours may be attributed to miR-520g (or miR-517c) function. Using expression changes in the tumours and the biological functions of the genes to select target candidates can potentially circumvent the inaccuracy of the target prediction algorithms. This approach, however, may be confounded by the heterogeneity of the tumours and of their expression profiles, normal tissue contaminants in samples, and the potential synergistic contributions of other C19MC microRNAs. Notwithstanding these limitations, it is reasonable to hypothesize that some of the apoptosis genes downregulated in C19MC amplified tumours may be targets of miR-520g, since miR-520g confers resistance to apoptosis consistently across different cell line backgrounds.2

The question of whether the apoptosis genes downregulated in C19MC amplified tumours are miR-520g (or miR-517c) targets was addressed using qRT-PCR. RNA levels of candidate targets were measured in cells with and without stable miR-520g (or miR-517c) overexpression, in the context of an apoptotic trigger. The Daoy cell line was used, since it exhibited the most robust resistance to apoptosis upon stable miR-520g (or miR-517c) overexpression.2 None of the tested genes exhibited a qRT-PCR expression profile upon serum withdrawal that would explain the anti-apoptotic phenotype of miR-520g overexpression (Figure 3.7; Supplemental Table I). As miRNAs can modulate target protein expression without changes in target RNA level, miR-520g (or miR-517c) may yet modulate the translation of apoptosis genes. In summary, these results suggest that apoptosis resistance may be a secondary effect of miR-520g (or miR-517c) function and not a consequence of direct miR-520g (or miR-517c) action on apoptotic pathway genes.

MAP3K5 BCL6

5 5 10% FBS 48h 10% FBS 48h 0.1% FBS 48h 4 0.1% FBS 48h 4 0.1% FBS 72h 0.1% FBS 72h

3 3

2 2 Relative expression Relative expression Relative 1 1

0 0

Daoy−pcDNA Daoy−520g Daoy−517c Daoy−pcDNA Daoy−520g Daoy−517c

CDKN1B BAD

3.5 5 10% FBS 48h 10% FBS 48h 0.1% FBS 48h 3.0 0.1% FBS 48h 4 0.1% FBS 72h 0.1% FBS 72h 2.5

3 2.0

1.5 2

Relative expression Relative expression Relative 1.0 1 0.5

0 0.0

Daoy−pcDNA Daoy−520g Daoy−517c Daoy−pcDNA Daoy−520g Daoy−517c

VEGFA CD38

10% FBS 48h 4 10% FBS 48h 8 0.1% FBS 48h 0.1% FBS 48h 0.1% FBS 72h 0.1% FBS 72h 3 6

4 2 Relative expression Relative expression Relative 2 1

0 0 Daoy−pcDNA Daoy−520g Daoy−517c Daoy−pcDNA Daoy−520g Daoy−517c

Figure 3.7. qRT-PCR of apoptosis genes in miR-520g overexpressing cells. RNA expressions relative to control cells (Daoy-pcDNA in 10% FBS) are shown for select genes with function in apoptosis that are downregulated in C19MC amplified tumours. Daoy cells overexpressing miR-520g or miR-517c and control cells were growth in media containing 10% or 0.1% FBS and harvested after 48h or 72h. Bars represent means from two experiments in at least two replicates ≤ SEM. Genes whose inductions upon serum starvation are suppressed in the presence of miR-520g or miR-517c would be considered promising candidates; no such genes were identified.

3.2.3 Target identification strategy II

Given that miRNAs may regulate pathways by targeting multiple genes, it may be feasible to first identify broad target pathways and then home in on specific target genes. Therefore, I first determined pathways that are dysregulated in the context of miR-520g overexpression. The two cell lines used, hNSC and PFSK, do not express miR-520g endogenously. PFSK is a CNS-PNET cell line. Conversely, the hNSC model was used, because CNS-PNET display markers of all three primary CNS lineages and may be derived from early progenitors during development. Next, I identified candidate genes whose RNA expressions were downregulated by miR-520g overexpression using qRT-PCR. However, since miRNAs do not necessarily suppress targets at the RNA level, candidates whose RNA expression remained unchanged were not excluded from downstream validation. As with Strategy I, this approach may circumvent the limitations of stringent prediction algorithms.

Identifying specific pathways disrupted by miR-520g overexpression

Developmental signalling pathways are often dysregulated in pediatric brain tumourigenesis, especially those involved in differentiation and cell fate decisions. Indeed, miR-520g expression diminishes as embryonic stem cells differentiate. We thus investigated whether they are similarly dysregulated upon miR-520g overexpression. Cells stably overexpressing miR-520g were compared to the parent background to identify significantly dysregulated genes, which were subsequently subjected to enrichment analysis, restricted to developmental signalling pathways widely implicated in cancer.

In the hNSC background, miR-520g overexpression led to the dysregulation of genes involved in the Wnt, Notch, Hedgehog, and TGF-b signalling pathways (Figure 3.8). Conversely for PFSK cells, miR-520g overexpression did not significantly result in the dysregulation of genes involved in any of the tested signalling pathways, after multiple hypotheses testing correction; however, miR-520g overexpression appeared to have the most effect on Wnt signalling genes. One possible explanation for the lack of pathway enrichment among dysregulated genes in PFSK cells is that they were cultured under normal growth conditions, whereas the hNSC cells were cultured under differentiating conditions. Although PFSK is among the few CNS-PNET cell lines available, the lack of an established differentiation protocol for PNET cells may limit its use for studying miR-520g function.

PFSK hNSC p-value p-value

18 3.5e-04 32 2.5e-05 WNT WNT 10 0.016 46 1.3e-08

6 0.019 6 0.29 Notch Notch 4 0.044 12 0.011

2 0.77 12 0.0097 Hedgehog Hedgehog 2 0.52 16 0.0021 miR−517c miR−517c 9 miR−520g 0.022 18 miR−520g 0.0016 SIGNALING PATHWAY TGF−β TGF−β 4 0.26 21 0.0027

012345 0246810 SIGNIFICANCE OF ENRICHMENT (-log p)

Figure 3.8. KEGG Pathway enrichment analysis of miRNA-overpressing PFSK and hNSC expression profiles. Bars represent significance of enrichment for KEGG signalling pathways in genes significantly dysregulated in PFSK or hNSC overexpressing miR-517c or miR-520g. Higher [-log p] values indicate greater significance, as determined by the hypergeometric test. Numbers of significantly dysregulated genes that fall into each signalling pathway category according to the KEGG database are shown. The Bonferroni-corrected significance levels (-log p value thresholds) are indicated by the dashed lines. Data presented are published in Li et al.2

Using hNSC as the model for studying miR-520g function, all four of the aforementioned developmental signalling pathways represent attractive candidate miR-520g target pathways. In particular, Wnt signalling113 and TGF-b signalling114 have been implicated in stem cell potency and function, warranting further target searches in these pathways. Genes from these pathways (PRICKLE2, BMP6, SMAD3, and TGFBR3) were further subjected to screening by qRT-PCR together with genes identified by Strategy III detailed below.

3.2.4 Target identification strategy III

In order to enhance the specificity of miRNA target prediction algorithms, the predictions from different algorithms were intersected to derive a set of commonly predicted targets. Next, the RNA expression levels of the candidates were determined in cells overexpressing miR-520g.

Candidates whose RNA expressions decreased upon miR-520g overexpression were considered promising, though those with unchanged RNA expressions may yet be miR-520g targets.

Predicting miR-520g targets using different algorithms

Target identification is a necessary step in understanding the function of miR-520g, as well as validating its putative target signalling pathways. Prediction algorithms can help narrow the search space and facilitate focused experiments. As different algorithms use different criteria and approaches for predicting targets (reviewed in Bartel et al.46), the consensus of their predictions may offer a list of bona fide candidates for downstream validation. Three different algorithms where chosen: miRanda92, TargetScan93, and PITA94. Refer to Materials and Methods for a discussion on the criteria used by the different algorithms. The consensus of their predictions provided a list of 64 candidate targets (Figure 3.9; Table 3.II) that are supported by several lines of computational evidence and thus serves as a starting point for downstream validation.

TargetScan Pita TargetScan Pita

miR-520g miR-517c

126 18 40 9 0 6

64 7 195 93 9 11

TargetScan 403 1924 TargetScan 25 368 Pita 215 Pita 24 miRanda 2276 miRanda 395 Total 2460 Total 410 miRanda miRanda

Figure 3.9. Overlap of predicted targets by different algorithms. Venn diagrams represent the degree of agreement between miR-520g (or miR-517c) target predictions by TargetScan, Pita, and miRanda. Poor agreements in predicted targets were observed for both miR-520g and miR-517c.

Table 3.II. Common predicted miR-520g targets by TargetScan, PITA, and miRanda.

AFF4 MXD1 ANGPT1 NAALADL2 ARID4B NEUROD2 ARL4C NHLH1 ATP2B2 NPAS3 ATRX NPTX1 BAI2 NR4A2 BMP6 NR4A3 BNIP3L NUFIP2 CALU PDIA3 CAMK2N1 PITX1 CHUK PLAGL2 CIC PLCB1 CKS1B PPP6C CPEB3 PRICKLE2 CROP PRRX1 CUL3 PRUNE DBN1 RND3 DPYSL5 SEPT8 DYRK1A SLC41A1 EIF5 SMOC2 FLRT2 SORL1 IGSF3 SS18L1 ITPKB SUV420H1 KIF26B TLE4 KLF10 TMEM123 KLF12 TMUB2 LHX8 TNFAIP1 LRRTM3 TNRC6A MAPRE1 TRPS1 MID1 TTN MIPOL1 XRRA1

Determining RNA expression changes of candidates upon miR-520g overexpression

To screen through candidate targets, qRT-PCR was used to determine whether the candidate RNA expressions are downregulated in PFSK and hNSC cells stably overexpressing miR-520g. Candidates were selected based on consensus target prediction, their involvement or crosstalk with the Wnt and TGF-b signalling pathways, their known tumourigenic function in the literature, as well as their microarray expression profiles in cells overexpressing miR-520g.

Promising candidates that exhibited downregulation upon stable miR-520g overexpression in the hNSC included TGFBR3, NPTX1, BAI2, TNRC6A, TRPS1, AFF4, and TNFAIP1 (Figure 3.10). Although the expression levels of most of these genes did not change in PFSK cells overexpressing miR-520g, hNSCs are likely a better model for studying miR-520g function, given the phenotypes observed in hNSC overexpressing miR-520g. These genes served as candidate targets for further validation.

TGFBR3 NPTX1

pcDNA pcDNA 1.5 miR−520g 1.5 miR−520g

1.0 * * 1.0 *

Relative expression Relative * 0.5 * expression Relative 0.5

* * 0.0 0.0

PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

BAI2 TNRC6A

pcDNA 2.0 pcDNA miR−520g miR−520g 1.5

1.5

1.0 1.0 * * Relative expression Relative Relative expression Relative 0.5 * 0.5 *

0.0 0.0

PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

AFF4 TNFAIP1

2.0 pcDNA pcDNA miR−520g 1.5 miR−520g

1.5

1.0 1.0 * * * * Relative expression Relative Relative expression Relative 0.5 * 0.5

0.0 0.0

PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

TRPS1

2.0 pcDNA miR−520g 1.5

1.0

Relative expression Relative 0.5 * 0.0 * PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

BMP6 SMAD3

2.0 pcDNA pcDNA miR−520g miR−520g 6 1.5

4 * 1.0 * Relative expression Relative Relative expression Relative 0.5 2 * * 0.0 0

PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

SORL1 KLF12

1.5 4 pcDNA pcDNA miR−520g miR−520g

3 * 1.0 * * 2

0.5 Relative expression Relative Relative expression Relative 1 * 0 0.0

PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

TLE4 PRICKLE2

2.0 pcDNA 12 pcDNA miR−520g miR−520g 1.5 * 10 * 8

1.0 * 6 Relative expression Relative Relative expression Relative 4 0.5 * 2

0.0 0 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2 PFSK−r1 PFSK−r2 hNSC−d1 hNSC−d2

Figure 3.10. qRT-PCR of target candidates in PFSK-520g and hNSC-520g cells. RNA expressions relative to control cells (pcDNA) are shown for genes predicted to harbour miR-520g binding sites. PFSK cells overexpressing miR-520g were thawed from two independent stocks (PFSK-r1 and PFSK-r2) and cultured in normal growth conditions. The hNSCs were cultured under two differentiating conditions: FBS exposure (hNSC-d1) or growth factor withdrawal (hNSC-d2). Bars represent means from two experiments in at least two replicates ≤ SEM; * p < 0.05, Student’s t test.

3.2.5 Downstream validation of candidate target genes

Validating candidate miR-520g targets by luciferase reporter assay

In order to establish that miR-520g binds to the 3’UTR of selected candidate targets and post- transcriptionally repress their expression, luciferase reporter constructs harbouring putative miR- 520g binding sites were prepared, and the activity of the luciferase reporter was measured in the presence or absence of miR-520g (Figure 3.11; Table 3.III). See Materials and Methods for discussions on luciferase reporter constructs, choice of cell line, and positive controls.

The pmirGLO-miR-520g-t positive controls exhibited robust repression upon miR-520g co- transfection in NCCIT (Figure 3.12A). A 40% repression was achieved with the pmirGLO-miR- 520g-t construct, comparable to luciferase assay results reported in the literature. The repression of pmirGLO-miR-520g-t was not enhanced at an increased miRNA/luciferase ratio (Figure 3.12B), indicating the miRNA/luciferase ratio was sufficiently high for miRNA-mediated repression. Repression of pmirGLO-miR-520g-t was abrogated by mutations disrupting either 5’ or 3’ end base-pairing with miR-520g. Moreover, repression was not observed with other constructs intended as positive controls: pmirGLO-miR-520g-s4 and pmirGLO-ABCG2 (Figure 3.12). Repression was similarly not observed in constructs containing a miR-520g binding sites from the 3’UTR of CAMK2N1, CDKN1A, NPTX1, or TGFBR3, suggesting that these candidates may not be direct miR-520g targets. Some candidates (such as CDKN1A), however, harbour more than one predicted miR-520g binding site, which were not tested in the assay (Supplemental Figure 7); repression of such target genes may require miR-520g binding to multiple target sites. Other possibilities for the lack of repression include: dependence of miR- 520g function on factors not expressed by assayed cell lines, the state of the cells following transfection, and insufficiency in the amount of transiently transfected miRNA.

PGK promoterluc2 poly(A) signal Reporter transcript

miR-520g putative binding site 5' ...CAUGAAAAGAGAAAGCACUUUGA... 3’ Target 3' UTR |||| ||||||| 3' UGUGAGAUUUCCCUUC-GUGAAACA 5’ hsa-miR-520g

PGK promoterluc2 poly(A) signal Negative reporter control

mutated miR-520g putative binding site 5' ...CAUGAAAAGAGAAAGGAUUCUCA... 3’ Target 3' UTR |||| | | | 3' UGUGAGAUUUCCCUUC-GUGAAACA 5’ hsa-miR-520g

SV40 promoterhRluc-neo poly(A) signal Internal reporter control

Figure 3.11. Luciferase reporter assay. The pmirGLO plasmid contains both the Firefly luciferase (luc2) locus and the Renilla luciferase (hRluc- neo) internal control locus. Transcripts derived from each locus are shown. Either a fragment of 3’UTR (which contains miR-520g binding sites) of the candidate genes or the putative miR-520g binding site alone (~20 bp) is cloned downstream of the luc2 coding region. In the presence of miR-520g, the reporter transcript may be bound by miR-520g, leading to post-transcriptional regulation of the Firefly luciferase reporter.

Table 3.III. Luciferase reporter constructs.

Name Description Verified pmirGLO Luciferase reporter construct backbone. 9 pmirGLO-miR-520g-s2 Two tandem repeats of the miR-520g seed match 9 (CACTTTGataCACTTTG) pmirGLO-miR-520g-s2m Two tandem repeats of a mutated miR-520g seed match 9 (CAGTATCataCAGTATC) pmirGLO-miR-520g-s4 Four tandem repeats of the miR-520g seed match 9 (CACTTTGataCACTTTGataCACTTTGataCACTTTG) pmirGLO-miR-520g-s4m Four tandem repeats of a mutated miR-520g seed match 9 (CAGTATCataCAGTATCataCAGTATCataCAGTATC) pmirGLO-miR-520g-s8 Eight tandem repeats of the miR-520g seed match 9 pmirGLO-miR-520g-s8m Eight tandem repeats of a mutated miR-520g seed match 9 pmirGLO-miR-520g-t Sequence complementary to the mature miR-520g 9 (ACACTCTAAAGGGAAGCACTTTGT) pmirGLO-miR-520g-t1m1 Sequence complementary to the mature miR-520g with mutations 9 disrupting base-pairing with the 5’ end of miR-520g (ACACTCTAAAGGGAAGATATATAT) pmirGLO-miR-520g-t1m2 Sequence complementary to the mature miR-520g with mutations 9 disrupting base-pairing with the 3’ end of miR-520g (ATATATTTATGGGAAGCACTTTGT) pmirGLO-ABCG2-olg miR-520g binding site in the 3’UTR of ABCG2 9 pmirGLO-ABCG2-m1-olg mutated variant 9 pmirGLO-CAMK2N1-olg miR-520g binding site in the 3’UTR of CAMK2N1 9 pmirGLO-CAMK2N1-m1-olg mutated variant 9 pmirGLO-CDKN1A-olg miR-520g binding site in the 3’UTR of CDKN1A 9 pmirGLO-CDKN1A-m1-olg mutated variant 9 pmirGLO-NPTX1-olg miR-520g binding site in the 3’UTR of NPTX1 9 pmirGLO-NPTX1-m1-olg mutated variant 9 pmirGLO-TGFBR3-olg miR-520g binding site in the 3’UTR of TGFBR3 9 pmirGLO-TGFBR3-m1-olg mutated variant 9 pmirGLO-TGFBR3 Fragment (~1kb) of the TGFBR3 3’UTR 9 pmirGLO-BAI2 BAI2 3’UTR (~300bp) 9 pmirGLO-TNRC6A Fragment (~1kb) of the TNRC6A 3’UTR 9 pmirGLO-AFF4 Fragment (~1kb) of the AFF4 3’UTR 9 pmirGLO-TNFAIP1 Fragment (~1kb) of the TNFAIP1 3’UTR 9 pmirGLO-SMAD7 Fragment (~1kb) of the SMAD7 3’UTR 9

See Materials and Methods for description of construct preparation; see Supplemental Table III for sequences of oligonucleotides/primers used in the preparation.

Figure 3.12. No luciferase reporters of putative miR-520g targets were repressed by miR-520g. NCCIT cells were co-transfected with luciferase constructs and miRNA expression vectors using PEI at an N/P ratio of 15.5 and harvested for luciferase reporter assays 48 hr later. Firefly luciferase activities were normalized to Renilla luciferase activities and expressed as relative values using pcDNA-transfected samples as paired reference. Bars represent mean of replicates ≤ SEM from representative experiments repeated twice; * p < 0.05, Student’s t-test. Results provided no support for any candidate miR-520 target. (A) 300 ng of the luciferase construct and 600 ng of the miRNA expression vector were used. (B) To confirm that sufficient miRNA expression vector was used, the assays were also conducted with 250 ng of the luciferase construct and 750 ng of the miRNA expression vector.

Further validating candidate miR-520g targets using immunoblotting

In order to determine whether any candidates were prematurely dismissed by the luciferase reporter assay, protein expressions of selected candidates were further determined in the presence of miR-520g stable or transient expression by western blotting. SMAD7 and TGFBR3 were included, since miR-520g may modulate TGF-b signalling. Cell cycle inhibitors p21/CDKN1A and p27/CDKN1B were included, since cell regulation plays an important role in differentiation. NPTX1 is involved in neuronal death and miR-520g may target it to mediate the observed apoptosis resistance phenotype.

In cell lines (Daoy and UW228) endogenously expressing p21/CDKN1A, robust downregulation was observed in the presence of stable miR-520g overexpression, suggesting that p21 may be a direct or indirect target of miR-520g (Figure 3.13A). Transient transfection of miR-520g might not effect p21 downregulation in Daoy cells, however (preliminary data not shown). On the other hand, the protein expression of other candidate targets, such as SMAD7 and NPTX1, were not repressed in the presence of stable miR-520g overexpression (in NIH3T3, Daoy, and UW228) or upon transient miR-520g transfection in NCCIT (Figure 3.13). Further, miR-520g-mediated repression of p27/CDKN1B and TGFBR3 was not observed in cells endogenously expressing these proteins.

3.2.6 Specificity of miR-520g mediated repression

The luciferase activity of pmirGLO-miR-520g-t was repressed by miR-520g, while those of the mutant variants were not (Figure 3.12). The pmirGLO-miR-520g-t construct and its variants all have similar accessibility as determined by RNAfold secondary structure prediction (Supplemental Figure 6); therefore, the lack of repression in the mutant constructs cannot be explained by a decrease in site accessibility resulting from the nucleotide substitutions. This suggests that miR-520g-mediated repression is abrogated as a consequence of disruption of base- pairing between miR-520g and the mutant constructs.

Base-pairing disruptions of 5 nucleotides in the 3’ end of miR-520g (pmirGLO-miR-520g-t1m2) abrogated repression, despite intact base-pairing with the miR-520g seed. Further, even the presence of four tandem repeats of the seed match (pmirGLO-miR-520g-s4) did not lead to miR- 520g mediated repression of reporter activity. These findings suggest that base-pairing with the miR-520g seed may not be sufficient for miR-520g mediated silencing. Conversely, base-pairing

disruption of 5 nucleotides in the 5’ end of miR-520g (pmirGLO-t1m1) also abrogated repression. Taken together, these results indicate that miR-520g may only bind highly complementary sites in the target transcript and base-pairing with the 3’ or 5’ end of the miRNA alone is not sufficient.

3.2.7 Summary

Similar to other miRNAs, miR-520g appears to modulate many pathways, especially those involved in development. Although miR-520g confers resistance to apoptosis, it may not directly target genes in the apoptosis pathway. Conversely, miR-520g may regulate cell cycle progression by repressing p21, a pivotal regulator of cell cycle progression in stem cells. Aberrant inhibition of p21 may in turn lead to over-expansion of stem/progenitor cells during CNS development. This potential mechanism would be consistent with the purported role of ectopic miR-520g expression in maintaining neural stem/progenitor cells in CNS-PNET.

Figure 3.13. Western blotting analyses to validate putative miR-520g targets (A) Control cells and cells stably overexpressing miR-520g were cultured in normal growth medium and total protein lysates were harvested at 70~80% confluency. The protein levels of putative miR-520g targets were then determined by immunoblotting. (B) NCCIT cells were transiently transfected with miRNA expression vector (pcDNA-miR-520g), miRNA oligonucleotide (olg-520g), or their respective negative controls (pcDNA and olg-NC). Total protein lysates were harvested 48 hr later. The protein levels of putative miR-520g targets were then determined by immunoblotting. HEK293, HeLa, and NIH3T3 lysates were included as control samples. Antibody against actin was used as a loading control. Results are representative of at least two independent experiments.

Chapter 4 Discussions and Future Directions

4.1 The role of miR-520g and other C19MC miRNAs in development

As a gene must be expressed in order to exert its function, characterizing the expression pattern of a gene is a crucial step toward understanding its function. For miR-520g and C19MC miRNAs, analyses of their expression profiles suggest that they may be involved in early development, since they are expressed in embryonic stem cells and primitive tissues such as the placenta.

Expression analysis revealed that C19MC miRNAs are predominately expressed in the placenta; this restricted expression of C19MC miRNAs have also been reported in many other studies: microarray,57,115 northern blotting,56 and small RNA library sequencing.116 This expression pattern suggests that C19MC miRNAs are involved in placental development. Paradoxically, the entire miRNA cluster is found only in the primate order of placental mammals (eutherians), suggesting that C19MC miRNAs may be dispensable for placental development and may also function in specific developmental states not assayed in these expression screens.

Analyses of publically available expression data and observations in other studies collectively suggest that they are expressed predominately in the placenta, choriocarcinoma (trophoblastic cancer of the placenta)107, undifferentiated hESCs, and embryonal carcinoma.98,107,117-120 Taking the expression patterns reported in these studies together, C19MC miRNAs are expressed early during embryonic development (at the blastocysts stage or earlier) in both the embryoblast and trophoblast compartments. While C19MC miRNA expression is maintained as the trophoblast compartment develops into the placenta, embryonic stem cells downregulate expression of C19MC miRNAs upon differentiation down multiple lineages. It remains unclear, however, how early C19MC miRNA is suppressed during embryonic stem cell differentiation.

In agreement with other studies, expression analysis further revealed that C19MC miRNA expression is absent from the adult brain,56,116 which is consistent with the proposition that miR- 520g and other C19MC miRNAs are involved in early brain development. It may thus be informative to determine whether miR-520g and C19MC are expressed in fetal brain and regions of the brain associated with neuronal progenitors such as the ganglionic eminences that would eventually give rise to adult stem cells in the subependymal zone.121,122

Contrary to this hypothesis, some evidence suggest that C19MC miRNAs are likely not expressed beyond embryonic stem cells. We observed that several human neural stem cell lines do not express miR-520g and miR-517c, as determined by qRT-PCR. A microarray study107 similarly revealed that C19MC miRNAs are not expressed by any of a panel of neural stem and progenitor cell lines. Used in this study were several primary neuronal progenitor cells derived from fetal and postnatal sources, in addition to glial, fibroblast, mesenchymal, and endothelial cell lines.107,123 These observations collectively suggest that C19MC miRNAs may not be expressed in cellular players of neurogenesis. Accordingly, C19MC miRNA may not be involved in neurogenesis during normal development, though it remains possible that C19MC miRNAs are expressed in early progenitors and that the neural stem and progenitor cells assayed were already committed too far down the neuronal lineage. Additionally, neural stem cell cultures and ex vivo cells may not be representative of the neural stem/progenitors in the developing brain, and C19MC miRNA expression may be restricted to a small population of cells during CNS development.

In order to further understand the function of miR-520g, its endogenous expression pattern in normal fetal brain tissues across different stages of development should be further examined, using in situ hybridization (ISH) to detect the microRNA, concurrently with immunochemistry to identify different cell type markers. In situ hybridization of miRNAs have been technically challenging, owing to their small size.124 Kloosterman et al.124 recently showed the feasibility of using of locked nucleic acids (LNA) as ISH probes for the detection of miRNAs. Owing to chemical modification of the furanose ring in the ribose group of nucleic acids, LNA have increased hybridization affinity and specificity toward complementary DNA and RNA molecules.

By concurrently performing immunohistochemical analysis of cell type markers, such as the stem/progenitor marker nestin, whether miR-520g expression is restricted to neural stem/progenitors cells can be determined. If miR-520g is involved in neurogenesis, its expression would coincide with stem/progenitor marker expression in a spatially restricted manner (e.g. confined to ventricular and subventricular zones in the developing cortex and ganglionic eminences), as well as a temporally restricted manner (i.e. expression does not persist into later stages of development).

Taken together, currently known expression patterns of C19MC suggests that C19MC miRNA play a role in maintaining hESC and may promote pluripotency and self-renewal. C19MC miRNA are silenced as embryonic stem cells differentiate during normal development. In the context of cancer, aberrant re-activation of C19MC in committed stem/progenitor cells may contribute to tumourigenesis by maintaining the stem/progenitor cell pool. Ectopic expression of C19MC in different committed stem/progenitor cells may hence give rise to various cancers including CNS-PNET.

4.2 Candidate genes and pathways that may be targeted by miR-520g

Analysis of the tumour expression profiles revealed that C19MC miRNAs modulate developmental signalling and apoptosis pathways. Cell culture models further pointed to the involvement of TGF-b signalling. These two approaches provided some candidate genes. Other candidate genes were also identified based on miRNA target prediction algorithms.

The RNA expressions of several candidates were verified to be downregulated upon miR-520g overexpression, including TGFBR3, NPTX1, BAI2, and TNRC6A. Also known as betaglycan, TGFBR3 is a co-receptor for the TGF-b superfamily and modulates TGF-b signalling; its role is consistent with my finding that TGF-b signalling is dysregulated upon miR-520g overexpression. NPTX1 is involved in neurodevelopment and has been shown to mediate neuronal death.125 BAI2 is a brain-specific angiogenesis inhibitor. TNRC6A plays a role in post- transcriptional gene silencing through the RNA interference and microRNA pathways, and its function may represent a negative feedback mechanism for miR-520g (and the C19MC).

In contrast, genes whose expression levels showed inconsistent direction of change (BMP6 and SMAD3) under the two experimental differentiating conditions are less likely to be miR-520g targets. Furthermore, since miRNAs may modulate target protein expression without affecting transcript level, genes that showed no transcript level change (KLF12 and TLE4) may still be miR-520g targets. Despite harbouring a conserved miR-520g binding site in its 3’UTR, PRICKLE2 was upregulated in the presence of miR-520g overexpression. As the cells were stably overexpressing miR-520g, this observed upregulation could be secondary to miR-520g action. Although precedence exists for miRNA-mediated translational activation (resulting in increased protein expression),126 no miRNAs have been shown to enhance the stability of target transcripts. It would be interesting to determine whether the miR-520g binding site in the 3’UTR

of PRICKLE2 can mediate transcript stability, or whether miR-520g targets the promoter of PRICKLE2.

Candidate genes identified by various strategies were ultimately subjected to downstream validation by luciferase reporter assay and western immunoblotting. The findings, however, do not provide support for TGF-b signalling genes, such as TGFBR3 and SMAD7, as direct miR- 520g targets (Figure 3.12; Figure 3.13). The neuronal death gene NPTX1 similarly does not appear to be miR-520g target. On the other hand, the cyclin-dependent kinase (CDK) inhibitor p21/CDKN1A was downregulated at the protein level in the context of miR-520g overexpression; thus, it serves as a potential miR-520g target. Interpretation of these results, however, should take in account the limitations of techniques and cellular models used in our validation experiments, as detailed in later sections.

4.3 Cell cycle inhibitor p21 is a potential miR-520g target

The repression of p21/CDKN1A protein expression in the context of stable miR-520g overexpression suggests that p21 may be a miR-520g target. Further, expression array analysis indicate that p21 transcript is not differentially expressed between miR-520g overexpressing and control PFSK, Daoy, and hNSCs (not shown), suggesting that if miR-520g directly targets p21, it likely inhibit p21 via translational repression. The expression analysis should be further validated using qRT-PCR.

Although the protein expression of p21 is inhibited by miR-520g, the luciferase reporter assay failed to demonstrate that miR-520g binds to its putative target site in the 3’UTR of p21. The reporter construct used, however, only contained one of two predicted conserved binding site in the p21 transcript (Supplemental Figure 7). Perhaps both binding sites are required for miR- 520g mediated repression. This claim should be confirmed by reporter assays using a construct containing the full length p21 3’UTR. Further, necessary factors required for miR-520g function may not be expressed in NCCIT cells under the conditions in which the luciferase reporter assays were conducted. The transfected cells may not be in a cellular state amenable to microRNAs- mediated translational repression with the transfection protocol used. Above all, whether miR- 520g directly suppresses p21 should be determined with further luciferase reporter assays.

The putative targeting of p21 by miR-520g provides a potential mechanism whereby ectopic miR-520g expression may promote neural stem cell multipotency, just as endogenous miR-520g expression may promote embryonic stem cell multipotency. As differentiation of stem cells requires cell cycle exit, preventing the function of a cell cycle inhibitor may contribute to suppression of differentiation. Consistent with this notion, ectopic miR-520g overexpression prevents growth arrest of hNSCs under differentiating conditions.

4.4 Is p21 an important miR-520g target in CNS-PNET pathogenesis?

4.4.1 Functional studies of p21 as a miR-520g target

Once a candidate miRNA target has been validated, whether its interaction with the miRNA explains the function of the miRNA would need to be explored, in order to elucidate the mechanism by which the miRNA promotes tumourigenesis. For overexpressed miRNAs, the first step would be to investigate whether the downstream consequence of target repression (or induction) is consistent with the outcome of miRNA overexpression. The second would be to determine whether transduction of validated targets abolishes the observed miRNA overexpression phenotype. In the event that the validated target is induced by the miRNA, its expression should be knocked down instead.

If p21 is validated as a direct miR-520g target, functional studies should be carried out in hNSCs to determine whether the repression of p21 contributes to the defective differentiation phenotype seen in hNSC with ectopic miR-520g expression. As stem cell differentiation requires cell cycle exit, suppression of p21 may contribute to the observed inhibition of hNSC differentiation by miR-520g. To this end, it would be intriguing to determine the phosphorylation status of RB in miR-520g overexpressing cells. p21 inhibits cyclin-dependent kinase 2 (CDK2), which in turns phosphorylates RB to permit G1/S transition.127 Therefore, RB would be expected to be hyper- phosphorylated in miR-520g overexpressing cells, if miR-520g promotes cell cycle progression by repressing p21. Further, the inhibition of differentiation for miR-520g overexpressing hNSCs should be reversible with the re-introduction of p21 with mutated miR-520g binding sites.

4.4.2 How does the targeting of p21 by miR-520g contribute to CNS-PNET pathogenesis?

The CDK inhibitor p21 plays a pivotal role in maintaining the quiescence of stem cells, as demonstrated by studies in several models, including embryonic stem cells,128 leukemia stem

cells (cancer stem cells),129 adult hematopoietic stem cells,130 and adult neural stem cells.122,131,132 Importantly, p21 appear to be the target of several miRNAs in stem cells. The slow proliferation of miRNA-deficient mouse embryonic stem cells, for instance, is caused in part by the relief of miRNA-mediated inhibition on p21.128 This phenotype can be rescued by the re-introduction of miRNAs targeting p21, such as miRNAs from the murine Early Embryonic microRNAs Cluster (EEmiRC).128 The importance of p21 in stem cell regulation is further underscored by the finding that human leukemia stem cells upregulate miR-17-92 in order to suppress p21 and enhance proliferation.129 Furthermore, several other human miRNAs have been shown to target p21, including many miRNAs from C19MC.133 It is therefore important to determine how disruption of p21 affects stem cell maintenance.

In adult p21-null mice, the lack of p21 promotes hematopoietic stem cell expansion, ultimately leading to their exhaustion upon serial transplantation of the marrow.130 Additionally in these mice, the loss of p21 lead to expansion of subependymal neural stem cells postnatally, eventually resulting in their depletion in late adulthood.122 (p21 loss did not appear to affect the proliferation of pre-natal neural progenitors.122) Further, a larger fraction of quiescent adult neural stem cells re-entered the cell cycle in p21-null mice after ischemic brain injury.131 Taken together with the observations that p21-null mice undergo normal development and are largely phenotypically normal,134 these findings suggest that maintaining neural stem cell quiescence in postnatal mice may be a primary non-redundant function of p21, which is only revealed under conditions of stress. By inhibiting this non-redundant function of p21, miR-520g could potentially contribute to CNS-PNET formation during early postnatal life. However, p21-null mice only form tumours late in life,134,135 indicating loss of p21-mediated stem cell quiescence is insufficient for early tumour formation. It is therefore unlikely that miR-520g principally suppress p21 to induce cell- cycle re-entry and expansion of postnatal neural stem cells. Conversely, miR-520g may inhibit p21 and other genes sharing redundant functions in CNS development, together with other C19MC miRNAs. Accordingly, it would be informative to explore of the role of p21 in neurogenesis during pre-natal development.

During neurogenesis, neuroepithelial progenitors (NEPs) and radial glial cells engender neurons that populate the CNS. Derived from NEPs, radial glial cells are the main proliferating population in CNS development, and they have been shown to give rise to most post-mitotic neurons in the cerebrum, with the exception of neurons in tissues derived from ganglionic

eminences and interneurons of various regions.21,23,24 As NEPs and radial glial cells remain at the apical (ventricular) surface, they are collectively referred to as apical progenitors.

An extensive literature indicates that cell cycle regulators play pivotal role in the differentiation of neural progenitors.136-139 While negative cell cycle regulators promote neurogenesis, proliferative factors inhibit differentiation. This effect is clearly seen by the lengthening of the cell cycle during CNS development from 8 hours at the onset of neurogenesis to 18 hours by the end.17 As the cell cycle lengthens, the G1 phase increases from 3 to 13 hours, while the other phases remain unchanged, which points to the pivotal role of CDK inhibitors governing G1 to S transition.17 The Ink4 class (p16/Ink4a, p15/Ink4b, p18/Ink4c, and p19/Ink4d) and the Cip/Kip class (p21/Cip1, p27/Kip1, p57/Kip2) of CDK inhibitors work coordinately during this transition, partly by controlling the phosphorylation status of RB and RB-like proteins (p107 and p130).140

However, the cell cycle control of apical progenitors does not appear to be mediated by p21, since these progenitors do not express p21.141-143 Induction of p21 expression is possible, though not without high-dose, exogenous administration of factors as such as TGFb1.144 These observations are consistent with the normal CNS development of p21-null mice.134 Expression of p21 during CNS development is largely absent before birth, and mostly restricted to post-mitotic cortical neurons after birth, suggesting that it may function in maintaining post-mitotic quiescence of differentiated cells in early post-natal life.142,143 Aside from the cortex, p21 is also expressed in the lining of the ganglion eminences, along with other CDK inhibitors. This observation suggests that p21 may be involved in cell cycle exit of neurons derived from the ganglion eminence. Indeed, p21 has been shown to mediate cell cycle exit in late striatal neurogenesis.145 By adulthood, overall p21 expression diminishes but persists in adult neural stem cells in the ependymal zone.122,142,143 Taken together, these findings suggest that p21 primarily function in maintaining quiescence, but can additionally regulate cell cycle exit in specific regions of the developing brain.

At this point, it is difficult to explain the oncogenic function of miR-520g primarily in terms of its suppression of p21, due to the expression pattern of p21 and the effect of p21 knockout. Importantly, many other cell cycle inhibitors play roles that are both distinct from and overlap with those of p21 during CNS development. Therefore, miR-520g and other miRNAs

overexpressed by C19MC amplification likely target several other genes in various pathways, whose dysregulation would cooperatively contribute to CNS-PNET pathogenesis.

On the other hand, p21 also plays other roles that are important in development and tumourigenesis. For instance, p21 mediates DNA damage-induced growth arrest, which has been shown to be defective in p21-null mice.134 Conceivably, genes involved in DNA repair may be targeted to synergistically promote tumour formation or progression, by preventing maturing CNS cells to respond appropriately to DNA damage. Further, p21 also regulates cytoskeletal formation and cellular migration,146 which are critical steps in neurogenesis as maturing neurons migrate to their destinations.13 Progenitor cells that migrate to inappropriate locations may receive aberrant extracellular signals that disrupt their differentiation, which may in turn contribute to tumourigenesis.

4.4.3 What other targets could contribute to pathogenesis?

Genes involved in TGF-b and Wnt signalling, as well as apoptosis pathways would all likely cooperatively contribute to pathogenesis. In addition, CDK inhibitors have many crucial functions during CNS development second to their cell cycle regulation, such as maintaining quiescence, promoting cell cycle exit, and inducing growth arrest or cell death following DNA damage. Given their importance, multiple CDK inhibitors would likely be targeted by overexpressed C19MC miRNAs.

For example, p27 may be an important target. It has an expression pattern in the developing cortex that fits the role as a cell cycle regulator of apical progenitors.141-143 The role of p27 as a modulator of neurogenesis has been further confirmed with constitutive p27 knockout and conditional p27 overexpression mouse models.147-149 Knockout of p27 decreases cell cycle exit of neuronal progenitors and increases the outer cortical layers in the cerebrum.147 In adulthood, lack of p27 does not affect the number of adult neural stem cells, but enhances the proliferation of transiently amplifying progenitors.149 Conversely, conditional overexpression of p27 in neural progenitors increases cell cycle exit and inhibits neurogenesis during development.148 Further, cumulating evidence suggest the p27 have neurogenic function independent of its cell cycle activity.150

Many miRNA target prediction algorithms, including TargetScan, miRanda, PITA, DIANA- microT, and RNA22, do not predict a binding site for miR-520g or other C19MC miRNAs in the 3’UTR of p27. An indirect mechanism for miR-520g-mediated p27 suppression may exist, however. Many C19MC miRNAs, including miR-520g, are predicted to target CAMK2N1, which has been shown to be a tumour suppressor in colon adenocarcinoma.151 Overexpression of CAMK2N1 induces cell cycle arrest by stabilizing p27.151 Therefore, C19MC miRNAs may suppress CAMK2N1 to indirectly inhibit p27 activity.

miR-520g does not appear to target CAMK2N1, however. Immunoblotting showed that miR- 520g overexpressing NIH3T3 did not result in reduced p27 protein levels (Figure 3.13) and luciferase reporter assay showed that miR-520g did not suppress the reporter with a putative miR-520g binding site from CAMK2N1 (Figure 3.12). It is possible that other overexpressed C19MC miRNAs may target CAMK2N1 and this possibility should be further investigated.

4.5 Limitations of current model systems

The cell models used in this study include tumour cell lines (PFSK, Daoy, UW228, and NCCIT) and untransformed cell lines (hNSC, and NIH3T3). As PFSK is one of the few well-established CNS-PNET cell lines, medulloblastoma cell lines (Daoy and UW228) were also used. Medulloblastoma tumours, however, are molecularly distinct from CNS-PNET; they are characterized by different copy number aberrations and expression profiles. Further, none of the cell lines express C19MC miRNAs at high levels, which eliminates the option of performing knock-down experiments to complement the overexpression approach. As tumour cell lines have already undergone tumourigenic transformation, overexpression of C19MC miRNAs may not necessarily enhance their tumourigenicity.

On the other hand, hNSCs were used to identify signalling pathways disrupted by miR-520g overexpression. An important consideration is that the hNSCs have undergone negative selection to stably express miR-520g. The observed expression changes in the developmental signalling pathways may thus be secondary effects of miR-520g function; genes in these pathways may not be direct targets. Similarly in the immunoblotting assays, stable miR-520g overexpression was established in the panel of cell lines used. The suppression (or lack of suppression) observed may be influenced by cellular adaptation to negative selection. In addition, hNSCs exhibit multipotency and characteristics of early neural progenitors, they have likely undergone fate re-

programming during culture establishment and propagation.25 In this respect, it has been demonstrated that oligodendrocyte precursors can be induced to become tripotent in culture.25

Accordingly, it would be important to also study the effect of C19MC amplification in mouse models, ex vivo cells, and primary neural progenitor cell lines. Mouse models would be powerful means of examining the synergistic effects of conditionally overexpressing multiple C19MC miRNA in an in vivo setting. However, C19MC is not well conserved in rodents, though it may be related to the mouse EEmiRC. Using ex vivo cells and primary neural progenitor cell lines may therefore be two of the few options available for studying the function of C19MC.

4.6 Co-factors in miRNA-mediated post-transcriptional regulation

Despite the lack of repression for putative miR-520g targets, it is important to note that the current luciferase reporter assay may only detect genes that are targeted by transcription cleavage or degradation, since the experimental conditions may not be amenable to miRNA-mediated translational repression. Repression through transcription cleavage or degradation typically occurs when a siRNA/miRNA base-pair to target sites with perfect complementarity. This would provide an explanation for the apparent requirement of extensive complementarity for miR-520g mediated repression in the reporter assays, as evidenced through the abrogation of repression by disrupting either 5’ or 3’ base-pairing.

Although the experimental read-out, luciferase activity, reflects the protein expression of the reporter, the state of the cells may not be conducive to miRNA-mediated translational repression. Vasudevan et al.54 have shown that miRNA mediated translational regulation is controlled by the

cell cycle. The authors observed the strongest translational repressive effect in the S/G2 phase

and minimal repression in the G1 phase. Since asynchronously growing cells are predominantly

in G1 and the cells have not been synchronized in current luciferase reporter experiment, minimal translational repression would be expected. Further, the toxicity associated with the transfection may induce cell cycle arrest, which may switch the repression effect of the miRNA-mRNA interaction to translational activation.47 In fact, Vasudevan et al.54 have attributed the variability in magnitude of miRNA-mediated repression reported in the literature to differences in cell cycle states as a consequence of the use of different transfection protocols. As per the authors’ recommendations, the cells can be synchronized by a brief serum withdrawal after the

transfection and followed by serum re-exposure to allow the cells to enter to S/G2 prior to the harvest.

An important regulation of miRNA-mediated translational repression is the Fragile X mental retardation protein (FMRP), which has been implicated in synaptic maturation and function.152 The relative high abundance of FMRP in the brain may underscore the importance of miRNA- mediated translational repression in CNS development. Conceivably, putative targets with roles in CNS development – CAMK2N1, CDKN1A, NPTX1, and TGFBR3 – may be regulated by miR-520g during translation in a cell cycle dependent manner.

4.7 Future candidate miRNA target screens and alternative strategies

As promising as p21/CDKN1A appears as a candidate target of miR-520g, its possible interaction with miR-520g likely only partially explains the miR-520g overexpression phenotype. Given that p21-null mice do not develop tumours until late in life,135 disruptions of additional genes and pathways by miR-520g and other miRNAs upregulated C19MC amplification are likely crucial in CNS-PNET pathogenesis. Other genes should therefore be pursued, through luciferase reporter assays or alternative methods of target identification.

4.7.1 Screening more genes with luciferase reporter assays

For future screens of putative miRNA targets, it is also important to consider the use of a miRNA/siRNA duplex or a miRNA expression vector encoding the pri-miRNA hairpin. Despite its common use in the literature and the potential for siRNA to behave like miRNA,153 the biogenesis of siRNA and miRNA are distinct and, as a consequence, the compositions of the effector RNA-induced silencing complexes (RISC) are different,154 which may lead to differences in ultimate function. In interest of enhancing the repressive potential, higher miRNA level may be achievable through miRNA/siRNA duplex transfection without overloading the RNA processing machinery (which would result in non-specific reporter repression). Nonetheless, the currently used miR-520g expression vector robustly upregulates miR-520g level (Supplemental Figure 4) and is sufficient to effect repression of the positive control reporter construct (Figure 3.12). Since miR-520g expression is downregulated in NCCIT upon retinoic acid treatment, its endogenous expression may serve important functions in undifferentiated NCCIT cells. Therefore, the knock-down of miR-520g may also be used for

luciferase screens in NCCIT, and it would be expected to induce reporter activity of putative miR-520g targets.

Another important consideration for target genes harbouring binding sites for multiple miRNAs is the co-transfection of multiple miRNAs, which may, however, require the transfection of miRNA/siRNA duplexes.

4.7.2 Assaying protein expression of target candidates using In-Cell Western

Since the final direct outcome of miRNA action is the repression of the protein expression of its target (through different mechanisms126), measuring protein levels using In Cell Western provides a means to evaluate target candidates. This technology allows the quantitation of levels of the protein products using the immunofluorescence technique in a medium-throughput manner. The cells are first fixed in the culture plates, the target protein is then labelled with the primary antibody, followed by labelling with fluorochrome-conjugated secondary antibody and subsequent imaging and quantitation of the fluorescence signal, which correlates with protein expression. Protein expression of target genes may be induced or suppressed by the miRNA.

4.7.3 Enriching for miR-520g bound transcripts using immunoprecipitation with antibodies against Argonaute

As an alternative approach for target identification, the Argonaute protein could be immunoprecipated to enrich for miR-520g bound transcripts. Mature miRNAs incorporate into and function via effector ribonucleoprotein complexes known as RNA-induced silencing complexes (RISC), which contain Argonaute (Ago) subfamily proteins as a core component.126 Immunoprecipating the RISC complex using antibodies against Ago can therefore also co- precipitate transcripts bound by miRNA expressed at high levels in the cell. By comparing levels of co-precipitated transcripts in cells transfected (stably or transiently) with miR-520g against the control cells using qRT-PCR, one can identify transcripts that are bound by miR-520g. This approach provides a more direct evidence for miR-520g regulation compared to measuring transcript level changes in the presence of miR-520g; further, it need not be limited by the accuracy of target binding site prediction, nor does it rest on the premise that miRNAs post- transcriptionally downregulate (instead of upregulate) their targets.

4.8 Concluding remarks

The expression patterns of miR-520g and C19MC miRNAs suggest that they may play a role in stem cell maintenance during development. In cancer, their aberrant upregulation may lead to the overexpansion of stem/progenitor cells, consequently contributing to tumour formation and progression. Ectopic miR-520g expression disrupts developmental signalling and may further interfere with cellular differentiation. Collaborating with other overexpressed C19MC miRNAs, miR-520g may suppress cell cycle inhibitors such as p21 and p27 in order to hinder cell cycle exit during CNS development. C19MC amplification likely contributes to CNS-PNET pathogenesis by modulating a multitude of genes and pathways; a major challenge is in determining the cooperative effects of a great number of overexpressed miRNAs acting upon an even greater number of targets, using appropriate model systems.

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Appendices

Supplemental Table I. qRT-PCR primers for quantifying transcript levels of apoptosis genes.

Gene Forward sequence Reverse sequence Validated Expressed

RPLP0 GTGTTCGACAATGGCAGCAT CTGCAGACAGACACTGGCAAC 9 9 NLRP3 ATAACATGCCCAAGGAGGA TTCACCAATCCATGAGAACAG 9 9 TLR2 GGCCAGCAAATTACCTGTGT ACACCAGTGCTGTCCTGTGA 9 9 CDKN2C GACCCTAAAGAATGGCCG AGCAAGTCTTGTGTAGACTG 8 8 VEGFA ACTGAGGAGTCCAACATCAC TCTTTCTTTGGTCTGCATTCAC 9 9 BCL6 GATTCTAGCTGTGAGAACGGG GGTCACACTTGTAGGGTTTGTC 9 9 BAD ACTCCTTTAAGAAGGGACTTCC CAAGTTCCGATCCCACCAG 9 9 CRYAB GTTCTCTGTCAACCTGGATGTG CATGTTCATCCTGGCGCTC 9 8 ADRB2 GATTTCAGGATTGCCTTCCA TATCCACTCTGCTCCCCTGT 9 9 TRADD AATCTGAAGTGCGGCTCG GCCGATTCACTACAGGCT 8 8 DAD1 ATCCTAGCGGTTTGCCTG AACAAGGTGCAGGATGGT 9 9 CD38 GAAGATTCCAGAGACTTATGCC CACTGAAGAAACTTGTCAGGTC 9 8 BECN1 GGATGTGGAGAAAGGCAAGA AATTGTGAGGACACCCAAGC 9 9 BCL2A1 AAGCAAAACGTCCAGAGTGC CCCAGTTAATGATGCCGTCT 8 8 SOD1 GAAGGTGTGGGGAAGCATTA CTCCAACATGCCTCTCTTCA 9 9 IFIH1 ACCAAATACAGGAGCCATGC GCCCATTGTTCATAGGGTTG 9 9 AIFM2 TGGTGCTCTGAGAGTGAACG CGCTGCTTCACAGAGTTGAC 9 9 CIDEB GCATTGGAGACCCTACTGCT TGACAGCACTCCACTCCTTG 8 8 RELA GCAGCTGCAGTTTGATGATG ATCAGCATGGGCTCAGTTGT 9 9 TAX1BP1 AGCAGGCCTTCTTGAGTTGA TTCTGCTTGCAGTTGGTCAC 9 8 MAP3K5 CAGCTGGACACCAGTTTGAA TCATGTGGTCATTGGCTAGG 9 9 GCLM AATCTTGCCTCCTGCTGTGT ACTCGTGCGCTTGAATGTC 9 9 CDKN1B TGTCAAACGTGCGAGTGTCT TTCCATGTCTCTGCAGTGCT 9 9

A gene is considered expressed at a detectable level if its CT value is less than 30 in at least one sample. Validated primers have amplification efficiencies of ~2.0.

Supplemental Table II. qRT-PCR primers for quantifying transcript levels of candidate targets.

Gene Forward sequence Reverse sequence Validated Expressed

SMAD3 AGACACCAGTTCTACCTCCT GGGTCTCTGGAATATTGCTCTG 9 9 TGFBR3 CCCATCTCCTCAGTCCACAT ACAGTCTGGAGACCCCAGTG 9 9 SORL1 GCTGCTGTGGTGGTGCCCAT TGGCGAAGGCGGTGAAGCTG 9 9 SMOC2 TGCACTCCGGCTGCAATCGT AGGGTCGGCCGTACATCACA 8 9 PRICKLE2 AACTTGGGCCGCGGGAATGT CAGCGCGTGACGCAAACACA 9 9 BMP6 TGCTCCTTCCCACTCAACGCA AGTTGGCGCACAGCACGGTT 9 9 CAMK2N1 CGCCTGCAGGACACCAACAACT AGGAGGTGCCTTGTCGGTCA 9 9 NPTX1 GGTGTTGGAGGAGGTCAAGA CCAGCTGTGGGAATCCTTTA 9 9 TNFAIP1 TCGAATCCTCCACCAAGCCCGT AAGAGCACGCGGCCGTTGAA 9 9 TRPS1 ATGCAACGCGTGTGGCCTCT TGCCTCTGGGTTAAGGCGCT 9 9 TNRC6A TGCTGCGGCATCCAGCACAT AGCCAGTGGGGCGATTTCCA 9 9 AFF4 GCCTGCGATGCGAGTCTTTGCT TTGCTTCCCAAGCCAGGCGA 9 9 KLF12 TGGGAAGGCTGCACCTGGAAGT GCGGTGCAGGGCCAAATGAT 9 9 CHUK TGTGGAACCTGAGGCCGCTT ACAGACAGACGTTCCCGAAGCC 8 8 SLC41A1 ACGTGGCCACACCCATTGCT ACAGGCAGCAGGGCCACAAA 9 9

A gene is considered expressed at a detectable level if its CT value is less than 30 in at least one sample. Validated primers have amplification efficiencies of ~2.0.

Supplemental Table III. Oligonucleotides used in preparing luciferase reporter constructs

Construct Forward sequence Reverse sequence Enzymes pmirGLO-miR-520g-s2 CTAGGGCCCTAGTCACTT CTAGACAAAGTGTATCAA SacI, XbaI TGATACACTTTGT AGTGACTAGGGCCCTAGA GCT pmirGLO-miR-520g-s2m CTAGGGCCCTAGTCAGTA CTAGAGATACTGTATGAT SacI, XbaI TCATACAGTATCT ACTGACTAGGGCCCTAGA GCT pmirGLO-miR-520g-s4 CTAGGGCCCTAGTCACTT CTAGACAAAGTGTATCAA SacI, XbaI TGATACACTTTGATACAC AGTGTATCAAAGTGTATC TTTGATACACTTTGT AAAGTGACTAGGGCCCTA GAGCT pmirGLO-miR-520g-s4m CTAGGGCCCTAGTCAGTA CTAGAGATACTGTATGAT SacI, XbaI TCATACAGTATCATACAG ACTGTATGATACTGTATG TATCATACAGTATCT ATACTGACTAGGGCCCTA GAGCT pmirGLO-miR-520g-s8 CTAGGGCCCTAGTCACTT CTAGACAAAGTGTATCAA SacI, XbaI TGATACACTTTGATACAC AGTGTATCAAAGTGTATC TTTGATACACTTTGATAC AAAGTGTATCAAAGTGTA ACTTTGATACACTTTGAT TCAAAGTGTATCAAAGTG ACACTTTGATACACTTTGT TATCAAAGTGACTAGGGC CCTAGAGCT pmirGLO-miR-520g-s8m CTAGGGCCCTAGTCAGTA CTAGAGATACTGTATGAT SacI, XbaI TCATACAGTATCATACAG ACTGTATGATACTGTATG TATCATACAGTATCATAC ATACTGTATGATACTGTA AGTATCATACAGTATCAT TGATACTGTATGATACTG ACAGTATCATACAGTATC TATGATACTGACTAGGGC T CCTAGAGCT pmirGLO-miR-520g-t CTAGCGGCCGCTAGTACA CTAGAACAAAGTGCTTCC SacI, XbaI CTCTAAAGGGAAGCACTT CTTTAGAGTGTACTAGCG TGTT GCCGCTAGAGCT pmirGLO-miR-520g-t1m1 CTAGCGGCCGCTAGTACA CTAGAATATATATCTTCC SacI, XbaI CTCTAAAGGGAAGATATA CTTTAGAGTGTACTAGCG TATT GCCGCTAGAGCT pmirGLO-miR-520g-t1m2 CTAGCGGCCGCTAGTATA CTAGAACAAAGTGCTTCC SacI, XbaI TATTTATGGGAAGCACTT CATAAATATATACTAGCG TGTT GCCGCTAGAGCT pmirGLO-ABCG2-olg CTAGCGGCCGCTAGTTCA CTAGATCAAAGTGCTTCT SacI, XbaI CATAAAAAAGAAGCACTT TTTTTATGTGAACTAGCG TGAT GCCGCTAGAGCT pmirGLO-ABCG2-m1-olg CTAGCGGCCGCTAGTTCA CTAGATATTTATACTTCTT SacI, XbaI CATAAAAAAGAAGTATAA TTTTATGTGAACTAGCGG ATAT CCGCTAGAGCT

85 pmirGLO-CAMK2N1-olg CTAGCGGCCGCTAGTCAT CTAGATCAAAGTGCTTTC SacI, XbaI GAAAAGAGAAAGCACTTT TCTTTTCATGACTAGCGG GAT CCGCTAGAGCT pmirGLO-CAMK2N1-m1-olg CTAGCGGCCGCTAGTTAA CTAGAAATTTAATATTAA SacI, XbaI GACTGCATTAATATTAAA TGCAGTCTTAACTAGCGG TTT CCGCTAGAGCT pmirGLO-CDKN1A-olg CTAGCGGCCGCTAGTGAA CTAGATCAAAGTGCCATC SacI, XbaI GTAAACAGATGGCACTTT TGTTTACTTCACTAGCGG GAT CCGCTAGAGCT pmirGLO-CDKN1A-m1-olg CTAGCGGCCGCTAGTGAA CTAGATATTTATACCATCT SacI, XbaI GTTTACAGATGGTATAAA GTAAACTTCACTAGCGGC TAT CGCTAGAGCT pmirGLO-NPTX1-olg CTAGCGGCCGCTAGTTAA CTAGAACAAAGTGATCTT SacI, XbaI GACTGCAAAGATCACTTT TGCAGTCTTAACTAGCGG GTT CCGCTAGAGCT pmirGLO-NPTX1-m1-olg CTAGCGGCCGCTAGTTAA CTAGAAATTTAAGATTAA SacI, XbaI GACTGCATTAATCTTAAA TGCAGTCTTAACTAGCGG TTT CCGCTAGAGCT pmirGLO-TGFBR3-olg CTAGCGGCCGCTAGTGGA CTAGAGCAAAGTGGCATC SacI, XbaI ATAATATGATGCCACTTT ATATTATTCCACTAGCGG GCT CCGCTAGAGCT pmirGLO-TGFBR3-m1-olg CTAGCGGCCGCTAGTGGA CTAGAGATTTAATGCATC SacI, XbaI ATAATATGATGCATTAAA ATATTATTCCACTAGCGG TCT CCGCTAGAGCT pmirGLO-TGFBR3 GCCTCGAGTGTCCAGGTG GCTCTAGAAACAAGGAGG XhoI, XbaI AGAACATCCA TATCACTGAGCTT pmirGLO-BAI2 GCCTCGAGGGACTGCCCA GCTCTAGACACAGAGTGA XhoI, XbaI CTGCATATAAA AGTTTATTCCCAAC pmirGLO-TNRC6A GCCTCGAGGCATATGGAC GCTCTAGATCACCTCCTG XhoI, XbaI TGACCCACCT GCTAGTGCTT pmirGLO-AFF4 GCCTCGAGCTGCATGGTT GCTCTAGAGCTTCAGAAT XhoI, XbaI TATGGTGCTG GCAAGCTCAT pmirGLO-TNFAIP1 GCCTCGAGGCATATGGAC GCTCTAGATCACCTCCTG XhoI, XbaI TGACCCACCT GCTAGTGCTT pmirGLO-SMAD7 GCCTCGAGGAGAGGTTTG GCTCTAGAAGCTAGGTGA XhoI, XbaI CAGTCCCAAG TAACACCCATAGAA pmirGLO-NPTX1 GCCTCGAGCGATCTACTG GCTCTAGATCCAAGACAC XhoI, XbaI GACCGCAGAC AGGTTCACCA pmirGLO-CAMK2N1 GCCTCGAGGAGAGAATAA GCTCTAGATCCAAGCATT XhoI, XbaI GAACGGCGGTAA CCTGTACGTG pmirGLO-TNRC6A GCCTCGAGCGAGGGAAA GCTCTAGAGCTCTTTGATT XhoI, XbaI GGAGCACTAAG TGGGACAGG

A B

HEK293TV HEK293TV

4 ● 30 ● 25 3 20

● 2 15 10 1 ● 5 ● 0 ● 0 ● ● ● ● Firefly luciferase activity (10^6) Firefly luciferase activity (10^6) Firefly luciferase

100 150 200 250 300 0 50 100 150

Luciferase plasmid [ng] Luciferase plasmid [ng]

C D

HEK293TV HEK293TV

0.6 10 ● ● 0.5 8 0.4 6 0.3 ● 0.2 4 0.1 2 ● ● 0.0 ● 0 ● ● ● ● Renilla luciferase activity (10^6) Renilla luciferase activity (10^6) Renilla luciferase 100 150 200 250 300 0 50 100 150

Luciferase plasmid [ng] Luciferase plasmid [ng]

Supplemental Figure 1. Determination of the minimum amount of the luciferase plasmid required in the transfection of HEK293TV. HEK293TV cells were transfected with the indicated amount of luciferase plasmid using PEI at an N/P ratio of 38.8 in 24-well plates and harvested for luciferase assay 48 hr later. Firefly luciferase activities are shown in A and B; Renilla luciferase activities are shown in C and D. Transfections of luciferase plasmid at doses between 100 ng and 300 ng yield linear relationships with respect to Firefly (A) and Renilla (C) luciferase activities.

A HEK293TV (pCDH)

1.4

? pmirGLO 1.2 ? pmirGLO−520g−s4 ? pmirGLO−520g−s4m 1.0 ?

0.8

0.6

? ? 0.4 ? ? ? ?

Relative luciferase activity luciferase Relative ? ? ? ? 0.2 ? ? ? ? ? ? ? ? 0.0

0 100 200 300 400

miRNA expression plasmid [ng]

Supplemental Figure 2. Optimization of co-transfection to achieve luciferase activity repression in HEK293TV. HEK293TV cells were co-transfected with 100 ng of the luciferase plasmid and indicated amounts of the miR-520g expression plasmid using PEI at an N/P ratio of 38.8 in 24-well plates and harvested for luciferase assays 48 hr later. Firefly luciferase activities were normalized to the Renilla luciferase activity and expressed relative to transfections with no miRNA expression plasmid. The relative luciferase activity of the positive control luciferase construct (pmirGLO-520g-s4) was not repressed in comparison to the backbone luciferase construct (pmirGLO) at any dose of miR-520g expression plasmid assayed. Two different miRNA expression plasmid backbones were used (pCDH and pcDNA).

A B

NCCIT NCCIT

25 40 ● ● ● ● 20 ● ● 30 ● ● ● ● 15 ● ● 20 ● ● ● ● 10 ● ● 10 ● ● 5 ● ●

● ● 0 0 Firefly luciferase activity (10^6) Firefly luciferase Renilla luciferase activity (10^6) Renilla luciferase 20 40 60 80 20 40 60 80

N/P ratio N/P ratio

C D

NCCIT NCCIT

● ● ● 4 ● 8 ● ● ● 3 ● 6 ●

● ●

2 4 ●

1 ● 2 ●

● ● 0 ● ● 0 ● ● Firefly luciferase activity (10^6) Firefly luciferase Renilla luciferase activity (10^6) Renilla luciferase 200 300 400 500 600 700 200 300 400 500 600 700

Luciferase plasmid [ng] Luciferase plasmid [ng]

Supplemental Figure 3. Optimization of transfections in NCCIT. NCCIT cells were transfected with PEI at varying N/P ratios (A & B) or varying amounts of luciferase plasmid (C & D) and harvested for luciferase assays 48 hr later. (A & B) An N/P ratio of ~40 maximizes Firefly and Renilla luciferase activities. However, significant toxicity based on morphological features and Trypan Blue staining was observed at this ratio (not shown). (C & D) Transfections of luciferase plasmid at doses between 250 ng and 600 ng yield linear relationships with respect to Firefly (C) and Renilla (D) luciferase activities.

Supplemental Figure 4. Validation of miR-520g transient transfection in NCCIT. NCCIT cells were transfected with varying doses (ng) of pcDNA-miR-520g using PEI and harvested for qRT-PCR 48 hr later. The total amount of plasmid was maintained at 1000 ng using the pcDNA plasmid as a carrier. The cells were transfected in 6-well plates, but the indicated amounts of plasmid are equivalent amounts for transfections in 24-well plates. The level of the mature miR-520g was detected using the Taqman miRNA qRT-PCR assay. The expression level was normalized to the RNU6B control and expressed relative to transfections with no pcDNA-miR-520g.

Supplemental Figure 5. Optimization of co-transfection to achieve luciferase activity repression in NCCIT. NCCIT cells were co-transfected with 300 ng of the luciferase plasmid and indicated amounts of the miR- 520g expression plasmid using PEI at an N/P ratio of 15.5 in 24-well plates and harvested for luciferase assays 48 hr later. Firefly luciferase activities were normalized to the Renilla luciferase activity and expressed relative to transfections with 300 ng of the control miRNA expression plasmid (pcDNA; not shown). The relative luciferase activity of the positive control luciferase construct (pmirGLO-520g-s4) was most highly repressed in comparison to the backbone luciferase construct (pmirGLO) at a dose of 600 ng of the miR-520g expression plasmid.

A B C C C G C G G G G C G C C G C G U G U G U G U G C G C G G U G U A U A U G C G C CC U C U C C C U A A A U U A C G A C U U C GCA A U A A U A G U C G C U A U U A A U A G G A A U A A U A U U A U U U A A C A C U A G A G C G G C A C G C G U A U C A U G UC G A U A G U C G C C G C G G C G C C G C C C G C A U G A U C A C A C G A C U G C A G A C C U G G C C C A A C G C A A G C U C U G U C A C U C A A U G U G G AAAU C U C G G A G A C C G A G G G G G U A U A G A G A G C C G A A U U A U A U U C U C U C U C A C U U G G G A U UG A C C U A G U C U A C A U A AG A C G G G G C C G U U U G U U A G G U U A G A U A G C C G U C C G C U G G C 01 G A G C A G 01 G A U C G C A G C C A U C G G C C A C G G A G A A C G G A U A A A U A A A A C A A A C C U U U G A A U A U C G AU C G U A U G C G U A C G C U U A U G C C G C U G G U G C G C C G G C C G C G C C A A G C U C G A U A A U G C U A A A U U A A U A C A U G U A U G A UC U G G C G C AG A A G C C C C U A G AG C U G G U C C U U U A C U C G G A C C UG U G U C U A G A G A A C G G C G U U G U A G U A C G C U G C 01 G G A C A G U C G A G C C C G G A A A U A A A A C

Supplemental Figure 6. RNA secondary structures of the 3’UTR of luciferase reporter constructs. RNAfold was used to predict the RNA secondary structures based on reporter construct sequences of (A) pmirGLO-miR-520g-t, (B) pmirGLO-miR-520g-t1m1, and (C) pmirGLO-miR-520g-t1m2. Designed miR-520g target site within the 3’UTRs of the constructs are highlighted in blue. Colours indicate probability of each nucleotide to base-pair. Target sites in all the constructs are located in regions of moderate base-pairing probability; thus, they are comparably accessible to the microRNA.

Supplemental Figure 7. miR-520g binding sites in the 3’UTR of p21 predicted by TargetScan. Sequences of the p21/CDKN1A 3’UTR near the two predicted miR-520g binding sites are shown for human (Hsa) and various other species. The seed match is highlighted in white. Base-pairing of the putative binding sites with miR-520g is shown at the bottom. Whether miR-520g can mediate repression through Site 1 was tested by luciferase reporter assays (Figure 3.12).