The Critical Role of Histone Methylation in Tumour Progression and As Anti-Cancer Targets in Neuroblastoma

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The critical role of histone methylation in tumour progression and as anti-cancer targets in neuroblastoma

Matthew Wong

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

Supervisor: Dr Tao Liu

Co-supervisor: A. Prof Patsie Polly

School of Women’s and Children’s Health

Faculty of Medicine

February 2016

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THE UNIVERSITY OF NEW SOUTH WALES

Thesis/Dissertation Sheet

Surname or Family name:

First name: Matthew Other name/s: Kwok Kei Wong

Abbreviation for degree as given in the University calendar: PhD

School: School of Women’s and Children’s Heath Faculty: Faculty of Medicine

Title: The critical role of histone methylation in tumour progression and as anti-cancer targets in neuroblastoma

N-Myc induces neuroblastoma by regulating the expression of target oncogenes. Histone H3 lysine 79 (H3K79) methylation at Myc-responsive elements of target gene promoters is a strict prerequisites for Myc-induced transcriptional activation. DOT1L is the only known histone methyltransferase that catalyses mono-methylation (me), di- methylation (me2) and tri-methylation (me3) at the histone H3K79 position, which have been linked to gene transcriptional activation. JMJD6 is a bi-functional arginine demethylase and lysyl-hydroxylase. The JMJD6 gene is located on the chromosome 17q25 position. 17q21-gter gain has been identified as the most frequent chromosome alternation in neuroblastoma and an indicator of poor patient prognostic. Here, I investigated the roles of DOT1L and JMJD6 in N-Myc over-expressing neuroblastoma. I found that N-Myc up-regulated DOT1L mRNA and protein expression, by binding to an E-box at the DOT1L gene promoter. Knocking-down DOT1L reduced the mRNA and protein expression of the N-Myc target genes, ODC1 and E2F2. DOT1L and N-Myc formed a protein complex, and knocking-down DOT1L reduced histone H3K79me2 and N-Myc protein binding at the promoters of the N-Myc target genes ODC1 and E2F2, and reduced neuroblastoma cell proliferation in vitro and tumour progression in neuroblastoma-bearing mice. In a publicly available microarray gene expression dataset, high levels of DOT1L gene expression in tumours correlated with high levels of MYCN gene expression and poor patient survival independent of MYCN amplification, age at diagnosis and disease stage. I have also demonstrated that JMJD6 up-regulated both N-Myc and c-Myc in neuroblastoma cell lines. Conversely N-Myc and c-Myc did not affect JMJD6 mRNA or protein expression. Knocking down JMJD6 reduced neuroblastoma cell proliferation in vitro and tumour progression in neuroblastoma-bearing mice. JMJD6 gene expression correlated with MYCN gene expression in human neuroblastoma tissue microarray gene expression datasets. High DOT1L gene expression was also a prognostic factor for poor neuroblastoma[Grab your reader’s patient attention outcome. with a great quote from the document or use this space to Inemphasize conclusion, a key thes point.e data To identify place this DOT1L text box as aanywhere novel co -onfactor the page,in N-Myc just dragoncogenesis, it.] and provide critical evidence for the potential utilization of DOT1L inhibitors for the therapy of MYCN amplified neuroblastoma. JMJD6 up-regulates N-Myc and c-Myc gene expression and JMJD6 gene gain is a potential mechanism for 17q21-qter gain driven neuroblastoma tumourigenesis.

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I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only). Matthew Wong Pei Yan Liu 1/3/2016

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Table of Contents

List of Figures ...... vii

List of Tables ...... xi

List of Abbreviations ...... x

List of publications ...... xi

Conference presentations ...... xi

Acknowledgement ...... xii

Abstract ...... xiii

Chapter 1: Literature review and project aims ...... 1

1.1 Cancer ...... 1

1.2 Neuroblastoma ...... 2 1.2.1 Neuroblastoma Staging...... 4 1.2.2 Hereditary Neuoblastoma ...... 10 1.2.3 Neuroblastoma and anaplastic lymphoma kinase ...... 11 1.2.4 Drug resistance in neuroblastoma...... 12

1.3 C-Myc and N-Myc regulate gene expression ...... 14 1.3.1 Myc mediates transcriptional activation ...... 15 1.3.2 Myc mediates gene repression ...... 16 1.3.3 Myc regulation of miRNA expression ...... 18

1.4 N-Myc ...... 20 1.4.1 N-Myc in embryonic development ...... 21 1.4.2 N-Myc induces neuroblastoma ...... 21 1.4.3 Strategies to target Myc ...... 25

1.5 Myc downstream targets ...... 28 1.5.1 The Elongation 2 Factor (E2F) Family...... 28 1.5.2 E2F gene function ...... 29 1.5.3 Ornithine decarboxylase 1 ...... 31

1.6 Histone methylation and de-methylation ...... 33 1.6.1 Histone methylation ...... 35 1.6.2 Histone methyltransferases ...... 36 1.6.3 Histone demethylases ...... 37

1.7 The H3K79 histone methyltransferase, Disruptor of telomeric silencing 1-like (DOT1L) ...... 38 1.7.1 DOT1L protein structure ...... 39 1.7.2 Regulatory functions of DOT1L...... 41 1.7.3 The role of DOT1L in DNA damage response ...... 44 1.7.4 DOT1L and mixed lineage leukaemia ...... 45 1.7.5 The role of DOT1L in other cancers ...... 50

1.8 Jumonji domain-containing protein 6 ...... 51 1.8.1 JMJD6 protein structure ...... 52 1.8.2 The enzymatic functions of JMJD6 ...... 53 1.8.3 The biological functions of JMJD6 ...... 55 1.8.4 The role of JMJD6 in cancer ...... 56

1.9 Cancer therapies targeting epigenetic markers ...... 58 1.9.1 Cancer treatments targeting DNA methylation ...... 58 1.9.2 Histone deacetylase (HDAC) inhibitors ...... 59 1.9.3 EZH2 histone methyltransferase inhibitors ...... 61 1.9.4 DOT1L histone methyltransferase inhibitors ...... 62 1.9.5 Anti-cancer efficacy of DOT1L inhibitors ...... 66

1.10 Hypothesis ...... 69 1.10.1 Project Aims ...... 70

Chapter 2: Materials and methods ...... 71

2.1 Mammalian cell culture ...... 71 2.1.1 Passaging of mammalian cells ...... 71 2.1.2 Cryopreservation and thawing of cells ...... 72 2.1.3 Cell count ...... 72

2.2 Transfection ...... 73 2.2.1 Transient siRNA transfection ...... 73 2.2.2 Plasmid transfection ...... 75

2.3 Alamar blue assay ...... 76

2.4 Reverse transcription PCR (RT-PCR) ...... 77 2.4.1 RNA extraction ...... 77 2.4.2 cDNA synthesis ...... 77 2.4.3 PCR amplification and RT-PCR analysis ...... 79

2.5 Immunoblot analysis ...... 81 2.5.1 Protein extraction ...... 81 2.5.2 Histone acid extraction ...... 82 2.5.3 Gel electrophoresis and immunoblotting ...... 83

2.6 Protein co-immunoprecipitation assay ...... 85

2.7 Chromatin imunoprecipitation (ChIP) assay ...... 87

2.8 Establishment of neuroblastoma cell lines stably transfected with DOX-inducible

shRNA constructs ...... 90

2.9 In vivo mouse experiments...... 92

2.10 Bioinformatics analysis of gene expression data ...... 93

2.11 Patient tumor sample analysis ...... 94

2.12 Statistical analysis ...... 95

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Chapter 3: DOT1L regulates N-Myc target gene expression in neuroblastoma ...... 96

3.1 Introduction ...... 96

3.2 Results ...... 99 3.2.1 N-Myc upregulates DOT1L gene expression in neuroblastoma cells ...... 99 3.2.2 N-Myc binds to a non-canonical E-box at the DOT1L gene promoter ...... 103 3.2.3 DOT1L knockdown causes decreased N-Myc target gene transcription and reduces neuroblastoma cell proliferation ...... 105 3.2.4 DOT1L-mediated H3K79 methylation facilitates N-Myc protein binding to target genes promoters ...... 111 3.2.5 The small molecular DOT1L inhibitor SGC0646 reduces DOT1L and N-Myc

target gene expression in neuroblastoma cells ...... 118

3.3 Discussion ...... 125

Chapter 4: DOT1L gene expression promotes neuroblastoma tumour growth and serves as an independent prognostic factor for poor patient outcome ...... 130

4.1 Introduction ...... 130

4.2 Results ...... 133 4.2.1 Doxycycline-inducible DOT1L knockdown reduces ODC1 and E2F2 gene expression and neuroblastoma cell proliferation ...... 133 4.2.2 DOT1L shRNA reduces neuroblastoma tumour progression and improves overall survival in vivo...... 138 4.2.3 High level of DOT1L gene expression in human neuroblastoma tissues positively

correlate to MYCN gene expression and poor patient prognosis ...... 143

4.3 Discussion ...... 150

Chapter 5: JMJD6 up-regulates Myc and promotes neuroblastoma tumour progression

...... 154

5.1 Introduction ...... 154

5.2 Results ...... 157 5.2.1 JMJD6 gene gain frequently occurs in human neuroblastoma tissues ...... 157 5.2.2 JMJD6 up-regulates N-Myc and c-Myc expression in neuroblastoma cell lines .. 159 5.2.3 JMJD6 induces neuroblastoma cell proliferation ...... 164 5.2.4 Doxycycline-inducible JMJD6 knockdown reduces N-Myc and c-Myc gene expression and neuroblastoma cell proliferation ...... 166 5.2.5 JMJD6 shRNA reduces neuroblastoma tumour progression and improves overall survival in vivo...... 174 5.2.6 JMJD6 expression positively correlates to Myc expression in human neuroblastoma

tissues...... 180

5.3 Discussion ...... 187

Chapter 6. Final Discussion ...... 191

6.1 General discussion ...... 191 6.2 Conclusion ...... 202 6.3 Future Directions ...... 203

List of Figures

Figure 1.1. The mechanism of DOT1L catalysing histone H3K79 methylation with its substrate, S-adenosyl-L-methionine (SAM) ...... 40

Figure 1.2. Model of possible MLL-AF9 and DOT1L-mediated gene transcription mechanism in MLL-driven leukaemia ...... 49

Figure 1.3. Current small molecular DOT1L inhibitors ...... 64

Figure 3.1. Knocking down N-Myc gene expression leads to a reduction in DOT1L mRNA and protein expression ...... 100

Figure 3.2. Overexpression of N-Myc in a MYCN-non-amplified neuroblastoma cell line results in increased DOT1L mRNA and protein expression ...... 102

Figure 3.3. N-Myc binds to a non-canonical E-box at the DOT1L gene promoter ...... 104

Figure 3.4. DOT1L knockdown reduces the RNA and protein expression of N-Myc target gene, ODC1 ...... 106

Figure 3.5. DOT1L knockdown reduces the RNA and protein expression of N-Myc target gene, E2F2 ...... 109

Figure 3.6. Knocking-down DOT1L or E2F2 leads to reduced cell proliferation in N-Myc overexpressing neuroblastoma cell lines ...... 110

Figure 3.7. DOT1L forms a protein complex with N-Myc ...... 112

Figure 3.8. H3K79 di-methylation peaks occur in the intron 1 region of the N-Myc target gene, E2F2 ...... 114

Figure 3.9. Knocking-down DOT1L reduces H3K79 di-methylation at the E2F2 and ODC1 gene promoters ...... 115

Figure 3.10. DOT1L knock-down decreases N-Myc protein binding to E-box regions of E2F2 and ODC1 gene promoters...... 117

Figure 3.11. The DOT1L inhibitor SGC0946 reduced neuroblastoma colony formation 120

Figure 3.12. The DOT1L inhibitor SGC0946 reduced H3K79me2 in a dose dependant manner ...... 122

Figure 3.13. The DOT1L inhibitor SGC0946 reduced ODC1 and E2F2 gene expression in N-Myc over-expressing neuroblastoma cell lines ...... 124

Figure 4.1 DOT1L shRNA knocked down DOT1L, E2F2 and ODC1 mRNA and protein expression ...... 134

Figure 4.2 DOT1L shRNA knocks down DOT1L, E2F2 and ODC1 mRNA and protein expression ...... 135

Figure 4.3 DOT1L shRNA decreases H3K79me2 and reduces cell proliferation ...... 137

Figure 4.4 Knocking down DOT1L decreases tumour progression and improves overall survival in neuroblastoma-bearing mice ...... 139

Figure 4.5 DOT1L shRNA knocks down DOT1L, ODC1 and E2F2 protein expression in BE(2)-C xenograft tumours ...... 141

Figure 4.6 DOT1L shRNA decreases DOT1L, ODC1 and E2F2 protein expression in Kelly neuroblastoma tissues...... 142

Figure 4.7 High DOT1L gene expression correlates with MYCN gene expression in human neuroblastoma tissue samples...... 144

Figure 4.8 High levels of DOT1L gene expression in human neuroblastoma tissues correlates with poor overall patient survival...... 146

Figure 4.9 High levels of DOT1L gene expression in MYCN-amplified human neuroblastoma tissues correlate with poor overall patient survival...... 147

Figure 5.1 MYCN gene amplification and JMJD6 gene gain co-occur in human neuroblastoma tissues ...... 158

Figure 5.2. JMJD6 knockdown decreases N-Myc mRNA and protein expression ...... 160

Figure 5.3. JMJD6 knockdown decreases c-Myc mRNA and protein expression...... 161

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Figure 5.4. Myc does not regulate JMJD6 expression ...... 163

Figure 5.5. JMJD6 knockdown decreases neuroblastoma cell proliferation ...... 165

Figure 5.6. JMJD6 shRNA knocks down JMJD6 and N-Myc mRNA and protein expression in N-Myc overexpressing cells ...... 167

Figure 5.7. JMJD6 shRNA knocks down JMJD6 and c-Myc mRNA and protein expression in c-Myc overexpressing cells ...... 168

Figure 5.8. JMJD6 shRNAs decrease neuroblastoma cell proliferation in CHP-134 and SK- N-AS stable cell lines ...... 170

Figure 5.9. JMJD6 shRNAs reduce neuroblastoma colony formation ...... 172

Figure 5.10. JMJD6 shRNAs reduce neuroblastoma colony formation ...... 173

Figure 5.11. Knocking down JMJD6 decreases tumour progression and improves overall mouse survival ...... 176

Figure 5.12. JMJD6 shRNA decreases JMJD6 and N-Myc protein expression in CHP-134 neuroblastoma xenografts ...... 178

Figure 5.13. JMJD6 shRNA decreases JMJD6 and c-Myc protein expression in SK-N-AS neuroblastoma xenografts ...... 179

Figure 5.14. JMJD6 expression correlates to Myc expression in human neuroblastoma patient samples ...... 181

Figure 5.15. High JMJD6 expression in human neuroblastoma tissues correlates to poor patient prognosis ...... 183

Figure 6.1 Proposed model for N-Myc-driven neuroblastoma ...... 200

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List of Tables

Table 1.1: The International Neuroblastoma Staging System (INSS) ...... 6

Table 1.2: The International Neuroblastoma Risk Group Staging System (INRGSS) ...... 8

Table 2.1: siRNA sequences targeting N-Myc, c-Myc, DOT1L, E2F2 and JMJD6 ...... 73

Table 2.2: Amount of siRNA and lipofectamine used for siRNA transfections ...... 74

Table 2.3: The components of the cDNA master mix.78 Table 2.3: Primer sequence for RT- PCR ...... 78

Table 2.4: Primer sequence for RT-PCR ...... 80

Table 2.5: List of all antibodies used for immunoblotting ...... 84

Table 2.6: Primer sequences for RT-PCR analysis of ChIP ...... 89

Table 2.7: shRNA sequences used to generate stable cell lines ...... 91

Table 4.1: Multivariable Cox regression analysis of DOT1L expression in tumour tissues as a factor prognostic for outcome in 476 neuroblastoma patients ...... 149

Table 5.1: High JMJD6 gene expression is an independent prognostic factor for poor patient outcome in neuroblastoma ...... 185

List of Abbreviations

ACEC Animal Care and Ethics Committee (UNSW)

AML Acute myeloid leukemia

BSA Bovine serum albumin cDNA Complementary DNA

DMSO Dimethyl sulfoxide

DOT1L DOT1-like

FCS Foetal calf serum

H3K79 Histone H3 Lysine 79

HDAC Histone deacetylase

INSS International neuroblastoma staging system

MEM Minimal essential media miRNA microRNA

ODC1 Ornithine decarboxylase 1

PBS Phosphate buffered saline

PCR Polymerase chain reaction

RPMI medium Roswell Park Memorial Institute medium

RT-PCR Reverse transcriptase polymerase chain reaction

UTR Untranslated region

List of publications

Matthew Wong, Patsie Polly, and Tao Liu. The histone methyltransferase DOT1L: regulatory functions and a cancer therapy target. Am J Cancer Res. 2015; 5(9): 2823–2837. Published online August 15 2015.

Conference presentations

Matthew Wong, Patsie Polly, and Tao Liu. The role of DOT1L in neuroblastoma. European

Cancer Congress (Vienna), September 27th 2015.

Matthew Wong, Patsie Polly, and Tao Liu. The role of DOT1L in neuroblastoma. Lorne

Cancer Congress (Melbourne), February 13th 2014.

Acknowledgement

I would like to thank everybody from the Children Cancer Institute Australia (CCIA) and especially everyone from the Histone Modification project that have helped me these four years. The experiments and results wouldn’t have been possible without the support of the people from my lab. I‘d also like to thank my supervisor and co-supervisor, Dr Tao Liu and

A. Prof Patsie Polly who have guided me through this scientific endeavour to its conclusion. I have to thanks the support staff (Aldona et al) who have helped make everything in the lab work. A special thanks to everyone in the mouse house, who help me with my mouse work.

Finally I’d like to thank everyone who supported me outside the lab, especially my family.

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Abstract

N-Myc induces neuroblastoma by regulating the expression of target oncogenes.

Histone H3 lysine 79 (H3K79) methylation at Myc-responsive elements of target gene promoters is a strict prerequisites for Myc-induced transcriptional activation. DOT1L is the only known histone methyltransferase that catalyses mono-methylation (me), di-methylation

(me2) and tri-methylation (me3) at the histone H3K79 position, which have been linked to gene transcriptional activation. JMJD6 is a bi-functional arginine demethylase and lysyl- hydroxylase. The JMJD6 gene is located on the chromosome 17q25 position. 17q21-gter gain has been identified as the most frequent chromosome alternation in neuroblastoma and an indicator of poor patient prognostic.

Here, I investigated the roles of DOT1L and JMJD6 in N-Myc over-expressing neuroblastoma. I found that N-Myc up-regulated DOT1L mRNA and protein expression, by binding to an E-box at the DOT1L gene promoter. Knocking-down DOT1L reduced the mRNA and protein expression of the N-Myc target genes, ODC1 and E2F2. DOT1L and N-

Myc formed a protein complex, and knocking-down DOT1L reduced histone H3K79me2 and

N-Myc protein binding at the promoters of the N-Myc target genes ODC1 and E2F2, and reduced neuroblastoma cell proliferation in vitro and tumour progression in neuroblastoma- bearing mice. In a publicly available microarray gene expression dataset, high levels of

DOT1L gene expression in tumours correlated with high levels of MYCN gene expression and poor patient survival independent of MYCN amplification, age at diagnosis and disease stage.

I have also demonstrated that JMJD6 up-regulated both N-Myc and c-Myc in neuroblastoma cell lines. Conversely N-Myc and c-Myc did not affect JMJD6 mRNA or protein expression. Knocking down JMJD6 reduced neuroblastoma cell proliferation in vitro

xiii and tumour progression in neuroblastoma-bearing mice. JMJD6 gene expression correlated with MYCN gene expression in human neuroblastoma tissue microarray gene expression datasets. High DOT1L gene expression was also a prognostic factor for poor neuroblastoma patient outcome.

In conclusion, these data identify DOT1L as a novel co-factor in N-Myc oncogenesis, and provide critical evidence for the potential utilization of DOT1L inhibitors for the therapy of MYCN amplified neuroblastoma. JMJD6 up-regulates N-Myc and c-Myc gene expression and JMJD6 gene gain is a potential mechanism for 17q21-qter gain driven neuroblastoma tumourigenesis.

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Chapter 1: Literature review and project aims

1.1 Cancer

Cancer occurs in a range of cell types and is caused by a build-up of genetic and epigenetic abnormalities. This results from genetic and environmental factors, such as viral infections, carcinogenic chemicals and radiation exposure. In order for a cell to become cancerous, genetic and epigenetic abnormalities, such as genetic mutations, oncogene overexpression/amplification and tumour suppressor gene silencing need to occur (Hanahan 2000,

Baylin 2006). These changes result in increased cell proliferation and resistance to cell death.

The uncontrolled cell proliferation leads to tumours that can eventually invade the blood stream or the lymphatic system, resulting in tumour metastasis.

One of the most common genetic abnormalities found in tumour tissues is the amplification/gain of function mutation of the Myc oncogenes. Myc oncoproteins including c-Myc and N-Myc are over-expressed in approximately 50% of human malignant tissues from the general population of cancer patients (Nesbit 1999). MYCN oncogene amplification and consequent over-expression of N-Myc mRNA and protein are seen as a clonal feature in one quarter of tumours, and correlate with poor prognosis in patients with neuroblastoma

(Brodeur 2003). C-Myc gene amplification and mutations are often observed in adult cancer tissues, with 33% of primary pancreatic tumours demonstrating c-Myc oncogene amplification (Schleger 2002), and 65% of Burkitt's lymphomas exhibiting at least one amino acid substitution within the c-Myc protein (Bhatia 1993).

Virtually all types of human cancer show epigenetic abnormalities which co-operate with genetic changes to induce tumour initiation and progression (Baylin 2006, Feinberg

2006). Unlike genetic alterations, which are very difficult to reverse, epigenetic aberrations including histone deacetylation, aberrant histone methylation status and promoter DNA hypermethylation are potentially reversible, allowing the malignant cell population to revert to a more ‘normal’ state through epigenetic therapy including inhibitors of histone deacetylases, DNA methylation as well as histone methyltransferases (Bolden 2006, Yoo

2006, Daigle 2011).

1.2 Neuroblastoma

Neuroblastoma is an embryonal tumour of the autonomic nervous system and the most commonly diagnosed cancer in early childhood, with a median age of 17 months at the time of diagnosis (Brodeur 2003, Smith 2010). Neuroblastoma occurs in primordial neural crest cells that later comprise the sympathetic ganglia and adrenal medulla. Its clinical behaviour shows large variation, from spontaneous regression to inexorable progression despite intensive multimodal therapy, which has been attributed to molecular differences among tumours.

Neuroblastoma has the highest rate of spontaneous regression among human cancers.

Children with late stage neuroblastoma often have initial progression of multifocal disease followed by spontaneous regression. Delayed implementation of normal apoptotic pathways have been one proposed explanation (Brodeur 2003). The apoptosis pathway of programmed cell death can be triggered by both exogenous and endogenous signals. Nerve growth factor

(NGF) withdrawal is a major signal for apoptosis in the developing nervous system. So

2 blocking signal transduction through the neurotropin receptors can initiate the apoptotic pathway. Members of the tumour necrosis factor receptor family, such as p75 that binds to

NGF and CD95/Fas (Bunone 1997), and members of the retinoic acid receptor family can mediate the initiation of apoptosis in neuroblastoma cell lines (Fulda 1997). Increased CD95 expression seems to be essential for chemotherapy induced apoptosis in neuroblastoma

(Fulda 1997).

Aggressive neuroblastomas show dysfunction in the apoptotic pathway, allowing tumour cells to evade apoptosis and promoting tumour growth. The apoptosis suppressor genes Bcl-2 and Bcl-X are highly expressed early in neuronal ontogeny (Krajewska 2002).

Bcl-2 is highly expressed in primary tumours and neuroblastoma cell lines (Hanada 1993), with the level of Bcl-2 expression inversely related to the proportion of cells undergoing apoptosis (Oue 1996). However, there has been no established correlation between the level of Bcl-2 expression in primary tumours and prognostic variables (Ikeda 1995, Tonini 1997).

The Bcl-2 protein may play an important role in the acquired resistance to chemotherapy with transfection of cDNA encoding Bcl-2 and Bcl-X into neuroblastoma cells causing resistance to alkylator agent-induced apoptosis in a dose dependent manner (Dole 1995). Caspases are proteolytic enzymes that execute the apoptosis signal. Increased expression of interleukin 1β- converting enzyme (caspase-1) and other caspases in neuroblastoma was associated with favourable biological features and improved patient outcomes (Posmantur 1997, Bradshaw

1998).

A lack of understanding of molecular and genetic risk factors in neuroblastoma have meant a lack of screening arrays for testing therapeutic strategies pre- and post-treatment.

Currently immunocyto-chemical and PCR-based assays are used to detect neuroblastoma

3 specific transcripts such as tyrosine hydroxylase, GD2 synthase and PgP9.5 in the bone marrow or blood at the time of diagnosis as well as post-treatment in order to assess and monitor the effectiveness of treatment. These assays increase the sensitivity of neuroblastoma detection, diagnosis of recurrence and improve patient outcome (Cheung 2001, Fukuda 2001,

Reynolds 2001).

1.2.1 Neuroblastoma Staging

Clinical presentation of neuroblastoma varies depending on the primary site of the tumour and disease staging. Neuroblastoma is classified into three main clinical scenarios: localised tumours, metastatic tumours and 4S tumours. Localised tumours present with few symptoms and are sensitive to chemotherapy (Maris 2007). The majority of localised tumours have favourable biological features and can be treated successfully with surgery alone (Evans

1996, Perez 2000). Patients with metastatic tumours generally present with prominent symptoms at the time of diagnosis. Patients with 4S tumours have a small localised tumour with metastasis in the liver, skin or bone marrow which have a high likelihood of spontaneous regression (Maris 2007).

The International Neuroblastoma Staging System (INSS) was developed in the mid-

1990s for the worldwide comparison of patient outcomes depending on treatment

(http://www.cancer.net/cancer-types/neuroblastoma-childhood/stages-and-groups) (Brodeur

1993). This is based on physical examinations, imaging tests, surgery results and biopsies of the tumour and surrounding tissue (Brodeur 1993, London 2011).

Lower stage neuroblastomas are classified as INSS stages 1, 2A and 2B, and are generally diagnosed in children before 1 year of age with localised tumours. These neuroblastomas are curable with surgery and little to no adjuvant therapy. Higher stage neuroblastomas are classified as INSS stages 3 and 4, are often unresectable due to having spread to adjacent organs or having surrounded critical nerves and blood vessels. Advanced

4S neuroblastomas typically metastasise to regional lymph nodes and bone marrow via the hematopoietic system and can also infiltrate the liver. Additional prognostic markers such as age, DNA ploidy, tumour histology, chromosome deletions/gains and N-Myc gene amplification are used to determine a patient’s prognosis (Brodeur 2003).

Table 1.1: The International Neuroblastoma Staging System (INSS). Adapted from Brodeur (1993).

Staging Definition

1 Localised tumour with complete gross excision, with or without

microscopic residual disease; representative ipsilateral lymph nodes

negative for tumour microscopically (nodes attached to and removed with

the primary tumour could be positive)

2A Localised tumour with incomplete gross excision; representative ipsilateral

non-adherent lymph nodes negative for tumour microscopically

2B Localised tumour with or without complete gross excision, with ipsilateral

non-adherent lymph nodes positive for tumour. Enlarged contralateral

lymph nodes should be negative microscopically

3 Unresectable unilateral tumour infiltrating across the midline, with or

without regional lymph node involvement; or localised unilateral tumour

with contralateral regional lymph node involvement; or midline tumour with

bilateral extension by infiltration (unresectable) or by lymph node

involvement

4 Any primary tumour with dissemination to distant lymph nodes, bone, bone

marrow, liver, skin, or other organs (except as defined by stage 4S)

4S Localized primary tumour (as defined for stage 1, 2A or 2B) with

dissemination limited to skin, liver, and/or bone marrow (limited to infants

< 1 year of age)

Recently neuroblastoma staging has transitioned from the INSS to the International

Neuroblastoma Risk Group Staging System (INRGSS) (http://www.cancer.net/cancer- types/neuroblastoma-childhood/stages-and-groups), a more robust staging system that incorporates image defined risk factors (Cohn 2009, Monclair 2009). Using the INGRSS, patients with neuroblastoma are classified into three groups: low risk, intermediate risk and high risk, based on the clinical and biological features of the tumour. These risk factors: age at time of diagnosis, INSS staging, tumour histopathology, DNA index and MYCN gene amplification status, are then used to stratify treatment intensity (Table 1.2). Patients in the low and intermediate risk groups have an overall survival rate of 90% with minimal therapy

(Rubie 2011). The high risk patient group have poor therapeutic outcome and often become chemotherapy and radiotherapy resistant with extensive metastasis to regional lymph nodes and bone marrow with possible infiltration of the liver (Brodeur 2003, Baker 2010, Strother

2012).

Table 1.2: The International Neuroblastoma Risk Group Staging System (INRGSS).

Adapted from Marris 2007.

INSS Age at time MYCN Ploidy Histology Other INRGSS risk stage of diagnosis group 1 Low 2A/2B Not amplified >50% Intermediate resection Not amplified <50% Intermediate resection Not amplified Biopsy only High Amplified 3 <547 days Not amplified Intermediate >547 days Not amplified Favourable Intermediate Amplified High >547 days Not amplified Unfavourable High 4 <365 days High <365 days Intermediate 364-547 Amplified High days 364-547 DI = 1 High days 364-547 Unfavourable High days 364-547 Not amplified DI > 1 Favourable Intermediate days >547 days High 4S <365 days Not amplified DI > 1 Favourable Asymptomatic Low <365 days Not amplified DI = 1 Intermediate <365 days Missing Missing Missing Intermediate <365 days Not amplified Asymptomatic Intermediate <365 days Not amplified Unfavourable Intermediate <365 days Amplified High

Most neuroblastoma cell lines and advanced primary tumours have either near diploid or tetraploid DNA content, while favourable neuroblastomas, especially those in children less than 1 year of age usually have a hyperdiploids or triploid DNA index (Brodeur 1997).

Diploid/tetraploid tumours are characterised by chromosomal rearrangements, including amplification, deletion and unbalanced translocations, while hyperdiploid tumours typically have whole chromosome gains with few structural rearrangements (Brodeur 1993). There appears to be a fundamental difference among neuroblastoma tumours with diploid/tetraploid tumours demonstrating general genomic instability and the hyperdiploid tumours having mutations in the machinery of mitosis and chromosomal segregation (Look 1984).

High risk clinical prognostic factors include age >18 months at diagnosis, amplification of the MYCN gene, and structural chromosomal alterations. While whole chromosome 17 gain predicts good prognosis, segmental deletions of chromosome arms 1p,

3p, 4p, and 11q as well as segmental gains of chromosome arms 1q and 17q predict poor prognosis (Tomioka 2008, Janoueix-Lerosey 2009, Maris 2010). Analysis of Giemsa-banded karyotypes derived from neuroblastoma primary tumours and cell lines showed recurrent abnormalities in the long arm of chromosome 17 (Gilbert 1984). This gain of 17q genetic material is a common genetic abnormality in primary neuroblastomas due to unbalanced 1;17 translocations that occur frequently and result in loss of distal 1p and gain of distal 17q material (Savelyeva 1994, Van Roy 1997). However, these 17q translocation breakpoints are heterogeneous, often involving other chromosomes (Lastowska 1997). Using comparative genomic hybridisation analyses it has been shown that the 17q21-qter gain occurred in 50-

75% of primary tumours (Altura 1997). A 25 megabase region at the 17q translocation has been shown to be the smallest region of gain using in situ hybridisation mapping (Meddeb

1996), making it the likely location of genes that promote neuroblastoma tumourigenesis when present in increased copy number.

1.2.2 Hereditary Neuoblastoma

Hereditary neuroblastoma has been observed with 1-2% of patients having a family history of the disease (Knudson 1972, Friedman 2005). This is similar to other embryonal childhood cancers where familial predisposition has been observed (Burnichon 2012).

Familial neuroblastoma is inherited in an autosomal dominant Mendelian fashion with incomplete penetrance. Those affected with hereditary neuroblastoma are often diagnosed with at infancy with multiple primary tumours present (Kushner 1986). This indicates that hereditary neuroblastoma may occur as a result of a germline mutation in one allele of tumour suppressor gene/genes. There is remarkable heterogeneity among cases of hereditary neuroblastoma, even among a family the cancer can range from asymptomatic and spontaneously regressing neuroblastoma to rapidly progressive and metastatic tumours

(Maris 1997). Thus, it has been hypothesized that the timing of inactivation of the second tumour suppressor gene allele and additional germline mutations confer the end clinical phenotype (Maris 1997).

The similarity between neuroblastoma and other genetically determined congenital malformations of neural crest cells, such as Hirschsprung (HSCR) disease and congenital central hypoventilation syndrome (CCHS) has led to germline mutations of predisposed genes being the suspected cause of hereditary neuroblastoma (Rohrer 2002). The identification of the paired-like homeobox 2B (PHOX2B) gene as the major disease causing gene in isolated and syndromic CCHS, leads to it also being considered as a candidate gene

10 for neuroblastoma. A documented familial case of neuroblastoma and another patient with the HSCR-neuroblastoma has led to PHOX2B being the first gene where germline mutations are predisposed to neuroblastoma (Trochet D 2004). The anaplastic lymphoma kinase (ALK) gene was found to explain most cases of hereditary neuroblastoma. It was identified using linkage analysis of the whole genome in neuroblastoma pedigrees that showed a significant signal at the chromosome bands 2p23-2 (Mossé 2008).

1.2.3 Neuroblastoma and anaplastic lymphoma kinase

Anaplastic Lymphoma Kinase (ALK) is a receptor tyrosine kinase predominantly expressed in the developing nervous system (Motegi 2004). When altered by translocation, mutation or amplification, ALK has been shown to have oncogenic properties in several tumour types including non-small cell lung cancer, anaplastic large cell lymphoma and neuroblastoma (Chen 2008, George 2008, Janoueix-Lerosey 2008, Mossé 2008, La Madrid

2012). High ALK expression is a prognostic factor for poor patient outcome in neuroblastoma patients (Carpenter 2012).

ALK has been found to collaborate with N-Myc to advance neuroblastoma tumour development by blocking apoptotic signals in hyperplastic neuroblasts, allowing their continued expansion and oncogenic transformation (Liu 2012, Zhu 2012). Down-regulation of ALK was shown to lead to decreased proliferation and differentiation in neuroblastoma cells (Passoni 2009).

Sequencing of 194 samples from patients with high risk neuroblastoma showed somatically acquired mutations in the tyrosine kinase domain of ALK in 12.4% of samples

(Mossé 2008). Nine mutations were mapped to critical regions of the kinase domain and predicted with high probability to be oncogenic drivers. Mutations resulted in constitutive phosphorylation with targeted knockdown of ALK mRNA resulting in profound growth inhibition in neuroblastoma cell lines with mutant or amplified ALK as well as two out of six wild type cell lines for ALK (Mossé 2008). In 2012, it was demonstrated that immunohistochemistry of ALK expression was an independent test of poor patient prognosis, linking high ALK protein expression to low survival of neuroblastoma making it a potential therapeutic target using small molecular tyrosine kinase inhibitors (Duijkers 2012).

1.2.4 Drug resistance in neuroblastoma

Patients with high risk neuroblastoma have a 5 year event-free survival rate of <50% despite treatment involving intensive chemotherapy and surgery, followed by myeloabative therapy with hematopoietic stem cell rescue and then differentiation therapy with retinoic acid (Matthay 1999). Many neuroblastoma patients initially respond well to chemotherapy but disease progression recommences after the conclusion of treatment. Neuroblastoma cell lines derived from tumours at relapse show increased resistance to standard chemotherapy agents compared to cell lines established at diagnosis (Keshelava 1997). Therefore, acquired drug resistance appears to be an important cause of neuroblastoma treatment failure. The most well characterised mechanism of multidrug resistance involves increased expression of the adenosine triphosphate dependant efflux pump P-glycoproteins, which are encoded by the

PGY1 (also known as MDR1) and the multidrug resistance-associated protein (MRP) genes

(Bradshaw 1998). In cancer cells, increased expression of p-glycoproteins can occur via transcriptional activation, increased mRNA stability or genomic amplification and has been

12 hypothesized to confer resistance to natural product drugs such as anthracyclines, epipodphyllotoxins and vinca alkaloids (Ronison 1991).

In neuroblastoma, PGY1 overexpression occurs after chemotherapy treatment (Bates

1991), and is restricted to advanced stage tumours, correlating with a poor response to chemotherapy (Goldstein LJ 1990, Chan 1991). However, this is controversial as other groups were unable to replicate these results using immunohistochemistry (Dhooge 1997) or

RT-PCR techniques (Norris 1996). PGY1 expression is also inversely correlated to N-Myc expression (Nakagawara 1991), and was found to be restricted to normal stromal cells in neuroblastoma primary tumour biopsy specimens (Favrot 1991). Therefore, PGY1 may be transcriptionally activated in response to cell differentiation and not chemotherapy (Bates

1989), meaning that PGY1 over-expression is rarely the cause of de novo drug resistance in untreated neuroblastomas.

MRP family functions as an efflux pump that can render a cell resistant to anticancer agents when overexpressed (Bradshaw 1998). A study of 60 primary untreated neuroblastomas (Norris 1996) showed that MRP expression was strongly correlated with N-

Myc expression and poor patient survival. Three E-box binding motifs were also identified in the MRP promoter region, suggesting that N-Myc directly modulates MRP expression. This was tested by transfecting N-Myc antisense RNA into a neuroblastoma cell line that overexpressed both MRP and N-Myc, resulting in the reduction of MRP mRNA to undetectable levels (Norris 1997). A subset of the MRP family, the ATP-binding cassette, subfamily C (ABCC) transporters have also been shown to contribute to the malignant phenotype in childhood neuroblastoma independent of cytotoxic drug efflux (Henderson

2011). The ABC subfamily C member 1 (ABCC1), ABCC3 and ABCC4 are also direct transcriptional targets of N-Myc (Haber 2006, Porro 2010, Henderson 2011).

1.3 C-Myc and N-Myc regulate gene expression

Myc is a family of transcription factors made up of known oncogenes, c-Myc, L-Myc and N-Myc (Vennstrom 1982, Brodeur 1984, Nau 1985). Myc oncogenes regulate many growth promoting signalling pathways and are an early response gene family downstream of many ligand signalling pathways. Due to its essential role in target gene regulation, cell cycle regulation, apoptosis, senescence, differentiation and metabolism, Myc expression is highly regulated by numerous mechanisms, involving transcriptional regulatory motifs located within its promoter region.

Studies of fulminant chicken tumours caused by oncogenic retroviruses, led to the discovery of the v-Myc oncogene in avian myelocytomatosis virus (MC29) (Sheiness 1979).

The v-Myc oncogene was found to be derived from the c-Myc gene in the host chicken genome (Bártová 1982). The human homolog was found to be located on chromosome 8 using Southern blotting. C-Myc was confirmed to possess oncogenic properties when a region of its chromosome 8 was found to be translocated to chromosomes 2, 14 and 22 in

Burkitt lymphoma cells (Dalla-Favera 1982). The c-Myc signalling pathway was also found to be essential for the development of colon carcinoma via enhancing T-cell factor transcriptional activation, leading to cancer development (He 1998). Recent studies have found that c-Myc oncogene is one of the most amplified oncogenes across a range of human cancers (Beroukhim 2010).

Myc family proteins contain a basic Helix-Loop-Helix (bHLH) domain and a Leucine zipper domain at its C terminus. These motifs have been found in sequence specific DNA binding proteins and shown to be critical for Myc protein-protein binding and transactivator function. Fusion of the Myc N-terminus and the Gal4 DNA-binding domain showed that the

Myc N-terminus was a potent transactivator of downstream N-Myc target genes, such as

(Kato 1990).

1.3.1 Myc mediates transcriptional activation

The discovery of MAX in 1991 (Blackwood 1991) has been critical in elucidating the function of Myc, as many later studies have demonstrated that Myc/MAX interaction is required for critical biological functions such as apoptosis and cell cycle progression (Hurlin

2006). The bHLH and Leucine zipper motifs of Myc allow it to heterodimerise with MAX, a small ubiquitously expressed protein that can bind to a range of bHLH proteins. This

Myc/MAX complex has much greater DNA binding capability than Myc proteins alone and functions as a sequence specific DNA binding protein complex. The heterodimer recruits a range of cofactors to E-box sequences 1 kilobase up or downstream of the transcription start site of target genes in order to start gene transcription. Recruited cofactors include proteins involved in chromatin remodelling, histone acetylation and ubiquitination, such as histone acetyltransferase complexes that possess the transformation/transcription domain associated protein (TRRAP) subunit (McMahon 1998). Other cofactors include the S-phase kinase- associated protein 2 (SKP2) ubiquitin ligase and cyclin-dependent kinase 9 (CDK9), which can directly phosphorylate RNA polymerase II and thereby enhance transcriptional elongation (Kanazawa 2003).

Study of Myc mediated gene transcription have identified a wide range of up- regulated genes (Kim 2008, Seitz 2011). For Myc it has been difficult to definitively identify gene sets that are directly controlled by Myc across all cell and cancer types and are critical to Myc-driven oncogenetic properties (Eilers 2008, Chandriani 2009).

The canonical E-box sequence (CACGTG) occurs throughout the human genome, on average once every 4kb (Eilers 2008). The Myc/MAX heterodimer is also able to bind to non-canonical E-box sequences and even to gene promoters lacking an E-box (Guccione

2006, Zeller 2006, Boone 2011, Lin 2012). E-boxes are also able to bind a wide range of basic Helix-Loop-Helix domain and Leucine zipper proteins (Jones 2004). This frequency of

E-box occurrence and the ability of Myc to bind promoters has made it difficult to identify

Myc target genes by examination of the DNA sequence of genes.

Other factors also influence Myc binding, with Myc found to preferentially bind to E- boxes that are located close to CpG islands (Fernandez 2003, Zeller 2006), which are known to define transcriptionally active chromatin regions (Kundu 1999). Myc binding is also influenced by post-transcriptional modifications on nucleosomes, avoiding E-boxes in heterochromatin regions but associated with chromatin areas epigentically modified with histone H3 methylation at lysine residues 4 (H3K4) and 79 (H3K79) (Guccione 2006, Lin

2012).

1.3.2 Myc mediates gene repression

Recent evidence has shown that N-Myc represses as many genes as it up-regulates with a gene signature of 157 genes that directly correlate with N-Myc protein level but not with N-Myc amplification (Valentijn 2012). The 157 gene signature recognizes a type of

16 neuroblastoma marked by stabilization of N-Myc at the protein level. However, there are 21 down-regulated genes involved in neuronal differentiation (Valentijn 2012).

Myc represses the transcription of certain genes both directly, by binding to DNA, and indirectly, by modulating microRNA expression. Direct repression occurs via Myc binding to the core promoter region of target genes and interaction with two zinc finger transcription factors, Spi1 and Miz1(Peukert 1997). Both Spi1 and Miz1 have been found to bind to the promoters of Myc repressed genes. When not bound to Myc, Spi1 and Miz1 bind to DNA and stimulate transcription. This has been demonstrated in a Myc mouse mutant

MycV394D, with a point mutation in Myc that prevents it from binding to Miz1, but still allows Myc-MAX binding (Gebhardt 2006). This variation, MycV394D possesses transcription factor activity but could not bind to Miz1, meaning it could not repress target genes normally repressed by Myc.

One mechanism by which N-Myc contributes to neuroblastoma onset is by repressing the nerve growth factor receptor (NGFR) gene (Brodeur 2009). NGFR, also known as

P75NTR encodes a membrane receptor that binds neurotrophins with low affinity. It is suggested that the intracellular regions of NGFR contain death domains capable of inducing neuronal cell death (Casaccia-Bonnefil 1998). NGFR expression levels are prognostic of differentiated tumours in neuroblastoma (Schulte 2009), with low NGFR expression levels in aggressive neuroblastomas possessing N-Myc overexpression. N-Myc binds to the NGFR promoter causing its repression (Iraci 2011). Knocking down of N-Myc by siRNA induces

NGFR expression and sensitizes neuroblastoma cells to NGF mediated apoptosis (Iraci

2011). N-Myc also represses known anti-apoptotic genes such as Galectin-3 suggesting N-

Myc serves a complex dual role in apoptosis regulation (Veschi 2012).

1.3.3 Myc regulation of miRNA expression

Myc has also been shown to indirectly modulate gene transcription by up and down- regulating the expression of small non-coding RNAs, known as microRNAs (miRNAs)

(Chang 2008). In 1989 the first evidence was presented demonstrating that microRNA

(miRNA) products, 21-25 base pairs in length, were capable of regulating gene expression with LIN-1 protein abundance in C. elegans being directly regulated by a miRNA product encoded by the lin4 gene (Ambros 1989, Lee 1993). Since many studies have examined the role of these miRNAs in gene regulation and it has been demonstrated that miRNAs are deregulated in a variety of tumours showing both a tumour suppressing function and an oncogenic function (Liu 2013).

Individual miRNAs can target multiple mRNA transcripts from different genes, increasing the complexity of Myc gene regulation and its importance in gene regulation. One cluster of miRNAs that is up-regulated by c-Myc in human cancer cell lines is miR-17-92, a known oncogene. The miR-17-92 cluster targets transforming growth factor beta (TGF-β) receptor 2 and inhibits the expression of the effector SMAD4, both elements of the TGF-β signalling pathway. This in turn down-regulates clusterin, a member of the thrombospondin type I repeat (TSR) superfamily, stimulating angiogenesis and tumour growth (Dews 2010).

This indirect pathway of clusterin down-regulation is also likely to be present in neuroblastoma as N-Myc has also been shown to up-regulate the miR-17-92 miRNA cluster

(Schulte 2008).

In neuroblastoma it has been shown that N-Myc can act as a transcriptional regulator factor of miRNA expression (Buechner 2012). N-Myc suppresses miR-152 expression thus serving an important role in the control of the genome methylation status as DNA

18 methyltransferase 1 (DNMT1) is a direct target of miR-152 (Das 2010). The miR-17-92 cluster is also a known N-Myc target, leading to its up-regulation with one downstream effect being the down-regulation of DKK3 a gene with tumour suppressor function involving the

Wnt pathway (De Brouwer 2012). Low levels of DKK3 are associated with N-Myc amplified neuroblastoma tumours and its down-regulation promotes G-1 arrest and checkpoint skipping by down-regulation of β-catenin and cyclin D.

The miR-17-92 cluster has also been associated with the negative regulation of clusterin, a tumour and metastasis suppressor gene in neuroblastoma (Chayka 2009). miR-

591, a short tumour suppressor RNA is down-regulated in N-Myc amplified neuroblastoma

(Shohet 2011). miR-542-5p expression is inversely correlated with N-Myc expression in neuroblastoma with its low expression correlating to poor patient outcome (Schulte 2010).

The tumour suppressor effect of miR-542-5p was demonstrated in vivo with knockdown of miR-542-5p blocking cellular invasiveness, decreasing primary tumour growth and metastasis in an orthotopic mouse xenograft model in SCID mice (Bray 2011). This demonstrates the anti-cancer potential of targeting miRNAs in neuroblastoma.

N-Myc directly binds to the promoter region of miR-355, and transcriptionally represses miR-355 expression, leading to TGF-β pathway activation, cell migration and invasiveness (Lynch 2012). N-Myc overexpression in neuroblastoma has also been positively correlated with other known oncogenic miRNAs including miR380-5p (Swarbrick 2010), miR-9 (Ma 2010) and miR-221 (Schulte 2008).

1.4 N-Myc

N-Myc and c-Myc have different patterns of expression in normal tissues. C-Myc is expressed in all proliferating adult human tissues, while N-Myc is expressed in the developing embryo, with low/absent expression in adults (Hirvonen 1989). C-Myc and N-

Myc genes have a pattern of complementary gene expression during embryo development with c-Myc expressed in many tissues but reduced or absent in the neuroepithelium, which expresses high levels of N-Myc instead (Downs 1989). N-Myc is normally expressed during embryogenesis and specifically during early cell differentiation and development stages in the parts of the central nervous system, kidney (Hirvonen 1989), hair follicles (Mugrauer

1988), intestine and lung (Dildrop 1988).

The biochemical properties of N-Myc, including dimerisation with MAX and DNA binding, are similar to c-Myc. Like c-Myc, N-Myc is a transcription factor that controls the expression of many target genes. These target genes in turn regulate essential cellular processes such as apoptosis, cell proliferation, differentiation, metabolism and protein synthesis.

N-Myc has been shown to substitute c-Myc functions in mouse models when the endogenous c-Myc gene is replaced with the N-Myc sequence (Malynn 2000). This results in homozygous N-Myc expressing individuals able to reach adulthood and reproduce, demonstrating that when expressed from the same locus the N-Myc gene is functionally identical to c-Myc.

1.4.1 N-Myc in embryonic development

N-Myc plays a critical role in embryonic development with N-Myc gene mutations being linked to birth defects (Hurlin 2005). Similar to c-Myc, exogenously expressed N-Myc promotes reprogramming of somatic cells to become pluripotent stem cells (Smith 2010).

Neither Myc proteins are required for this reprogramming to occur, but their presence has been shown to be crucial to maintaining pluripotency and cell renewal in a murine model

(Moon 2011). The individual loss of either c-Myc or N-Myc has been shown to have no effect on embryonic stem cells, but the loss of both Myc genes results in the loss of pluripotency and leads to spontaneous differentiation (Smith 2010). N-Myc has also been shown to up-regulate the expression of pluripotency genes, including leukemia inhibitory factor (cholinergic differentiation factor), Lin28b, Kruppel-like factor 2 and 4, in neuroblastoma and neuronal progenitor cells (Cotterman 2009).

N-Myc also plays an essential role in controlling early differentiation and cell proliferation in the neuroepithelium of the nervous system, heart, intestine, kidney and lung.

While N-Myc overexpression in avian and murine neural crest cells leads to increased neuron generation (Wakamatsu 1997), targeted deletion of N-Myc results in neuronal differentiation and severely compromised cell proliferation (Knoepfler 2002). These studies suggest that N-

Myc down-regulation would cause terminal differentiation of tumours.

1.4.2 N-Myc induces neuroblastoma

N-Myc was first discovered in neuroblastoma cell lines as amplified DNA homologous to the c-Myc oncogene (Schwab 1983). MYCN gene amplification causes N-

Myc mRNA and protein over-expression and correlates with poor prognosis in patients with

21 neuroblastoma (Maris and Matthay 1999, Brodeur 2003). Importantly, targeted N-Myc overexpression in transgenic mice leads to the development of neuroblastoma, confirming the capacity of N-Myc to induce neuroblastoma tumourigenesis (Weiss 1997). Studies have shown that N-Myc induces neuroblastoma by modulating gene transcription, leading to cell proliferation and differentiation block (Maris and Matthay 1999, Brodeur 2003).

N-Myc overexpression in neuroblastoma is a recognised prognostic risk factor, contributing to neuroblastoma invasiveness, tumour un-differentiation and angiogenesis

(Schwab 1985, Chan 1997, Goodman 1997). N-Myc plays a central role in neuroblastoma invasiveness primarily by direct or indirect repression of α2, α3 and β1 integrin subunits, which affect the cell matrix and cell-cell interactions (Judware 1997). Caveolin-1 whose down-regulation elicits anchorage-independent growth and tumour formation, is also directly down-regulated by N-Myc (Park 2001). ATP-binding cassette, subfamily C (ABCC) transporter genes that control cell motility and invasion in addition to their typical drug efflux function are also regulated by N-Myc (Porro 2010). Overexpression of ABCC 1 and 4 in neuroblastoma tumours have been associated with reduced event free survival (Henderson

2011).

Aggressive neuroblastomas at stages 3 and 4 are characterised by a low grade of differentiated cells (Maris 1999). N-Myc can form several transcriptional complexes capable of regulating directly and indirectly the expression of genes involved in the neuronal differentiation process. Differentiation is a cellular process where a less specialised cell becomes more specialised during development.

The neuronal leucine-rich repeat (NLRR) family of transmembrane proteins has been shown to influence neuroblastoma tumour differentiation with NLRR3 upregulated in neuroblastoma cells that had been treated with retinoic acid, in order to induce tumour cell differentiation (Akter J 2011). NLRR3 is also directly down-regulated by N-Myc, in association with Miz-1. Another member of the protein family, NLRR1 was shown to positively regulate neuroblastoma cell proliferation and is predominately expressed in primary tumours with N-Myc amplification (Hossain 2012).

Studies have also shown that stable N-Myc knockdowns in mice using lentiviral short hairpin RNAs (shRNAs) can induce p27 and nuclear export sequence increase, subsequently stimulating neuronal differentiation pathways in neuroblastoma (Jiang 2011).

Neuroblastomas without N-Myc overexpression have also been characterised by normal expression levels of proteins involved in the sonic hedgehog signalling pathway: Shh, GLI1 and Ptch1 corresponding to a good patient prognosis although the molecular link between these two is not known (Souzaki 2010).

N-Myc plays a critical role in regulating the expression of neurotrophic tyrosine receptor kinase (NTRK) family genes, especially tropomyosin kinase A (TrkA) receptors

(Nakagawara 1993) with aggressive neuroblastoma tumours characterised by low levels of

TrkA expression (Brodeur 2003). Tropomyosin receptors TrkA, TrkB and TrkC play a crucial role in the development and maintenance of the central and peripheral nervous system by regulating cell differentiation. The primary ligands for these transmembrane receptors are nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF) and neurotropin-3

(NT-3) respectively (Kaplan 1991, Klein 1991, Brodeur 2009). N-Myc suppresses the expression of TrkA and TrkC, demonstrated using RNA interference technology to silence N-

Myc and resulting in up-regulation of both TrkA and TrkC (Nara 2007). N-Myc also up- regulates the expression of Bmi1t protein, leading to repression of kinase family member 1B beta (KIF1Bb) and tumour suppressor in lung cancer 1 (TSLC1) gene transcription thus maintaining an undifferentiated cell status (Ochiai 2010).

Another important contributor to cell differentiation is Transglutaminase 2 (TG2), a multifunctional enzyme that catalyses transamidation and multimerisation of proteins (Folk

1977). TG2 is involved in both intra- and extra-cellular processes. It has been demonstrated that N-Myc blocks TG2 gene transcription by recruiting HDAC1 to Sp1-binding sites at the

TG2 gene core promoter (Fesus 2002), and that N-Myc mediated repression of TG2 is essential to inhibit neuronal differentiation in N-Myc amplified neuroblastoma (Chiba 2004).

N-Myc also prevents neuronal differentiation by repressing transcription of the CDKL5 gene through interaction with Sp1 at Sp1-binding sites of the CDKL5 gene promoter (Valli 2012).

N-Myc overexpression correlates to the induction of angiogenesis, where new capillaries are generated from pre-existing vessels, a key pathological feature of aggressive solid tumours that ensures the continuous flow of nutrients and the ability to metastasise.

Angiogenesis is a key pathological marker in neuroblastoma with the overexpression of N-

Myc inducing angiogenesis (Katzenstein 2000, Ribatti 2002). N-Myc has been demonstrated to both transcriptionally activate angiogenic factors and repress angiogenic inhibitors (Kang

2008).

The first angiogenesis factor found to be repressed by N-Myc was Activin-A, which exhibited anti-angiogenic properties from non-N-Myc amplified neuroblastoma cell culture medium (Fotsis 1999, Breit S 2000). A similar strategy was used to identify IL-6 as another

24 important anti-angiogenic factor repressed by N-Myc (Hatzi 2002). Overexpression of the N-

Myc downstream regulated gene (NDRG) family has also been correlated with angiogenesis in different cancers. NDGR1 enhanced expression of angiogenic growth factors through the

IL-1a-driven signalling pathway, resulting in tumour angiogenesis in gastric cancer cells

(Murakami Y 2013). NDRG4, which is down regulated by N-Myc was also shown to promote angiogenesis in meningioma cells in vitro (Kotipatruni 2012).

N-Myc overexpression has also been found in other cancer types, often of embryonic or neuroendocrine origin, such as glioblastoma (Hui AB 2001), medulloblastoma (Rouah

1989), retinoblastoma (Lee 1984), rhabdomyosarcoma (Dias 1990), small cell lung cancer

(Nau 1986), Wilm’s tumour (Nisen 1986) and ovarian cancer (Helland 2011). N-Myc overexpression may play important roles in these cancer types, with N-Myc over-expression contributing to the initiation, progression and maintenance of medulloblastoma in mice, suggesting a central role for N-Myc in the pathogenesis of medulloblastoma (Lee 1993,

Swartling 2010).

1.4.3 Strategies to target Myc

Research on the Myc family has suggested that Myc is an attractive target for cancer therapy. However, therapeutically targeting Myc protein specifically has been challenging due to Myc sharing common protein binding domains with other transcription factors. As there is no Myc specific motif to use as a molecular target, treatments affecting Myc could potentially affect the myriad of downstream Myc gene pathways leading to off target effects

(Cheung 2013).

There are five mechanistically different classes of therapeutic agents targeting Myc.

The first approach of Myc targeting focused on blocking the interaction between Myc and

MAX to disrupt their protein interaction (Berg 2002). This approach is challenging due to the lack of a recognisable target motif for Myc inhibitor design, however the preclinical testing of two compounds (10058-F4 and Mycro3) have highlighted the clinical potential of this approach (Prochownik 2010). Inhibition of the Myc/MAX interaction by compound 10058-

F4 induced cell cycle arrest, neuronal differentiation and apoptosis in MYCN amplified neuroblastoma cell lines and significantly prolonged survival in TH-MYCN mice (Zirath

2013).

The second approach to Myc inhibition targets the transcription of MYCN through the inhibition of BET bromodomain proteins such as Brd4, which modulate gene transcription and recruit transcription factors to Myc gene promoters (Delmore 2011). In multiple myeloma and other cancers, Brd3 and Brd4 bromodomain proteins have been demonstrated to be regulatory factors for Myc gene transcription (Wu 2007). It has emerged that ligands which exhibit size and shape which are complementary with BET bromodomains competitively bind with BET acetyl-lysine recognition pockets, displacing transcription factors and down-regulating the transcription of Myc and Myc dependent genes (Mertz

2011).

The third approach to inhibit Myc targets the interactions between Myc and transcription factors such as AURKA, CDK1, CDK2 and CHK1. For example, CHK1 is an important kinase in DNA repair and is modulated by Myc (Ferrao 2012). Studies have shown increased levels of CHK1 mRNA expression in MYCN amplified neuroblastoma (Cole 2011).

CHK1 inhibitors have been explored in combination with inhibitors targeting Wee1, a

26 proteinase kinase that regulates G2 checkpoint response to DNA damage. Combination treatments of CHK1 and Wee1 inhibitors in neuroblastoma displayed synergy in reducing neuroblastoma cell growth in vitro and in neuroblastoma xenografts in vivo (Russell 2013).

CHK1 and CDK protein inhibitors have shown highly selective and potent anti-cancer effects, and are currently in early phase clinical trial for various adult cancers (Chu 2008,

Walton 2012, Thompson 2013).

The fourth approach involves targeting proteins that stabilise Myc protein. Candidates include phosphatidylinositol 3 kinase (PI3K), mammalian target of rapamycin (mTOR) and

Auraora A kinase (AURKA). Activation of these pathways correlates with aggressive stage neuroblastoma tumours and MYCN amplification (Segerström 2011). Inhibition of the PI3K pathways lead to decreased N-Myc protein but not mRNA expression, and results in induction of cell growth inhibition and apoptosis (Chesler 2006). AURKA is highly overexpressed in many human tumours. It binds to and stabilises N-Myc, leading to neuroblastoma development through interference with cell-cycle exit of neuronal blasts (Otto

2009). AURKA-mediated stabilisation of N-Myc protein is the target of AURKA inhibitors such as AT9283 and MLN8237, which disrupt the AURKA/N-Myc complex promoting the degradation of N-Myc protein mediated by the Fbxm7 ubiquitin ligase (Brockmann 2013).

The AURKA inhibitor, MLN8237 demonstrated promising anti-cancer effects against neuroblastoma in a pre-clinical study (Maris 2010), and has entered Phase I clinical trials

(Mossé 2012).

The last approach to Myc inhibition aims to regulate Myc protein expression or modify Myc protein function. Retinoids were discovered to reduce N-Myc expression and consequently induce neuronal differentiation in neuroblastoma cells. A retinoic acid

27 analogue, 13-cis retinoic acid was developed and confirmed to significantly prolong survival in high risk neuroblastoma patients (Matthay 1999). 13-cis retinoic acid was shown to significantly downregulate N-Myc expression, inducing cell cycle arrest and stimulating neuronal differentiation, and is currently in clinical use for treatment of high risk neuroblastoma (Matthay 2009, Park 2009).

1.5 Myc downstream targets

Both c-Myc and N-Myc exert their cell cycle regulation and tumour cell proliferation effects by regulating gene transcription of downstream targets. Studies have shown that primary human tumours with Myc deregulation have a distinct gene expression profile compared to tumours with normal Myc levels (Berwanger 2002, Lossos 2002). These findings indicate that Myc exerts its tumourigenic effects through specific downstream target genes such as the E2F family and ODC1(Meyer 2008).

1.5.1 The Elongation 2 Factor (E2F) Family

Elongation 2 Factor (E2F) was originally identified as a cellular transcription factor recruited by adenovirus type 5 leading to transcription initiation from the viral E2 promoter

(Kovesdi 1986). Subsequently E2F proteins were also found to play a critical role in cell cycle regulation of uninfected mammalian cells by modulating target gene transcription. E2F binding sites are found at the promoter regions of several cell cycle regulation genes including c-Myc, DHR2, Cdc2, and retinoblastoma protein (Rb) (Blake 1989, Hiebert 1989,

Dalton 1992). Binding of E2F to Rb resulted in a transcription suppressor complex targeting genes with E2F binding sites at their gene promoters.

Human E2F1 was first identified by probing expression libraries with recombinant Rb

(Helin 1992). E2F1 was found to bind to the same E2F binding sites and to Rb. A E2F-1

DNA binding domain motif was used to screen a cDNA library, identifying two homologs;

E2F2 and E2F3a (Ivey-Hoyle 1993, Lees 1993). Currently the E2F protein family consists of

E2F1, E2F2, E2F3a, E2F3b, E2F4, E2F5, E2F6, E2F7 and E2F8 (de Bruin 2003, Maiti

2005).

1.5.2 E2F gene function

E2F1, E2F2 and E2F3a all share several protein motifs, including a DNA binding domain, a transactivation domain, a cyclin binding domain, a dimerization domain allowing interaction with transcription factor proteins, and a tumour suppressor protein association domain embedded within the transactivation domain (Ivey-Hoyle 1993). These three E2F proteins are considered ‘activators’ that are heavily expressed in late G1 phase and associate with E2F regulated promoters during the G1/S transition inducing quiescent cells to divide

(Sherr 2000, Dick 2013). E2F3b and E2F4-8 act as suppressors, and are found associated with E2F bind elements on E2F target genes during G0 (Takahashi 2000). Early work showed E2F1 over-expression induced apoptosis in vitro (Wu 1994, Kowalik 1995), but

E2F2 and E2F3 did not kill REF52 fibroblasts (DeGregori 1997). Later it was shown that all three induced apoptosis of RAT1 fibroblasts, with E2F1 being the most potent (Moroni

2001).

All E2F proteins play a critical role in cell cycle regulation of mammalian cells by modulating target gene transcription via interacting with Rb (Dyson 1998). Rb negatively

29 regulates E2F transcriptional activity by binding to and masking the transactivation domain of E2F (Helin 1993). When bound to E2F, Rb also directly represses E2F target genes by recruiting chromatin remodelling complexes and histone-modifying enzymes to E2F target gene promoters. The N-terminal domains of both c-Myc and N-Myc have been shown to bind to Rb, the tumour suppressor protein (Rustgi 1991). The activation of G1 phase Cdks leads to phosphorylation of the Rb protein, resulting in the release of E2F and the expression of E2F target genes (Nevins 2001). The Elongation 2 Factor proteins, E2F1, E2F2 and E2F3a transcriptionally activate target genes involved in DNA synthesis during the transition from

G1 to S phase (Müller , Su 2015).

Evidence of a cross talk effect was shown between E2F proteins, with E2F3a induced apoptosis in the pituitary gland (Denchi 2005) and in skin cells (Paulson 2006) requiring

E2F1 up-regulation. These studies raised doubts about the ability of E2F2 and E2F3a to induce apoptosis independently of E2F1.

Evidence has emerged of the different roles of E2F2 and E2F3a. E2F2-/- mice, endothelial specific E2F3a knockout mice, and their littermates with wild type E2F2 and

E2F3a expression with hind limb ischemic injuries were compared. It was found that in endothelial cells E2F2 impaired, while E2F3a promoted the angiogenic response to peripheral ischemic injuries by influencing the cell cycle progression (Zhou 2013). The E2F1 cone photoreceptor apoptosis pathway was found to be p53 and p73 independent (DeGregori

2006). However E2F2 was found to induce p53 dependant cone photoreceptor apoptosis independent of E2F1 and E2F3a (Chen D 2013). This shows that the E2F2 activated apoptosis pathway is distinct from that of E2F1.

The activating members of the E2F protein family, E2F1, E2F2 and E2F3 activate

MYCN promoter in transient transfections in an E2F site dependent manner. A 200bp region upstream of the MYCN transcription start sites is highly conserved in eukaryotes and controls basal promoter activity (Hiller 1991). Dimethyl sulfate in vivo footprinting of this region revealed sites that were either hypersensitive or protected from modification by dimethyl sulfate in N-Myc overexpressing neuroblastoma cells. However, these sites were absent in cells without N-Myc overexpression (Lutz 1997). One of the protected regions corresponds to two inversely oriented and overlapping E2F binging sites indicating that the E2F family of transcription factors regulates N-Myc expression in neuroblastoma (Strieder 2003). E2F1,

E2F2 and E2F3 bind to the MYCN promoter in vivo in N-Myc overexpressing neuroblastoma cells and inhibition of E2F activity via overexpression of p16INK4A reduced N-Myc mRNA levels. Several signals known to downregulate N-Myc expression require E2F binding sites or are associated with changes in the binding of E2F proteins to the MYCN promoter (Strieder

2003). This data points to a potential feedback loop linking E2F and N-Myc for the maintenance of N-Myc expression in high risk neuroblastoma.

1.5.3 Ornithine decarboxylase 1

Ornithine decarboxylase 1 (ODC1) is a pyridoxial phosphate dependent amino acid decarboxylase consisting of a homodimer with two active sites made up of residues from both subunits (Coleman 1994). It is responsible for catalysing the first step in the polyamine biosynthesis pathway, where ornithine is converted to putrescine, which is then converted to the polyamines spermidine and spermine (Gerner 2004). In mammals ODC1 is essential for polyamine synthesis de novo so the ODC1 gene is highly regulated by a range of growth factors and the ODC1 protein has a relatively high turnover rate compared to other enzymes.

This protein degradation is brought about by the 26S proteasome, but does not require ubiquitination. Instead ODC1 forms a non-covalent bond with a protein called antizyme, which then directs it to the proteasome (Kahana 2005). Proteasome degradation of ODC1 begins at the COOH terminus with a deletion of the 37bp forming the COOH terminus rendering ODC1 stable even in the presence of antizyme (Persson 2003). A novel pathway for ODC1 degradation during oxidative stress is regulated by NAD(P)H quinine oxidoreductase (NQO1) and does not require the COOH-terminal domain. NQO1 binds to

ODC1 and stabilises it. This interaction can be disrupted by dicoumarol, sensitizing ODC1 to degradation by the 26 S proteasome, independent of antizyme and ubiquitin (Asher 2005).

Antizyme was first shown to be a non-competitive inhibitor of ODC1 that was synthesized in response to increased polyamine levels (Heller 1976). It increases the degradation of ODC1 by enhancing its interaction with the proteasome but does not increase the rate of proteasomal processing (Zhang 2003). Antizyme itself is not broken down by

ODC1 and will be released from the ODC1-antizyme complex to breakdown more ODC1

(Gandre 2002). Further control of ODC1 expression is exerted at the translation step with excess polyamines reducing the translation of ODC1 mRNA. Ribosomal protein synthesis is known to require polyamines but is inhibited by their excess (Shantz 1999), and ODC1 is particularly sensitive to this although the mechanism remains unknown.

ODC1 is also controlled at the transcriptional level by a variety of factors. The ODC1 gene promoter region contains multiple sequences that allow protein binding, such as a

TATA box, cAMP response element, AP-1 and AP-2 sites, CAAT and LSF motifs, GC-rich

Sp1 binding sites, and two E-boxes (Zhao 2001, Qin 2004). The two E-boxes, consisting of the canonical CACGTG sequence allow binding of the MYC/MAX transcription factor to the

ODC1 gene promoter, with mRNA transcription activated when MYC levels are elevated.

The E-box sites are occupied by the inactive Mnt/MAX complex in quiescent cells, resulting in low levels of ODC1 transcription (Packham 1997, Nilsson 2004).

DNA polymorphisms in close proximity to the E-boxes have been found to affect

MYC/MAX binding, most notably a single nucleotide polymorphism (SNP) of an A instead of G located 317 base pairs downstream of the transcription start site in intron 1 (Guo 2000).

This position is between the two E-boxes, 5 base pairs before the second E-box and increases

MYC/MAX binding leading to increased ODC1 promoter activity. The major G allele is present in 76% of Caucasians, and the minor A allele is present in the remaining 24%

(O'Brien 2004). This SNP is a genetic marker for prostate and colon cancer risk by increasing

ODC1 mRNA transcription (Martinez 2003, Evageliou 2009).

1.6 Histone methylation and de-methylation

Chromatin is the highly organised structure of DNA and histone proteins within the cell nucleus. It plays an essential role by condensing DNA and controlling gene expression.

Euchromatin are regions of chromatin that appear lightly coloured when stained by G- banding, and contain the majority of actively transcribed genes (Jenuwein T 2001).

Heterochromatin is darkly coloured when stained and contains densely packed DNA with genes typically not expressed (Sexton 2007). Heterochromatin can be further classified as either facultative or constitutive. Facultative heterochromatin is found near the telomere, centromere and also the inactivated X chromosome of female mammals. Genes located here still retain the ability to be transcribed, but are typically silent (Trojer 2007). In contrast,

33 constitutive heterochromatin is not transcribed and these regions form structural components such as the centromere (Dimitri P 2009).

Histones are basic charged proteins that form the foundational building blocks of chromatin. They contain 146bp of DNA wrapped around a histone octamer in 2 superhelical turns (Kornberg 1999). This histone octamer consists of 2 H2A-H2B dimers and a H3-H4 tetramer. These 4 'core' histones (H2A, H2B, H3 and H4) are relatively similar in structure and are highly evolutionarily conserved, with all 4 featuring a 'helix turn helix turn helix' motif that facilitates dimerisation (Luger 1997). There are also variant histone subunits:

H2A.X, H2A.Z, macro.H2A, H3.3 and CENP-A (Kouzarides 2007, Talbert 2010). These histone units and subunits perform specialised roles, with their gene expression and incorporation into the chromatin structure typically occurring outside the S-phase

(Kouzarides 2007, Talbert 2010).

Each histone subunit has an N-terminus tail, which sits outside the main nucleosome core and is the location of the majority of post-translational modifications, including methylation, acetylation, phosphorylation and ubiquitination (Gurley 1978, Strahl 2000).

Changes to the pattern of post translational modifications present on the N-terminal tails of histone proteins result in changes to chromatin packaging and DNA accessibility, thus post- transcriptional modifications regulate a range of cellular processes including DNA replication, repair, transcriptional gene expression and the mitotic chromosome condensation phase (Kouzarides 2007, Talbert 2010).

1.6.1 Histone methylation

Post-translational histone modifications have become a focus of research due to their ability to regulate gene transcription by modifying chromatin structure. Histone modifications can interact and crosstalk, forming a complex web of gene regulation called the histone code

(Strahl 2000). The four well-known histone modifications are acetylation (Parbin 2014), methylation (Leung 2014), phosphorylation (Pérez-Cadahía 2010) and ubiquitination (Cao

2012).

Histone methylation was the first post-translational histone modification identified by radio-labelling cell extracts (Allfrey V. G. 1964). It involves the attachment of a methyl group to a basic amino residue: lysine (K) (Murray 1964) or arginine (R) (Byvoet 1972). Of these two, lysine residue methylation is the best studied, with lysine undergoing mono, di-, or tri-methylated on the ԑ–amine group.

Methyl groups are generally thought to have slowest turnover rate out of the four common histone modifications. However, methylation marks on different lysine residues have been shown to have differing turnover rates (Zee 2010). Mass spectrometry has identified many lysine residues in core histone proteins to be dynamically methylated and demethylated (Young 2010). The most comprehensively studied lysine methylation sites are located on the N-terminal tail (H3K4, H3K9, H3K27, H3K36 and H4K20) and in the histone core (H3K79) (Zhang 2001, Greer 2012).

Cross talk among different histone lysine residue methylation modulates gene transcription with H3K9 methylation overlapping with H3K4 de-methylation in regions of

35 heterochromatin; and euchromatic regions show the opposite with H3K4 methylated and

H3K9 demethylated (Noma 2001).

H3K4 mono-methylation (H3K4me), di-methylation (H3K4me2), tri-methylation

(H3K4me3), H3K36me3, H3K79me, H3K79me2, H3K9me and H3K27me are linked to gene transcription (Bernstein 2002, Bannister 2005, Barski 2007, Mohan 2010). Differing levels of methylation at the same histone position has been shown to have different effects with

H3K9me2, H3K9me3, H3K27me2, H3K27me3 and H4K20me linked to gene repression

(Cao 2002, Nishioka 2002, Snowden 2002). In addition, methylation at H3K9me2 and

H4K20me2 are linked to DNA damage responses (Sanders 2004, Faucher 2010). The different types and sites of histone methylation regulate gene transcription by being recognised by chromatin effector molecules, leading to recruitment of cofactors that change the chromatin state (Greer 2012).

1.6.2 Histone methyltransferases

Histone methyltransferases target either lysine or arginine residues, with the majority belonging to the SET domain methyltransferase protein superfamily (Wang 2001, Nishioka

2002, Schultz 2002, Dillon 2005). SET domain methytransferases function by transferring a methyl group from S-adenosyl-L-methionine (SAM) to the amino group of a lysine residue on the histone or non-histone protein, leaving a methylated lysine residue and S-adeno-L- homocysteine (SAH) as a by-product (Dillon 2005). Further methyl groups are added progressively to achieve di- and tri- methylation.

Many histone methyltransferases have been shown to be involved in cancer and neurological diseases (Bae 2014, Hua 2014). One of the most well studied is Enhancer of

Zest Homologue 2 (EZH2), a histone lysine methyltransferase belonging to the the Polycomb group (PcG) protein family. EZH2 is the active catalystic subunit of the Polycomb Repressive

Complex 2 (PRC2), targeting histone H3 lysine 27 for mono, di and tri-methylation(Cao

2002). PRC2 is involved in a range of normal cellular processes, including cellular differentiation and stem-cell plasticity. Up-regulation of EZH2 is a marker for aggressive prostate and breast cancers (Kleer 2003, Xu 2012). Recurrent gain of function mutations have been identified at the Y641, A677 and A687 residues within the EZH2 catalytic domain

(Sneeringer 2010, Majer 2012). These mutations alter the substrate specificity of EZH2, increasing the conversion of H3K27 di-methylation to tri-methylation, while wild type EZH2 preferentially converts H3K79 mono-methylation to di-methylation. EZH2 gain of function mutations have been found in follicular lymphoma and Germinal Centre B-Cell like Diffuse

Large B-Cell lymphoma (Wigle 2011). A range of small molecular EZH2 inhibitors have been synthesized and shown good in vitro and in vivo efficacy against lymphoma cells

(Knutson 2012, McCabe 2012, Konze 2013).

1.6.3 Histone demethylases

Histone methylation was originally believed to be irreversible (Byvoet 1972) until the discovery of Lysine Specific Demethylase 1 (LSD1), also known as KDM1A. Since 2004, a total of 15 lysine demethylases have been discovered (Højfeldt 2013), and have been separated into 2 families: the LSD family consisting of the amine-oxidase related enzymes

LSD1 and LSD2, and the Jumonji C-terminal (JMJC) domain containing family (Yamane

2006, Allis 2007).

LSD1 converts Histone 3 Lysine 4 mono- and di-methylation into unmethylated

H3K4 (Shi 2004). The catalytic mechanism of LSD family demethylases requires a lone electron pair on the lysine ε-nitrogen atom, meaning it cannot demethylate tri-methylated lysines (Forneris 2005). LSD1 has been shown to require the removal of acetylated lysine residues on Histone 3 before H3K4me2 demethylation could efficiently occur, due to LSD1 being a part of a complex that included histone deacetylases (Forneris 2005, Forneris 2006).

The JMJC protein domain has been found in 31 human proteins with 17 of these demonstrating demethylase activity (Kooistra 2012). The enzymatic mechanism of JMJC demethylases involves two cofactors, Fe(II) and 2-oxoglutarate binding to the JMJC domain and reacting with dioxygen to form an active oxoferryl intermediate that hydroxylates the ζ- methyl groups of the methylated lysine substrate (McDonough 2010). This results in an unstable lysyl hemiaminal that breaks down to release methyl groups from nitrogen. This mechanism allows the mono-, di- and tri-de-methylated lysine. Currently there are no known histone lysine demethylases that target H4K20 and H3K79 methyl marks.

1.7 The H3K79 histone methyltransferase, Disruptor of telomeric silencing 1-like

(DOT1L)

Disruptor of telomeric silencing 1 (DOT1) was first identified through a genetic screen for proteins whose over-expression would lead to impaired telomeric silencing in yeast

(Singer 1998). The DOT1 homolog gene, DOT1-like (DOT1L), has been found in a range of species, including drosophila (List 2009), protozoa (Jansen 2006) and mammals (Jones 2008) with mouse and human versions of DOT1L sharing an 88% similarity at the amino acid level

(Feng 2002, Min 2003).

DOT1L is the only known histone methyltransferase that targets the histone H3 lysine

79 (H3K79) position, located on the nucleosome surface instead of the N-terminal tail where epigenetic modifications normally occur (Feng 2002, Min 2003). It adds methyl groups in a non-progressive manner, requiring DOT1L to dissociate and reassociate to H3K79 as it adds methyl groups to generate mono-methylation (H3K79me), di-methylation (H3K79me2) and tri-methylation (H3K79me3).

1.7.1 DOT1L protein structure

Instead of a SET domain, DOT1L has an AdoMet binding motif similar to arginine and DNA methyltransferases (Sawada 2004). It is currently the only known non-SET histone methyltransferase protein (Feng 2002, Min 2003). This makes DOT1L a key target for specific therapeutic treatments, with several small molecular inhibitors developed and one currently in clinical trials (Daigle 2011, Anglin 2013, Daigle 2013).

Study of the crystal structure of DOT1L has shown that the AdoMet binding pocket must be near a lysine binding channel and the C-terminus of the catalytic domain in order for nucleosome binding and enzymatic activity to occur (Min 2003). This active site of DOT1L closely resembles that of catechol-O-methyltransferases and L-isoaspartyl methyltransferases, which is highly conserved in eukaryotic organisms (Min 2003).

Histone Octamer Histone Octamer

SAM SAH

Figure 1.1. The mechanism of DOT1L catalysing histone H3K79 methylation with its substrate, S-adenosyl-L-methionine (SAM).

A methylated H3K79 residue and S-adeno-L-homocysteine (SAH) are produced. DOT1L then dissociates, with additional methyl groups then able to be added in a sequential manner.

1.7.2 Regulatory functions of DOT1L

The distribution of all three forms of H3K79 methylation on human histones has been studied using mass spectrometry, demonstrating that H3K79me is the most abundant and correlates with the fraction of histone H3 modified by acetylation (Zhang 2004). This suggests H3K79 methylation enrichment at active gene transcription sites. Further studies focusing on individual genes in mammalian cells have correlated H3K79me2 with transcriptional activation (Schübeler 2004, Morillon 2005). Subsequent quantitative- chromatin immunoprecipitation (q-ChIP) studies of H3K79 methylation across the human genome reveal that H3K79me3 is present at higher levels in silent gene regions in comparison to active regions, linking it to gene repression (Barski 2007). This demonstrates the complex regulatory effects of DOT1L on a wide range of functions in eukaryotic organisms, with H3K79me and H3K79me2 associated with active gene transcription and

H3K79me3 with gene repression in human cells.

DOT1L inhibition may enhance reprogramming in a broad range of cell types by facilitating the silencing of lineage-specific programs of gene expression. Inhibition of

DOT1L by shRNA or a small molecule accelerates reprogramming, significantly increases the yield of pluripotent stem cell (iPSCs) colonies, and substitutes for KLF4 and c-Myc

(Onder 2012). Genome wide analysis of H3K79me2 distribution revealed that DOT1L inhibition leads to loss of H3K79me2 among genes normally repressed in the pluripotent state and fibroblast specific genes associated with the epithelial to mesenchymal transition

(Onder 2012).

Methylation of H3K79, mediated by DOT1 and DOT1L, has been implicated in transcriptional elongation and cell cycle regulation. Nearly 90% of histone H3 in

Saccharomyces cerevisiae (S. cerevisiae) bears H3K79me, H3K79me2 or H3K79me3. The level of H3K79me2 fluctuates between different stages of the cell cycle in S. cerevisiae, with a low level of H3K79me2 at the G1 phase, gradually increasing at the S phase and peaking at the G2/M phase, while H3K79me3 remains constant throughout the cell cycle (Schulze 2009).

S. cerevisiae mutants arrested at G1 and G2/M phases showed increased H3K79me3 levels demonstrating H3K79 methylation levels increase progressively over time in arrested cells

(De Vos 2011).

H3K79me2 associates to gene promoter and coding regions during transcriptional activation of hepatic genes in G0/G1 enriched human liver carcinoma cells (Kouskouti 2005).

The mechanism responsible for targeted DOT1L binding and consequent H3K79 methylation of actively transcribed genes involves DOT1L binding to the phosphorylated C-terminal domain of actively transcribing RNA polymerase II (RNAP II) (Kim 2012). Similarly human liver carcinoma cancer cells arrested in G2/M phases have increased H3K79 methylation levels compared to G0/G1 enriched cells , showing that this methylation mark was generated independently of gene transcription in the S phase (Kouskouti 2005).

H3K79 methylation has been shown to control sexual differentiation in silk worms

(Bombyx mori), with higher H3K79me2 levels on the insulin-like growth factor II mRNA- binding protein (Imp) gene promoter in males than females (Suzuki 2014). RNAi-mediated depletion of DOT1L results in a total abolishment of male-specific Imp (Suzuki 2014).

H3K79 methylation levels in Drosophila correlate to transcriptional activity

(Schübeler 2004). The Drosophila ortholog of DOT1, grappa (gpp), has been identified as a dominant suppressor of pair-dependant silencing, necessary for the maintenance phase of

Bithorax complex expression (Shanower 2005). H3K79 methylation expression during embryogenesis is conserved in Drosophila, mouse, rat and human spermatids and also independent of H3K4 and H3K9 methylation (Dottermusch-Heidel 2014). During chromatin reorganisation in spermatids, H3K79 methylation is accompanied by H4 hyperacetylation and may be a prerequisite for proper histone to protamine transition (Dottermusch-Heidel 2014).

DOT1L serves further developmental roles in a wide range of species. It is directly regulated during tadpole development in the model system Xenopus tropicalis by thyroid hormone receptor, which binds to a thyroid hormone response element in the DOT1L gene promoter region (Matsuura 2012). This triggers a positive feedback loop with liganded thyroid hormone receptor recruiting histone modifying coactivator complexes that enhance

H3K79 methylation and target gene transcription. Embryos treated with DOT1L specific transcription activator-like effector nuclease show low H3K79 methylation and experience growth difficulties as tadpoles, ultimately leading to tadpole mortality (Wen 2014).

DOT1L has been shown as a crucial regulator of early mammalian haematopoiesis by regulating the steady state levels of GATA2, a growth factor essential for early erythropoiesis

(Tsai 1994), and PU.1, a transcription factor that inhibits erythropoiesis and promotes myelopoiesis (Back 2004). DOT1L knockout mice display reduced GATA2 and increased

PU.1 levels and early embryonic death due to anaemia, indicating that DOT1L is essential for embryonic development and prenatal haematopoiesis (Feng 2010). Conditional DOT1L targeting strategies show DOT1L also playing a role in adult haematopoiesis maintenance, with DOT1L deletion in mice resulting in pancytopenia and failure of hematopoietic homeostasis (Jo 2011, Nguyen 2011). These findings demonstrate that DOT1L plays a role in

43 gene transcription, somatic reprogramming, cell cycle regulation, development and haematopoiesis, via H3K79 methylation.

1.7.3 The role of DOT1L in DNA damage response

DOT1 was identified in a screen of radiation sensitive yeast mutants for DNA damage checkpoint defects, with DOT1 yeast mutants exposed to ionizing radiation becoming defective at the G1 and intra-S phase checkpoint (Wysocki 2005). Checkpoint mediated arrest at the pachytene stage in dmc1 and zip1 S. cerevisiae mutants was also shown to be DOT1- dependent, with loss of DOT1 leading to continued meiosis and the generation of unviable cells (San-Segundo 2000). DOT1 was also shown to be required for cell cycle arrest in response to double stranded DNA breaks (San-Segundo 2000).

In mouse embryonic fibroblast cells treated with UV, DOT1L reduction leads to UV hypersensitivity and reduced recovery of transcription initiation. DOT1L was found to promote an open chromatin structure to reactivate RNA Pol II transcription after DNA damage and was not involved in the nuclear excision repair pathway (Oksenych 2013). Thus,

DOT1-mediated H3K79 methylation may plays a critical role in DNA damage signalling (De

Vos 2011).

In the human osteosarcoma cell line U2OS, in vitro experiments established that

53BP1 bound most efficiently to H3K20me2 (Botuyan 2006). This was confirmed using a stable DOT1L knockdown DT-40 chicken model system, which showed that H3K79 methylation was not critical for 53BP1 recruitment to DNA damage sites (FitzGerald 2011).

However, using U2OS cells, H3K79me2 was shown to be an alternate pathway of 53BP1

44 recruitment in response to DNA damage during the G1 and G2/M cell cycle phases, when

H3K20me2 levels dropped (Wakeman 2012). In addition, suppression of DOT1L inhibited recruitment of the double-stranded DNA break repair protein 53BP1 to sites of DNA damage in 293T cells (Huyen 2004). Thus both H3K79 and H3K20 methylation are capable of 53BP1 recruitment in response to DNA damage repair, with each methylation covering different stages of the cell cycle.

1.7.4 DOT1L and mixed lineage leukaemia

In humans, DOT1L is involved in the oncogenesis of several leukaemia subtypes, mostly characterised by chromosomal translocations involving the mixed lineage leukaemia

(MLL) gene. MLL chromosomal translocations involving the cytogenetic band 11q23 produce a wide array of fusion proteins associated with Acute Lymophoblastic Leukaemia

(ALL), Acute Myeloid Leukaemia (AML) and Mixed Lineage Leukaemia (Ziemin-van der

Poel 1991, Dimartino 1999, Biondi 2000).

DOT1L has been found in protein complexes with RNA PII, factors AF4, AF6, AF9,

AF10 or ENL (Bitoun 2007, Krivtsov 2008, Nguyen 2011, Deshpande 2013), all known to be involved in chromosomal translocation-induced fusion with the MLL protein. DOT1L and

AF10 have been isolated from yeast and mammalian two-hybrid assays as binding partners of

ENL, which is a MLL fusion partner with transactivation abilities and known to associate with AF4 (Okada 2005, Zeisig 2005). AF4 stimulates kinase elongation by P-TEFb and interacts with AF9 and AF10 to recruit DOT1L to the Pol II elongation complex at ectopic loci, resulting in aberrant gene expression and contributing to MLL leukaemogenesis (Bitoun

2007, Barry 2010). The MLL-AF6 fusion protein requires H3K79 methylation for the

45 maintenance of MLL-AF6 target oncogenic gene expression, with gene expression analysis and ChIP-sequencing finding high levels of H3K79me2 at MLL target gene promoters

(Deshpande 2013). Abnormally high levels of H3K79 methylation on MLL target gene promoters in MLL leukaemia cells are indicative of aberrant DOT1L activity in these leukaemia cells due to MLL fusion oncoproteins recruiting DOT1L, causing overexpression of MLL target genes (Deshpande 2012). This has further been shown with inducible expression of the MLL-ENL fusion gene activating H3K79me2 on MLL target genes, while inhibiting DOT1L binding leads to the MLL-ENL fusion gene losing its transforming ability

(Okada 2005).

A notable family of genes dysregulated in leukaemia is the homeobox (HOX) gene family, which is highly expressed in multipotent haematopoietic stem cells (HSCs) but down- regulated once the HSCs have become differentiated (Buske 2002, Thorsteinsdottir 2002).

Epigenetic regulation of HOX loci are modulated by the MLL protein which introduces the

H3K4me3 histone mark, resulting in HOX transcriptional activation (Milne 2002). DOT1L-

AF10 interaction activates HOXA9 gene transcription and plays an important part in MLL-

AF10-mediated leukaemogenesis. In addition, DOT1L contributes to clathrin assembly lymphoid myeloid leukaemia protein (CALM)-AF10-mediated leukaemic transformation by preventing nuclear export of CALM-AF10 and by up-regulating HOXA5 gene expression through H3K79 methylation (Okada 2006). Consequently inhibiting DOT1L results in suppression of MLL-AF10 and CALM–AF10 mediated transformation by down-regulating leukaemogenic genes such as HOXA and Meis1 (Chen 2013).

H3K79 methylation by DOT1L is also crucial for the expression of critical MLL-AF4 target oncogenes such as HOXA in human MLL-AF4 leukaemia cells (Krivtsov 2008). In

46 experiments with conditional DOT1L knockout mice, H3K79me2 has been found to drive

MLL-AF9 fusion gene-mediated leukaemogenesis, and DOT1L is required for up-regulation of HOXA and Meis1 gene expression and consequent initiation and maintenance of MLL-

AF9-induced leukaemogenesis in vitro and in vivo (Nguyen 2011). A 10 amino acid region of human DOT1L (865-874) has been identified as the AF9/ENL binding site, with alanine scanning mutagenesis analysis showing that four conserved hydrophobic residues within the binding site are essential for interactions with the C-terminal binding domain of AF9/ENL

(Shen 2013). However, other MLL cell lines do not require DOT1L for oncogenic transformation (Jo 2011), illustrating a crucial role for DOT1L in leukaemogenesis with specific oncogenes.

Figure 1.2. Model of possible MLL-AF9 and DOT1L-mediated gene transcription mechanism in MLL-driven leukaemia.

(A) SUV39H1 and SIRT1 increase H3K9 methylation and decrease H3K9 acetylation, preventing MLL-AF9 and Elongation Assisting Proteins (EAP) complex binding to gene promoters. (B) DOT1L inhibits SIRT1 and SUV39H1 chromatin localization, thereby maintaining an open chromatin state with elevated H3K9 acetylation and H3K79 methylation and minimal H3K9 methylation at MLL fusion protein target gene promoters. MLL-AF9 forms a protein complex with DOT1L, recognises elevated H3K9 acetylation via its YEATS domain, and recruits the EAP complex containing RNA Pol II and other transcription factors at MLL fusion protein target gene promoters, leading to transcriptional activation.

1.7.5 The role of DOT1L in other cancers

The complex regulatory role of DOT1L in MLL-driven leukaemia and physiologically normal eukaryotic organisms has led to interest in its possible function in various other cancer types. RNAi-mediated depletion of DOT1L in A549 and NCI-H1299 lung cancer cells results in chromosomal mis-segregation, cell-cycle arrest at the G1 phase and senescence (Kim 2012). Overexpression of DOT1L reverses these RNAi-mediated phenotype changes in lung cancer cells.

DOT1L increases the tumorigenic potential of colorectal cancer cells by inducing

NANOG, SOX2 and Pou5F1 gene expression (Kryczek 2014). High DOT1L gene expression and consequently increased H3K79me2 levels are predictors of poor patient survival

(Kryczek 2014), indicating DOT1L having a tumorigenic role in colorectal cancer.

DOT1L has also been recently linked to breast cancer with a study of a genomic database of over 1000 patient samples showing that higher levels of DOT1L expression correlated with breast cancer compared to normal breast tissues (Zhang 2014). In addition, high DOT1L levels in approximately 50% breast cancer tissues correlated with approximately 20 pro-proliferative genes from the PAM50 gene set (Zhang 2014), further suggesting a role for DOT1L in breast cancer.

Chromatin immunoprecipitation assays have linked H3K4 and H3K79 methylation, and H3 acetylation to the ability of the c-Myc transcription factor to recognise and bind to target gene promoters (Guccione 2006). H3K4me2, H3K4me3 and H3K79me2 are generally associated with transcription machinery (Kim 2005), and these methylation marks were shown to precede and be independent of c-MYC binding at target gene promoters. This

50 suggests that H3K79 methylation is a critical histone modification for regulating cell proliferation and a novel mark for a wide range of cancer types.

1.8 Jumonji domain-containing protein 6

The Jumonji domain-containing protein 6 (JMJD6) alternatively known as PTDSR or

PSR, is a member of the superfamily of non-haem iron(II) and 2-oxoglutarate (2OG)- dependent oxygenases, featuring the Jumonji C (JmjC) domain (Hausinger 2004, Loenarz

2008). Mammalian 2OG-oxygenases catalyse hydroxylations, resulting in stable alcohol products and N-methyl demethylation reactions (Loenarz 2008).

Mammalian 2OG-oxygenases play an important developmental role in higher animals with the Jumonji C domain being conserved in proteins from bacteria to eukaryotes (Ge

2012). However, the enzymatic properties of JMJD6 have been the subject of considerable debate (Böttger 2015). JMJD6 has also recently linked with poor prognosis in breast, colon and lung cancers (Zhang 2013, Wang 2014, Poulard 2015).

1.8.1 JMJD6 protein structure

JMJD6 has a JmjC domain (residues Pro141 to Gln286 of human JMJD6), which is conserved in proteins from eukaryotes to bacteria (Ge 2012), making it a member of a widely distributed metalloenzyme family characterized by the presence of a distorted double- stranded β-helix (DSBH) fold (Clissold 2001). In addition to its JmjC domain, human JMJD6 contains other motifs conserved in predicted JMJD6 proteins in animals from mammals to cnidarians. These include three apparent nuclear localization signals (NLSs) (Pro141 to Lys145,

Lys167 to Pro171 and Arg373 to Arg378 in human JMJD6), an AT hook (Lys300 to Ser309)

(Clissold 2001), a putative sumoylation site (Leu316 to Glu319) (Hahn 2008) and a polyserine domain.

JMJD6 like other mammalian 2OG oxygenases, catalyses hydroxylation reactions, resulting in stable alcohol products. N-methyl demethylation reactions occur during the initial hydroxylation. The common core protein structural fold of all 2OG oxygenases comprises a

DSBH fold surrounded by characteristic secondary structure elements (Aik W 2012). This

DSBH fold forms a barrel-type structure with two β-sheets, which support highly conserved binding motifs for Fe(II) and 2OG (Clifton 2006, McDonough 2010). The metal is most commonly bound by a HXD/E(X)nH motif. In reported 2OG oxygenase crystal structures, the

2OG C-5 carboxylate is bound by a basic (Lys/Arg) and at least one alcohol residue (Aik W

2012). The substrates of 2OG oxygenases are known to include both proteins and nucleic acids, and smaller molecules, including amino acid derivatives and lipids (Hausinger 2004).

The 2OG oxygenases were first identified as prolyl and lysyl hydroxylases involved in collagen biosynthesis and have been found to play many other important roles in animals including in epigenetic regulation, hypoxia sensing, fatty acid metabolism and DNA repair

(Loenarz 2011).

1.8.2 The enzymatic functions of JMJD6

JMJD6 plays an important developmental role in higher animals with initial reports identifying JMJD6 as a phosphatidylserine receptor responsible for engulfment of apoptotic cells (Fadok VA 2000). However, subsequent studies have questioned whether it is a true phosphatidylserine receptor, finding that JMJD6 does not directly function in the clearance of apoptotic cells (Wolf 2007).

JMJD6 was subsequently assigned a role in catalysing N-methyl-arginine residue demethylation on the N-terminus of the human histones H3 and H4 (Chang 2007). It was proposed that JMJD6 played a role in epigenetic regulation by catalysing demethylation of histone H3R2 and H4R3. A H4R3 methylation specific antibody was incubated with bulk histones with or without recombinant JMJD6 and also after overexpression of V5-tagged

JMJD6 in Hela cells, showing evidence of JMJD6 catalysed demethylase activity. The demethylation reaction catalysed by JMJD6 was reported to be dependent on and stimulated by Fe(II), 2OG and ascorbate as an iron-binding JMJD6 mutant did not show any demethylase activity. Mass spectrometry analysis of arginine-methylated peptide sequences of histones H4 an H3 was conducted after incubation with recombinant JMJD6, showing further evidence of 2OG oxygenase activity. H3R2 mono-methylation and H4R3 mono- methylation antibodies were used for immunoprecipitation, leaving the possibility of off- target effects from the antibodies used (Chang 2007). Further evidence of JMJD6 mediated demethylase activity was reported with JMJD6 found to target H4R3me2 and the methyl-cap of 7SK snRNA, however H3R2 demethylation was not detected (Liu W. 2013). JMJD6 has

53 also been reported to demethylate R260 in the transcription factor Erα, however only antibody generated evidence was reported (Poulard 2014). Mass spectrometry analysis of histone H4 peptides incubated with JMJD6 also showed evidence of oxidation on two lysine residues

(H4K5 and H4K8), indicating possible lysine hydroxylation on histone peptides catalysed by

JMJD6 (Chang 2007).

The initial report of JMJD6 histone arginine demethylase activity has been challenged in multiple reports (Webby 2009, Boeckel 2011, Unoki 2013, Wang 2014). Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry analysis of histone H3 and H4 fragment peptides have failed to detect JMJD6 arginine demethylase activity, however lysine hydroxylation of histones was observed (Webby 2009, Han 2012, Unoki 2013). The arginine demethylation status of H4R3 did not change when JMJD6 was knocked down in endothelial cells (Boeckel 2011). Comparisons of lysine methylation at H3K4, H3K9, H3K27, H3K36 and H4K20 in wild type and JMJD6 depleted mouse embryonic fibroblasts found no obvious role for JMJD6 in histone lysine demethylation (Chang 2007).

The splicing factor, U2AF65 was found to undergo post-translational lysyl-5- hydroxylation catalysed by JMJD6 (Webby 2009). This demonstrated a role for JMJD6 in epigenetic regulation of RNA splicing. Lysyl hydroxylation is a well-characterised post- transcriptional modification in proteins with collagenous domains that are catalysed by

FE(II)- and 2OG dependent oxygenases in the endoplasmic reticulum (Markolovic 2015).

However, JMJD6 is predominantly localized to the nucleus (Cikala 2004, Webby 2009). The lysine hydroxylation catalytic ability of JMJD6 was confirmed by the finding that JMJD6 cataylses autohydroxylation of internal lysine residues (Mantri 2012). Recombinant JMJD6

54 was found to undergo self-hydroxylation on K111 and K167 and was also identified by mass spectrometry analysis on endogenous JMJD6 purified from HeLa cells. The mechanism of

JMJD6 self-hydroxylation was shown to be identical to the substrate hydroxylation, via hydroxylation of lysine residues at an unactivated carbon in the lysl side chain (Mantri 2012).

The hydroxylation of lysines in histone peptides catalysed by JMJD6 was confirmed in vitro by comparing histone modifications in whole embryos of wild type and JMJD6 knockout mice at embryonic day 14.5 (Unoki 2013). In conclusion, JMJD6 has been clearly identified as a 2OG oxygenase. However, the histone H3R2 and H4R3 demethylase function of JMJD6 is still in question due to conflicting reports (Böttger 2015).

1.8.3 The biological functions of JMJD6

Multiple biological functions of JMJD6 have been suggested. The activity of JMJD6 towards the splicing factor U2AF65 indicate a role for JMJD6 in pre-mRNA splice modulation (Webby 2009, Barman-Aksözen 2013, Heim 2014). Knockdown of JMJD6 in

HeLa cells increased alternate splicing of a α-tropomyosin minigene construct (Webby 2009).

An alternate spliced transcript of JMJD6 has been shown to be enriched in the nucleoli and to interact with nucleolar proteins (Wolf 2013). JMJD6 was also shown to play a role in alternative pre-mRNA splicing in human umbilical vein endothelial cells and mice (Boeckel

2011). The JMJD6 homologue in C. elegans, PSR-1 has been reported to be involved in the regulation of axonal fusion of posterior lateral mechanosensory neurons (Neumann 2015).

The potential activity of JMJD6 on histone substrates indicate a possible function in transcriptional regulation (Chang 2007, Unoki 2013).

The interaction between JMJD6 with Brd4 has also connected JMJD6 with transcriptional pause release (Liu W. 2013). Promoter proximal pause of Pol II is a critical regulatory event that occurs prior to Pol II transcription initiation of a large gene set

(Adelman 2012). Brd4 is a bromodomain-containing DNA binding protein, belonging to the bromo- and extra-terminal (BET) domain family of proteins (Devaiah 2013). Brd4 has been identified as a component of multiprotein complexes and is a potential cancer treatment target for acute myeloid leukemia (Hewings 2013). Brd4-dependent JMJD6 recruitment to long range anti-pause enhancers leads to demethylation of H4R3me2, which is read directly by

7SK snRNA (Liu W. 2013). JMJD6 also demethylated 7SK snRNA leading to release of the

7SK snRNA/HEXIM inhibitory complex. This interaction between JMJD6 and Brd4 with the

P-TEFb complex leads to its activation and transcriptional pause release (Liu W. 2013).

1.8.4 The role of JMJD6 in cancer

JMJD6 has been linked with poor prognosis in breast, colon and lung cancers (Zhang

2013, Wang 2014, Poulard 2015). High JMJD6 mRNA and protein expression correlated to poor patient prognosis in 154 lung adenocarinoma patients (Zhang 2013). JMJD6 was also shown to be expressed in breast cancer tumours associated with the worst outcomes, such as

ER- and basal-like, Claudin-low, Her2-enriched, and ER+ Luminal B (Lee 2012).

Knockdown of JMJD6 in breast cancer cell lines resulted in suppressed cell proliferation but not apoptosis, and conversely JMJD6 overexpression increased cell growth (Lee 2012).

These findings were confirmed with tissue microarray immunohistochemical staining analysis of 133 breast cancer patient tumours, indicating that JMJD6 was highly expressed in

56 aggressive breast cancer tumours and high JMJD6 expression was associated with poor disease free patient survival (Poulard 2015).

The effect of JMJD6 expression on cancer cell growth may be due to its interaction with the p53 oncoprotein. JMJD6 protein physically associated with p53 in HCT116 cells and hydroylates p53, leading to p53 de-acetylation in vitro and in vivo (Wang 2014). This hydroxylation of p53 promotes the association of p53 with the p53 negative regulator,

MDMX, leading to repression of p53-mediated target gene expression (Wang 2014).

Depletion of JMJD6 enhanced p53 transcriptional activity, resulting in G1 cell cycle arrest, promoting apoptosis and sensitizing cells to DNA damaging agent induced death.

Knockdown of JMJD6 repressed p53-dependent colon cancer cell proliferation and tumourigenesis in vivo (Wang 2014). Immunohistochemical staining showed that JMJD6 protein was higher in patient colon adenocarcinoma samples compared to adjacent normal tissue. Microarray analysis of 90 colon carcinoma patient samples found positive correlations between JMJD6 expression and colon cancer aggressiveness indicators; depth of invasion, lymph node metastasis and advanced tumour node metastasis. High JMJD6 protein was also associated with poor differentiation. Cox regression analysis showed that high JMJD6 expression was associated with shorter survival times, however high JMJD6 expression was not a statistically significant independent risk factor for colon adenocarcinoma (Wang 2014).

1.9 Cancer therapies targeting epigenetic markers

Treatment of cancer typically involves chemotherapy and/or radiotherapy. However, these treatments are both non-specific and damaging to normal cells, resulting in numerous side-effects (Evans 2001). Finding biomarkers able to predict cancer chemotherapy response would help both clinicians and patients to choose better medication and treatment regimes, potentially leading to personalised cancer therapy.

Epigenetic modifications play a crucial role in regulating normal cells, and aberrant epigenetic modifications play an important role in driving tumourigenesis (Sharma 2010).

The relatively reversible character of epigenetic modifications, in contrast to genetic changes, has resulted in the development of therapeutic strategies targeting various epigenetic modifications.

1.9.1 Cancer treatments targeting DNA methylation

DNA methylation is the most extensively studied epigenetic mark and has been found to play an important role in genomic imprinting, X-chromosome inactivation and silencing of retrotransposons, repetitive elements and tissue specific genes (Smith 2013). Methylation of mammalian genomic DNA is catalysed by DNA methyltransferases (DNMTs). DNMTs 1,

3A and 3B coordinate mRNA expression in normal tissues and overexpression in tumours

(Robertson 1999). The expression levels of these DNMTs are elevated in cancers of the colon, prostate, breast, liver and in leukemia marking these DNMTs as potential anti-cancer targets (el-Deiry 1991, Patra 2002, Girault 2003, Oh 2007).

5-azacytidine (5-AC, Vidaza) and 5-aza-2′-deoxycytidine (5-AZA-CdR, Decitabine) were synthesized in 1964 and characterised as global DNA methyltransferase inhibitors that incorporate into DNA to inhibit DNA methylation (Christman 2002). Clinical trials on patients with haematological malignancies lead to FDA approval of 5-azacytidine and 5-aza-

2′-deoxycytidine for treatment of myelodysplastic syndrome (Silverman 2002, Issa 2004,

Rüter 2006). Both of these DNA methyltransferase inhibitors have also showed efficacy against AML (Kantarjian 2012, Lübbert 2012). Cell cycle associated genes epigenetically silenced in colorectal cancer and AML cells were induced synergistically by the combination of DNA methyltransferase inhibitors and histone deacetylase inhibitors (HDACs) leading to clinical trials investigating this drug combination (Cameron 1999, Gore 2006).

1.9.2 Histone deacetylase (HDAC) inhibitors

Histone acetylation levels correlate to transcriptional activation of genes and is catalysed by histone acetyltransferases (HATs) and histone deacetylases (HDACs) (Jenuwein

2001). In normal cells, the balanced activities of HATs and HDACs regulate cellular proliferation and differentiation, however hypoacetylation of histones is considered a hallmark of cancerous cells (Krämer 2001).

HDAC inhibitors are a group of small molecular inhibitors that target HDACs by inhibiting their deacetylase activity and have proven to be promising anticancer agents in cancer therapy. HDAC inhibitors cause the accumulation of acetylated histones and non- histone proteins that are involved in the regulation of gene expression, cell proliferation, cell migration and cell death (Marks 2010, West 2014).

Multiple HDAC inhibitors have displayed potent anticancer effects in vivo and in vitro, and undergone further clinical development in recent years (Slingerland 2014). HDAC inhibitors exert anticancer effects mainly through induction of cell cycle arrest, DNA damage, inhibition of angiogenesis and induction of apoptosis (Marks 2010, Khan 2012,

Kaushik 2015). HDAC inhibitors induce cell cycle arrest at G1 phase by inducing p21, a cycline dependent kinase inhibitor that is essential for regulation of G1 progression.

Induction of p21 results in Rb dephosphorylation with subsequent effects on E2F transcriptional activity (Rosato 2005, Zhao 2005). HDAC inhibitors have also been shown to induce G2/M arrest to escape cell death in normal cells, a possible mechanism for selective induction of cell death in tumour cells only (Khan 2012).

Histone deacetylase inhibitors exert anticancer effects mechanistically by inducing accumulation of reactive oxygen species, resulting in DNA damage and ultimately apoptosis

(Ruefli 2001, Ungerstedt 2005). HDAC inhibitors have been consistently shown to induce accumulation of the phosphorylated form of H2XA, a marker of in tumour cells (Pilch 2003).

Genes involved in DNA repair, such as RAD51, BRCA1, BRCA 2 and Ku70 are also downregulated by HDAC inhibitors (Munshi 2005, Frew 2009).

Despite this research, there is still uncertainty about the mechanism that HDAC inhibitors use to induce cell death as they have been shown to upregulate both death receptors and ligands in tumour cells, but not in normal cells (Nebbioso 2005). HDAC inhibitors cause cell death through activation of mitochondrial and death receptor pathways (Marks 2005,

Carew 2008). HDAC inhibitors downregulate pro-survival proteins, such as Bax, Bmf, Bik and Bim (Kroemer 2007), and upregulate pro-apoptotic proteins, such as Bcl-2, Bcl-X and

Mcl-1 (Jiang 2004), leading to induction of the mitochondrial apoptosis pathway (Nakata

2004, Insinga 2005). The death receptor pathway is initiated by the binding of death receptors such as Fas and TNF-1 to their ligands, which activates caspase 8 and caspase 10, with consequent activation of caspase 3 (Jiang 2004).

The first HDAC inhibitor discovered was Trichostatin A (TSA) and was found to cause histone hyperacetylation and inhibit cell proliferation at nanomolar concentrations, but its high toxicity prevented therapeutic use (Dokmanovic 2007). Other synthetic HDAC inhibitors derived from hydroxamic acid such as Panobinostat and SAHA (suberoyanilide hydroxamic, Vorinostat) have improved therapeutic profiles. SAHA and romidepsin are the most extensively studied HDAC inhibitors and have been approved by the FDA for treatment of cutaneous T-cell lymphoma in clinics (Garcia-Manero 2008, Piekarz 2009).

1.9.3 EZH2 histone methyltransferase inhibitors

The EZH2 protein has been a drug target due to its role in epigenetic regulation of gene expression, as it is a part of the polycomb repressive complex 2 and mediates tri- methylation of H3K27, which is predominately associated with transcriptional repression

(Cao 2002). The first EZH2 inhibitor, DZNap functioned by indirect inhibition of S- adenosylhomocysteine hydrolase (SAH) causing degradation of EZH2 protein and other members of the PCR2 complex such as SUZ12 and EED (Tan 2007). This caused downstream H3K27 demethylation. DZNep displayed promising results in vitro including cell cycle inhibition and apoptosis in leukemia cell lines (Zhou 2011), however the specificity of the drug was questioned when it was shown to deplete multiple histone methylation marks

(Miranda 2009).

Novartis developed an EzH2 inhibitor, EI1 that functioned by competitively binding to the SAM substrate binding domain. It was shown to reduce H3K27 methylation and reactivate target genes, without depleting EZH2 levels (Qi 2012). EI1 effectively reduced

H3K27 methylation in both wild type and mutant EZH2 B-cell lymphoma cell lines, but cell growth inhibition was only observed in the mutant cell line (Qi 2012).

Epizyme also developed an EZH2 inhibitor, EPZ005687 that worked via SAM competition. It was demonstrated to be 500 fold more selective to EZH2 compared to a panel of 15 different methyltransferases and selectively killed lymphoma cells harbouring EZH2 activating mutations (Knutson 2012). Another EZH2 inhibitor, EPZ-6438 was shown to induce apoptosis and differentiation in malignant rhabdoid tumours cells with SMARCB1 inactivating mutations (Knutson 2013). It also decreased tumour progression in a mouse xenograft model (Knutson 2013) and has entered phase1 and 2 clinical trials for patients with non-Hodgkin’s lymphoma harbouring activating EZH2 mutations.

1.9.4 DOT1L histone methyltransferase inhibitors

Aberrant H3K79 methylation mediated by DOT1L is associated with various types of aggressive MLL fusion gene-driven leukaemia, with P-TEFb, ENL, AF4, AF6 AF9 and

AF10 proteins involved in recruiting DOT1L to the RNA PII complex. H3K79me2 has been shown to be critical to MLL target gene expression with loss of H3K79me2 leading to loss of tumorigenicity in MLL-driven leukaemia. In addition, DOT1L promotes cell cycle progression in lung cancer cells and is associated with poor patient prognosis in colorectal cancer (Kim 2012, Kryczek 2014). These observations raise the possibility of DOT1L playing a major role in other forms of cancer and will be a subject for future inquiry.

DOT1L is a promising target due to it being the only known H3K79 histone methyltransferase, its unique non-SET catalytic domain and its role in promoting and maintaining MLL leukaemogenesis (Feng 2002, Min 2003). The first DOT1L specific small molecular inhibitor was EPZ004777, designed by Epizyme using a traditional ligand-based approach based on the DOT1L substrate SAM and the product SAH (Daigle 2011).

EPZ004777 displayed specificity against DOT1L with little reactivity against a panel of eight other histone methyltransferases. Modifications to EPZ00477 lead to the synthesis of

EPZ5676 (Daigle 2013) and SGC0946 (Yu 2012).

SGC0946 features an additional bromine atom at position 7 targeting a hydrophobic cleft present in DOT1L to improve the DOT1L inhibitor’s binding affinity (Yu 2012).

Another novel DOT1L inhibitor, SYC-522, was synthesized based on the structure of SAH with additional urea group, showing specificity for DOT1L when tested against three representative histone methytransferases: PRMT1, PRMT4 and SUV39H1 (Anglin 2012).

These four DOT1L specific small molecular inhibitors are designed to occupy the SAM binding pocket, inducing DOT1L conformational changes and leading to the opening of a hydrophobic pocket outside of the SAM binding domain (Daigle 2013).

Figure 1.3. Current small molecular DOT1L inhibitors

Chemical structures of DOT1L inhibitors. (A) DOT1L catalyses histone H3K79 methylation by transferring a methyl group from its substrate S-adenosyl-L-methionine (SAM) to the amino group of a lysine residue on the histone. A methylated H3K79 residue and S-adeno-L- homocysteine (SAH) are produced, and DOT1L then dissociates. Additional methyl groups are added in a sequential and similar manner. (B) Small molecular DOT1L inhibitors:

EPZ004777, EPZ5676, SGC0946 and SYC-522. All are based on SAH backbone and target the SAM binding pocket of DOT1L.

1.9.5 Anti-cancer efficacy of DOT1L inhibitors

The anti-cancer efficacy of allosteric DOT1L inhibitors has been test in vitro and in vivo. The first reported DOT1L inhibitor, EPZ004777 demonstrated an IC50 of 400±100 pM to inhibit DOT1L enzymatic activity in a biochemical radionucleotide assay (Daigle 2011).

Treatment with EPZ004777 caused apoptosis in MLL-rearranged leukaemia cells in vitro and blocked leukaemia progression in mice by suppressing the expression of HOXA cluster genes and Meis1 (Daigle 2011). MLL-AF6 transformed mouse bone marrow cells also demonstrated a dose-dependent reduction in H3K79me2 and a reduction in cell number when treated with 10 µM EPZ004777 for 10 days (Deshpande 2013). Flow cytometry analyses of

DNA content and Annexin V staining showed that DOT1L inhibition reduced the number of

MLL-AF6 transformed cells at the S-phase, and increased apoptotic cell death (Deshpande

2013). In addition, when administered by subcutaneously implanted osmotic pumps for 14 days, treatment with EPZ00477 in immunodeficient mice xenografted with MV4-11 acute myeloid leukemia cells resulted in a dose-dependent increase in mouse survival (Daigle

2011). Pre-treatment of mice with EPZ004777 considerably decreased the in vivo spleen- colony-forming ability of MLL-AF10 or CALM-AF10 transformed bone marrow cells

(Daigle 2011).

In a biochemical radionucleotide assay, EPZ5676 demonstrated a superior enzyme inhibition Ki value of ≤0.08 Nm compared to EPZ004777. EPZ5676 had an IC50 of 3nM and

5nM in MV4-11 and HL60 leukaemia cells, respectively (Daigle 2013), and demonstrated synergistic anticancer effects when used in combination with cytarabine and daunorubicin to treat MOLM-13 and MV4-11 MLL-rearrangement leukaemia cells lines (Klaus 2014).

Continuous intravenous treatment of MV4-11 xenograft bearing rats with EPZ5676 for 21

66 days led to dose-dependent leukemia regression. A dosage of 70mg/kg resulted in complete regression (Daigle 2013).

While the IC50 of SGC0946 to inhibit DOT1L enzymatic activity was 300 pM in a biochemical radionucleotide assay, the IC50 of SGC0946 in inhibiting MCF10A mammary epithelial cell viability increased to 8.8 ± 1.6 nM, still representing a significant improvement over EPZ004777, which exhibited an IC50 of 84±20nM (Yu 2012). Treatment of MLL- rearranged MV4-11and THP1 leukemia cells with the other DOT1L inhibitor SYC-522 led to cell cycle arrest and cell differentiation, and treatment of primary MLL-rearranged AML cells resulted in up to 50% decrease in colony formation and promotion of monocytic differentiation (Anglin 2012). SYC-522 was also tested in combination with existing chemotherapeutics: mitoxantrone, etoposide or cytarabine. Pretreatment with SYC-522 for 3 or 6 days sensitized primary MLL-rearranged leukamemia cells to treatment with all three chemotherapy agents (Liu 2014).

DOT1L inhibitors have also demonstrated anticancer effects against solid tumor cells.

SYC-522 and EPZ004777 induce differentiation and inhibit proliferation, self-renewal and metastatic potential in DOT1L overexpressing breast cancer MDA-MB231 estrogen receptor negative (ER-), BT549 (ER-) and MCF-7 (ER+) cells (Zhang 2014).

Currently all reported DOT1L inhibitors have the common substructure of adenosine, making them competitive to the DOT1L enzyme substrate SAM and resulting in overall poor pharmacokinetic properties (Daigle 2011, Anglin 2013). Further improvements in the metabolic stability of DOT1L inhibitors are required for in vivo use.

The unique structural features of DOT1L have made it an emerging drug target with several allosteric small molecular inhibitors showing selective inhibitory effects and low IC50 concentrations in vitro. Further chemical modifications to the first small molecular DOT1L inhibitor, EPZ004777, have led to the generation of EPZ5676 with improvements in metabolic stability and anticancer efficacy. Moreover, small molecular DOT1L inhibitors have shown synergy when used in combination with existing chemotherapeutics and a

DOT1L inhibitor, EPZ5676 is currently in Phase 1 clinical trials in leukemia patients.

A limiting factor in DOT1L inhibitor discovery has been the complex biochemical assays necessary to determine loss of H3K79 methylation. Two new assays involving nanoparticle proximity and fluorescence polarisation respectively have been created for future DOT1L inhibitor screening and lead optimisation (Yi 2015).

An alternative strategy for targeting DOT1L in MLL would be to target the DOT1L binding sites of the MLL-fusion proteins (Shen 2013). Targeting these MLL-AF9 and

AF9/ENL binding sites in DOT1L could potentially result in fewer adverse effects than the current approach of targeting DOT1L enzymatic activity. Inhibitors targeting these binding sites could also have improved pharmacokinetic properties compared to existing DOT1L inhibitors based on SAH. Thus future DOT1L inhibitors have the potential to deliver better patient outcomes in treating MLL leukemia and potentially other forms of cancers where

H3K79 methylation dis-regulation is present.

1.10 Hypothesis

The central hypothesis of this study is that epigenetic modification enzymes, DOT1L and JMJD6 are regulators of the function of N-Myc and overexpression of c-Myc and N-

Myc, which are critical drivers of tumourigenesis and tumour progression in neuroblastoma.

Specifically:

1. The H3K79 histone methyltransferase, DOT1L is crucial for N-Myc modulated

transcriptional activation and tumour progression by forming a protein complex

with N-Myc at the N-Myc target gene promoters and inducing H3K79

methylation.

2. The histone demethylase and lysyl hydroxylase, JMJD6 modulates c-Myc and N-

Myc gene transcription, leading to promotion of neuroblastoma cell proliferation

and tumour progression.

1.10.1 Project Aims

To address these hypotheses, this study will investigate the effects of the epigenetic modification enzymes, DOT1L and JMJD6 on the regulation of N-Myc function as well as

N-Myc and c-Myc gene expression in neuroblastoma and identify potential drug targets for neuroblastoma treatment. Thus the project aims to:

1) Demonstrate N-Myc up-regulation of DOT1L and investigate its mechanism.

2) Investigate the role of DOT1L-mediated H3K79 methylation in N-Myc mediated

gene transcription.

3) Investigate the role of DOT1L in neuroblastoma cell proliferation and tumour

progression.

4) Investigate whether a high level of DOT1L gene expression in human

neuroblastoma tissues is an independent marker for poor patient survival.

5) Demonstrate JMJD6 regulation of c-Myc and N-Myc gene transcription.

6) Investigate the role of JMJD6 in promoting neuroblastoma cell proliferation and

tumour progression.

7) Investigate whether a high level of JMJD6 gene expression in human

neuroblastoma tissues is an independent marker for poor patient survival.

Chapter 2: Materials and methods

2.1 Mammalian cell culture

All cells were maintained in medium purchased from ThermoFisher Scientific

(Waltham, MA, USA). All media was supplemented with 10% fetal calf serum (FCS) and

o maintained at 37 C in an incubator with 5% CO2 (Steri-Cult incubator 200, Forma Scientific

Incorporation, Marietta, OH, USA). Human neuroblastoma BE(2)-C, CHP-134, SK-N-AS and HEK-293 cells were cultured in Dulbecco's modified Eagle's medium supplemented with

10% fetal calf serum. Kelly cells were grown in RPMI 1640 medium supplemented with 10% fetal calf serum. Cells were tested to be mycoplasma free using the MycoAlert® Mycoplasma

Detection Kit (Lonza, Rockland Inc, USA) on a quarterly basis. The identity of all cell lines was verified by small tandem repeat profiling conducted at Garvan Institute or Cellbank

Australia in 2015.

2.1.1 Passaging of mammalian cells

Cells were routinely cultured in T-75 flasks to between 60% and 80% confluency. For passaging, the cell culture media was removed and cells were washed with 4mLs of warm

PBS, followed by a two minute incubation with 2mLs of trypsin EDTA solution at 37oC for enzymatic dissociation of the adherent cells from the flask surface. Upon cell detachment, media containing FCS was added to deactivate the trypsin. Cells were then centrifuged for 3 minutes at 15000 x g at room temperature. The cell pellet was resuspended in 10mLs of fresh

71 media. The media containing the cells were then transferred to a fresh flask with cell culture media at dilutions of 1:5, 1:10 or 1:20 and stored in the incubator.

2.1.2 Cryopreservation and thawing of cells

Cells were harvested and centrifuged at 15000 x g for 3 minutes. The cell pellet was then suspended in media containing 10% DMSO (Sigma, St Louis, MO, USA) and 30% FCS.

Aliquots of 1mL cell media were transferred into a cryovial for storage at -80 oC for up to one week then moved to liquid nitrogen tanks for long term storage.

Frozen vials of cells were thawed as needed. The cryovial was warmed in a 37oC water bath for 3-5 minutes until the cell suspension was totally defrosted and then transferred to a falcon tube containing 10mL of warm media. This tube was centrifuged at 15000 x g for

3 minutes at room temperature. The supernatant was removed and the cell pellet was suspended in the appropriate growth media and placed into T-75 flasks. The cells were passaged once before any experimental use.

2.1.3 Cell count

Cells were counted prior to each experiment so that the appropriate cell number was used. A small aliquot of cells (20L) was mixed with the same volume of trypan blue 0.4% solution and mounted on a haemocytometer. The number of alive cells was counted under an inverted Zeiss microscope using the 10X objective. A cell suspension was made containing the required number of cells for each specific experiment.

2.2 Transfection

2.2.1 Transient siRNA transfection

Specific gene knockdown was achieved using siRNAs directed specifically against N-

Myc, E2F2, DOT1L, c-Myc and JMJD6 genes. Allstars negative control siRNA (scrambled) was used to account for potential non-specific effects of siRNAs. All siRNAs were purchased from Qiagen (Hamburg, Germany) or Ambion (Austin, TX, USA). Two individual siRNAs were purchased to target any particular gene and stored at 50M stock concentrations.

Table 2.1: siRNA sequences targeting N-Myc, c-Myc, DOT1L, E2F2 and JMJD6.

siRNA target siRNA sequence (sense)

Control siRNA 5’-AACAGTCGCGTTTGCGACTGG-3’

N-Myc siRNA-1 5’-CGGACGAAGAUGACUUCUATT-3’

N-Myc siRNA-2 5’-CAGCGAGCUGAUCCUCAAATT-3’

c-Myc siRNA-1 5’-CGGUGCAGCCGUAUUUCUATT-3’

c-Myc siRNA-2 5’-GGAGGAACGAGCUAAAACGTT-3’

DOT1L siRNA-1 5’-GGCCUUCGUCGAAGCAGAATT-3’

DOT1L siRNA-2 5’-CACUAUCGACCGCACCAUATT-3’

E2F2siRNA-1 5’-GAGACGAGGGAUUAUUUCATT-3’

E2F2 siRNA-2 5’-GGGACCAGGUAGACUUUAATT-3’

JMJD6 siRNA-1 5’-UGUGAAUAGUGCCAAGAAATT-3’

JMJD6 siRNA-2 5’-UGACAGAGCCCAAGAAUGAUU-3’

Cells were transfected using Lipofectamine 2000 (Life Technologies, Carlsbad, CA) as previously described (Liu, Erriquez et al. 2014, Sun, Liu et al. 2014). The volume of siRNA and Lipofectamine varied according to the experimental setup as shown in Table 2.1.

Briefly, Lipofectamine was mixed with Opti-MEM medium (Gibo-Life Technologies,

Carlsbad, CA, USA) and incubated for 5 minutes at room temperature. It was then combined with the required number of cells and plated in a T-25 flask for protein extractions or a 96 well plate for Alamar blue assays. After eight hours, the transfection medium was removed and replaced with fresh cell culture media containing 10% FCS.

Table 2.2 Amount of siRNA and lipofectamine used for siRNA transfections.

Transfection 96 well plate 24 well plate T-25 Flask

reagent

siRNA Mixture

siRNA (L) 0.09 0.36 3

Opti-MEM (L) 25 50 500

Lipofectamine

Mixture

Lipofectamine 2000 0.25 1 10

(L)

Opti-MEM (L) 25 50 500

Total per well/flask 50 100 1000

2.2.2 Plasmid transfection

For plasmid transfections, the required cells were plated and allowed to reach a confluency of 70-80% overnight in 10cm petri dishes. The following day, the media was removed and replaced with transfection mixture containing plasmid (2μg), Lipofectamine

(50μL), Opti-MEM (750μL) and FCS free medium (5mL). This was incubated for 8 hours before the transfection media was removed and replaced with normal media containing 10%

FCS.

2.3 Alamar blue assay

Cell proliferation was examined using Alamar blue assays as previously described

(Liu T 2009). The experiment was conducted using 96 well plates, with each well holding

200μL of media. 20μL of Alamar blue (Life Technologies, Carlsbad, CA, USA) was added to each well using a multichannel pipette. Following 6 hours incubation with Alamar blue at

37oC, the plate was read on a microplate reader at 570/595 nm (VICTOR X Light

Luminescence Plate Reader, USA). Results were calculated according to the optical density absorbance units and expressed as percentage change in viable cell numbers, compared with control samples.

2.4 Reverse transcription PCR (RT-PCR)

To examine gene expression changes in the cells after siRNA mediated knockdown,

RNA was extracted and RT-PCR analysis was performed as described below.

2.4.1 RNA extraction

RNA was extracted from cells using the PureLink RNA Mini kit (Life Technologies,

Carlsbad, CA, USA) according to the manufacturer's instructions. Approximately 1x10^5 –

1x10^6 were pelleted and lysed by incubation with 350μL of lysis buffer containing 1% β- mercaptoethanol and homogenised by vortexing, followed by the addition of 350μL of 70% ethanol. All of solution was then transferred to RNAeasy mini columns, which were then placed in collection tubes. The flow-through was discarded after centrifuging at 12000 x g for

15 seconds. The column was then subjected to three washed, one with RW1 and twice with

RPE buffer. Finally, 30μL of nuclease free water was added to the column and incubated at room temperature for 1 minute, after which the column was centrifuged with the RNA eluted into the collection tube. RNA samples were quantified using a Nanodrop (ND) 1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA) and stored immediately at -

o 80 C. RNA quality was determined by the 260nm/280nm and 230nm/280nm ratios with ratios of

1.8 – 2 indicating acceptable RNA quality. If the ratios were lower than 1.8, then the RNA sample would be discarded.

2.4.2 cDNA synthesis

Synthesis of cDNA from RNA samples was carried out using M-MLV Reverse

Transcriptase (Life Technologies, Carlsbad, CA, USA). 300ng of RNA was diluted with water to a total volume of 4.67μL was mixed with 5.33μL of master mix as demonstrated in

Table 2.2, and incubated for 90 minutes at 37oC, followed by 15 minutes at 75oC. For

77 subsequent RT-PCR analysis, 20μL of water was added to the synthesized cDNA to make it up to the concentration of 10ng per μL and stored at -20 oC.

Table 2.3: The components of the cDNA master mix. All reagents were purchased from

Life Technologies.

Reagent Volume per

reaction (μL)

Buffer FS (5X) 2

DTT 0.33

dNTPs (10mM) 1

Random primers (0.1 μg/ μL) 1

Reverse Transcriptase 1

Total 5.33

2.4.3 PCR amplification and RT-PCR analysis

Quantitative RT-PCR was performed to examine the gene expression changes at mRNA level with the Applied Biosystems 7900 and SYBR Green PCR Master Mix (Life

Technologies, Carlsbad, CA, USA). Synthesized cDNA (μL) was added to RT-PCR reaction mixture containing 12.5μL of SYBR Green Master Mix, 10μM each of forward and reverse primers of the gene of interest (Table 2.3) and up to 25μL total volume of DNAase and

RNAase free water.

The reaction containing the cDNA and the mixture was initially denatured at 95oC for

6 minutes, then subjected to 20-35 cycles consisting of a denaturation step, 95oC for 45 seconds, an annealing step at 55oC for 45 seconds, extension step at 72oC for 1 minute and a final extension step of 7 minutes.

The household gene, Actin was used as a loading control and its expression was examined in every sample in the same plate. All samples were run in duplicates on a MyIQ real time detection system (BioRad, California, USA) and analysed using the MyIQ software.

The Ct value was used to calculate the relative gene expression. Target gene expression was first normalised to the Actin loading control, then normalised to the control treatment. The log fold difference was then calculated and expressed as mean ± SEM of three independent experiments.

Table 2.4: Primer sequence for RT-PCR. All primers were synthesised by Sigma

(ST Louis, MO, USA).

N-Myc F: CGACCACAAGGCCCTCAGTA

R: CAGCCTTGGTGTTGGAGGAG

DOT1L F: GCCGGTCTACGATAAACATCAC

R: CGAGCTTGAGATCCGGGATT

E2F2 F: GGCCAAGAACAACATCCAGT

R: CGTGTTCATCAGCTCCTTCA

ODC1 F: AAAGTTGGTTTTGCGGATTG

R: GGAAGCTGACACCAACAACA

JMJD6 F: CGACTGTGTCAGCAAAGAGC

R: GGAGCAGAAGAGCGAGAAC

c-Myc F: GGATTTTTTTCGGGTAGTGGAA

R: TTCCTGTTGGTGAAGCTAACGTT

Actin F: AGGCCAACCGCGAGAAG

R: ACAGCCTGGATAGCAACGTACA

2.5 Immunoblot analysis

2.5.1 Protein extraction

For the analysis of protein expression by immunoblot, cells were harvested and washed with cold PBS then with cold trypsin for 3 minutes and centrifuged at 8000 x g for 3 minutes. The cell pellet was resuspended in 1mL cold RIPA buffer made of 150mM NaCl,

50Mm Tris pH 7.5, 0.5% Sodium deoxycholate, 1% Noidet p-40 (All purchased from Sigma,

St Louis, MO, USA) and 0.1% SDS (MP Biomedicals LLC, Aurora, OH, USA) and also

0.01% 10x protease inhibitor (Sigma, St Louis, MO, USA). After 30 second vortexing and 30 minute incubation on ice, the lysed were then centrifuged at 13000 x g for 20 at 4oC. The supernatant was then transferred to a fresh eppendorf tube. The protein concentration was measured using the Bicinchoninic Acid (BCA) assay.

For the protein standard, 0, 62.5, 125, 250, 500, 1000 μg/mL concentration of bovine serum albumin was used. The protein sample was diluted 1:5 in 25μL volume, with duplicates. For the assay setup, 25μL of the standard or sample solution was added to each well in a 96 well plate, followed by the addition of 200μL BCA solution and incubated for 30 minutes at 37oC.The absorbance of the samples were read at 570nm on a Biota II plate reader

(GE Healthcare, Sydney, NSW, Australia). A standard curve was generated and used to calculate the concentration of the unknown protein samples. All experimental protein samples were equalised to 50 μg/μL and stored at -80oC until required.

2.5.2 Histone acid extraction

In order to extract histones from cells a nuclear extraction buffer consisting of 10mM

Tris-HCl, 10mM MgCl2, 25mM KCl, 1% Triton X-100, 8.6% sucrose and 1% protease inhibitor was used (Daigle 2011). Cells were trypsinised and spun down at 1300 x g for 3 minutes at 4oC, then washed to 1mL cold PBS. The cells were spun down again at 1300 x g for 3 minutes at 4oC and lysed by incubating for 5 minutes on ice with 250μL nuclear extraction buffer. The nuclei were collected by centrifuging at 600 x g for 5 minutes at 4oC and washed once with TE buffer (pH 7.4).

The supernatant was removed and the pellet was resuspended with 0.4N cold sulphuric acid for 1 hour on ice. The solution was precipitated by centrifugation at 10000 x g for 10 minutes at 4oC. The supernatant was transferred to a fresh tube with 10X volume of ice cold acetone and incubated for 2 hours at -20oC to precipitate the histones. The histones were collected by centrifuging at 10000 x g for 10 minutes at 4oC and the pellet was washed wih ice cold acetone before being air dried for 20 minutes in a biosafety cabinet. The histine pellet was resuspended in RNAase free water and quantified using the BCA assay prior to being loaded on a 15% SDS-Polyacrylamide gel.

2.5.3 Gel electrophoresis and immunoblotting

To denature the proteins, 20μL of protein was mixed with 6x loading buffer containing 20% β-Mercaptoethanol (Sigma, St Louis, MO, USA) and incubated for 5 minutes at 95oC. Gel electrophoresis was carried out in 7-10% SDS-Polyacrylamide gels. Following protein separation with electrophoresis for 2 hours at 110V the proteins were transferred onto

Hybond-C nitrocellulose membrane for 3 hours at 180 milliamps. Following the protein transfer, the membrane was blocked with 10% skim milk for an hour at room temperature or overnight at 4oC.

Membranes were then washed three times over 15 minutes in PBS-Tween-20 (PBST), consisting of 1x PBS with 0.1% Tween-20, and then incubated overnight at 4oC with a primary antibody diluted in 1% skim milk in PBST. The membranes were then washed three times with PBST over 15 minutes to wash off excess primary antibodies, and then incubated for one hour at room temperature with secondary antibodies conjugated with horseradish peroxidase in PBST with 1% skim milk in PBST. The membranes were washed three times with 1% skim milk in PBST to wash off excess secondary antibodies, and the protein bands were visualised with SuperSignal (Thermo Fisher Scientific, Waltham, MA) by incubation for 5 minutes. The membranes were sealed between two sheets of plastic and placed into an

X-ray cassette, then exposed to X-ray films which were developed and scanned. Membranes were stripped using stripping buffer, washed with PBST and re-probed with other primary antibodies. Lastly the membranes were re-probed with an anti-actin antibody as a loading control. A list of all antibodies used is presented in Table 2.4.

Table 2.5: List of all antibodies used for immunoblotting.

Target Supplier Catalogue Antibody type Primary incubation Size

gene number and dilution (kDa)

DOT1L Abcam ab64077 Rabbit 1:2000 Overnight at 185

polyclonal 4oC

E2F2 Santa Cruz sc-633 Rabbit 1:3000 1hr at RT 48

polyclonal

ODC1 Santa Cruz sc-33539 Rabbit 1:500 Overnight at 51

polyclonal 4oC

N-Myc Santa Cruz sc-53993 Mouse 1:2000 1hr at RT 49

polyclonal

JMJD6 Abcam ab135066 Rabbit 1:1000 Overnight at 46

polyclonal 4oC c-Myc Santa Cruz sc-764 Rabbit 1:500 Overnight at 57

polyclonal 4oC

H3K79me2 Abcam ab3594 Rabbit 1:1000 Overnight at 17

polyclonal 4oC

Total H3 Abcam ab1791 Rabbit 1:1000 Overnight at 15

polyclonal 4oC

Actin Sigma A3853 Mouse 1:10000 1hr at RT 37

polyclonal

2.6 Protein co-immunoprecipitation assay

In order to study protein-protein interactions between DOT1L and N-Myc, HEK293 human embryonic cells were transiently co-transfected with an N-Myc-pcDNA3.1 expression construct, together with an empty vector or Flag-DOT1L-pcDNA3.1 construct for 48 hours in

10cm cell culture dishes as previously described. Protein was extracted from the cells sonication with ice for 25 minutes, with the cells suspended in 500μL a non-denaturing lysis buffer consisting of 20mM Tris HCl pH 8, 137mM NaCl, 1% Nonidet P-40 (NP-40) and

2mM EDTA and 0.01% protease inhibitor.

This solution was spun down at 13000 x g for 20 minutes and the supernatant was extracted with 50μL frozen at -20oC to be used as input. Protein G Sepharose beads (GE

Healthcare, Little Chalfont, UK) were pre-washed with NP-40 buffer three times and resuspend 1:2 with NP-40 buffer. Each protein sample was brought up to 1mL with NP-40 and 50mL of the G beads solution was added. This tube was then incubated on a slow speed rotating wheel for 1 hour at 4oC to allow unspecific proteins to bind to the beads.

The solution was then centrifuged at 2000 x g for 1 minute at 4oC and the supernatant was moved to a new eppendorf tube where it was incubated with 2.5μg of an Anti-N-Myc mouse monoclonal antibody (Merck Millipore, Victoria, Australia) overnight at 4oC on a slow speed rotating wheel. Mouse IgG was used as a negative control.

Afterwards 8 μL of the G bead solution was added to each tube and incubated for 3 hours at 4oC on a slow speed rotating wheel to pulldown the N-Myc antibody. The tubes were spun down at 2000 x g for 1 minute at 4oC and the supernatant was discarded. The beads

85 were washed 3 times with 500μL of NP-40 buffer and resuspended in 30μL of Co-IP sampling buffer. This was heated for 10 minutes at 95oC to elute and denature the protein, then transferred onto ice for immediate immunoblotting.

2.7 Chromatin imunoprecipitation (ChIP) assay

ChIP assays were performed to examine protein and DNA interactions according to the method described in (Tian 2012) with the 17-295 Chromatin immunoprecipitation assay kit (Merck Millipore, Victoria Australia). Briefly, BE(2)-C cells were grown in a T-175 flask and harvested at 70-80% confluency. The cells were then resuspended in media with 37% formaldehyde for 10 minutes, followed by a 5 minute incubation with 1.25M glycine on a slow rotating wheel at RT. Cells were then centrifuged for 5 minutes at 4oC and washed with cold PBS, then resuspended in SDS Lysis buffer and sonicated for 1 hour to shear the DNA to 200-800 bp fragments.

The cell lysates were incubated with protein A agarose beads on a slow rotating wheel for an hour at 4oC and centrifuged to remove non-specific binding. The supernatant was incubated overnight with 5μg of either an Anti-N-Myc mouse monoclonal antibody (Merck

Millipore, Victoria, Australia), rabbit anti-H3K79me2 antibody (Abcam), rabbit or a mouse control IgG (Santa Cruz Biotech) on a slow rotating wheel at 4oC. Afterwards protein A agarose beads were added and incubated for 3 hours on a slow rotating wheel at 4oC to pull down the bound DNA with the antibody. The beads with the bound DNA were then washed with Low Salt Wash buffer, High Salt Wash buffer, LiCl Immune Complex Wash buffer and

TE was buffer according to the kit instructions. The cross linked DNA was then un-linked by an incubation overnight at 65oC with 10mM NaCl. The DNA was then purified by incubations with RNase A and Protease K, then passed through a MinElute PCR purification kit (Qiagen, USA). The purified DNA was then analysed by PCR using primer sequences designed to cover the core promoter regions of the DOT1L, ODC1 and E2F2 genes containing Myc responsive element E-Boxes or to target remote negative control regions

(Table 2.5).

Fold enrichment of the DOT1L, E2F2 and ODC1 gene core promoter regions by the anti-N-Myc or anti-H3K79me2 antibody was calculated by dividing the PCR product from the DOT1L, E2F2 and ODC1 gene core promoter region by the PCR product from the negative control region, relative to input.

Table 2.6: Primer sequences for RT-PCR analysis of ChIP

DOT1L UTR Amplicon A – F: GTGAGAGGGGGTTTCTCCAT

DOT1L UTR Amplicon A – R: TTGCTGTAGCTCCAAGTCCA

DOT1L UTR Amplicon B – F: GCTCATTGTGCTCGCTTCAC

DOT1L UTR Amplicon B – R: CCCCGACTCCCTCTTTGTAG

DOT1L UTR Amplicon C – F: CCTCCACCGTCCCTACCT

DOT1L UTR Amplicon C – R: GAGTCCAGGGTCTCCGTTC

DOT1L UTR Amplicon D – F: GAACGGAAGGGGTAACTCGT

DOT1L UTR Amplicon D – R: CCGAGTAGGAAAAGCGTGAC

E2F2 UTR Amplicon A GCTCCTTCCACTCCATTTGA

Negative control– F:

E2F2 UTR Amplicon A ACCTGGCTCCATATCCTCCT

Negative control– R:

E2F2 UTR Amplicon B – F: AGGTTCCTGGCCTTCATTTT

E2F2 UTR Amplicon B – R: CCCAGACCCAGCAGTGTATT

E2F2 UTR Amplicon C – F: ATTGTTTGGCCAGAAACCAG

E2F2 UTR Amplicon C – R: CATGGCAGATTGGATGTGAG

E2F2 UTR Amplicon D – F: TCAGAAATGGGGTTCAGGTC

E2F2 UTR Amplicon D – R: AGGGATTGGAAGCAGAGGTT

ODC1 E-box amplicon – F: GAGGAAGGGAGGGAGCGAG

ODC1 E-box amplicon – R: GAGCTGTGAAGACGGGGGC

Negative control primers – F: GAGCTTTCAGCCAGTCCAAC

Negative control primers – R: GGGACCAACTCCCATTTTCT

2.8 Establishment of neuroblastoma cell lines stably transfected with DOX-inducible shRNA constructs

The lentiviral DOX-inducible GFP-IRES-shRNA FH1tUTG construct (Herold 2008) from Dr Marco Herold (Walter and Eliza Hall Institute of Medical Research, Melbourne,

Australia) was used to generate control shRNA, JMJD6 or DOT1L shRNA expressing construct and neuroblastoma cell lines.

The DOT1L shRNA and scrambled control shRNA sequences were selected from previously published work (Onder 2012). The JMJD6 shRNA sequences were designed using

Primer3. All shRNA sequences used displayed in Table 2.6.

Each shRNA oligo was cloned into Xhol and Bsmb1 restriction sites in the FH1tUTG construct. The DOX-inducible GFP-IRES shRNA FH1tUTG construct was co-transfected into 293T cells along with viral packaging constructs: pCAG-kGP1.1R, pCAG4-RTR2 and pCAGG5-VSVG (Hanawa 2005). The viral media were collected after 24 hrs and used to infect BE(2)-C, Kelly, CHP-134 and SK-N-AS neuroblastoma cells with polybrene (Santa

Cruz). The viral media was changed three times over 72 hours. GFP-based cell sorting was used to select cells with top 5% GFP protein expression. Cells were grown to 70-80% confluency in T-75 flasks and an aliquot was frozen down. The stable cell lines treated with either control or doxycycline treatment to confirm shRNA expression using RT-PCR, immunoblot and alamar blue assays.

Table 2.7: shRNA sequences used to generate stable cell lines

Gene Mature Product ShRNA sequence Target Sense: DOT1L TCCCGAGTGTTATATTTGTGAATTTCAAGAGAATTCACAAATATAACACTC GAGTGTTATATT shRNA - 1 TGTGAAT TTTTTC

Anti-sense: TCGAGAAAAAGAGTGTTATATTTGTGAATTCTCTTGAAATTCACAAATATA ACACTC Sense: DOT1L TCCCCACCTCTGAACTTCAGAATTTCAAGAGAATTCTGAAGTTCAGAGGTG CACCTCTGAACT shRNA - 2 TCAGAAT TTTTTCTCGAG

Anti-sense: TCGAGAAAAACACCTCTGAACTTCAGAATTCTCTTGAAATTCTGAAGTTCA GAGGTG Sense: JMJD6 CGAAGCTATTAC TCCCCGAAGCTATTACCTGGTTTAATTCAAGAGATTAAACCAGGTAATAGC shRNA - 1 CTGGTTTAA TTCGTTTTTC

Anti-sense: TCGAGAAAAACGAAGCTATTACCTGGTTTAATCTCTTGAATTAAACCAGGT AATAGCTTCG Sense: JMJD6 ATGGACTCTGGA TCCCATGGACTCTGGAGCGCCTAAATTCAAGAGATTTAGGCGCTCCAGAGT shRNA - 2 GCGCCTAAA CCATTTTTTC

Anti-sense: TCGAGAAAAAATGGACTCTGGAGCGCCTAAATCTCTTGAATTTAGGCGCTC CAGAGTCCAT Sense: Scrambled GCACTACCAGA TCCCGCACTACCAGAGCTAACTCAGATAGTACTTTCAAGAGA Control GCTAACTCAGAT AGTACTATCTGAGTTAGCTCTGGTAGTGC TTTTTC shRNA AGTACT Anti-sense: TCGAGAAAAAGCACTACCAGAGCTAACTCAGATAGTACTTCTCTTGAAAGT ACTATCTGAGTTAGCTCTGGTAGTGC

2.9 In vivo mouse experiments

Animal experiments were approved by the Animal Care and Ethics Committee of

UNSW Australia, and the animals’ care was in accord with institutional guidelines. 48 female

Balb/c nude mice aged 5 to 6 weeks were injected subcutaneously while under anesthesia with either 2×106 DOX-inducible DOT1L shRNA BE(2)-C cells or 8×106 DOX-inducible

DOT1L shRNA Kelly cells suspended in 1ml of FCS free media into the right flank. For the

JMJD6 stable cell lines, 5×106 DOX-inducible JMJD6 shRNA-1 CHP-134 and 8×106 JMJD6 shRNA-2 SK-N-AS stable cells were subcutaneously injected into right flank of 48 female

Balb/c nude mice aged 5 to 6 weeks with a 1:1 ratio of cell in FCS free media and matrigel

(growth factor reduced) (In Vitro Technologies, NSW Australia).

The mice were further separated into doxycycline treatment or control treatment subgroups of 12 mice each. In the JMJD6 shRNA experiment, once tumours reached 50mm3 each mouse was moved to a treatment cage containing either doxycycline feed (600mg/kg) or control feed. Alternatively in the DOT1L shRNA experiment mice were fed with the vehicle control 10% sucrose water or DOX at 2mg/ml in 10% sucrose water when tumours reached

0.005cm3 in volume. Tumour growth was measured every two days using calipers with tumour volume calculated by (length x width x height)/2 (Monga 2000). Mice were culled once tumour volume reached 1cm3, and tumour tissue snap-frozen and analyzed by immunoblotting for protein expression.

2.10 Bioinformatics analysis of gene expression data

Results from the microarray hybridization were stored at the Peter Wills

Bioinformatics Centre (PWBC) at the Garvan Institute. The data was loaded into R package

(http://r-project.org/), followed by analysis with Bioconductor software packages

(http://www.bioconductor.org/).

The experimental data was downloaded and retrieved as Affymetrics CEL files. The raw data files were converted into a gene expression data set (gct file) for Gene Pattern software analysis, using the Gene Pattern Illumina converter tool. Background subtraction was performed to remove signals due to non-specific hybridisation. The expression data in the gct files were normalised by scale normalisation to adjust for non-biological variations between samples. The data was also log transformed prior to analysis. A cls file contained the categorical phenotype of the experimental dataset with the given sample names. The conversion and normalisation process were conducted by Dr Bing Liu from the Kid’s Cancer

Alliance.

2.11 Patient tumor sample analysis

Gene expression was examined in 88 (Versteeg dataset) (Molenaar, Koster et al.

2012) and 476 (Kocak dataset) (Oberthuer, Juraeva et al. 2010, Kocak, Ackermann et al.

2013) human neuroblastoma samples in the publically available gene expression datasets

(http://r2.amc.nl).

The mean ± standard error was calculated for each continuous variable of interest.

Differences were tested for significance using ANOVA among groups or unpaired t-tests for two groups. A probability value of 0.05 or less was considered statistical significant.

Pearson’s correlation between DOT1L and JMJD6 gene expression with N-Myc and c-Myc expression in the tumour tissues were calculated. The patient cohort was dichotomised (lo versus high gene expression) on the basis of the median value of gene expression in the cohort, and repeated using the lower and upper quartiles of gene expression. Overall survival of patients was the time of diagnosis until death or until last contact if the patient did not die.

Survival analysis was performed using GraphPad Prism 6.0 using Kaplan-Meier analysis

(Jager 2008) and comparisons of survival curves were made using two sided log-rank test.

2.12 Statistical analysis

Experiments were conducted 3 times in duplicates. Data were analysed with Prism 6 software (GraphPad) and presented as mean ± standard error. Differences were analyzed for significance using ANOVA among groups or two-sided t-test for two groups. All statistical tests were two-sided. A p value of less than 0.05 was considered statistically significant.

Correlation between DOT1L and N-Myc, ODC1 as well as E2F2 expression in human neuroblastoma tissues was analysed with Pearson’s correlation. Probability of survival was investigated according to the method of Kaplan and Meier and two-sided log-rank tests (Jager

2008). Multivariable Cox regression analyses were performed after inclusion of disease stage, age at diagnosis, MYCN amplification status and DOT1L expression levels. Probabilities of survival and hazard ratios (HRs) were provided with 95% confidence intervals.

Proportionality was confirmed by visual inspection of the plots of log(2log(S(time))) versus log(time), which were observed to remain parallel (Liu 2015).

Chapter 3: DOT1L regulates N-Myc target gene expression in neuroblastoma

3.1 Introduction

Neuroblastoma is the most commonly diagnosed extra-cranial paediatric solid tumour in early childhood, with a median diagnostic age of 17 months (Brodeur 2003, Smith 2010).

Neuroblastoma arises from neural crest cells and is characterised by a large variation in clinical behaviour, from spontaneous regression to inexorable progression despite intensive multimodal therapy (Matthay 1995). This has been attributed to molecular differences among tumours. Adverse clinical prognostic factors include age >18 months at diagnosis, structural chromosomal alterations, and amplification of the MYCN oncogene (Brodeur 2003, Tomioka

2008, Janoueix-Lerosey 2009, Maris 2010).

N-Myc is normally expressed during embryogenesis and specifically during early cell differentiation and development stages in the central nervous system, kidney, hair follicles, intestine and lungs (Dildrop 1988, Mugrauer 1988, Hirvonen 1989). N-Myc critically contributes to aggressive stage 3 and 4 neuroblastomas by directly and indirectly regulating the expression of genes involved in neuronal differentiation, malignant transformation and cell proliferation (Maris 1999).

Both N-Myc and c-Myc have been shown to form a heterodimer with MAX, and this heterodimer in turn recruits a range of co-factors that alter chromatin structure leading to

96 transcriptional modulation (Grandori 2000). The mechanism of N-Myc interactions with chromatin in MYCN amplified neuroblastoma has not been reported.

DOT1L is a unique histone methyltransferase as it is the only known histone methyltransferase that catalyses mono-methylation (me), di-methylation (me2) and tri- methylation (me3) at the H3K79 position (Feng 2002, Min 2003). The distribution of all three forms of H3K79 methylation on human histones has been studied using mass spectrometry, demonstrating that H3K79me is the most abundant and correlates with the fraction of histone

H3K79 modified by acetylation (Zhang 2004). This suggests H3K79me enrichment at active gene transcription sites. Quantitative-chromatin immunoprecipitation (q-ChIP) studies of

H3K79 methylation across the human genome reveal that H3K79me3 is present at higher levels in silent gene regions in comparison to active regions, linking H3K79me3 to gene repression, while H3K79me and H3K79me2 have been linked to gene transcription

(Schübeler 2004, Morillon 2005, Barski 2007). This demonstrates the complex regulatory role played by DOT1L in gene expression and the post-transcriptional modifications.

DOT1L is involved in the oncogenesis of several leukaemia subtypes, mostly characterised by chromosomal translocations involving the mixed lineage leukaemia (MLL) gene. DOT1L has been shown to complex with AF4, AF6, AF9, A10 and ENL, all known to be involved in chromosomal translocation-induced fusion with the MLL protein in Acute

Lymophoblastic Leukaemia (ALL), Acute Myeloid Leukaemia (AML) and Mixed Lineage

Leukaemia (Ziemin-van der Poel 1991, Dimartino 1999, Biondi 2000). DOT1L-mediated

H3K79 methylation has been demonstrated to be a distinguishing feature of MLL-AF4 acute lymphoblastic leukaemia with a critical role in maintaining MLL-AF4 driven gene expression

(Krivtsov 2008). A small molecular DOT1L inhibitor, EPZ004777 has shown decreased

97 proliferation, decreased expression of MLL-AF6 target genes and cell cycle arrest of MLL-

AF6 transformed cells (Deshpande 2013). DOT1L-mediated H3K79 methylation is responsible for maintenance of an open chromatin state around MLL-AF9 target genes

(Zeisig 2005, Nguyen 2011). This makes DOT1L dis-regulation a critical driver of leukaemogenesis in MLL-driven leukaemia.

Crucially H3K79me2 has also been reported to be crucial for c-Myc binding to target gene promoters (Guccione 2006, Martinato 2008), although whether c-Myc recruited DOT1L has not been addressed. N-Myc is structurally similar to c-Myc (Nesbit CE 1999). Here I investigated N-Myc up-regulation of DOT1L gene expression and the role of DOT1L- mediated H3K79 methylation in N-Myc amplified neuroblastoma.

3.2 Results

3.2.1 N-Myc upregulates DOT1L gene expression in neuroblastoma cells

N-Myc activates gene transcription by binding to Myc-responsive element E-Boxes at target gene promoters (Blackwell, Huang et al. 1993, Adhikary and Eilers 2005). My bioinformatics analysis revealed a non-canonical E-Box (CACGCG) -288bp upstream of

DOT1L gene transcription start site. I therefore examined whether N-Myc modulated DOT1L gene expression in the MYCN-amplified human BE(2)-C and Kelly neuroblastoma cell lines.

The cells were transfected with N-Myc siRNA-1 or N-Myc siRNA-2 which targeted different regions of the N-Myc mRNA or SCR control siRNA. RNA and protein were extracted from the cells after 48 hours. RT-PCR and immunoblot analyses showed that the N-Myc siRNAs efficiently knocked down N-Myc gene expression, and reduced DOT1L mRNA and protein expression in both N-Myc over-expressing neuroblastoma cell lines (Figure 3.1A and Figure

3.1B).

I next examined whether N-Myc over-expression up-regulated DOT1L gene expression using SHEP-tet21N cells, which were developed from N-Myc non-amplified

SHEP cells after stable transfection with a tetracycline withdrawal-inducible N-Myc expression construct (Lutz 1996), The SHEP-tet21N cells given either a vehicle control treatment, resulting in N-Myc overexpression or tetracycline treatment, causing a reduction in

N-Myc expression. RT-PCR and immunoblot analysis of N-Myc and DOT1L gene and protein expression was carried out after 72 hours of tetracycline treatment, showing increased

N-Myc and DOT1L mRNA and protein expression (Figure 3.2A and 3.2D). Taken together these results demonstrate that N-Myc up-regulates DOT1L gene expression in neuroblastoma cells.

A. c

c B E -(2 )C K E L L Y y

- o

o 1 .5

1 .5 i

r 1 .0

g x x **

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B. BE(2)-C Kelly

DOT1L

N-Myc

Actin

100

Figure 3.1. Knocking down N-Myc gene expression leads to a reduction in DOT1L mRNA and protein expression.

BE(2)-C and Kelly neuroblastoma cells were transfected with control siRNA, N-Myc siRNA-

1 or N-Myc siRNA-2 for 48 hours, followed by RT-PCR (A) and immunoblot (B) analyses of N-Myc and DOT1L expression. Error bars represent standard error. *,**,*** and **** indicate p < 0.05, 0.01, 0.001 and 0.0001 respectively.

101

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N 0 .5

R l

l 0 .0 o

o 0 F F l ) l l) l o o r m tr /m t / n g n g o o u c u c 2 2 ( e ( le l e c e ic n h n li li h c e c e y V y V c c a a tr tr e e T T

Tetracycline (2ug/ml) control Vehicle

N-Myc

DOT1L

Actin

Figure 3.2. Overexpression of N-Myc in a MYCN-non-amplified neuroblastoma cell line results in increased DOT1L mRNA and protein expression.

SHEP-Tet/21N cells were treated with tetracycline (2ug/ml) or vehicle control for 72 hours.

RT-PCR (A) and immunoblot (B) analyses were conducted for N-Myc and DOT1L expression. Error bars represent standard error. **indicate p < 0.01.

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3.2.2 N-Myc binds to a non-canonical E-box at the DOT1L gene promoter

Myc proteins exert oncogenic effects by binding to canonical and non-canconical E- boxes (Perini 2005, Murphy 2009). To examine whether N-Myc modulated DOT1L gene expression by binding to the DOT1L gene promoter, I performed chromatin immunoprecipitation (ChIP) assays with an anti-N-Myc antibody or control IgG. RT-PCR analysis was done using a set of four primers targeting the DOT1L gene promoter (Figure

3.3A).

Amplicon A is located -607bp to -775bp upstream of the DOT1L TSS. Amplicon B is located -136bp to -220bp upstream of the DOT1L TSS, near a non-canonical E-box

(CACGCG) region located -288bp upstream of the DOT1L transcription start site. Amplicons

C and D are located 128bp to 234bp and 395bp to 554bp downstream of the DOT1L TSS respectively, in the DOT1L intron 1 region. A primer set targeting a region located -4000bp up-stream of the E2F2 gene was used as a negative control.

The ChIP assays showed that N-Myc antibody immunoprecipitated the non-canonical

E-box region (Amplicon B) seven-fold higher than the negative control region (Figure 3.3B).

Amplicons A, C and D located to either side of amplicon B displayed much lower enrichment by the N-Myc antibody. This positive result for Amplicons A, C and D was most likely due to these three amplicons being within 1000bp of Amplicon B, resulting from N-Myc binding leakage from the E-box region as the DNA was sheared into fragments ranging from 200bp to 1000bp during sonication. These data demonstrate the mechanism of N-Myc regulation of

DOT1L, via N-Myc protein binding to the E-box at the DOT1L gene promoter leading to

DOT1L gene transcription.

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A m p lic o n A A m p lic o n B A m p lic o n C A m p lic o n D 1 0 1 0 1 0 1 0

8 8 ** 8 8

e h

t 6

t h

6 t

t 6

o t

r r

n 4 n 4 n

p 4 p

4 e

c c

i 2

i 2 i i 2 ****

2 g

r r

d d

l 0

l l

l 0 0 0

D F D Ig G N -M y c Ig G N -M y c Ig G N -M y c Ig G N -M y c

Figure 3.3. N-Myc binds to a non-canonical E-box at the DOT1L gene promoter.

Schematic representation of the DOT1L gene promoter and the four amplicons designed to cover it (A). ChIP assays were performed with a control IgG or N-Myc antibody (Ab), followed by PCR with primers targeting the negative control region (far upstream of the

E2F2 gene) or the DOT1L gene promoter region (Amplicons A, B, C and D) in BE(2)-C cells

(B). Fold enrichment of the DOT1L gene promoter by the anti-N-Myc antibody was calculated as the difference in cycle thresholds obtained with the anti-N-Myc Ab compared with the control IgG, relative to input and the E2F2 negative control region. Error bars represent standard error. *,** and **** indicate p < 0.05, 0.01and 0.0001 respectively.

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3.2.3 DOT1L knockdown causes decreased N-Myc target gene transcription and reduces neuroblastoma cell proliferation

Myc proteins control the expression of myriad genes, in both normal physiological and cancer settings. These downstream targets have been demonstrated to play an essential role in neuroblastoma tumourigenesis (Dang 1999). I examined whether DOT1L regulated the expression of N-Myc target genes E2F2 and ODC1 in neuroblastoma, using DOT1L and

N-Myc siRNA transfections in BE(2)-C and Kelly cell lines. As histone H3K79 demethylation occurs slowly, DOT1L siRNA transfections were carried out twice at 48 hour intervals, for a total 96 hour incubation. RT-PCR and immunoblot analyses showed reduced

ODC1 mRNA (Figure 3.4A) and protein expression (Figure 3.4B) as a result of DOT1L knockdown with N-Myc siRNA as a positive control.

105

B E (2 )-C K e lly

T n

n 1 .5 1 .5

1 .0 1 .0

x g

g ** * e

e *

** ** a

a 0 .5 0 .5 A

A **** h

h **** ****

l 0 .0 0 .0

o F F 1 1 1 2 1 1 1 2 A - - - - A - - - - N A A A A N A A A A N N iR N N N N iR N N s iR iR iR iR s iR iR iR iR l l s s s s s s s s ro L L c c ro L L c c t 1 1 y y t 1 1 y y n T T n T T o -M -M o -M -M C O O C O O D D N N D D N N

B. 1

1 K e lly

B E (2 )-C C

D i

O 1 .5 o

1 .5

r e

e 1 .0

r e 1 .0 p g **

p *

g x

n ****

e **** ****

h 0 .5 **** A

h 0 .5 A

**** c

N ****

l R

o 0 .0 o 0 .0 1 2 1 2 F F - - -1 -2 1 2 A - - A - - A A A A N A A A A N N N R N N N N iR N N i R R R R s iR iR iR iR s i i i i l s s l s s s s s s o o r L L c c tr L L c c t y y 1 1 y y n 1 1 n T T T T M M o -M -M o - - C O O C O O D D N N D D N N

C. BE(2)-C Kelly

DOT1L

ODC1

Actin

DOT1L Control DOT1L DOT1L Control DOT1L siRNA-2 siRNA siRNA-1 siRNA-2 siRNA siRNA-1

106

Figure 3.4. DOT1L knockdown reduces the RNA and protein expression of N-Myc target gene, ODC1.

BE(2)-C and Kelly cells were transfected with control siRNA, DOT1L siRNA-1, DOT1L siRNA-2, N-Myc siRNA-1, or N-Myc siRNA-2 for 96 hours, followed by RT-PCR analysis of DOT1L gene expression (A) and ODC1 gene expression (B). Immunoblot analysis was performed to examine DOT1L and ODC1 protein expression (C). Error bars represent standard error. *,**,*** and **** indicate p < 0.05, 0.01, 0.001 and 0.0001 respectively.

107

Another N-Myc target gene was E2F2, which belongs to the E2F protein family

(Kovesdi 1986, Ivey-Hoyle 1993). To examine whether DOTL regulated E2F2 expression,

DOT1L and N-Myc siRNA transfections were carried out in BE(2)-C and Kelly cells. RT-

PCR and immunoblot analysis showed that DOT1L siRNAs and N-Myc siRNAs reduced

E2F2 mRNA (Figure 3.5A) and protein expression (Figure 3.5B). These results confirmed that DOT1L and N-Myc regulate ODC1 and E2F2 expression.

Up-regulation of ODC1 has been well-documented to contribute to N-Myc-mediated neuroblastoma cell proliferation (Nilsson 2005, Hogarty 2008). Next I examined the effect of

DOT1L and E2F2 knock downs upon neuroblastoma cell proliferation. BE(2)-C and Kelly neuroblastoma cells were transfected with control siRNA, DOT1L siRNA-1, DOT1L siRNA-

2, E2F2 siRNA-1 or E2F2 siRNA-2 for 96 hours, followed by Alamar blue assays. Alamar blue assays showed that transfection with DOT1L siRNAs or E2F2 siRNAs reduced the number of BE(2)-C and Kelly cells (Figure 3.6). This suggests that DOT1L promotes neuroblastoma cell proliferation, and that up-regulation of E2F2 contributes to DOT1L- mediated neuroblastoma cell proliferation.

108

B E (2 )-C 2

2 K e lly

n 2

o 1 .5

E 1 .5

r e

1 .0 r 1 .0

p g

* p

n x

n **

a e

a **

0 .5 **** h 0 .5 *** A

A **** c

**** c

R o

0 .0 o 0 .0 F F 1 2 1 2 1 2 1 2 A - - - - A - - - - N A A A A N A A A A N N iR N N R N N N N R R R R i R R s i i i i s i i iR iR l s s s s l s s s s o r L L c c ro L L c c t y y t n 1 1 n 1 1 y y o T T M M o T T M M O O - - O O - - C N N C N N D D D D B.

BE(2)-C Kelly

E2F2

Actin N -Myc DOT1L Control DOT1L N-Myc N-Myc DOT1L Control DOT1L N-Myc siRNA-2 siRNA-2 siRNA siRNA-1 siRNA-1 siRNA-2 siRNA-2 siRNA siRNA-1 siRNA-1

Figure 3.5. DOT1L knockdown reduces the RNA and protein expression of N-Myc

target gene, E2F2.

BE(2)-C and Kelly cells were transfected with control siRNA, DOT1L siRNA-1, DOT1L

siRNA-2, N-Myc siRNA-1, or N-Myc siRNA-2 for 96 hours, followed by RT-PCR analysis

(A) and immunoblot analysis (B) of E2F2 expression. Error bars represent standard error.

*,**,*** and **** indicate p < 0.05, 0.01, 0.001 and 0.0001 respectively.

109

l e e B E (2 )-C

c K e lly

e l l 1 5 0

b 1 5 0

1 0 0 f 1 0 0

o o

e **** ***

e g 5 0 g a **** 5 0

**** a

t ****

t n

n ****

e c

0 c r 0 r e 1 2 1 2 1 2 1 2 A - - - - e A - - - -

P A A A A A A A A N P N N N N N N N iR iR N N R R R R R R R R s i i i i s i i i i l s s s s l s s s s o o tr L L 2 2 tr L L 2 2 n 1 1 F F n 1 1 F F o T T 2 2 o T T 2 2 C O O E E C O O E E D D D D

Figure 3.6. Knocking-down DOT1L or E2F2 leads to reduced cell proliferation in N-

Myc overexpressing neuroblastoma cell lines.

BE-(2)C and Kelly cells were transfected with control siRNA, DOT1L siRNA-1, DOT1L siRNA-2, E2F2 siRNA-1 or E2F2 siRNA-2. Ninety-six hours later cell proliferation was analysed using Alamar blue assay. Error bars represent standard error. *, **, *** and **** indicate p < 0.05, 0.01, 0.001 and 0.0001 respectively.

110

3.2.4 DOT1L-mediated H3K79 methylation facilitates N-Myc protein binding to target genes promoters

DOT1L has been demonstrated to be a critical driver of tumourigenesis in MLL leukemia as a component of the Elongation Assisting Proteins (EAP) complex along with

RNA PII, factors AF4, AF6, AF9, AF10 or ENL (Bitoun 2007, Krivtsov 2008, Nguyen 2011,

Deshpande 2013). H3K79 methylation has been shown to maintain an open chromatin state along with elevated H3K9 acetylation and minimal H3K9 methylation at MLL fusion target genes (Chen 2015).

Based on the ability of DOT1L to complex with various MLL proteins, I investigated whether the mechanism of DOT1L action in neuroblastoma was via protein-protein binding with N-Myc to drive transcription of downstream N-Myc target genes. HEK293 cells were co-transfected with an N-Myc-expression construct, together with a construct encoding empty vector or Flagg-tagged DOT1L. Immunoprecipitation with an anti-Flag antibody pulled-down DOT1L protein and N-Myc protein in cells co-transfected with the DOT1L and the N-Myc expression constructs, but not N-Myc in cells transfected with the N-Myc expression construct alone (Figure 3.7). The data confirms that DOT1L and N-Myc proteins form a protein complex.

111

IP: IgG anti-FLAG ab 2% Input control pcDNA3.1 N-Myc + + + + + pcDNA3.1 DOT1L-FLAG + - + - +

DOT1L

N-Myc

Actin

Figure 3.7. DOT1L forms a protein complex with N-Myc.

HEK293 cells were co-transfected with N-Myc-pcDNA3.1 expression construct, together with empty vector or hDOT1L-FLAG-pcDNA3.1 construct for 48 hours. Protein was extracted from the cells and co-immunoprecipitation was carried out using an anti-FLAG antibody or a mouse IgG as a negative control. Immunoblot analysis was carried out using an anti-N-Myc antibody and anti-DOT1L antibody.

112

Since H3K79me2 at target gene promoters was reported to be critical for MYC binding to target gene promoters (Guccione 2006), I examined whether knocking-down

DOT1L expression reduced H3K79 methylation and N-Myc protein binding to E-boxes at target gene promoters. ChIP assays were performed with a control IgG or anti-H3K79me2 antibody and DNA-protein complex from BE(2)-C cells, followed by PCR with primers targeting the E2F2 gene promoter or a negative control region. Amplicons for PCR were designed for the E2F2 gene (Figure 3.8A) based on ChIP-seq data with anti-H3K79me2 and c-Myc antibodies in K562 and HeLa cells from the UCSC Genome Browser database

(http://genome.ucsc.edu/cgi-bin/hgGateway). ChIP assays confirmed that H3K79me2 peaked at the E2F2 intron 1 region covered by amplicon C with a 100 fold increase in the presence of

H3K79me2, compared with the negative control region (Figure 3.8B). The two flanking amplicons, B and D, showed less than 20 fold increase in H3K79 di-methylation.

BE(2)-C cells were then transfected with either one of the two independent DOT1L siRNAs or a scrambled control siRNA. ChIP assays were carried out 72 hours later using an

H3K79me2 antibody or control IgG to examine the effect on H3K79me2. The results showed that there was a decrease from 100 fold to 30 fold in the presence of H3K79me2 at the E2F2 intron 1 region covered by amplicon C (Figure 3.9A). The flanking amplicons, B and D also showed a decrease in H3K79me2 but this was less than the decrease at amplicon C. A similar

H3K79me2 decrease was also shown in the ODC1 promoter region, using an amplicon that covered 2 E-boxes located in the 5’UTR of the ODC1 gene (Figure 3.9B and C). This indicates that DOT1L induces histone H3K79 methylation at the N-Myc target gene promoters.

113

A m p lic o n B A m p lic o n C A m p lic o n D 2 0 0 2 0 0

t 2 0 0

n n

e e

e 1 5 0 1 5 0 * 1 5 0

r r

r 1 0 0 1 0 0 1 0 0

d l

5 0 5 0 l 5 0

o o

o *

F F F * 0 0 0 Ig G H 3 K 7 9 m e 2 Ig G H 3 K 7 9 m e 2 Ig G H 3 K 7 9 m e 2

Figure 3.8. H3K79 di-methylation peaks occur in the intron 1 region of the N-Myc target gene, E2F2.

Schematic representation of the E2F2 gene promoter region (A). Amplicon A was located > -

3000bp upstream of the E2F2 gene transcription start site, amplicon B covered an E-box sequence -431bp upstream of the E2F2 transcription start site, ampicon C covered the intron

1 region and ampicon D covered the intron 3 region of the E2F2 gene. ChIP assays were performed in BE2C cells with an H3K79me2 antibody or control IgG, followed by PCR with primers targeting the 4 amplicons (B). Error bars represent standard error. *indicate p < 0.05.

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A. A m p lic o n B A m p lic o n C A m p lic o n D * 1 5 0

t 1 5 0 * 1 5 0 t

* t

m m

1 0 0 m h

h 1 0 0 1 0 0

r r

n n

n *

5 0 5 0 5 0 * *

d d

* d

o o

* * o

F F

0 F 0 0

1 2

- -

L L

1 1

A A

1 1

A A

T T

N N

O O

R R

i i

D D

s s

H 3 K 7 9 m e 2 a b H 3 K 7 9 m e 2 a b H 3 K 7 9 m e 2 a b

C. O D C 1 E -b o x A m p lic o n B. ODC1 TSS * t 2 0 **

n * e

m 1 5

ODC1 E-box h

c i

r 1 0

-100 200 400 600 l 5

CACGT

CACGT o

1 2

- -

L L

1 1

A A

T T

N N

i O

R R

i i

D D

s s

H 3 K 7 9 m e 2 a b

Figure 3.9. Knocking-down DOT1L reduces H3K79 di-methylation at the E2F2 and

ODC1 gene promoters.

BE(2)-C cells were transfected with control siRNA, DOT1L siRNA-1 or DOT1L siRNA-2 for 72 hours. ChIP assays were performed with a control IgG or anti-H3K79me2 antibody.

PCR was performed with primers targeting a negative control region (amplicon A) or the

E2F2 gene promoter region covered by amplicons B, C and D (A). Schematic representation of the ODC1 gene promoter region (B). PCR was performed with primers targeting a negative control region (E2F2 Amplicon A) or the two E-box at the ODC1 gene promoter region (C). Error bars represent standard error. * and ** indicate p < 0.05 and 0.01 respectively.

115

To further examine the effect of DOT1L-mediated H3K79me2 on N-Myc binding to target gene promoter E-boxes, ChIP assays were performed using an N-Myc antibody or control IgG after BE(2)-C cells were transfected with control siRNA, DOT1L siRNA-1 or

DOT1L siRNA-2 for 72 hours and PCR with primers targeting the E2F2 and ODC1 gene promoter regions or a negative control region. ChIP assays showed that the anti-N-Myc antibody immunoprecipitated both the E2F2 and ODC1 promoter regions with E-boxes at 2 fold higher than control IgG in cells transfected with scrambled control siRNA. In comparison to the scrambled siRNA, DOT1L siRNAs reduced N-Myc protein binding at the

E-Boxes of both E2F2 and ODC1 gene promoters (Figure 3.10). These findings together suggest that DOT1L-mediated H3K79 methylation is crucial to N-Myc binding to E-boxes in target gene promoter regions.

116

E 2 F 2 g e n e p ro m o te r O D C 1 g e n e p ro m o te r re g io n w ith E -b o x re g io n s w ih E -b o x e s

t 4 t

n 4

e m

3 ** m 3 *

h h

i r 2 r

n 2 n

e *

** ** *

d l 1 d

l 1

o F

0 F

l 0

1 2

2 1

- -

L L

- -

L L

1 1

A A

1 1

A A

T T

N N

T T

N N

O O

R R

O O

i i

R R

i i

D D

s s

D D

s s

N -M y c a b N -M y c a b

Figure 3.10. DOT1L knock-down decreases N-Myc protein binding to E-box regions of

E2F2 and ODC1 gene promoters.

BE(2)-C cells were transfected with control siRNA, DOT1L siRNA-1 or DOT1L siRNA-2 for 72 hours. ChIP assays were performed with an N-Myc antibody or control IgG, followed by PCR with primers targeting the E-box regions of the E2F2 and ODC1 gene promoters or the E2F2 gene Amplicon A as the negative control. Error bars represent standard error. * and

** indicate p < 0.05 and 0.01 respectively.

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3.2.5 The small molecular DOT1L inhibitor SGC0646 reduces DOT1L and N-Myc target gene expression in neuroblastoma cells

DOT1L is a promising target for anti-cancer treatment due to uniqueness as the only known H3K79 histone methyltransferase, a non-SET catalytic domain and a role in promoting and maintaining MLL leukaemogenesis (Feng 2002, Min 2003). The first DOT1L specific small molecular inhibitor was EPZ004777, designed by Epizyme using a traditional ligand-based approach based on the DOT1L substrate SAM and the product SAH (Daigle

2011). Modifications to EPZ00477 lead to the synthesis of SGC0946, featuring an additional bromine atom at position 7 targeting a hydrophobic cleft present in DOT1L to improve the

DOT1L inhibitor’s binding affinity (Yu 2012).

Our earlier finding demonstrated that DOT1L-mediated H3K79 methylation was necessary for N-Myc binding to target gene promoters at E-box sites. In turn this would lead to the over-expression of N-Myc downstream genes, of which E2F2 and ODC1 are examples, and a consequent increase in neuroblastoma cell proliferation. Thus I investigated whether the small molecular DOT1L inhibitor, SGC0946, was effective in targeting N-Myc overexpressing neuroblastoma cell lines.

BE(2)-C and Kelly cells were treated with a range of doses of SGC0946, followed by clonogenic assays. Treatment with SGC0946 caused dose-dependent reductions in clonogenicity (Figure 3.11), however the two N-Myc amplified cell lines showed different trends in response to increased SGC0946 doses. When treated with increasing doses of

SGC0946 the BE(2)-C cell line did not show any significant drops in clonogenicity until the maximum dose of 20uM, which caused near total decrease in colony formation after 10 days.

118

In comparison the Kelly cell line displayed an earlier dose response with the maximum dosage also causing near total decrease in colony formation after 12 days.

119

B E (2 )-C K e lly d

1 5 0 d 2 5 0

m m

r 2 0 0

o o

f 1 0 0

1 5 0

i i

n 1 0 0

5 0 n

o l

l * * * o

o 5 0 C ** C 0 0 * 5 5 5 0 0 O 1 2 O 5 5 5 0 0 S 2 .2 2 2 1 2 1 S 1 . M 3 1 1 . M .3 D 0 D 0 S G C 0 9 4 6 (u M ) S G C 0 9 4 6 (u M )

Figure 3.11. The DOT1L inhibitor SGC0946 reduced neuroblastoma colony formation.

BE(2)-C and Kelly neuroblastoma cells were treated with DMSO vehicle control or 0.3125 uM, 1.25 uM, 2.5 uM, 5 uM and 20 uM of SGC0946. Treatment media was refreshed every 3 days. Colonies were fixed with methanol after 10 days treatment for BE(2)-C and 12 days for

Kelly. Colonies were stained with 0.05% crystal violet and counted using Quantity1 software.

Error bars represent standard error. * and ** indicate p < 0.05 and 0.01 respectively.

120

As SGC0946 targets the methyltransferase activity of DOT1L by competitively binding to the substrate binding domain, I investigated the effect of the SGC0946 treatment on total H3K79me2 levels in BE(2)-C and Kelly cell lines (Figure 3.12). These results showed that in BE(2)-C cells, SGC0946 decreased total H3K79me2 in a dose dependant manner. However in Kelly cell, H3K79me2 was dramatically decreased even with the medium dose of 1.25uM. This mirrors the previous clonogenicity results with the Kelly cells showing a more sensitive and dosage dependant response to SGC0946 treatment compared to the BE(2)-C cell line.

Of particular interest is the short response time between SGC0946 treatment and a decrease in H3K79me2 compared to the colon forming assays. This demonstrates that a long delay is present between the direct effect of inhibiting the H3K79 methyltransferase activity of DOT1L and the downstream effects of decreased neuroblastoma cell proliferation.

121

Figure 3.12. The DOT1L inhibitor SGC0946 reduced H3K79me2 in a dose dependant manner.

BE(2)-C and Kelly cells were treated with either DMSO vehicle control, 1.25 uM or 5 uM

SGC0946. After 96 hours, histones were extracted and subjected to immunoblot with an anti-

H3K79me2 antibody with an anti-total H3 antibody as the loading control.

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Next the effect of DOT1L inhibition on DOT1L downstream target gene transcription was examined. The small molecular DOT1L inhibitor, SGC0946 was used to treat N-Myc overexpressing neuroblastoma cell lines, BE(2)-C and Kelly for 7 days. The SGC0946 treatment reduced ODC1 and E2F2 gene expression in both cell lines in comparison to the vehicle control treatment. ODC1 reduction was most effectively reduced in Kelly, with

BE(2)-C cells showing less than 20% reduction in ODC1 gene expression. There was no difference in ODC1 and E2F2 gene expression between the 1.25uM or 5uM doses of

SGC0946 treatment.

123

B E (2 )-C K e lly

C n n 1 .5

1 .5 D

O O

r 1 .0 1 .0

p e

e ** p

** x

g g

x * *

a e

e 0 .5 0 .5

o 0 .0 0 .0 F F l l o M M o M M tr u u tr u u n 5 5 n 5 5 o .2 6 o .2 6 c 1 4 c 1 4 e l 6 9 le 6 9 ic 4 0 ic 4 0 h 9 C h 9 C e 0 G e 0 G V C S V C S G G S S

B E (2 )-C K e lly

n 2

2 1 .5 1 .5

s n

r 1 .0 1 .0

e p

p * * g g **

* x

e e

h 0 .5 0 .5

o 0 .0 0 .0 F F l l o M M o M M tr u u tr u u n 5 5 n 5 5 o 2 o 2 c . 6 c . 6 1 4 1 4 le 6 9 le 6 9 ic 4 0 ic 4 0 h 9 C h 9 C e 0 G e 0 G V C S V C S G G S S

Figure 3.13. The DOT1L inhibitor SGC0946 reduced ODC1 and E2F2 gene expression in N-Myc over-expressing neuroblastoma cell lines.

N-Myc overexpressing neuroblastoma cell lines BE(2)-C and Kelly were treated with either

DMSO vehicle control or the DOT1L inhibitor, SGC0946 for 7 days. RT-PCR assays was conducted for ODC1 (A) and E2F2 (B) gene expression. All control and treatment media was refreshed after 3 days. Error bars represent standard error. * and ** indicate p < 0.05 and 0.01 respectively.

124

3.3 Discussion

In this chapter I demonstrated that N-Myc up-regulated DOT1L in neuroblastoma cell lines via binding to an E-box in the DOT1L gene promoter. This corresponds with recent reports which have shown that DOT1L cooperates with c-Myc in breast cancer (Cho 2015).

Together DOT1L and c-Myc were shown to upregulate p300 acetyltransferases, causing epithelial-mesenchymal transition (EMT) regulators to be epigenetically activated and resulting in breast cancer progression. The critical role of DOT1L in breast cancer was further demonstrated through selective inhibition of DOT1L mediated H3K79 methylation resulting in reduced cell proliferation and metastatic potential of breast cancer (Zhang 2014).

DOT1L-mediated H3K79 methylation was demonstrated to promote N-Myc protein binding to E-boxes located in the gene promoter regions of N-Myc target genes, E2F2 and

ODC1, causing their consequent overexpression. Knockdown of DOT1L reduced the

H3K79me2 peaks located at the target gene promoters and reduced N-Myc binding to E- boxes at target gene promoters. These findings confirm previous reports of H3K79 methylation being crucial for Myc binding to target gene promoters (Guccione 2006,

Martinato 2008).

Both E2F2 and ODC1, the N-Myc target genes studied here act upon different pathways to increase tumour cell proliferation. Here I demonstrated DOT1L-mediated

H3K79me2 recruited N-MYC to an E-box in the E2F2 gene promoter region, leading to

E2F2 overexpression and increased neuroblastoma cell proliferation. E2F2 has been shown to be involved in cell cycle regulation with the activation of G1 phase Cdks leading to phosphorylation of the Rb protein, resulting in the release of E2F2 and the expression of

125

E2F2 target genes involved in DNA synthesis (Nevins 2001). RNAi mediated knockdown of

E2F2 has also been reported to inhibit tumour initiation in glioblastoma cells (Nakahata

2014). Loss of E2F2 resulted in reduced tumour incidence in a c-Myc induced breast cancer mouse model (Fujiwara 2011). E2F1, E2F2, E2F3a and c-Myc were demonstrated to control cell proliferation in wild-type cells by cooperating to promote progression though the S/G2 transition, with minimal effect on the G1/S transition of the cell cycle (Liu 2015). However, in cells lacking Rb protein expression, c-Myc and E2F1, E2F2 and E2F3a take part in an abnormal transcriptional programme that induces upregulation of c-Myc and E2F target genes followed by premature entry into the S phase and excessive cell proliferation (Liu

2015).

ODC1 is a pyridoxial phosphate dependant amino acid decarboxylase, and is essential to polyamine synthesis de novo in mammals (Auvinen 1992, Bettuzzi 1999). Due to this critical role, the ODC1 gene is highly regulated by a range of growth factors including c-Myc and N-Myc (Coleman 1994). The ODC1 gene promoter region contains multiple sequences that allow protein binding, such as a TATA box, cAMP response element, AP-1 and AP-2 sites, CAAT and LSF motifs, GC-rich p1 binding sites, and 2 E-boxes (Zhao 2001, Qin

2004). The two E-boxes, with sequence CACGTG, allows the binding of the MYC/MAX transcription factor to the ODC1 gene promoter, with mRNA transcription activated when

MYC levels are elevated (Packham 1997, Nilsson 2004).

My findings of DOT1L mediated H3K79 methylation recruiting N-Myc to E-boxes at the ODC1 gene promoter demonstrate an additional layer of control for ODC1 gene expression and polyamine synthesis in neuroblastoma. Furthermore high risk neuroblastoma

126 tumours without N-Myc amplification were demonstrated to overexpress ODC1, in comparison to lower risk tumours (Hogarty 2008). This meant elevated ODC1 gene expression was associated with poor patient prognosis, independent of N-Myc amplification in a large neuroblastoma cohort (Hogarty 2008). ODC1 has also displayed promise as a drug target to inhibit polyamine synthesis, inhibition of ODC1 by difluoromethylornithine

(DFMO) decreased tumour penetrance in TH-MYCN mice treated pre-emptively (Gamble

2012). DFMO also displayed synergistic effects in combination with chemotherapy in treating established tumours in TH-MYCN and viability models. DFMO has completed stage

1 clinical trials targeting polyamine addiction in relapsed/refactory neuroblastoma patients, displaying good tolerance of doses 500-1500mg/m2/day (Saulnier Sholler 2015).

Here reducing DOT1L gene expression in neuroblastoma was shown to lead to reduced expression of N-Myc downstream target genes, in turn decreasing neuroblastoma cell proliferation and clonogenicity. This suggests that targeting DOT1L would be an effective strategy to indirectly target N-Myc driven gene transcription and a potential therapeutic treatment for neuroblastoma.

Small molecular DOT1L inhibitors have been reported with the EPZ004777 derivative EPZ5676 currently undergoing clinical trials for the treatment of MLL rearranged leukemia. EPZ004777 was designed by Epizyme using a traditional ligand-based approach based on the DOT1L substrate SAM and the product SAH (Daigle 2011). EPZ004777 displayed specificity against DOT1L against a panel of eight other histone methyltransferases and in vivo efficacy. A combination of the DOT1L inhibitor, EPZ004777 and SRT1720, a

SIRT1 activator showing enhanced anti-proliferative activity against pre-treated MLL-

127 rearranged leukemia cells by supressing HOXA7 and Meis1 in vivo (Chen 2015).

Modifications to EPZ00477 lead to the synthesis of EPZ5676 (Daigle 2013) and SGC0946

(Yu 2012).

SGC0946 features an additional bromine atom at position 7 targeting a hydrophobic cleft present in DOT1L to improve the DOT1L inhibitor’s binding affinity (Yu 2012). It was reported to have an IC50 of 8.8 ± 1.6 nM in mixed lineage leukemia cells (Yu 2012). Here in the Kelly, N-Myc amplified neuroblastoma cell line, the DOT1L inhibitor SGC0946 displayed a 50% reduction in clonogenicity after 12 days of treatment at 1.25uM. However the other N-Myc amplified neuroblastoma cell line tested, BE(2)-C did not show any significant reductions in clonogenicity when treated for with dosages up to 10uM of

SGC0946 for 10 days. This difference in clonogenicity response to SGC0946 treatment could potentially be due to differences in H3K79me2 reduction between the two neuroblastoma cell lines, with the Kelly cell line displaying a better knockdown of H3K79me2 than the BE(2)-C cell lines when treated with SGC0946.

An alternate strategy for targeting DOT1L in neuroblastoma would be to target its protein binding domains, as I have shown that DOT1L is binds to N-Myc. Studies of DOT1L binding to MLL-AF9 and AF9/ENL suggest possible candidate sites. A 10 amino acid region of human DOT1L (865-874) has been identified as the AF9/ENL binding site, with four conserved hydrophobic residues within the binding site being shown to be essential for interactions with the C-terminal binding domain of AF9/ENL (Shen 2013). DOT1L binding to MLL-AF9 has been shown at two additional sites using nuclear magnetic resonance.

Structure-guided point mutations of these binding sites lead to a graded reduction in DOT1L recruitment to MLL-AF9, with differential loss of H3K79me2 and H3K79me3 at MLL-AF9

128 target genes (Kuntimaddi 2015). Blocking DOT1L protein binding to the N-Myc complex could thus be a strategy to target the MYCN gene pathway indirectly in neuroblastoma with potential patient benefits.

In this chapter, I have shown that N-Myc up-regulates DOT1L gene expression in N-

Myc overexpressing neuroblastoma cell lines via binding to a non-canonical E-box sequence at the DOT1L gene promoter. DOT1L and N-Myc proteins were shown to complex together and DOT1L mediated H3K79 methylation was demonstrated to promote N-Myc binding to

E-boxes located in the gene promoters of the N-Myc target genes, E2F2 and ODC1. This caused their consequent overexpression and increased neuroblastoma cell proliferation.

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Chapter 4: DOT1L gene expression promotes neuroblastoma tumour growth and serves as an independent prognostic factor for poor patient outcome

4.1 Introduction

MYCN gene amplification and N-Myc onco-protein over-expression are known to induce neuroblastoma initiation and progression (Nakagawara 1994, Weiss 1997, Brodeur

2003, Song 2007). Myc oncoproteins, including N-Myc and c-Myc, exert oncogenic effects by regulating gene transcription (Adhikary 2005). Myc-regulated gene transcription and overexpression of target genes, such as ODC1, has been shown to promote neuroblastoma tumorigenesis (Adams 1985, Chesi 2008, Hogarty 2008) and tumour progression (Dang

2012, Kim 2015)

Neuroblastoma has an extremely heterogeneous outcome, ranging from spontaneous regression to rapid metastasis and death. Those in low and intermediate subgroups have a 80-

95% event free survival rate, while the high risk subgroup have <50% event free survival rate

(Maris JM 2007). Traditional prognostic factors for poor patient outcome in neuroblastoma include MYCN gene amplification, advanced neuroblastoma disease staging, >1 year of age at diagnosis and loss of heterozygosity for chromosome 1p or 11q (Kubota M 2000, Peuchmaur

M 2003).

Soon after its initial discovery, MYCN gene amplification was found to correlate to poor neuroblastoma patient prognosis (Brodeur 1984, Iehara T 2006). High N-Myc levels were found to contribute to neuroblastoma cell proliferation, differentiation, adhesion, motility, invasion and degradation of surrounding matrices to promote tumour metastasis

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(Schwab 1985, Goodman LA 1997, Weiss 1997, Malynn 2000, van Golen 2003) . In addition

N-Myc overexpression was found to correlate with tumour angiogenesis and pluripotency of neural crest cells (Ozer E 2007, Nakagawa M 2010). A mouse model was created with human

MYCN gene expression targeted to migrating cells in the neural crest via the rat tyrosine hydrolase (TH)-promoter during early development (Weiss 1997). This established that overexpression of the MYCN gene in migrating neural crest cells lead to neuroblastoma tumourigenesis.

The international neuroblastoma staging system (INSS) was developed in the mid-

1990s and is widely used to facilitate the comparison of neuroblastoma tumours from patients worldwide. INSS differentiates patients into five stages based upon in situ tumour staging, surgery results, physical examinations and histopathological profiling of tissue biopsies from both the tumour and potential metastatic sites (Brodeur 1993).

Neuroblastoma patients diagnosed at greater than one year of age also have poor outcome (Brodeur 1993). In general, patients diagnosed before one year of age with localised tumour are curable with surgery to resect the tumour. Conversely older patients with extensive metastases and amplified MYCN gene expression usually die from disease progression despite intensive therapy (Cheung NK 2012).

New molecular prognosis factors reveal molecular mechanisms driving individual neuroblastoma tumours, potentially leading to the identification of new drug targets. For example, the ALK gene mutation has been found to occur in approximately 8-12% of human neuroblastoma tissues, and to correlate with poor patient prognosis (George 2008, Mossé

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2008, Ogawa 2011). Treatment with the ALK inhibitor, Crizotinib leads to anti-tumour activity in preclinical murine models of neuroblastoma (Krytska 2015).

Based on my findings in the previous chapter, DOT1L-mediated H3K9 methylation is critical for N-Myc protein recruitment to E-boxes at N-Myc target gene promoters such as

E2F2 and ODC1. This leads to increased N-Myc target gene expression and increased neuroblastoma cell proliferation in vitro. Thus I hypothesized that DOT1L would also increase neuroblastoma tumour progress in vivo and that DOT1L would be an independent prognostic factor for poor neuroblastoma patient outcome.

I established two doxycycline-inducible DOT1L knockdown stable cell lines using two different neuroblastoma cell lines, BE(2)-C and Kelly. These cells were xenografted into

Balb/c nude mice and tumour growth was monitored. Human neuroblastoma tissue microarray gene expression datasets were analysed to investigate the relationship between

DOT1L gene expression, MYCN gene expression and patient overall survival.

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4.2 Results

4.2.1 Doxycycline-inducible DOT1L knockdown reduces ODC1 and E2F2 gene expression and neuroblastoma cell proliferation

In order to study the effect of DOT1L knockdown on tumour growth in vivo, I used the GFP-FH1tUTG doxycycline inducible shRNA lentiviral vector system to establish doxycycline inducible DOT1L shRNA stable cell lines (Herold MJ 2008). A DOT1L shRNA oligo (Onder 2012) and a SCR control shRNA oligo were cloned into the GFP-FH1tUTG vector, and then transfected into 293T cells. Viral particles were used to infect BE(2)-C and

Kelly neuroblastoma cell lines, followed by cell sorting and selection of the top 5% GFP expressing cell fraction.

Validation of the doxycycline inducible DOT1L shRNA BE(2)-C and Kelly stable cells was performed by qRT-PCR and immunoblot analyses. Doxycycline treatment over 72 hours successfully knocked down DOT1L mRNA and protein in both the DOT1L shRNA

BE(2)-C (Figures 4.1A and B) and Kelly (Figures 4.2A and B) stable cell lines, compared to no effect in the SCR control shRNA cell lines. Doxycycline treatment also reduced mRNA and protein expression of the N-Myc target genes, E2F2 and ODC1, in both DOT1L shRNA

BE(2)-C (Figures 4.1B and C) and DOT1L shRNA Kelly (Figures 4.2A and B) cell lines compared to no effect in the SCR control shRNA cell lines. The decrease in E2F2 and ODC1 mRNA and protein expression was lower than that the observed DOT1L reduction due to

E2F2 and ODC1 being downstream targets of the DOT1L shRNA.

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A. C.

L B E (2 )-C BE(2)-C

1 T

n Control shRNA DOT1L shRNA

1 .5

o O

D s

*** s

n Control DOX Control DOX

i e

1 .0

p g

x DOT1L

a 0 .5

h c

l 0 .0 ODC1 o

F l x l x o o r o r o t D t D n n o + o + C A C A E2F2 + N + N R R A h A h N s N s R l R o L h r h 1 s t s T l n Actin o L O r o 1 t C T D n o O C D B.

B E (2 )-C B E (2 )-C

F C

n 1 .5

i E * i

e 1 .0 e

1 .0

0 .5 a 0 .5

0 .0 0 .0

F F l x l x l x l x o o o o o o ro o r r tr t D t D t D D n n n n + o + o + o + o C A C A C A C A N N + N + N + + R R R R A h A h A h A h N s N s N s N s l R l R R R L o L h o h 1 h r h 1 s r s s t s T t T l n l n L L O o o O ro o 1 r 1 D t C T D t C T n n O o O o D C D C

Figure 4.1 DOT1L shRNA knocked down DOT1L, E2F2 and ODC1 mRNA and protein expression.

Doxycycline inducible DOT1L shRNA BE(2)-C cells and doxycycline inducible SCR control shRNA BE(2)-C cells were treated with vehicle control or 2µg/ml doxycycline for

72 hours, followed by qRT-PCR (A and B) and immunoblot (C) analyses of DOT1L, E2F2 and ODC1. * and *** indicate p < 0.05 and 0.001 respectively.

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A. C.

K e lly Kelly L

1 Control shRNA DOT1L shRNA T

n 1 .5 o

i D

s ***

Control DOX Control DOX

n e

i 1 .0

p g

x DOT1L

e n

0 .5 a

N c

l 0 .0

o ODC1

F l x l x o ro o r o t D t D n n o + o + C A C A + N + N E2F2 R R A h A h N s N s R l R L h o h 1 s tr s l T n L O ro o 1 Actin t C T D n o O C D

B. K e lly K e lly

F n

1 .5 n 1 .5

i E

i * O

e 1 .0

0 .5 0 .5

R l 0 .0

o 0 .0

F F l x l x l l x o x ro o r o o o o o t D t D r tr t D D n + n + n n o o o + o + C A C A C A C A + N + N + N + N R R A R R A h h A h A h N s N s N N s l s R R L R l R L h o h 1 o h s r s h r 1 t T s t s T l n L l n o o O L O r 1 D ro o 1 t C T t C T D n n o O O D o C C D

Figure 4.2 DOT1L shRNA knocks down DOT1L, E2F2 and ODC1 mRNA and protein expression.

Doxycycline inducible DOT1L shRNA Kelly cells and doxycycline inducible SCR control shRNA Kelly cells were treated with vehicle control or 2µg/ml doxycycline for 72 hours, followed by qRT-PCR (A) and immunoblot (B) analyses of DOT1L, E2F2 and ODC1. * and

*** indicate p < 0.05 and 0.001 respectively.

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Having confirmed that the DOT1L shRNA in both BE(2)-C and Kelly stable cell lines was doxycycline inducible and knocked down DOT1L expression, I investigated the effect of this DOT1L knockdown on H3K79 methylation in the DOT1L shRNA BE(2)-C and Kelly stable cell lines using an acid extraction method for histone protein extraction and total histone H3 as a loading control. Immunoblot analysis of H3K79me2 showed that H3K79me2 was reduced when the doxycycline-inducible DOT1L shRNA BE(2)-C and Kelly cells were treated with doxycycline compared to the vehicle control for 72 hours (Figure 4.3A). The

SCR control shRNA BE(2)-C and Kelly cells showed no effect in H3K79me2 levels after treatment with doxycycline compared with the vehicle control treatment.

I investigated the effect of this doxycycline inducible DOT1L shRNA on neuroblastoma cell proliferation using Alamar blue assays (Figure 4.3B). Both SCR control shRNA BE(2)-C and Kelly cells showed <20% reductions in cell number as a result of doxycycline treatment in comparison to the vehicle control. Doxycycline treatment reduced cell numbers by 50% in the DOT1L shRNA BE(2)-C cells and 70% in the DOT1L shRNA

Kelly cells compared to the vehicle control treatment.

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A. BE(2)-C Kelly DOT1L Control DOT1L Control shRNA shRNA shRNA shRNA + - + - Doxycycline + - + - H3K79me2

Total H3

r r

e B E (2 )-C e

b K e lly

b m

1 5 0 m

u 1 5 0

n ***

l ***

l e

1 0 0 e 1 0 0

5 0 e 5 0

a h

h 0 0

l x l x l x l x o o o o o o o % o % r r r r t t t D t D D D n n n n + + o + o + o o C A C A C A C A + N + N + N + N R R A R A R A h A h h h N N s N s N s s R l R L R l R L h o h h o h s r s 1 s r s 1 t T t T l n L l n L o o 1 O o o O tr D r 1 D C T t C T n O n O o o C D C D

Figure 4.3 DOT1L shRNA decreases H3K79me2 and reduces cell proliferation.

Doxycycline-inducible SCR control shRNA or DOT1L shRNA BE(2)-C and Kelly cells were treated with vehicle control or 2µg/ml doxycycline. (A) Seventy-two hours after treatment, histone was extracted from the cells with acid extraction method, and subjected to immunoblot analysis of H3K79me2 and total H3. (B) Ninty-six hours after treatment,

Alamar blue assays were conducted. Results were calculated according to optical density absorbance units, and expressed as percentage change in the number of cells relative to doxycycline-inducible control shRNA cells treated with vehicle controls.

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4.2.2 DOT1L shRNA reduces neuroblastoma tumour progression and improves overall survival in vivo

The doxycycline-inducible DOT1L shRNA BE(2)-C and Kelly stable cell lines were each injected into the flanks of 24 Balb/c nude mice, with a total of 48 Balb/c nude mice used. The mice were further separated into doxycycline treatment or control treatment subgroups of 12 mice each. Once tumours were palpable, the mice was fed with either 2mg/ml of doxycycline in 10% sucrose water or the control treatment of 10% sucrose water. Tumour growth was measured every two days using calipers with tumour volume calculated by

(length x width x height)/2 (Monga 2000). Mice were culled once tumour volume reached

1cm3.

The doxycycline treatment sub-group displayed slower rates of tumour growth in comparison to the control treatment group in both doxycycline-inducible DOT1L shRNA

BE(2)-C and Kelly xenografts (Figure 4.4A and B). The DOT1L shRNA BE(2)-C xenografts displayed a consistently lowered tumour growth rate when treated with doxycycline (Figure

4.4A). The DOT1L shRNA Kelly xenografts displayed a pause in tumour growth when treated with doxycycline followed by tumour growth resuming at the control treatment rate

(Figure 4.4B).

Kaplan-Meier survival analysis of the DOT1L shRNA BE(2)-C (Figure 4.4C) and

Kelly (Figure 4.4D) xenografts showed that doxycycline treatment increased overall survival probability by two fold to the control treatment.

138

A. B.

)

) D O T 1 L s h R N A B E (2 )-C D O T 1 L s h R N A K e lly

3 3

1 5 0 0 1 5 0 0 m m

C o n tro l C o n tro l

(

tre a tm e n t tre a tm e n t e

1 0 0 0 e 1 0 0 0 m

D o x y c y c lin e m u

u D o x y c y c lin e

l o

tre a tm e n t o tre a tm e n t

5 0 0 r 5 0 0

u T T 0 0 0 2 0 4 0 6 0 8 0 0 2 0 4 0 6 0 8 0 D a y D a y

C. D.

D O T 1 L s h R N A B E (2 )-C D O T 1 L s h R N A K e lly

l i

i C o n tro l tre a tm e n t b

b 1 .0 0 C o n tro l tre a tm e n t 1 .0 0 a

a (n = 1 1 ) b

b (n = 1 0 )

r r

p 0 .7 5

p 0 .7 5 D o x tre a tm e n t

D o x tre a tm e n t

l a a (n = 1 1 )

(n = 1 1 ) v

v i i 0 .5 0

0 .5 0 v

l p < 0 .0 0 0 1

l 0 .2 5

l 0 .2 5 p < 0 .0 0 0 1

e v

v 0 .0 0 0 .0 0 O O 0 2 0 4 0 6 0 8 0 0 2 0 4 0 6 0 8 0 T re a tm e n t D a y s T re a tm e n t D a y s

Figure 4.4 Knocking down DOT1L decreases tumour progression and improves overall survival in neuroblastoma-bearing mice.

DOT1L shRNA BE(2)-C and Kelly cells were each injected into the flanks of 24 Balb-c nude mice. Each group was divided into doxycycline and control sub-groups consisting of

12 mice each. Once tumours reached 0.005cm3 in volume, the mice were fed with 10% sucrose with or without 2mg/ml doxycycline.(A) Tumour growth was measured every two days using calipers, and tumour volume was calculated using (Length x Width x Height)/2.

Mice were culled when tumour volume reached 1cm3. (B) Kaplan-Meier survival curves showed the probability of overall survival of the mice according to doxycycline or vehicle control treatment. P-value was obtained from two-sided log-rank test.

139

At the conclusion of the in vivo experiment, the mice were culled, the tumour tissue snap frozen and protein extracted. Immunoblot analysis showed that both the DOT1L shRNA

BE(2)-C (Figure 4.5A) and Kelly (Figure 4.6A) tumours displayed a decrease in DOT1L protein expression as a result of doxycycline treatment compared to the control treatment.

The protein expression of N-Myc target genes, ODC1 and E2F2, in both DOT1L shRNA

BE(2)-C (Figure 4.5A) and Kelly (Figure 4.6A) tumours were also reduced in the doxycycline treatment group, compared to the control treatment group.

The DOT1L, ODC1 and E2F2 protein expression of each individual BE(2)-C and

Kelly tumour varied within the two treatment groups due to the heterogeneity of each individual tumour and only a fraction of the whole tumour being used for immunoblot analysis. Thus immunoblot results were quantified using the Quantity One program for the doxycycline and control treatment groups. This showed statistically significant reductions in

DOT1L, E2F2 and ODC1 protein expression of the doxycycline treatment group in comparison to the control treatment group in BE(2)-C (Figure 4.5B) and Kelly tumours

(Figure 4.6B). Taken together, knocking down DOT1L gene expression with doxycycline reduces ODC1 and E2F2 protein expression, reduces neuroblastoma tumour progression and improves overall survival in vivo.

140

D O T 1 L s h R N A B E (2 )-C D O T 1 L s h R N A B E (2 )-C D O T 1 L s h R N A B E (2 )-C

2 .0 2 .5 * 2 .0 n

n *

n t

* i

t c

c 2 .0

1 .5 c 1 .5

1 .5

1 .0 1 1 .0

2 1

C 1 .0

2 D

O 0 .5 0 .5

0 .5 E

O D 0 .0 0 .0 0 .0 l x l x l x o o o o o o tr tr tr n D n D n D o o o c c c le le le ic ic ic h h h e e e V V V

Figure 4.5 DOT1L shRNA knocks down DOT1L, ODC1 and E2F2 protein expression in BE(2)-C xenograft tumours.

Doxycycline-inducible DOT1L shRNA BE(2)-C tumour tissues were analysed using immunoblot for DOT1L, ODC1, E2F2 and actin loading control protein expression (A). The immunoblots were quantified using Quantity One (B). * indicates p < 0.05.

141

B. D O T 1 L s h R N A K e lly D O T 1 L s h R N A K e lly D O T 1 L s h R N A K e lly

2 .0 1 .5 2 .0

n n

i * n

*** i t

i *

c c

1 .5 c 1 .5

1 .0 A

1 .0 1 1 .0

C F

T 0 .5

2 D

O 0 .5 0 .5

O D 0 .0 0 .0 0 .0 l x l x l x o o o o o o tr tr tr n D n D n D o o o c c c le le le ic ic ic h h h e e e V V V

Figure 4.6 DOT1L shRNA decreases DOT1L, ODC1 and E2F2 protein expression

in Kelly neuroblastoma tissues.

Doxycycline-inducible DOT1L shRNA Kelly tumour tissues were analysed using

immunoblot for DOT1L, ODC1, E2F2 and actin loading control protein expression (A).

The immunoblots were quantified using Quantity One (B). * and *** indicate p < 0.05

and 0.001 respectively.

142

4.2.3 High level of DOT1L gene expression in human neuroblastoma tissues positively correlate to MYCN gene expression and poor patient prognosis

To assess clinical relevance of DOT1L expression in human neuroblastoma tissues, I investigated DOT1L gene expression in human neuroblastoma tissues in publically available

Kocak (Oberthuer 2010, Kocak 2013) and Versteeg (Molenaarm 2012) microarray gene expression datasets consisting of 476 and 88 human neuroblastoma patients samples respectively. The Kocak dataset contains single colour gene expression profile data from 476 neuroblastoma patients, generated using the 44K oligonucleotide microarray and accessible through GEO ID gse45547 and the R2 platform (http://r2.amc.nl). The Versteeg dataset is directly downloadable from http://r2.amc.nl. Two-sided Pearson’s correlation study showed that DOT1L mRNA expression correlated to N-Myc mRNA expression in both Kocak and

Versteeg human neuroblastoma tissue microarray datasets (Figure 4.6A and B).

143

1 2 K o c a k d a ta s e t

) 2

( R

1 0 n

T e

r 8 O

p R = 0 .4 2 4 1

x D

e p = < 0 .0 0 0 1 6 5 1 0 1 5 2 0 N -M y c m R N A e x p re s s io n (lo g 2 )

V e rs te e g d a ta s e t 8

B. )

( R

T e

r 4 O

p R = 0 .3 2 4 3

x D

e p = 0 .0 0 2 2 5 1 0 1 5 N -M y c m R N A e x p re s s io n (lo g 2 )

Figure 4.7 High DOT1L gene expression correlates with MYCN gene expression in human neuroblastoma tissue samples.

Two-sided Pearson’s correlation study was performed to examine correlation between

DOT1L mRNA expression and N-Myc mRNA expression in tumour tissues from 88 and 476 neuroblastoma patients in the publically available microarray gene expression

Kocak (A) and Versteeg (B) datasets respectively, which were downloaded from R2 microarray analysis and visualization platform (http://r2.amc.nl).

144

Kaplan-Meier survival analysis showed that high levels of DOT1L mRNA expression in tumour tissue were associated with poor patient prognosis, using a median DOT1L gene expression as the cut-off point in the Kocak (Figure 4.7A) and Versteeg (Figure 4.7B) human neuroblastoma tissue microarray datasets. Using a top quartile DOT1L gene expression as the cut-off point, Kaplan-Meier survival analysis also showed that high DOT1L mRNA expression levels in tumour tissues were associated with poor patient prognosis (Figure 4.7C and D).

Kaplan-Meier survival analysis was also conducted on the MYCN amplified cohort within the Kocak human neuroblastoma tissue microarray dataset, which consisted of 72 human neuroblastoma patients samples (Figure 4.8). In this high risk MYCN gene amplified cohort, high DOT1L mRNA expression correlated to poor patient prognosis using both a median and top quartile cut off for DOT1L mRNA expression.

145

A. B.

K o c a k d a ta s e t, a ll s a m p le s V e e rs te g d a ta s e t, a ll s a m p le s y

y (C u t-o ff: M e d ia n D O T 1 L e x p re s s io n ) t

(C u t o ff: M e d ia n D O T 1 L e x p re s s io n ) t

b a

1 .0 0 L o w D O T 1 L (n = 2 3 8 ) a 1 .0 0 b

b L o w D O T 1 L (n = 4 4 )

0 .7 5 0 .7 5 l

H ig h D O T 1 L (n = 2 3 8 ) l a

a p = 0 .0 0 4

i v

0 .5 0 v 0 .5 0

u s

s H ig h D O T 1 L (n = 4 4 )

l l

0 .2 5 l 0 .2 5 a

p = < 0 .0 0 0 1 a

e v

0 .0 0 v 0 .0 0 O 0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0 O 0 2 5 0 0 5 0 0 0 7 5 0 0 1 0 0 0 0 D a y s D a y s

D. C. K o c a k d a ta s e t, a ll s a m p le s V e e rs te g d a ta s e t, a ll s a m p le s (C u t o ff: T o p q u a rtile D O T 1 L e x p re s s io n )

y (C u t o ff: T o p q u a rtile D O T 1 L e x p re s s io n )

b a

1 .0 0 L o w D O T 1 L (n = 3 5 9 ) a 1 .0 0

o o

r L o w D O T 1 L (n = 6 6 )

p p

0 .7 5

l 0 .7 5

a a

v H ig h D O T 1 L (n = 1 1 7 )

i i

v 0 .5 0 v

r 0 .5 0 H ig h D O T 1 L (n = 2 2 )

l 0 .2 5 l

l 0 .2 5 a

p = < 0 .0 0 0 1 a

r r

e p = 2 .2 8 e -1 2 e v 0 .0 0

v 0 .0 0 O

0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0 O 0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0 1 0 0 0 0 D a y s D a y s

Figure 4.8 High levels of DOT1L gene expression in human neuroblastoma

tissues correlates with poor overall patient survival.

Kaplan–Meier survival analysis showed the probability of overall survival of patients

according to the median level (A and B) or top quartile (C and D) of DOT1L

expression in the 88 and 476 neuroblastoma patients in the Kocak (A) and Versteeg

(B) human neuroblastoma microarray gene expression datasets respectively.

146

K o c a k d a ta s e t, M Y C N -a m p lifie d s a m p le s

t i

l (C u t o ff: M e d ia n D O T 1 L e x p re s s io n )

i b

a 1 .0 0

b p = 0 .0 9 3 3 o

r p

0 .7 5

a v

i L o w D O T 1 L (n = 3 6 )

v 0 .5 0

l 0 .2 5

a H ig h D O T 1 L (n = 3 6 ) r

e v 0 .0 0

O 0 2 0 0 0 4 0 0 0 6 0 0 0 D a y s

K o c a k d a ta s e t, M Y C N -a m p lifie d s a m p le s

y t

i (C u t o ff: T o p q u a rtile D O T 1 L e x p re s s io n )

i b

a 1 .0 0

b p = 0 .0 1 1 1

r p

0 .7 5

a v

i L o w D O T 1 L (n = 5 5 )

v 0 .5 0

l 0 .2 5

a H ig h D O T 1 L (n = 1 7 )

r e

v 0 .0 0

O 0 2 0 0 0 4 0 0 0 6 0 0 0 D a y s

Figure 4.9 High levels of DOT1L gene expression in MYCN-amplified human neuroblastoma tissues correlate with poor overall patient survival.

Kaplan–Meier survival analysis showed overall patient survival, with median (A) and top quartile (B) DOT1L gene expression as the cut off points in the MYCN amplified neuroblastoma tissue cohort from the Kocak dataset, consisting of 72 patient samples.

147

Based on the Kaplan-Meier curves, I further analysed the Kocak human neuroblastoma tissue microarray dataset to determine if high DOT1L expression was an independent prognostic factor for patient outcome in neuroblastoma. I used multivariate COX regression modelling to compare the effect of DOT1L gene expression on overall survival and event free survival to the four accepted neuroblastoma risk factors: age at diagnosis >12 months, disease staging and MYCN gene amplification status. This showed that high DOT1L gene expression was a statistically significant independent prognostic factor for poor patient outcome in neuroblastoma (Table 4.1).

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Table 4.1: Multivariable Cox regression analysis of DOT1L expression in tumour tissues as a factor prognostic for outcome in 476 neuroblastoma patients*

Event-free survival Overall survival Factors HR (95%CI) P value HR (95%CI) P value High DOT1L expression 1.90 (1.315-2.753) .0001 1.81 (1.076-3.045) 0.025 (median level as cut-off) MYCN amplification 2.03 (1.397-2.949) .0002 4.52 (2.885-7.080) 4.5E-11 Age > 18 months 1.07 (0.749-1.529) .710 1.60 (1.000-2.563) .050 Stages 3 & 4† 1.05 (1.032-1.072) 2.1E-7 1.07 (1.041-1.108) 8.0E-6 High DOT1L expression 1.96 (1.329-2.903) .001 1.97 (1.180-3.281) 0.010 (upper quartile as cut-off) MYCN amplification 1.69 (1.110-2.575) .015 3.70 (2.230-6.139) 4.1E-7 Age > 18 months 1.02 (0.710-1.473) 0.904 1.54 (0.953-2.475) .078 Stages 3 & 4† 1.05 (1.034-1.074) 5.5E-8 1.08 (1.043-1.111) 4.0E-6

* DOT1L expression was considered high or low in relation to the median or high quartile

DOT1L expression in all 476 tumours analyzed. Hazard ratios were calculated as the antilogs of the regression coefficients in the proportional hazards regression. Multivariable Cox regression analysis was carried out by including the above listed four factors into the Cox regression model. P value was obtained using two-sided log-rank test.

† Tumour stage was classified as favorable (International Neuroblastoma Staging System stages 1, 2 and 4S) or unfavorable (International Neuroblastoma Staging System stages 3 and

4).

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4.3 Discussion

By analyzing 35 histone marks after genomic binding by c-Myc, Bruno Amati’s group have revealed that histone H3 lysine 4 (H3K4) tri-methylation and histone H3K79 di- methylation at Myc-responsive elements of target gene promoters are strict prerequisites for

Myc-induced transcriptional activation (Guccione 2006). The histone H3K4 trimethylaiton presenter WDR5 has recently been shown to bind to N-Myc and c-Myc proteins, and WDR5- mediated histone H3K4 tri-methylation has been shown to play an essential role in Myc- mediated target gene transcription in vitro and tumourigenesis in mice (Sun 2015). The role of DOT1L, the only histone H3K79 methyltransferase, in Myc-mediated tumour initiation and progression has not been previously studied.

Previous in vivo mouse experiments have used a homozygous DOT1L knockout mouse model with loss of DOT1L resulting in early embryonic death due to anaemia (Feng

2010). This demonstrates that DOT1L is essential for embryonic development and prenatal haematopoiesis. Due to homozygous DOT1L knockdown in mice resulting in embryonic death, inducible DOT1L knockout mouse models have been used to study DOT1L.

A tamoxifen-inducible Cre mediated DOT1L loss of function mouse model has been used to study the role of DOT1L in MLL gene translocation-driven leukaemia. Inducible

DOT1L knockout MLL-AF9 cells were transplanted into the bone marrow of recipient Ly5.1 mice, with tamoxifen treatment increasing survival and reduced leukaemia infiltration of the liver in mice transplanted with the inducible DOT1L knockout MLL-AF9 cells, demonstrating the critical role of DOT1L in MLL-AF9 mediated leukaemogenesis (Nguyen

2011). Tamoxifen administration causes the translocation of Cre-recombinase into the

150 nucleus resulting in efficient recombination of the DOT1L allele, removing exons 5 and 6, and loss of H3K79 methyltransferase function (Jones 2008, Nguyen 2011).

Here I used a lentiviral single vector system (Herold MJ 2008), to generate a doxycycline inducible DOT1L shRNA neuroblastoma xenograft mouse model to study knock down of DOT1L in vivo. This doxycycline inducible shRNA neuroblastoma xenograft model has also been used to study N-Myc (Henriksen 2011). The shRNA sequence targeting

DOT1L (Onder 2012), was confirmed to be functioning with RT-PCR and immunoblot analysis of the doxycycline inducible DOT1L shRNA stable BE(2)-C and Kelly cells showing DOT1L mRNA and protein expression reduced due to doxycycline treatment.

Critically the DOT1L shRNA reduced total H3K79me2 in both BE(2)-C and Kelly stable cell lines, in contrast the inducible Cre mediated DOT1L loss of function mouse model still allowed DOT1L protein expression and thus protein-protein interactions to still occur.

The N-Myc target genes E2F2 and ODC1 displayed decreased mRNA and protein as a result of DOT1L shRNA mediated DOT1L knock down in the doxycycline-inducible

DOT1L shRNA BE(2)-C and Kelly tumours, confirming the results in chapter 3. This

DOT1L knockdown led to a reduction in neuroblastoma tumour progression confirming my previous in vitro results. Overall survival probability was also improved in the DOT1L shRNA BE(2)-C and Kelly mouse model as a result of DOT1L knock down. This demonstrates that DOT1L plays an important role in N-Myc-driven neuroblastoma progression, and that DOT1L is a potential molecular target for treatment of neuroblastoma.

In the last decades, risk-classification algorithms for neuroblastoma patients have been actively developed. The most commonly used markers for poor neuroblastoma patient

151 survival are older age at the time of diagnosis, advanced disease stage and MYCN gene amplification (Brodeur 2003, Maris 2010). A recent study showed that high levels of the histone H3K4 trimethylation presenter WDR5 in human neuroblastoma tissues strongly associated with poor patient survival (Sun 2015), independent of traditional neuroblastoma prognostic markers for neuroblastoma patients: disease stage, diagnosis age, and MYCN gene amplification status (Brodeur 2003, Cheung 2013).

In this Chapter, DOT1L gene expression was found to positively correlate to MYCN gene expression in human neuroblastoma tissues in the Kocak (Oberthuer 2010, Kocak 2013) and Veersteg (Molenaarm 2012) human neuroblastoma microarray gene expression datasets.

This confirms the result in chapter 3 that N-Myc up-regulated DOT1L gene expression in

BE(2)-C and Kelly neuroblastoma cell lines.

Kaplan-Meier survival analysis of the Kocak and Veersteg datasets, using both median and top quartile cut off poinst for high DOT1L expression, showed that a high level of DOT1L gene expression in human neuroblastoma tissues correlated to poor patient survival. Importnatly, multivariate Cox regression modelling showed that a high level of

DOT1L gene expression in human neuroblastoma tissues was strongly associated with poor patient survival, independent of traditional neuroblastoma prognostic factors including age at diagnosis, disease stage and MYCN gene amplification status. The data confirm the important role of DOT1L gene up-regulation in human neuroblastoma tissues as a marker for poor patient prognosis and as a novel therapeutic target.

In conclusion, I have shown that DOT1L promotes neuroblastoma tumour progression in vivo in a mouse xenograft model. The protein expression of N-Myc target genes, ODC1

152 and E2F2, was also decreased when DOT1L was knocked down in vivo. High DOT1L gene expression in human neuroblastoma tissues correlated to high N-Myc expression and poor patient prognosis in human neuroblastoma tissues. This prognostic power of DOT1L gene expression was independent of traditional neuroblastoma patient prognostic factors including age at diagnosis, disease stage and MYCN gene amplification status. Taken together, DOT1L- mediated H3K79 methylation drives N-Myc amplified neuroblastoma tumour progression, and DOT1L is a novel potential molecular target for neuroblastoma treatment.

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Chapter 5: JMJD6 up-regulates Myc and promotes neuroblastoma tumour progression

5.1 Introduction

JMJD6 is a ferrous iron [Fe(II)] and 2-oxoglutarate (2OG)-dependent enzyme, and a member of the largest identified family of non-haem oxygenases (Hausinger 2004, Loenarz

2008). JMJD6 plays an important developmental role in higher animals, however the enzymatic properties of JMJD6 have been the subject of considerable debate (Böttger 2015).

JMJD6 was first identified as a punitive phosphatidylserine receptor involved in phagocytosis of apoptotic cells, under the name PSR (Fadok VA 2000). This was later shown to be incorrect, possibly due to unspecific binding of the phosphatidylserine receptor monoclonal antibody mAb217 on the plasma membranes of macrophages (Williamson 2004).

JMJD6 was suggested to be a 2-oxoglutarate (2OG) dependent dioxygenase localized to the nucleus, after comparisons of the predicted JMJD6 protein structure with the 2OG- dependent HIF-α asparaginyl hydroxylase FIH (Lando 2002). The 2OG dependent oxygenase activity of JMJD6 was reported in 2007, where JMJD6 was identified as arginine demethylase targeting histone H3 arginine 2 di-methylation (H3R2me2) and histone H4 arginine 3 di-methylation (H4R3me2) (Chang 2007).

The initial report of JMJD6 histone arginine demethylation activity has been challenged with reports finding no JMJD6 demethylase activity targeting H3R2 and H4R3

(Webby 2009, Boeckel 2011, Unoki 2013, Wang F. 2014). Thus the role of JMJD6 as a

154 histone arginine demethylase is inconclusive due to the selectivity of the antibodies previously used not being fully defined (Chang 2007). However the H4R3 arginine demethylase activity of JMJD6 was reinforced from a study of JMJD6-Brd4 interaction, but no H3 demethylation activity was detected (Liu W. 2013). JMJD6 and Brd4 were found to form a protein complex and co-bind distal anti-pause enhancers to regulate he propter- proximal pause release of transcription complexes via long range interactions, resulting in transcriptional activation of target genes (Liu W. 2013).

JMJD6 has also been shown to function as a lysyl hydroxylase. Tandem affinity coupled with mass spectrometry experiments in HEK-293T cells identified 40 potential

JMJD6 protein interaction partners, including the essential splice factor U2 auxiliary factor

65kDa subunit which JMJD6 targeted for hydroxylation at the lysine residues (Webby 2009).

JMJD6 regulation of mRNA alternate splicing was confirmed by Flag-HA tagged JMJD6 from HeLa cell lysates, GFP pulldown experiments and immunoprecipitation of endogenous

JMJD6 (Rahman 2011, Heim 2014). JMJD6 also has displayed broad protein binding activity with reported interactions with p53 in human colon carcinoma HCT116 cells (Wang F.

2014). JMJD6-mediated p53 protein hydroxylation leads to p53 protein deacetylation and inactivation.

Chromosomal abnormalities have been found to commonly occur in neuroblastoma.

Deletion of chromosome 1q, and gain of chromosome 2p and 17q have been shown to correlate to poor neuroblastoma patient prognosis (Kaghad 1997, Brodeur 2003). 17q gain has been identified as the most frequent chromosome alternation in neuroblastoma (Bown

1999, Trakhtenbrot 2002). The JMJD6 gene is located on chromosome 17q25

155

(http://www.uniprot.org/docs/humchr17). High JMJD6 expression has been also been linked to poor prognosis in breast, colon and lung cancers (Zhang J. 2013, Wang F. 2014, Poulard C

2015).

As JMJD6 forms a protein complex with Brd4 (Liu W. 2013), and Brd4 is known to activate MYC and MYCN gene transcription (Dawson 2011, Zuber 2011, Puissant 2013), in this study I examined regulation of MYC and MYCN expression by JMJD6 in neuroblastoma cell lines, and the effect of JMJD6 knock down on neuroblastoma cell proliferation and tumour progression. I also examined JMJD6 expression in human neuroblastoma microarray datasets and its potential use as a prognostic factor of poor patient outcome.

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5.2 Results

5.2.1 JMJD6 gene gain frequently occurs in human neuroblastoma tissues

Chromosome 17q-ter gain and MYCN gene amplification frequently occurs in human neuroblastoma tissues and predict poor patient survival (Brodeur 2003). I examined the frequency of JMJD6 gene gain and whether JMJD6 gene gain and MYCN amplification occurred together in human neuroblastoma tissues, using a publically available single nucleotide polymorphism (SNP) array dataset originally generated by the Therapeutically

Applicable Research to Generate Effective Treatments initiative (https://target- data.nci.nih.gov/, last accessed June 12, 2013) (Pugh 2013). Gene copy number analysis with the SNP array data revealed that MYCN amplification was observed in 89 of 341 (26.1%) samples for data which passed quality control. JMJD6 gene gain was present in 91 of the 341

(26.7%) samples (Supplementary tables S5.1 and S5.2). Fifty-six samples showed both

JMJD6 gene gain and MYCN amplification, representing 62.9% of MYCN amplified samples and 61.5% of samples with JMJD6 gene gain. This demonstrates that JMJD6 gene gain occurs in approximately one quarter of human neuroblastoma tissues, and that MYCN amplification and JMJD6 gene gain frequently co-occur in human neuroblastoma tissues.

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MYCN amplified JMJD6 gene- gained

33 56 35

n=217

Figure 5.1 MYCN gene amplification and JMJD6 gene gain co-occur in human neuroblastoma tissues.

MYCN gene amplification and JMJD6 gene gain were examined with SNP array data generated by the Therapeutically Applicable Research to Generate Effective Treatments

(TARGET) initiative (https://target-data.nci.nih.gov/) containing 341 patient neuroblastoma samples which passed quality control.

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5.2.2 JMJD6 up-regulates N-Myc and c-Myc expression in neuroblastoma cell lines

JMJD6 forms a protein complex with Brd4 (Liu W. 2013), and Brd4 is well known to activate MYC and MYCN gene transcription (Dawson 2011, Mertz 2011, Zuber 2011,

Puissant 2013). I examined whether JMJD6 modulated Myc gene expression in human neuroblastoma cell lines. The MYCN amplified neuroblastoma cell lines, BE(2)-C and CHP-

134 were transfected with JMJD6 siRNA-1 or JMJD6 siRNA-2 which targeted different regions of the JMJD6 mRNA, or SCR control siRNA. RNA was extracted from the cells after

48 hours and protein was extracted after 72 hours. RT-PCR and immunoblot analyses showed that the JMJD6 siRNAs efficiently knocked down JMJD6 expression, and reduced N-Myc mRNA and protein expression in both MYCN amplified neuroblastoma cell lines (Figure

5.2A and Figure 5.2B).

A MYCN non-amplified c-Myc highly expressing neuroblastoma cell line, SK-N-AS was transfected with the JMJD6 siRNA-1, JMJD6 siRNA-2 or SCR control siRNA. RNA was extracted from the cells after 48 hours and protein was extracted after 72 hours. RT-PCR and immunoblot analyses showed that the JMJD6 siRNAs efficiently knocked down JMJD6 expression, and reduced c-Myc mRNA and protein expression in the MYCN non-amplified neuroblastoma cell line (Figure 5.3A and Figure 5.3B).

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F 0 .0 0 .0 1 2 1 2 - - A - - A A A N A A N N N N N R iR i R R R R s i i s i i l s s l s s o o 6 6 r 6 6 r t D D t D D n J J n J J o o M M M M C J J C J J

B. BE(2)-C CHP-134

N-Myc

JMJD6

Actin

Figure 5.2. JMJD6 knockdown decreases N-Myc mRNA and protein expression.

Two MYCN overexpressing neuroblastoma cell lines, BE(2)-C and CHP-134 were transfected with either JMJD6 siRNA-1, JMJD6 siRNA-2 or SCR control siRNA. JMJD6 and N-Myc gene expression was analysed with qRT-PCR after 48hrs. JMJD6 and N-Myc protein expression was analysed by immunoblot after 72hrs. Error bars represent standard error. ** indicates p < 0.01.

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S K -N -A S S K -N -A S

c D y 1 .0

1 .0 n

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0 .8 **

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p 0 .6

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B. SK-N-AS

c-Myc

JMJD6

Actin

Figure 5.3. JMJD6 knockdown decreases c-Myc mRNA and protein expression.

A c-Myc overexpressing neuroblastoma cell line, SK-N-AS was transfected with either

JMJD6 siRNA-1, JMJD6 siRNA-2 or SCR control siRNA. JMJD6 and c-Myc gene expression was analysed with qRT-PCR after 48hrs (A). JMJD6 and c-Myc protein expression was analysed by immunoblot after 72hrs (B). Error bars represent standard error. ** indicates p < 0.01.

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Having shown that N-Myc and c-Myc were down-regulated by JMJD6 siRNA in neuroblastoma cell lines, I tested if there was any feedback effect with Myc expression modifying JMJD6 expression in neuroblastoma cells. A MYCN amplified neuroblastoma cell line, CHP-134 was transfected with N-Myc siRNA-1, N-Myc siRNA-2 or SCR control siRNA. RNA was extracted from the cells after 48 hours and protein was extracted after 72 hours. RT-PCR and immunoblot analyses showed that the N-Myc siRNAs efficiently knocked down N-Myc mRNA and protein expression, but did not reduce JMJD6 mRNA or protein expression in the CHP-134 MYCN amplified neuroblastoma cell line (Figure 5.4A and Figure 5.4C).

A MYCN non-amplified neuroblastoma cell line, SK-N-AS was transfected with c-

Myc siRNA-1, c-Myc siRNA-2 or SCR control siRNA. RNA was extracted from the cells after 48 hours and protein was extracted after 72 hours. RT-PCR and immunoblot analyses showed that the c-Myc siRNAs efficiently knocked down c-Myc mRNA and protein expression, but did not reduce JMJD6 mRNA or protein expression in the MYCN non- amplified neuroblastoma cell line (Figure 5.4B and Figure 5.4D). This demonstrates that

JMJD6 up-regulates Myc gene expression in neuroblastoma cell lines but Myc did not affect

JMJD6 gene expression.

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C H P -1 3 4 B. c S K -N -A S

A. c

y y

n n M 1 .5

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0 .5 h A

h ****

c **** ****

o 0 .0

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F 1 2 1 2 A - - A - - N A A N A A R N N iR N N i s iR iR s iR iR l l s s s s o ro r c c t c c t y y n y y n o M M o -M -M - - C

C N N c c 6

C H P -1 3 4 6 S K -N -A S

J n 1 .5 n 1 .5

o ns

i M

ns M ns ns

1 .0 1 .0

a 0 .5 0 .5

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o F F 1 2 1 2 A - - A - - N A A N A A iR N N iR N N s iR iR s iR iR l s s l s s o o tr c c tr c c n y y n y y M M o -M -M o - - C N N C c c C. CHP-134 D. SK-N-AS

JMJD6 JMJD6

N-Myc c-Myc

Actin Actin

Figure 5.4. Myc does not regulate JMJD6 expression.

The MYCN amplified neuroblastoma cell line, CHP-134 was transfected with either N-Myc

siRNA-1, N-Myc siRNA-2 or SCR control siRNA. The MYCN non-amplified

neuroblastoma cell line, SK-N-AS was transfected with either c-Myc siRNA-1, c-Myc

siRNA-2 or SCR control siRNA. JMJD6 gene expression was analysed with qRT-PCR

after 48hrs (A), and with immunoblot after 72hrs (B). Actin was analysed as a loading

control. Error bars represent standard error. *** and **** indicate p < 0.001 and 0.0001.

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5.2.3 JMJD6 induces neuroblastoma cell proliferation

As JMJD6 regulates Myc expression, next I examined the effect of JMJD6 knock down upon neuroblastoma cell proliferation. BE(2)-C, CHP-134 and SK-N-AS neuroblastoma cells were transfected with SCR control siRNA, JMJD6 siRNA-1 or JMJD6 siRNA-2 for 96 hours, followed by Alamar blue assays. Alamar blue assays showed that the

JMJD6 siRNA transfection reduced the cell numbers compared to the control siRNA in the

BE(2)-C and CHP-134 MYCN amplified neuroblastoma cell lines (Figure 5.5A) and the

CHP-134 MYCN non-amplified cell line (Figure 5.5B). This suggests that JMJD6 promotes neuroblastoma cell proliferation.

164

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r e

1 2 0 e 1 2 0

m u

u **** n

9 0 n 9 0

l l

**** l

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n ****

****

e g

g n

3 0 n 3 0

0 0

% % 1 2 1 2 A - - A - - N A A N A A N N N N iR iR s iR iR s iR iR l s s l s s o o r 6 6 r 6 6 t D D t D D n J J n J J o o M M M M C J J C J J

S K -N -A S r

e 1 2 0

b m

n 9 0

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6 0 * * * *

n i

e g

n 3 0

h c

0 % 1 2 A - - N A A N N iR s IR IR l s s o r 6 6 t D D n J J o M M C J J

Figure 5.5. JMJD6 knockdown decreases neuroblastoma cell proliferation.

Two N-Myc overexpressing neuroblastoma cell lines, BE(2)-C and CHP-134 were transfected with either JMJD6 siRNA-1, JMJD6 siRNA-2 or SCR control siRNA, followed by Alamar blue assays after 96hrs (A). A c-Myc overexpressing neuroblastoma cell line, SK-N-AS was transfected with either JMJD6 siRNA-1, JMJD6 siRNA-2 or SCR control siRNA, followed by Alamar blue cell analysis after 96hrs (B).

Error bars represent standard error. **** indicate p < 0.0001.

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5.2.4 Doxycycline-inducible JMJD6 knockdown reduces N-Myc and c-Myc gene expression and neuroblastoma cell proliferation

In order to study the effect of JMJD6 knockdown on tumour growth in vivo, I used the

GFP-FH1tUTG doxycycline inducible shRNA lentiviral vector system to establish doxycycline inducible JMJD6 shRNA stable cell lines (Herold MJ 2008). Two JMJD6 shRNA oligoes and a SCR control shRNA oligo were cloned into the GFP-FH1tUTG vector, and then transfected into 293T cells. Viral particles were used to infect CHP-134 and SK-N-

AS neuroblastoma cell lines, followed by cell sorting and selection of the top 5% GFP expressing cell fraction for the SK-N-AS cells.

Validation of the doxycycline inducible JMJD6 shRNA CHP-134 and SK-N-AS stable cells was performed by qRT-PCR and immunoblot analyses. Doxycycline treatment over 72 hours successfully knocked down JMJD6 mRNA and protein in both the JMJD6 shRNA-1 and shRNA-2 CHP-134 (Figures 5.6A and B), and the JMJD6 shRNA-1 and shRNA-2 SK-N-AS (Figures 5.7A and B) stable cell lines, compared to no effect in the SCR control shRNA cell lines. Doxycycline treatment also reduced mRNA and protein expression of N-Myc in the JMJD6 shRNA CHP-134 (Figures 5.6A and B), and c-Myc in the JMJD6 shRNA SK-N-AS (Figures 5.7A and B) cell lines compared to no effect in the SCR control shRNA cell lines.

166

C H P -1 3 4 s ta b le c e lls C H P -1 3 4 s ta b le c e lls

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1 .0 g 1 .0

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l o 0 .0 F 0 .0 l l l x l x l x l x x x o o o o o o o o o o r o r o r r r r D t D t D t D t D t D t n n n n n + + + n + o + o + o o o o A C 1 C 2 C A C -1 C -2 C - - N + A + A + N + A + A + R R 1 N 2 N -1 N -2 N A h - - A h R R s A R A R N s A A N h h l h h R l N s N s R N s N s o h o R R h r R 6 R 6 tr 6 6 s t h h s h h l n s D s D l n s D s D J J o o J J o o 6 6 r 6 6 r C M M t C M M t D D D J D J n J J J J n J J o o M M C M M C J J J J

CHP-134 B. JMJD6 Control JMJD6 shRNA-1 shRNA shRNA-2

Control DOX Control DOX Control DOX

JMJD6

N-Myc

Actin

Figure 5.6. JMJD6 shRNA knocks down JMJD6 and N-Myc mRNA and protein

expression in N-Myc overexpressing cells.

Doxycycline inducible JMJD6 shRNA-1, JMJD6 shRNA-2 and SCR control shRNA

CHP-134 cells were treated with vehicle control or 2µg/ml doxycycline for 72 hours,

followed by qRT-PCR (A) and immunoblot (B) analyses of JMJD6 and N-Myc. Error

bars represent standard error. **,*** and **** indicate p < 0.01, 0.001 and 0.0001

respectively.

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A. S K -N -A S s ta b le c e lls S K -N -A S s ta b le c e lls 1 .5 1 .5

* 6

** c * y

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s s

1 .0 1 .0

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h 0 .5

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F F 0 .0 0 .0

x l x l x l x l x l x l o o o o o o o o o o r o r o r tr tr tr D t D t D t D D D n n n n n n + + + + o + o + o o o o A C 1 C 2 C A C -1 C -2 C - - N + + + N + A + A + A A R R 1 N 2 N -1 N -2 N A h - - A h R R R R N s A A N s A h A h l h h l N N R N s N s R o s s h o R R h r R R tr 6 6 s t h 6 h 6 s h h n D D l n s D s D l s s o o J J o o J J r 6 6 r 6 M 6 M t C M M t C D D n D J D J n J J J J J J o o M M C M M C J J J J

SK-N-AS JMJD6 Control JMJD6 B. shRNA-1 shRNA shRNA-2

Control DOX Control DOX Control DOX

JMJD6

c-Myc

Actin

Figure 5.7. JMJD6 shRNA knocks down JMJD6 and c-Myc mRNA and protein

expression in c-Myc overexpressing cells.

Doxycycline inducible JMJD6 shRNA-1, JMJD6 shRNA-2 and SCR control shRNA SK-N-

AS cells were treated with vehicle control or 2µg/ml doxycycline for 72 hours, followed by

qRT-PCR (A) and immunoblot (B) analyses of JMJD6 and c-Myc. Error bars represent

standard error. * and ** indicate p < 0.05 and 0.01 respectively.

168

Having confirmed that the JMJD6 shRNA in both CHP-134 and SK-N-AS stable cell lines was doxycycline inducible and knocked down JMJD6 expression, I investigated the effect of this JMJD6 knockdown on neuroblastoma cell proliferation using Alamar blue assays (Figure 5.). Doxycycline treatment over 96 hours reduced cell numbers by >50% in the JMJD6 shRNA-2 CHP-134 and JMJD6 shRNA-2 SK-N-AS cells compared to the SCR control shRNA CHP-134 and SK-N-AS cells treated with vehicle control. The JMJD6 shRNA-1 CHP-134 cells only displayed a 20% decrease in cell number when treated with doxycycline, in comparison to the vehicle control treatment. The JMJD6 shRNA-1 SK-N-AS cells displayed no significant decrease in cell number when treated with doxycycline, in comparison to the vehicle control treatment. This shows that the JMJD6 shRNA-2 oligo had a greater effect on neuroblastoma cell proliferation compared to the JMJD6 shRNA-1 oligo.

169

C H P -1 3 4

A. %

1 5 0

s l l ****

e ns ** c

1 0 0

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m u 0 l l l o x o x o x N r r tr o t o t o n D n D n D o o o + + + C C C A -1 -2 + + + N A A A R -1 N -2 N N h s A R A R R N h N h l s s h o R R s r 6 6 l t h h n s D s D o J J tr o 6 6 n C D M D M o J J J J C M M

J J %

S K -N -A S

B. s l

l 2 0 0

e * ** c

1 5 0 ns

r 1 0 0

e b

5 0 m

u l l l x x x 0 o o o r o r o r o t t t N D D D n n n + o o o + + C 1 C 1 C 2 - + - + - + A A A 1 2 A N - N - N N R A R A R R h N h N h s s s h l R R s o h 6 h 6 l r s D s D o t r 6 J 6 J t n o D M D M n J J J J o C M M C J J

Figure 5.8. JMJD6 shRNAs decrease neuroblastoma cell proliferation in CHP-134 and

SK-N-AS stable cell lines.

Alamar blue cell viability assays were conducted to analyse the impact of JMJD6 shRNA on cell proliferation. Doxycycline inducible JMJD6 shRNA CHP-134 (A) and SK-N-AS

(B) cell lines were treated for 96hrs with 2ug/ml of doxycycline or a vehicle control. Error bars represent standard error. *,** and **** indicate p < 0.05, 0.01 and 0.0001 respectively.

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The doxycycline inducible JMJD6 shRNA CHP-134 and SK-N-AS stable cell lines were further analysed with colony formation assays JMJD6 shRNA-1, JMJD6 shRNA-2 and

SCR control shRNA CHP-134 and SK-N-AS cells were treated for 2 weeks with either doxycycline or vehicle control, then colony formation was quantified.

Doxycycline treatment in both JMJD6 shRNA-1 and shRNA-2 CHP-134 cell lines

(Figure 5.9), reduced colony formation by 90% in comparison to the vehicle control treatment. Doxycycline treatment in the JMJD6 shRNA-1 and shRNA-2 SK-N-AS cell lines displayed reduced colony formation of 50% and 90% respectively, in comparison to the vehicle control treatment (Figure 5.10). The SCR control SK-N-AS cell line did not display a significant reduction in colony formation between the doxycycline or vehicle control treatments.

The JMJD6 shRNA-2 oligo showed a greater decrease in colony formation compared to the JMJD6 shRNA-1 oligo in both CHP-134 and SK-N-AS neuroblastoma cell lines, similar to the previous Alamar blue assay results. Notably the JMJD6 shRNA-1 SK-N-AS cells displayed the poorest reduction in colony formation when treated with doxycycline.

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A. CHP-134 stable cell lines

Control JMJD6 JMJD6 shRNA shRNA-1 shRNA-2

Vehicle Control

Doxycycline

2ug/ml, 2wks d

B. e C H P -1 3 4 s ta b le c e lls m

r 1 5 0 o

f ****

s ****

e 1 0 0

o l

o 5 0

l l l x o X o X o r r % 0 r o t t t O O D n D n D n o o o + + + C C C A 1 2 + - + - + N 1 A 2 A R - - A N N h A A N s R R R l N h N h h o R s R s r s t h 6 h 6 l s s o n D D r o 6 J 6 J t C D D n J M J M o J J M M C J J

Figure 5.9. JMJD6 shRNAs reduce neuroblastoma colony formation.

Doxycycline inducible JMJD6 shRNA-1, JMJD6 shRNA-2 and SCR control shRNA CHP-

134 cell lines were treated for 2 weeks with either 2ug/ml of doxycycline or vehicle control.

Treatment media was refreshed every 3-4 days. Colonies were analysed with colony

formation assay and quantified using Quantity One. Error bars represent standard error.

**** indicate p < 0.0001.

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A. SK-N-AS stable cell lines

Control JMJD6 JMJD6 shRNA shRNA-1 shRNA-2

Vehicle Control

Doxycycline 2ug/ml, 2wks

d S K -N -A S s ta b le c e lls e

m 1 5 0

r **

o **

e 1 0 0

l o

c 5 0

l l l % x o x o x o r r 0 r o t o t o t D n D n D n o o o + + + C C C 1 2 A + - + - + N A A 1 2 A R - N - N N h A R A R s R N h N h l s s h o R R r s t h 6 h 6 l s D s D o n r o 6 J 6 J t C D M D M n J J J J o M M C J J

Figure 5.10. JMJD6 shRNAs reduce neuroblastoma colony formation.

Doxycycline inducible JMJD6 shRNA-1, JMJD6 shRNA-2 and SCR control shRNA SK-N-

AS cell lines were treated for 2 weeks with either 2ug/ml of doxycycline or vehicle control.

Treatment media was refreshed every 3-4 days. Colonies were analysed with colony

formation assay and quantified using Quantity One. Error bars represent standard error. **

indicate p < 0.01.

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5.2.5 JMJD6 shRNA reduces neuroblastoma tumour progression and improves overall survival in vivo

To exclude potential off-target effects of the JMJD6 shRNAS, the doxycycline- inducible JMJD6 shRNA-1 CHP-134 and JMJD6 shRNA-2 SK-N-AS stable cell lines were selected for in vivo experiments. Each stable cell line was injected into the flanks of 24

Balb/c nude mice, with a total of 48 Balb/c nude mice used. The mice were further separated into doxycycline treatment or control treatment sub-groups of 12 mice each. Once tumours reached 50mm3 each mouse was moved to a treatment cage containing either doxycycline feed (600mg/kg) or control feed. Tumour growth was measured every two days using calipers with tumour volume calculated by (length x width x height)/2 (Monga 2000). Mice were culled once tumour volume reached 1cm3.

The doxycycline treatment sub-group displayed slower rates of tumour growth in comparison to the control treatment group in both the doxycycline-inducible JMJD6 shRNA-

1 CHP-134 (Figure 5.11A) and JMJD6 shRNA-2 SK-N-AS xenografts (Figure 5.11B). The

JMJD6 shRNA-1 CHP-134 xenografts displayed a consistently lowered tumour growth rate when treated with doxycycline (Figure 5.11A). In comparison the JMJD6 shRNA-2 SK-N-

AS xenografts displayed a pause in tumour growth when treated with doxycycline followed by tumour growth resuming at a rate slightly slower than the control treatment group (Figure

5.11A).

Kaplan-Meier survival analysis showed that doxycycline treatment of the JMJD6 shRNA-1 CHP-134 xenografts increased overall survival probability by 50% compared to the control treatment (Figure 5.11C). The JMJD6 shRNA-2 SK-N-AS xenografts displayed a

174

>50% increase in overall survival probability in comparison to the control treatment (Figure

5.11D).

175

A. J M J D 6 s h R N A -1 B. J M J D 6 s h R N A -2 C h P -1 3 4 c e ll x e n o g ra fts S K -N -A S c e ll x e n g ra fts

1 5 0 0 1 5 0 0

C o n tro l tre a tm e n t: C o n tro l tre a tm e n t:

)

) 3

3 N o rm a l fe e d N o rm a l fe e d m

1 0 0 0 D o x y c y c lin e m 1 0 0 0 D o x y c y c lin e

(

tre a tm e n t: D o x tre a tm e n t: D o x

e m

fe e d 6 0 0 m g /k g m fe e d 6 0 0 m g /k g

5 0 0 r 5 0 0

T T

0 0 0 1 0 2 0 3 0 4 0 5 0 0 1 0 2 0 3 0 4 0 T re a tm e n t D a y s T re a tm e n t D a y s

C. D. J M J D 6 s h R N A -1 J M J D 6 s h R N A -2 C H P -1 3 4 c e ll x e n o g ra fts S K -N -A S c e ll x e n o g ra fts

y D o x tre a tm e n t y

t D o x tre a tm e n t

l l i 1 .0 0 i 1 .0 0

b (n = 1 2 )

a b

C o n tro l tre a tm e n t b C o n tro l tre a tm e n t o

0 .7 5 o

r 0 .7 5 r

p (n = 1 1 ) p

(n = 1 2 )

v v i 0 .5 0 p < 0 .0 0 0 1

i 0 .5 0 p < 0 .0 0 0 1

0 .2 5

l 0 .2 5

e e

v 0 .0 0

v 0 .0 0 O 0 1 0 2 0 3 0 4 0 5 0 O 0 1 0 2 0 3 0 4 0 T re a tm e n t D a y s T re a tm e n t D a y s

Figure 5.11. Knocking down JMJD6 decreases tumour progression and improves overall

mouse survival.

JMJD6 shRNA-1 CHP-134 and JMJD6 shRNA-2 SK-N-AS stable cells were each injected

into the flanks of 24 Balb-c nude mice. Each group was divided into either a treatment or

control sub-group consisting of 12 mice with treatment beginning once tumours reached

50mm3 in volume. Mice were fed with 600mg/kg doxycycline feed or control feed. Tumour

volume was calculated using (Length x Width x Height)/2 and tumour growth was measured

every two days using calipers (A). Mice were culled when tumour volume reached 1cm3.

Kaplan-Meier curves were plotted to analyse the effect of knocking down JMJD6 on overall

mouse survival (B).

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At the conclusion of the in vivo experiment, the mice were culled, the tumour tissue snap frozen and protein extracted. Immunoblot analysis showed that both the JMJD6 shRNA

CHP-134 (Figure 5.12A and B) and SK-N-AS (Figure 5.13A and B) tumours displayed a decrease in JMJD6 protein expression as a result of doxycycline treatment compared to the control treatment. The protein expression of N-Myc in JMJD6 shRNA-1 CHP-134 tumours

(Figure 5.12A) and c-Myc in JMJD6 shRNA-2 SK-N-AS tumours (Figure 5.13A) was also reduced as a result of doxycycline treatment, compared to the control treatment.

The JMJD6, N-Myc and c-Myc protein expression of each individual CHP-134 and

SK-N-AS tumour varied within the two treatment groups due to the heterogeneity of each individual tumour and only a fraction of the whole tumour being used for immunoblot analysis. Thus immunoblot results were quantified using the Quantity One program for the doxycycline and control treatment groups. This showed a statistically significant reduction in

JMJD6 protein expression of the doxycycline treatment group in comparison to the control treatment group in both CHP-134 and SK-N-AS tumours. N-Myc protein expression was shown to be significantly decreased in JMJD6 shRNA-1 CHP-134 tumours treated with doxycycline compared to control feed (Figure 5.12B). The protein expression of c-Myc in

JMJD6 shRNA-2 SK-N-AS tumours was also significantly reduced with doxycycline treatment compared to control treatment (Figure 5.13B).

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A. JMJD6 shRNA-1 CHP-134 cell xenografts

Doxycycline Vehicle control

JMJD6

N-Myc

Actin

B. J M J D 6 s h R N A -1 J M J D 6 s h R N A -1 C h P -1 3 4 c e ll x e n o g ra fts C h P -1 3 4 c e ll x e n o g ra fts 2 .5 2 .5

n ** *

t t

c 2 .0 2 .0

/ /

1 .5 1 .5

c y

D 1 .0 1 .0

M -

M 0 .5 0 .5

N J 0 .0 0 .0 l x l x o o o o tr tr n D n D o o c c le le ic ic h h e e V V

Figure 5.12. JMJD6 shRNA decreases JMJD6 and N-Myc protein expression in CHP-

134 neuroblastoma xenografts.

JMJD6 shRNA-1 CHP-134 tumour tissues were analysed using immunoblot after each individual mouse was culled. Protein expression of JMJD6, N-Myc and Actin loading control was examined (A). The immunoblots were quantified using Quantity One (B). Error bars represent standard error. * and ** indicate p < 0.05 and 0.01 respectively.

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A. JMJD6 shRNA-2 SK-N-AS cell xenografts

Doxycycline Vehicle control

JMJD6

c-Myc

Actin

B. J M J D 6 s h R N A -2 J M J D 6 s h R N A -2 S K -N -A S c e ll x e n o g ra fts S K -N -A S c e ll x e n o g ra fts

2 .5 2 .5

n n i *

i **

t t

c 2 .0 2 .0

/ 1 .5

1 .5

6 **

* c y

D 1 .0 1 .0

- M

0 .5 c 0 .5 J 0 .0 0 .0 l l x o x ro o r o t t D n D n o o c c le le ic ic h h e e V V

Figure 5.13. JMJD6 shRNA decreases JMJD6 and c-Myc protein expression in SK-N-AS neuroblastoma xenografts.

JMJD6 shRNA-2 SK-N-AS tumour tissues were analysed using immunoblot after each individual mouse was culled. Protein expression of JMJD6, c-Myc and Actin loading control was examined (A). The immunoblots were quantified using Quantity One (B). Error bars represent standard error. * and ** indicate p < 0.05 and 0.01 respectively.

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5.2.6 JMJD6 expression positively correlates to Myc expression in human neuroblastoma tissues

To assess clinical relevance of JMJD6 expression in human neuroblastoma tissues, I investigated JMJD6 gene expression in human neuroblastoma tissues in publically available

Kocak (Oberthuer 2010, Kocak 2013) and Versteeg (Molenaarm 2012) microarray gene expression datasets consisting of 476 and 88 human neuroblastoma patients samples respectively. The Kocak dataset contains single colour gene expression profile data from 476 neuroblastoma patients with prognosis information, generated using the 44K oligonucleotide microarray and accessible through GEO ID gse45547 and the R2 platform (http://r2.amc.nl).

The Versteeg dataset is directly downloadable from http://r2.amc.nl. Two-sided Pearson’s correlation study showed that JMJD6 mRNA expression correlated to N-Myc mRNA expression in both Kocak and Versteeg human neuroblastoma tissue microarray datasets

(Figure 5.14A).

In addition, a two-sided Pearson’s correlation study of the MYCN non-amplified sub- population from the Kocak dataset, consisting of 404 neuroblastoma patient samples, showed that JMJD6 mRNA expresssion correlated with c-Myc mRNA expression (Figure 5.14B).

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A K o c a k d a ta s e t (a ll s a m p le s ) V e e rs te g d a ta s e t (a ll s a m p le s )

1 0

)

) 2

2 1 3

A o

o 9

(

1 1

6 s

s 8

p J

J 9 x

x 7 e e R = 0 .2 2 7 3 R = 0 .2 2 7 3 p < 0 .0 0 0 1 p < 0 .0 0 0 1 7 6 5 1 0 1 5 2 0 6 8 1 0 1 2 1 4

N -M y c m R N A e x p re s s io n (lo g 2 ) N -M y c m R N A e x p re s s io n (lo g 2 )

K o c a k d a ta s e t (M Y C N n o n -a m p lifie d s a m p le s )

1 3

)

(

R 1 1

e r

M 9

p J

x R = 0 .1 9 6 e p < 0 .0 0 0 1 7 1 0 1 5 c -M y c m R N A e x p r e s s io n (lo g 2 )

Figure 5.14. JMJD6 expression correlates to Myc expression in human neuroblastoma patient samples.

Correlation between JMJD6 mRNA expression and N-Myc mRNA expression in tumour tissues from 88 and 476 neuroblastoma patients in the publically available microarray gene expression Kocak and Versteeg datasets respectively (A). Correlation between JMJD6 mRNA expression and c-Myc mRNA expression in tumour tissues from 404 MYCN non-amplified neuroblastoma patients in the Kocak dataset (B). Accessed using the R2 microarray analysis and visualization platform (http://r2.amc.nl).

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Kaplan-Meier survival analysis showed that high levels of JMJD6 mRNA expression in tumour tissue were associated with poor patient prognosis, using a median JMJD6 mRNA expression as the cut-off point in the Kocak human neuroblastoma tissue microarray dataset

(Figure 5.15A). Using top and bottom quartile JMJD6 gene expression as the cut-off points,

Kaplan-Meier survival analysis also showed that high JMJD6 mRNA expression levels in tumour tissues were associated with poor patient prognosis (Figure 5.15B).

182

A K o c a k d a ta s e t

(C u t-o ff: M e d ia n e x p r e s s io n )

i b

a 1 .0 0 L o w J M J D 6 (n = 2 3 8 )

o r

p 0 .7 5 p < 0 .0 0 0 1

a v

i 0 .5 0

v H ig h J M J D 6 (n = 2 3 8 )

r u

s 0 .2 5

a r

e 0 .0 0

v 0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0 O D a y s

B K o c a k d a ta s e t K o c a k d a ta s e t

(C u t o ff: to p q u a r tile e x p r e s s io n ) (C u t o ff: b o tto m q u a r tile e x p r e s s io n )

l i

b L o w J M J D 6 (n = 3 5 7 )

b L o w J M J D 6 (n = 1 1 9 )

a 1 .0 0

r o

r p < 0 .0 0 0 1

p 0 .7 5

p 0 .7 5 l

p < 0 .0 0 0 1

v i

0 .5 0 v i

v 0 .5 0 r

v H ig h J M J D 6 (n = 3 5 7 )

u u s 0 .2 5

H ig h J M J D 6 (n = 1 1 9 ) s

l 0 .2 5

a r

e 0 .0 0

e 0 .0 0 v

0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0 v

O 0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0

D a y s O D a y s

Figure 5.15. High JMJD6 expression in human neuroblastoma tissues correlates to poor

patient prognosis.

Kaplan–Meier survival analysis examining the probability of overall survival of patients

according to the median level of JMJD6 expression in the 476 neuroblastoma patients in the

Kocak human neuroblastoma dataset (A). Top and bottom quartile were used as cut offs for

JMJD6 expression for Kaplan–Meier analysis of the Kocak dataset (B).

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Based on the Kaplan-Meier curves, I further analysed the Kocak human neuroblastoma tissue microarray dataset to determine if high JMJD6 expression was an independent prognostic factor for patient outcome in neuroblastoma. I used multivariate COX regression modelling to compare the effect of JMJD6 gene expression on overall survival and event free survival to the four accepted neuroblastoma risk factors: age of diagnosis >12 months, disease staging and MYCN gene amplification. Median, upper quartile and lower quartile cut offs were used for high JMJD6 mRNA expression. This showed that high JMJD6 mRNA expression in human neuroblastoma tissues was a statistically significant independent prognostic factor for poor patient outcome (Table 5.1).

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Table 5.1: High JMJD6 gene expression is an independent prognostic factor for poor

patient outcome in neuroblastoma

Overall survival Event-free survival

Factor

Hazard ratio P value Hazard ratio (95% CI) P value (95% CI)

High JMJD6 expression 4.80 (2.27 – 10.18) 4.26E-05 1.65 (1.13 – 2.42) 0.010009 (median cut off)

Age > 12 months 3.26 (1.81 – 5.88) 8.79E-05 1.66 (1.14 – 2.43) 0.008548

Stage 3 & 4 2.82 (1.41 – 5.64) 0.003435 2.43 (1.61 – 3.69) 2.59E-05

MYCN gene 3.19 (2.06 – 4.94) 2.16E-07 1.87 (1.28 -2.73) 0.001223

amplification

High JMJD6 expression 4.52 (1.41 – 14.43) 0.010963 1.17 (1.03 – 2.84) 0.038321

(lower quartile cut off)

Age > 12 months 3.77 (2.09 – 6.80) 9.7E-06 1.75 (1.20 – 2.55) 0.00345

Stage 3 & 4 3.24 (1.63 – 6.45) 0.00082 2.50 (1.65 – 3.77) 1.33E-05

MYCN gene 3.50 (2.25 – 5.44) 2.68E-08 1.96 (1.34 – 2.86) 0.000488

amplification

High JMJD6 expression 1.87 (1.16 – 3.01) 0.010162 1.56 (1.07 – 2.27) 0.01973

(upper quartile cut off)

Age > 12 months 3.55 (1.94 – 6.48) 3.93E-05 1.66 (1.13 – 2.44) 0.010185

Stage 3 & 4 3.17 (1.57 – 6.43) 0.001352 2.45 (1.62 – 3.73) 2.6E-05

MYCN gene 3.11 (1.97 – 4.91) 1.02E-06 1.78 91.2 – 2.63) 0.004215

amplification

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Multivariate Cox regression modelling of the Kocak data set, with the level of JMJD6 expression considered high or low in relation to the median level of expression in all tumours.

Hazard ratios were calculated as the antilogs of the regression coefficients in the proportional hazards. Multivariable analysis was performed following the inclusion of four factors: high

DOT1L expression, age of diagnosis >12 months, neuroblastoma tumour staging and MYCN gene amplification, into the Cox regression model. P value was obtained from the two sided log-rank test. Tumour stage was categorized as favorable (INSS stages 1, 2, and 4S) or unfavorable (INSS stages 3 and 4).

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5.3 Discussion

In this chapter, I have found that JMJD6 gene gain occurs in approximately one quarter of human neuroblastoma tissues, and that MYCN amplification and JMJD6 gene gain frequently co-occur in human neuroblastoma tissues with > 60% of MYCN amplified neuroblastoma tumours also having JMJD6 gene gain.

Unbalanced 17q21-ter gain is one of the most important chromosome abnormalities in human neuroblastoma tissues, and is more common in MYCN amplified neuroblastoma tumours than MYCN non-amplified tumours (Caron 1995, Bown 1999, Trakhtenbrot 2002,

Vandesompele 2005). A mechanism for 17q21-ter gain-mediated neuroblastoma progression has not been found but candidates have been suggested in the literature. A novel non-coding

RNA, ncRAN has been mapped to the chromosome 17q25.1 and shown to be associated with poor neuroblastoma patient prognosis (Yu 2009). Survivin, an inhibitor of apoptosis protein whose expression is cell cycle regulated has also been mapped to 17q25 and is associated with poor patient prognosis (Islam 2000). As the JMJD6 gene is located on chromosome 17 at the q25 position (http://www.uniprot.org/docs/humchr17), gain of 17q21-ter would lead to

JMJD6 gene gain and overexpression.

Here I have shown that JMJD6 upregulates N-Myc mRNA and protein expression in

MYCN amplified neuroblastoma cell lines and c-Myc expression in a MYCN non-amplified neuroblastoma cell line. However neither N-Myc or c-Myc knockdown reduces JMJD6 gene expression. MYC and MYCN gene transcription has been reported to be regulated by the bromodomain protein Brd4, with Brd4 activating MYC and MYCN gene transcription by binding to their gene promoters and enhancers (Dawson 2011, Mertz 2011, Zuber 2011,

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Lovén 2013, Puissant 2013). JMJD6 and Brd4 have been found to co-bind distal anti-pause enhancers to regulate the promoter-proximal pause release of transcription complexes via long range interactions and therefore enhance target gene expression (Liu W. 2013). My results suggest that JMJD6 up-regulaes MYC and MYCN gene expression by forming a protein complex with Brd4 at their gene enhancers. This represents a potential molecular mechanism for 17q21-ter gain to promote neuroblastoma tumourigenesis via JMJD6 up- regulation of N-Myc and c-Myc transcription in neuroblastoma.

In this chapter, JMJD6 knock down was shown to reduce cell proliferation in neuroblastoma cell lines. Colony formation assays showed that knocking down JMJD6 expression with Dox-inducible JMJD6 shRNAs considerably reduced the colony formation capacity of neuroblastoma cell lines. Crucially, knocking down JMJD6 expression using two independent Dox-inducible shRNA oligoes considerably reduced tumour progression in mice xenografts. Furthermore, immunoblot analysis confirmed that treatment with Dox reduced

JMJD6, N-Myc and c-Myc protein expression in tumour tissues from mice xenografted with

Dox-inducible JMJD6 shRNA neuroblastoma cells. These data demonstrate that JMJD6 induced neuroblastoma cell proliferation in vitro and tumour progression in vivo, at least partially through up-regulation of N-Myc and c-Myc expression.

Previously, JMJD6 knockout in mice resulted in developmental defects and fetal death (Li 2003, Böse 2004, Kunisaki 2004). The cause of death in all three mouse models was attributed to impaired heart muscle differentiation. JMJD6 knockdown and subsequent rescue in zebrafish also confirmed the role of JMJD6 in development and organogenesis

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(Hong 2004). In addition, JMJD6 has been shown to promote colon cancer by hydroxylating p53, resulting in its inactivation (Wang 2014).

In this project, I have found that JMJD6 mRNA expression correlates to N-Myc mRNA expression in the Kocak human neuroblastoma tissue gene expression microarray dataset. A previous report has found that human neuroblastomas with unbalanced 17q gain had the highest MYCN amplification (Kuzyk 2015). It also found that MYCN non-amplified neuroblastomas with numerical gain of 17q had low MYCN expression, however they did not investigate c-Myc expression in this tumour subset. Here I have demonstrated that JMJD6 mRNA expression correlated to c-Myc mRNA expression in the MYCN non-amplified sub- group of the Kocak human neuroblastoma tissue microarray dataset.

Neuroblastoma with numerical gain of chromosome 17 have a better prognosis compared to those with no gain or unbalanced partial gain (Theissen 2014). Gain of chromosome are 17q21-ter is the most common chromosomal alteration in neuroblastoma and is associated with advanced disease stage, age at diagnosis > 1 year old, deletion of chromosome 1p and MYCN amplification, all of which predict poor patient outcome (Bown

1999, Bown 2001, George 2007). Importantly, multivariate analysis has shown that 17q21-ter gain in human neuroblastoma tissues is a powerful independent prognostic factor for poor patient survival (Bown 1999).

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In the current study, multivariate analysis demonstrates that high JMJD6 mRNA expression is a prognostic factor of poor patient outcome, independent of MYCN amplification, age at diagnosis and neuroblastoma disease staging. High JMJD6 expression has been also been linked to poor prognosis in breast, colon, lung and oral cancers (Zhang J.

2013, Wang F. 2014, Lee 2015, Poulard C 2015). JMJD6 was found to be highly expressed in aggressive breast tumours, with high JMJD6 expression associated with poor disease free survival (Poulard C 2015). In colon cancer, JMJD6 was found to promote tumourigenesis via negative regulation of p53 by hydroxylation of lysine 382 (Wang F. 2014). High JMJD6 expression was shown to correlate to tumour size, pathological grade, pN status, pT status and pleural invasion in lung adenocarcinoma (Zhang J. 2013). JMJD6 was found to be highly expressed in human oral squamous cell carcinoma cell lines, with JMJD6 knockdown found to suppress the self-renewal capacity and anchorage independent growth (Lee 2015). This shows that high JMJD6 gene expression correlates to poor patient survival in a range of cancers beyond neuroblastoma and demonstrates that JMJD6 could be a potential molecular target for anti-cancer treatments.

In conclusion, I have shown that JMJD6 upregulates N-Myc and c-Myc expression in neuroblastoma. JMJD6 increases neuroblastoma cell proliferation in vitro and tumour progression in vivo. High JMJD6 mRNA expression is a prognostic factor of poor patient outcome, independent of MYCN amplification, age at diagnosis and neuroblastoma disease staging. This indicates that JMJD6 is a candidate gene overexpressed from 17q21-ter chromosome gains in neuroblastoma, driving Myc overexpression and neuroblastoma tumourigenesis and tumour progression.

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Chapter 6. Final Discussion

6.1 General discussion

c-Myc and N-Myc are therapeutic targets due to their role as master regulators of a diverse range of cellular functions driving cancer initiation and progression (Whyte 2013).

MYC is the most frequently over-expressed oncogene in human cancers. N-Myc is a key oncogenic transcription factor driving neuroblastoma(Brodeur 2003, Murphy 2008). N-Myc protein overexpression is caused by amplification of the MYCN oncogene at chromosome

2p24 in roughly half of non-localised neuroblastoma cases, and MYCN gene amplification is associated with rapid tumour progression and poor outcome in neuroblastoma patients

(Brodeur 1995, Bordow 1998, Katzenstein 1998, Huang 2013). A prospective Children’s

Cancer Group study, CCG-3881 showed that patients with MYCN non-amplified tumours had a 93 ± 4% EFS, in comparison those with amplified MYCN copy number had a 10 ± 7% EFS

(Schmidt 2000).

MYCN amplification is identified at a lower frequency in other neuronal tumours, such as astrocytoma carcinoma, glioblastoma, retinoblastoma and small cell lung carcinoma

(Savelyeva 2001, Schwab 2004). Amplified copies of the oncogene MYCN can display a non- telomeric extra-chromosomal structure known as double minutes or an intra-chromosomal structure (Itoh 1998, Yoshimoto 1999). Fluorescent in situ hybridisation has been used in a clinical setting to examine potential amplication of the MYCN gene at chromosome 2p24

(Mathew 2001).

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Amplification of the MYCN gene has been shown to been linked with the amplification of other oncogenes. The DEAD (Asp-Glu-Ala-Asp) box helicase 1 (DDX1) gene, located at the 400 kb region on the fifth edge of the MYCN gene has been found to be co-amplified in approximately 50% of MYCN amplified neuroblastoma and retinoblastoma tumours (Godbout 1993, Godbout 2007). The ALK gene localised at chromosome 2p23 has also been shown to be co-amplified with MYCN in 22.8% of neuroblastoma tissues (Mossé

2008).

Here in Chapter 5, I have shown that the JMJD6 gene, located on chromosome 17q25, is gained in 62.9% of MYCN–amplified and 16.1% of MYCN-non-amplified human neuroblastoma tissues. Knocking down JMJD6 expression reduces N-Myc in MYCN amplified neuroblastoma cell lines and c-Myc in MYCN non-amplified cell lines. This reduction in JMJD6 expression reduces neuroblastoma cell proliferation in vitro and tumour progression in vivo.

Amplification of chromosome 2p24 commonly co-occurs with gain of chromosome

17q21-ter (Bown 1999, Trakhtenbrot 2002). Recently the insulin-like growth factor-2 mRNA-binding protein 1 (IGF2BP1) gene, located on chromosome 17q21 was reported to be over-expressed due to chromosomal 17q21-ter gain with potential oncogenic effects, through post-transcriptionally increasing N-Myc mRNA expression (Bell 2015). My findings in

Chapter 5 shows that JMJD6 is a candidate oncogene overexpressed from 17q21-ter chromosome gains in neuroblastoma, responsible for further upregulating N-Myc expression in MYCN amplified neuroblastomas and c-Myc in MYCN non-amplified neuroblastomas, as well as promoting neuroblastoma progression.

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Previously high JMJD6 expression in tumour tissues has been linked to poor patient prognosis in breast, colon and lung cancers (Zhang 2013, Wang 2014, Poulard 2015). In this study, I have found that high JMJD6 expression in tumour tissues correlated to poor overall survival, and served as a prognostic factor for neuroblastoma patient prognosis, independent of traditional neuroblastoma prognostic factors: age at the time of diagnosis (>12 months), unfavourable staging (INSS stages 3 and 4) and MYCN amplification.

N-Myc regulates target gene transcription either directly or indirectly. N-Myc indirectly mediates the expression of multiple genes simultaneously via activation of noncoding RNAs, such as miRNA and long non-coding RNAs (Chen 2007, Schulte 2008, Liu

2015). Direct Myc regulation was demonstrated by c-Myc binding to the cofactor Max to form heterodimers that were first reported to directly bind with high affinity to two adjacent, consensus E-boxes in the promoter of the rat ODC gene (Walhout 1997). Genes knocked down by N-Myc shRNA have been shown to possess E-box sequences in their promoter regions suggesting they were direct N-Myc targets (Alaminos 2003). DNA polymorphisms near the E-boxes in the ODC1 gene promoter have been found to inhibit MYC/Max binding, most notably a SNP of A instead of G located 317 base pairs downstream of the transcription start site in intron 1 (Guo 2000). In quiescent cells, E-box sites are occupied by the inactive

Mnt/Max complex resulting in low levels of N-Myc target gene transcription (Smith 2004).

These studies establish the role of E-boxes as direct c-Myc/N-Myc protein binding sites in target gene promoters.

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Myc-Max heterodimers interact with a variety of co-activator proteins to influence chromatin structure and activities of RNA polymerase I, II and III to promote transcription of

Myc downstream target genes to drive neuroblastoma tumour progression (Knoepfler 2006).

Previous reports using ChIP-Seq found that Myc binding site recognition was determined by chromatin context (Guccione 2006, Martinato 2008). H3 acetylation and H3K79 methylation at E-boxes of Myc target gene promoters were found to be pre-requisites for Myc binding.

This was confirmed experimentally here in Chapter 3 with DOT1L-mediated H3K79 methylation demonstrated to promote N-Myc protein binding to E-boxes located in the gene promoter regions of N-Myc target genes, E2F2 and ODC1, causing their consequent overexpression. Knockdown of DOT1L reduced H3K79 di-methylation at the target gene promoters and reduced N-Myc binding to E-boxes at the target gene promoters, leading to reduced neuroblastoma cell proliferation and tumour progression. This corresponds with a recent report that DOT1L binds with c-Myc to upregulate p300 acetyltransferases in breast cancer (Cho 2015).

In Chapter 3, E2F2, ODC1 and DOT1L were demonstrated to be N-Myc target genes, upregulated by N-Myc in MYCN amplified neuroblastoma cell lines. Thus E2F2, a member of the E2F protein family involved in cell cycle regulation with the activation of G1 phase

Cdks (Kovesdi 1986, Ivey-Hoyle 1993, Nevins 2001), is confirmed as an N-Myc target gene in MYCN amplified neuroblastoma. DOT1L-mediated H3K79 methylation results in N-Myc recruitment to an E-box in the E2F2 gene promoter, leading to E2F2 overexpression.

Knockdown of DOT1L leads to reduced neuroblastoma cell proliferation in vitro and tumour progression in the doxycycline inducible DOT1L shRNA neuroblastoma cell mouse xenograft model, and knockdown of E2F2 leads to reduced neuroblastoma cell proliferation

194 in vitro. However the mouse model used in Chapter 3 did not examine neuroblastoma tumour initiation. In the literature, E2F2 knockdown in glioblastoma cells in vivo and in a breast cancer mouse model reduces tumourigenesis (Fujiwara 2011, Nakahata 2014), raising a possibility of E2F2 playing a role in neuroblastoma tumour initiation and progression. My data therefore suggest that E2F2 is an N-Myc and DOT1L target gene in neuroblastoma and that up-regulation of E2F2 is partly responsible for DOT1L and N-Myc-mediated neuroblastoma cell proliferation and tumour progression.

ODC1 is a pyridoxial phosphate dependant amino acid decarboxylase, and is essential for polyamine synthesis de novo in mammals (Auvinen 1992, Bettuzzi 1999). Due to this critical role, the ODC1 gene is highly regulated by a range of growth factors including c-Myc and N-Myc (Coleman 1994). The ODC1 gene promoter region contains multiple sequences that allow protein binding, such as a TATA box, cAMP response element, AP-1 and AP-2 sites, CAAT and LSF motifs, GC-rich p1 binding sites, and two E-boxes (Zhao 2001, Qin

2004). The two E-boxes, with sequence CACGTG, allows the binding of the MYC/ Max transcription factor to the ODC1 gene promoter, with mRNA transcription activated when

MYC levels are elevated (Packham 1997, Nilsson 2004).

In Chapter 3, I demonstrated that DOT1L mediated H3K79 di-methylation results in

N-Myc protein recruitment to the two E-boxes at the ODC1 gene promoter. This demonstrates an additional layer of control for ODC1 gene expression and polyamine synthesis in neuroblastoma. ODC1 is a potential molecular drug target to inhibit polyamine synthesis, with inhibition of ODC1 by difluoromethylornithine (DFMO) resulting in decreased tumour penetrance in TH-MYCN mice treated pre-emptively (Gamble 2012).

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DFMO has displayed synergistic effects in combination with chemotherapy in treating established tumours in TH-MYCN transgenic mouse models and recently completed stage 1 clinical trials targeting polyamine addiction in relapsed/refractory neuroblastoma patients

(Saulnier Sholler 2015). MYCN non-amplified high risk neuroblastoma tumours were reported to overexpress ODC1, in comparison to lower risk tumours, with elevated ODC1 gene expression associated with poor patient prognosis, independent of N-Myc amplification in a human neuroblastoma tissue dataset (Hogarty 2008). This could be due to the activity of c-Myc and DOT1L in MYCN non-amplified neuroblastoma, which could be explored in future through treatment of neuroblastoma with small molecule DOT1L inhibitors.

Future experiments involving site directed mutagenesis of DOT1L would be required to reveal the precise binding site of DOT1L to N-Myc, and the importance of this protein- protein interaction to N-Myc mediated gene transcription. A possible candidate site is a 10 amino acid region of human DOT1L (865-874) that has been identified as the AF9/ENL binding site (Shen 2013). Two additional binding sites between DOT1L and MLL-AF9 have also been found, with point mutations of these sites leading to a graded reduction in DOT1L recruitment to MLL-AF9, with differential loss of H3K79me2 and H3K79me3 at MLL-AF9 target genes (Kuntimaddi 2015).

In Chapter 4, high DOT1L gene expression in tumour tissues was shown to correlate with lower overall survival in both an inducible DOT1L shRNA mouse xenograft model and human neuroblastoma tissue microarray datasets. High DOT1L gene expression was found to be a prognostic marker for poor patient outcome independent of traditional neuroblastoma

196 prognostic factors: age at the time of diagnosis (>12 months), unfavourable staging (INSS stages 3 and 4) and MYCN amplification. This makes DOT1L a potential molecular target for treatment of MYCN amplified neuroblastoma.

Small molecular DOT1L inhibitors have already been synthesized for treatment of

MLL gene rearranged leukemia (Okada 2005, Krivtsov 2008, Daigle 2011). In MLL rearranged leukemia the onco-MLL loses its C-terminal tail and fuses with AF4, AF9, AF10 or ENL partner proteins, which recruit DOT1L causing abnormal H3K79 methylation. This leads to overexpression of the MLL target genes HOXA9 and Meis1, leading to leukemogenesis. Small molecular DOT1L inhibitors have been reported with EPZ004777 designed by Epizyme using a traditional ligand-based approach based on the DOT1L substrate SAM and the product SAH (Daigle 2011). Modifications to EPZ00477 lead to the synthesis of EPZ5676 (Daigle 2013) and SGC0946 (Yu 2012). EPZ5676 is currently undergoing clinical trials for the treatment of MLL rearranged leukemia.

In Chapter 3, the DOT1L inhibitor, SGC0946 reduced clonogenicity of a MYCN amplified neuroblastoma cell line after 12 days of treatment at 1.35uM. This reduction in clonogenicity was poor compared to the reported 60% decrease in cell viability when treated with 1uM of SGC0946 in mixed lineage leukemia cell lines (Yu 2012). An alternative drug design strategy would be targeting protein-protein binding of DOT1L to both N-Myc and c-

Myc. Studies of DOT1L binding to MLL-AF9 and AF9/ENL suggest possible candidate protein-binding sites on the DOT1L protein (Shen 2013, Kuntimaddi 2015). Thus blocking

DOT1L protein binding to Myc could be an alternate strategy to target the Myc-driven tumour progression including neuroblastoma.

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N-Myc up-regulate genes expression through maintaining active chromatin via widespread histone acetylation and methylation across the genome (Knoepfler 2006). On the other hand, N-Myc represses the transcription of different sets of genes through several different mechanisms. N-Myc interacts with DNA (Cytosine-5-)-Methyltransferase 3 Alpha

(DNMT3A), Enchancer of Zeste 2 Polycomb Repressive Complex 2 Subunit (EZH2) and various histone deacetylases (HDACs) (Seoane 2001, Liu 2007, Sander 2008). N-Myc is recruited by Miz-1 to target gene promoters, such as p15INK4B, a transcriptonal initiator leading to transcriptional silencing in part by recruitment of DNMT3A (Seoane 2001). Myc and DNMT3A have been found to form a ternary complex with Miz-1 which co-represses the p21Cip1 promoter (Brenner 2005). N-Myc has also been found to associate with EZH2, a methyltransferase and member of the polycomb repressor complex 2 (Sander 2008, Corvetta

2013), and the interaction between N-Myc and EZH2 requires the MYC box domain III, which is necessary for N-Myc to promote transformation (Herbst 2005). Furthermore, N-Myc interacts with HDAC1, HDAC2 and SIRT1 in neuroblastoma (Liu 2007, Marshall 2011,

Shahbazi 2014). N-Myc acts as a transrepressor by recruiting the HDAC1 protein to an Sp-1 binding site in the TG2 promoter in a manner distinct from N-Myc binding to E-box binding sites as a transactivator (Liu 2007). Repression of TG2 expression by N-Myc was necessary for the inhibitory effect of N-Myc on neuroblastoma cell differentiation. Cyclin G2 (CCNG2) was commonly repressed by N-Myc and HDAC2 in neuroblastoma, and c-Myc and HDAC2 in pancreatic cancer. N-Myc acts as a transrepressor by recruiting HDAC2 protein to Sp1- binding sites at the CCNG2 gene promoter (Marshall 2010). N-Myc protein is stabilised via a positive feedback loop where N-Myc directly induces transcription of the histone deacetylase

SIRT1 which in turn increases N-Myc protein stability (Marshall 2011). SIRT1 binds to the

Myc Box 1 domain of N-Myc to form a transcriptional repressor complex at the gene

198 promoter of MKP3, with repression of MKP3 leading to ERK protein phosphorylation followed by N-Myc protein phosphorylation at Serine 62 and N-Myc protein stabilisation

(Marshall 2011). These data demonstrated that N-Myc is a key epigenetic regulator, playing a role in silencing tumour suppressor genes and upregulating tumour initiation genes in neuroblastoma by regulating DNA methylation, histone deacetylation and histone methylation (Marshall 2011).

Taken together my results refine our understanding of N-Myc driven oncogene transcription in neuroblastoma. The model of MYCN driven neuroblastoma begins with amplification of chromosome 2p24 leading to MYCN overexpression. The JMJD6 gene, located on chromosome 17q25, is gained in 62.9% of MYCN–amplified and 16.1% of MYCN- non-amplified human neuroblastoma tissues, leading to JMJD6 overexpression. In Chapter 5,

I demonstrated that JMJD6 upregulates N-Myc in MYCN amplified neuroblastoma and c-

Myc in MYCN non-amplified neuroblastoma. N-Myc in turn causes DOT1L overexpression by binding to an E-box at the DOT1L gene promoter, as shown in Chapter 3. DOT1L complexes with N-Myc and catalyzes H3K79me2 at N-Myc target gene promoters. The recruitment of N-Myc to E-box Myc binding sites causes gene transcription and the overexpression of oncogenes such as ODC1 and E2F2, driving neuroblastoma initiation and tumour progression (Figure 6.1).

199

2p24 Co-amplified/gained 17q21-ter

JMJD6

N-Myc

DOT1L

200

Figure 6.1 Proposed model for N-Myc-driven neuroblastoma.

(A) Amplificaiton of the MYCN gene at 2p24 and gain of the JMJD6 gene at 17q25 frequently co-occur in human neuroblastoma. JMJD6 upregulates N-Myc gene expression in

MYCN amplified neuroblastoma. N-Myc upregulates DOT1L by binding to an E-box at the

DOT1L gene promoter. (B) DOT1L catalyzes H3K79 di-methylation at N-Myc target gene promoters and recruits N-Myc to E-box binding sites at N-Myc target gene promoters, causing oncogene transcription and neuroblastoma progression (B).

201

6.2 Conclusion

In conclusion, the JMJD6 gene located on chromosome 17q25 is gained frequently in

MYCN–amplified and less frequently in MYCN-non-amplified human neuroblastoma tissues, leading to overexpression of JMJD6. JMJD6 upregulates N-Myc MYCN gene expression, with N-Myc in turn upregulating DOT1L by binding to an E-box at the DOT1L gene promoter. DOT1L-mediated H3K79 di-methylation at N-Myc target gene promoters recruits

N-Myc to E-boxes located at the N-Myc target gene promoters, causing increased oncogene transcription and neuroblastoma progression.

Knocking down either DOT1L or JMJD6 reduces neuroblastoma cell proliferation in vitro and tumour progression in vivo. Both DOT1L and JMJD6 gene expression in human neuroblastoma tissues correlates positively to N-Myc gene expression. In addition high

DOT1L and JMJD6 expression correlates with poor patient outcome independent of traditional neuroblastoma patient prognostic factors. Therefore, high levels of DOT1L and

JMJD6 expression in tumour tissues can be employed as clinical prognostic markers for neuroblastoma patient outcome, and DOT1L and JMJD6 are potential molecular targets for neuroblastoma.

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6.3 Future Directions

Future directions of this project would involve studying the mechanism of JMJD6 up- regulation of N-Myc and c-Myc in neuroblastoma. JMJD6 has been shown to up-regulate gene expression by forming a transcriptional activator complex with BRD4 at target gene anti-pause enhancer regions (Liu W. 2013). My hypothesis would be direct binding of JMJD6 to the anti-pause enhancers of the MYCN and MYC genes, which could be tested using ChIP sequencing with antibodies again JMJD6, BRD4 as well as positive and negative anti-pause enhancer markers in DOX-inducible JMJD6 shRNA CHP134 or SK-N-AS cells after treatment with vehicle control or DOX. The ability of JMJD6 to transcriptionally control

MYCN and MYC expression through anti-pause enhancers would be further tested by cloning the N-Myc and c-Myc promoters along with corresponding anti-pause enhancers into luciferase vectors for luciferase assays.

Further experiments would involve site directed mutagenesis of DOT1L to reveal the precise binding site of DOT1L to N-Myc. This could reveal novel DOT1L drug targets. More

DOT1L inhibitors in the literature could also be tested in neuroblastoma cell lines as both single agents and in combination with existing chemotherapy agents. Any promising drug combinations would be further tested in vivo using Th-MYCN mice.

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