Characterisation and Functional Validation of ERG Phosphorylation in Normal Haematopoietic and Leukaemic Cells

Home , Immunogen

Yizhou Huang

A thesis in fulfilment of the requirements for the degree of

Doctor of Philosophy

Prince of Wales Clinical School

Faculty of Medicine

September 2015

Huang: ERG Phosphorylation and Leukaemogenesis

Abstract

Direct modulation of oncogenic transcriptional programs by targeting aberrantly regulated transcription factors is a promising area of research for cancer treatment. The

ETS factor ERG (ETS-related gene) plays an important role in haematopoiesis and is also a potent oncoprotein with leukaemogenic activity in mouse models. In humans, high ERG expression is associated with poor patient outcomes in acute myeloid leukaemia (AML) and T-cell acute lymphoblastic leukaemia (T-ALL). However, gaps still exist in our knowledge regarding the post-translational regulation of ERG. Protein phosphorylation is known to regulate the transcriptional activity of many ETS factors.

Yet, as a known phosphoprotein, how ERG activity responds to phosphorylating signalling pathways that are associated with the onset and progression of leukaemia is largely unknown.

To unravel the post-translational regulation of ERG, I used liquid chromatography coupled tandem mass spectrometry to identify five phosphorylated serines (S) (S55, S88, S103, S222, S283) on endogenous ERG immunoprecipitated from MOLT-4 T-ALL cells with S283 phosphorylation (pS283) strongly enriched in leukaemic cells compared with healthy haematopoietic stem/progenitor cells (HSPCs).

Generation of a customised anti-ERG pS283 antibody to probe upstream signalling pathways in primary ALL and AML xenografts identifies early T-cell precursor ALL cells with poor prognosis to exhibit particularly high levels of pS283, and there was a direct association between levels of pS283 and active extracellular signal-regulated kinase (ERK). Over-expression of phosphomimetic ERG mutant (S283D) enhanced the ii

Huang: ERG Phosphorylation and Leukaemogenesis

expansion and clonogenicity of transduced primary HSPCs more than wild-type (WT)

ERG. This phenotype was associated with induction of genes involved in mitogen- activated protein kinase (MAPK)/ERK signalling. Further experiments showed ERG pS283 was directly modulated by ERK, consistent with the existence of a positive feedback loop that stabilised this modification in leukaemic cells. There were no substantial differences between WT and mutant ERG with regards to protein stability, nuclear transfer or direct DNA binding, however, there was increased enrichment of

S283D ERG at specific leukaemia-associated enhancers.

This work significantly expands existing knowledge of ERG phosphorylation in leukaemic cells and identifies a specific modification that could be targeted to modulate

ERG-driven leukaemic transcriptional programs.

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Acknowledgements

First and foremost my heart-felt thanks go to my parents, Wei Huang and

Yingwei Liu, whose unconditional support and patience made my overseas study possible ever since 2007. Heart-warming love also goes to my husband Han Shen, who is without doubt one of the greatest treasures I found in the Lowy Cancer Research

Centre, and has always been holding my hands during the ups and downs throughout my PhD.

My gratitude goes to my supervisors John Pimanda, Jason Wong and Julie

Thoms for their advice and guidance, and for their constant encouragement and help in preparing this thesis. Julie Thoms offered enormous help in revising the literature review, and more importantly, she has always had faith in me during my candidature.

My friends and co-workers in the Pimanda lab have been particularly wonderful.

They were always ready to help, and provided a truly collegial environment to work in.

Their support, funny stories and laughter brought a smile to my face even in the most arduous moments. “Thank you” cannot be said enough to Julie Thoms, Melinda Tursky and Kathy Knezevic for keeping me company during my major emotional breakdowns, whose comforting hugs I will always remember. Special thanks also go to my dear friend and my lovely desk neighbour Kate Yifang Guan, who has always been there to share the joyful and upset moments in our “nerdy” lives and has made my PhD a truly colourful journey.

Huang: ERG Phosphorylation and Leukaemogenesis

Thank you to Julie Thoms, Melinda Tursky and Kathy Knezevic for teaching me experimental techniques and data analysis, to Dominik Beck and Julie Thoms for the bioinformatic analysis, to Santi Suryani for the protocols and tricks in handling primary leukaemic cells, and to Jake Olivier for his help and advice with statistical analysis.

Additional thanks go to the people mentioned in each research chapter and the

Contributions chapter.

My gratitude goes to the University of New South Wales (UNSW) Australia for the University International Postgraduate Scholarship and the Translational Cancer

Research Network for the top-up scholarship. Thank you also to UNSW Australia

Postgraduate Research Support Scheme and my supervisors for the funding which allowed me to present at conferences.

Huang: ERG Phosphorylation and Leukaemogenesis

Publications

Wong JJL, Ritchie W, Ebner OA, Selbach M, Wong JWH, Huang Y, Gao D, Pinello N,

Gonzalez M, Baidya K, Thoeng A, Khoo TL, Bailey CG, Jolst J, Rasko JEJ,

“Orchestrated intron retention regulates normal granulocyte differentiation.” Cell,

2013; doi:10.1016/j.cell.2013.06.052

Tursky ML, Beck D, Thoms JAI, Huang Y, Kumari A, Unnikrishnan A, Knezevic K,

Evans K, Richards LA, Lee E, Morris J, Goldberg L, Izraeli S, Wong JWH, Olivier J,

Lock RB, MacKenzie KL, Pimanda JE, “Over-expression of ERG in cord blood progenitors promotes expansion and recapitulates molecular signatures of high ERG leukaemias.” Leukaemia, 2014; doi: 10.1038/leu.2014.299.

Thoms JAI, Knezevic K, Liu J, Glaros E, Thai T, Qiao Q, Huang Y, Papathanasiou P,

Tunningley R, Whittle B, Yeung A, Chandrakanthan V, Wong JWH, Ward R, Thomas

S, Pimanda JE. “Arrested Haematopoiesis and Vascular Relaxation Defects in Mice with a Mutation in Dhfr.” Blood, 2015. (Submitted manuscript)

Unnikrishnan A, Guan Y, Thoms JAI, Huang Y, Knezevic K, Beck D, Wong JWH,

Pimanda JE, “A quantitative proteomics approach identifies new transcriptional regulators of ERG.” Nucleic Acid Research, 2015. (Submitted manuscript)

Huang: ERG Phosphorylation and Leukaemogenesis

Presentations

Huang Y, Thoms JAI, Tursky ML, Knezevic K, Chandrakanthan V, Suryani S, Lock R,

MacKenzie K, Wong JWH, Pimanda JE. “ERG phosphorylation in normal haematopoietic and leukaemic cells”. Prince of Wales Clinical School Postgraduate

Research Seminar, 2013. Oral presentation.

Huang Y, Thoms JAI, Tursky ML, Knezevic K, Chandrakanthan V, Suryani S, Lock R,

MacKenzie K, Wong JWH, Pimanda JE. “Leukaemogenic potential of ERG is mediated by phosphorylation via the MAPK/ERK pathway”. New Directions in Leukaemia

Research (NDLR), 2014. Poster presentation.

Huang Y, Thoms JAI, Tursky ML, Knezevic K, Chandrakanthan V, Suryani S, Lock R,

MacKenzie K, Wong JWH, Pimanda JE. “Leukaemogenic potential of ERG is mediated by phosphorylation via the MAPK/ERK pathway”. Lorne Genome, 2014. Poster presentation.

Huang Y, Thoms JAI, Tursky ML, Knezevic K, Chandrakanthan V, Suryani S, Lock R,

MacKenzie K, Wong JWH, Pimanda JE. “Leukaemogenic potential of ERG is mediated by phosphorylation via the MAPK/ERK pathway”. Prince of Wales Clinical School

Postgraduate Research Seminar, 2013. Poster presentation.

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Huang: ERG Phosphorylation and Leukaemogenesis

Abbreviations

ALL Acute lymphoblastic leukaemia AML Acute myeloid leukaemia AMKL Acute megakaryocytic leukaemia APML Acute promyelocytic leukaemia ATP Adenosine triphosphate BM Bone marrow BMIF Biomedical imaging facility BRIL Biological resources imaging laboratory BSA Bovine serum albumin BTK Bruton’s tyrosine kinase CB Cord blood CDK Cyclin-dependent kinase CFU Colony forming unit ChIP Chromatin immunoprecipitation CK Casein kinase CMP Common myeloid progenitors CLP Common lymphoid progenitor Ct Threshold cycle DDA Data dependent acquisition DMEM Dulbecco's modified Eagle’s medium DMSO Dimethyl sulfoxide dNTP Deoxynucleoside triphosphate DP Distal promoter DTT Dithiothreitol EDTA Ethylenediaminetetraacetic acid EMSA Electromobility shift assay EPO Erythropoietin ERG ETS-related gene ERK Extracellular signal-regulated kinase ES Enrichment score ETP Early T-cell precursor ETS E-twenty six EWS Ewing sarcoma EWSBR Ewing sarcoma breakpoint region FACS Fluorescence activated cell sorting FBS Foetal bovine serum FLI1 Friend Leukaemia virus Integration site 1 Flt3L FMS-like tyrosine kinase 3 ligand FSC Forward scatter

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FP Fluorescence polarisation FT Fourier Transform GATA Globin transcription factor G-CSF Granulocyte-colony stimulating factor GFOLD Generalised fold change GFP Green fluorescence protein GMP Granulocyte-macrophage progenitors GRB2 Growth factor receptor-bound protein 2 GREAT Genomic regions enrichment of annotations tool GSEA Gene set enrichment analysis GST Glutathione S-transferase HBSS Hanks’ balanced salt solution HEK Human embryonic kidney HF High fidelity HPC Haematopoietic progenitor cell/s HREC Human Research Ethics Committee HRP Horseradish peroxidase HSC Haematopoietic stem cell HSPC Haematopoietic stem and progenitor cell IL Interleukin IMDM Iscove's modified Dulbecco's medium IPTG Isopropyl β-D-1-thiogalactopyranoside IRES Internal ribosomal entry site ITC Isothermal titration calorimetry JAK Janus-activated kinases JNK c-Jun N-terminal kinases LB Luria-Bertani LC Liquid chromatography LC-MS/MS Liquid chromatography coupled tandem mass spectrometry LMO2 LIM domain only 2 LYL1 Lymphoblastic leukemia associated haematopoiesis regulator 1 MAPK Mitogen-activated protein kinase MBP Myelin basic protein MDS Myelodysplastic syndrome MEK Mitogen-activated protein kinase kinase MEP Megakaryocyte erythroid progenitor MIG MSCV-IRES-GFP MOPS 3-(N-morpholino)propanesulfonic acid) MS/MS Tandem mass spectrometry MSCV Murine stem cell virus NDLR New directions in leukemia research NEB New England Biolab NES Normalised enrichment score ix

Huang: ERG Phosphorylation and Leukaemogenesis

NFW Nuclease free water ONPG Ortho-nitrophenyl-β-galactoside P/S Penicillin / streptomycin PAGE Polyacrylamide gel electrophoresis PBS Phosphate buffered saline PCR Polymerase chain reaction PDGF Platelet-derived growth factor PE Phycoerythrin PFA Paraformaldehyde PIN Prostatic intraepithelial neoplasia PKC Protein kinase C PMA Phorbol 12-myristate 13-acetate PNT Pointed PP Proximal promoter PRSS Postgraduate Research Support Scheme PTM Post-translational modification/s PU.1 Purine protein binding protein 1 PVDF Polyvinylidene fluoride RAR Retinoic acid receptor RBC Red blood cell RIPA Radioimmunoprecipitation assay RPMI Roswell Park Memorial Institute RTK Receptor tyrosine kinase RT-PCR Real time polymerase chain reaction RUNX1 Runt-related transcription factor 1 SCE Stem cell enhancer SCF Stem cell factor SCL Stem cell leukaemia SD Standard deviation SDS Sodium dodecyl sulfate SLIM Site-directed, ligase-independent mutagenesis SSC Side scatter S/T Serine/threonine STAT Signal transducers and activators of transcription TAF1 Transcription initiation factor TFIID subunit 1 T-ALL T-cell acute lymphoblastic leukemia TBS Tris-buffered saline TBS-T Tris-buffered saline-Tween TCRN Translational Cancer Research Network TE Tris-EDTA TFA Trifluoroacetic acid TKI Tyrosine kinase inhibitor TLS Translocation liposarcoma x

Huang: ERG Phosphorylation and Leukaemogenesis

TMD Transient myeloproliferative disorder TNF Tumour necrosis factor TOP1 Topoisomerase 1 TPO Thrombopoietin UIPA University International Postgraduate Award UNSW University of New South Wales UTR Untranslated region VCM Virus containing media WT Wild type α-MEM α-minimum essential media

Huang: ERG Phosphorylation and Leukaemogenesis

Table of Contents

ABSTRACT ...... II

ACKNOWLEDGEMENTS ...... IV

PUBLICATIONS ...... VI

PRESENTATIONS...... VII

ABBREVIATIONS ...... VIII

TABLE OF CONTENTS ...... XII

LIST OF FIGURES ...... XVIII

LIST OF TABLES ...... XX

CHAPTER 1. LITERATURE REVIEW ...... 1

1.1. GENERAL INTRODUCTION ...... 1

1.2. HAEMATOPOIESIS ...... 2 1.2.1. Normal haematopoiesis ...... 2 1.2.2. Aberrant haematopoiesis ...... 6

1.3. TRANSCRIPTIONAL CONTROL OF HAEMATOPOIESIS ...... 8 1.3.1. The role of transcription factors in controlling gene output ...... 9 1.3.2. The ETS family of transcription factors ...... 13

1.4. THE ETS-RELATED GENE (ERG) ...... 16 1.4.1. ERG in normal haematopoiesis ...... 19 1.4.2. ERG in cancer ...... 20 1.4.2.1. ERG translocations and cancer ...... 21 1.4.2.2. ERG over-expression and cancer ...... 23 1.5. POST-TRANSLATIONAL REGULATION OF PROTEIN FUNCTION ...... 27 1.5.1. Post-translational modifications (PTMs) ...... 28 1.5.2. Regulation of transcription factor activity by phosphorylation ...... 32 1.5.3. Kinases ...... 43 1.5.3.1. Kinases and phosphatases ...... 43 1.5.3.2. RAS pathway ...... 44 1.5.3.3. MAPK/ERK pathway ...... 47 1.5.3.3.1. Components of the MAPK pathway ...... 47 xii

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1.5.3.3.2. MAPK regulation of ETS factor activities ...... 50 1.5.3.4. Kinases as drug targets ...... 52 1.5.4. Relevance of phosphorylation to leukaemia treatment ...... 52

1.6. HYPOTHESES AND AIMS ...... 54

CHAPTER 2. MATERIALS AND METHODS ...... 56

2.1. GENERAL TISSUE CULTURE ...... 56 2.1.1. Cell lines and primary cells ...... 56 2.1.2. Cell culture ...... 57 2.1.2.1. Cell line culture and cryopreservation ...... 57 2.1.2.2. Primary cell culture ...... 58 2.1.3. Cell viability determination ...... 58 2.1.3.1. Trypan Blue exclusion assay...... 58 2.1.3.2. AlamarBlue assay ...... 59 2.1.4. Stable isotope-labelling by amino acids in cell culture (SILAC) ...... 59

2.2. IMMUNOBLOTTING ...... 59 2.2.1. Preparation of whole cell lysate ...... 59 2.2.2. Preparation of cytosolic and nuclear lysates...... 60 2.2.3. Protein Concentration Quantification ...... 60 2.2.4. SDS-polyacrylamide gel electrophoresis (SDS-PAGE) ...... 61 2.2.5. Protein transfer ...... 62 2.2.6. Antibody probing ...... 62 2.2.7. Immunodetection ...... 65

2.3. PHOSPHOPROTEOMIC ANALYSIS ...... 65 2.3.1. Cell lysis and immunoprecipitation ...... 65 2.3.2. Enzymatic digestion ...... 66 2.3.2.1. Trypsin/chymotrypsin reconstitution and storage ...... 66 2.3.2.2. In-gel enzymatic digestion ...... 66 2.3.2.3. In-solution enzymatic digestion ...... 67 2.3.3. Phosphopeptide enrichment ...... 68 2.3.4. Desalting of protein digest ...... 69 2.3.5. Mass spectrometry ...... 69 2.3.5.1. Liquid chromatography (LC) ...... 69 2.3.5.2. Tandem mass spectrometry (MS/MS) ...... 70 2.3.6. Mass spectrometry data analysis...... 71 2.3.7. Nuclear/cytoplasmic phosphopeptide normalisation ...... 71

2.4. PLASMID PREPARATION ...... 72 2.4.1. Plasmid construction ...... 72 2.4.1.1. Polymerase chain reaction (PCR) ...... 72 xiii

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2.4.1.2. Subcloning ...... 73 2.4.1.3. pMIG+ ERG construction ...... 74 2.4.1.4. GST-ERG expression vector construction ...... 76 2.4.2. Bacterial Transformation with Plasmid DNA ...... 76 2.4.3. Mini-preparation ...... 77 2.4.4. Confirmation of plasmid DNA ...... 78 2.4.4.1. Diagnostic digest ...... 78 2.4.4.2. DNA Sequencing and clean-up ...... 78 2.4.5. Maxi-preparation of plasmid DNA ...... 80 2.4.6. Glycerol Stocks ...... 80

2.5. ERG MUTAGENESIS ...... 81 2.5.1. Point mutation - Site-directed mutagenesis ...... 81 2.5.2. Deletion mutation ...... 83

2.6. EXPRESSION AND PURIFICATION OF GST-ERG PROTEIN ...... 85

2.7. GENERATION OF ERG PS283-SPECIFIC ANTISERUM ...... 86 2.7.1. Antigen synthesis and antibody generation ...... 86 2.7.2. Optimisation of probing condition ...... 87

2.8. CORD BLOOD CD34+ HHSC TRANSDUCTION AND ASSAYS ...... 89 2.8.1. Stock of cord blood CD34+ Cells ...... 89 2.8.1.1. Cord blood ethics approval ...... 89 2.8.1.2. Cord blood CD34+ cell enrichment ...... 89 2.8.2. Virus production ...... 90 2.8.2.1. Thawing and preparation of Phoenix cells ...... 90 2.8.2.2. Transfection of Phoenix cells ...... 91 2.8.3. Retroviral transduction of cord blood cells ...... 92 2.8.3.1. Thawing cord blood Cells ...... 92 2.8.3.2. Pre-stimulation and Cord Blood Cell Infection ...... 92 2.8.4. Cell culture of cord blood cells...... 94 2.8.4.1. Self-renewal assay ...... 94 2.8.4.1.1. Cytokine-driven culture for the expansion of progenitor cells ...... 94 2.8.4.1.2. Calculations of Expansion ...... 95 2.8.4.2. CFU assay ...... 95 2.8.5. Flow cytometry and fluorescence-activated cell sorting (FACS) ...... 98 2.8.5.1. Flow cytometry of GFP and CD34 population ...... 98 2.8.5.2. FACS ...... 98 2.8.6. Segmented regression analysis for cytokine-driven culture ...... 99 2.8.7. Quantitative real-time PCR (qRT-PCR) ...... 99 2.8.7.1. RNA extraction ...... 99 2.8.7.2. PCR amplification of cDNA ...... 100 xiv

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2.8.7.3. Quantitative PCR (qPCR)/qRT-PCR ...... 101 2.8.8. RNA sequencing ...... 103 2.8.8.1. Sample preparation ...... 103 2.8.8.2. Bioinformatics analysis ...... 103 2.8.8.2.1. Alignment to the human genome and expression quantification ...... 103 2.8.8.2.2. Gene Set Enrichment Analysis (GSEA) ...... 104 2.8.9. ChIP sequencing ...... 105 2.8.9.1. ChIP sample preparation ...... 105 2.8.9.2. ChIP sequencing ...... 107 2.8.9.3. Bioinformatic analysis ...... 108 2.9. KINASE PATHWAY ANALYSIS ...... 109 2.9.1. In vitro kinase assay ...... 109 2.9.2. In vivo MAPK inhibition/activation...... 109 2.9.3. CFU assay with MEK inhibitor ...... 110

2.10. MUTAGENESIS ASSAYS ...... 111 2.10.1. Protein degradation assay ...... 111 2.10.1.1. HEK293T transfection ...... 111 2.10.1.2. De novo protein synthesis inhibition ...... 111 2.10.1.3. Protein quantification ...... 112 2.10.2. Immunofluorescence ...... 112 2.10.2.1. Retroviral transduction of MOLT-4 cells ...... 112 2.10.2.1.1. Transient transfection of viral producer cells ...... 112 2.10.2.1.2. Retroviral transduction of MOLT-4 cells ...... 112 2.10.2.2. Cytospin and staining ...... 113 2.10.2.3. Confocal Imaging ...... 115 2.10.3. Fluorescence polarisation (FP) assay ...... 115 2.10.3.1. Expression and purification of GST-ERG protein ...... 115 2.10.3.2. Fluorescence Polarization Measurements ...... 116 2.10.4. ChIP assay ...... 117 2.10.4.1. Retroviral transduction of MOLT-4 cells ...... 117 2.10.4.2. ChIP ...... 117 2.10.5. Transactivation/reporter gene assay ...... 119

2.11. STATISTICAL ANALYSIS ...... 120

CHAPTER 3. IDENTIFICATION OF ERG S283 PHOSPHORYLATION IN LEUKAEMIC CELLS ...... 121

3.1. HUMAN ERG IS PHOSPHORYLATED ON FIVE SERINES ...... 121

3.2. INTRACELLULAR LOCATION OF ERG PHOSPHOSITES ...... 127

3.3. POTENTIAL ASSOCIATION OF ERG PS283 WITH LEUKAEMIA ...... 129

3.4. GENERATING AN ERG PS283 ANTIBODY ...... 133

Huang: ERG Phosphorylation and Leukaemogenesis

3.5. SCREENING PRIMARY ALL FOR ERG PS283 EXPRESSION...... 141

3.6. CHAPTER SUMMARY ...... 143

CHAPTER 4. ERG PS283 INDUCES A PROLIFERATIVE PHENOTYPE IN HSPC ...... 144

4.1. THE PRINCIPLE UNDERLYING THE MUTAGENESIS ASSAY...... 144

4.2. ERG S283 MUTANTS ARE ACTIVE HAEMATOPOIETIC TRANSCRIPTION FACTORS...... 147

4.3. ERG S283 PHOSPHOMIMETIC MUTANT PROMOTES HSPC EXPANSION ...... 155

4.4. ERG S283 PHOSPHOMIMETIC MUTANT ENHANCES HSPC CLONOGENICITY ...... 159

4.5. ERG S283 PHOSPHOMIMETIC MUTANT INDUCES AN ONCOGENIC GENE SIGNATURE ...... 163

4.6. CHAPTER SUMMARY ...... 170

CHAPTER 5. ERG PS283 IS MODULATED BY THE MAPK/ERK2 PATHWAY ...... 171

5.1. MAPK/ERK2 PHOSPHORYLATES ERG S283 IN VITRO ...... 171

5.2. MAPK/ERK PHOSPHORYLATES ERG S283 IN VIVO ...... 178 5.2.1. MAPK/ERK phosphorylates ERG S283 in leukaemic cell lines ...... 178 5.2.2. MAPK/ERK phosphorylates ERG S283 in primary leukaemic xenograft cells ...... 186

5.3. ERG PS283 LEVEL CORRELATES WITH ERK ACTIVITY IN HAEMATOPOIETIC CELLS ...... 188

5.4. ERG PS283 INHIBITION DOES NOT IMPACT ON LEUKAEMIC CELL VIABILITY ...... 190

5.5. REDUCED CLONOGENICITY BY ERK INHIBITION IN LEUKAEMIC CELLS ...... 192

5.6. MEK INHIBITION ALTERS HEPTAD IN VIVO DNA BINDING ...... 194

5.7. CHAPTER SUMMARY ...... 196

CHAPTER 6. INVESTIGATION OF THE IMPACT OF PS283 ON ERG STABILITY, NUCLEAR LOCALISATION, DNA BINDING AND TRANSCRIPTION INITIATION ...... 198

6.1. S283 PHOSPHORYLATION DOES NOT AFFECT ERG PROTEIN STABILITY ...... 198

6.2. S283 PHOSPHORYLATION DOES NOT AFFECT ERG NUCLEAR LOCALISATION ...... 202

6.3. S283 PHOSPHORYLATION DOES NOT AFFECT ERG IN VITRO DNA BINDING...... 204

6.4. S283 PHOSPHORYLATION INCREASES ERG IN VIVO DNA BINDING ...... 206

6.5. DIFFERENTIAL DNA BINDING BY ERG S283 PHOSPHOMIMETIC MUTANT IN HSPCS ...... 209

6.6. S283 PHOSPHORYLATION DOES NOT AFFECT ERG TRANSACTIVATION ABILITY ...... 219

6.7. CHAPTER SUMMARY ...... 224

CHAPTER 7. CONCLUDING REMARKS AND FUTURE DIRECTIONS ...... 227

CONTRIBUTIONS ...... 234

DISCLOSURE OF INTEREST ...... 236

REFERENCES ...... 237

APPENDICES – SUPPLEMENTARY MATERIALS ...... 265

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List of Figures

FIGURE 1-1 THE HAEMATOPOIETIC HIERARCHY...... 5

FIGURE 1-2 SCHEMATIC OF TRANSCRIPTION FACTOR BOUND REGULATORY ELEMENTS...... 11

FIGURE 1-3 PHYLOGENETIC TREE OF THE ETS FAMILY...... 15

FIGURE 1-4 HUMAN ERG GENE AND PROTEIN STRUCTURE...... 18

FIGURE 1-5 PHOSPHORYLATION REGULATES TRANSCRIPTION FACTOR ACTIVITY...... 33

FIGURE 1-6 MODEL OF ETS1 AUTO-INHIBITION AND MECHANISM OF PHOSPHORYLATION-DEPENDENT INHIBITION OF ETS1

DNA BINDING...... 38

FIGURE 1-7 SCHEMATIC OF FLI1 DEPHOSPHORYLATION-MEDIATED TRANSCRIPTIONAL COMPLEX FORMATION...... 42

FIGURE 1-8 OVERVIEW OF THE RAS-RAF-MEK-ERK PATHWAY...... 46

FIGURE 1-9 GENERAL SET-UP OF THE MAPK PATHWAY...... 49

FIGURE 2-1 SCHEMATIC OF THE RETROVIRAL CONSTRUCT CONTAINING ERG CDNA...... 75

FIGURE 3-1 MS COVERAGE OF ENDOGENOUS ERG FROM MOLT-4 T-ALL CELLS...... 124

FIGURE 3-2 MS ANALYSIS OF ERG FROM MOLT-4 T-ALL CELLS REVEALED FIVE PHOSPHORYLATED SERINES...... 125

FIGURE 3-3 CYTOPLASMIC AND NUCLEAR ABUNDANCE OF ERG PHOSPHORYLATION...... 128

FIGURE 3-4 ERG PS283 IS ABUNDANT IN LEUKAEMIC CELL LINES, BUT NOT IN HEALTHY CD34+ HSPC...... 132

FIGURE 3-5 ANTISERUM CLONE REPORT OF ERG PS283 ANTIBODY...... 134

FIGURE 3-6 ERG PS283 ANTISERUM CANDIDATE SCREENING...... 137

FIGURE 3-7 SENSITIVITY TESTING OF TWO CANDIDATE CLONES OF ERG PS283 ANTIBODY...... 138

FIGURE 3-8 OPTIMISATION OF THE PROBING CONDITION FOR ANTI-ERG PS283 ANTIBODY...... 140

FIGURE 3-9 THE ETP ALL XENOGRAFTS EXHIBIT HIGHER LEVELS OF ERG S283 PHOSPHORYLATION...... 142

FIGURE 4-1 SCHEMATIC EXPLANATION OF THE MUTAGENESIS STRATEGY...... 146

FIGURE 4-2 EXPERIMENTAL PROCEDURE OF CD34+ HSPC TRANSDUCTION...... 149

FIGURE 4-3 ERG EXPRESSION IN HSPC CYTOKINE-DRIVEN CULTURES...... 152

FIGURE 4-4 PERCENTAGE OF TRANSDUCED CELLS IN HSPC CYTOKINE-DRIVEN CULTURE...... 154

FIGURE 4-5 ELEVATED CD34% IN TRANSDUCED HSPC BY ERG S283 PHOSPHOMIMETIC MUTANT...... 156

FIGURE 4-6 ERG S283 PHOSPHOMIMETIC MUTANT PROMOTES THE MAINTENANCE AND EXPANSION OF HSPC...... 158

FIGURE 4-7 ERG S283 PHOSPHOMIMETIC MUTANT INDUCES A MORE CLONOGENIC PHENOTYPE IN HSPC...... 160

FIGURE 4-8 GSEA OF HSC AND LEUKAEMIA GENE SIGNATURES UP-REGULATED BY ERG S283 PHOSPHOMIMETIC MUTANT IN

CD34+ HSPC...... 165

FIGURE 4-9 GSEA OF ONCOGENIC SIGNATURES UP-REGULATED BY ERG S283 PHOSPHOMIMETIC MUTANT IN CD34+ HSPC...... 167

FIGURE 4-10 ELEVATED RAS/MEK SIGNALLING BY ERG S283 PHOSPHOMIMETIC MUTANT IN CD34+ HSPC...... 169

FIGURE 5-1 ERG ISOFORM 3 HARBOURS A CLASSIC MAPK DOCKING SITE...... 173

FIGURE 5-2 MAPK/ERK2 PHOSPHORYLATES ERG S283 IN VITRO...... 175

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FIGURE 5-3 ERG S283 IS PHOSPHORYLATED BY ERK2 IN VITRO VIA THE DEF DOMAIN...... 177

FIGURE 5-4 EXPERIMENTAL PROCEDURE OF MEK INHIBITION/ACTIVATION ON MOLT-4 CELLS...... 179

FIGURE 5-5 ERG S283 PHOSPHORYLATION IS SPECIFICALLY INHIBITED BY MEK/ERK INHIBITOR IN VIVO...... 182

FIGURE 5-6 ERG S283 PHOSPHORYLATION IS SPECIFICALLY INHIBITED BY MEK/ERK INHIBITOR IN LEUKAEMIC CELL LINES. 185

FIGURE 5-7 ERG S283 PHOSPHORYLATION IS SPECIFICALLY INHIBITED BY MEK/ERK INHIBITOR IN PRIMARY ETP ALL

XENOGRAFT CELLS...... 187

FIGURE 5-8 ERG PS283 LEVEL CORRELATES WITH ACTIVE ERK IN HAEMATOPOIETIC CELLS...... 189

FIGURE 5-9 MEK/ERK INHIBITION IS NON-LETHAL ON PRIMARY ALL CELLS...... 191

FIGURE 5-10 MEK/ERK INHIBITION RESULTS IN REDUCED COLONY FORMATION BY LEUKAEMIC CELLS WITH HIGH ERG PS283...... 193

FIGURE 5-11 MEK INHIBITION ALTERS HEPTAD BINDING AT ERG +85 ENHANCER IN KG-1 CELLS...... 195

FIGURE 6-1 ERG S283 PHOSPHORYLATION DOES NOT AFFECT ERG PROTEIN STABILITY...... 200

FIGURE 6-2 ERG S283 PHOSPHORYLATION DOES NOT AFFECT ERG NUCLEAR LOCALISATION...... 203

FIGURE 6-3 REPRESENTATIVE FP ISOTHERMS OF ERG BINDING TO DNA...... 205

FIGURE 6-4 ERG S283 PHOSPHORYLATION INCREASES ERG IN VIVO DNA BINDING...... 208

FIGURE 6-5 CHIP SEQUENCING TRACES OF GENES WITH DIFFERENTIAL DNA BINDING AND ALTERED EXPRESSION INDUCED BY

ERG S283D IN HSPC...... 215

FIGURE 6-6 CHIP SEQUENCING TRACE OF BTG2 IN ERG TRANSDUCED HSPC...... 216

FIGURE 6-7 TRANSACTIVATION ASSAY DOSE TITRATION...... 221

FIGURE 6-8 S283 PHOSPHORYLATION DOES NOT AFFECT ERG TRANSACTIVATION ABILITY...... 223

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List of Tables

TABLE 2-1 ANTIBODY CONCENTRATIONS USED FOR IMMUNOBLOTTING...... 64

TABLE 2-2 PRIMER SEQUENCES FOR SITE-DIRECTED MUTAGENESIS...... 82

TABLE 2-3 PRIMER SEQUENCES FOR ERG DELETION USING SITE-DIRECTED, LIGASE-INDEPENDENT MUTAGENESIS (SLIM). ... 84

TABLE 2-4 SUMMARY OF PROBING CONDITIONS FOR ANTI-ERG PS283 ANTIBODY...... 88

TABLE 2-5 CORD BLOOD CELL CULTURE MEDIA ...... 97

TABLE 2-6 PRIMER SEQUENCE USED FOR QRT-PCR AMPLIFICATION...... 102

TABLE 2-7 SUMMARY OF ANTIBODY PROBING CONDITIONS FOR IMMUNOFLUORESCENCE...... 114

TABLE 2-8 PRIMER SEQUENCES FOR ERG CHIP QRT-PCR...... 118

TABLE 4-1 ERG S283 PHOSPHOMIMETIC MUTANT INCREASES THE EXPANSION AND CLONOGENICITY OF HSPC IN CYTOKINE-

DRIVEN CULTURE...... 161

TABLE 6-1 TRANSCRIPT LEVELS OF IDENTIFIED GENES WITH ALTERED DNA BINDING...... 217

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Chapter 1. Literature Review

1.1. General introduction

Cancer development and progression is a multi-stage process arising from the additive and cooperative activities of multiple pathways, resulting in the activation of proto-oncogenes and the inactivation of tumour suppressor genes (Goh et al., 2007).

Delineation of the biological processes involved in the development of cancer will provide a better understanding of how disruption of the balance between proliferation, differentiation and apoptosis leads to malignancy, as well as to guide the discovery of potential therapeutic targets.

Direct modulation of gene expression by targeting oncogenic transcription factors is an emerging area of research for cancer treatment. The transcription factor encoded by the E-twenty-six (ETS)-related gene, ERG, belongs to the ETS family of transcription factors and plays an important physiological role in haematopoiesis (Ko and Prives, 1996; Loughran et al., 2008), angiogenesis (Birdsey et al., 2008) and bone development (Iwamoto et al., 2001). Specifically, ERG is an essential regulator of the haematopoietic stem cell (HSC) function showing high expression levels in HSCs and subsequent down-regulation in the progenitor cell compartments (Bohne et al., 2009). It is also a potent human oncoprotein which has been proven leukaemogenic in murine models (Baldus et al., 2006; Marcucci et al., 2007; Metzeler et al., 2009; Mullighan et al., 2007; Rainis et al., 2005; Shimizu et al., 1993; Thoms et al., 2011; Tsuzuki et al.,

2011). ERG over-expression induces proliferation of HSCs in liquid culture (Tursky et al., 2015) and is required for leukaemia maintenance (Thoms et al., 2011; Tsuzuki et al.,

Huang: Chapter 1. Literature Review

2011). Although aberrant ERG expression has been detected in a wide range of malignancies, gaps still exist in our knowledge regarding how the transcriptional function of ERG is regulated. Delineating upstream pathways that regulate post- translational modifications (PTM) may assist the understanding of the role of ERG in oncogenesis and cancer prevention. A thorough understanding of this will be useful in the development of new strategies for the treatment of a number of human malignancies.

Protein phosphorylation is one of the major mechanisms regulating transcription factor activity (Krishna and Wold, 1993). It is known to modulate five aspects of protein function, including stability, nuclear localisation, DNA binding capability, transcription activation, and interaction with other proteins (Hunter and Karin, 1992; Seo and Lee,

2004). Despite our growing understanding of the biological processes that regulate many ETS family members, little is known about ERG phosphorylation and its impact on ERG transcriptional activity. This knowledge is of fundamental importance if we are to develop molecular therapies to target ERG-associated haematological and solid organ malignancies.

1.2. Haematopoiesis

1.2.1. Normal haematopoiesis

Haematopoiesis is defined as the formation and development of normal blood cells by HSCs that are resident in the bone marrow (Foster et al., 2009). In a healthy adult, approximately 1011–1012 new blood cells are produced daily to maintain the peripheral circulation (Mosaad, 2014). Two waves of haematopoiesis occur during the 2

Huang: Chapter 1. Literature Review life-span of a vertebrate: embryonic haematopoiesis, which generates transitory haematopoietic cell populations during embryogenesis before the formation of the bone marrow; and definitive haematopoiesis, which originates later in development and refers to the ongoing production of all the mature blood lineages from the bone marrow in the embryo and throughout adulthood (Medvinsky et al., 2011).

The haematopoietic system is a hierarchy comprised of a self-renewing stem cell population sustaining a large pool of non-renewing progeny (Testa, 2011) (Figure 1-1).

It is one of the first complex tissues to develop in the mammalian conceptus (Dzierzak and Speck, 2008) via differentiation from mesodermal cells within the yolk sac around embryonic day E7-7.5 in the mouse foetus (Lensch and Daley, 2004). The haematopoietic hierarchy is comprised of over 50 functionally distinct cell populations categorised into more than 11 lineages and 14 mature cell types (Ema et al., 2014). The majority of these cells have a limited lifespan, and require continual replenishment from a small sub-set of self-renewing HSCs (Dykstra and de Haan, 2008). HSCs constitute only 0.005% of the mononuclear cells within the bone marrow and are unique compared with all other haematopoietic cells, as they have the ability to self-renew to maintain the

HSC pool while differentiating into daughter cells, and can thereby sustain blood cell production throughout a lifetime (Morrison and Weissman, 1994). All types of circulating blood cells including the myeloid (monocytes, neutrophils, basophils, eosinophils, erythrocytes and platelets) and the lymphoid lineages (T-cells and B-cells)

(Figure 1-1) are derived from the pluripotent HSCs through a progression of commitment and differentiation that begins with the generation of multi-potential and lineage-restricted progenitors (Aggarwal et al., 2012). The cell fate choices of haematopoietic stem and progenitor cells (HSPC) between self-renewal, proliferation 3

Huang: Chapter 1. Literature Review and differentiation are influenced by the interaction of external factors such as active signalling pathways and intercellular communications, and internal factors such as the cell’s gene expression profile (Novershtern et al., 2011; Orkin and Zon, 2008).

Huang: Chapter 1. Literature Review

Figure 1-1 The haematopoietic hierarchy.

The multiple lineages of the haematopoietic system are depicted. LT-HSC, long term haematopoietic stem cell; ST-HSC, short term HSC; CMP, common myeloid progenitor; CLP, common lymphoid progenitor; MEP, megakaryocyte erythroid progenitor; GMP, granulocyte macrophage progenitor; RBC, red blood cell. Image adapted from Orkin and Zon (2008).

Huang: Chapter 1. Literature Review

1.2.2. Aberrant haematopoiesis

The balance of cell proliferation, differentiation and quiescence must be tightly controlled to maintain blood homeostasis, and dysregulation can lead to malignancies

(Gomez-Lopez et al., 2014; Zhu and Emerson, 2002). Haematologic malignancies include lymphoma, myeloma, and leukaemia (Freireich et al., 1984). Lymphoma is generally known as the cancer of the lymphatic system due to malignant transformation of lymphocytes (Marcus et al., 2014). It is subdivided into Hodgkin’s and non-

Hodgkin’s lymphoma, with the latter being predominant making up 90% of diagnosed cases (Bhatia and Robison, 1999; Marcus et al., 2014). Myeloma refers to a malignancy of plasma cells normally responsible for antibody production (Raab et al., 2009). In multiple myeloma, production of normal blood cells from the bone marrow is interfered by the accumulation of abnormal plasma cells (Rollig et al., 2015).

This thesis mainly focuses on the pathogenesis of leukaemia, which is defined as the abnormal, uncontrolled proliferation of one or more haematopoietic cell types in the bone marrow which suppresses the production of normal blood cells (Nowak et al.,

2009). The self-renewal ability of the bone marrow is normally limited to HSCs.

However, leukaemic cells acquire the capacity to self-renew as a result of disruption to the regulatory mechanisms that govern normal haematopoiesis, allowing the production of unlimited progeny while inhibiting their differentiation into mature blood cells

(Aggarwal et al., 2012). A characteristic abnormality of leukaemic cells is that they are blocked at an early stage of their development and can no longer differentiate into functional mature cells (Gomez-Lopez et al., 2014; Kantarjian et al., 1985).

Huang: Chapter 1. Literature Review

The different types of leukaemias are classified according to the onset and establishment of the disease, the number of white blood cells present in the peripheral blood and the lineage origin of the diseased cell type (Brown, 1993; Wandt et al., 2010).

Specifically, acute leukaemias possess mostly undifferentiated immature cell types, while the cell types are predominantly mature in chronic leukaemias (Brown, 1993).

These are then subcategorised on the basis of lineage bias observed within the abnormal population into acute myeloid leukaemia (AML), acute lymphoblastic leukaemia

(ALL), chronic myeloid leukaemia (CML) and chronic lymphocytic leukaemia (CLL)

(Estey and Dohner, 2006; Pui et al., 2008; Testa, 2011). However, high heterogeneity is observed even within these subcategories, with many different types and combinations of genetic and/or epigenetic lesions detected from patient samples (Guieze and Wu,

2015; Liesveld, 2015).

Enormous progress in characterising leukaemogenesis has been achieved in the past three decades. Cytogenetic and molecular studies of leukaemia have led to the identification of a variety of genetic alterations such as chromosomal translocations and aberrant expression of key cellular regulatory elements, as well as alterations in signalling pathways that have the potential to induce oncogenic changes (Darnell, 2002;

Vardiman et al., 2009). Cytogenetic aberrations include chromosome polyploidy/deletion or translocation. The former alters gene copy number, resulting in over-expression of oncogenic proteins or reduced gene dosage of tumour suppressors, while the latter leads to expression of proteins with aberrantly regulated functions

(Peters and MacCormac, 1987; Shanafelt et al., 2006). Molecular lesions include small additions, deletions or point mutations which typically alter signalling pathways and impact on downstream transcriptional control (Hagmar et al., 1998; Han et al., 1984; 7

Huang: Chapter 1. Literature Review

Mrozek et al., 2001). The expression levels of certain genes have also been recognised as independent prognostic markers to predict patient outcome in molecular subsets of

AML and ALL patients (Eid et al., 2010; Marcucci et al., 2011; Metzeler et al., 2009;

Vrooman and Silverman, 2009).

Despite our growing understanding of the leukaemogenic process, novel treatment strategies are still required to improve the survival rates of patients with acute leukaemias, especially AML. The overall 5 year survival rate1 for AML patients is just

20%, meaning that 80% patients will succumb to the disease within five years of diagnosis. Only 5% of older patients (>65 yrs) survive after 5 years of diagnosis (Davis et al., 2014; Estey and Dohner, 2006). The overall 5 year survival rate of ALL for all age groups is 70%; however, only 40% patients aged 25 and above survive after 5 years of diagnosis and this number further drops to 15% for patients aged 65 and above

(Davis et al., 2014; Narayanan and Shami, 2012). Deeper understanding of aberrant haematopoiesis will result in finer stratification of patients into risk categories and subsequently the development of personalised treatment regimens (Guzman and Allan,

2014).

1.3. Transcriptional control of haematopoiesis

The gene regulatory state is defined by concerted actions of various components including cell surface receptors, upstream mediators, chromosome structure, and importantly transcription factors (Wilkinson and Gottgens, 2013). Blood homeostasis and the identity of blood cells are tightly regulated by transcriptional regulatory

1 The 5 year period is calculated from the date of diagnosis. 8

Huang: Chapter 1. Literature Review networks which governs the patterns of genes gene expression and ultimately define cell phenotype (Orkin, 1995; Orkin and Zon, 2008). Transcription factors are common targets of oncogenic activities, thus are frequently involved in the development of leukaemia through their roles in maintaining transcriptional regulation in the haematopoietic system (Eppert et al., 2011; Kvinlaug et al., 2011).

1.3.1. The role of transcription factors in controlling gene output

A transcription factor is a protein that directly or indirectly binds to specific

DNA sequences to modulate (initiate or repress) the first step in protein synthesis, that is, the transcription of genetic information from DNA to mRNA (Levine and Tjian,

2003). Transcription factors reside in or translocate into the nucleus to modulate gene expression by binding to specific DNA sequences, recruiting the transcriptional machinery including other factors and RNA polymerases, and thereby regulating processes such as cell growth, development and differentiation (Leeanansaksiri and

Dechsukhum, 2006). The transcription machinery is a complex of many proteins, some in common for all genes and some unique to particular gene targets (Pennisi, 2000). It is the specific binding of transcription factors that determines in large part the connectivity of gene regulatory networks as well as the quantitative level of gene expression (Tan et al., 2008a).

To aid the recognition of coding genes by RNA polymerase, one or more transcription factors must be bound to certain regulatory regions to form a functional transcription initiation complex (Figure 1-2) (Luscombe et al., 2000; Noonan and

McCallion, 2010). Such regulatory elements include promoter, enhancer or other

Huang: Chapter 1. Literature Review regulators. Specifically, promoters are found in the 5’ end of genes directly adjacent to the transcription start site (Figure 1-2) (Noonan and McCallion, 2010). Enhancers and repressors, on the other hand, are generally located away from the transcription initiation sites (Figure 1-2) (Noonan and McCallion, 2010). Different from promoters, enhancers and repressors can be upstream, downstream, or intronic of the coding gene

(Noonan and McCallion, 2010). Bound enhancers/repressors can remotely impact on the activity of the promoters to promote or inhibit transcription initiation, respectively

(Figure 1-2) (Noonan and McCallion, 2010). Therefore, not only the accessibility of the chromatin, but also the binding of transcription factors are necessary for the initiation of

RNA synthesis.

The human genome encodes a large number of transcription factors, which contribute to complex gene regulation, accurate developmental patterning and growth control (Wei et al., 2010). It is estimated that HSCs express approximately 200 different transcription factors which regulate distinct sets of target genes in temporally and spatially appropriate patterns and at correct levels to ensure normal development

(Leeanansaksiri and Dechsukhum, 2006; Zhu and Emerson, 2002). The specificity and accuracy of transcriptional output is of paramount importance, as dysregulation of transcriptional response leads to many human diseases including cancer (Gilliland,

2001; Oikawa, 2004; Tootle and Rebay, 2005).

Huang: Chapter 1. Literature Review

Figure 1-2 Schematic of transcription factor bound regulatory elements. Gene regulatory elements are upstream of the coding gene. The general transcriptional machinery binds to the promoter (P) sequence to mediate basal transcriptional control of a gene. Enhancer (E) and repressor (R) sequences mediate positive and negative effects of transcription through interaction with the promoter sequence.

Huang: Chapter 1. Literature Review

As mentioned above, haematopoiesis is defined as blood cell development from pluripotent HSCs to phenotypically distinct mature blood cell lineages (Orkin, 1995).

Each commitment step requires the activation of lineage-specific genes, while unnecessary and conflicting genes are concomitantly repressed via concerted regulations by transcription factors (Nerlov et al., 2000). In this way, transcription factors enable haematopoietic cells to attain functionally distinct phenotypes through the activation of specific gene expression and thus, control much of haematopoiesis (Orkin and Zon, 2008). Functional characterisation of transcription factor activities and their interactions with signalling pathways is required for the understanding of HSPC cell fate regulation (Gottgens, 2015; Novershtern et al., 2011; Orkin and Zon, 2008). During the past decade, a map of transcriptional activators and repressors that regulate gene expression in HSCs, their precursors and progenies, at distinct stages of development has been drafted (Aggarwal et al., 2012; Orkin and Zon, 2008; Wilkinson and Gottgens,

2013). These factors control a program that first establishes the pool of HSCs in the foetus, and later guides decisions between self-renewal, lineage commitment with progressive differentiation and quiescence to maintain homeostasis (Novershtern et al.,

2011). A good example is the toggle switch formed by the globin transcription factor 1

(GATA1) and the purine protein binding protein 1 (PU.1) which acts in a see-saw fashion to regulate the binary fate decision between erythroid and myelomonocytic commitment (Huang et al., 2007; Nerlov et al., 2000). When GATA1 concentration increases and PU.1 concentration decreases, the multipotent progenitor cell differentiates into erythroid cells, while expression of PU.1 inhibits GATA1 expression and drives myelomonocytic differentiation (Huang et al., 2007).

Huang: Chapter 1. Literature Review

The genetic program directing haematopoietic fate determination involves known developmental signalling pathways that converge on the directed expression of a small set of pivotal haematopoietic transcription factors (Aggarwal et al., 2012;

Novershtern et al., 2011). Changes in the expression levels of these factors can significantly impact on the normal gene expression patterns and cellular phenotype

(Brown et al., 2010; Darnell, 2002). Aberrant regulation of the regulatory mechanisms such as the epigenetic environment and post-translational modifications can also engender the onset of malignancies in the HSPC compartment (Chang and Karin, 2001;

Gottgens, 2015; Redig and Platanias, 2008). Oncogenic activity can result from the activation of existing transcription factors, abnormal expression of transcription factor genes, or the formation of chimeric transcription factor genes (Darnell, 2002).

Development of therapeutic strategies for inhibiting transcription is of major interest for modulating gene expression associated with various malignancies (Darnell, 2002).

Knowledge and insights gained from the study of HSC-related transcription factors will ultimately be directed toward molecular clinical therapies of human blood-related genetic diseases and leukaemias. It is therefore essential to assess the veracity of inferred regulatory networks through subsequent experimental validation.

1.3.2. The ETS family of transcription factors

Most transcription factors can be grouped into families based on common DNA binding domains leading to similar DNA sequence preferences (Ko and Engel, 1993).

The ETS family of transcription factors is characterised by a highly conserved 85 amino acid winged helix-turn-helix motif called the ETS domain that allows monomeric binding to a core recognition sequence 5’-GGAA/T-3’ in the promoter or enhancer of

Huang: Chapter 1. Literature Review their target genes (Donaldson et al., 1996). Over 25 mammalian ETS family members control various haematopoietic processes, including cellular proliferation, differentiation, lymphocyte development and activation, transformation and apoptosis

(Hollenhorst et al., 2007; Oettgen, 2009; Seth and Watson, 2005) (Figure 1-3). ETS factors are also associated with cellular transformation and cancer progression through regulation of target genes including oncogenes, tumour suppressor genes, apoptosis- related genes, differentiation-related genes, angiogenesis-related genes, and invasion and metastasis-related genes (Baldus et al., 2006; Bohne et al., 2009). Therefore, ETS factors and/or the genetic pathways that they regulate could be potential molecular targets for selective cancer therapy (Oikawa, 2004). The important role of these factors in normal blood development is highlighted by the direct link between haematopoietic defects and aberrant regulation of ETS factor expression or expression of the mutant

ETS factor forms (Hsu et al., 2004; Huang et al., 2008; Huang et al., 2009; Lacadie and

Zon, 2011; Oikawa and Yamada, 2003; Stankiewicz and Crispino, 2009).

Huang: Chapter 1. Literature Review

Figure 1-3 Phylogenetic tree of the ETS family. ETS family phylogenetic tree linking members with closely homologous amino acid sequences to demonstrate their evolutionary relationship. The horizontal branch lengths relate to predicted evolutionary distance. Longer branches are more divergent and short branch lengths indicate highly similar homologs. Human (black) and drosophila (blue)

ETS members are shown including alternative aliases. Image adapted from Oettgen

(2009) and Hollenhorst (2007).

Huang: Chapter 1. Literature Review

A complex network of various pathways regulates the development and regulation of HSCs (Wilkinson and Gottgens, 2013). Several ETS transcription factors were identified to be essential for development of definitive haematopoiesis during embryogenesis (Hsu et al., 2004; Seth and Watson, 2005). One of the hallmark ETS factors involved in haematopoietic development is PU.1, which activates gene expression during myeloid and B-lymphoid cell development (Nerlov et al., 2000).

Other ETS factors include the two closely related transcriptional activator proteins ERG and Friend Leukaemia virus Integration site 1 (FLI1), which both play crucial roles in haematopoietic development (Kruse et al., 2009; Taoudi et al., 2011) and multiple forms of cancer (Lessnick and Ladanyi, 2012; Martens, 2011; Tomlins et al., 2005).

1.4. The ETS-related gene (ERG)

The human ERG gene (ENSG00000157554, http://www.ensembl.org/, release

81-July 2015) is located on chromosome 21 (location 21q22.3, gene coordinate chromosome 21: 38,380,027-38,661,780, genome build/assembly GRCh38/hg38). The gene product ERG corresponds to Uniprot identifier P11308 (http://www.uniprot.org/).

Combinations of multiple promoters and three alternative translation initiation sites give rise to 16 transcripts (splice variants) in human cells (Cunningham et al., 2015;

Duterque-Coquillaud et al., 1993; Rao et al., 1987). At least five ERG isoforms are transcriptionally active and bind to the consensus ETS motif (5’-GGAA/T-3’) via the

ETS domain (Wang et al., 1992). Different isoforms show cell-type specific expression with ERG2 and ERG3 being best characterised due to their frequent implications in cancers (Iwamoto et al., 2001; Vijayaraj et al., 2012). Two promoters drive the expression of the ERG gene (Bohne et al., 2009; Owczarek et al., 2004). The ERG2

Huang: Chapter 1. Literature Review isoform arises from a distal promoter and is largely found in solid organs such as the prostate (Figure 1-4A) (Duterque-Coquillaud et al., 1993; Owczarek et al., 2004).

Transcription of the ERG3 isoform is regulated by the alternate proximal promoter and is the predominant isoform in the blood lineages (Figure 1-4A) (Bohne et al., 2009;

Owczarek et al., 2004). Apart from the promoters involved and the resulting N-terminal sequence of amino acids, the major difference between these two isoforms is the presence of exon 12 in ERG3 (Figure 1-4A). Another ERG3-like isoform lacking exon12 is referred to as ERG3∆exon12. Full length ERG mentioned in this study refers to ERG3.

Transcription factor proteins contain a number of functional domains which determine the specificity of their actions, including DNA binding, transcriptional activation and protein partner binding domains (Mackereth et al., 2004; Marais et al.,

1993; Siddique et al., 1993). Full length ERG3 consists of 486 amino acids, with the

Pointed (PNT) domain spanning amino acids 120-206 and the ETS domain covering amino acids 318-398 (Figure 1-4B) (Carrere et al., 1998; Siddique et al., 1993). The

PNT domain is conserved within a subset of ETS factors (Sood et al., 2009) regulating

ERG interaction with other proteins (Carrere et al., 1998; Mackereth et al., 2004). The

ETS domain defines ERG as an ETS factor and mediates ERG binding to DNA (Graves et al., 1996; Sharrocks et al., 1997). The unstructured regions around the functional domains may also participate in regulating transcription factor activity by interacting with the functional domains or with other proteins (Daughdrill et al., 2007; Olson et al.,

2005).

Huang: Chapter 1. Literature Review

Figure 1-4 Human ERG gene and protein structure.

(A) Gene structures of human ERG isoform 2 and 3. The exons are in blocks with exon numbers labelled above. White indicates untranslated regions (UTR), grey indicates coding region, black indicates the ETS domain. DP, distal promoter; PP, proximal promoter. Image made by J. Thoms based on information from Owczarek et al. (2004) and Bohne et al. (2009). (B) Linear protein structure of human ERG isoform 3 with two functional domains. PNT, Pointed; ETS, E-twenty six. The amino acids are numbered underneath.

Huang: Chapter 1. Literature Review

1.4.1. ERG in normal haematopoiesis

In mammals, ERG play a key role in multiple developmental processes during embryogenesis including definitive haematopoiesis (Loughran et al., 2008), angiogenesis (Birdsey et al., 2012), cartilage and bone development (Iwamoto et al.,

2001) and development of the cardiac system (Vijayaraj et al., 2012). ERG continues to function in adult processes such as haematopoiesis by maintaining self-renewal of the

HSCs in the bone marrow (Ng et al., 2011), angiogenesis by regulating endothelial cell survival, motility and tubulogenesis (Birdsey et al., 2008; Birdsey et al., 2012; Hewett et al., 2001; Mohamed et al., 2010), and skeletal homeostasis by blocking differentiation of chondrocytes (Flajollet et al., 2012). The focus of this review is the role of ERG in regulating haematopoiesis.

ERG’s role in definitive haematopoiesis was established using the Mld2

(multilineage defect) missense mutation, turning serine 329 into a proline residue

(S329P) in the ETS domain of ERG (Loughran et al., 2008; Ng et al., 2011). Despite equivalent stability to wild type ERG and intact DNA binding capacity, the mutation abolished ERG’s transcription initiation ability. Homozygous adult mice (ErgMld2/Mld2) exhibit impaired definitive haematopoiesis and die at midgestation (Loughran et al.,

2008). Further analysis of murine embryo chimeras has revealed that although Erg is dispensable for HSC formation and specification, it is essential for HSC self-renewal and thus, for the maintenance of definitive haematopoiesis during development (Taoudi et al., 2011). Heterozygous adult mice (Erg+/Mld2) experience a reduction in HSPC numbers and mild thrombocytopenia (Loughran et al., 2008), which suggests a role of

Erg during megakaryocyte maturation or platelet release (Ng et al., 2011). A role for

ERG in early haematopoiesis has also been proposed by Taoudi et al., that while ERG is 19

Huang: Chapter 1. Literature Review dispensable during HSC specification and initiation of definitive haematopoiesis, it is later required for driving the expression of Runt-related transcription factor 1 (RUNX1) and GATA2 in order to maintain HSC numbers (Taoudi et al., 2011).

In adults, correct ERG gene dosage is critical for the maintenance of HSC function (Loughran et al., 2008; Taoudi et al., 2011). During normal haematopoiesis within both the myeloid and the lymphoid lineages, ERG is highly expressed in the primitive populations such as the HSCs, while its expression is down-regulated as the blood cell differentiates into progenitors, and further drops in the terminally differentiated cells such as granulocytes, monocytes, and T cells (Bohne et al., 2009;

Rainis et al., 2005; Thoms et al., 2011). It is worth noting that a gradual decrease rather than an immediate and complete switching-off of ERG expression is observed when

HSCs differentiate into haematopoietic progenitor cells (HPC). The significance of this phenomenon is that besides maintaining the stem cell population, a self-renewal program in these partially differentiated cells could potentially be re-initiated when repopulation is needed (Novershtern et al., 2011).

1.4.2. ERG in cancer

Apart from being an essential regulator of haematopoiesis, ERG has also been recognised as a potent oncogene in humans and mice (Goldberg et al., 2013; Metzeler et al., 2009; Salek-Ardakani et al., 2009; Thoms et al., 2011). Various chromosomal translocations involving the ERG gene, together with ERG over-expression, have been reported in many types of malignancies particularly prostate cancer and leukaemia

(Baldus, 2004; Ichikawa et al., 1994; Klezovitch et al., 2008; Kong et al., 1997).

Huang: Chapter 1. Literature Review

1.4.2.1. ERG translocations and cancer

The central aim of cancer research is to identify altered genes that play a causal role in cancer development (Workman, 1999). Many such genes have been identified through the analysis of recurrent chromosomal rearrangements that are characteristic of various malignancies (Rowley, 2001). Through the association of chromosomal translocations with a particular phenotypic change in cancer, it has been shown that transcription factors are commonly involved in oncogenesis, via their ability to alter the expression of cellular genes (Codrington et al., 2005; Pan et al., 2008; Tomlins et al.,

2005; Wiedemann et al., 1991).

Two major types of protein products resulting from chromosome translocation have been described in the literature. The first type results in the expression of a protein fused to a regulatory element which regulates its aberrant expression. A well- documented example of ERG truncation is the fusion of the androgen-responsive trans- membrane protease, serine 2 (TMPRSS2) gene to the DNA binding ETS domain of

ERG (Soller et al., 2006; Tomlins et al., 2005). In normal prostate epithelium,

TMPRSS2 expression is induced by androgen receptor binding which subsequently regulates epithelial cell differentiation (Yu et al., 2010). In 50% prostate cancer cases, fusion of the 5’ untranslated exon of TMPRSS2 containing the androgen-responsive element and the exons encoding ERG DNA-binding domain is generated by a common chromosome translocation (Clark et al., 2007; Soller et al., 2006; Tu et al., 2007).

Androgen receptor binding consequently leads to high expression of N-terminally truncated ERG in the prostate epithelium, which then drives the expression of an

Huang: Chapter 1. Literature Review oncogenic gene signature and generates a neoplastic phenotype (King et al., 2009; Tu et al., 2007). The presence of the TMPRSS2-ERG fusion gene is associated with poor prognosis (Soller et al., 2006; Tomlins et al., 2005) and has been shown to induce the development of pre-cancerous prostatic intraepithelial neoplasia (PIN) in mouse models

(Klezovitch et al., 2008; Tomlins et al., 2005).

The second type of translocation yields chimeric fusion proteins containing translated functional domains encoded by different genes. An example of ERG fusion protein is TLS (translocation liposarcoma)-ERG, which juxtaposes the TLS gene on chromosome 16 and the ERG gene on chromosome 21, resulting in the expression of a fusion protein (Ichikawa et al., 1994; Kong et al., 1997). In the chimeric protein, the

DNA-binding domain of ERG is retained while the N-terminus is replaced by the TLS

N-terminal RNA-binding motif which activates transcription (Ichikawa et al., 1994;

Kong et al., 1997; Prasad et al., 1994). As a result, the fusion protein with multiple functional domains is capable of altering normal cellular processes by activating aberrant gene expression (Pereira et al., 1998). TLS-ERG fusion has been associated with poor prognosis in human AML, secondary AML associated with myelodysplastic syndrome (MDS), and CML in blast crisis (Ichikawa et al., 1994; Kim et al., 2009a;

Kong et al., 1997; Pan et al., 2008; Prasad et al., 1994). Additionally, TLS-ERG over- expression by retroviral transduction of primary human HSPC induces a proliferation pattern similar to that seen in human myeloid leukaemia including enhanced self- renewal of immature cells as well as aberrant myeloid and erythroid differentiation

(Pereira et al., 1998; Warner et al., 2005). Over-expression of TLS-ERG in a myeloid progenitor cell line also induces a more proliferative phenotype than transduction with

ERG alone, and blocks terminal differentiation (Ichikawa et al., 1994; Pan et al., 2008). 22

Huang: Chapter 1. Literature Review

The oncogenic activity of TLS-ERG in multiple leukaemia types suggests a significant contribution by this fusion to leukaemogenesis. Another example of ERG fusion protein formation is the EWS (Ewing sarcoma)-ERG fusion which is found in 10% of Ewing sarcoma cases (Hsu et al., 2004; Oikawa and Yamada, 2003). Fusion of the 5’ activation domain of the Ewing sarcoma breakpoint region 1 (EWSBR1) gene to the highly conserved 3’ DNA binding domain of an ETS family member (examples including ERG and the closely related FLI1, with FLI1 fusion more commonly found) is characteristic of Ewing sarcoma (Oikawa and Yamada, 2003; Sorensen et al., 1994) and plays a role in initiating a malignant phenotype (Codrington et al., 2005).

A significant overlap in gene expression profiles induced by different ERG- associated chromosome translocations further emphasises the role of ERG in the onset of malignancies (Cironi et al., 2008; Ladanyi, 1995) and also suggests that ERG over- expression would promote established cancer.

1.4.2.2. ERG over-expression and cancer

In addition to its presence in chromosomal translocations, over-expression or aberrantly maintained expression of ERG is also capable of promoting and maintaining leukaemia (Baldus et al., 2006; Marcucci et al., 2007; Thoms et al., 2011; Tsuzuki et al.,

2011). Trisomy of ERG has also been strongly implicated in the development of transient haematological malignancy in Down syndrome (Ng et al., 2010; Rainis et al.,

2005).

Huang: Chapter 1. Literature Review

As mentioned earlier, ERG expression is high in the HSC population but low in the differentiated haematopoietic cells (Rainis et al., 2005; Thoms et al., 2011). A key characteristic of leukaemia is the enlarged proportion of immature cells due to enhanced proliferation as well as blocked differentiation (Becker and Jordan, 2011; Lane and

Gilliland, 2010). Consequently, high level of ERG can be indicative of a leukaemogenic phenotype (Martens, 2011). Several studies reported aberrantly maintained ERG expression as a prognostic marker for poor clinical outcome in adult leukaemia (Baldus et al., 2006; Hecht et al., 2013; Marcucci et al., 2007). In multiple leukaemia types including cytogenetically normal AML (Eid et al., 2010; Marcucci et al., 2007; Schwind et al., 2010), complex karyotype AML (Baldus, 2004; Hecht et al., 2013), and T-ALL

(Baldus et al., 2006; Baldus et al., 2007), high ERG level predicts higher incidence of relapse, while patients with low ERG level tend to have improved survival rate.

Additionally, a high risk type of T-ALL, early T-cell precursor ALL (ETP ALL), shows higher ERG expression levels than typical T-ALL, which is considered linked to the inferior survival of this leukaemia subtype (Coustan-Smith et al., 2009).

The mechanism of ERG-driven leukaemogenesis is implicated in the onset of an oncogenic gene signature. For example, in cytogenetically normal AML with ERG over-expression, genes associated with proliferation are up-regulated, while expression of genes promoting differentiation and apoptosis is inhibited (Marcucci et al., 2007).

Additionally, ERG is thought capable of maintaining its own expression in the absence of chromosome translocation via the activity of the ERG +85 enhancer (Diffner et al.,

2013; Thoms et al., 2011). Located 85 kb downstream of the murine Erg promoter

(Wilson et al., 2010), the ERG +85 enhancer is active in both the HSCs and acute leukaemic cells such as the MOLT-4 cell line (Thoms et al., 2011; Wilson et al., 2010). 24

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This enhancer drives ERG expression when bound by the leukaemogenic transcription factor heptad including stem cell leukaemia (SCL), lymphoblastic leukemia associated haematopoiesis regulator 1 (LYL-1), LIM domain only 2 (LMO2), FLI1, GATA2,

RUNX1 and ERG itself (Diffner et al., 2013; Wilson et al., 2010). Besides ERG, many of these components also positively regulate their own expression as well as the expression of other members, suggesting the expression of the heptad can be self- sustaining to maintain a stem cell-like gene signature (Beck et al., 2013). In another study of the same enhancer, Diffner et al. reported the global gene expression signature of an AML group more closely resembled HSCs than other AML groups and independently predicted worse survival when compared to an AML group with inactive

ERG +85 enhancer (Diffner et al., 2013). The indispensability of ERG in maintaining the transcriptome for a primitive phenotype is therefore well-addressed by its sustained expression in leukaemic cells (Diffner et al., 2013; Thoms et al., 2011).

ERG’s role in leukaemia is also implicated in Down syndrome. Characterised by a trisomy of chromosome 21, Down syndrome patients have an extra copy of all the genes on chromosome 21 including ERG, which can lead to the onset of transient myeloproliferative disorder (TMD) (Ng et al., 2010; Rainis et al., 2005; Roy et al.,

2009). TMD is observed at birth in approximately 10% of Down syndrome children,

30% of which later transforms into acute megakaryocytic leukaemia (AMKL) (Hasle et al., 2000; Roy et al., 2009; Zipursky, 2003). A Down syndrome mouse model with three copies of Erg shows development of megakaryocytic dysplasia, thrombocytopenia, increased numbers of undifferentiated cells and decreased numbers of red blood cells

(Ng et al., 2010). Normal haematopoiesis is restored by reducing Erg copy number to n=2 (Ng et al., 2010), indicating that trisomic ERG is required for the Down syndrome- 25

Huang: Chapter 1. Literature Review associated TMD. Additionally, a truncated version of GATA1 (GATA1s) has been detected in all cases of Down syndrome-derived TMD and AMKL (Rainis et al., 2005).

Enhanced megakaryocytic progenitor expansion and blockage of erythrocyte differentiation are observed via the synergy of ERG with GATA1s (Birger et al., 2013;

Rainis et al., 2005).

Studies using murine models with over-expression of Erg also provided evidence of ERG being a potent leukaemogenic factor (Carmichael et al., 2012;

Goldberg et al., 2013; Salek-Ardakani et al., 2009; Thoms et al., 2011; Tsuzuki et al.,

2011). When transplanted with transduced foetal liver progenitors over-expressing Erg, mice develop AMKL, manifested as increased proliferation and prolonged replating capacity of the megakaryocytic progenitors (Salek-Ardakani et al., 2009). Adult mice with enforced haematopoietic Erg over-expression also experience rapid development of lymphoid leukaemia as well as erythro-megakaryocytic leukemia (Carmichael et al.,

2012). Additionally, an early progenitor myeloid leukaemia induced by transgenic Erg expression shows activation of a transcriptional program similar to high ERG expressing human AML (Goldberg et al., 2013). Data from these murine models suggest that not only high ERG level induces leukaemia, and also more importantly, it does so by transforming the immature cells with multi-lineage potential via the induction of a leukaemogenic gene signature.

Despite its frequent implication in cancers, over-expressed ERG has not been evaluated as a potential therapeutic target, possibly due to its indispensable physiological roles in HSPCs and in turn the lack of a therapeutic window. However, there have been no studies to date examining the difference in the post-translational 26

Huang: Chapter 1. Literature Review regulation of ERG activity between leukaemic cells and normal HSPCs. This represents a significant gap in our understanding of ERG and its role in leukaemia. Given that perturbing protein modification that dysregulates ERG transcriptional activity would be a feasible approach to treat ERG-related malignancies by sparing its physiological functions, the identity of the aberrantly regulated signalling cascades requires elucidation.

1.5. Post-translational regulation of protein function

The precise modulation of gene transcription plays a vital role in both development and response to the environment of all higher organisms (Aggarwal et al.,

2012; Levine and Tjian, 2003). The temporal activation or repression of specific genes is accomplished via a plethora of transcriptional regulators (Walsh et al., 2005). The diversity of the metazoan proteome greatly exceeds the number of proteins predicted by

DNA coding capacities (Munoz and Heck, 2014). The two major mechanisms for expanding the genome coding capacity to generate diversity in the corresponding proteome are mRNA splicing (Black, 2003; Maniatis and Tasic, 2002) and post- translational modification (PTM) of proteins (Bode and Dong, 2004; Hunter and Karin,

1992; Seo and Lee, 2004). The significance of the latter mechanism is shown by the fact that primary gene induction or repression in eukaryotes does not require de novo protein synthesis (Krishna and Wold, 1993), instead, cells can respond rapidly to extracellular stimuli by altering the location and activities of transcription factors through the use of

PTMs (Tootle and Rebay, 2005). While transcriptome analysis can identify a cell- specific gene expression signature, the addition of proteome analysis adds penetration and biological information to our knowledge of protein functions (Unwin et al., 2006).

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Therefore, a comprehensive characterisation of transcription factor activity must include the higher-order modes of regulation such as protein modifications (Tian et al., 2004).

1.5.1. Post-translational modifications (PTMs)

PTM refers to the covalent addition of a functional group to a protein after its translation (Krishna and Wold, 1993). Many PTMs are known to have pivotal roles in cellular physiology and diseases and have been extensively reviewed in previous literature (Han and Martinage, 1992; Krishna and Wold, 1993; Parekh and Rohlff, 1997;

Spoel et al., 2010). A brief summary of the major PTMs including glycosylation, ubiquitination, acetylation, methylation and phosphorylation is provided in this review.

Importantly, cross-talk between distinct protein modifications may also determine the spatial and temporal activity of transcription factors that in turn profile the cellular transcriptome (Seo and Lee, 2004; Walsh et al., 2005).

Glycosylation

Glycosylation, the addition of a sugar moiety to proteins, lipids, or other organic molecules inside or outside the cell (Roberts et al., 1998), represents a co-translational and post-translational mechanism of PTM (Uy and Wold, 1977). Being site and substrate specific, this covalent modification is tightly regulated and reversible (Roberts et al., 1998). Glycosylation plays a central role in protein localisation, protein-protein interaction, structural stability of the cell, immune responses and modulation of cell signalling (Varki and Lowe, 2009). Dysfunctional glycosylation events can lead to

Huang: Chapter 1. Literature Review diseases including cancer, liver cirrhosis, diabetes, and exacerbated HIV infection

(Mendez et al., 2010; Xue et al., 2010).

Ubiquitination

The major role of ubiquitination is to target proteins for degradation and recycling in a highly dynamic and coordinated fashion (Wilkinson, 1987). Proteins targeted for degradation are tagged on lysine residue(s) (K) by the covalent attachment of a small regulatory protein, ubiquitin, which can then be recognised by proteases for tight control of their concentration within a cellular compartment (Rechsteiner, 1987;

Wilkinson, 1987). Ubiquitination has a role in modulating diverse cellular functions such as cell proliferation and differentiation, autophagy, apoptosis, immune response,

DNA repair, neural degeneration, myogenesis and stress response (Jin et al., 2011; Shi and Kehrl, 2010). It is a major component in many diseases and disorders including cancer, neurodegenerative disorders, HIV infection, herpes and liver disease (Bergeron et al., 2010; Gutekunst et al., 1999; Keutgens et al., 2010; Weber et al., 1999). For example, RUNX1 can be ubiquitinated on multiple lysine residues to promote its degradation by the ubiquitin–proteasome pathway (Huang et al., 2001). Consistently, different isoforms of mouse Runx1 generated from alternative splicing show various protein stabilities depending on the numbers of lysine residues present (Komeno et al.,

2014).

Acetylation

Acetylation occurs on lysine (K) residues via the action of acetyltransferases, and is also a co-translational and post-translational process (Arif et al., 2010).

Acetylation as well as deacetylation of histones is of particular interest due to its role in 29

Huang: Chapter 1. Literature Review chromatin conformation regulation and subsequent gene regulation (Choi and Howe,

2009). Hyperacetylated chromatin is transcriptionally active, and hypoacetylated chromatin is silent (Blanca et al., 2008). For example, acetylation of K4 on histone H3

(denoted as ‘H3K4’), one of the five main histone proteins involved in the structure of chromatin in eukaryotic cells, is a marker of open chromatin, which allows access of the transcriptional machinery including various transcription factors and RNA polymerase

(Gavazzo et al., 1997; Hebbes et al., 1988). Removal of the neutral acetyl groups by histone deacetylases increases the positive charge of histones by exposing lysine side chains and encourages high-affinity binding between histones and negatively-charged

DNA. The increased DNA binding condenses DNA structure and prevents transcription

(Chen and Townes, 2000; Popova et al., 2009). Thus, a single lysine alteration on histones can significantly impact the cellular homeostasis by altering downstream gene expression (Arif et al., 2010; Glozak et al., 2005).

Methylation

Protein methylation has impact on many physiological processes including embryogenesis and postnatal development (Migliori et al., 2010; Yang et al., 2009) as well as numerous pathological conditions such as cancer and occlusive disease

(Dudman et al., 1996; Weaver, 2007). The most commonly methylated amino acid residues are lysines (K) and arginines (R). Lysine methylation is of particular interest due to its role in epigenetics and chromatin remodelling upon acetylation (Yang et al.,

2009). For example, trimethylated/monomethylated K4-acetylated histone H3 (denoted as ‘H3K4me3’/‘H3K4me1’) are correlated with active promoter (Gao et al., 2010;

Huang et al., 2012; Okitsu et al., 2010; Wei et al., 2009)/enhancer regions (Fernandez et al., 2015; Tran and Huang, 2014) of genes, respectively. In contrast, trimethylation of 30

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K27 on histone H3 is a marker of silenced regions (Barski et al., 2007; Rosenfeld et al.,

2009). Lysine methylation of non-histone proteins has also been reported. Examples include p53 (Tornaletti and Pfeifer, 1995), NF-κB (Lu et al., 2013) and other transcription factors implicated in tumourigenesis (Migliori et al., 2010; Sarris et al.,

2014). In haematopoiesis, myeloid differentiation of CD34 HSPCs is inhibited by

RUNX1 methylation at the arginine residue R223 (Vu et al., 2013).

Phosphorylation

Phosphorylation is the addition of a phosphate group onto serine (S)/threonine

(T)/tyrosine (Y) residues by a class of enzymes called kinases (Hunter and Karin, 1992).

By coupling with the action of phosphatases which remove phosphate groups, this PTM offers rapid and dynamic control of the biological activity of numerous proteins including transcription factors and is by far the most commonly reported PTM in mammalian cells (Hunter and Karin, 1992; Whitmarsh and Davis, 2000).

Phosphorylation mediates various aspects of cellular functions including proliferation, differentiation, metabolism, survival, motility and gene transcription (Ghosh and

Adams, 2011; Hunter and Karin, 1992), but is also frequently implicated in progression of cancer (Levine and Puzio-Kuter, 2010; Patschinsky et al., 1982). Being the focus of this thesis, the functional impact of phosphorylation in controlling transcription factor activity is reviewed in more detail in the following sections.

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1.5.2. Regulation of transcription factor activity by phosphorylation

Living cells sense and respond to the changing environment through signalling pathways which allow extracellular stimuli to be communicated to the gene expression circuitry within the nucleus (Chang and Stewart, 1998). Phosphorylation of transcription factors has a major role in this aspect (Tootle and Rebay, 2005). For example, latent transcription factors can be activated at the cell membrane by phosphorylation, and then enter the nucleus to participate in transcription regulation. In other pathways, the kinase enters the nucleus and regulates the activity of resident nuclear-transcription factors

(Darnell, 2002; Ghosh and Adams, 2011; Manning et al., 2002).

The mechanisms by which phosphorylation mediates transcription factor activity include alteration in its stability, translocation to the nucleus, change in DNA-binding affinity, reinforcing transcription initiation, and regulation of interaction with binding partners (Hunter and Karin, 1992) (Figure 1-5). These possibilities are not mutually exclusive, and in principle, phosphorylation at multiple sites of a protein can result in distinct modes of regulation (Tootle and Rebay, 2005).

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Figure 1-5 Phosphorylation regulates transcription factor activity.

Schematic showing how phosphorylation may affect transcription factor activity inside or outside the cell on five aspects. TF, transcription factor; P, phosphorylation.

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Protein stability

The concentration of a protein within a cellular compartment is determined by not only the rate of protein synthesis but also the rate of degradation (Whitmarsh and

Davis, 2000). A classic example of phosphorylation regulated protein stability involves the tumour suppressor p53, which is induced by various stress stimuli including DNA damage, and coordinates an adaptive gene expression programme leading to growth arrest or cell death (Bode and Dong, 2004). p53 can be phosphorylated on multiple sites by different kinases (Katayama et al., 2004; Li et al., 2004; Sakaguchi et al., 1997) For example, transcription initiation factor TFIID subunit 1 (TAF1) directly phosphorylates p53 at T55, leading to p53 degradation (Li et al., 2004). Aurora kinase A, which is frequently over-expressed in bladder and other human cancers, phosphorylates p53 at

S315, resulting in its destabilisation and degradation (Katayama et al., 2004). More interestingly, phosphorylation of p53 at different sites can have opposite downstream effects. Specifically, S392 phosphorylation enhances p53 tetramer formation upon DNA damage, which is critical to its ability to activate transcription, while S315 phosphorylation largely reverses this effect (Bode and Dong, 2004; Sakaguchi et al.,

1997).

Nuclear localisation

The modulation of nuclear translocation of a given transcription factor can be viewed as the first level of transcriptional control (Whitmarsh and Davis, 2000). The nuclear compartmentalisation of genetic material in eukaryotes allows transcription factors to be sequestered in the cytoplasm and rendered inactive through lack of access to their target sequences, which thus affords a rapid mechanism of regulation not available to prokaryotes (Tomancak and Ohler, 2010). Classic examples of 34

Huang: Chapter 1. Literature Review phosphorylation-mediated nuclear localisation include the signal transducers and activators of transcription (STAT) proteins, which are phosphorylated by the Janus- activated kinases (JAK) (Broughton and Burfoot, 2001). Specifically, the inactive form of STAT is unphosphorylated, which usually resides in the cytoplasm and is unable to bind DNA (Ruff-Jamison et al., 1995). Upon phosphorylation, STAT is able to homo- or hetero-dimerise, translocate into the nucleus, bind DNA, and activate gene expression

(Furqan et al., 2013; Valentino and Pierre, 2006). Likewise, phosphorylation of p53 at

T81 by the c-Jun N-terminal kinase (JNK) under stress conditions generally results in its stabilisation and accumulation in the nucleus, followed by activation (Buschmann et al.,

2001). Furthermore, the ETS factor ELK-1 only translocates into the epithelial cell nucleus when phosphorylated at T417 (Morris et al., 2012). The level of ELK-1 T417 phosphorylation is higher in adenocarcinoma compared to normal colon epithelial cells and correlates with the tumour differentiation grade (Morris et al., 2012).

DNA binding

Following nuclear localisation, the DNA binding activity of transcription factors can be modulated by phosphorylation (Whitmarsh and Davis, 2000). Specific binding of transcription factors largely determines the connectivity of gene regulatory networks, as well as the quantitative level of gene expression (Krajewska, 1992). Alteration in DNA binding activity by phosphorylation appears to be a common mechanism regulating many different types of transcription factors (Cowley and Graves, 2000; Imamova et al.,

1997; Ma et al., 2013; Wyszomierski et al., 1999). Phosphorylation which modulates

DNA binding generally occurs on sites either within, or adjacent to, the transcription factor DNA binding domain (Papavassiliou et al., 1992). Examples of phosphorylation regulated DNA-binding include Ikaros, a zinc finger containing DNA-binding protein 35

Huang: Chapter 1. Literature Review that plays pivotal role in immune homeostasis (Thompson et al., 2007). Phosphorylated of Ikaros by the Bruton’s tyrosine kinase (BTK) at S214 and S215 in close vicinity of zinc finger 4 within the DNA binding domain augments its sequence specific DNA binding ability, which is mandatory for its optimal function B-cell development (Ma et al., 2013).

Therapeutic approaches have been developed to target transcription factor activities by blocking their DNA interactions. An example is the blockade of retinoic acid receptor α (RARα) function for the treatment of acute promyelocytic leukaemia

(APML). The transcription factor RARα is a receptor protein whose action is regulated by retinoic acid binding. The RARα gene is fused to the promyelocytic leukaemia gene in APML, and using retinoic acid derivatives that target the DNA binding activity of the

RAR moiety has proven successful in treatment of this disease (Huang et al., 1988).

Other examples include S3I-201 inhibiting STAT3 DNA binding (Siddiquee et al.,

2007), the isoquinolone alkaloid compound berberine interfering with TATA binding protein (Wang et al., 2011), or synthetic polyamides specifically designed for transcription factor DNA binding modulation through their sequence selective binding to the minor groove of the DNA helices (Doss et al., 2006).

In most cases, phosphorylated proteins tend to bind DNA with higher affinity due to the negatively charged phosphate group interacting with the positively charged

DNA backbone (Papavassiliou et al., 1992). However, a well-studied example of phosphorylation regulating ETS factor activity demonstrates that ETS1, when phosphorylated, is autoinhibited by being stabilised in an inhibitory conformation

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(Cowley and Graves, 2000). Loss of phosphorylation causes unfolding of the protein and leads to DNA binding (Cowley and Graves, 2000) (Figure 1-6).

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Figure 1-6 Model of ETS1 auto-inhibition and mechanism of phosphorylation- dependent inhibition of ETS1 DNA binding.

Electrostatic interactions between phosphoserines (P) and the basic residues of the inhibitory module of ETS1 stabilise the inhibitory conformation, shifting the equilibrium toward the folded state. DNA binding is repressed by the higher energetic cost of the conformational change that accompanies DNA binding. Image adapted from

Cowley and Graves (2000).

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Phosphorylation can also positively or negatively modulate DNA binding of the same transcription factor, depending on other factors such as the specific residue(s) being phosphorylated and other regulatory proteins interacting with the transcription factor. For example, protein kinase C (PKC)-mediated phosphorylation of several residues within the DNA binding domain of Sp1 enhances its binding to the platelet- derived growth factor (PDGF)-D promoter (Tan et al., 2008b). Conversely, casein kinase II (CK-II)-mediated phosphorylation of T668 on the same transcription factor decreased its binding to a consensus Sp1 binding site DNA sequence (Armstrong et al.,

1997). Depending on the cellular context, Sp1 can therefore respond differently to the kinases and alter gene expression accordingly.

Transcription initiation

Following DNA binding, active transcription factors initiate transcription via their transactivation domains. This process can also be affected by phosphorylation even when sequence-specific DNA binding is unchanged (Whitmarsh and Davis, 2000). In most cases, phosphorylation exerts positive regulatory effects on transactivation (Wang et al., 2012). RUNX1 is an example of transcription factor whose transactivation function is stimulated by phosphorylation (Zhang et al., 2008). RUNX1 regulates lineage-specific genes during hematopoiesis and stimulates G1 cell-cycle progression

(Ichikawa et al., 2004). Triple phosphorylation of human RUNX1 S48, S303 and S424 by cyclin-dependent kinase mildly reduces DNA affinity while progressively increasing transactivation of a RUNX1-responsive reporter and promoting cell proliferation

(Zhang et al., 2008). Another good example of phosphorylation regulated transcription activation is p53. When unphosphorylated at S15, p53 fails to mediate growth arrest, while DNA binding at a representative p53-responsive promoter remains detectable 39

Huang: Chapter 1. Literature Review

(Loughery et al., 2014). Further mechanistic analysis reveals that DNA damage does not recruit p53 with unphosphorylated S15 and fails to stimulate histone acetylation (a measure of chromatin relaxation), suggesting that pS15 is required for p53 function in the physiological context (Loughery et al., 2014).

Interaction with other proteins

Typically, transcription factors do not act independently but form complexes by direct physical contact with other transcription factors, chromatin modifiers and cofactor proteins, which bind together and assemble upon the regulatory regions of

DNA to affect transcription (Fedorova and Zink, 2008; Naef and Huelsken, 2005; Tan et al., 2008a; Zhang et al., 2004). The implication of this is that tissue-specific gene expression is not exclusively determined by the expression of certain transcription factors, but instead relies on tissue-restricted interactions among them (Tan et al.,

2008a). In other words, each factor may be expressed in a variety of tissues, but it is only where two or more transcription factors are co-expressed and co-localised that an interaction, and its functional consequences, may occur (Ravasi et al., 2010).

It is estimated that approximately 75% of all metazoan transcription factors heterodimerise with other factors (Walhout, 2006). Examples of phosphorylation affecting transcription factor binding to its protein partners include the ETS factor FLI1 in megakaryoblastic cells, where dephosphorylation enables its interaction with

RUNX1, triggers subsequent protein complex formation and activates transcription of differentiation-associated genes (Huang et al., 2009) (Figure 1-7). Additionally, transforming growth factor (TGF)-induced T312 phosphorylation of FLI1 is a prerequisite for FLI1 interaction with p300/CREB-binding protein associated factor 40

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(PCAF). The downstream effect of this is upregulated transcriptional activity of FLI1 on the collagen promoter in dermal fibroblasts (Asano and Trojanowska, 2009).

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Figure 1-7 Schematic of FLI1 dephosphorylation-mediated transcriptional complex formation.

Model of differentiation-dependent dephosphorylation of FLI1 and subsequent

FLI1/RUNX1/GATA1/FOG1 multi-protein complex formation during megakaryocytic differentiation. Image adapted from Huang et al. (2009).

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Although the transcriptional activities of many members of the ETS family are known to be modulated by phosphorylation (Asano and Trojanowska, 2009; Cowley and Graves, 2000; Huang et al., 2009; Yang et al., 1999), very little is known about the identity and mechanism of ERG phosphorylation in leukaemia development. A review of the current state of literature of ERG phosphorylation will be discussed in Chapter 3.

Establishing whether ERG phosphorylation affects its function has therapeutic implications, for one mechanism of perturbing aberrant ERG activity would be to inhibit its phosphorylation.

1.5.3. Kinases

1.5.3.1. Kinases and phosphatases

Phosphorylation is a highly dynamic and reversible process (Remenyi et al.,

2006). Phosphorylation is mediated by active protein kinases, while dephosphorylation or removal of a phosphate group is catalysed by phosphatases (Hunter, 1995). The broad spectrum of kinases and phosphatases offers various pathways that transmit a wide range of signals to gene targets via changes in the phosphorylation status of signalling intermediates and transcription factors (Ptacek et al., 2005). Examples of these signals include viruses, growth factors, cell cycle, hormones, glucose and mechanical stress (Whitmarsh and Davis, 2000). A proper balance of action between kinases and phosphatases is key to maintaining cellular homeostasis (Hunter, 1995). For example, autophagy, a cell death mechanism, is phosphorylation-dependent (Yeh et al.,

2010). Auto-phosphorylation of the Atg1 protein acts as a ‘regulatory switch’ that determines the initiation of the process (Yeh et al., 2010).

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In most systems controlled by phosphorylation, the activity of the protein kinase rather than the phosphatase is modulated (Hunter, 1995). Protein kinases represent the single largest mammalian enzyme family with more than 500 members in the human proteome and they constitute about 2% of all human genes (Manning et al., 2002).

These enzymes have been implicated in a wide array of complex cellular functions and pathways, ranging from metabolic regulation to tumourigenesis (Chang and Karin,

2001). The identification of kinase substrates and their phosphorylation sites are important for multiple reasons – the biochemical dissection of phosphorylation pathways, the role of PTM in the function of substrate proteins, the establishment of kinase-substrate relationships, and providing insights into the possible regulation of cellular physiology by signalling pathways (Mann and Jensen, 2003). Among the targets of the protein kinase cascades are nuclear transcription factors which regulate genes that ultimately confer specific cellular phenotypes (Hunter and Karin, 1992). Aberrant signalling causes many diseases, and the knowledge of kinase cascades has led to the identification of promising therapeutic targets which have been linked to various cancers as well as inflammatory, metabolic and bone diseases (Wang et al., 2012).

1.5.3.2. RAS pathway

Many kinase cascades have oncogenic activities when aberrantly regulated (Ali et al., 2009; Chohan et al., 2015; Friday and Adjei, 2008; Yip, 2015). For example, the

RAS pathway has been extensively reviewed as a molecular target for cancer treatment

(Graham and Olson, 2007; Saxena et al., 2008). The RAS proteins control signalling pathways that are key regulators of several aspects of normal cell growth and malignant transformation (Avruch et al., 1994). They are aberrant in approximately 30% human

Huang: Chapter 1. Literature Review cancers due to activating mutations in the RAS genes themselves or to alterations in the upstream or downstream signalling components (Malumbres and Barbacid, 2003;

Stirewalt et al., 2001). A concise summary of oncogenic RAS mutations can be found in

Prior et al. (2012). RAS is active when in a membrane-bound, GTP-bound state, and can be inactivated by GTPases to the GDP-bound state (Friday and Adjei, 2008) (Figure 1-

8). Oncogenic RAS mutations tend to lock RAS in its active state, resulting in constitutive RAS signalling and over-expression of genes implicated in oncogensis

(Saxena et al., 2008; Schubbert et al., 2007). Rational therapies that target the RAS pathways might inhibit tumour growth, survival and spread (Friday and Adjei, 2008;

Graham and Olson, 2007; Saxena et al., 2008).

There are three members in the RAS family, H-RAS, K-RAS and N-RAS

(Malumbres and Barbacid, 2003; Prior et al., 2012), which show varying abilities to activate different downstream cascades (Yan et al., 1998). One of the best-studied RAS- mediated pathways is the RAS-Raf–MEK–ERK signalling cascade, a classical RAS-

MAPK signalling pathway implicated in growth-factor-mediated cell proliferation, differentiation and cell death (Malumbres and Barbacid, 2003). The Raf kinases

(including A-Raf, B-Raf and C-Raf) are preferencially activated by K-RAS (Yan et al.,

1998), which then activates MEK1/2 to phosphorylate ERK1 and ERK2 (Avruch et al.,

1994; Chang et al., 2003). The RAS-Raf–MEK–ERK pathway ultimately activates cytoplasmic or nuclear proteins, including the ETS family of transcription factors, which then activates multiple genes that promote transcription, cell cycle progression and cell migration (Berndt et al., 2011; Chang et al., 2003) (Figure 1-8).

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Figure 1-8 Overview of the RAS-Raf-MEK-ERK pathway.

This figure illustrates how the RAS-Raf-MEK-ERK pathway responds to extracellular stimuli and acts on nuclear target proteins. Growth factors bind to membrane-bound receptor tyrosine kinase (RTK) and activate growth factor receptor-bound protein 2

(GRB2). This triggers SOS recruitment and increases the level of active RAS (RAS-

GTP). RAS then activates one of its key effector downstream pathways, the Raf-MEK-

ERK pathway. Active ERK1/2 (phosphorylated) phosphorylate cytoplasmic or transcription factors (Wei et al.) to activate their DNA binding and trigger the transcription of proliferation-associated genes. Phosphatases such as PP2A inactivate pERK1/2 by removing the phosphates. Image adapted from Schubbert et al. (2007).

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Dysregulation of the RAS pathway has been implicated in leukaemias. By screening the key exons of RAS signalling-associated genes from a large ALL cohort

(n=86), Case et al. found that 35% of diagnostic and 25% of relapse samples present somatic mutations that deregulate the pathway, making it one of the most common genetic aberrations (Case et al., 2008). To specifically study the oncogenic role of RAS in the context of AML, Kim et al. used a leukaemic mouse model expressing a repressible mutant of N-RAS and showed that after AML development, repression of N-

RAS expression induces a marked decrease of AML blast cells accompanied by increased differentiation and reduced disease aggressiveness (Kim et al., 2009b).

Additionally, Goldberg et al. found that transgenic Erg over-expression causes myeloid progenitor leukemia by activating a transcriptional program associated with RAS activation (Goldberg et al., 2013). Targeting the RAS pathway has therefore been widely proposed as a potential therapeutic strategy for leukaemia treatment.

1.5.3.3. MAPK/ERK pathway

1.5.3.3.1. Components of the MAPK pathway

Of the downstream pathways of RAS, an aberrantly regulated MEK/ERK cascade is most frequently reported with oncogenic activity (Chang et al., 2003; Friday and Adjei, 2008; Roberts and Der, 2007). The MAPKs are a widely conserved family of serine/threonine (S/T) protein kinases involved in many cellular programs such as cell proliferation, differentiation, motility and death (Yang et al., 2003). The MAPK signalling pathway can be activated in response to a diverse range of stimuli including mitogens, growth factors, cytokines and stress (Baccarini, 2005; Meloche and

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Pouyssegur, 2007) and is an important target in the diagnosis and treatment of cancer

(Roberts and Der, 2007). Upon stimulation, a sequential three-part protein kinase cascade is initiated, consisting of a MAPK kinase kinase (MAPKKK or MAP3K), a

MAPK kinase (MAPKK / MAP2K / MEK), and a MAPK (Kolch, 2000). The final target can be cytoplasmic substrates or most importantly, transcription factors in the nucleus (Figure 1-9).

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Figure 1-9 General set-up of the MAPK pathway.

Schematic representation of the MAPK pathway consisting of MAPKKK, MAPKK and

MAPK. MAPKKK respond to extracellular signals and MAPK is the final executor of the signalling to the transcription factors. Image adapted from Kolch (2000).

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The consensus motif of MAPK docking consists of a serine/threonine residue preceding a proline (S/TP, also called ‘proline-directed S/T’) (Clark-Lewis et al., 1991;

Crews et al., 1992). The MAPK family consists of three distinct groups of kinases:

ERK1/2, JNK and p38 (Selvaraj et al., 2015). ERK is the most studied with regards to the RAS/Raf signalling cascade in haematopoietic cells (McCubrey et al., 2007). ERK is activated through dual phosphorylation of T182 and Y184 residues by MEK (Crews et al., 1992). ERK governs mainly proliferation, differentiation, and cell survival through being activated by a wide range of cytokine and growth factor stimuli (Friday and Adjei, 2008). Increased ERK activity is associated with cell proliferation (Willard and Crouch, 2001). Similarly, JNK and p38 pathways also control cell proliferation, differentiation, survival and the migration of specific cell types (Sui et al., 2014;

Wagner and Nebreda, 2009). Physiological functions of these signalling pathways include antagonising cell proliferation and morphological transformation, whereas cancer cells can subvert these pathways to facilitate proliferation, survival and invasion

(Gallo and Johnson, 2002).

1.5.3.3.2. MAPK regulation of ETS factor activities

The RAS-MAPK signalling pathway can impact on gene expression signature by phosphorylating and altering the function of ETS transcription factors by various mechanisms including altering their subcellular localisation (Arai et al., 2002), changing their DNA binding affinity (Carlson et al., 2011) or increasing co-activator recruitment

(Foulds et al., 2004; Li et al., 2003). Knowing that an ETS factor is a MAPK target is important for understanding the regulatory mechanisms (Chang et al., 2003). For example, Plotnik et al. recently demonstrated that binding of ETS proteins to a RAS-

Huang: Chapter 1. Literature Review response element consisting of neighbouring ETS and AP-1 binding sites alters cancer cell migration (Plotnik et al., 2014). Specifically, the ubiquitously expressed ETS1 protein binds the ETS/AP-1 sequences in the enhancers of cell migration genes in a physiological context. When phosphorylated by ERK, the transactivation potential of

ETS1 is enhanced and thus the expression of cell migration-promoting genes (Plotnik et al., 2014). Another ETS factor ELK-1 contains many phosphorylation sites targeted by various MAPKs following exposure to stress or mitogenic stimuli (Gille et al., 1995b;

Li et al., 2003; Zhang et al., 2007). The different combinations of phosphorylated sites in ELK-1 allow specificity of cellular responses mediated through redundant signalling pathways activated by distinct stimuli (Gille et al., 1995a; Gille et al., 1995b; Li et al.,

2003; Yang et al., 1999). For example, growth factors and mitogens activate the Raf-

MEK-ERK pathway, resulting in regulation of growth and differentiation through transcriptional activation of ELK-1 with phosphorylated S383 (Li et al., 2005; Rao and

Reddy, 1994). Additionally, ternary complex formation of ELK-1 was enhanced by phosphorylation at S324 or S422 but inhibited by phosphorylation at T336 (Gille et al.,

1995a).

ERG contains many putative MAPK motifs (ST/P), making it a possible MAPK target (Selvaraj et al., 2015). Despite the importance of MAPK signalling in regulating the ETS family and that ERG has been confirmed as phosphorylated by ERK in prostate cancer cells (Selvaraj et al., 2015), it is unknown what phosphorylation status ERG has and how it can respond to kinase signalling pathway(s) during leukaemogenesis. The understanding of ERG interaction with kinase signalling cascades will not only help us to accumulate knowledge on how HSCs arise, function, and are regulated in the adult stage, but also will provide us insight on how leukaemia develops. 51

Huang: Chapter 1. Literature Review

1.5.3.4. Kinases as drug targets

The central role of protein kinases in signal transduction pathways has generated intense interest in targeting these enzymes for a wide range of therapeutic indications

(Graham and Olson, 2007; McCubrey et al., 2007). Specifically, manipulating signalling pathways with kinase inhibitors has emerged as a promising area of medicinal research, and several kinase inhibitors have been approved for clinical applications

(Friday and Adjei, 2008; Graham and Olson, 2007). One of the most remarkable achievements in cancer research in the last decade was the development of the tyrosine kinase inhibitor (TKI) “Gleevec” (imatinib) for the treatment of CML (Druker, 2008).

The unsurpassed success of imatinib has led to great efforts to apply the approach of targeted inhibition of kinases in other pathological conditions (Iqbal and Iqbal, 2014).

Examples include Intedanib, a triple kinase inhibitor of VEGFR, FGFR and PDGFR for the treatment of idiopathic pulmonary fibrosis (Antoniu and Kolb, 2010), Icotinib, a selective EGF receptor tyrosine kinase inhibitor for the treatment of non-small-cell lung cancer (Tan et al., 2015) and CX-4945, a CK-II inhibitor for the treatment of various human cancers including leukaemia (Chon et al., 2015) Therefore, new understanding the role of phosphorylation is critical for delineating cell signalling cascades and the development of inhibitors for therapeutic use.

1.5.4. Relevance of phosphorylation to leukaemia treatment

Modulation of oncogenic transcription factors is a promising area to develop targeted therapies, particularly in cancer (Darnell, 2002). Given the powerful potential of haematopoietic transcription factors in controlling normal haematopoiesis and their

Huang: Chapter 1. Literature Review frequent dysregulation in haematological malignancies, they are obvious therapeutic targets (Novershtern et al., 2011). However, development of drugs that precisely manipulate aberrantly regulated transcription factors while sparing their normal physiological activities has been difficult to achieve, however, hope lies in looking for aberrantly regulated upstream mediators that specifically cause the abnormal functions of their transcription factor targets (Pabst and Mueller, 2007).

Characterisation of leukaemia pathophysiology has a direct impact on disease- specific treatment strategies, diagnosis, and prognosis (Lane and Gilliland, 2010;

Narayanan and Shami, 2012). Considering leukaemia being the 8th most commonly diagnosed cancer in Australia with more than 3000 new cases diagnosed each year, identification of the molecular defects involved in the various subtypes of leukaemia is required in order to direct cancer therapy treatments and to accurately predict a patient’s response to therapy (Guzman and Allan, 2014). As more knowledge is gathered about their mechanisms of action, new substances which restore the physiological action of transcription factors and abolish leukaemogenesis may be developed (Wertheim et al.,

2012). Given the prevalence of aberrant ERG expression in leukaemia and the impact of phosphorylation on many other ETS factors, the study of ERG phosphorylation is vital to the understanding of leukaemia biology. The association between ERG phosphorylation and disease aggressiveness can be used as a prognostic parameter when analysing patient cohorts from ERG-related malignancies, which may help to divide large cohorts into more effective subsets for prognostic analyses. It could also give clinicians a more informed way of stratifying leukaemia patients for treatment purposes.

Through the ability to conform therapy to individual patients, their chance for a cure is increased (Guzman and Allan, 2014). Deeper understanding of ERG activity regulation 53

Huang: Chapter 1. Literature Review in leukaemia will augment these and provide novel target pathways for future therapies, potentially through inhibition of upstream kinase pathways.

1.6. Hypotheses and aims

It is evident that phosphorylation is an important form of PTM controlling transcription factor activity. More specifically, it has been well documented in regulating ETS factor activity in many diseases including cancer. Given the contribution of ERG to the initiation and development of leukaemia, and as an independent predictor of poor outcome in AML and T-ALL patients, it is worth questioning whether phosphorylation is a modulator at certain stages during this process.

This study was designed to examine the presence and functional impact of phosphorylation on ERG activity as a leukaemogenic transcription factor in haematopoietic cells.

The following hypotheses were proposed:

1. Endogenous ERG in leukaemic cells is phosphorylated.

2. Phosphorylation affects ERG activity as a transcription factor.

This study aimed to:

1) Identify the phosphorylation site(s) in human ERG from haematopoietic cells

(Chapter 3);

2) Examine the effect of phosphomutant ERG expression on human HSPC

expansion capabilities (Chapter 4);

Huang: Chapter 1. Literature Review

3) Identify the upstream mediator(s) regulating ERG phosphorylation in

haematopoietic cells (Chapter 5);

4) Investigate the mechanism of ERG phosphorylation in ERG activity regulation

(Chapter 6).

Huang: Chapter 2. Materials and Methods

Chapter 2. Materials and Methods

This chapter describes the general materials and methods used within this thesis.

The suppliers of materials and catalogue numbers are listed when being first mentioned in the text. A summary list of all reagents (Table S1), software and equipment (Table

S2) can be found in the appendices - supplementary materials. All procedures were carried out in PC2-certified laboratory facilities.

2.1. General tissue culture

2.1.1. Cell lines and primary cells

MOLT-4, KG-1, ME-1 and human embryonic kidney (HEK) 293T cells were purchased from ATCC. Phoenix cells were a generous gift from Dr K. MacKenzie’s lab

(Children Cancer Institute Australia). Primary leukaemic xenograft cells were generous gifts from Prof R. Lock’s lab (Children Cancer Institute Australia).

For bone marrow CD34+ HSPC, mobilised apheresis samples from granulocyte- colony stimulating factor (G-CSF) treated healthy donors were obtained from the Prince of Wales Hospital. The CD34+ fraction was purified using an automated CliniMACS cells separation system (Miltenyi Biotec, Bergist Gladbach, Germany). Collection of bone marrow from healthy donor was approved by the Ethics Committee at the Prince of Wales hospital and endorsed by the Human Research Ethics committee at UNSW

Australia.

Huang: Chapter 2. Materials and Methods

Human cord blood samples were obtained from the Sydney Cord Blood Bank

(Prince of Wales hospital) on the day of collection and enriched for CD34+ population by autoMACS (Miltenyi Biotec Australia Pty Ltd) (section 2.8.1).

2.1.2. Cell culture

All cultures were grown at 37C in 5% CO2 in highly humidified standard tissue culture incubators, and passaged when sub-confluent unless otherwise indicated. All tissue culture media were supplemented with 2 mM L-glutamine (Life technologies,

35050-061) and 100 U/ml of penicillin-streptomycin (P/S) for cell lines or 50 µg/ml of gentamicin (Life technologies, 15750-060) for human cord blood cells.

2.1.2.1. Cell line culture and cryopreservation

MOLT-4, KG-1 and ME-1 cells were maintained in Roswell Park Memorial

Institute (RPMI) 1640 medium (Life technologies, 11875-093) supplemented with 10% foetal bovine serum (FBS) (Life technologies, 10099-141). HEK293T cells were maintained in Dulbecco’s modified Eagle’s medium (DMEM) (Life technologies,

11965-092) supplemented with 10% FBS. Phoenix cells were maintained in Minimal

Essential medium alpha (αMEM) (Life technologies, 12571-071) supplemented with

10% FBS and passage number was kept below 10.

To passage adherent cells, media were aspirated and cells washed in phosphate buffered saline (PBS) prior to incubation at 37C with 0.25% trypsin ethylenediaminetetraacetic acid (EDTA) (Life technologies, 15090-046) until

Huang: Chapter 2. Materials and Methods detachment. Trypsin was deactivated with 1:1 dilution of growth media containing FBS.

Cells for cryopreservation were aliquoted, then centrifuged and resuspended in FBS containing 10% dimethyl sulfoxide (DMSO, Sigma, D2650) and aliquoted at 0.5-1ml per cryovial, then slow cooled in Mr FrostyTM freezing containers (Thermo Scientific,

5100-0001) to -80C, and subsequently transferred to liquid nitrogen for long term storage.

2.1.2.2. Primary cell culture

Culturing of human cord blood cells can be found in section 2.8.4. Thawing and culturing of leukaemic xenografts were gently performed using serum free QBSF-60 media (Quality Biological, 160-204-101) supplemented with 10 ng/ml Flt3L. Briefly, the frozen cryovial of cells was gently thawed in 37 °C water bath until a small core of ice remained. The cell suspension was then added drop-wise to warm QBSF-60 aliquots to wash off DMSO. The pellet was either lysed for immunoblotting (section 2.2.1) or equilibrated overnight prior to drug treatment.

2.1.3. Cell viability determination

2.1.3.1. Trypan Blue exclusion assay

The viability of cell lines and human cord blood cells were determined with

Trypan Blue (0.4%, Sigma, T8154) suspension and haemocytometer counting. The viable/dead cells were counted under a microscope for viability calculation.

Huang: Chapter 2. Materials and Methods

2.1.3.2. AlamarBlue assay

The viability of xenograft cells after treatment with MEK inhibitor (section

2.9.2) was determined by adding 15 µl AlamarBlue to 100 µl cell suspension and viability calculated by measuring end-point absorbance at 570 nm and 595 nm at 6 hr on a spectrophotometer. This experiment was performed by S. Suryani at Children Cancer

Institute Australia.

2.1.4. Stable isotope-labelling by amino acids in cell culture (SILAC)

SILAC RPMI 1640 media (Life technologies, A2494401) with L-Arginine.HCl

13 13 ( C6, 99%) and L-Lysine.2HCl ( C6, 99%) (Cambridge Isotope Laboratories Inc.,

USA) supplemented with 10% dialysed FBS (Life technologies, 26400-036) were used to culture MOLT-4 cells for six consecutive passages.

2.2. Immunoblotting

2.2.1. Preparation of whole cell lysate

The optimal volume of lysis buffer was determined empirically for each cell type, as the cell size varies. For western blotting, the optimal protein concentration of the resulting lysate was 4 mg/ml. For immunoprecipitation (section 2.3.1), the optimal protein concentration of the resulting lysate was 1-2 mg/ml.

Cells were lysed in cold RIPA (radioimmunoprecipitation assay) buffer [1%

(vol/vol) Triton X-100, 0.1% sodium dodecyl sulphate (SDS), 0.5% sodium

Huang: Chapter 2. Materials and Methods deoxycholate, 150 mM NaCl, 50 mM Tris-HCl (pH 7.5), 1mM EDTA] with 1× protease inhibitors (cOmplete Mini protease inhibitor cocktail tablets, Roche, 11836153001) and

1× phosphatase inhibitors (PhosSTOP phosphatase inhibitor cocktail tablet, Roche,

4906845001), incubated for 10 min on ice with occasional vortexing, cell debris cleared by centrifugation at 4°C, 10000 g for 10 min and supernatant transferred to fresh tubes.

Samples were stored at -80C.

2.2.2. Preparation of cytosolic and nuclear lysates

The cytosolic and nuclear fractions of MOLT-4 cells were prepared using the

Subcellular Protein Fractionation Kit (Thermo Scientific, PI-78840) following manufacturer’s instructions. Briefly, cells were collected after PBS wash and gently lysed in cold cytosolic extraction buffer (supplied) with freshly added 1× protease inhibitors and phosphatase inhibitors. After 10 min incubation on ice, the lysate was centrifuged at 2500 rpm, 5 min, 4°C with low deceleration to separate the cytosolic lysate from the nuclei. The cytosolic fraction was transfered into clean tubes, and the nuclei were further lysed in cold nuclear extraction buffer (supplied) with freshly added

1× protease inhibitors and phosphatase inhibitors. After vigorous vortexing to assist lysis, the lysate was centrifuged at 10000 g at 4°C for 10 min to remove membranous debris.

2.2.3. Protein Concentration Quantification

The protein concentrations of cell extracts were measured in duplicates using the

Biorad protein assay reagent (Biorad, 500-0006). Briefly, a standard curve was generated using serial dilutions of bovine serum albumin (BSA, Sigma, A9306) with 60

Huang: Chapter 2. Materials and Methods known concentrations. x μl sample was added to (160-x) μl milli-Q water (generally use

1 μl sample in 159 μ water, scale up or down as needed so that the final reading lies within the standard curve) in a clear flat-bottomed 96-well plate. 40 μl protein assay reagent was then added and mixed thoroughly with the diluted sample by agitating at

1000 rpm for 15 sec. The plate was then subjected to an endpoint reading at 620 nm using the SpectraMAX 190 absorbance microplate reader (Biostrategy). The protein concentration was calculated as the average value of duplicate measurements in reference to the BSA standard curve.

푃푟표푡푒𝑖푛 푐표푛푐푒푛푡푟푎푡𝑖표푛 (푚푔/푚푙)

(퐴푣푒푟푎푔푒 푟푒푎푑𝑖푛푔 − 푦 𝑖푛푡푒푟푐푒푝푡) = 푠푙표푝푒

200 × ( ) 푣표푙푢푚푒 표푓 푠푎푚푝푙푒 푎푑푑푒푑 (휇푙)

2.2.4. SDS-polyacrylamide gel electrophoresis (SDS-PAGE)

The same quantity of protein (50 µg/lane) was aliquoted for each sample, and sample volume increased to the same amount with appropriate lysis buffer. A final concentration of 1× NuPAGE LDS sample buffer (Life technologies, NP0007) and

0.1M dithiothreitol (DTT, Sigma, D9779) was added and heated to 95C for 5 min on a dry heating block to linearise protein. Samples were quick cooled on ice and pulse centrifuged, then loaded into a NuPAGE Novex 4 – 12% Bis Tris gradient gel (Life technologies, NP0321BOX). SeeBlue Plus2 molecular weight marker (7 l/lane) (Life technologies, LC5925) was run in parallel to determine protein sizes. Proteins were electrophoresed at 120 V for 1.5 hr in 3-(N-morpholino)propanesulfonic acid) (MOPS)

Huang: Chapter 2. Materials and Methods running buffer (Life technologies, B0001) until the dye front reached the bottom of the gel.

2.2.5. Protein transfer

Following electrophoresis, proteins were transferred from the gel to nitrocellulose membrane (iBlot transfer stack, Life technologies, IB3010-02) using an iBlot system (Program 3, 8.5 min transfer, Life technologies). The membrane was then washed in Tris-buffered saline (TBS) and stained in Ponceau S solution (Sigma, P7170) for 1 min with gentle agitation at room temperature2 before rinsing in TBS to confirm even and complete transfer.

2.2.6. Antibody probing

The membrane was rinsed in TBS to wash off the Ponceau S staining, and blocked while rocking in fresh 5% skim milk (Woolworths)/TBS or 3% BSA/TBS for 3 hr at 4°C. Primary antibody was diluted in 3% skim milk/TBS-Tween (TBS-T, 0.05% v/v) or 1% BSA/TBS-T and incubated with the membrane with rocking at 4C overnight. Excess antibody was removed with 3× 5 min rocking in TBS-T, and secondary antibody was diluted in 3% skim milk/TBS-Tween20 (TBS-T, 0.05% v/v,

Sigma, P2287) or 1% BSA/TBS-T and incubated at 4°C for 3 hr, followed by 3 additional TBS-T washes. For the detection of more than one protein (e.g. ERG and β-

2 All procedures carried out at room temperature referred to a standard air-conditioned PC2 laboratory with temperature at 20-25°C. 62

Huang: Chapter 2. Materials and Methods actin), the membrane was reprobed without stripping 3 . Specific antibody probing conditions are listed in Table 2-1.

3 Stripping causes significant loss of protein on nitrocellulose membranes. 63

Huang: Chapter 2. Materials and Methods

Table 2-1 Antibody concentrations used for immunoblotting.

Catalogue Working Probing Antibody Supplier Diluent number dilution condition 3% skim milk Anti-ERG1/2/3 Santa Cruz sc-354x 1/2500 4°C, overnight /TBS-T 3% skim milk Anti-β-actin-HRP Santa Cruz sc-47778 1/5000 4°C, 3 hrs /TBS-T Anti-pS283-ERG ProMab N/A 1/3000 1% BSA/TBS-T 4°C, overnight Anti-pERK1/2 Cell Signaling 9101 1/1000 5% BSA/TBS-T 4°C, overnight 3% skim milk Anti-Rabbit-HRP Dako P0448 1/2500 4°C, 3 hrs /TBS-T Anti-Mouse-HRP Dako P0260 1/3000 1% BSA/TBS-T 4°C, 3 hrs For immunoblotting used in this project, antibody name, supplier, catalogue number, working dilution, diluents and probing conditions are listed.

Huang: Chapter 2. Materials and Methods

2.2.7. Immunodetection

Visualisation was performed by enhanced chemiluminescence with ECL reagents (Santa Cruz, sc2048). Images were captured using an ImageQuant LAS 4000 imager (version 1.2, Build 1.2.1.119) using standard or high sensitivity. Images were contrast adjusted using linear graduation and relative protein amount quantified by densitometry using the ImageQuant TL software (version 7.0).

2.3. Phosphoproteomic analysis

2.3.1. Cell lysis and immunoprecipitation

Whole-cell extracts from >3×107 MOLT-4 cells were prepared using lysis buffer with the following ingredients: 20 mM HEPES-NaOH (pH 7.8), 300 mM NaCl, 1 mM

EDTA, 20% glycerol, 0.5% NP-40, protease inhibitor, 10 mM NaF, 1 mM Na3VO4. In specific, 1 ml lysis buffer was used per 1×107 cells. The lysate was cleared for debris by centrifuging at 4°C, 10000 g for 10 min, followed by overnight incubation with the polyclonal rabbit anti-ERG1/2/3 antibody (2 μg / 1×107 cells) at 4°C. On the next day, protein G Dynabeads (Life technologies, 10003D) were washed once with Ab binding buffer (supplied), and antibody-bound ERG was adsorbed for 3 hr at 4°C (20 μl

Dynabead suspension per 1×107 cells). The beads were then washed 3× by brief vortexing with low detergent lysis buffer [20 mM HEPES-NaOH (pH 7.8), 300 mM

NaCl, 1 mM EDTA, 20% glycerol, 0.1% NP-40]. The ERG-bound beads were subjected to SDS-PAGE (section 2.2.4) under non-reducing conditions (without DTT or

Huang: Chapter 2. Materials and Methods

β-mercaptoethanol) in the sample buffer to avoid dissociation of the light and heavy chains of the antibody4 or in-solution digestion (section 2.3.2.3).

2.3.2. Enzymatic digestion

2.3.2.1. Trypsin/chymotrypsin reconstitution and storage

Lyophilised trypsin (Trypsin Gold, Mass Spectrometry Grade, Promega, V5280) was reconstituted in 50 mM acetic acid (Sigma, A6283) at 1 µg/µl and stored in 5 µl aliquots at -80°C. Chymotrypsin (Roche, 1141846700125) was reconstituted in 1 mM

HCl at 0.1 µg/µl and stored in 5 µl aliquots at -80°C.

For digestion, trypsin was diluted in milli-Q water from 1 µg/µl stock.

Chymotrypsin was diluted in 1 mM HCl from 0.1 µg/µl stock.

2.3.2.2. In-gel enzymatic digestion

The SDS-PAGE gel was stained with Coomassie Blue stain (NuSep, SG-021) overnight at room temperature in 5% acetic acid, and the band containing ERG

(approximately 54 kDa) was excised and diced into 1 mm3 cubes with a clean blade. Gel pieces were destained using freshly made 60% (v/v) acetonitrile (Sigma, 34967) in 25 mM NH4HCO3 solution and dried in a SpeedVac centrifugal evaporator (Thermo

Scientific). The vacuumed gel can be kept at -20°C for long-term storage, or reduced

4 The heavy chain of immunoglobulin has a similar molecular weight to ERG. A dissociated heavy chain will therefore runs at a similar rate as ERG on a SDS-PAGE gel. Digestion of the excised band will in turn have a strong IgG signal on the mass spectrometry, masking the ERG signal. 66

Huang: Chapter 2. Materials and Methods and alkylated by DTT and iodoacetamide (Sigma, I1149), respectively, followed by in- gel digestion with trypsin or chymotrypsin.

Specifically, 10 mM DTT and 55 mM iodoacetamide were freshly prepared using 25 mM NH4HCO3 and kept on ice. Iodoacetamide solution was kept in dark. The gel pieces were rehydrated with sufficient DTT and incubated at 56°C for 30 min. The

DTT supernatant was carefully removed with a fine pipette tip, followed by iodoacetamide treatment in dark at room temperature for 15 min. Upon careful removal of iodoacetamide supernatant, the gel was washed 3 × 10 min, each round with 100 µl

60% (v/v) acetonitrile in 25 mM NH4HCO3. The gel was dried again in a centrifugal evaporator, rehydrated on ice with 25 mM NH4HCO3 containing trypsin (12 ng/µl) or chymotrypsin (12.5 ng/µl) and incubated overnight at 37°C. On the next day, the supernatant was collected with a fine pipette tip (this contains the peptides) and was dried in a centrifugal evaporator. The dried peptides can be stored at -20°C and reconstituted later for mass spectrometry analysis.

2.3.2.3. In-solution enzymatic digestion

For in-solution digestion, ERG-bound beads were resuspended in 20 µl 25 mM

NH4HCO3. The protein was reduced and alkylated by DTT and iodoacetamide, respectively, followed by in-solution digestion with trypsin or chymotrypsin. In specific, 100 mM DTT and 100 mM iodoacetamide were freshly prepared using 25 mM

NH4HCO3 and kept on ice. Iodoacetamide solution was kept in dark. Resuspended beads were treated with DTT (final concentration 5 mM) at 56°C for 40 min, followed by 5 mM iodoacetamide treatment in dark at room temperature for 30 min. 0.1 µg/µl

Huang: Chapter 2. Materials and Methods trypsin/chymotrypsin were added at 1:20-1:50 (w/w) (estimated 2 µg immunoprecipitated ERG from 3×107 MOLT-4 cells) to protein for overnight digestion at 30°C with gentle agitation. On the next day, the digest was collected off the beads using a magnetic rack (Life technologies, 12321D), and spun at 10000 g for 10 min to remove debris/precipitation [undissolved precipitation may clog the TiO2 column during phosphopeptide enrichment (section 2.3.3)].

2.3.3. Phosphopeptide enrichment

The in-solution digest was enriched for phosphopeptides using Titansphere®

Phos-TiO2 kit (GL Sciences Inc., 5010-21309) according to manufacturer’s instructions.

Briefly, buffers were prepared freshly on the day of experiment. Buffer A (column equilibration buffer) contains 1 volume of 2% trifluoroacetic acid (TFA, Sigma,

302031) and 4 volumes of acetonitrile. Buffer B (binding buffer) contains 3 volumes of buffer A and 1 volume of solution B (supplied, 90% lactic acid) and is protected from light. Elution buffer contains 5% NH4OH (diluted with milli-Q water from 30%

NH4OH, Sigma, 221228) and is protected from light.

The column was equilibrated with 20 µl buffer A by centrifuging at 3000 g for 2 min at room temperature, followed by 20 µl equilibration with buffer B (3000 g, 2 min, room temperature). The digest was then mixed with buffer B at 3:10 (v/v) ratio and loaded onto the column. Phosphopeptides were bound by centrifuging at 1000 g for 10 min at room temperature. The flow-through was re-applied to the column and the centrifugation was repeated. The column was then washed once with 20 µl buffer B

(3000 g, 2 min, room temperature) and three times with 20 µl buffer A (3000 g, 2 min,

Huang: Chapter 2. Materials and Methods room temperature). The phosphopeptides were eluted into clean recovery tube with

2×50 µl 5% NH4OH (1000 g, 5 min, room temperature).

2.3.4. Desalting of protein digest

The eluted phosphopeptides were desalted using C18 ziptip columns (Millipore,

Z720070-96EA) following manufacturer’s instructions before mass spectrometry analysis. In brief, buffers were prepared freshly on the day of experiment. Equilibration buffer contains 0.1% formic acid (98% formic acid for mass spectrometry, Sigma,

94318-50ML-F, diluted with milli-Q water). Elution buffer contains 1% formic acid in

50% (v/v) acetonitrile. Before desalting, the enriched phosphopeptide eluate was acidified to pH ≤ 3 with 20% (v/v) TFA (approximately 70 µl TFA per 100 µl eluate).

Upon application onto a p10 pipette with the volume set on 10 μl, the ziptip was first equilibrated twice with 100% acetonitrile and twice with equilibration buffer. To bind the phosphopeptides, the sample was gently pipetted up and down for 10-20 times. The peptides were eluted with 10 μl elution buffer and vacuum dried in a centrifugal evaporator. The dried peptides were kept at -20°C until reconstitution for mass spectrometry analysis.

2.3.5. Mass spectrometry

2.3.5.1. Liquid chromatography (LC)

Liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) was conducted at the Bioanalytical Mass Spectrometry Facility (BMSF), UNSW

Australia. LC was performed using an Ultimate 3000 HPLC and autosampler system

Huang: Chapter 2. Materials and Methods

(Dionex, Amsterdam, Netherlands). Samples were injected into a fritless nanoLC column (75µm x ~10cm) containing C18 media (3µm, 200 Å Magic, Michrom) manufactured according to Gatlin (Gatlin et al., 1998). Peptides were eluted using a linear gradient according to the conditions on the table below, over 50 min, at a flow rate of 0.200 µl/min. Mobile phase A consisted of 0.1% Formic Acid in H2O, while mobile phase B consisted of acetonitrile:H2O (8:2) with 0.1% Formic Acid.

Time (min) %B

0.0 2.0

4.0 10

40.0 45.0

41.0 85.0

41.5 85.0

42.0 2.0

50.0 2.0

2.3.5.2. Tandem mass spectrometry (MS/MS)

High voltage (1800 V) was applied to a low volume tee (Upchurch Scientific) and the column tip positioned ~ 0.5 cm from the heated capillary (T=250°C) of a LTQ

FT Ultra (Thermo Electron, Bremen, Germany) mass spectrometer. Positive ions were generated by electrospray and the LTQ FT Ultra operated in data dependent acquisition mode (DDA). A survey scan m/z 350-1750 was acquired in the FT ICR cell

(Resolution = 100,000 at m/z 400, with an accumulation target value of 1,000,000 ions). Up to the six most abundant ions (>3000 counts) with charge states > +2 were sequentially isolated and fragmented within the linear ion trap using collisionally

Huang: Chapter 2. Materials and Methods induced dissociation with an activation q = 0.25 and activation time of 30 msec at a target value of 30000 ions. M/z ratios selected for MS/MS were dynamically excluded for 30 sec.

2.3.6. Mass spectrometry data analysis

Mascot software (version 2.3.2; Matrix Science) with the UniProtKB/Swissprot database (released 2013) search algorithm was used for protein identification. The analysis of protein identification and quantification was carried out as described by the software user guide. Search parameters included i) variable modifications: oxidation of methionine (M), phosphorylation of serine, threonine and tyrosine (STY); ii) Fixed modification: carbamidomethylation of cysteins; iii) for SILAC experiments only:

13 13 Arginine (R) Label: C6, Lysine (K) label: C6; iv) enzyme specified was trypsin/chymotrypsin and allowing maximum three missed cleavages. All peptides with high-quality tandem mass spectra were manually annotated and confirmed using the

Xcalibur software (version 2.2, Thermo Scientific). The sequences and phosphorylation sites of all identified phosphopeptides were carefully assigned accordingly.

2.3.7. Nuclear/cytoplasmic phosphopeptide normalisation

MOLT-4 cells were fractionated (section 2.2.2) and ERG immunoprecipitation and MS analysis performed separately for each fraction. Phosphopeptide signals were quantified from in-solution digested and phosphoenriched samples, while the total ERG signal for all identified peptides was quantified using the in-gel sample result. The ratio of total nuclear ERG to total cytoplasmic ERG was calculated, which was then averaged and used for the normalisation of the phosphopeptide signals. 71

Huang: Chapter 2. Materials and Methods

푁푢푐푙푒푎푟 푁푢푐푙푒푎푟 𝑖푛푡푒푛푠𝑖푡푦 표푓 푝푒푝푡𝑖푑푒 퐴 푅푎푡𝑖표 퐴 ( ) = 퐶푦푡표푝푙푎푠푚 퐶푦푡표푝푙푎푠푚𝑖푐 𝑖푛푡푒푛푠𝑖푡푦 표푓 푝푒푝푡𝑖푑푒 퐴

푁푢푐푙푒푎푟 퐴푣푒푟푎푔푒 푟푎푡𝑖표 ( ) = (푅푎푡𝑖표 퐴 + 푅푎푡𝑖표 퐵 + ⋯ + 푅푎푡𝑖표 푁)/푁 퐶푦푡표푝푙푎푠푚

푆𝑖푔푛푎푙 𝑖푛푡푒푛푠𝑖푡푦 표푓 푝ℎ표푠푝ℎ표푝푒푝푡𝑖푑푒 푁표푟푚푎푙𝑖푠푒푑 푝ℎ표푠푝ℎ표푝푒푝푡𝑖푑푒 푠𝑖푔푛푎푙 = 퐴푣푒푟푎푔푒 푟푎푡𝑖표

2.4. Plasmid preparation

2.4.1. Plasmid construction

2.4.1.1. Polymerase chain reaction (PCR)

PCR reaction contains 1 U high fidelity (HF) Platinum Taq polymerase (Life technologies, 11304-011), 1× Platinum Taq HF buffer (supplied), 2 mM MgSO4

(supplied), 0.2 mM deoxynucleoside triphosphate (dNTP, Promega, U1330), 0.4 µM forward primer (Life technologies, customised DNA oligos), 0.4 µM reverse primer, 5 ng template DNA, and x µl nuclease free water (NFW) to make the reaction volume to

50 µl.

The PCR was performed on a DNA Engine Multi-Bay Thermal Cycler (Biorad) with the following cycling condition:

1. 94°C 2 min

2. 94°C 20 sec

3. 65°C 30 sec, reduce 1°C/cycle

4. 68°C 90 sec 72

Huang: Chapter 2. Materials and Methods

5. Go to step 2, repeat 9×

6. 94°C 20 sec

7. 55°C 30 sec

8. 68°C 90 sec + 5 sec/cycle

9. Go to step 6, repeat 19×

10. 4°C forever

Parental DNA was digested with 10 U DpnI [New England Biolab (Wagner and

Nebreda)] by incubating at 37°C for 60 min. The samples can be stored at -20°C until use.

Samples were cleaned using the QIAquick PCR purification kit (QIAGEN,

28104) as per manufacturer’s instructions. The concentration of eluted DNA was determined using a Nanodrop spectrophotometer (Thermo Scientific) prior to restriction enzyme digestion.

2.4.1.2. Subcloning

The insert and backbone (5 µg each) were digested with restriction enzymes5

(Wagner and Nebreda) to create compatible sticky ends. The digested backbone was treated with Antarctic phosphatase (NEB, M0289) to prevent recircularisation of the empty vector. The digested DNA was cleaned using the QIAquick PCR purification kit, followed by the insert ligation into the backbone using T4 DNA ligase (Promega,

M1801). The entire length of the insert in the final vector was confirmed by sequencing

(section 2.4.4).

5 Specific enzymes used are listed in the subsections of each plasmid in section 2.4.1. 73

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2.4.1.3. pMIG+ ERG construction

Full length human ERG3 cDNA (NM_182918.3, corresponding to Homo sapiens v-ets avian erythroblastosis virus E26 oncogene homolog, transcript variant 1, mRNA) was PCR amplified (section 2.4.1.1) with customised primers 6 to add restriction digest sites preceding the start codon (MfeI: 5’-

ATATAcaattgATGGCCAGCACTATTAAGGA-3’) and after the stop codon (NotI: 5’-

ATAAGAATgcggccgcTTAGTAGTAAGTGCCCAGA-3’) to facilitate in-frame ligation into an murine stem cell virus (MSCV) - internal ribosomal entry site (IRES) - green fluorescence protein (GFP) (pMIG+) backbone (Figure 2-1). The replication defective retroviral vector pMIG+ [a variant of pMIG (Cheng et al., 1996) with an extended multiple cloning sequence] encodes for the expression of GFP downstream of an IRES. The multiple cloning site of pMIG+ was digested with EcoRI and NotI.

6 The restriction sites are in lower case. The start and stop codons are underlined. 74

Huang: Chapter 2. Materials and Methods

Figure 2-1 Schematic of the retroviral construct containing ERG cDNA.

A murine stem cell virus (MSCV)-based retrovirus carrying the cDNA encoding human

ERG downstream of a long terminal repeat promoter was used (Hahn et al.). An internal ribosome entry site (IRES) sequence allows the green fluorescent protein (GFP) reporter gene to be transcribed from the same promoter as ERG but translated separately.

Huang: Chapter 2. Materials and Methods

To generate the HA-ERG insert, the forward primer MfelI: 5’-

ATATAcaattgGCCACCATGTACCCATACGACGTCCCAGACTACGCTGCCAGCA

CTATTAAGGA-3’ and reverse primer NotI: 5’-

ATAAGAATgcggccgcTTAGTAGTAAGTGCCCAGA-3’ were used for PCR.

2.4.1.4. GST-ERG expression vector construction

For generation of the glutathione S-transferase (GST) fusion ERG expression vector, full-length and deletion mutant cDNAs encoding human ERG3 were amplified by PCR (section 2.4.1.1) with customised primers to add restriction digest sites prior to the start of ERG sequence 7 (BglII: 5’-

ATATAagatctGGTGGTGCCAGCACTATTAAGGA-3’) and after the stop codon

(XhoI: 5’-ATATActcgagTTAGTAGTAAGTGCCCAGA-3’) to facilitate in-frame ligation into the pGEX-4T-1 bacterial expression vector (a kind gift from Merlin

Crossley’s lab, UNSW Australia) with the isopropyl-1-thio-β-galactopyranoside

(IPTG)-inducible lac promoter. The multiple cloning sequence of pGEX-4T-1 was digested with BamHI and XhoI.

2.4.2. Bacterial Transformation with Plasmid DNA

Ligation samples were transformed into JM109 bacteria according to manufacturer’s instructions. Briefly, JM109 cells (Promega, P9751) were thawed on ice, and 20l of cells were combined with 2 l of ligation product. The cell/DNA mixture was incubated for 20 min on ice, followed by 45 sec heat shock in a 42C water bath,

7 The absence of a start codon between the GST tag and ERG avoids transcription of untagged ERG. 76

Huang: Chapter 2. Materials and Methods

and a further 2 min on ice. Luria-Bertani (LB) broth (300 l) was added, followed by a

60 min replication phase in a 37C shaker. The whole volume was plated onto LB agar plates containing 100 g/ml ampicillin (Sigma, A9518), air dried and incubated overnight in a 37C bacterial oven.

2.4.3. Mini-preparation

DNA extraction from colonies was performed using the miniprep boiling method. Single colonies were inoculated into 2 ml LB broth containing 100 g/ml ampicillin and shaken for 14 hr in aerated flasks at 37C. 1.5 ml cells were centrifuged for 5 min at 10000 g, then thoroughly lysed in 300 µl lysis buffer [80 g/L sucrose, 5%

TritonX100, 50 mM Tris (pH 8.0), 50 mM EDTA] containing 100 µg/ml lysozyme

(Sigma, L6876). The remaining 0.5 ml was kept at 4°C for the expansion of correct candidates. Lysate was boiled for 1 min followed by centrifugation at 10000 g for 15 min at room temperature. The fluffy pellet (contains cellular protein) was carefully removed with sterilised toothpick. DNA was precipitated with 270 µl isopropanol and centrifuged at 10000 g for 10 min. Upon careful removal of the supernatant, the DNA pellet (this may not be visible) was reconstituted in 50 µl Tris-EDTA (TE) buffer (pH

7.8) with freshly added RNaseA (10 µg/ml, Life technologies, EN0531). The resultant

DNA was subjected to diagnostic digest to confirm candidate constructs.

Huang: Chapter 2. Materials and Methods

2.4.4. Confirmation of plasmid DNA

2.4.4.1. Diagnostic digest

5 µl miniprep DNA was digested with restriction enzymes to check for banding pattern and identify candidate vectors. The digest product were loaded into 1% agarose gel (AppliChem, A2114 0500) with DNA stain SYBR safe (Life technologies, S33102), electrophoresed at 80 V for 60 min, and visualised on Universal Hood II (Biorad) using

Quantity One software (version 4.6.7).

For pMIG+ ERG construction, candidate vectors were identified by diagnostic digest with restriction enzyme NdeI. Empty vectors were visualised as a single 6.6 kbp band, and the presence of a correctly oriented ERG insert identified by the presence of

4.7, 2.7 and 6.6 kbp bands. For pGEX-4T-1 ERG (GST-ERG expression vector) construction, candidate vectors were identified by diagnostic digest with restriction enzyme BamHI and XhoI. Empty vectors were visualised as a single 4.9 kbp band, and the presence of a correctly oriented ERG insert identified by the presence of 1.5 and 4.9 kbp bands.

2.4.4.2. DNA Sequencing and clean-up

Miniprep candidate vectors were cleaned up with the PCR clean-up kit, concentration measured using the Nanodrop spectrophotometer and sequenced to confirm correct DNA sequence. 20 µl sequencing reaction was set up using 400 ng

DNA template, 1 µl BigDye Terminator V3.1, 3.5 µl 5× sequence buffer (supplied),

0.32 µl sequencing primer (10 µM stock) and nuclease free water (NFW) (QIAGEN,

129114) using the following thermol cycling program: 78

Huang: Chapter 2. Materials and Methods

96°C 10 sec

50°C 5 sec

60°C 4 min

Repeat for a further 25 cycles

Hold at 4°C until ready to purify

The sequencing primers of ERG used in this study included forward primers 5’-

ATGGCCAGCACTATTAAG-3’, 5’-CTACGCAAAGAATTACAAC-3’, 5’-

CGCTACGCCTACAAGTTC-3’ and reverse primers 5’-GCTCATCTTGGAAGTCTG-

3’, 5’- AAGGCGGCTACTTGTTGGTC-3’.

The final product was cleaned up using the ethanol/EDTA precipitation method.

For a 20 µl reaction, 5 µl EDTA (125 mM) and 60 µl 100% ethanol were added and mixed well. Following 15 min precipitation at room temperature, the sample was centrifuged at 14000 g for 20 min at room temperature. Upon careful removal of the supernatant, 160 µl freshly made 70% ethanol (w/v) was added to wash the DNA pellet8. The centrifugation step was repeated, supernatant removed and pellet was dried on a 95°C heat block for 1 min and sequenced on an AB 3730 Capillary Sequencer at the Ramaciotti Centre for Genomics, UNSW Australia. The sequence of miniprep product was aligned to human ERG3 cDNA using Geneious (version 5.3.6) to confirm correct sequence.

8 DNA pellet may not be visible. Ethanol should be carefully added carefully on the opposite side of the tube hinge to avoid disrupting the pellet. 79

Huang: Chapter 2. Materials and Methods

2.4.5. Maxi-preparation of plasmid DNA

Maxi-preparations of confirmed colonies were performed using the

NucleoBond® Xtra Midi kit (Macherey-Nagel, 740410) as per manufacturer’s recommendations. Transformed JM109 cells were grown overnight in a 37 °C shaker in

100-500 ml LB broth containing 100 g/ml ampicillin. Cells were collected by centrifugation at 5000 g for 15 min at 4C, then resuspended in 8 ml RES buffer

(supplied, kept at 4°C) containing RNaseA (supplied). Cells were lysed in equal volume of LYS buffer (supplied) with a 5 min incubation, which was then halted by adding

NEU buffer (supplied). The sample was mixed thoroughly before loaded onto the pre- equilibrated gravity-flow columns which were used to capture and wash DNA. DNA was eluted with 5 ml of ELU buffer (supplied) and precipitated with 3.5 ml 100% isopropanol, followed by centrifugation at 4°C, 5000 g for 60 min. DNA pellet was washed with 2 ml of 70% (w/v) ethanol, and centrifuged at 5000 g for 15 min. After the supernatant was removed, the pellet was air-dried for 10 min before reconstituted in 100

l TE buffer (pH 7.8). The DNA yield and quality/purity were determined using

Nanodrop spectrophotometer.

2.4.6. Glycerol Stocks

Glycerol stocks of confirmed vectors were produced from fresh culture of transformed JM109 grown in LB broth containing 100 g/ml ampicillin. A 7:3 ratio of bacterial culture and glycerol (Sigma, G5516) were mixed and immediately stored in cryovials at -80C. Glycerol stock was thawed and inoculated into fresh LB broth with ampicillin for the expansion of plasmid DNA.

Huang: Chapter 2. Materials and Methods

2.5. ERG mutagenesis

2.5.1. Point mutation - Site-directed mutagenesis

Various pMIG+ ERG constructs with point mutations were generated using the

QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies, 210518) according to the manufacturer’s instructions. Briefly, the pMIG+ ERG plasmid was used as a backbone vector to generate the mutant ERG constructs with alanine or aspartate mutations at S283. 50 µl mutagenesis reaction was set up using 5µl reaction buffer

(10×, supplied), 1 µl dNTP mix (supplied), 1.5 µl QuikSolution reagent (supplied), 1 µl

QuikChange Lightning polymerase (supplied), 1.25 µl forward primer (10 µM stock, ), 1.25 µl reverse primer (10 µM stock), 50 ng DNA template (5 µl of 10 ng/µl), 34 µl NFW. The cycling parameters were:

1. 95°C 2 min

2. 95°C 20 sec

3. 60°C 10 sec

4. 68°C 4.5 min (30 sec/kbp of plasmid length, pMIG+ ERG=8.1kbp)

5. Go to step 2, repeat 17×

6. 68°C 5 min

7. 4°C forever

The mutagenesis primer sets were listed in Table 2.2. The resultant product was transformed into JM109 cells and sequence confirmed as per section 2.4.4. The mutation was also subcloned into pMIG+ HA-ERG for tagged constructs.

Huang: Chapter 2. Materials and Methods

Table 2-2 Primer sequences for site-directed mutagenesis.

Primer name Primer sequence

ERG3 S283A sense 5’-GAAAGCTGCTCAACCAGCTCCTTCCACAGTGCC-3’

ERG3 S283A antisense 5’-GGCACTGTGGAAGGAGCTGGTTGAGCAGCTTTC-3’

ERG3 S283D sense 5’-CCCAGTCGAAAGCTGCTCAACCAGATCCTTCCACAGT-3’

ERG3 S283D antisense 5’-ACTGTGGAAGGATCTGGTTGAGCAGCTTTCGACTGGG-3’

Mutated codons are in bold and underlined.

Huang: Chapter 2. Materials and Methods

2.5.2. Deletion mutation

To avoid the introduction of additional non-coding nucleotides for restriction enzyme cutting within the gene, site-directed, ligase-independent mutagenesis (SLIM)

(Chiu et al., 2008) was performed instead of the aforementioned approach. Four primers were specifically designed per deletion mutation, as listed in Table 2-3.

Detailed protocol and the PCR conditions can be found in Chiu et al. Briefly, 25

µl PCR reaction was set up containing 0.5 U Phusion Hot start HF DNA polymerase

(Thermo Scientific, F-540), 1× Phusion HF buffer (supplied), 200 µM dNTP, 2.5 mM

MgSO4, 10 pmol each primer and 5 ng DNA template (Chiu et al., 2008). The PCR program used was:

1. 98°C 30 sec

2. 98°C 15 sec

3. 55°C 20 sec

4. 72°C 30 sec/kb, 4 min for 8 kb plasmid

5. Go to step 2, repeat 24×

6. 72°C 10 min

Huang: Chapter 2. Materials and Methods

Table 2-3 Primer sequences for ERG deletion using site-directed, ligase- independent mutagenesis (SLIM).

Primer Name Primer Sequence

ERG exon12 deletion Forward 1 5’-CATGCTAGAAACACAGGGGATTTACCATATGAGCCCCCC-3’

ERG exon12 deletion Reverse 1 5’-CATTAACCGTGGAGAGTTTTGTA-3’

ERG exon12 deletion Forward 2 5’-GATTTACCATATGAGCCCCCC-3’

ERG exon12 deletion Reverse 2 5’-CCCTGTGTTTCTAGCATGCATTAACCGTGGAGAGTTTTGTA-3’

ERG ETS deletion Forward 1 5’-AATCCAGGCAGTGGCCAGTTCCACGGGATCGCCCAGG-3’

ERG ETS deletion Reverse 1 5’-TGCAAGGCGGCTACTTGTTG-3’

ERG ETS deletion Forward 2 5’-TTCCACGGGATCGCCCAGG-3’

ERG ETS deletion Reverse 2 5’-CTGGCCACTGCCTGGATTTGCAAGGCGGCTACTTGTTG-3’

The principals of primer design are explained in Chiu et al. (2008). The tail sequences are underlined.

Huang: Chapter 2. Materials and Methods

The PCR products were hybridised with 10 µl each product in hybridisation buffer [150 mM NaCl, 25 mM Tris (pH 9.0), 20 mM EDTA] using the following thermal cycles:

1. 99°C 3 min

2. 65°C 5 min

3. 30°C 40 min

4. Go to step 2, repeat 2×

The hybridised product can then be transformed into JM109 cells for candidate screening.

2.6. Expression and purification of GST-ERG protein

The pGEX-4T-1 ERG plasmid was constructed as per section 2.4.1.4. The recombinant plasmid was transformed into competent E.coli strain BL21(DE3) cells

(NEB, C2527I) (section 2.4.2) and single transformants expanded in LB broth containing ampicillin (100 µg/mL) at 37°C. When the culture reached an optical density of 0.6 at 600 nm reading, expression of the GST-tagged ERG was induced with 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG, Sigma, I6758) at 37°C for 3 hr with agitation. The induction was halted by the addition of EDTA to a final concentration of

1 mM. The cells were harvested by centrifugation at 5000 g for 10 min at 4°C, lysed in lysis buffer (50 mM Tris pH 7.5, 150 mM NaCl, 50 mM EDTA, 0.5% NP-40, 1%

Triton X-100) with freshly added protease inhibitor cocktail, 10 mM DTT and 2 mM phenylmethylsulfonyl fluoride (PMSF, Sigma, P7626), and further disrupted by 5min sonication using a probe sonicator. After removing the cell debris by centrifugation at

5000 g for 30 min at 4°C, GST-tagged ERG protein was purified from the respective

Huang: Chapter 2. Materials and Methods culture supernatant on glutathione agarose beads (Sigma, G4510) in accordance with the manufacturer’s instructions. The ERG-bound beads were washed three times with 1%

Triton in PBS, and GST-ERG eluted with 10 mM reduced L-Glutathione (Sigma,

G4251) in 100 mM Tris (pH 7.5), 120 mM NaCl. The eluate was concentrated using a protein concentrator tube with 30 kDa cut-off (VWR, 28-9323-61). The concentration of the GST-ERG fusion protein was measured using Nanodrop spectrophotometer and purity assessed by SDS-PAGE, followed by coomassie staining.

2.7. Generation of ERG pS283-specific antiserum

2.7.1. Antigen synthesis and antibody generation

Mouse monoclonal phospho-specific antibody for ERG pS283 was produced by

ProMab Biotechnologies, Inc. (U.S.A.) using the artificially synthesised phosphopeptide

PTPQSKAAQP(p)*S*PSTVPKTEDQ, S283 highlighted by asterisk.

In phase I of monoclonal antibody production, five Balb/c mice were immunised and boosted with the standard immunisation protocol. In phase II production, upon obtaining an acceptable titre of the immunogen (3 mg) by the enzyme-linked immunosorbent assay (ELISA) evaluation, hybridoma fusion was performed using mouse splenocytes with the highest titre and myeloma cells. Supernatant from the growing hybridoma wells were screened by ELISA, and 10 positive supernatant clones of each antigen were shipped from ProMab Biotechnologies, Inc. (U.S.A.) to our lab for sensitivity/specificity evaluation using purified phosphorylated/non-phosphorylated recombinant GST-ERG. Clone supernatant was probed in neat condition to test blots at

4°C overnight with prior blocking in 1% BSA/TBS-T. In phase III production when 86

Huang: Chapter 2. Materials and Methods candidate clones were picked, the clones were subcloned by limiting dilution and isotyped. Ascites production from >10 Balb/c mice and antibody purification were performed using the final selection of one candidate clone.

2.7.2. Optimisation of probing condition

The antibody was supplied in PBS and was stored at -20°C in 50 µl aliquots to avoid freeze-thaw cycles. The optimal probing condition was determined using Table 2-

4 with MOLT-4 whole cell lysate.

Huang: Chapter 2. Materials and Methods

Table 2-4 Summary of probing conditions for anti-ERG pS283 antibody.

Diluent Dilution Factor 1/3000 1/10000 1/15000 1/20000 4°C 5% skim milk/TBS-T √ √ √ √ overnight 1% BSA/TBS-T √ √ √ √ Room temp 5% skim milk/TBS-T √ √ √ √ 3 hr 1% BSA/TBS-T √ √ √ √ 37°C 5% skim milk/TBS-T √ √ √ √ 1 hr 1% BSA/TBS-T √ √ √ √

A range of condition combinations was tested for the optimisation of probing conditions of the customised ERG pS283 antibody.

Huang: Chapter 2. Materials and Methods

2.8. Cord blood CD34+ hHSC transduction and assays

2.8.1. Stock of cord blood CD34+ Cells

2.8.1.1. Cord blood ethics approval

Human cord blood was collected with informed consent by the Sydney Cord

Blood Bank under approval from the South Eastern Area Health Service Northern

Network, which was ratified by the UNSW Human Research Ethics Committee (HREC

SESIAHS 08/190).

2.8.1.2. Cord blood CD34+ cell enrichment

Blood from cord blood collection bags containing citrate phosphate dextrose anticoagulant solution was diluted 1:1 with PBS. Diluted blood was aliquoted at 35 ml per 50 ml tube, underlaid with 15 ml Lymphoprep (Vital Diagnostics, 1114547), then density gradient centrifuged (800 g, 30 min, room temperature) with zero deceleration.

Mononuclear cells were collected from the buffy layer and washed twice with PBS, and centrifuged at 490 g for 7 min at room temperature. An aliquot of cells were counted with trypan blue.

CD34+ cells were enriched using CD34+ direct antibody-labelled magnetic beads (Miltenyi Biotec, 130-046-703) as per manufacturer’s instructions on an

AutoMACS machine (Miltenyi Biotec). Briefly, mononuclear cells were resuspended at

3×108 cells/ml of cold running buffer (Miltenyi Biotec, 130-091-221), and combined with 1 l FcR blocking reagent (supplied) and 1 l CD34 microbeads per 1×106 mononuclear cells. Cells were incubated for 30 min at 4C and then washed with 20 ml

Huang: Chapter 2. Materials and Methods cold running buffer. Following centrifugation at 490 g for 10 min, cells were resuspended to 2×108 cells/ml in cold running buffer and passed through a pre- separation filter (30 µm, Miltenyi Biotec, 130-041-407) to produce a single cell suspension. CD34+ cells were enriched with double column selection of positive cells

(PosselD2 setting) and cell numbers and viability determined by manual count with trypan blue. Aliquots of 1×104 cell were stained with CD45-FITC (BD Biosciences,

555482) and CD34-phycoerythrin (PE) (BD Biosciences, 348057) antibodies for flow cytometry analysis of CD45+ CD34+ population purity. Following a wash in running buffer, cells were centrifuged (800 g, 10 min, room temperature) and cryopreserved in

FBS2 (Life technologies, 10099-141, Lot 7212348Y; 16000-044, Lot 1085998)9 with

10% DMSO.

2.8.2. Virus production

2.8.2.1. Thawing and preparation of Phoenix cells

Phoenix cells were maintained at low passage numbers (< passage 10) and never let to reach confluency to ensure high virus-producing capacity. On day 1, cryopreserved Phoenix cells were thawed in a 37C water bath until a small core of frozen media remained before added drop-wise to pre-warmed α-MEM containing 10%

FBS. Cells were centrifuged at 800 g for 7 min at room temperature and resuspended in fresh α-MEM with 10% FBS. Following the determination of viability and cell concentration, cells were seeded at 1.3 × 106 cells / T25 flask in α-MEM supplemented

9 In this study, where FBS was needed for human cord blood cells, only low endotoxin FBS that has been found to optimise haematopoietic culture was used (refered to as FBS2 in text). If switching to a different lot number, preliminary tests on cord blood must be performed in advance. 90

Huang: Chapter 2. Materials and Methods with 10% FBS – this seeding density will give 70% confluency on the next day for transfection. The seeding density can be scaled up 3 fold for T75 flasks.

2.8.2.2. Transfection of Phoenix cells

Maxiprep pMIG+ (HA-)ERG viral vector DNA was prepared under sterile conditions in a biohazard hood. DNA was precipitated at 12 µg / T25 flask with 1/10 volume of 3M sodium acetate (pH 5.8) and 2 volume of 100% ethanol overnight at -

20°C. Precipitated DNA was collected at 14000 g at 4°C for 30 min. Upon careful removal of the supernatant, the pellet was washed once with 500 µl cold (-20°C) 70%

(w/v) ethanol followed by centrifugation at 14000 g, 4°C, 6 min. The pellet was air- dried in a sterile hood and dissolved in 500µl / 12 µg Opti-MEM (serum and antibiotics free, Life technologies, 31985-070). Meanwhile, Lipofectamine 2000 reagent (Life technologies, 11668-019) was diluted with Opti-MEM (12 μl Lipofectamine 2000 / 488

µl Opti-MEM / 12 µg DNA), followed by gentle drop-wise addition of the DNA to the

Lipofectamine-Opti-MEM mix for a 20 min room temperature incubation.

Culture media were removed from pre-seeded Phoenix cells and replaced with

2ml Opti-MEM containing 10% FBS (antibiotic free). The DNA/Lipofectamine mix was added to the cells drop-wise, and the flask rocked back and forth to ensure even coverage. The cells were incubated overnight (<16 hr) in a 5% CO2 humidified tissue culture incubator. The transfection mix was replaced with fresh α-MEM with 10% FBS on the following morning to allow cells to recover, and changed in the evening to 4.5ml of the appropriate growth media for transduction of target cells on the following day.

Huang: Chapter 2. Materials and Methods

2.8.3. Retroviral transduction of cord blood cells

2.8.3.1. Thawing cord blood Cells

Cryopreserved CD34+ cord blood cells were revived by quickly thawing in a

37°C water bath until a small core of frozen medium remained. The cell suspension was then gently added drop-wise into a 10× volume of warm Iscove's Modified Dulbecco's

Medium (IMDM, Life technologies, 12440-053) supplemented with 30% FBS2, 2mM

L-glutamine and 50 g/ml gentamicin (Life technologies, 15750-060). Cells were centrifuged at 1000 g for 8 min at room temperature to remove DMSO and resuspended in media for manual count and viability determination. When required, multiple CD34+ cord blood samples were combined to provide sufficient number of cells for transduction.

2.8.3.2. Pre-stimulation and Cord Blood Cell Infection

Cord blood transduction procedure was performed in IMDM containing 20%

FBS2, 2mM L-glutamine and 50 g/ml gentamicin. Following thawing, cells were initially pre-stimulated at 2×105/ml with stem cell factor (SCF, 100 ng/ml, Amgen,

AA1580-00), thrombopoietin (TPO, 50 ng/ml, Peprotech, 30018), FMS-like tyrosine kinase 3 ligand (Flt3L, 100 ng/ml, Peprotech, 30019), and interleukin (IL)-6 10 (20 ng/ml, Novartis Pharmaceuticals) for 72 hr prior to transduction.

On the day before round 1 transduction, media on transfected Phoenix cells were changed to IMDM (4-5 ml / T25 flask) with 20% FBS2, 2mM L-glutamine, 50 g/ml

10 Discontinued product. Catalogue number not available. 92

Huang: Chapter 2. Materials and Methods

gentamicin. Non-tissue culture treated 6-well plates (Thermo, 150239) were coated with

24 μg/ml retronectin (Takara, T100B) in PBS overnight at 4°C on a levelled surface.

On the first day of transduction, the virus containing media (VCM) with fresh retroviral particles with pMIG+, pMIG+ ERG WT, pMIG+ ERG S283A, or pMIG+

ERG S283D packaged in Phoenix cells was collected, centrifuged at 1000 g for 8 min to collect any suspension cells, followed by filtration through 0.45 μm polyvinylidene fluoride (PVDF) membrane. Upon removal of retronectin, the plates were incubated with 2ml of 2% BSA in PBS for 30 min to block non-specific cell binding, followed by rinsing with 3ml of 1M HEPES in Hank’s buffered saline solution (HBSS) and then 30 min incubation with 2 ml/well fresh VCM at room temperature. Meanwhile, expanded

CD34+ cells were harvested by pipetting, centrifuged at 800 g for 7 min at room temperature, and resuspended in IMDM for cell count and viability determination. Cells were split evenly across all conditions, centrifuged, and resuspended in appropriate

VCM with the addition of SCF, TPO, Flt3L (all 100 ng/ml), IL-6 (20 ng/ml), and protamine sulphate (8 g/ml, MP Biomedicals, 219472901). Cells were then transferred to virus/retronectin-coated plates at 2 ml/well and spinoculated at 1100 rpm for 90 min at 30°C before returning to a standard tissue culture incubator for >6 hr incubation.

For subsequent rounds of transduction, 1.5 ml of transduced culture was gently harvested from each well, and centrifuged at 800 g for 7 min at room temperature.

Media were aspirated and cell pellet resuspended in fresh VCM with cytokines and protamine before returning to the original retronectin-coated wells. Media on transfected Phoenix cells were changed at the end of each day to IMDM (4-5 ml / T25

Huang: Chapter 2. Materials and Methods

flask) with 20% FBS2, 2mM L-glutamine, 50 g/ml gentamicin for transduction on the following day. A total of five rounds of transduction were performed over three days.

In the morning following the last round transduction, cells were harvested, counted and replated at 2×105 cells/ml in IMDM supplemented with 20% (vol/vol)

FBS2, SCF, TPO, Flt3L (all 100 ng/mL) and IL-6 (20 ng/mL) for an additional 3-day expansion. After expansion, cells were harvested and counted, and transduction efficiency was assessed by flow cytometry analysis (section 2.8.5) of GFP expression.

This time point was designated as week 0. Cells were then used for various assays and analyses.

2.8.4. Cell culture of cord blood cells

Transduced cord blood cells were seeded into assays at week 0 to determine their self-renewal, expansion and differentiation capabilities. On the same day of each week, the cells were harvested, counted and replated, with aliquots set aside for flow cytometry, colony-forming unit (CFU) assay and RNA extraction, until replicative exhaustion [when the weekly fold expansion of the culture was less than 1 (i.e. harvested cell number < plated cell number)]. Where cell numbers allowed, cells were also cryopreserved for future use. A summary of the media and additives for all cord blood cultures used in this study can be found in Table 2-5.

2.8.4.1. Self-renewal assay

2.8.4.1.1. Cytokine-driven culture for the expansion of progenitor cells

Huang: Chapter 2. Materials and Methods

Transduced cells were grown in liquid culture with cytokines selected for the expansion of progenitor cells. Each week, cells were harvested by pipetting, counted, replated and expanded at 4×104/ml in IMDM supplemented with 10% FBS2, 2mM L- glutamine, 50 g/ml gentamicin, 50 ng/ml SCF, 10 ng/ml TPO, 50 ng/ml Flt3L and 10 ng/ml IL-6.

2.8.4.1.2. Calculations of Expansion

The following calculations were used on a weekly basis to monitor cells during culture:

Cell viability:

(푙𝑖푣푒 푐푒푙푙푠) % (푡표푡푎푙 푐푒푙푙푠)

Expansion:

(ℎ푎푟푣푒푠푡푒푑 푐푒푙푙 푛푢푚푏푒푟)

(푐푒푙푙 푛푢푚푏푒푟 푝푙푎푡푒푑 푡ℎ푒 푝푟푒푣𝑖표푢푠 푤푒푒푘)

Cumulative expansion:

(푒푥푝푎푛푠𝑖표푛) × (푒푥푝푎푛푠𝑖표푛 표푓 푝푟푒푣𝑖표푢푠 푤푒푒푘푠)

Replicative exhaustion occurred when:

(푒푥푝푎푛푠𝑖표푛) < 1.0

2.8.4.2. CFU assay

Clonogenic progenitors were quantified in triplicate semi-solid cultures of 1% methylcellulose (Fluka BioChemika, 64630) in IMDM supplemented with 30% FBS2,

2mM L-glutamine, 50 g/ml gentamicin, 50 M -mercaptoethanol (Sigma, M3148),

Huang: Chapter 2. Materials and Methods

0.1 mM hemin (Fluka BioChemika, 51280), 20 ng/ml SCF, 20 ng/ml IL-3, 20 ng/ml IL-

6, 6 µg/ml erythropoietin (EPO, Amgen, AA5534-00) and 20 ng/ml G-CSF11 (Amgen)

(Schuller et al., 2007). Cultures were incubated at 1.1ml/35mm dish (Thermo Scientific,

171099) at 37C, 5% CO2 for 14-16 days when total and GFP+ colonies were counted.

Colony data were analysed on a weekly basis using the following calculations:

CFU frequency:

(퐶표푙표푛푦 푐표푢푛푡)

(10000 푐푒푙푙푠 푝푙푎푡푒푑)

Cumulative CFU:

(퐶퐹푈 푓푟푒푞푢푒푛푐푦) × (푐푢푚푢푙푎푡𝑖푣푒 푒푥푝푎푛푠𝑖표푛)

11 Discontinued product. Catalogue number not available. 96

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Table 2-5 Cord blood cell culture media

Culture Media Additives

Pre-stimulation IMDM SCF 100 ng/ml

20% FBS2 TPO 50 ng/ml

2 mM L-glutamine Flt3L 100 ng/ml

50 g/ml gentamicin IL-6 20 ng/ml

Transduction IMDM SCF 100 ng/ml

20% FBS2 TPO 100 ng/ml

2 mM L-glutamine Flt3L 100 ng/ml

50 g/ml gentamicin IL-6 20 ng/ml

Protamine sulphate 8 g/ml

Post-transduction expansion IMDM SCF 100 ng/ml

20% FBS2 TPO 100 ng/ml

2 mM L-glutamine Flt3L 100 ng/ml

50 g/ml gentamicin IL-6 20 ng/ml

Cytokine-driven progenitor culture IMDM SCF 50 ng/ml

10% FBS2 TPO 10 ng/ml

2 mM L-glutamine Flt3L 50 ng/ml

50 g/ml gentamicin IL-6 10 ng/ml

The media and additives for all cord blood culture used in this study.

Huang: Chapter 2. Materials and Methods

2.8.5. Flow cytometry and fluorescence-activated cell sorting (FACS)

2.8.5.1. Flow cytometry of GFP and CD34 population

Flow cytometry was used for the simultaneous multiparametric analysis of cells, including cell size and granularity, GFP expression and the expression of cell surface marker CD34 by staining with fluorophore conjugated antibodies. Cells for flow cytometry were washed once in PBS and resuspended in cold FACS buffer (2% FBS2 in PBS) for staining with CD34-PE or IgG-PE antibody (BD Biosciences, 349043).

Antibodies were added at 1/20 dilution into the cell suspension followed by 1 hr staining at 4°C. Excess antibody was washed off with the addition of >1 ml cold FACS buffer and centrifugation at 800 g for 7 min at 4°C. Cells were resuspended in a minimum of 200l cold FACS buffer and stored at 4C until acquisition. Data from cells were acquired on the FACSCalibur system (BD Biosciences) using CellQuest Pro software (BD Biosciences, version 6) for 10000 – 30000 events / sample, then analysed using Flowjo software (Tree Star Inc., version 10.0.7).

For the flow plot analysis, cells were first gated on the basis of forward scatter

(FSC, indicating cell size) and side scatter (SSC, indicating granularity) to exclude debris. Cells within this gate were then analysed for GFP expression and PE staining.

2.8.5.2. FACS

For RNA sequencing (section 2.8.8) and chromatin immunoprecipitation (ChIP) sequencing (section 2.8.9), subpopulations of cord blood cells (GFP+ CD34+ or GFP+ only) were enriched by FACS at week 0. Cells were resuspended at 3×107 cells / ml in 98

Huang: Chapter 2. Materials and Methods cold FACS buffer with 2 mM EDTA and filtered into Falcon 12 × 75 mm polystyrene test tubes (Falcon, #2235) as single cell suspension immediately prior to sorting.

Enrichment was performed using an Influx Cell Sorter (BD Biosciences) running FACS

Sortware software (BD Biosciences, version 1.0.650) in Class II Biosafety containment at UNSW Australia Biological Resources Imaging Laboratory (BRIL) flow cytometry facility. Cells were first gated by FSC versus trigger pulse width, by SSC versus SSC area, and by FSC versus SSC to exclude debris and cell aggregates. Target cells were then sorted on the basis of GFP expression (and PE staining).

2.8.6. Segmented regression analysis for cytokine-driven culture

R software (v3.0.2) was used for statistical analysis of transduced cord blood cell expansion (Expt1, 2, 3) over time using a segmented regression approach with a linear mixed model to separately estimate changes in each variable over time. A quadratic time term and a random effect for time were included when model fit was substantially improved. A p-value < 0.05 was considered statistically significant.

2.8.7. Quantitative real-time PCR (qRT-PCR)

2.8.7.1. RNA extraction

For expression analysis, mRNA was extracted using the RNeasy Mini kit

(QIAGEN, 74104) according to manufacturer’s instructions. Briefly, harvested cells were washed twice in PBS, lysed in 350 l lysis buffer (supplied) with 143 mM - mercaptoethanol and vortexed for 1 min. Lysate can be stored at -80C. For extraction, all centrifugation occurred at 10000 g at room temperature. Lysate was mixed with 350

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l 70% (w/v) ethanol and loaded onto the RNeasy spin columns with a 2 ml collection tube and centrifuged for 15 sec. Columns were washed with 350 l wash buffer

(supplied) and centrifuged for 15 sec, then incubated with 30 Kunitz units12 of DNase

(QIAGEN, 79254) for 15 min at room temperature, followed by the addition of 350 l wash buffer and 15 sec centrifugation. Columns were washed twice with 500 l ethanol buffer (supplied) with a 15 sec and a 2 min centrifugation, respectively. RNA was eluted with 30 l RNase-free water (supplied) and centrifuged for 1 min into

DNA/RNA LoBind collection tube (Eppendorf, 0030108051) and concentration measured by a Nanodrop spectrophotometer.

2.8.7.2. PCR amplification of cDNA

cDNA synthesis was performed with 500 ng RNA in 0.2 ml PCR tubes. RNA was first prepared with 1 g random primers (Promega, C119A) and incubated for 10 min at 65C. M-MLV buffer was then added containing 200 units M-MLV reverse transcriptase (Life technologies, 28025-013), 10 mM DTT (supplied), 1 mM mixed dNTP, and 20 units RNase-inhibitor (Promega, N261A) for a 20 µl reaction. Samples were incubated for 10 min at 25C, then 90 min at 37C, and 10 min at 70C in a DNA

Engine Multi-Bay Thermal Cycler.

12 One Kunitz unit is defined as the amount of DNase I that causes an increase in A260 of 0.001 per minute per milliliter at 25°C, pH 5.0, with highly polymerised DNA as the substrate Kunitz M (1950). Crystalline desoxyribonuclease; isolation and general properties; spectrophotometric method for the measurement of desoxyribonuclease activity. The Journal of general physiology 33(4): 349-362.. 100

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2.8.7.3. Quantitative PCR (qPCR)/qRT-PCR

qRT-PCR was performed in duplicate on an Mx3000P qPCR machine (Agilent

Technologies) using Express SYBR GreenER qPCR Supermix Universal (Life technologies, 11784-01K) and ROX (supplied) as reference dye. A 2-step PCR program was used with the following cycling condition:

1. 95C 2 min (initial melt step)

2. 95C 15 sec

3. 60C 60 sec

4. Go step 2, repeat 39×

The threshold cycle (Ct) values were taken when the amplification reaction for all samples was in the exponential phase. A standard curve was generated using known quantities of cDNA derived from the Meg-01 cell line (ERG expressing cell line) and used to calculate the amount of transcript in each sample, then expression of all genes was normalised to the control gene (ABL). The primer sets used for qRT-PCR were listed in Table 2-6.

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Table 2-6 Primer sequence used for qRT-PCR amplification.

Primer Name Primer sequence

ERG3 Forward 5’-GCTGCTCAACCATCTCCTTCC-3’

ERG3 Reverse 5’-AAGGCGGCTACTTGTTGGTC-3’

ABL Forward 5’-TGGAGATAACACTCTAAGCATAACTAAAGGT-3’

ABL Reverse 5’-CCATTTTTGGTTTGGGCTTCACACCATT-3’

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2.8.8. RNA sequencing

2.8.8.1. Sample preparation

Transduced cord blood cells from Expt2 and Expt3 week 0 were used for RNA sequencing. Pools of GFP+ CD34+ cells were selected by FACS (section 2.8.5) and total RNA extracted (section 2.8.7.1). Eluted RNA concentration was measured using a

Nanodrop spectrophotometer and integrity/quality determined using Bioanalyzer

(Agilent technologies).

2.8.8.2. Bioinformatics analysis

2.8.8.2.1. Alignment to the human genome and expression quantification

TruSeq cDNA libraries were generated from 200 ng total input RNA using

Illumina’s simplified sample prep kit by BGI Tech Solutions CO. Ltd. (Hong Kong,

China) following manufacturer’s instructions

(http://www.illumina.com/content/dam/illumina- marketing/documents/products/datasheets/datasheet_truseq_sample_prep_kits.pdf).

Briefly, mRNA is first purified using polyA selection from total RNA, then chemically fragmented and converted into single-stranded cDNA using random hexamer priming.

The second strand is then generated to create double-stranded cDNA. For TruSeq library construction, blunt-end DNA fragments are generated from double-stranded cDNA using a combination of fill-in reactions and exonuclease activity. An ‘A’-base is then added to the blunt ends of each strand, preparing them for ligation to the sequencing adaptors. Each adapter contains a ‘T’-base overhang on 3’-end providing a complementary overhang for ligating the adapter to the ‘A’-tailed fragmented DNA. 103

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The final products are sequenced on the Illumina HiSeq2000 analyser by BGI Tech

Solutions CO. Ltd. (Hong Kong, China) using standard protocol.

The sequencing reads were aligned to the human genome assembly hg19 using the software package TopHat (version 1.3.1) with standard parameters (Trapnell et al.,

2009). Transcript expression was quantified as reads across exons using the analyzeRNA script from the HOMER software suite (Integrative Genomics and

Bioinformatics Core, version 4) (Heinz et al., 2010) with standard parameters and normalised by the transcript length. To confirm identity of the most abundant ERG transcripts, data were visualised and compared to RefSeq and GENCODE using the

UCSC genome browser (Genome Bioinformatics Group). ERG transcript counts were normalised by the trimmed mean of M-values (TMM) (Robinson et al., 2010).

All genes expressed in week 0 ERG WT and ERG S283D GFP+ CD34+ populations were matched and ranked according to their differential expression using

Generalised fold change (GFOLD) software (version 1.1.0) (Feng et al., 2012). This ranked list was used to interrogate the enrichment of these genes in various expression signatures (section 2.8.8.2.2).

2.8.8.2.2. Gene Set Enrichment Analysis (GSEA)

The ERG +85 enhancer (Ullrich et al.) signature was obtained from Diffner et al. Gene sets ‘up-regulation in ETP ALL’ and ‘up-regulation in HSC vs GMP’ were obtained from Tursky et al. Additional gene sets were derived from publicly available

104

Huang: Chapter 2. Materials and Methods datasets on the MSigDB (Subramanian et al., 2005) website (HALLMARK, Oncogenic pathways).

GSEA was performed using the Preranked module with the GSEA Java Desktop software (Broad institute, version 2.0.13) (Reich et al., 2006) to interrogate the enrichment of oncogenic pathways and gene expression signatures. GSEA used a running sum statistic to identify groups of genes that are enriched in the top or bottom of the ranked list of genes. As gene set size can influence the confidence in results, gene sets consisting of 15 – 500 genes are considered reliable (as recommended by the GSEA software developers). In our analysis 1000 repeated random permutations of gene set expression signatures were used to increase the precision of analysis. The enrichment score (ES) is the maximum deviation from zero of a running-sum statistic that is calculated for each gene set expression signature, and is normalised to the size of the gene set expression signature to produce the normalised enrichment score (NES) which allows comparison of enrichment across multiple gene sets. A p-value < 0.05 is considered significant.

2.8.9. ChIP sequencing

2.8.9.1. ChIP sample preparation

A large scaled retroviral transduction of cord blood cells (Expt4) was performed and week 0 cells taken for ChIP sequencing. Pools of GFP+ cells were selected by

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FACS (section2.8.5)13 and ERG-bound ChIP material extracted using a ChIP-grade

ERG antibody (Santa Cruz, sc-354x) as previously described (Thoms et al., 2011).

Briefly, cells (>2×107) were harvested and washed with PBS, followed by incubation with 1% (w/v) formaldehyde (Sigma, 252549) for 10 min at room temperature. To terminate the cross-linking, cells were incubated with 125 mM glycine for 5 min. Cells were washed with PBS and lysed with a cut p1000 pipette tips14 on ice in cell lysis buffer [10 mM Tris (pH 8.0), 10 mM NaCl, 0.2% NP-40 (Sigma, NP40S), freshly added 1×protease inhibitor cocktail, freshly added 10 mM sodium butyrate] for

10 min to recover nuclei. After centrifugation at 1500 g for 5 min, nuclei were lysed in nucleus lysis buffer [50 mM Tris (pH 8.0), 10 mM EDTA, 1% SDS, freshly added protease inhibitor cocktails, freshly added 10 mM sodium butyrate] on ice for 10 min.

The lysate was diluted in IP dilution buffer [20 mM Tris (pH 8.0), 2 mM EDTA,

150mM NaCl, 1% Triton-X100, 0.01% SDS] and sonicated (settings: high, 30sec pulses) in 0.5 ml sonication tubes (Diagenode, WA-004-0500, 100 µl/tube) using

BioRuptor® sonicator (Diagenode) to yield an average fragmentation size of approximately 200 bp. The chromatin was pre-cleared with 100 μg rabbit IgG (Sigma,

I5006) for 1 hr followed by incubation with 100 μl protein G agarose beads (Roche,

11719416001) for 2 hr. For each sample, 300 μl pre-cleared chromatin was aliquoted

(input for the subsequent qRT-PCR analysis) and the remaining chromatin was divided and incubated with the anti-ERG antibody (10 µg/reaction) or rabbit IgG (10

µg/reaction) overnight at 4°C. To collect antibody-bound protein/DNA complex,

13 ChIP requires >2×107 cells/condition to proceed with. Large scaled transduction and sorting for GFP+ but not GFP+ CD34+ allow maximal number of cells retrieved for the experiment. 14 A cut tip allows gentle lysis and protects the nuclear membrane from physical disruption. 106

Huang: Chapter 2. Materials and Methods chromatin was incubated with 50 μl protein G agarose beads for 2 hr at 4°C. Protein G agarose pellets were washed twice with 500 μl IP wash buffer 1 [20mM Tris (pH 8.0),

2mM EDTA, 50 mM NaCl, 1% Triton-X100, 0.1% SDS], once with IP wash buffer 2

[10mM Tris (pH 8.0), 21 1mM EDTA, 0.25M LiCl, 1% NP-40, 1% Sodium deoxycholate] and twice with TE [10mM Tris (pH 8.0), 1mM EDTA].

Immunoprecipitated chromatin was eluted in 300 μl elution buffer (100mM NaHCO3,

1% SDS) and reverse cross-linking was obtained by incubation with RNase A (3 µg/ml) and NaCl (0.3M final concentration) at 67°C overnight, followed by treatment with

Proteinase K (200 µg/ml, Life technologies, EO0491) at 45°C for 2 hr. Input DNA was treated with RNase A and Proteinase K simultaneously. DNA was extracted twice using phenol-chloroform followed by ethanol/EDTA precipitation. Purified DNA was resuspended in 20 µl TE (pH 8.0) for ChIP sequencing.

2.8.9.2. ChIP sequencing

Library preparation was performed by BGI Tech Solutions (Hong Kong, China) using a variation of the Illumina’s standard protocol. The workflow involves end repair of ChIP enriched DNA using T4 DNA polymerase, Klenow DNA polymerase and T4 polynucleotide kinase to generate blunt ended fragments. ‘A’ bases were added to the 3’ ends using Klenow fragments (3’ to 5’ exo minus) to generate DNA fragments for ligation of adapters, which have a single ‘T’ base overhang at their 3’ end. Adapters were ligated to the DNA fragments using DNA ligase. Adapter-modified DNA fragments were amplified by PCR (15 cycles) and size selected (200 ± 25 bp) by running PCR products on a 2% agarose gel and purifying using a gel extraction kit

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(QIAGEN, 28704). The libraries were validated and clusters generated on flow cells, and sequenced using a HiSeq2000 analyser.

2.8.9.3. Bioinformatic analysis

The publicly available peak-finding program FindPeaks (version 4.2) from the

HOMER software suite was used to call peaks. Genome-wide binding profiles for ERG and the heptad complex (ERG, RUNX1, FLI1, GATA2, LMO2, LYL1 and SCL) in human CD34+ HSPC were obtained from Beck et al. Chromosome region datasets containing ERG bound peaks, heptad bound peaks, and peaks exclusively bound by

ERG S283D were saved as .bed format, and the read coverage ± 1kb around the centre of all peaks from the ChIP sequencing data was mapped onto the peak datasets calculated at 5 bp wiggle steps using the seqMINER program (version 1.3.3)(Ye et al.,

2011). Reads at the centre of all peaks were normalised using the average and SD of reads within the 2000 bp segment, and the normalised values were taken to locate differentially bound regions between ERG WT and ERG S283D. Extracted binding regions with absolute difference > 3 were assigned to two nearest genes (based on a conservative distance of at most 100000 kb) using annotations provided by the genomic regions enrichment of annotations tool (GREAT) analysis package. Chi-square tests

(http://graphpad.com/quickcalcs/contingency1/) were used to access significance between the identified bound regions for ERG WT and ERG S283D using the reads at the centre of the peak, and the sum of reads around the centre (± 1kb). The significantly differentially bound peaks were also combined with the expression data for the nearest gene(s) from RNA sequencing, where expression between ERG WT and ERG S283D samples is differed by >50%.

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2.9. Kinase pathway analysis

2.9.1. In vitro kinase assay

All in vitro kinase assays were carried out according to manufacturer’s recommendations. Briefly, in a 30 µl reaction, 3 µl of 10× kinase buffer (supplied) and adenosine triphosphate (ATP, final concentration 200 µM, Sigma, A2383) was added to

50 µg purified GST-ERG fusion protein with 1.5 nmol myelin basic protein (MBP,

Sigma, M1891). 20 ng ERK2 (NEB, P6080L) or 2 µg ERK1 (Sapphire Bioscience, 000-

00568) were added for incubation at 30°C for 30 min15 and 90 min, respectively. The reaction mixture was resolved in SDS-PAGE gel, coomassie stained and the GST-ERG band (approximately 80 kDa) excised. The sample was in-gel digested with trypsin and subjected to mass spec analysis as described above. Quantification of phosphorylate and non-phosphorylated peptides were performed using the Xcalibur software (Thermo, version 2.2).

2.9.2. In vivo MAPK inhibition/activation

All treatments were performed according to manufacturer’s instructions. Cells were serum-starved16 (i.e. cell lines equilibrated in media containing 0.2% FBS, primary leukaemic xenograft cells equilibrated in serum-free QBSF-60 media) overnight and treated with the following inhibitors: MEK inhibitor U0126 (Promega, V1121), 10 µM

15 Reaction time of ERK2 was adjusted to 90 min for the result in Figure 5-3 to increase the percentage of phosphorylation. 16 For the comparison of kinase inhibitor treatment to vehicle control without subsequent activator treatment, serum starvation was not performed. 109

Huang: Chapter 2. Materials and Methods in 0.2% DMSO at room temperature for 30 min; JNK inhibitor SP600125 (Sigma,

S5567), 50 µM in 0.5% DMSO at room temperature for 40 min; p38 kinase inhibitor

SB203580 (Promega, V1161), 10 µM in 0.1% DMSO at 37°C for 1-2 hr. For MAPK activation, cells were treated with the following activators: MEK activator phorbol 12- myristate 13-acetate (PMA, Sigma, P8139), 100 nM in 0.1% DMSO at 37 °C for 30 min; JNK activator anisomycin (Sigma, A9789), 25 µg/ml in 0.1% DMSO at room temperature for 30 min; p38 kinase activator sorbitol (Sigma, S1876), 500 mM in matching medium at 37 °C for 30 min. For vehicle treatment, cells were treated with matching concentration of DMSO under the same condition. The treated cells were subsequently harvested for ERG immunoprecipitation and mass spectrometry analysis, or cell lysis and immunoblotting.

2.9.3. CFU assay with MEK inhibitor

CD34+ cord blood cells were revived as per section 2.8.3.1 and equilibrated for

3 hr in a tissue culture incubator in cytokine-driven progenitor culture media (Table 2-5) at 4×104 cells/ml. KG-1, ME-1 and equilibrated cord blood cells were pre-treated with

U0126 (10 µM, 0.1% DMSO) or vehicle (0.1% DMSO) at room temperature for 30 min before seeded into CFU assays at 3×103 cells/plate, 2.5×104 cells/plate17, and 5×x102 cells/plate, respectively, with the presence of a final concentration of 10 µM U0126 and/or 0.1% DMSO in culture. See section 2.8.4.2 for detailed CFU protocol.

17 The seeding densities were determined empirically for these cell lines in a trial CFU assay. 110

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2.10. Mutagenesis assays

2.10.1. Protein degradation assay

2.10.1.1. HEK293T transfection

HEK293T cells were seeded at 4×105 cells/well in 6-well plates to reach 50% confluency when transfected with Lipofectamine 2000 reagent on the next day.

Generally, 0.5-2 µg/well total plasmid DNA was mixed with 125 μl Opti-MEM and added drop-wise to pre-mixed Lipofectamine / Opti-MEM (7.5 µl Lipofectamine / 117.5

µl Opti-MEM / well). The DNA / Lipofectamine / Opti-MEM mix was then incubated at room temperature for 20 min before added drop-wise to the cells for overnight transfection at 37°C. The transfection mix was replaced with 3 ml fresh DMEM supplemented with 10% FBS the next morning, and cells were cultured for another 24-

48 hr for protein synthesis.

2.10.1.2. De novo protein synthesis inhibition

Various pMIG+ ERG constructs were transfected into HEK293T cells at 1 µg / well, 8 wells / construct. After 48 hr post-transfection, culture medium was replaced with fresh DMEM supplemented with 10% FBS, premixed with 20 µg/ml cycloheximide (Sigma, C7698) 18 for protein synthesis inhibition. One well was harvested upon the addition of cycloheximide for t=0; the rest of the wells were harvested at indicated time points over a period of five days19.

18 Direct addition of non-diluted cycloheximide stock solution to cell culture is avoided as this will kill the cells at the spot of application. 19 The interval was determined specifically for ERG, as it has a relatively long half-life. For fast-degrading proteins, shorter intervals should be used to get a linear degradation pattern. 111

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2.10.1.3. Protein quantification

Refer to section 2.2 for immunoblotting procedure. By immunoblotting for ERG and β-actin (housekeeping gene), densitometry of all the bands was plotted against time to generate a linear degradation equation for half-life calculation.

2.10.2. Immunofluorescence

2.10.2.1. Retroviral transduction of MOLT-4 cells

MOLT-4 cells were transduced with retrovirus containing pMIG+, pMIG+ HA-ERG WT, pMIG+ HA-ERG S283A or pMIG+ HA-ERG S283D.

2.10.2.1.1. Transient transfection of viral producer cells

Refer to section 2.8.2.

2.10.2.1.2. Retroviral transduction of MOLT-4 cells

MOLT-4 cell transduction procedure was performed in RPMI containing 10%

FBS, 2mM L-glutamine and 100 U/ml P/S (no cytokines). On the day prior to round 1 transduction, cells were seeded at 2.5×105 / 2 ml / well in 6-well plate. Media on producers were changed to RPMI with 10% FBS, 2mM L-glutamine, 100 U/ml P/S. A total of five rounds of transduction were performed over three days. The detailed transduction procedure is described in section 2.8.3.2. In the morning following the last round of transduction, cells were expanded in RPMI supplemented with 10% FBS,

2mM L-glutamine and 100 U/ml P/S for an additional 3-day expansion. Expanded cells

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Huang: Chapter 2. Materials and Methods were harvested and counted, and transduction efficiency assessed by flow cytometry analysis of GFP expression. Cells were used for various assays or cryopreserved for future use20.

2.10.2.2. Cytospin and staining

2.5 × 105 HA-ERG expressing MOLT-4 cells were resuspended in 100 l 2%

FBS in PBS and centrifuged onto poly-L-lysine coated slides (Polysciences, 22247-1) using Shandon single cytofunnels (Thermo Scientific) at 800 g for 10 min at room temperature. Attached cells were fixed immediately with 1% paraformaldehyde (PFA,

Electron Microscopy Sciences, 15710) for 20 min at room temperature. Fixed cells were washed twice with PBS, followed by permeabilisation with 0.05% Triton X-100 in PBS for 15 min at room temperature. After one PBS wash, the cells were blocked overnight with 10% donkey serum (Sigma, D9663) in PBS at room temperature. On the next day,

2% BSA solution in PBS was freshly prepared and filtered through 0.45 µm PVDF filters. Probing conditions for primary/secondary antibodies are listed in Table 2-7.

Excess antibody was washed off at room temperature three times with PBS. DAPI

(nuclear stain) was added to the final wash after secondary antibody probing.

20 Cryopreserved transduced MOLT-4 cells can be expanded for 1-2 passages before GFP expression drops. 113

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Table 2-7 Summary of antibody probing conditions for immunofluorescence.

Antibody Catalogue number Dilution Diluent Probing condition

Anti-HA Abcam 1/250 2% BSA/PBS 4°C, overnight

ab9110

Anti-ERG Santa Cruz 1/500 2% BSA/PBS 4°C, overnight

sc-354x

Anti-rabbit-Fluoro 568 Invitrogen 1/500 2% BSA/PBS 4°C, 1 hr

A10042

DAPI Life technologies 1/2000 PBS Room temperature,

D1306 20 min

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2.10.2.3. Confocal Imaging

Confocal imaging was performed at the Mark Wainwright Analytical Centre,

Biomedical Imaging Facility (BMIF), UNSW Australia. Images were captured on

ZEISS LSM780 microscope.

2.10.3. Fluorescence polarisation (FP) assay

A. Boulton and C. Schmidt (Department of Chemistry, University of Virginia,

U.S.A.) provided the FP assay protocol and performed the experiment. Experimental details in GST-ERG expression and purification may vary from the protocol used by Y.

Huang (section 2.6). Supplier detail and catalogue numbers may not be available for all the reagents used.

2.10.3.1. Expression and purification of GST-ERG protein

A recombinant plasmid containing full length ERG3 in a pGEX vector (for GST tagged recombinant protein expression) was constructed, transformed into Arctic

Express RP (Agilent) cells and single transformant expanded in Terrific Broth containing ampicillin (100 µg/ml) at 37°C. When culture reached an optical density of

1.2 at 600 nm reading, temperature was reduced to 10°C and culture was allowed to cool for 1 hr. Following cooling, expression of GST-ERG was induced with 1 mM

IPTG for 16 hr with agitation. The cells were harvested by centrifugation at 3000 g for

10 min at 4°C, resuspended and lysed in 50 mM Tris (pH 7.8), 500 mM KCl, 1 mM

DTT. Cell membrane was further disrupted using an Avestin Emulsiflex C4 cell disrupter at 12500 psi. After removing the cell debris by centrifugation at 35000 g for 1 hr at 4°C, clarified lysate was adsorbed onto glutathione agarose beads (Sigma)

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DTT] to remove contaminating proteins. Following elution with 10 mM reduced glutathione (Sigma), the recombinant protein was digested overnight with Pierce

Universal nuclease (Thermo Scientific) to digest contaminating DNA.

Protein was further purified by ion exchange and size exclusion using an AKTA prime and an in-house packed column of Q Sepharose. Eluted protein was diluted 6× and loaded by cycling overnight in the cold room. Column was washed with 100 mM

KCl in 50 mM Tris (pH 7.8) and then bound protein eluted using a gradient of 100 mM

- 1 M KCl. Fractions containing GST-ERG were combined and concentrated to 4 ml.

An in-house packed column with s-100 resin was equilibrated in FP buffer [50 mM Tris

(pH 7.5), 300 mM KCl, 1 mM DTT] and 2 ml concentrated GST-ERG was loaded onto the column. This was repeated for the remaining 2 ml GST-ERG. Fractions containing

GST-ERG were consolidated and concentrated to 30 µM for binding measurements.

2.10.3.2. Fluorescence Polarization Measurements

GST-ERG protein was incubated at room temperature for 30 min with 50 nM

TxR M2 DNA (5’-AGGACCGGAAGTAACT/TxR-3’) in 50 mM Tris (pH 7.5), 300 mM KCl, 1 mM DTT. Following incubation 3-fold serial dilutions were performed using buffer containing only 50 nM TxR M2 DNA. Dilutions were allowed to incubate at room temperature for 30 min. Samples were read using a PHERAstar (BMG Labtech) using a Texas Red FP Optical Module (BMG Labtech) Ex-560 Em-630,630. Using the raw data obtained, anisotropy was calculated using MARS (BMG Labtech) software

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(version 1.20 R2). Data were plotted and curves fit using Origin (OriginLabs) software

(version 7.5).

2.10.4. ChIP assay

2.10.4.1. Retroviral transduction of MOLT-4 cells

Refer to section 2.10.2.1.

2.10.4.2. ChIP

MOLT-4 cells over-expressing HA-ERG were subjected to ChIP analysis

(section 2.8.9.1) with a ChIP grade anti-HA antibody (Abcam, ab9110). The ChIP material was reconstituted in 30 µl TE (pH 8.0) and was amplified using specific primer sets (Table 2-8) for qRT-PCR (section 2.8.7). Primers flanking specific ERG binding elements (+85 enhancer and the hHEX+1 enhancer genomic locus) were used to assess

ERG occupancy. Primers amplifying a region near the LMO2 gene were used as an unbound negative control.

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Table 2-8 Primer sequences for ERG ChIP qRT-PCR.

Primer Name Primer Sequence

+85 Forward 5’-ACAACACCACTCCGCATTG-3’

+85 Reverse 5’-TGAACACTCGTTACAAGACTAATC-3’

hHEX+1 Forward 5’-CCTGACCCTTTCCGTTCATA-3’

hHEX+1 Reverse 5’-ATGCAGCCAGGAAAACACTT-3’

LMO2 Forward 5’-GAAATAAATATCTCCACTGTCCTG-3’

LMO2 Reverse 5’-CTATCTGCCTATCTCTCATCTATC-3’

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2.10.5. Transactivation/reporter gene assay

The luciferase assay system (Promega) was used in this study. The transactivation activity of ERG was visualised by a reporter gene system using the +85

SCE-luciferase plasmid. HEK293T cells were seeded in quadruplicate for each tested condition (triplicate for luciferase activity measurement and one for immunoblotting) and transfected with the luciferase reporter gene pGL2b-+85-luc (1.5 µg/well), 0.25 µg of the expression vectors pMIG+/pMIG+ ERG and 0.2 µg control plasmid pEFBOS-

LacZ. (Refer to section 2.10.1.1 for detailed transfection protocol). After 48 hr, cell lysates were prepared in LB buffer [25 mM Tris phosphate (pH 7.8), 8 mM MgCl2, 1%

BSA, 1% Triton X-100, 15% glycerol, 1 mM DTT (freshly added), 1 mM ATP, 5%

(w/v) D-luciferin (Sigma, L9054)] and luciferase activity measured on a luminometer

(GLOMAX 96 microplate luminometer, Promega) using the GLOMAX software

(Promega, version 1.7.1). Luciferase activity readings were normalised for LacZ activity readings.

LacZ activity was determined using 20 µl lysate in 150 µl LacZ buffer [82 mM

Na2HPO4, 18 mM NaH2PO4, 1 mM MgCl2, 0.1% (w/v) ortho-Nitrophenyl-β-galactoside

(ONPG, Thermo Scientific, 34055), 50 mM β-mercaptoethanol] and absorbance at 405 nm measured using a kinetic setting on the Spectra MAX 190 absorbance microplate reader.

For ERG expression measurement, cell lysates from the same transfection group were immunoblotted for ERG and β-actin (section 2.2).

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2.11. Statistical analysis

In this study, unless otherwise described, an unpaired Student’s t-test was applied for statistical analysis, and a p-value < 0.05 was considered statistically significant.

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Chapter 3. Identification of ERG S283 Phosphorylation in Leukaemic Cells

To investigate links between ERG phosphorylation and leukaemogenesis, I first set out to identify ERG phosphorylation sites in leukaemic cells. The leukaemic cell lines used in this project are MOLT-4, a human T-ALL cell line (Minowada et al.,

1972); KG-1, a human acute myelogenous leukaemia cell line (Koeffler and Golde,

1978); and ME-1, a human acute myelomonocytic leukaemia cell line with eosinophilia

(Yanagisawa et al., 1991). All three cell lines have high endogenous ERG expression

(Diffner et al., 2013; Su et al., 2004).

3.1. Human ERG is phosphorylated on five serines

ERG is a known to be phosphorylated on serine residues (Murakami et al.,

1993). Phosphorylation at ERG S222 of the TMPRSS2-ERG fusion protein has been identified in prostate cancer cells and reported to be associated with cell migration and invasion (Selvaraj et al., 2015). However, the specific site(s) of ERG phosphorylation in leukaemia and their role have not been elucidated. MOLT-4 T-ALL cell line, which is high in endogenous ERG expression (Su et al., 2004), was initially selected for the identification of ERG phosphorylation sites in this study. Due to the relatively low abundance of ERG compared with abundant cytoskeletal proteins such as actin, endogenous ERG was immunoprecipitated as an initial enrichment step to enhance mass spectrometry signals (Figure 3-1A). Since different enzymes digest their protein

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The identity of ERG was confirmed by LC-MS/MS with 61% sequence coverage from the in-gel trypsin digested sample (Figure 3-1B) and 20% sequence coverage from the in-gel chymotrypsin digested sample (Figure 3-1C). Parallel phosphoenrichment of the same trypsin digested sample showed that endogenous ERG from MOLT-4 T-ALL cells was phosphorylated on four unique serine residues –S88,

S103, S222 and S283 21 (Figure 3-2A, B). Since ERG is phosphorylated at S55 in normal mouse tissues (Huttlin et al., 2010), but the cleavage pattern of trypsin does not cover this residue as the proteolytic peptide containing S55 consists of only four amino acids (peptide sequence MSPR) (Figure 3-1B) and is outside the mass range of the mass spectrometer, chymotrypsin digestion was performed to determine whether ERG S55 is phosphorylated in MOLT-4 cells. Upon phosphoenrichment of the chymotrypsin- digested ERG, S55 was the only phosphorylation detected in immunoprecipitated ERG from MOLT-4 cells (Figure 3-2A). Among the five phosphoserines identified, S55, S88 and S103 are located within the N-terminus unstructured domain of ERG, while S222 and S283 reside between the PNT and ETS domains which regulate ERG protein-protein interaction (Carrere et al., 1998) and direct DNA binding (Siddique et al., 1993), respectively. The presence and identity of the phosphoserines were manually confirmed from the corresponding tandem mass spectra (Figure 3-2C, Figure S1).

To ensure detection of all existing phosphorylation sites in ERG, replicate trypsin digestions were performed for this study (n=6). S88 and S283 were identified by

21 Amino acid number are based on full-length ERG3, consisting of 486 amino acids. 122

Huang: Chapter 3. ERG S283 Phosphorylation in Leukaemic Cells the Mascot searching software in all six independent experiments. S103 was identified in one experiment, indicating its low abundance in MOLT-4 cells. S222 was identified in one experiment but was also identified manually using the Xcalibur browser in two replicate experiments. The failed detection of pS222 by Mascot is likely due to its low m/z ratio (m/z = 433.2001) which caused the peptide to be not selected for MS/MS during data depending data acquisition. Chymotrypsin digestion and phosphoenrichment was only performed once in which ERG pS55 was identified.

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Figure 3-1 MS coverage of endogenous ERG from MOLT-4 T-ALL cells.

(A) Coomassie stained SDS-PAGE gel with excised immunoprecipitated ERG band.

Protein G Dynabeads with bound ERG was resuspended in 50 µl 1× sample buffer and was loaded into three lanes. (B-C) MS coverage of (B) trypsin digested or (C) chymotrypsin digested ERG from in-gel digestion. The peptide hits are matched to human ERG3 isoform (486 amino acids) from the UniProtKB/Swissprot database.

Identified peptides are shown in bold red.

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Figure 3-2 MS analysis of ERG from MOLT-4 T-ALL cells revealed five phosphorylated serines.

(A) MS peptide coverage of phosphoenriched ERG. Residues detected in tryptic peptides are in red and residues detected in chymotryptic peptides are in blue.

Phosphorylated serines are highlighted in green. (B) A schematic showing the phosphorylation sites identified for ERG and their relative positions to the two functional domains (PNT, Pointed; ETS, E-twenty six). (C) Representative tandem mass spectrum of the phosphorylated peptide containing S283. The b- and y-ions are annotated and labelled on the spectrum and MS1 accurate mass spectrum is shown in

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Huang: Chapter 3. ERG S283 Phosphorylation in Leukaemic Cells the inset. Note that for clarity, some regions of the mass spectrum have been amplified

10 fold.

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It should be noted that phosphoenrichment using TiO2 columns is typically biased for the identification of phosphoserine and phosphothreonine as these are generally of much higher abundance compared with phosphotyrosine (Rush et al.,

2005). Phosphotyrosines are typically enriched using phosphotyrosine-specific antibodies (Zoumaro-Djayoon et al., 2012). However, ERG has been shown to be only phosphorylated on serine residues (Murakami et al., 1993), thus the enrichment of phosphotyrosine from immunoprecipitated ERG was not attempted.

3.2. Intracellular location of ERG phosphosites

To compare the level of each ERG phosphopeptide within the nucleus and the cytoplasm, MOLT-4 cells were fractionated with ERG immunoprecipitated and MS analysed separately for the two fractions. Total protein quantification from in-gel digested sample shows that ERG is primarily located in the nucleus of MOLT-4 cells, with the nuclear fraction having 4 times of ERG compared to the cytoplasm (Figure S2).

To account for potential biased detection of phosphopeptides due to differential ERG abundance from different cellular compartments, the signal intensity of each phosphopeptide was normalised against the total ERG protein from the corresponding fraction to indicate the relative abundance of phosphorylation (Figure 3-3).

ERG S88 is mostly phosphorylated in the cytoplasm, while ERG pS283 is primarily detected from the nuclear fraction. ERG S222 is phosphorylated to a comparable extent in both fractions (Figure 3-3). ERG S103 was not detected in this experiment due to its low abundance. Coverage of ERG S55 requires chymotrypsin digest which was not part of this experiment.

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Figure 3-3 Cytoplasmic and nuclear abundance of ERG phosphorylation.

The nuclear and cytoplasmic levels of each ERG phosphosite were determined using

MOLT-4 cells. Normalisation was performed against the total ERG amount from each cellular compartment.

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3.3. Potential association of ERG pS283 with leukaemia

To focus my research on relevant ERG phosphorylation site(s), a literature search was performed using the results from three previous studies. ERG phosphorylation sites were retrieved from the respective supplementary data when needed which highlighted ERG S283, a serine residue phosphorylated in MOLT-4 cells, is not found in healthy HSPC [Supplementary Table of Guo et al. (2013)], normal mouse tissues [Table S1 of Huttlin et al. (2011)] or the prostate cancer cell line

(Singareddy et al., 2013) (Figure 3-4A).

To confirm this, the same experimental procedure was performed on another leukaemic cell line, the KG-1 AML cell line, as well as primary CD34+ HSPCs from the bone marrow of a healthy donor. As mentioned in section 3.1, within cells ERG is present in low abundance and phosphosites can only be identified after phosphoenrichment. This violates the validity of direct calculation of the % phosphorylation using the signal intensities of the unphosphorylated and phosphorylated versions of the same peptide. An alternative approach was therefore employed for the comparison of ERG S283 phosphorylation level from different cell types based on the observation that ERG S88 was abundantly phosphorylated in all three cell types.

Although not all samples would necessarily have equal level of ERG S88 phosphorylation, this modification was used as a reference to indicate the relative level of pS283. The signal intensities of phosphopeptides containing pS88 and pS283 were manually extracted using Xcalibur (Figure 3-4B, C). pS283 levels were plotted as a ratio to S88 phosphorylation (Figure 3-4D). Interestingly, ERG S283 phosphorylation, while always abundantly present at equivalent abundance to pS88 in both MOLT-4 T-

ALL and KG-1 AML cell lines, was detected at over 100 fold lower abundance to pS88 129

Huang: Chapter 3. ERG S283 Phosphorylation in Leukaemic Cells in healthy HSPCs (Figure 3-4A, B, C, D). No replicate experiment was performed for the MS identification of ERG phosphorylation from CD34+ HSPC due to the large cell number (> 3×107) required for immunoprecipitation and limited availability of this cell type.

In a recent study, Selvaraj et al. reported that when being in vitro phosphorylated, ERG S222 phosphorylation preceded S103 and S283 phosphorylation.

Over-expression of exogenous ERG in a prostate epithelial cell line (RWPE1) lacking endogenous ERG expression showed phosphorylation at S222 contributed to enhanced cell migration (Selvaraj et al., 2015). Despite the functional impact of ERG S222 phosphorylation on prostate cell migration, this study still focused on ERG S283 phosphorylation and its importance in leukaemic cells as this modification was barely detectable in healthy HSPC.

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Figure 3-4 ERG pS283 is abundant in leukaemic cell lines, but not in healthy

CD34+ HSPC.

(A) Summary table of the presence (Y) / absence (N) of ERG phosphorylation in different cell types in this study and in previous literatures. Phosphorylation status when not applicable is denoted as “-”. (B-C) Signal intensities of the spectra containing phosphorylated S88 and S283 in (B) MOLT-4 and KG-1 cells and (C) MOLT-4 and

CD34+ HSPC were extracted from the corresponding mass spectra and quantified as area under peak (AA). (D) ERG pS283 signals in MOLT-4, KG-1 and CD34+ HSPC quantified using MS were plotted as a ratio to the level of pS88 on a log 10 scale.

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3.4. Generating an ERG pS283 antibody

Primary samples (patient samples, xenograft samples) are usually only available in small cell numbers, either hard to or cannot be propagated in culture. Since ERG being a transcription factor is present in low abundance within the cell, it is essential to perform immunoprecipitation and phosphoenrichment prior to MS analysis of the phosphorylation site/level, which generally requires >3×107 cells per sample. To enable the detection of ERG pS283 from small number of cells and allow unbiased parallel comparison of the level of this modification across multiple samples, a customised mouse monoclonal antibody recognising ERG pS283 was generated.

Purified ERG expressed in bacteria (unphosphorylated) and in vitro phosphorylated purified ERG was used for the quality check of the antibody. Based on the quality report of 19 clones generated by ProMab Biotechnologies Inc. (U.S.A.), clone #1-8 recognised both phosphorylated and unphosphorylated ERG; clone #9-10 recognised only unphosphorylated ERG; clone #11-19 recognised only phosphorylated

ERG (Figure 3-5).

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Figure 3-5 Antiserum clone report of ERG pS283 antibody.

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19 clones were generated by ProMab Biotechnologies Inc. (U.S.A.) against the synthetic ERG phosphopeptide containing pS283 [PTPQSKAAQP(p)SPSTVPKTEDQ] and screened by blotting against phosphorylated [in vitro ERK2-treated, 56% phosphorylation (Figure S3), lane 1-19] or non-phosphorylated (lane 20-38) purified

GST-ERG (approximately 80 kDa).

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As the intention of generating this antibody was to only quantify the level of

ERG pS283 in cell lysates while sparing the nonphosphorylated protein, clone supernatant #11-19 was further tested by blotting against MOLT-4 whole cell lysate

(Figure 3-6). Unfortunately, none of the clones successfully picked up a pS283 signal, likely due to the low concentration of antibody present in the clone supernatant.

However, clone #13-19 were not considered ideal candidates as they showed various levels of non-specific bands (Figure 3-6). Clone #11 and #12 had minimal background

(Figure 3-6), which were further tested using purified phosphorylated [in vitro

MAPK/ERK2 treated, 56% phosphorylation on ERG S283 (Figure S3)] GST-ERG.

Both clones had specificity against phosphorylated GST-ERG (80 kDa) while not recognising the non-phosphorylated protein (Figure 3-7). The stronger signal of phosphorylated GST-ERG (80 kDa) and the visibility of endogenous ERG band (54 kDa) in MOLT-4 lysate from clone #12 (Figure 3-7) indicated higher sensitivity of this clone, which was therefore chosen for subsequent antibody production.

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Figure 3-6 ERG pS283 antiserum candidate screening. The potential candidates of ERG pS283 antiserum clone supernatant were picked based on the clone report and further screened using MOLT-4 whole cell lysate (50µg/lane) to assess sensitivity and specificity. Blot blocking was performed using 1% BSA/TBS-T.

The clone numbers are labelled and a positive blot using an anti-ERG1/2/3 antibody

(Santa Cruz, sc-354x) is included for reference.

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Figure 3-7 Sensitivity testing of two candidate clones of ERG pS283 antibody. Two final candidate clones of the ERG pS283 antibody - clone #11 (left panel) and clone #12 (right panel) - were tested using MOLT-4 whole cell lysate (50 µg/lane), phosphorylated (ERK2-treated, 56% phosphorylation) and non-phosphorylated purified

GST-ERG (approximately 80 kDa). Blot blocking was performed using 1% BSA/TBS-

T. Clone specificity and sensitivity were determined by immunoblotting on identical blots using the same exposure setting.

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Upon receiving the purified antibody concentrate, the probing condition was optimised using different combinations of conditions (dilution 1/1000-1/20000, diluent

5% skim milk/TBS-T / 1% BSA/TBS-T, probing temperature 4°C / 20°C / 37°C, probing time 1 hr / 3 hr / overnight) against MOLT-4 whole cell lysate (Figure 3-8).

Mammalian milk contains high level of casein which is highly phosphorylated (Kunz and Lonnerdal, 1990; Li et al., 2012) therefore is not recommended for the probing of anti-phosphorylation antibodies due to potential non-specific binding and interference with target protein recognition. The optimal probing condition of the customised anti-

ERG pS283 antibody was found to be between 1/1000 to 1/5000 dilution in 1%

BSA/TBS-T, 4°C overnight (Figure 3-8). 1/3000 dilution was used in subsequent experiments for minimal background signal.

It is noticeable that the antibody produces non-specific bands when probed against endogenous cell lysate due to cross-reactivity with other cellular proteins

(Figure 3-8B). Nevertheless, the identity of pS283 ERG band can be ascertained given there is only one band around 54 kDa (Figure 3-8B).

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Figure 3-8 Optimisation of the probing condition for anti-ERG pS283 antibody. Anti-ERG pS283 antibody was probed using MOLT-4 whole cell lysate (50 µg/lane) under different conditions as indicated. The blot was blocked and probed in 5% skim milk/TBS-T (A) or 1% BSA/TBS-T (B). The pERG band (54 kDa) was indicated by arrow.

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3.5. Screening primary ALL for ERG pS283 expression

As the primary intention of generating an anti-ERG pS283 antibody is to evaluate the level of ERG S283 phosphorylation in primary samples with small cell number, upon successful validation of the customised ERG pS283 antibody, a panel of

19 T-ALL xenografts including five ETP ALL xenografts were screened for direct comparison of their ERG pS283 levels. All xenograft cells were generous gift from Prof

R. Lock’s lab (Children Cancer Institute Australia) and the genetic profiles have been characterised and previously published (Suryani et al., 2014). Various phosphorylation levels were detected in these primary samples although the ETP ALL samples, which are known for their high risk of treatment failure and poor patient outcome (Coustan-

Smith et al., 2009), showed consistently high levels of ERG S283 phosphorylation

(Figure 3-9). Comprehensive information in terms of survival and patients’ response to specific treatment regimens on these xenografts was not available. However, this antibody can be used for correlating ERG S283 phosphorylation level with survival/response to treatment in the future.

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Figure 3-9 The ETP ALL xenografts exhibit higher levels of ERG S283 phosphorylation.

19 primary ALL xenografts including five ETP ALL xenografts were immunoblotted for S283 phosphorylation in ERG using the customised anti-pS283 ERG antibody in comparison with CD34+ HSPC. Expression of ERG pS283, total endogenous ERG and

β-actin were shown.

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3.6. Chapter summary

In summary, five phosphoserines were identified on endogenous ERG in

MOLT-4 T-ALL cells. By comparing with the phosphorylation status of ERG in other cell types determined in this study as well as previously published literatures, S283 phosphorylation was noted by its high abundance in leukaemic cell lines, but low levels in healthy CD34+ HSPC and other cell types. By using a customised ERG pS283 antibody, a potential link between this modification and the leukaemic phenotype was further suggested, as high pS283 was observed in ETP ALL cells, a subset of ALL with poor clinical outcome (Coustan-Smith et al., 2009).

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Chapter 4. ERG pS283 Induces a Proliferative Phenotype in HSPC

Considering that over-expression of wild-type ERG induces human HSPC expansion/clonogenicity (Tursky et al., 2015), I further investigated the effect of high expression of ERG S283 phosphomutants on the same aspects.

4.1. The principle underlying the mutagenesis assay

The contribution of ERG S283 phosphorylation on its function was determined by performing site-directed mutagenesis to replace this amino acid with either alanine to eliminate the effects of inducible phosphorylation or aspartic acid to form a phosphomimetic functional group that mirrors constitutive phosphorylation (Figure 4-

1). More specifically, as the hydroxyl side chain (-OH) on serine (S) residues can normally be phosphorylated, mutation to alanine (A) with a non-polar and unphosphorylatable side chain is considered a ‘phosphodefective’ change. On the other hand, mutation to aspartic acid (D) is referred to as a ‘phosphomimetic’ change as it introduces a negatively charged carboxylic acid side chain (-COOH) which mimics the phosphate group on phosphorylated serine residues (Figure 4-1). The alanine mutant should therefore behave as a non-phosphorylated serine, while the aspartic acid mutant is expected to be perceived as a phosphoserine by the cell. This is the conventional approach to study the impact of phosphorylation, which has been used by past studies to

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2008; Smith and Miskimins, 2011; Xie et al., 2015; Zhang et al., 2008).

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Figure 4-1 Schematic explanation of the mutagenesis strategy.

Chemical structures of amino acids used for ERG S283 mutant generation. The functional side chains are circled in red. Phos, phosphorylation.

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4.2. ERG S283 mutants are active haematopoietic transcription factors

To investigate the effect of ERG S283 mutant over-expression in CD34+ HSPC, human ERG3, the major ERG isoform found in haematopoietic cells (Bohne et al.,

2009), was inserted into a retroviral expression vector and transduced into human cord blood cells. The retroviral packaging cell line, Phoenix cells, generate RD114- pseudotyped viral particles when transfected with retroviral vectors. This viral pseudotype has been shown to be the optimal envelope protein for viral transduction of immature haematopoietic cell populations (Neff et al., 2004). The vector pMIG+ contains an IRES-GFP cassette which allows easy identification of transduced cells by their expression of GFP. CD34+ cord blood cells were pre-stimulated with cytokines

SCF, TPO, Flt3L and IL-6 to initiate cell cycling for three days, then underwent five rounds of transduction over three days to maximise transduction efficiency, followed by three days of expansion to allow for GFP and ERG expression and to increase cell numbers (Figure 4-2). This time point was designated as week 0, when the cells were split across a variety of functional assays.

A total of four transduction experiments were performed in this study. Expt1, 2 and 3 were kept in culture until replicative exhaustion to assess the impact of high ERG

S283 mutant expression on transduced cell expansion and clonogenicity. Expt4 was a large-scaled transduction, sorted for GFP+ population at week 0 for ChIP sequencing. A fraction of Expt2 and 3 week 0 cells were sorted for GFP+ CD34+ double positive cells for RNA extraction and sequencing. Expt3 and 4 do not have pMIG+ ERG S283A condition. ERG S283A condition was contaminated in Expt3 at an early time point and

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Figure 4-2 Experimental procedure of CD34+ HSPC transduction.

(A) Schematic of cord blood (CB) CD34+ cell transduction procedure. Cells were pre- stimulated for three days to initiate cell cycling, then underwent five rounds of transduction over three days to optimise vector uptake and integration, followed by three days of expansion, all of which were done in the presence of cytokines SCF, TPO,

Flt3L, and IL-6 (concentrations in Table 2-5). Cells harvested post-expansion were designated as week 0 cells for assays. (B) Representative flow cytometry dot plots

(Expt2) showing the gated viable cells post-expansion. Untransduced mock cells were used to set the gate for GFP+ cells. The percentage of GFP+ cells are shown in the boxed regions of the gated populations. FSC, forward scatter.

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The transduction protocol was optimised with different combinations of conditions (polylysine-coated vs non-coated flasks for producer cell seeding, αMEM vs

DMEM for producer cell culturing, HA-tagged vs untagged ERG constructs) and the optimal condition (described in section 2.8.2-2.8.3) was determined by the highest viral titre of the VCM (data not shown). Highest titre was achieved using virus producers grown in αMEM on non-coated flask, transfected with untagged pMIG+ ERG constructs. The transduction efficiency of pMIG+ (approximately 65%) was consistently higher than the pMIG+ ERG constructs (approximately 40%) in all four transductions (representative flow cytometry plots shown in Figure 4-2B), possibly due to easier incorporation of a plasmid smaller in size (pMIG+ 6.6 kb; pMIG+ ERG 8.1 kb). This did not affect the interpretation of results, as the effect of ERG S283 mutants was directly compared to WT ERG, and all ERG constructs have comparable transduction efficiency.

To determine the functional effect of ERG pS283 on HSPC expansion, transduced human cord blood cells were cultured in media with cytokines selected to maintain and expand the progenitor cells (SCF 50 ng/ml, TPO 10 ng/ml, Flt3L 50 ng/ml, IL-6 10 ng/ml). The cells were passaged weekly, with aliquots taken for flow cytometry, CFU assays and RNA extraction. Total ERG expression from three independent transduction experiments (Expt1, 2, 3) was determined by qRT-PCR from week 0 until replicative exhaustion. ERG expression was substantially elevated in ERG

WT and S283 mutants transduced cells, while ERG level in pMIG+ cells were maintained at very low levels throughout the culture period (Figure 4-3). ERG protein level was not further determined by immunoblotting, as it requires cell extract from

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Tursky et al. have previously shown that relative to untransduced cells, ERG expression levels in pMIG+ transduced CD34+ cord blood cells fall (untransduced range 3.2-11.1, pMIG+ range 0.5-1.4) at week 0 as a result of the transduction procedure (Tursky et al., 2015). Transduced cells are cultured in high cytokine concentrations to induce cell cycling and to encourage retroviral uptake and integration.

The resultant GFP+ population consists of cells that have successfully integrated the plasmid construct into their genome. The transduction procedure alters CD34+ heterogeneity, biasing the population toward a more progenitor like composition in both pMIG+ and pMIG+ ERG cultures. This accounts for the lower ERG expression level observed in the pMIG+ transduced cells compared to the untransduced cells (Tursky et al., 2015), while ERG level was boosted in the pMIG+ ERG transduced cells by ERG over-expression. This observation highlights the importance of using cord blood matched pMIG+ transduced cells as the negative control to allow direct comparison of the effect of high ERG expression in ERG transduced cell populations (Tursky et al.,

2015).

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Figure 4-3 ERG expression in HSPC cytokine-driven cultures.

ERG transcript levels from three independent cord blood transduction experiments are shown. The data were normalised to a housekeeping gene ABL for all samples. Top to bottom = Expt1, Expt2, Expt3. Error bars were calculated from duplicate qRT-PCR measurements.

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In all three ERG conditions, comparable outgrowth of high ERG expressing clone (GFP+) was observed which stabilised at week 7 until the end of the culture

(Figure 4-4), suggesting the S283 mutant ERG protein remained functional as a growth promoting transcription factor in human HSPC. In contrast, the transduced population

(GFP+) declined in the pMIG+ cells and remained at a low level (Figure 4-4). This was significant when averaged across three independent experiments (p<0.0001 for all three

ERG conditions).

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1 2 0 M IG 1 0 0 E R G W T E R G S 2 8 3 A 8 0

% E R G S 2 8 3 D

P 6 0

F G 4 0

2 0

0 0 2 4 6 8 1 0 1 2 1 4 T im e (W e e k )

Figure 4-4 Percentage of transduced cells in HSPC cytokine-driven culture.

The % GFP of HSPC was measured by flow cytometry at each week until replicative exhaustion. Untransduced cells were used as negative gates for GFP = 0. Error bars represent SD from three independent transduction experiments. p-values were determined using a segmented regression approach with a linear mixed model fitting all three experiments to separately estimate changes in each variable over time. Same level of statistical significance was obtained for all three ERG conditions. A p-value<0.05 was considered statistically significant. ****p<0.0001.

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4.3. ERG S283 phosphomimetic mutant promotes HSPC expansion

The primitive population in cord blood cells is marked by the expression of the stem cell surface marker CD34. Within the transduced population (GFP+), the CD34%

(GFP+ CD34+ %) was higher in all three ERG over-expressing conditions immediately after transduction (week 0) compared to the pMIG+ control, and remained elevated throughout the culture period (Figure 4-5). This is in line with the findings in Figure 4-4 that ERG S283 mutants retained their transcriptional activity. Interestingly, pMIG+

ERG S283D construct exhibited a more dramatic elevation in CD34+ population in comparison with WT and S283A ERG (Figure 4-5), indicating maintenance of the more primitive population by constitutive phosphorylation at ERG S283. The same trend was observed across three independent transduction experiments (Expt1, 2, 3), with a representative graph of Expt2 shown in Figure 4-5. Statistical analysis was not performed on these data, as there was not an appropriate model to fit the curvature.

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4 0

M IG

% 3 0 E R G W T

+ E R G S 2 8 3 A 4 3 E R G S 2 8 3 D

D 2 0

+ P

F 1 0 G

0 0 2 4 6 8 1 0 1 2 1 4

T im e ( W e e k )

Figure 4-5 Elevated CD34% in transduced HSPC by ERG S283 phosphomimetic mutant.

Percentage of CD34+ cells within the GFP+ population from a representative transduction experiment (Expt2). Cells from matching conditions stained with IgG-PE were used as negative gates for CD34% = 0.

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ERG S283D over-expression was also associated with a dramatic increase in cell expansion compared to ERG WT cells, evident from week 8 post-transduction (Figure 4-

6). The enhanced proliferative capacity was accounted for by the expansion of transduced cells (GFP+) and more specifically the CD34+ transduced (GFP+ CD34+) population (Figure 4-6A). The proliferative capacity of ERG WT GFP+ CD34+ cells, although longer lasting in comparison to the pMIG+ cells, reached their peak within 11 weeks of culture, whereas this was extended to 14 weeks in the ERG S283D culture

(Figure 4-6A). In other words, the enhanced expansion contributed to an increase in the duration of the ERG S283D culture before the cells reached replicative exhaustion.

Irrespective of individual cord blood variability, the cumulative expansion of the GFP+

CD34+ cells of the ERG S283D condition in all three independent experiments was consistently enhanced relative to the ERG WT cells (Table 4-1, p<0.001).

The increased expansion observed in CD34+ ERG S283D transduced cells was also evident in the GFP+ CD34- population (Figure 4-6B, Table 4-1, p<0.0001). This data indicate that the capacity of the CD34+ cells to differentiate beyond the CD34+ stage is not altered by mutant ERG over-expression and suggest that ERG S283 phosphorylation contributes to better maintenance and expansion of the HSPC in cytokine-driven culture.

For Figure 4-6 and later Figure 4-7, statistical significance was calculated from the difference in regression parameters between the ERG WT and ERG S283D curves across three independent experiments (Expt1, 2, 3). p-values are therefore not shown on the representative graphs as they do not represent the trend in individual experiment, but are included in the main text and summarised in Table 4-1. 157

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Figure 4-6 ERG S283 phosphomimetic mutant promotes the maintenance and expansion of HSPC.

Transduced cord blood cells were cultured with human SCF, TPO, Flt3-L and IL-6 until replicative exhaustion to address the maintenance and expansion of HSPC.

Representative graphs (Expt2) showing the cumulative fold expansion of CD34+ (A) and CD34- (B) cells within the transduced (GFP+) fraction over time calculated relative to the cell number at week 0.

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4.4. ERG S283 phosphomimetic mutant enhances HSPC clonogenicity

As the CD34+ population is very heterogeneous, additional functional assays were employed to characterise the effect of ERG S283 phosphorylation in more detail on the phenotype of primitive HSPC. Assessment of the clonogenic potential using a

CFU assay was performed weekly during the cytokine-driven culture until replicative exhaustion. An increased frequency of CFU in the ERG WT cultures was maintained compared to the pMIG+ condition, resulting in a greater production of GFP+ CFU with high ERG expression (Figure 4-7, Table 4-1) – this is consistent with previously published findings by Tursky et al. Additionally, both ERG S283 mutants also produced more colonies compared to the pMIG+ cells (Figure 4-7, Table 4-1), consistent with them being active transcription factors with leukaemogenic activity. Most importantly,

ERG S283D cells showed even higher colony forming ability in the transduced population (GFP+), evident from week 7, in comparison to the ERG WT condition

(representative data from Expt2 shown in Figure 4-7). Enhanced colony formation by

ERG S283D was observed in three independent experiments (Expt1, 2, 3) with statistical significance (Table 4-1, p<0.01).

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s l

l 1 0

e 1 0

+ P

F 1 0 8 M IG

U E R G W T

C a E R G S 2 8 3 A

l 6

+ 1 0 u

P E R G S 2 8 3 D

G C 4

0 1 0

r 1 0 2 e

p 0 2 4 6 8 1 0 1 2 1 4 T im e /w e e k

Figure 4-7 ERG S283 phosphomimetic mutant induces a more clonogenic phenotype in HSPC.

Transduced cord blood cells were seeded weekly for CFU assay until replicative exhaustion to assess the clonogenicity of HSPC. Seeding density was adjusted weekly to give 20-200 colonies per dish. Representative data (Expt2) show GFP+ CFU count per 10000 cumulative GFP+ cells from week 0.

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Table 4-1 ERG S283 phosphomimetic mutant increases the expansion and clonogenicity of HSPC in cytokine-driven culture.

GFP+ CD34+ GFP+ CD34- GFP+ CFU

Expt1* pMIG+ 3.00 ×100 2.21 ×102 5.58 ×106

ERG WT 1.95 ×102 2.12 ×103 2.49 ×107

ERG S283A 6.94 ×102 1.96 ×103 8.11 ×107

ERG S283D 9.93 ×102 1.93 ×103 3.96 ×107

Fold change 5.07 0.91 1.59

Expt2 pMIG+ 2.41 ×102 9.31 ×103 6.87 ×103

ERG WT 5.12 ×103 1.80 ×104 5.40 ×106

ERG S283A 2.86 ×103 4.53 ×104 1.36 ×106

ERG S283D 3.99 ×106 8.45 ×106 4.57 ×109

Fold change 779 469 845

Expt3# pMIG+ 4.75 ×101 4.05 ×103 8.74 ×103

ERG WT 3.57 ×103 5.42 ×104 2.31 ×106

ERG S283D 5.27 ×103 9.36 ×104 5.05 ×106

Fold change 1.47 1.73 2.19

p-value for effect of p<0.001 p<0.0001 p<0.01

ERG S283D over time

Data show area under the curve calculation of the cumulative expansion of GFP+

CD34+ and GFP+ CD34- populations, and the cumulative GFP+ colony formation for each independent cord blood replicate. Fold change was calculated as ERG S283D 

ERG WT. The p-values derive from a segmented regression approach using a linear

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* Expt1 data calculated from week 0 to week 6. Experiment was terminated at week 6.

# Expt3 does not have ERG S283A data.

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4.5. ERG S283 phosphomimetic mutant induces an oncogenic gene signature

GFP+ CD34+ cells of the pMIG+ ERG WT and pMIG+ ERG S283D conditions were sorted at week 0 post-transduction from two independent experiments (Expt2 and

3) for genome-wide expression analysis. High quality RNA (RNA integrity number 9.6-

10, 28S:18S ratio of 1.8–2.1, Table S3) was extracted and shipped for sequencing by

BGI Tech Solutions (Hong Kong, China). Following alignment of sequence tracks to the human genome (UCSC genome assembly hg19) and transcript expression quantification, ERG3 expression signal strength confirmed successful over-expression at equivalent levels in ERG WT and ERG S283D cells (Figure S5).

In order to investigate the effect of ERG S283 phosphorylation on the gene expression programs in human HSPC, genes for which expression was measured

(41087 transcripts) were ranked according to their differential expression [GFOLD analysis (Feng et al., 2012)] with ‘up-regulated in ERG S283D condition’ at the lower end and ‘down-regulated in ERG S283D condition’ at the upper end. This was used to interrogate the enrichment of various gene sets by GSEA.

Firstly, enrichment was assessed using the gene signatures driven by WT ERG over-expression in transduced CD34+ HSPC, contributing to a more proliferative phenotype and blockage of differentiation (Tursky et al., 2015). The further enhanced proliferation and clonogenicity observed in ERG S283D transduced cells suggest that some of these signatures, when compared with ERG WT, may be further enriched by the phosphomimetic mutant. Significantly enriched gene signatures by ERG S283D over-

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Huang: Chapter 4. ERG pS283 Induces Proliferative Phenotype expression include the ERG +85 stem cell enhancer (SCE) signature (Diffner et al.,

2013; Ullrich et al.) [normalised enrichment score (NES) 2.373, p<0.001], a gene set derived from Novershtern et al. of genes up-regulated in cord blood HSCs compared to granulocyte-macrophage progenitors (GMP) (Novershtern et al., 2011) (NES 2.191, p<0.001), and a gene signature driven by the heptad complex in primary HSPC (NES

1.330, p<0.05) (Figure 4-8). These analyses demonstrate that ERG S283 phosphorylation in CD34+ cord blood cells induces gene expression signatures more closely associated with HSCs than with lineage committed progenitors. Additionally, interrogation of a gene set derived from ETP ALL cells compared to non-ETP ALLs also showed enrichment in ERG S283D cells, indicating a leukaemogenic signature driven by ERG S283 phosphorylation (NES 1.634, p<0.01, Figure 4-8).

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Figure 4-8 GSEA of HSC and leukaemia gene signatures up-regulated by ERG

S283 phosphomimetic mutant in CD34+ HSPC.

GSEA analysis of genes that were up- (red) or down- (blue) regulated in CD34+ ERG

S283D over-expressing cells compared with ERG WT cells (Expt2 and 3). Sig, signature; SCE, stem cell enhancer; GMP, granulocyte-macrophage progenitor; ETP, early T-cell precursor; NES, normalised enrichment score.

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Apart from the up-regulation in stem cell / leukaemia-associated pathways, the publicly available gene signature packages including the HALLMARK and the

Oncogenic Pathway packages from the MSigDB (Subramanian et al., 2005) website were also used to assess enrichment. These pathways are considered enriched during malignant transformation. The epithelial-mesenchymal transition pathway (NES 2.416, p<0.001), inflammatory response pathway (NES 2.182, p<0.001) and the tumour necrosis factor alpha (TNFα) pathway (NES 1.998, p<0.001) were found up-regulated by ERG S283D over-expression in comparison with ERG WT (Figure 4-9). During embryogenesis, one of the fundamental processes regulated by ERG is the epithelial- mesenchymal transition (Saunders and McClay, 2014). TNFα is a cytokine involved in systemic inflammation by regulating the activity of immune cells. It is able to induce fever, apoptotic cell death, cachexia and inflammation (Locksley et al., 2001).

Dysregulation of TNF production has been implicated in a variety of human diseases including leukaemia (Kagoya et al., 2014; Locksley et al., 2001).

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Figure 4-9 GSEA of oncogenic signatures up-regulated by ERG S283 phosphomimetic mutant in CD34+ HSPC.

GSEA analysis of genes that were up- (red) or down- (blue) regulated in CD34+ ERG

S283D over-expressing cells compared with ERG WT cells (Expt2 and 3). TNF, tumour necrosis factor; NES, normalised enrichment score.

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Interestingly, GSEA analysis also revealed up-regulation of the KRAS (NES

1.933, p<0.001) and the MEK (NES 1.665, p<0.01) pathways by ERG S283D over- expression (Figure 4-10). The RAS-MEK pathway is known to associate with oncogenic activities (Friday and Adjei, 2008; Graham and Olson, 2007; Saxena et al.,

2008). Induction of this kinase pathway by ERG S283D over-expression indicates the involvement of ERG S283 phosphorylation in oncogenesis.

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Figure 4-10 Elevated RAS/MEK signalling by ERG S283 phosphomimetic mutant in CD34+ HSPC.

GSEA analysis of genes that were up- (red) or down- (blue) regulated in CD34+ ERG

S283D over-expressing cells compared with ERG WT cells (Expt2 and 3). NES, normalised enrichment score.

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Taken together, these findings suggest that ERG S283 phosphorylation in HSPC drives a gene expression signature associated with stem cell and oncogenic pathways including the RAS-MEK-ERK oncogenic signalling pathway.

4.6. Chapter summary

The results in this chapter describe the establishment of a growth promoting phenotype induced by WT ERG over-expression which is further enhanced by the ERG

S283 phosphomimetic mutant in healthy HSPC. In cytokine-driven cultures both ERG

S283 mutants were capable of inducing clonal expansion of transduced cells, indicating that S283 phosphorylation is dispensable for basal ERG transcription factor activity.

High expression of the S283 phosphomimetic mutant on the other hand resulted in the induction of a gene expression signature that is present in normal HSCs and leukaemic cells, contributing to the observed prolongation of CD34+ culture duration, maintenance of primitive CD34+ cells throughout culture and increased clonogenicity.

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Chapter 5. ERG pS283 is Modulated by the MAPK/ERK2 Pathway

In this chapter, I examined whether ERK2, a major kinase downstream of the

RAS-MAPK pathway, directly phosphorylates ERG S283.

5.1. MAPK/ERK2 phosphorylates ERG S283 in vitro

To delineate the upstream pathway mediating ERG S283 phosphorylation, instead of doing large-scaled kinase screening, the ERG peptide sequence was closely examined to locate putative kinase docking sites for a more feasible and rational identification of potential candidate kinase(s). A proline-directed serine/threonine

(S/TP) is the minimal consensus sequence for phosphorylation by all MAPKs (Roux and Blenis, 2004). Being a proline-directed serine, ERG S283 is likely to be a direct

MAPK target.

MAPKs have been reported to physically interact with their substrates through the DEF domain. Among the three MAPK family members (ERK, JNK, p38), this motif shows preference for ERK docking compared to JNK or p38 (Jacobs et al., 1999) and is found in only seven ETS factors including ERG (Selvaraj et al., 2015). The consensus

DEF domain sequence FxFP (FIFP in ERG) is located between the PNT and ETS domain of ERG, sitting in close proximity to S283, and is encoded within ERG exon12

(Figure 5-1). Consisting of 72 nucleotides and encoding 24 amino acids, ERG exon12 is

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Huang: Chapter 5. MAPK/ERK2 Phosphorylates ERG S283 spliced in ERG2 while remains intact in ERG3 - the major haematopoietic isoform. I therefore hypothesised that ERG-Δexon12 deletion mutant lacking the ERK docking

DEF domain would exhibit reduced S283 phosphorylation compared to full length ERG upon in vitro MAPK treatment.

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Figure 5-1 ERG isoform 3 harbours a classic MAPK docking site.

Schematic showing the putative MAPK docking motif DEF domain harboured within

ERG3 exon12 sequence. The peptide sequence encoded by exon12 is highlighted. The starting and ending amino acids of the domains are numbered underneath. PNT,

Pointed; ETS, E-twenty six.

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To confirm that ERK phosphorylates ERG S283 in vitro, a kinase assay was performed using ERK1/2 on affinity purified GST tagged WT ERG protein. The treated samples were then subjected to SDS-PAGE for in-gel trypsin digestion, followed by MS analysis without phosphoenrichment for phosphorylation quantification at S283. The percentage of S283 phosphorylation was calculated by extracting the signal intensities of both phosphorylated and unphosphorylated versions of the S283-containing peptide

(Figure 5-2A). It should be noted that generally MS should not be used to directly compare the abundance of two different peptides (e.g. unphosphorylated and phosphorylated versions) since the ionisation efficiency is likely to be affected by the presence of the phosphate group. However, MS is still valid for the comparison of the relative amount of phosphorylation across samples using an estimate of the percentage of phosphorylated residues. Under the same treatment conditions (30 min at 37°C),

ERK2 phosphorylated approximately 9.5% of ERG S283, while the phosphorylation level from ERK1 treatment was minimal (approximately 0.02%) (Figure 5-2B). From these data, I concluded that ERK2 was capable of phosphorylating ERG S283 in vitro.

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Figure 5-2 MAPK/ERK2 phosphorylates ERG S283 in vitro.

A kinase reaction (30 min treatment) was performed using ERK1 or ERK2 on purified

WT GST-ERG, followed by MS to quantify the % phosphorylation. (A) Signal intensities of the phosphorylated/nonphosphorylated peptides containing S283 from kinase treated ERG were extracted from the corresponding mass spectra, shown as area under peak (AA). (B) Bar graph showing the percentage of phosphorylated S283 in

ERG from indicated kinase assays.

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To examine whether the DEF domain plays a role in ERK2 docking and affects

ERG S283 phosphorylation, an ERG exon12 deletion mutant (ERG-∆exon12) was constructed and affinity purified via a GST tag. In vitro ERK2 assay on both full length and deletion mutant ERG constructs revealed that ERK2 strongly phosphorylated S283 on WT ERG (56% phosphorylation) while this phosphorylation was reduced more than

50% (21% phosphorylation) in the absence of the DEF domain (Figure 5-3A). To account for the variation in kinase efficiency across independent reactions, an internal control of MBP was included in the same reaction. MBP contains a wide range of kinase motifs and can be strongly phosphorylated by most kinases. By plotting the phosphorylated fraction of three randomly picked peptides from MBP, phosphorylation efficiency was shown to be comparable in both samples (Figure 5-3B).

It is worth noting that ERG S88 was hardly phosphorylated by ERK2 (Figure 5-

3A). This is not surprising, given that ERG pS88 is primarily located in the cytoplasm of MOLT-4 cells (Figure 3-3) where ERK is not active (Mutalik and Venkatesh, 2006).

Abundance of ERG pS88 in haematopoietic cells detected in this study is likely attributed to a different kinase. S103 from WT ERG was weakly phosphorylated by

ERK2 (Figure 5-3A), which was in line with its low abundance in endogenous ERG from haematopoietic cells. ERG S222 got strongly phosphorylated even after DEF domain deletion (Figure 5-3A), indicating that ERK2 was responsible for ERG S222 phosphorylation; however, its action was more likely to be independent of the DEF domain. As the detection of S55 requires chymotrypsin digestion, this site was not examined in this experiment.

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1 5 0 W T E R G

n E R G - e xo n 1 2

t a

l 1 0 0

y r

o ****

p s

o 5 0

8 3 2 3 8 0 2 8 S 1 2 2 S S S

B 1 5 0 W T E R G

E R G - e xo n 1 2

t a

l 1 0 0

p s

o 5 0

T R . .G . R K R P A T G V Q M I S P .N P S K P G P .S .T R R

Figure 5-3 ERG S283 is phosphorylated by ERK2 in vitro via the DEF domain.

(A) Bar graph comparing the percentage of phosphorylation across different sites between WT ERG and ERG exon12 deletion mutant (ERG-∆exon12) in in vitro ERK2 kinase assay. Error bars represent SD for all peptide spectral matches quantified in this experiment (n=3). ****p<0.0001. (B) Phosphorylation of selected peptides

(K.NIVTPR.T, R.TPPPSQGK.G and R.SGSPMAR.R) of myelin basic protein (MBP) to indicate equivalent kinase phosphorylating efficiency across separate reactions. Error bars represent SD calculated from three independent experiments.

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5.2. MAPK/ERK phosphorylates ERG S283 in vivo

To clarify the involvement of the RAS-MAPK signalling pathway in ERG S283 phosphorylation, I next examined whether ERG S283 becomes phosphorylated through the activation of ERK.

5.2.1. MAPK/ERK phosphorylates ERG S283 in leukaemic cell lines

To elucidate the effect of in vivo ERK activation in leukaemic cells, MOLT-4 T-

ALL cells were treated with PMA with or without a pre-treatment of ERK inhibitor.

PMA is a broadly used MEK/ERK activator in cell culture which increases phosphorylation on, but not limited to, ERK substrates. By combining PMA treatment with the MEK/ERK inhibitor U0126, specific ERK targets could be uncovered from the change in their phosphorylation pattern.

In this experiment, serum starved MOLT-4 cells were treated with U0126 (10

µM) or PMA (100 nM) as single agents, or in a combination with U0126 being the pre- treatment (Figure 5-4). The experiment was designed using a SILAC-based method

(Ong et al., 2002), where the unlabelled normal cells were drug-treated and phosphorylation level analysed simultaneously with the heavy isotope-labelled vehicle- treated (DMSO) cell lysate (Figure 5-4). A drug-treated/vehicle ratio above the x-axis on a log scale therefore implies increased phosphorylation upon treatment and vice versa.

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Figure 5-4 Experimental procedure of MEK inhibition/activation on MOLT-4 cells.

MOLT-4 cells were cultured in SILAC medium (blue) as the ‘untreated’ condition.

MOLT-4 cells in normal medium (pink) were serum starved, followed by treatment with either U0126 (10 µM) or PMA (100 nM). A fraction of the U0126-treated cells were further treated with PMA (100 nM). Each treated condition was mixed with the vehicle-treated (DMSO) SILAC MOLT-4 cells for a simultaneous process of cell lysis, immunoprecipitation (IP), phosphoenrichment and mass spectrometry (MS) analysis.

The mass spectra give peptide signals from both ‘light’ (unlabelled MOLT-4) and

‘heavy’ (SILAC MOLT-4) cultures for quantification. 179

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As shown in Figure 5-5, ERG S283 in MOLT-4 cells had reduced phosphorylation after MEK/ERK inhibitor U0126 treatment and elevated phosphorylation after ERK activator PMA treatment. The reduction in phosphorylation by U0126 was irreversible upon subsequent PMA treatment, suggesting the inhibition was specifically applied to ERK, which served as the only kinase responsible for this phosphorylation.

Various responses were observed for the other ERG phosphorylation sites.

Although ERG S222 had reduced phosphorylation following MEK/ERK inhibition and enhanced phosphorylation after PMA treatment, the inhibitory effect was completely reversible as the phosphorylation level on this residue was restored to the original level in the combination treatment group (Figure 5-5). Given the fact that U0126 is a specific and irreversible inhibitor of MEK/ERK and PMA is capable of activating many other kinases, the reduction in S222 phosphorylation was more likely due to the preceding serum starvation and the elevated phosphorylation was more likely contributed by another PMA-activated kinase pathway. Nevertheless, ERK should be, at least in part, active in ERG S222 phosphorylation in MOLT-4 cells, as the U0126+PMA treated condition had a much lower phosphorylation level on S222 compared to the PMA only condition (Figure 5-5). In other words, U0126 inhibited this phosphorylation to some extent, which was consistent with the previous finding that S222 could be heavily phosphorylated by ERK2 in vitro (Figure 5-3A).

Not surprisingly, ERG S88 phosphorylation level in MOLT-4 cells was not affected by either U0126 or PMA treatment, which also agreed with the result in Figure

5-3A that S88 was not an ERK substrate. Due to the low abundance of endogenously 180

Huang: Chapter 5. MAPK/ERK2 Phosphorylates ERG S283 phosphorylated ERG S103, this site was below the detection threshold in this experiment and was therefore not plotted. S55 phosphorylation required chymotrypsin digestion which was not performed.

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Figure 5-5 ERG S283 phosphorylation is specifically inhibited by MEK/ERK inhibitor in vivo.

The responses of three phosphoserines (S88, S222 and S283) in MOLT-4 T-ALL cells were assessed following treatment with U0126 (10 µM), PMA (100 nM) or PMA with prior U0126 treatment. SILAC MOLT-4 cells were treated with matching concentrations of DMSO as the vehicle control group. The level of phosphorylation was quantified by MS and plotted on a log10 scale as a ratio of treated/vehicle, with a ratio>0 being elevated phosphorylation and a ratio<0 being reduced phosphorylation upon treatment.

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The activities of the three MAPK members (ERK1/2, JNK, p38) on ERG S283 phosphorylation were examined using three leukaemic cell lines (MOLT-4, KG-1, ME-

1). Besides ERK inhibition/activation by U0126/PMA, serum starved cells were treated with SP600125 (50 µM)/anisomycin (25 µg/ml) for JNK inhibition/activation and

SB203580 (10 µM)/sorbitol (500 mM) for p38 inhibition/activation. The level of ERG

S283 phosphorylation was determined by immunoblotting using the customised ERG pS283 antibody (Figure 5-6), and specific kinase-substrate relationship was indicated by reduced phosphorylation in the inhibitor and inhibitor + activator treated samples (lane

3 and 4), and elevated phosphorylation in the activator treated samples (lane 5).

In Figure 5-6, ERG in MOLT-4 cells was specifically phosphorylated on S283 via both JNK and MEK/ERK pathways, as it showed low level of phosphorylation in both the inhibitor only and the inhibitor + activator conditions (lane 3 and 4), while

S283 phosphorylation intensified in the activator-treated conditions (lane 5). A similar pattern was observed for ME-1 cells, while it should be noted there seemed to be a slight restoration of phosphorylation by PMA following U0126 inhibition, which may be an indication of the action of other kinase(s) regulating this modification in ME-1 cells. In KG-1 cells, ERG S283 phosphorylation was only mediated by MEK/ERK, as there was no observable change in phosphorylation level when subjected to JNK and p38 manipulation.

In summary, ERK was the only MAPK capable of regulating ERG S283 phosphorylation in all three leukaemic cell lines. This finding is consistent with a recently published study which reported that unlike most ETS factors, ERG shows

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Figure 5-6 ERG S283 phosphorylation is specifically inhibited by MEK/ERK inhibitor in leukaemic cell lines.

The level of ERG S283 phosphorylation in three leukaemic cell lines (MOLT-4, KG-1 and ME-1) was immunoblotted following MAPK inhibition/activation. Serum starved cells were treated with SP600125 (50 µM)/anisomycin (25 µg/ml) for JNK inhibition/activation, SB203580 (10 µM)/sorbitol (500 mM) for p38 inhibition/activation, U0126 (10 µM)/PMA (100 nM) for MEK/ERK inhibition/activation. The levels of total endogenous ERG and β-actin were also shown.

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5.2.2. MAPK/ERK phosphorylates ERG S283 in primary leukaemic xenograft cells

The response of ERG S283 to in vivo MEK/ERK inhibition/activation was further tested using two primary ETP ALL xenograft samples (ETP1 and ETP2) with high levels of ERG expression and pS283 (Figure 3-9). A similar pattern to the leukaemic cell lines was observed that both ETP ALLs had irreversible inhibition of

S283 phosphorylation by the MEK/ERK inhibitor U0126, while ERK activator PMA enhanced this event (Figure 5-7).

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Figure 5-7 ERG S283 phosphorylation is specifically inhibited by MEK/ERK inhibitor in primary ETP ALL xenograft cells.

The response of ERG pS283 in two ETP ALL xenografts (ETP1, ETP2) was assessed following treatment with MEK/ERK inhibitor U0126 (10 µM) and/or activator PMA

(100 nM). The levels of ERG pS283, total ERG and β-actin were measured by immunoblotting.

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5.3. ERG pS283 level correlates with ERK activity in haematopoietic cells

The endogenous correlation between the level of active ERK (pERK) and ERG pS283 was determined by immunoblotting using a panel of leukaemic xenograft cells and leukaemic cell lines in comparison with healthy CD34+ HSPC. In most samples, there was a strong correlation between the level of pERK and ERG pS283, suggesting a role of ERK in ERG S283 phosphorylation regulation (Figure 5-8, Figure S6). Absence of ERK1/2 activity in CD34+ HSPC (Figure 5-8) is consistent with the findings in previous literatures (Bonati et al., 2002). While the ETP ALL xenografts were consistently high in ERG S283 phosphorylation (Figure 5-8, Figure S6), the AML xenografts showed various levels of this modification (Figure 5-8). However, without sufficient patient information on the xenograft origin, no causal links can be established at this stage between ERG pS283 level and survival. Regarding ERG pS283 level in

CD34+ HSPC and MOLT-4 cells, although there seem to be discrepancies between the western blotting band intensity (Figure 5-8) and the MS results (Figure 3-4), the % phosphorylation on S283 was still higher in MOLT-4 cells as it had less total ERG

(Figure 5-8).

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Figure 5-8 ERG pS283 level correlates with active ERK in haematopoietic cells.

Immunoblotting showing the endogenous levels of ERG pS283, total ERG, active

ERK1/2 (pERK1/2) and β-actin across a panel of primary ETP ALL xenografts, AML xenografts, primary CD34+ HSPC and leukaemic cell lines (MOLT-4, KG-1 and ME-

1).

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5.4. ERG pS283 inhibition does not impact on leukaemic cell viability

To unravel the importance of ERG pS283 in terms of cell survival, three ETP

ALL xenografts (ETP1, ETP2 and ETP3) were paired with three non-ETP ALL xenografts (ALL8, ALL16 and ALL44) with low levels of ERG pS283 (Figure 3-9). I hypothesised that after treated with MEK/ERK inhibitor U0126, leukaemic cells with high ERG pS283 might show increased cell apoptosis if survival of these leukaemic cells were dependent on this phosphorylation event, while the survival of cells with minimal ERG pS283 should be affected to a much lesser extent.

The tested U0126 concentrations were 0.0001 µM, 0.001 µM, 0.01 µM, 0.1 µM,

1 µM, 10 µM and 50 µM. The cells were exposed to either U0126 or matching concentrations of DMSO for a total of 72 hr before the viability was determined. The % survival relative to the DMSO treated group was plotted. Unfortunately, no difference in cell viability was observed between the non-ETP ALL (red lines) and the ETP ALL

(blue lines) cells (Figure 5-9), suggesting that cell survival was not dependent on

MEK/ERK-mediated phosphorylation in general. It should be noted that ideally the % viable cells should be >75% prior to treatment, however, some xenografts (e.g. ETP3) showed poor viability post-thawing (Figure 5-9).

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l o

r A L L 8 (6 8 .5 % )

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o t 0 0 .0 0 0 1 0 .0 0 1 0 .0 1 0 .1 1 1 0 1 0 0 U 0 1 2 6 c o n c e n tr a tio n [ M ]

Figure 5-9 MEK/ERK inhibition is non-lethal on primary ALL cells.

Three non-ETP ALL (ALL 8, ALL16 and ALL44) and three ETP ALL (ETP1, ETP2 and ETP3) xenograft samples were treated with MEK/ERK inhibitor U0126 (0.0001,

0.001, 0.01, 0.1, 1, 10, 50 µM) for 72 hr and viability measured by AlamarBlue assay.

The data are the % survival relative to the vehicle (DMSO) treated control. The % on the legend represents the % viable cells prior to treatment. The top and bottom graphs show results of biological replicates for each xenograft.

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5.5. Reduced clonogenicity by ERK inhibition in leukaemic cells

The clonogenicity of two leukaemic cell lines – KG-1 and ME-1, both with high level of ERG pS283 (Figure 5-8) – was assessed in the presence of MEK inhibitor

U0126 (10 µM) in comparison to the response of U0126 (10 µM) treated CD34+ HSPC.

The cells were pre-treated with U0126 (10µM) to remove ERG S283 phosphorylation prior to seeding into CFU assays in the presence of 10 µM U0126. After 14 days, all three cell types showed significantly reduced colony formation by the MEK inhibitor

U0126 treatment compared to the vehicle control group (CD34+ HSPC, p=0.033; KG-1, p=0.001; ME-1, p=0.008). Regardless of statistical significance being observed for all three cell types, the leukaemic cell lines with high ERG pS283 are more dependent on pS283 as they exhibited much greater reduction in colony numbers than the HSPC with minimal level of phosphorylation at ERG S283 (Figure 5-10). Also, the impact of MEK inhibition on HSPCs in the absence of ERG pS283 is not surprising, given the

MAPK/ERK pathway has indispensable physiological functions particularly proliferation (Campbell, 2014).

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p = 0 .0 3 3 v e h ic le 1 5 0 U 0 1 2 6

e p = 0 .0 0 8

t 1 0 0 a

l p = 0 .0 0 1

F 5 0 * * C * * *

0 C D 3 4 + K G -1 M E -1

Figure 5-10 MEK/ERK inhibition results in reduced colony formation by leukaemic cells with high ERG pS283.

Bar graph shows the colony counts of CD34+ HSPC, KG-1 and ME-1 cells with seeding densities of 5×102, 3×103 and 2.5×104 cells/plate, respectively, treated with vehicle (0.1% DMSO) or U0126 (10 µM in 0.1% DMSO). Error bars represents SD calculated from triplicate measurements. *p<0.05, **p<0.01, ***p<0.001. The exact p- values are labelled accordingly.

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5.6. MEK inhibition alters heptad in vivo DNA binding

Given that ERK-mediated ERG pS283 potentiates the proliferation and colony formation of HSPCs, I examined how in vivo DNA binding of the heptad is affected following MEK inhibition. For consistency with the result in section 5.5, KG-1 AML cells were used. Cells were treated with the MEK inhibitor U0126 (10 µM) or DMSO

(0.2%) and subjected to ChIP for each member of the heptad complex (ERG, SCL,

RUNX1, LMO2, LYL1, FLI1, GATA2) for assessment of in vivo DNA binding.

Binding was assessed at the ERG +85 enhancer which is active and bound by the heptad in KG-1 cells (Diffner et al., 2013).

MEK inhibition resulted in increased enrichment of ERG, RUNX1, and LMO2 at the ERG +85 enhancer, whereas FLI1 binding was decreased (Figure 5-11). GATA2 exhibited strong binding at ERG +85 enhancer which was not affected by MEK inhibition (Figure 5-11). SCL and LYL1 binding was present at low levels and showed minor variation after treatment (Figure 5-11). Taken together, these data show that

MEK inhibition results in variations to transcription factor binding at the ERG +85 enhancer.

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G 1 2 1 1 2 G L L I A Ig C X O L R N Y F T S M L E U L A R G

Figure 5-11 MEK inhibition alters heptad binding at ERG +85 enhancer in KG-1 cells. Chromatin immunoprecipitation (ChIP) assay measured binding of individual heptad factors (ERG, SCL, RUNX1, LMO2, LYL1, FLI1, GATA2) to the ERG +85 enhancer in vehicle (0.2% DMSO) or U0126 (10 µM) treated KG-1 cells. Enrichment was normalised to corresponding IgG control. Error bars were calculated from duplicate qRT-PCR reactions.

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5.7. Chapter summary

Together, these results show that ERG S283 phosphorylation is mediated by

MAPK/ERK. ERK1/2 translocate into the nucleus upon activation to phosphorylate nuclear substrates (Mutalik and Venkatesh, 2006), which is consistent with my findings in section 3.2 that ERG S283 is primarily localised in the nucleus. ERG S283 is directly phosphorylated in vitro by MAPK/ERK2 via its DEF domain which lies in close proximity to S283. As ERG2 differs to ERG3 by lacking the DEF domain, this result also explains why in previous studies, ERG S283 phosphorylation was not detected in cell types with ERG2 being the predominant ERG isoform (Huttlin et al., 2010;

Singareddy et al., 2013). Findings from in vivo kinase inhibition assays are consistent with the in vitro results, and the level of ERG pS283 correlates with active ERK level in both primary haematopoietic cells and leukaemic cell lines. It was not surprising that

MEK inhibition also led to a reduction in colony formation by HSPC lacking ERG pS283, given the RAS-MEK-ERK pathway plays a key role in cell proliferation

(Campbell, 2014; Drosten et al., 2014). Yet promisingly, the leukaemic cell lines with high ERG pS283 experienced even greater reduction in colony numbers, offering a potential therapeutic window for clinical translation. Leukaemia patients may be stratified based on their cellular level of ERG pS283 for the administration of MEK inhibitor as a treatment regimen.

Identification of the MAPK/ERK pathway being the upstream regulator of ERG

S283 phosphorylation complements the up-regulated RAS-MEK gene signature driven by ERG S283 phosphomimetic mutant in ERG transduced HSPCs, further suggesting

ERG S283 phosphorylation was a significant contributor to leukaemogenesis via the

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ERK shares a preferred phosphorylation motif with CDK5 (Hu et al., 2014). Without performing a more comprehensive kinase screening, we cannot rule out the possibility that ERG S283 is also phosphorylated by other kinases such as CDK5. However, the current findings are particularly intriguing because the RAS-MAPK signalling cascade is known to play a central role in oncogenesis (Malumbres and Barbacid, 2003; Saxena et al., 2008).

Two functional experiments were performed aiming to address the response of leukaemic cells upon depleting MEK activity. While colony formation was reduced by

MEK inhibition as expected, ERG DNA binding was increased at an ERG-responsive enhancer element correlated with a leukaemogenic gene signature (Thoms et al., 2011).

This inconsistency did not contradict the leukaemogenic potential of ERG pS283; rather, it suggests that assessment of DNA binding at only one site cannot represent the overall binding profile or predict the final read-out of cell behaviour. The dramatic increase in LMO2 binding following MEK inhibition is also of particular interest given its involvement in leukaemia development (McCormack et al., 2010). This may be consequent from altered heptad structure or direct DNA binding of LMO2. Changes in

RUNX1 and FLI1 binding, although to a lesser extent, also highlight that inhibiting a regulatory pathway such as MEK-ERK to deplete ERG pS283 will have unpredictable and undesirable off-target effects due to its involvement a broad spectrum of cellular activities. Therefore, future drug discovery will instead need to focus on designing inhibitors that specifically target the ERK-mediated phosphorylation of ERG S283.

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Chapter 6. Investigation of the Impact of pS283 on ERG Stability, Nuclear Localisation, DNA Binding and Transcription Initiation

To elucidate the mechanism by which S283 phosphorylation alters ERG activity,

I performed a range of mutagenesis assays using WT and S283 mutant ERG constructs to assess its protein stability, nuclear localisation, in vitro and in vivo DNA binding and transcription activation.

6.1. S283 phosphorylation does not affect ERG protein stability

The rate of degradation of a transcription factor could affect downstream target gene regulation and ultimately impact on the cellular phenotype. To assess the stability of ERG upon S283 mutation, WT and S283 mutant pMIG+ ERG constructs were expressed in HEK293T cells and ERG protein level assayed following the addition of cycloheximide (20 µg/ml), a protein synthesis inhibitor. Expressed ERG degraded over a period of five days and the cells were harvested at eight designated time points (t=0, 7,

26, 50, 56, 72, 97, 120 hr). The amount of ERG was quantified by immunoblotting

(Figure 6-1A, B) and plotted for half-life calculation (Figure 6-1C). The half-lives of

WT ERG, S283A ERG and S283D ERG were 38.5 hr, 38.5 hr and 36.5 hr, respectively

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(Figure 6-1D), leading me to conclude that S283 phosphorylation per se does not affect

ERG protein stability.

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Figure 6-1 ERG S283 phosphorylation does not affect ERG protein stability.

ERG half-life was measured by protein degradation assay. HEK293T cells expressing pMIG+ ERG (2.5 µg/well) were treated with 20 µg/ml cycloheximide at 48 hr post- transfection and harvested at indicated time points post-treatment. (A) Protein amount

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Huang: Chapter 6. Mechanistic Study of ERG pS283 was measured by immunoblotting and then quantified by densitometry. Blot shown was a representative from three independent experiments. (B) Quantitative data for the western blot described in A. (C) After normalising to β-actin, ERG level at each time point was calculated as a percentage of it at t=0 and plotted into an exponential decay curve. (D) Equations for line of best fit and R2 values were generated. The half-lives were calculated from the equations.

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6.2. S283 phosphorylation does not affect ERG nuclear localisation

To visualise the subcellular localisation of WT and S283 mutant ERG protein, immunofluorescence was performed on MOLT-4 cells transduced with pMIG+ HA-

ERG constructs using an anti-HA antibody. The HA tag allowed separation of the exogenously over-expressed ERG from endogenous ERG. Confocal immunofluorescence images showed that all three ERG constructs (WT, S283A,

S283D) were present primarily in the nuclei of MOLT-4 cells, with no difference in distribution observed across the variants (Figure 6-2A). Co-expressed GFP served as a marker for the transduced population and assisted locating the HA-ERG expressing cells in the ERG positive conditions (Figure 6-2A).

Cell fractionation and immunoblotting was performed in conjunction with immunofluorescence using the same cells. The samples were blotted for HA-ERG,

DNA topoisomerase 1 (nuclear protein) and β-actin (Figure 6-2B). Consistent with the result in Figure 6-2A and section 3.2 (Figure S2), ERG resides primarily in the nuclei of

MOLT-4 cells.

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Figure 6-2 ERG S283 phosphorylation does not affect ERG nuclear localisation.

(A) Transduced MOLT-4 cells expressing pMIG+ or pMIG+ HA-ERG (WT, S283A,

S283D) were stained for the nuclei (DAPI, blue), GFP (green) and HA-ERG (red). The exposure was adjusted using the corresponding negative controls (Mock, GFP negative; pMIG+, HA negative). The regions shown were representatives of 10 sections. (B) The cytoplasmic (C) and nuclear (N) fractions of transduced MOLT-4 cells expressing HA-

ERG were immunoblotted for HA-ERG, DNA topoisomerase 1 (TOP1) and β-actin.

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6.3. S283 phosphorylation does not affect ERG in vitro DNA binding

To assess ERG direct binding to DNA in an in vitro setting, GST-tagged full length ERG (WT and S283D mutant) was affinity purified and bound to a DNA segment (5’-AGGACCGGAAGTAACT-3’) containing the consensus ETS motif (5’-

GGAA/T-3’) in an FP experiment. FP is a quantitative, solution-based, homogeneous assay format which measures the rate of molecular rotation of a fluorescently labelled ligand and allows rapid and quantitative analysis of diverse molecular interactions and enzyme activities in vitro (Yan et al., 2005). FP is related to the molecular size and thus the differing rotational properties of small versus large molecules; the smaller the size and the faster the rotation, the lower the FP value (Heyduk et al., 1996). Since full length GST-tagged ERG has a relatively high molecular mass (approximately 80 kDa), its binding to a small fluorescently labelled DNA segment will result in a significant change in FP values.

In this experiment, comparable binding affinity of ERG WT (KD = 23 nM) and

S283D (KD = 22 nM) was observed (Figure 6-3, n=2). GST-ERG purification and the

FP assay were performed by A. Boulton and C. Schmidt (Department of Chemistry,

University of Virginia, U.S.A.).

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Figure 6-3 Representative FP isotherms of ERG binding to DNA.

Steady-state fluorescence anisotropy of DNA (5’-AGGACCGGAAGTAACT-3’) extrinsically labelled with a Texas Red fluorophore on the 5' end bound by various concentrations of full length GST-ERG (WT/S283D). The sigmoidal curve is the best- fit binding isotherm with KD of 22-24 nM. The experiment was performed in duplicates

(representative plots shown) by A. Boulton and C. Schmidt (Department of Chemistry,

University of Virginia, U.S.A.).

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6.4. S283 phosphorylation increases ERG in vivo DNA binding

Based on the findings in section 6.1 and 6.2, it was considered that all three ERG variants have comparable access to chromatin in the nucleus. Although in vitro FP assay showed no differential DNA binding of ERG to the consensus ETS sequence, change in

DNA binding can still be expected from a physiological setting. Therefore, I then examined ERG binding to DNA in MOLT-4 cells using the ChIP assay, which enables illumination of the effect of ERG S283 phosphorylation on its in vivo DNA binding.

In a genome wide survey of the ETS factor SCL binding sites, Wilson et al. showed that the ERG +85 enhancer was strongly bound by SCL and was active in foetal liver blood cells (Wilson et al., 2010). This enhancer contains sequence blocks that are highly conserved in mammalian cells including ETS, GATA and E-Box consensus motifs, allowing the binding of multiple transcriptional network partners which drives

ERG expression (Thoms et al., 2011). Chromatin accessibility profiles across the ERG loci showed the ERG +85 enhancer to be in an active configuration in MOLT-4 cells

(Thoms et al., 2011). Another enhancer, the hHEX+1 enhancer sitting 1 kb downstream of the HEX/PRH gene, is also strongly bound by ERG in MOLT-4 cells (Oram et al.,

2010). This enhancer was initially identified as a key mediator of early progenitor expansion in T-ALL (Donaldson et al., 2005) and later proven to play an important role in thymocyte self-renewal in leukaemic mouse models (McCormack et al., 2010).

In the current study, the chromatin of transduced MOLT-4 T-ALL cells over- expressing HA-ERG (WT, S283A, S283D, ∆ETS) was immunoprecipitated via the HA tag on DNA-bound ERG in order to exclude endogenous ERG binding. Binding at two

ERG-responsive regions in MOLT-4 cells were characterised – the ERG +85 enhancer 206

Huang: Chapter 6. Mechanistic Study of ERG pS283 and the hHEX +1 enhancer. ERG enrichment at both sites was calculated after normalisation to the corresponding IgG controls and plotted in comparison to the binding at a region near the LMO2 locus that is not accessible or bound by ERG in haematopoietic cells (Beck et al., 2013; Oram et al., 2010) (Figure 6-4A). Both enhancers showed the same enrichment pattern. While ERG S283A exhibited only a minor decrease in binding compared to WT ERG, the enhanced binding by ERG S283D compared to ERG S283A is promisingly interesting (Figure 6-4A). The level of ERG protein expression in the same transduced MOLT-4 cells was also determined by immunoblotting to take the amount of ERG available for DNA interaction into consideration. In this experiment, ERG WT was expressed to a lesser extent compared to the S283 mutants (Figure 6-4B). If further normalised to protein expression, the difference in enrichment between ERG WT and ERG S283D is alleviated, while the difference between ERG WT and ERG S283A is increased (data not shown). This is consistent with ERG S283 being largely phosphorylated in MOLT-4 cells. In other words, ERG WT should behave more closely to the phosphomimetic mutant, while difference is still expected between the opposite S283 mutants. As expected, enrichment by the ETS domain deletion mutant ERG (ERG-∆ETS) is absent on both sites (Figure 6-

4A), consistent with the fact that ERG interacts with DNA via its ETS domain (Siddique et al., 1993).

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Figure 6-4 ERG S283 phosphorylation increases ERG in vivo DNA binding.

(A) Chromatin immunoprecipitation (ChIP) assay measured HA-ERG binding to the

ERG +85 enhancer and the hHEX+1 enhancer in MOLT-4 cells. Binding at a region near the LMO2 locus served as an unbound negative control and ERG ETS deletion mutant (ERG-∆ETS) served as an ERG-positive but non-DNA binding condition.

Enrichment was normalised to corresponding IgG control. Error bars were calculated from duplicate qRT-PCR reactions. (B) Expression of ERG in transduced MOLT-4 cells used in the ChIP assay determined by immunoblotting.

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The ChIP assay is a commonly used approach to evaluate in vivo DNA binding and is superior to in vitro assays such as the electromobility shift assay (EMSA) and the

FP assay. The in vitro assays use purified proteins and DNA segments to measure the affinity of binding in an artificial setting, while ChIP measures in vivo enrichment of the transcription factor at specific target DNA sites by quantitative PCR. Thus, the ChIP assay takes into account the cellular context when assessing transcription factor binding.

In particular, the target DNA site is present in a more native state with regards to epigenetic modifications and accessibility and binding of a transcription factor is evaluated in context of other facilitating proteins that make up a transcriptional complex. However, a limitation of the ChIP assay that should not be overlooked is that enrichment at only a few known binding sites could be assessed. For a more comprehensive evaluation of ERG binding to DNA, ChIP sequencing is performed and is described in the following section.

6.5. Differential DNA binding by ERG S283 phosphomimetic mutant in HSPCs

Unlike ChIP, ChIP sequencing has the advantage of uncovering genome-wide binding of the protein of interest, including potential identification of previously unknown binding sites. Compared to cell lines, primary cells possess a more native cellular context that is capable of exhibiting a phenotype in response to changes in the internal/external environment. As over-expression of ERG S283 phosphomimetic mutant induced a proliferative phenotype in HSPC, and ERG WT is hardly phosphorylated in these cells based on the MS results, genome-wide DNA binding of

ERG S283D is assessed in comparison to ERG WT in HSPC using ChIP sequencing.

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pMIG+ ERG transduced human cord blood cells at week 0 (Expt4) were sorted for the GFP+ population, bound chromatin immunoprecipitated via ERG and ChIP sequenced. The resulting ERG-bound DNA sequences from the ERG S283D condition were compared to the ones of ERG WT to elucidate differentially bound DNA regions.

In this study, the ChIP sequencing tracks showed high background level of noise signals, which interfered with the peak calling process. The data quality is usually affected by factors like the efficiency of chromatin-protein crosslinking and/or immunoprecipitation in a certain experiment. Therefore, the binding was instead assessed on direct ERG-bound DNA targets (total 4803 sites) previously identified by

Beck et al. who did ChIP sequencing analysis by immunoprecipitating endogenous

ERG using human CD34+ mobilised peripheral blood cells (>1×108 cells) collected from a healthy donor (Beck et al., 2013). The data from Beck et al. were obtained by the same research lab using the same cell type and experimental procedure as for the experiment described herein, which is therefore considered a valid and suitable reference dataset. The read coverage profile of aligned reads at these ERG binding sites was extracted using the seqMINER program (Ye et al., 2011) with the following setting: left extension=5000 bp, right extension=5000 bp, wiggle step=5 bp. This gives 2000 reads (position 1-2000) at each chromosome site. The read at the peak centre (position

1000) of the binding site was normalised using the following equation:

푁표푟푚푎푙𝑖푠푒푑 푟푒푎푑 푐표푣푒푟푎푔푒

(퐸푥푡푟푎푐푡푒푑 푟푒푎푑 푐표푣푒푟푎푔푒 − 푎푣푒푟푎푔푒 푟푒푎푑 푐표푣푒푟푎푔푒 푓푟표푚 2000 푝표푠𝑖푡𝑖표푛푠) = (푆퐷 표푓 푟푒푎푑 푐표푣푒푟푎푔푒 푓푟표푚 2000 푝표푠𝑖푡𝑖표푛푠)

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The absolute difference between the normalised read coverage of ERG WT and ERG

S283D samples were calculated, ranked, and difference above 3 SD filtered (arbitrary cut-off for borderline statistical significance). This gives 430 sites. The statistical significance was then calculated with Chi-square test using the read coverage at the peak centre (position 1000) and the sum of reads from position 1-2000 (excluding the peak centre). The genes regulated by significantly (p<0.05) altered ERG bound regions were extracted using GREAT analysis package and combined with expression data

(RNA sequencing data, section 4.5) where the fold change (ERG WT/S283D) in expression is greater than 1.5 or less than 0.75 (50% difference, arbitrary cut-off, 4857 expressed genes filtered) to generate a final list of 33 genes.

[ERG WT(Expt2) + ERG WT(Expt3)] + 1 Expression fold change = 22 [ERG S283D(Expt2) + ERG S283D(Expt3)] + 1

The ChIP sequencing tracks of the filtered genes were manually validated to confirm differential DNA binding. Four genes (ADORA2A, RABL2A, CDA and

N6AMT1) were identified with changes in both DNA binding and gene expression above the arbitrary thresholds. One gene (BTG2) was identified with significant change in DNA binding but not the expression level. The ChIP sequencing traces were shown in parallel with the heptad (FLI1, ERG, LMO2, SCL, GATA2, LYL1, RUNX1) binding and histone markers (H3K27ac, H3K4me1, H3K4me3) which mark active transcription events (Figure 6-5, Figure 6-6). Specifically, ERG S283D showed enhanced binding at a regulatory element of ADORA2A gene but reduced binding for RABL2A, CDA and

N6AMT1 regulation compared to ERG WT (Figure 6-5). The normalised transcript

22 +1 on the numerator and denominator so that the denominator does not equals to 0 if expression value is 0. 211

Huang: Chapter 6. Mechanistic Study of ERG pS283 levels indicate that all four genes had up-regulated expression by ERG S283D binding

(Table 6-1).

ADORA2A (adenosine A2A receptor) encodes a member of the guanine nucleotide-binding protein (G protein)-coupled receptor (GPCR) superfamily, which responds to extracellular cues by activating adenylyl cyclase to induce synthesis of intracellular cAMP. The encoded protein is abundant in the basal ganglia, vasculature, T lymphocytes and platelets (Massink et al., 2015). It plays an important role in many biological functions, such as cardiac rhythm and circulation, cerebral and renal blood flow, immune function, pain regulation, and sleep (Li et al., 2013). An important and relevant physiological function of the A2A receptor is its negative regulation of over- reactive immune cells, thereby protecting tissues from collateral inflammatory damage

(Ohta and Sitkovsky, 2001).

RABL2A (RAB, member of RAS oncogene family-like 2A) is a member of the

RAB gene family which belongs to the RAS GTPase superfamily. The proteins in the family of RAS-related signalling molecules are small GTP-binding proteins that play important roles in the regulation of exocytotic and endocytotic pathways. This gene maps to the site of an ancestral telomere fusion event and may be a subtelomeric gene

(Wong et al., 1999).

CDA encodes an enzyme, cytidine deaminase, involved in pyrimidine salvaging.

The encoded protein forms a homotetramer that catalyses the irreversible hydrolytic deamination of cytidine and deoxycytidine to uridine and deoxyuridine, respectively.

Mutations in this gene are associated with decreased sensitivity to the cytosine 212

Huang: Chapter 6. Mechanistic Study of ERG pS283 nucleoside analogue cytosine arabinoside used in the treatment of certain childhood leukaemias (Demontis et al., 1998; Kuhn et al., 1993).

N6AMT1 (N-6 adenine-specific DNA methyltransferase 1) encodes protein methyltransferase. The encoded enzyme may be involved in the methylation of release factor I during translation termination (Figaro et al., 2008).

It is worth noting that the degree of ERG WT/S283D binding and the final transcriptional output occurred in opposite directions for different gene targets (Figure

6-5, Table 6-1), as bound transcription factors are capable of initiating or repressing transcription depending on the nature of the regulatory element (enhancer/repressor)

(Levine and Tjian, 2003; Noonan and McCallion, 2010).

The protein encoded by BTG2 (B-cell translocation gene 2) is a member of the

BTG/Tob family which has structurally related proteins with anti-proliferative properties. The BTG2 protein is involved in the regulation of the G1/S transition of the cell cycle (Hu et al., 2013; Takahashi et al., 2014). Reduced DNA binding at a heptad locus potentially regulating BTG2 expression was observed for ERG S283D (Figure 6-

6), however, no difference in BTG2 transcript level was detected (Table 6-1).

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214

Huang: Chapter 6. Mechanistic Study of ERG pS283

Figure 6-5 ChIP sequencing traces of genes with differential DNA binding and altered expression induced by ERG S283D in HSPC.

Four genes were identified with altered binding at regulatory DNA regions (absolute difference >3 SD in ChIP sequencing normalised reads) and differential expression (fold change >50% in RNA sequencing) by ERG S283D compared to ERG WT over-expression. The ChIP sequencing traces were extracted with the alignment of gene of interest. ChIP sequencing traces of the heptad members (FLI1, ERG, LMO2, SCL, GATA2,

LYL1, RUNX1) and histone markers (H3K27ac, H3K4me1, H3K4me3) from CD34+ HSPC were included as reference. The chromosome numbers and the corresponding loci of altered binding are shown below.

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Figure 6-6 ChIP sequencing trace of BTG2 in ERG transduced HSPC.

BTG2 was identified with altered binding at its regulatory DNA element (absolute difference >3 SD in ChIP sequencing normalised reads) by ERG S283D compared to

ERG WT over-expression. The ChIP sequencing traces were extracted with the alignment of gene of interest. ChIP sequencing traces of the heptad members (FLI1,

ERG, LMO2, SCL, GATA2, LYL1, RUNX1) and histone markers (H3K27ac,

H3K4me1, H3K4me3) from CD34+ HSPC were included as reference. The chromosome number and the corresponding locus of altered binding are shown.

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Table 6-1 Transcript levels of identified genes with altered DNA binding.

Expt2 Expt3 ERG WT ERG S283D ERG WT ERG S283D ADORA2A 40 51.5 59 83 RABL2A 28 40 22.5 37 CDA 11.5 11 8.5 18 N6AMT1 32.5 46.5 35 47.5 BTG2 248.5 359 676 631.5

Normalised transcript levels of genes with differential DNA binding identified by ChIP sequencing (absolute difference > 3 SD). ERG over-expressing HSPCs were sorted for the CD34+ population from the transduced population (GFP+) at week 0. Data from transduction Expt2 and Expt3 were shown. RNA sequencing data normalisation was performed by D. Beck.

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It is worth noting that transduction was performed using untagged ERG constructs as the pMIG+ HA-ERG constructs yielded lower viral transduction efficiency during protocol optimisation (data of viral titre not shown), and ChIP was therefore directly performed on ERG. As a consequence, over-expressed pMIG+ ERG as well as endogenous WT ERG were immunoprecipitated. However, DNA sequencing trace indicated that in the over-expressing context, endogenous ERG signal was completely negligible (Figure S4), and unless this relatively low level of endogenous ERG saturated the binding regions, the ChIP sequencing results should be able to reveal differential binding in this experimental setting. Due to the quality of the ChIP sequencing data, only minor changes in DNA binding were observed for a few genes. I was not able to identify a haematopoiesis-associated gene with concomitantly altered ERG binding at its regulatory DNA regions and protein expression. One possible explanation is that the binding changes are too minor to impact on gene expression, and/or the aberrant binding by the mutant ERG is compensated by other factors in the transcriptional complex. This is a valid assumption as ERG is known to bind DNA in a combinatorial setting (Beck et al., 2013; Diffner et al., 2013; Wilson et al., 2010). Failure to see enrichment on positive

ERG binding regions such as the ERG +85 enhancer also suggests the data quality being not ideal. Because of time constraints, this experiment was not repeated.

However, data of better quality could be obtained by using cord blood samples with even higher cell number to increase the amount of immunoprecipitated ERG-bound chromatin, or by optimising the immunoprecipitation protocol with more stringent wash condition to reduce non-specific bindings causing the noise signals. Alternatively, optimisation of the transduction procedure could be undertaken to use tagged ERG constructs for ChIP to resolve the concern of endogenous WT ERG saturating the binding sites of interest. 218

Huang: Chapter 6. Mechanistic Study of ERG pS283

6.6. S283 phosphorylation does not affect ERG transactivation ability

To obtain further insights into the functional importance of ERG S283 phosphorylation, I examined its impact on ERG-dependent transcriptional activation of a target reporter. A luciferase reporter construct was transfected together with pMIG+

ERG (WT, S283A or S283D) constructs into HEK293T cells. A LacZ expression construct was included in all samples to serve as an internal indicator of the transfection efficiency. The luciferase reporter construct on a pGL2b backbone contains an upstream

ERG-responsive segment, the ERG +85 enhancer sequence, which acts as a promoter in this setting and transactivates the expression of the downstream luciferase gene upon

ERG binding. The luciferase assay is a fluorescence based assay using a luminol reagent, which is metabolised into a coloured product by luciferase.

To avoid saturation of the ERG protein at the DNA sequence which can render no difference in the level of transactivation, the optimal dose combination was pre- determined by titration using either a fixed dose of the pMIG+ ERG plasmid23 (0.5

µg/well) with various concentrations of the luciferase plasmid (0-1.0 µg/well) (Figure

6-7A) or a fixed dose of the luciferase construct (1.5 µg/well) with a dose range of ERG

(0.1-0.9 µg/well) (Figure 6-7B). The normalised luciferase activity (Luc/LacZ) plateaued at 0.8 µg/well luciferase plasmid with 0.5 µg/well ERG plasmid (Figure 6-

7A), indicating that with this level of ERG, at least 0.8 µg/well luciferase construct is needed to avoid saturation. When using fixed dose of luciferase and varying doses of

23 pMIG+ ERG WT was used in the titration. 219

Huang: Chapter 6. Mechanistic Study of ERG pS283

ERG, the normalised luciferase activity plateaued at 0.3 µg/well ERG plasmid with 1.5

µg/well luciferase plasmid (Figure 6-7B). This dose combination demonstrated that less

ERG is needed to saturate even higher amount of the promoter compared to Figure 6-

7A. Since sub-saturation is defined as the promoter (luciferase construct) present in excess relative to the amount of ERG, the dose combination one step lower than the latter titration (0.25 µg/well ERG with 1.5 µg/well +85-luc) was used in the subsequent experiment.

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Huang: Chapter 6. Mechanistic Study of ERG pS283

Figure 6-7 Transactivation assay dose titration.

The optimal sub-saturation dose combination was titrated using a fixed dose of the

ERG/luciferase plasmid with various concentrations of the luciferase/ERG plasmid. The data presented are normalised against LacZ expression. Luc, luciferase.

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To test the transactivation capability of ERG S283 variants, luciferase activity was measured with pMIG+ or pMIG+ ERG transactivating the pGL2b +85-luciferase construct. Bar graph in Figure 6-8A shows that all three ERG constructs (WT, S283A,

S283D) were functional and capable of activating transcription at the ERG +85 site to a similar level. In the absence of the promoter and the luciferase gene, comparable baseline level of fluorescence was detected with all four conditions including the pMIG+ vector (Figure 6-8B). There was equivalent amount of ERG expression by immunoblotting (Figure 6-8C). From these data, I conclude that phosphorylation at

S283 does not alter the transcriptional activation by ERG in HEK293T cells. However, negative transactivation results should not be interpreted as ERG S283 phosphorylation being redundant in regulating ERG function. Other factors should also be taken into account. For example, while ERG is known to interact with other transcription factors during haematopoiesis regulation (Beck et al., 2013; Diffner et al., 2013; Wilson et al.,

2010), the relevant cellular context for ERG to exert its function properly is lacking in the HEK293T cells.

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Figure 6-8 S283 phosphorylation does not affect ERG transactivation ability.

(A) Bar graph shows ERG transactivation ability measured using HEK293T cells co- expressing pMIG+ ERG constructs (0.25 µg/well) and a luciferase gene with an upstream ERG-responsive +85 enhancer as the promoter sequence in a pGL2b backbone (1.5 µg/well). Data were normalised to LacZ (0.1 µg/well) activity. Error bars represent SD from triplicate measurements. (B) Bar graph shows the background level of fluorescence in the absence of a transactivation event. pMIG+/ERG

(WT/S283A/S283D) (0.25 µg/well) and the pGL2b empty vector (1.5 µg/well) were transfected into HEK293T cells. Luciferase activity (Luc) was determined and normalised to LacZ activity. Error bars represent SD from triplicate measurements. (C)

A representative western blot showing ERG protein levels in a transactivation assay.

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Huang: Chapter 6. Mechanistic Study of ERG pS283

6.7. Chapter summary

In this chapter, I evaluated a number of potential mechanisms by which ERG

S283 phosphorylation might impact on its activity. I first measured the half-lives of WT and S283 mutant ERG protein using an artificial over-expression system in HEK293T cells. The degradation pattern of ERG was generated with protein synthesis inhibition and quantified using immunoblotting. No difference was observed for ERG half-lives, laying the foundation for subsequent mutagenesis assays based on the premise that any observed difference would not be due to rapid/slow protein degradation.

As a transcription factor, the first level of control is for the protein to localise into the nucleus where it can bind DNA. Therefore, I next examined ERG nuclear localisation using immunofluorescence and cell fractionation combined with immunoblotting in transduced MOLT-4 cells expressing HA tagged ERG. MOLT-4 cells provide the relevant cellular context for ERG activity in leukaemic cells, and the

HA tag enables the separation of exogenous mutant ERG from endogenous WT ERG.

ERG was found to be primarily located in the nucleus, with no difference noted between the WT and the mutant proteins.

Given that neither protein stability nor nuclear localisation was altered upon mutating S283 to mimic constitutive phosphorylation, difference in the ERG-driven phenotype observed in CD34+ HSPC could be due to its activity inside the nucleus. The critical step for transcription initiation is the interaction between the transcription factor and the regulatory DNA sequence. A combination of both in vitro and in vivo protein-

DNA binding assays was employed. In vitro approaches (e.g. FP) generally allow

224

Huang: Chapter 6. Mechanistic Study of ERG pS283 quantification of the binding affinity of a given transcription factor to a minimal required consensus DNA sequence. In this study, no differential binding was observed for ERG in vitro DNA binding. However, in this artificial setting, the only interaction taking place is that between ERG and a 16 bp fragment of naked DNA. It is difficult to translate this information into actual in vivo function as a given transcription factor might not always regulate all targeted genes at the same time, or in all cell types, due to cell type-specific modulation of transcription factor activity by co-regulators. In other words, although purified ERG was folded properly into its tertiary structure, absence of the essential physiological environment including other protein partners critical for transcriptional complex formation and in turn indirect DNA binding may have a dramatic impact on the observed read-out. In vivo binding of HA tagged ERG on the

ERG +85 and the hHEX+1 enhancers in transduced MOLT-4 cells revealed only minor increase in DNA binding by ERG S283D compared to WT ERG, consisting with ERG being largely phosphorylated on S283 in MOLT-4 cells. However, an indicative enhancement in binding was observed in ERG S283D on both sites compared to the opposite phosphomutant ERG S283A. My attempt on assessing genome-wide ERG

DNA binding by ChIP sequencing of ERG transduced HSPC did not give satisfactory results due to high level of noise signals interfering with the identification of any true difference in binding. However, this is without doubt a well-designed experiment, and is expected to yield very promising results if optimised.

Transactivation assay, also known as luciferase reporter assay, is broadly used to study the functional aspects of known protein-DNA interactions. In most cases, the presence of the protein of interest and the protein-responsive DNA element are sufficient to give a quantitative measure of the protein’s transactivation ability. 225

Huang: Chapter 6. Mechanistic Study of ERG pS283

However in this study, although a phenotypic change was observed with the ERG

S283D mutant in HSPC, there was no difference observed in the ability of ERG S283 mutant to transactivate the reporter.

Taken together, these data suggest that although direct ERG-DNA interactions might not be affected by ERG S283 phosphorylation, indirect interactions via cooperative factors might play a role in ERG enrichment at target sites and combinatorial regulation of target genes. Elucidation of these partner proteins and establishing differences in their binding to S283 phosphorylated and unphosphorylated ERG and combinatorial DNA interactions will be informative in delineating the leukaemogenic process.

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Huang: Chapter 7. Conclusion and Future Directions

Chapter 7. Concluding Remarks and Future Directions

Targeting aberrantly activated signalling pathways that modify transcription factors has significant advantages over targeting the transcription factor itself as it may be required for normal physiological function. This is the first study to date that evaluates ERG phosphorylation and its functional impact in leukaemia. This work contributes to the understanding of ERG phosphorylation in human leukaemogenesis and to the identification of potential pathways that could be targeted in specific circumstances.

A notable aspect of this work is that ERG was purified directly from human leukaemic cell lines and primary CD34+ HSPC without exogenous over-expression to map the physiologically relevant phosphosites. In total, I catalogued five phosphorylation sites on human ERG – S55, S88, S103, S222, and S283. I chose one phosphorylation site pS283 that is located in between the two functional domains of

ERG and was abundantly detected in leukaemic cells, but not in healthy CD34+ HSPC, for additional analysis. Construction of a monoclonal antibody specifically recognising this phosphorylation on ERG enabled the recognition of the ETP ALL subtype from a panel of T-ALL leukaemic xenografts – high S283 phosphorylation correlates with their poor clinical outcomes.

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Huang: Chapter 7. Conclusion and Future Directions

For years, it has been known that the RAS-MAPK signalling cascade promotes oncogenesis (Chang and Karin, 2001). However, the mechanism by which MAPK signalling is linked with leukaemogenesis has remained elusive. The data presented in this study suggest that ERK2 directly phosphorylates ERG at S283 both in vitro and in vivo. Inhibition of MEK/ERK activity renders a decrease in colony formation by leukaemic cell lines with high ERG pS283. Self-renewal and clonogenic assays using the S283 phosphomutants provided insights into the biological consequence of ERG

S283 phosphorylation in HSPC. The mutant mimicking the constitutively phosphorylated protein exhibited enhanced proliferation and colony-forming efficiency compared to WT ERG. The S283A mutant mimicking a version of ERG that is resistant to phosphorylation at this site expanded and generated colonies with efficiency comparable to the WT protein. This was in agreement with my observation that ERG is largely unphosphorylated at S283 in primary CD34+ HSPC. Pathway analysis revealed up-regulation of several oncogenic pathways including the RAS-MEK-ERK cascade by

S283 phosphomimetic ERG, consistent with ERK-mediated phosphorylation of ERG

S283. Based on quantitative protein measurements, immunofluorescence, and DNA binding assays, the altered CD34+ HSPC phenotype was not the result of slower degradation or improper localisation of the S283D mutant, but likely to be due to enhanced and/or aberrant binding of this variant to target DNA in combination with an as yet to be identified co-factor.

Although mutating phosphorylated serine to alanine has been the conventional approach to study phosphorylation, it is possible that the alanine mutant may not always serve as a non-phosphorylated surrogate. It has recently been reported that non- phosphorylated serines are capable of forming hydrogen bonds using its hydroxyl side 228

Huang: Chapter 7. Conclusion and Future Directions chain with threonine residues in close vicinity and affect ERG protein folding and DNA accessibility to its ETS domain (Regan et al., 2013). This effect is absent in an alanine mutant with a non-polar side chain (Regan et al., 2013). The phosphomimetic aspartic acid mutation, on the other hand, is a close mimic of phosphoserines given its possession of a negatively charged side chain at physiological pH and a truer reflection of a phosphorylated serine.

Compared to the mutagenesis approach, using leukaemic cells with modified unphosphorylatable ERG could potentially improve the read-out. By using the CRISPR system (Jinek et al., 2012), an emerging genome editing method, leukaemic cell lines can be modified with specific changes made to their genome. For example, MOLT-4 cells can be edited to express ERG with exon12 or DEF domain deletion, which will expect to have less MAPK/ERK-mediated endogenous S283 phosphorylation. Exon12 deletion mutant will be considered more relevant as ERG3-∆exon12 is a naturally existing ERG isoform (Bohne et al., 2009). This way, the RAS-MEK-ERK pathway activity remains unchanged, and the observed behavioural change between normal and modified MOLT-4 cells will be purely due to altered ERG S283 phosphorylation level.

Aspects that are worth investigating in the future include visualisation of the tertiary ERG protein structure in the presence or absence of S283 phosphorylation.

Previous studies have shown that phosphorylation can alter protein conformation, thereby influencing their activity (Keshwani et al., 2015; McClure et al., 1992; Soares- dos-Reis et al., 2014; Vetter and Leclerc, 2001). For example, Vetter and Leclerc discovered that phosphorylation of two serine residues (S76 and S92) within the calcium-dependent calmodulin (CaM)-binding domain of human protein 4.1 isoform 229

Huang: Chapter 7. Conclusion and Future Directions alters its ability to adopt the alpha helical conformation in a position-dependent manner

(Vetter and Leclerc, 2001). Elucidation of the structural basis of ERG conformational change by ERK2-induced phosphorylation will require 3D structure determination of full-length ERG at atomic resolution before and after phosphorylation using X-ray crystallography or NMR spectroscopy. Due to time constraints, evaluation of ERG protein crystal structure was not part of this study.

Transcription factor regulation of downstream gene expression is complex, with its transactivation potential depending on combinatorial interactions between other transcription factors, cofactor proteins, and chromatin modifiers (Basuyaux et al., 1997;

Carrere et al., 1998)(Ravasi et al., 2010). A good example is that human OCT4, a transcription factor fundamental to maintaining cell pluripotency and self-renewal, harbours two critical phosphorylation sites at T234 and S235. Co-immunoprecipitation assays have identified protein partners that are enriched for ERK motifs, suggesting a shared upstream pathway regulating the activity of the transcriptional complex

(Brumbaugh et al., 2012). Combinatorial transcription factor binding is a well- recognised phenomenon in regulation of the transcriptional programs in CD34+ HSPC

(Beck et al., 2013; Diffner et al., 2013; Wilson et al., 2010). Our research team has previously shown that over 300 chromatin sites are bound by all seven transcription factors constituting a ‘heptad’ of factors that are associated with stem cell signatures in

HSPCs and leukaemic cells (Beck et al., 2013; Diffner et al., 2013). Additionally, many

ERG binding sites in HSPC were found co-occupied by other key haematopoietic transcription factors (Beck et al., 2013; Diffner et al., 2013; Wilson et al., 2010). Given the combinatorial nature of transcription factor binding, the cognate motif for a specific factor is often absent at DNA sequences bound by the factor. As one would expect, 230

Huang: Chapter 7. Conclusion and Future Directions modification of ERG by phosphorylation may directly affect its interactions with other proteins, thereby impact on the formation of a multi-protein regulatory complex. To date, the identities of ERG binding partners in leukaemic cells have not been revealed.

Attempts were made in this study using a co-immunoprecipitation approach but were not successful due to strong signals from non-specifically bound proteins and result inconsistency between independent experiments (data not shown). In the phylogeny of

ETS factors, ERG is most closely related to FLI1 (Figure 1-3) (Hollenhorst et al., 2007;

Oettgen, 2009). Phosphorylation of FLI1 impacts on its ability to complex with RUNX1 and regulates megakaryocytic differentiation (Huang et al., 2009). As such, in collaboration with Prof J. Bushweller from the University of Virginia, we are currently investigating combinatorial ERG/RUNX1-DNA binding using WT and S283D ERG proteins in an isothermal titration calorimetry (ITC) assay. Additional to assessing ERG interaction with the heptad members, the co-immunoprecipitation assay will be performed with optimised protocol (for example, modified cell lysis condition with different detergent concentrations) to reduce non-specific binding while retaining the true binders. This assay works by purifying ERG together with all its binding partners via an anti-ERG antibody, and all bound proteins can be subsequently identified by MS in an unbiased fashion including further characterisation of the PTMs on these physically associated proteins. Identifying specific interactions between ERG with pS283 and its binding partner(s) in a transcriptional complex that promotes HSPC expansion could be leveraged to design small molecules that interrupt these interactions.

This would be superior to inhibiting the upstream signalling pathways, which could have deleterious and unintended consequences because of the plethora of downstream targets.

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Huang: Chapter 7. Conclusion and Future Directions

Another area that is important to explore is the impact of mutant ERG on the ability of HSPC to differentiate in response to specific cytokines. As the presence of IL-

6 in the cytokine cocktail used during transduction does not favour the maintenance of erythrocytic or megakaryocytic progenitor cells, the differentiation capabilities of these populations could not be assessed using cells transduced with this protocol. Similarly, the transduction procedure did not support expansion of the lymphoid progenitors.

Another highlight of this study is the identification of a positive feedback loop between pS283 ERG and the MAPK/ERK signalling cascade in association with enhanced HSPC proliferation. This suggests the establishment of a direct link between

MAPK signalling and the transcriptional regulation of haematopoiesis. Despite its well- recognised role in oncogenesis (Campbell, 2014; Chung and Kondo, 2011), inhibition of the MEK-ERK pathway is not broadly applied for cancer treatment, likely due to its indispensable involvement in other physiological processes. As suggested by the unpredicted change in heptad DNA binding pattern following MEK inhibition (Figure

5-11), future work should instead focus on the development of specific ERG pS283 inhibitor by high throughput screening of a compound library or designing new molecules to avoid off-target effects. Candidate compounds are expected to inhibit the growth of ERG pS283-positive leukaemic cells while sparing healthy HSPCs using both in vitro and in vivo approaches. Their specific mechanisms of action on leukaemic cells and non-specific side effects on healthy cells should be thoroughly addressed before applied to clinical trials.

Other phosphorylation sites of ERG may be investigated to determine their potential contribution to other malignancies. For example, ERG S329P missense 232

Huang: Chapter 7. Conclusion and Future Directions mutation is the driving force of impaired definitive haematopoiesis in ErgMld2/Mld2 homozygous mice (Loughran et al., 2008). ERG S329 was outside the MS coverage of the current study; however, the local peptide sequence (326ELLS) fulfils the basic substrate motif of CK-I (D/EXXpS) (Amanchy et al., 2007; Marin et al., 2003). The presence of CK-I ERG S329 phosphorylation could be determined using a similar experimental design. Progressing from here, identifying other types of PTM on ERG may also provide valuable information on the regulation of its function. ERG is most probably modified in many ways in addition to phosphorylation. A recent study reported that ERG acetylation by p300 contributed to its interaction with enhancer/promoter regions, which influenced the recruitment and occupancy of a chromatin reader protein BRD4 (Roe et al., 2015). Additionally, different modifications on the same protein, especially at nearby locations, may interfere with each other

(Tootle and Rebay, 2005; Walsh et al., 2005). Studies have shown the effect of phosphorylation on other types of PTM. These include a study reporting that S59 phosphorylation of Sp1 is inversely related to its sumoylation. N-terminal sumoylation stabilises Sp1 protein, while increased S59 phosphorylation of Sp1 abolishes its sumoylation (Spengler et al., 2008). Since Sp1 phosphorylation allows for the up- regulation of Sp1-dependent genes that control cell-cycle progression and tumourigenesis, the desumoylated unstable Sp1 product induced by cell-cycle and mitotic kinases leads to enhanced proliferation and cancer development (Spengler et al.,

2008). Expanding the knowledge of such specific molecular lesions associated with certain subtypes of leukaemia could be harnessed to design targeted therapeutics with limited side effects.

233

Huang: Contributions

Contributions

The majority of experiments and data analyses presented herein were completed by Y. Huang. J. A. I. Thoms and K. Knezevic provided guidance and supervision for performing the experiments. L. Zhong and S. L. Lau assisted with the running of mass spectrometry samples. S. Suryani, E. Lee, and R. B. Lock kindly provided primary xenograft cells and essential reagents for the experiments in Chapter 3 and 5. The pGEX-4T-1 plasmid was a kind gift from M. Crossley’s lab. K. L. MacKenzie provided essential reagents, protocol, and supervision for the experiments in Chapter 4. M. L.

Tursky provided guidance for performing the experiments in Chapter 4 and assisted with data analysis. D. Beck assisted ChIP and RNA sequencing data analysis in Chapter

4. J. Olivier assisted with statistical analyses for the results in Chapter 4. S. Suryani provided guidance for handling ALL xenograft cells (Chapter 3 and 5) and performed

ALL xenograft viability assay (Chapter 5). V. Chandrankanan provided reagents for and kindly supervised and assisted with the immunofluorescence experiment in Chapter 6.

A. Boulton and C. Schmidt performed GST-ERG purification and the FP experiment in

Chapter 6. J. E. Pimanda, J. W. H. Wong, and J. A. I. Thoms assisted with data analysis and provided supervision for the entire study.

In addition, my greatest appreciation goes to J. A. I. Thoms for her help in proof-reading this thesis. Thanks go to R. O’brien at Children Cancer Institute Australia for her continuous assistance with flow cytometry booking and maintenance, the staff at

BMSF UNSW Australia for the use of mass spectrometry facilities, donors and staff of the cord blood banks at the Prince of Wales Hospital, staff at the BRIL flow cytometry 234

Huang: Contributions facilities for cell sorting, staff at the BMIF imaging centre for confocal microscopy, past and present members of the Pimanda laboratory for assistance with experimental troubleshooting and processing cord blood units. This work was funded by the National

Health and Medical Research Council (Australia) and Leukaemia Foundation

(Australia). Y. Huang received the University International Postgraduate Award (UIPA) and the Postgraduate Research Support Scheme (PRSS) conference travel fund from

UNSW Australia and the scholarship top-up from the Translational Cancer Research

Network (TCRN).

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Huang: Disclosure of interest

Disclosure of Interest

There is no conflict of interest in this study.

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Huang: References

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Appendices – Supplementary Materials

Table S1 List of reagents.

Reagent Supplier Catalogue 12 × 75 mm polystyrene test tubes Falcon 2235 Acetic acid Sigma Aldrich Pty Ltd, Australia A6283 acetonitrile Sigma Aldrich Pty Ltd, Australia 34967 Adenosine 5′-triphosphate disodium salt hydrate Sigma Aldrich Pty Ltd, Australia A2383 Agarose AppliChem Inc., USA A2114,0500 Ampicillin sodium salt Sigma Aldrich Pty Ltd, Australia A9518 Anisomycin Sigma Aldrich Pty Ltd, Australia A9789 Antarctic phosphatase New England Biolabs Inc., USA M0289S anti-ERG1/2/3(C17) antibody Santa Cruz Biotechnology, Inc., USA sc354x anti-ERK antibody Cell signaling 9101 anti-HA antibody Abcam ab9110 anti-mouse IgG-HRP antibody Dako, Agilent Technologies Australia Pty Ltd P0260 anti-pERK antibody Cell signaling 9102 anti-rabbit IgG-HRP antibody Dako, Agilent Technologies Australia Pty Ltd P0448 anti-β-actin-HRP antibody Santa Cruz Biotechnology, Inc., USA sc-47778 AutoMACS columns Miltenyi Biotec Australia Pty Ltd 130-021-101 AutoMACS running buffer Miltenyi Biotec Australia Pty Ltd 130-091-221 Bacterial Strain JM109, Glycerol Stock Promega Australia P9751 BigDye Terminator v3.1 Life Technologies Australia Pty Ltd 4337455 Bio-Rad concentration assay Bio-Rad Laboratories, Inc., USA 500-0001 BL21(DE3) Competent E. coli New England Biolabs Inc., USA C2527I BSA Sigma Aldrich Pty Ltd, Australia A8412 C18 ziptip columns Merck Millipore Corporation, USA Z720070-96EA CD34+ Direct antibody-labelled magnetic beads Miltenyi Biotec Australia Pty Ltd 130-046-703 CD34-PE, anti-human BD Australia and New Zealand 348057 CD45-FITC, anti-human BD Australia and New Zealand 555482 CFU blunt-end needles Stem Cell Technology 28110 Chymotrypsin Sequencing Grade from bovine pancreas Roche Diagnostics Pty Ltd, Australia 11418467001 cOmplete, Mini, EDTA-free Protease Inhibitor Cocktail Tablets Roche Diagnostics Pty Ltd, Australia 11836170001 Coomassie electrophoresis stain NuSep SG-021 Cord blood collection bag MacoPharma Australia Pty Ltd MSC1205DU Cryovial Interpath Services Pty Ltd, Australia 122263 Cycloheximide Sigma Aldrich Pty Ltd, Australia C7698 D-luciferin Sigma Aldrich Pty Ltd, Australia L9054 DMEM Life Technologies Australia Pty Ltd 11995-065 DMSO Sigma Aldrich Pty Ltd, Australia D2650 DNA oligonucleotide Life Technologies Australia Pty Ltd - DNase I QIAGEN Pty Ltd, Australia 79254 dNTP set Promega Australia U1330 Donkey serum Sigma Aldrich Pty Ltd, Australia D9663 D-sorbitol Sigma Aldrich Pty Ltd, Australia S1876 DTT Sigma Aldrich Pty Ltd, Australia D9779 Dynabeads (Protein G) Life Technologies Australia Pty Ltd 10003D DynaMag™-2 Magnet Life Technologies Australia Pty Ltd 12321D ECL Western Blotting Luminol Reagent Santa Cruz Biotechnology, Inc., USA sc-2048 EDTA Life Technologies Australia Pty Ltd AM9260G EPO, human recombinant Amgen Australia Pty Ltd AA5534-00 Ethanol Chem-Supply Pty Ltd, Australia EA043-2.5L-P Express SYBR GreenER QPCR Supermix Universal Life Technologies Australia Pty Ltd 11784-01K FBS (Dialyzed) Life Technologies Australia Pty Ltd 26400-036 FBS, for general use Life Technologies Australia Pty Ltd 10099-141 10099-141, lot 7212348Y; FBS, for hematopoietic cultures (refered to as FBS2 in text) Life Technologies Australia Pty Ltd 16000-044, lot 1085998 Flt3L, human recombinant Peprotech Inc., USA 30019 Formaldehyde solution Sigma Aldrich Pty Ltd, Australia 252549 Formic acid for mass spectrometry (98%) Sigma Aldrich Pty Ltd, Australia 94318-50ML-F G-CSF, human recombinant Amgen Australia Pty Ltd Not applicable Gel extraction kit QIAGEN Pty Ltd, Australia 28704 Page 265 of 297

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Gentamycin 50 mg/ml Life Technologies Australia Pty Ltd 15750-060 Glutathione agarose beads Sigma Aldrich Pty Ltd, Australia G4510 Glycerol Sigma Aldrich Pty Ltd, Australia G5516 HBSS Life Technologies Australia Pty Ltd 14025-092 Hemin Fluka BioChemika, Switzerland 51280 HEPES Sigma Aldrich Pty Ltd, Australia H0887 iBlot transfer stack Life Technologies Australia Pty Ltd IB3010-02 IgG from rabbit serum Sigma Aldrich Pty Ltd, Australia I5006 IgG1-PE BD Australia and New Zealand 349043 IL-3, human recombinant Novartis Pharmaceuticals Australia Pty Ltd 215-134 CHO-IL3 12/3 388 IL-6, human recombinant Novartis Pharmaceuticals Australia Pty Ltd Not applicable IMDM Life Technologies Australia Pty Ltd 12440-053 Iodoacetamide Sigma Aldrich Pty Ltd, Australia I1149 Isopropanol Chem-Supply Pty Ltd, Australia PA013-2.5L-P Isopropyl β-D-1-thiogalactopyranoside Sigma Aldrich Pty Ltd, Australia I6758 JM109 competent cells Promega Australia L2001 LDS sample buffer (4×) Life Technologies Australia Pty Ltd NP0007 L-glutamine Life Technologies Australia Pty Ltd 25030-081 L-Glutathione (reduced) Sigma Aldrich Pty Ltd, Australia G4251 Lipofectamine 2000 Life Technologies Australia Pty Ltd 11668-019 LoBind microcentrifuge tubes Eppendorf 30108051 Low protein binding filter, 0.45um Merck Millipore Corporation, USA SLHV033RS Luria-Bertani (LB) broth EZMix sachets Sigma Aldrich Pty Ltd, Australia L-7658 Lymphoprep Vital Diagnostics Australia Pty Ltd 1114547 Lysozyme Sigma Aldrich Pty Ltd, Australia L6876 MAPK/p42 (ERK2) New England Biolabs, Inc., USA P6080L MAPK/p44 (ERK1) Sapphire Bioscience 000-00568 MEK Inhibitor U0126 Promega Australia V1121 Methanol RCI Labscan Ltd, Thailand AR1115-P2.5L Methylcellulose Fluka BioChemika, Switzerland 64630 M-MLV reverse transcriptase, with buffer and 0.1M DTT Life Technologies Australia Pty Ltd 28025-013 MOPS running buffer (20×) Life Technologies Australia Pty Ltd NP0001-02 Mr Frosty Freezing Container Thermo Fisher Scientific Australia 5100-0001 Myelin Basic Protein from bovine brain Sigma Aldrich Pty Ltd, Australia M1891 NH4OH solution (30%) Sigma Aldrich Pty Ltd, Australia 221228 Non-tissue culture treated 6 well plates Thermo Fisher Scientific Australia 150239 NP-40 Sigma Aldrich Pty Ltd, Australia NP40S NucleoBond® Xtra Midi kit Macherey-Nagel 740410 NuPAGE Novex 4 – 12% Bis Tris gradient gel Life Technologies Australia Pty Ltd NP0321BOX NuPAGE sample buffer Life Technologies Australia Pty Ltd NP0007 ONPG Thermo Fisher Scientific Australia 34055 Opti-MEM media Life Technologies Australia Pty Ltd 31985-070 Paraformaldehyde Electron Microscopy Sciences 15710 PBS Life Technologies Australia Pty Ltd 21600-069 PCR tubes, thin walled 0.2ml Interpath Services Pty Ltd, Australia 324000 Penicillin / Streptomycin Life Technologies Australia Pty Ltd 10378-016 Phenylmethylsulfonyl fluoride Sigma Aldrich Pty Ltd, Australia P7626 PhosSTOP phosphatase inhibitor tablet Roche Diagnostics Pty Ltd, Australia 4906845001 Phusion™ Hot Start High-Fidelity DNA Polymerase Thermo Fisher Scientific Australia F-540 Platinum® Taq DNA Polymerase High Fidelity Life Technologies Australia Pty Ltd 11304-011 PMA Sigma Aldrich Pty Ltd, Australia P8139 Poly-L-Lysine Coated Microscope Slides Polysciences, Inc. 22247-1 Ponceau S solution Sigma Aldrich Pty Ltd, Australia P7170 Pre-separation filter Miltenyi Biotec Australia Pty Ltd 130-041-407 Protamine sulphate MP Biomedicals Australia 219472901 Protein G agarose beads Roche Diagnostics Pty Ltd, Australia 11719416001 Proteinase K, recombinant, PCR grade Life Technologies Australia Pty Ltd EO0491 QBSF-60 medium Quality biological 160-204-101 QIAquick PCR purification kit QIAGEN Pty Ltd, Australia 28104 QuikChange Lightning Site-Directed Mutagenesis kit Agilent technologies 210518 Random primers Promega Australia C119A Restriction enzymes New England Biolabs Inc., USA - RetroNectin Takara Bio Inc., USA T100B RNaseA Life Technologies Australia Pty Ltd EN0531 Rnase-inhibitor Promega Australia N261A

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RNeasy mini kit QIAGEN Pty Ltd, Australia 74104 RPMI 1640 Life Technologies Australia Pty Ltd 11875-093 SB203580 Promega Australia V1161 SCF, human recombinant Amgen Australia Pty Ltd AA1580-00 SeeBlue® Plus2 Pre-Stained Standard Life Technologies Australia Pty Ltd LC5925 SILAC RPMI 1640 medium Life Technologies Australia Pty Ltd A2494401 Skim milk powder Woolworths Ltd, Australia Homebrand Sodium acetate Sigma Aldrich Pty Ltd, Australia S-2889 Sorbitol Sigma Aldrich Pty Ltd, Australia S1876 SP600125 Sigma Aldrich Pty Ltd, Australia S5567 Subcellular protein fractionation kit Thermo Fisher Scientific Australia PI-78840 Suspension dish, 35mm Thermo Fisher Scientific Australia 171099 SYBR Safe DNA gel stain Life Technologies Australia Pty Ltd S33102 T4 DNA ligase Promega Australia M1801 Titansphere® Phos-TiO2 kit GL Sciences Inc. 5010-21309 TPO, human recombinant Peprotech Inc., USA 30018 Trifluoroacetic acid (TFA) Sigma Aldrich Pty Ltd, Australia 302031 Trypan Blue (0.4% sterile filtered) Sigma Aldrich Pty Ltd, Australia T8154 Trypsin (2.5%) Life Technologies Australia Pty Ltd 15090-046 Trypsin-Mass spectrometry grade Promega Australia V5280 Tween 20 Sigma Aldrich Pty Ltd, Australia P2287 Universal microscope slides Livingstone International Pty Ltd, Australia 7101-1B Vivaspin protein concentrator tube VWR 28-9323-61 Ziptips, C18, rack of 96 Merck Millipore Corporation, USA Z720070-96EA α-MEM Life Technologies Australia Pty Ltd 12571-071 β-mercaptoethanol Sigma Aldrich Pty Ltd, Australia M3148 Reagents used in this study with supplier and catalogue numbers.

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Table S2 Equipment and software.

Equipment or Software Version Supplier AutoMACS Original or Pro Miltenyi Biotec Australia Pty Ltd Bioanalyzer 2100 Agilent Technologies, Inc., USA BioRuptor® sonicator - Diagenode, Liège, Belgium CellQuest Pro software 6 BD Biosciences, Cytopeia, USA DeSeq software 1.15.1 www.bioconductor.org DNA Engine Multi-Bay Thermal Cycler - BioRad Laboratories, Inc., USA FACS Sortware 1.0.650 BD Biosciences, Cytopeia, USA FACSCalibur - BD Biosciences, Cytopeia, USA FindPeaks 4.2 Integrative Genomics and Bioinformatics Core, Salk Institute, USA FlowJo software 10.0.7 Tree Star Inc., USA FT mass spectrometer - Thermo Fisher Scientific Australia GFOLD algorithm software 1.1.0 www.mybiosoftware.com GLOMAX 96 microplate luminometer - Promega Australia GLOMAX software 1.7.1 Promega Australia GSEA Java Desktop software 2.0.13 Broad Institute, USA HOMER software 4 Integrative Genomics and Bioinformatics Core, Salk Institute, USA iBlot system Original Life Technologies Australia Pty Ltd Illumina HiSeq2000 analyzer - BGI Tech Solutions CO. Ltd., Hong Kong, China ImageQuant LAS 4000 imager and Control software 1.2 GE Healthcare Australia Pty Ltd ImageQuant TL software 7 GE Healthcare Australia Pty Ltd Influx Cell Sorter - BD Biosciences, Cytopeia, USA Mascot software 2.3.2 Matrix Science Mx3000P qPCR System Mx3000P Agilent Technologies, Inc., USA Mx3000P software 4.10 Agilent Technologies, Inc., USA Nanodrop Spectrophotometer ND-1000 Thermo Fisher Scientific Australia Pty Ltd Partek Genomics Suite software 6.12.0713 Partek Inc., USA R software 3.0.2 http://CRAN.R-project.org seqMINER 1.3.3 http://seqminer.genomic.codes/ Shandon Cytospin 4 Thermo Fisher Scientific Australia Spectra MAX 190 absorbance microplate reader - Biostrategy SpeedVac centrifuge evaporator - Thermo Fisher Scientific Australia TopHat software 1.3.1 http://ccb.jhu.edu/software/tophat UCSC human genome software hg19 Genome Bioinformatics Group, USA Xcalibur 2.2 Thermo Fisher Scientific Australia ZEISS fluorescence microscope LSM780 ZEISS Details of all software and equipment used in this study with version and supplier information.

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Figure S1 Representative tandem mass spectra of phosphorylated ERG peptides.

Representative tandem mass spectra of phosphorylated chymotryptic peptide containing

(A) S55 and tryptic phosphopeptides containing (B) S88, (C) S103, and (D) S222 in

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endogenous ERG from MOLT-4 T-ALL cells. The b- and y-ions are annotated and labelled on the spectra and the MS1 accurate mass spectra are shown in the inset. Note that for clarity, some regions of the mass spectra have been amplified 10 fold.

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/ N

y 3

n e

t 2

l a

n 1

i S 0

Figure S2 Relative ERG amount from the nuclear and cytoplasmic fraction.

MOLT-4 cells were fractionated, ERG immunoprecipitated, in-gel digested and analysed by MS. Total ERG peptide signals were extracted using Xcalibur and plotted as a ratio of nuclear (N) to cytoplasmic (C) for each identified peptide. Horizontal line indicates the average ratio.

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Figure S3 ERG is 56% phosphorylated by in vitro ERK2 treatment.

Purified WT GST-ERG is in vitro treated with MAPK/ERK2 for 90 min and phosphorylation level at S283 measured by MS without phosphoenrichment.

Phosphorylation level is quantified as the area of peak (AA).

푝ℎ표푠푝ℎ표푟푦푙푎푡푒푑 푆283 푝푒푝푡𝑖푑푒 % phosphorylation = 푝ℎ표푠푝ℎ표푟푦푙푎푡푒푑+푢푛푝ℎ표푠푝ℎ표푠푝ℎ표푟푦푙푎푡푒푑 푆283 푝푒푝푡𝑖푑푒

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Table S3 Quality assessment of extracted RNA for RNA sequencing.

Nanodrop BioAnalyser Approx conc. Expt# Sample 260/280 260/230 RIN 28s:18s Vol (µl) (ng/µl) pMIG+ 25 88.56 2.04 1.9 9.7 2.1 ERG WT 25 26.79 1.99 1.44 10 1.9 2 ERG S283A 25 21.14 2.06 1.15 9.6 1.9 ERG S283D 25 24.18 1.95 1.38 10 1.8 pMIG+ 25 43.42 2.09 1.01 10 1.9 ERG WT 25 49.93 2.13 1.74 9.9 2 3 ERG S283A 25 55.73 1.99 1.68 9.9 1.8 ERG S283D 25 60.36 2.04 0.82 10 2.1

The quality and integrity of extracted mRNA of week 0 transduced cord blood cells were assessed using the Nanodrop spectrophotometer and the BioAnalyser (Ramaciotti centre, UNSW Australia). RIN, RNA integrity number.

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Figure S4 DNA sequencing trace of ERG amino acid 283 codon from HSPC transduction. mRNA from week 0 transduced cord blood cells were reverse transcribed and cDNA sequenced using forward primer 5’-CTACGCAAAGAATTACAAC-3’ or reverse primer 5’-TGTACGGGAGGTCTGAGG-3’. The codon of amino acid 283 is boxed in black. TCT, serine; GCT, alanine; GAT, aspartic acid.

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Figure S5 Normalised RNA sequencing counts.

The normalised sequence counts of ERG WT and ERG S283D from RNA sequencing results of two independent CD34+ cord blood transduction experiments (Expt2 and 3).

Data normalisation and bar graph plotting were performed by D. Beck. Error bars represent SD calculated from replicate experiments. TMM, trimmed mean of M-values.

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Figure S6 ERG pS283 and pERK levels are consistent in ETP ALL replicates.

Biological replicates of ETP ALL xenograft cells raised in different spleens have similar levels of pS283 ERG and pERK. Immunoblotting showing the endogenous levels of

ERG pS283, total ERG, active ERK1/2 (pERK1/2) and β-actin.

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