Chapter 1: Introduction

A Clinical and Molecular Study of the Growth Disorder 3-M Syndrome

A thesis submitted to The University of Manchester for the degree of Doctor of Philosophy in the Faculty of Medical and Human Sciences

2011

Philip George Murray

School of Medicine

Faculty of Medicine and Human Sciences

Table of Contents

List of Figures ...... 6 List of Tables ...... 11 Abstract ...... 16 Declaration ...... 17 Copyright Statement ...... 18 Acknowledgements ...... 19 Attributed Work ...... 19 Chapter 1: Introduction ...... 20 1.1 Overview ...... 21 1.2 Normal Growth and Short Stature ...... 22 1.3 The Small for Gestational Age Infant ...... 23 1.3.1 Definition ...... 23 1.3.2 Hormonal Control of Intra-uterine Growth ...... 24 1.3.3 Outcomes for the SGA child ...... 25 1.3.4 Management of the SGA Child ...... 26 1.4 3-M syndrome ...... 27 1.4.1 Differential diagnosis of 3-M syndrome ...... 34 1.5 Identification of mutations in CUL7 in 3-M syndrome ...... 43 1.5.1 CUL7 gene and Mouse knockout models ...... 44 1.5.2 The Ubiquitination-Proteasomal System ...... 47 1.5.4 CUL7, apoptosis and p53 ...... 53 1.5.5 CUL7, the cell cycle and IGF-I signaling ...... 55 1.5.6 Expression and methylation of CUL7 in IUGR placental tissue ...... 56 1.6 OBSL1...... 60 1.7 Aims ...... 64 1.8 Key points ...... 65 Chapter 2: Materials and Methods ...... 66 2.1 Introduction ...... 67 2.2 Clinical data ...... 67 2.3 Statistical analysis ...... 67 2.4 Tissue and Cell Culture Procedures ...... 68 2.4.1 Skin biopsy technique and establishing fibroblast cell lines ...... 68 2.4.2 Routine growth culture and passaging ...... 68 2.4.3 Long term storage of cells ...... 69 2.4.4 Cell counting ...... 69 2.4.5 Generation of Cell Lysates ...... 69 2.4.6 GH and IGF-1 stimulation ...... 70 2.4.7 Generation of cell culture conditioned media ...... 70 2.4.8 WST-8 cell growth assay ...... 70 2.4.9 5-ethynyl-2'-deoxyuridine (EdU) incorporation ...... 70 2.4.10 Terminal dUTP nick end labelling (TUNEL) staining ...... 71 2.5 Protein based methods ...... 71 2.5.1 Bradford Assay of protein concentration ...... 71 2.5.2 Precipitation of protein from Conditioned cell culture media ...... 72

2 2.5.3 SDS polyacrylamide gel electrophoresis (SDS-PAGE) and Western Immunoblotting ...... 72 2.5.4 Stripping of Western Blots ...... 73 2.5.5 Measurement of IGF-2 in cell culture medium ...... 73 2.5.6 Measurement of serum IGF-2 and IGFBP-3 ...... 74 2.5.7 Immunoflourescence microscopy ...... 74 2.5.8 Cleaved Caspase-3 ELISA ...... 74 2.6 Nucleic Acid based techniques ...... 75 2.6.1 Extraction of DNA ...... 75 2.6.2 Extraction of RNA ...... 75 2.6.3 Measurement of DNA and RNA concentration ...... 75 2.6.4 Reverse Transcription ...... 75 2.6.5 Polymerase chain reaction ...... 75 2.6.6 Agarose gel electrophoresis ...... 76 2.6.7 Purification of DNA from PCR products ...... 76 2.6.8 DNA sequencing ...... 76 2.6.9 Quantitative Reverse Transcription Polymerase Chain Reaction (QPCR) ..... 77 2.7 Gene Expression Microarrays ...... 79 2.7.1 Preparation of RNA and hybridization to Affymetrix HU-133 plus 2.0 chip .. 79 2.7.2 Software and statistical analysis of gene expression microarrays ...... 79 2.8 Cellular Metabolomic Studies ...... 80 2.8.1 Metabolite Extraction ...... 80 2.8.3 Metabolome Statistical Analysis ...... 80 2.9 Fertilisation of Xenopus tropicalis oocytes and microinjection of Morpholino Oligonucleotides ...... 81 2.9.1 Obtaining Oocytes ...... 81 2.9.2 Obtaining Sperm...... 81 2.9.3 Fertilisation and Preparation for Microinjection ...... 82 2.9.4 Microinjection ...... 82 2.9.5 Embryo selection and husbandry ...... 83 2.10 Suppliers ...... 83 2.10.1 Antibodies Used ...... 84 2.11 Buffers and Solutions ...... 84 Chapter 3: Patients ...... 87 3.1 Introduction and Aims ...... 88 3.2 Patients with Cullin 7 mutations ...... 88 3.3 Patients with Obscurin-Like 1 mutations ...... 94 3.4 Patients with no identified mutation in OBSL1 or CUL7 ...... 107 3.5 Phenotype-Genotype comparison ...... 111 3.6 Response to treatment with recombinant human growth hormone ...... 119 3.7 IGFBP3 and IGF-I levels in 3-M syndrome patients ...... 121 3.9 Key Points ...... 122 Chapter 4: Functional studies on patient fibroblasts ...... 123 4.1 Introduction ...... 124 4.2 Potential Mechanisms of Growth Failure in 3-M syndrome ...... 125 4.2 Patient Fibroblast cell lines used in this study ...... 125 4.3 Hypothesis ...... 125 4.4 Aims and Objectives ...... 126 4.5 CUL7 – gene expression, protein expression and cellular localisation in 3-M syndrome fibroblasts ...... 126

3 4.6 OBSL1 – gene expression, protein expression and cellular localisation in 3-M syndrome fibroblasts ...... 132 4.7 p53 – gene and protein expression in 3-M syndrome fibroblasts ...... 140 4.8 Cyclin D1 – No evidence for accumulation in 3-M syndrome fibroblasts ...... 143 4.9 Cell proliferation in 3-M syndrome fibroblasts ...... 145 4.10 Apoptosis in 3-M syndrome fibroblasts ...... 148 4.11 IGFBP2, IGFBP3, IGFBP5 and IGFBP7 expression in 3-M syndrome ...... 152 4.12 IGF-1 stimulation in control and 3-M syndrome fibroblasts ...... 161 4.13 – GH signal Transduction in control and 3-M fibroblasts ...... 168 4.15 Key Points ...... 174 Chapter 5: Transcriptomic Studies ...... 175 5.1 Introduction ...... 176 5.2 Cell Lines used in the Transcriptomic Studies ...... 176 5.3 Introduction to Whole genome gene expression analysis ...... 177 5.4 Design of the Transcriptome Experiment ...... 178 5.5 Quality Control, Analysis Software Used and Initial Data Processing ...... 178 5.6 Probesets with differential expression between Control and 3-M syndrome fibroblasts ...... 183 5.7 Probesets with differential expression between Control and C7 fibroblasts .. 205 5.8 Probesets with differential expression between Control and OB fibroblasts . 216 5.9 Probesets with differential expression between Control and RA fibroblasts . 228 5.10 Summary of Microarray Studies ...... 238 5.11 Q-PCR Validation of Array findings 1 – IGF2 and H19 ...... 240 5.12 IGF-II levels in conditioned cell culture media and serum ...... 243 5.13 – Levels of CTCF in 3-M syndrome fibroblasts ...... 245 5.14 Q-PCR validation of Array Findings 2 – BEX1, LEP, IGFBP7, ZIC1, HOXC6, HOXA9, GPC6 ...... 247 5.15 – New Hypothesis for 3-M syndrome pathogenesis ...... 250 5.16 – Key points ...... 251 Chapter 6: Metabolomic Studies ...... 252 6.1 Introduction ...... 253 6.2 Cell Lines used in the Metabolomic Studies ...... 253 6.3 Metabolomic changes in 3-M cell lines compared to control ...... 255 6.3.1 Metabolomic fingerprint ...... 255 6.3.2 Metabolomic footprint ...... 259 6.4 Metabolomic changes in C7 cell line compared to control ...... 264 6.4.1 Metabolomic fingerprint ...... 264 6.4.2 Metabolomic footprint ...... 266 6.5 - Metabolomic changes in OB cell lines compared to control ...... 268 6.5.1 Metabolomic fingerprint ...... 268 6.4.2 Metabolomic footprint ...... 270 6.6 Metabolomic changes in RA cell lines compared to control ...... 272 6.6.1 Metabolomic fingerprint ...... 272 6.6.2 Metabolomic footprint ...... 274 6.7 Discussion ...... 276 6.8 Key Points ...... 277 Chapter 7: Modelling 3-M syndrome in the non-placental vertebrate Xenopus tropicalis ...... 278 7.1 Xenopus tropicalis ...... 279 7.2 Morpholino Oligonucleotides ...... 279

4 7.3 Identification of X. tropicalis OBSL1 ortholog and design of Morpholino Oligonucleotides ...... 281 7.4 Microinjection of Control Morpholino ...... 282 7.5 Injection of Morpholino Oligonucleotides targeted to alter splicing of xtObsl1 ...... 285 7.5.1 Injection of MO1 ...... 285 7.5.2 Injection of MO2 ...... 287 7.5.3 Injection of MO3 ...... 288 7.5.4 Injection of MO4 ...... 288 7.6 RT-PCR of xtObsl1 mRNA in uninjected and morpholino injected embryos ... 294 7.7 Discussion and Future Work Necessary to Confirm Initial Findings ...... 297 7.8 Key points ...... 298 Chapter 8: Discussion ...... 299 References ...... 306

Word Count 74,052

5 List of Figures

1.1. Clinical features of 3-M syndrome…………………………………….27 1.2. Height standard deviation score for 43 patients with 3-M syndrome due to mutations in CUL7…………………………………………....…33 1.3. Histopathological features of lung and placenta in 3-M and normal foetus………………………………………………………………………34 1.4. A child with typical facial features of Silver-Russell syndrome……...35 1.5. Characteristic facial features of Mulibrey nanism…………………….39 1.6. Proportionate short stature at the age of seven years and facial appearance at age of 13 years in a child with Bloom syndrome……42 1.7. Front and side view of a 13 year old boy with Seckel syndrome……43 1.8. The CUL7 gene consists of 26 exons encoding one transcript of and a protein of 1698 aa……………………………………………………...46 1.9. Cul7 -/- mice display intrauterine growth retardation and die at birth from respiratory distress……………………………………………..….47 1.10. The Ubiquitination-Proteasomal System…………………………...49 1.11. GH signal transduction……………………………………………….51 1.12. IGF-1 signal transduction…………………………………………….53 1.13. Putative mechanisms through which loss of CUL7 may lead to the growth impairment seen in 3-M syndrome…………………………….59 1.14. The OBSL1 gene comprises of 22 exons encoding three isoforms consisting of a four amino terminal domains, a central fibronectin domain and a variable number of carboxy terminal immunoglobulin domains……………………………………………………………………61 3.1 Facial phenotype with prominent ears, fleshy tipped nose, prominent ears and fleshy lips in family one…………………………………..……89 3.2 Schematic representation of the Cullin 7 gene and location of the mutations identified in Families 1-4……………………………………..93 3.3 Facial features and Prominent heels in the affected individual from Family Five………………………………………………………………...94 3.4 Clinical phenotype and pedigree in two affected siblings from family six………………………………………………………………………..….96 3.5 Growth chart from elder brother in family six…………………………..97

6 3.6 Growth charts from the affected individual in family eight…………..100 3.7 Clinical feature and family pedigree in two Egyptian brothers with a nonsense OBSL1 Mutation………………………………………….....103 3.8 Growth chart of youngest siblings from family twelve……………….105 3.9 Schematic representation of the OBSL1 gene and the location of the mutations found in families five to twelve……………………………..106 3.10 Growth chart from affected individual from family fourteen……..109 3.11 Clinical phenotype and growth chart for affected individual in family sixteen…………………………………………………………………….111 3.12 Height standard deviation score plotted against age patients with 3-M syndrome due to different gene mutations……………………...118 3.13 Weight standard deviation score plotted against age patients with 3-M syndrome due to different gene mutations……………………...118 3.14 Height and height velocity SDS before and after one year of GH therapy…………………………………………………………………....120 4.1 Expression of CUL7 mRNA in C7, OBF and RA fibroblasts……….128 4.2 Western Immunoblot for CUL7 in lysates generated from control fibroblasts and fibroblasts from a patient with CUL7 mutation (C7) and a patient with an OBSL1 mutation (OBF)…………………………..…129 4.3 Densitometric analysis of CUL7 in Western Immunoblots from lysates generated from Control, C7 and OBF fibroblasts………………...….130 4.4 CUL7 localises to the Golgi apparatus in skin fibroblasts with no mislocalisation in OBF fibroblasts……………………………………..131 4.5 Expression of OBSL1 mRNA in C7, OBF and RA fibroblasts……...135 4.6 Initial Western immunoblots for OBSL1………………………………136 4.7 Western immunoblots for OBSL1……………………………………..137 4.8 Western Immunoblots for OBSL1……………………………………..138 4.9 OBSL1 immunoflourescence in Control, C7 and OBF fibroblasts…139 4.10 Relative fold expression for TP53 in C7, OBF and RA fibroblasts………………………………………………………………...141 4.11 Western immunoblotting and densitometric analysis for levels of p53 protein in control, C7 and OBF lysates………………………..…142 4.12 Western immunoblotting and densitometric analysis for levels of Cyclin D1 protein in control, C7 and OBF lysates……………………144

7 4.13 Cell proliferation measured over 72 hours in control and 3-M syndrome fibroblasts by the WST-8 assay………………………...…146 4.14 Cell proliferation is significantly lower in 3-M syndrome fibroblasts than in control fibroblast measured by incorporation of EdU……….147 4.15 The percentage of cells undergoing apoptosis as measured by TUNEL staining………………………………………………………….151 4.16 ELISA for cleaved caspase-3 levels in control and 3-M patient fibroblasts……………………………………………………………..…152 4.17 Relative fold mRNA expression of IGFBP2 and IGFBP5 in 3-M syndrome fibroblasts……………………………………………………157 4.18 Western immunoblotting and densitometric analysis of IGFBP2 in precipitated protein from conditioned cell culture medium…….……158 4.19 Western immunoblot and densitometric analysis for IGFBP5 and –actin in fibroblast lysate for control and 3-M patient fibroblasts…159 4.20 Western immunoblotting and Densitometric analysis of IGFBP3 in precipitated protein from conditioned cell culture medium……….…160 4.21 Western immunoblotting and densitometric analysis of IGFBP7 in precipitated protein from conditioned cell culture medium………….161 4.22 Activation of IRS-1 following IGF-1 stimulation in control and C7 fibroblasts………………………………………………………………...165 4.23 Activation of IRS-1 following IGF-1 stimulation in control and OBF fibroblasts………………………………………………………………...166 4.24 Activation of AKT following stimulation with 100 ng/ml IGF-1 in control and C7 fibroblasts………………………………………………167 4.25 Activation of AKT following stimulation with 100 ng/ml IGF-1 in Control and OBF fibroblasts…………………………………………....168 4.26 Activation of MAPK following stimulation with GH at 200 ng/ml in control and C7 fibroblasts………………………………………………171 4.27 Activation of MAPK following stimulation with GH at 200 ng/ml in control and OBF fibroblasts…………………………………………….172 4.28 Activation of STAT5b following stimulation with GH at 200 ng/ml in control and C7 fibroblasts………………………………………………173

8 4.29 Activation of STAT5b following stimulation with GH at 200 ng/ml in control and OBF fibroblasts………………………………………….…174 5.1 Design of the whole Transcriptome Experiment……………………182 5.2 Principle component analysis of variance in the whole transcriptome data comparing 3-M and control fibroblasts…………………………183 5.3 Venn diagram for number of probesets up-regulated (defined as fold change >1.5 3M/control and expression level >50 in at least one cell line) for C7, OB and RA fibroblasts…………………………………..185 5.4 Venn diagram for number of probesets down-regulated (defined as fold change >-1.5 3M/control and expression level >50 in at least one cell line) for C7, OB and RA fibroblasts……………………………...185 5.5 IGF2 expression measured with qRT-PCR in C7, OBF, OBR and RA fibroblasts……………………………………………………………..…242 5.6 H19 expression measured with qRT-PCR in OBF, OBR, RA and C7 fibroblasts……………………………………………………………..…243 5.7 IGF-II concentration measured by ELISA is reduced in conditioned cell culture medium from 3-M syndrome fibroblasts compared to controls…………………………………………………………………...245 5.8 CTCF is increased in C7 and OBF cells but not RA cells…………..247 5.9 QRT-PCR validation of selected genes identified as being down- regulated in 3-M syndrome compared to control fibroblasts………..249 5.10 QRT-PCR validation of selected genes identified as being up regulated in 3-M syndrome compared to control fibroblasts………..250 6.1 Summary of changes in cellular energy metabolism in 3-M syndrome………………………………………………………………...263 7.1 Site of splice site morpholinos in xtObsl1………………………….…282 7.2 Trunk length and Intra-ocular distance measured at stage 50 (14 days) in uninjected and 10 ng control morpholino injected tadpoles…………………………………………………………………..285 7.3 Comparison of uninjected tadpoles and tadpoles injected with 10 ng MO1……………………………………………………………………….287 7.4 MO2 produces severely abnormal embryos with high mortality rates at doses of 2-10 ng……………………………………………………..….288

9 7.5 Light micrograph of an uninjected embryo and two growth retarded MO3 10 ng injected embryos (all embryos stage 50)……………….290 7.6 MO3 produces growth retarded but otherwise phenotypically normal embryos at 10 ng injection dose……………………………………….291 7.7 MO4 produces abnormal tadpoles with high mortality rates at doses above 2 ng……………………………………………………………….293 7.8 MO4 produces growth retarded but otherwise phenotypically normal embryos at 2 ng injection dose………………………………………...294 7.9 cDNA transcript of xtObsl1 amplified and the effects of MO1-4 on expected amplicon size…………………………………………………296 7.10 PCR of a fragment spanning exons 1-5 of xtObsl1 in cDNA generated from 5 stage 25 embryos from several groups………….297

10 List of Tables

1.1 Major causes of Short Stature…………………………………………………..23 1.2 Clinical Features in 3-M syndrome…………………………………………...... 31 1.3 Clinical features in SRS………………………………………………………....36 1.4 Diagnostic criteria for Mulibrey nanism………………………………………...40 2.1 Standard cycling conditions for PCR…………………………………………..76 2.2 TaqMan assays used in this project……………………………………………77 2.3 Standard QPCR Cycling conditions……………………………………………78 2.4 Primary Antibodies Used in this project……………………………………..85-6 2.5 Secondary Antibodies used during this project……………………………….86 3.1 Baseline Auxology in 22 patients from 16 families with 3-M syndrome…..113 3.2 Facial and radiological findings in 22 patients from 16 families with 3-M syndrome………………………………………………………………………...114 3.3 Non-facial clinical features in 22 patients from 16 families with 3-M syndrome………………………………………………………………………..115 3.4 Comparison of phenotype between genetic groups and between all patients in this study and a previously reported summary published 3-M case reports……………………………………………………………………………116 3.5 Serum IGFBP3 and IGF-I levels in five 3-M syndrome patients…………...121 5.1 dChip analysis of the microarray data………………………………………..180 5.2 Top 20 probesets with expression up-regulated in 3-M fibroblasts compared to control fibroblasts……………………………………………………………192 5.3 Top 20 probesets with expression down-regulated in 3-M fibroblasts compared to control fibroblasts…………………………………….…………199 5.4 Biological Process Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for 3-M compared to control…………………………………………………………………………....201 5.5 Molecular Function Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for 3-M compared to control…………………………………………………………………………….202 5.6 Cellular compartment Gene ontology terms over represented compared to background in the top 500 up-regulated probesets in 3-M compared to control…………………………………………………………………………….202 5.7 Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in 3-M compared to control…………………………………………………………………………….203

11 5.8 Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for 3-M compared to control ……………………………………………………………………………203 5.9 Molecular function gene ontology identified as being over represented compared to background in the top 500 down-regulated probesets in 3-M compared to control……………………………………………………………204 5.10 Cellular compartment Gene ontology terms over represented compared to background in the top 500 down-regulated probesets in 3-M compared to control…………………………………………………………………………….204 5.11 Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in 3-M compared to control…………………………………………………………………………….205 5.12 Top 20 probesets with expression up-regulated compared to background in C7 fibroblasts compared to control fibroblasts……………………………207 5.13 Top 20 probesets with expression down-regulated compared to background in C7 fibroblasts compared to control fibroblasts………….....209 5.14 Biological Process Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for C7 compared to control ………………………………………………………………………….211 5.15 Molecular Function Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for C7 compared to control……………………………………………………………………...... …212 5.16 Cellular compartment Gene ontology terms over represented compared to background in the top 500 up-regulated probesets in C7 compared to control……………………………………………………………………….….212 5.17 Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in C7 compared to control…………………………………………………………………………..213 5.18 Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for C7 compared to control…………………………………………………………………………..214 5.19 Molecular Function Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for C7 compared to control………………………………………………………………………….215 5.20 Cellular compartment Gene ontology terms over represented compared to background in the top 500 down-regulated probesets in C7 compared to control………………………………………………………………………….…215

12 5.21 Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in C7 compared to control………………………………………………………………………….…216 5.22 Top 20 probesets with expression up-regulated compared to background in OB fibroblasts compared to control fibroblasts……………………………218 5.23 Top 20 probesets with expression down-regulated compared to background in OB fibroblasts compared to control fibroblasts…………….220 5.24 Biological Process Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for OB compared to control…………………………………………………………………………....222 5.25 Molecular Function Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for OB compared to control………………………………………………………………………….…223 5.26 Cellular compartment Gene ontology terms over represented compared to background in the top 500 up-regulated probesets in OB compared to control…………………………………………………………………………....223 5.27 Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in OB compared to control…………………………………………………………………………….224 5.28 Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for OB compared to control…………………………………………………………………………….225 5.29 Molecular Function Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for OB compared to control………………………………………………………………………….…226 5.30 Cellular compartment Gene ontology terms over represented compared to background in the top 500 down-regulated probesets in OB compared to control…………………………………………………………………...……….227 5.31 Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in OB compared to control…………………………………………………………………………….228 5.32 Top 20 probesets with expression up-regulated compared to background in RA fibroblasts compared to control fibroblasts…………………………..230 5.33 Top 20 probesets with expression down-regulated compared to background in RA fibroblasts compared to control fibroblasts………….….232

13 5.34 Biological Process Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for RA compared to control……………………………………………………………………………234 5.35 Molecular Function Gene ontology terms over represented compared to background in the top 500 up-regulated probesets for RA compared to control………………………………………………………………………..….235 5.36 Cellular compartment Gene ontology terms over represented compared to background in the top 500 up-regulated probesets in RA compared to control…………………………………………………………………………...235 5.37 Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in RA compared to control……………………………………………………………………………235 5.38 Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for RA compared to control………………………………………………………………………….…236 5.39 Molecular Function Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for RA compared to control…………………………………………………………………………….237 5.40 Cellular compartment Gene ontology terms over represented compared to background in the top 500 down-regulated probesets in RA compared to control………………………………………………………………………….…237 5.41 Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in RA compared to control…………………………………………………………………………….238 5.42 Summary of top 20 up and down regulated probesets in each cell line group……………………………………………………………………………..240 5.43 Serum IGF-II levels in 3-M subjects and two non-3M syndrome patients…………………………………………………………………………...246 5.44 Validation of gene expression identified as being up or down regulated in the microarray…………………………………………………………………...251 6.1 Fingerprint Metabolites increased in 3-M syndrome compared to control..259 6.2 Fingerprint Metabolites decreased in 3-M syndrome compared to control…………………………………………………………………………….259 6.3 Footprint Metabolites increased in 3-M syndrome compared to control….264 6.4 Footprint Metabolites decreased in 3-M syndrome compared to control…264 6.5 Fingerprint Metabolites increased in C7 cells compared to control cells…266 6.6 Fingerprint Metabolites decreased in C7 cells compared to control cells...266

14 6.7 Footprint Metabolites increased in C7 cell conditioned media compared to control cell conditioned media………………………………………………....268 6.8 Footprint Metabolites decreased in C7 cell conditioned media compared to control cell conditioned media……………………………………………...….268 6.9 Fingerprint Metabolites increased in OB cells compared to control cells…270 6.10 Fingerprint Metabolites decreased in OB cells compared to control cells……………………………………………………………………………….270 6.11 Footprint Metabolites increased in OBSL1 cell conditioned media compared to control cell conditioned media………………………………….272 6.12 Footprint Metabolites decreased in OB cell conditioned media compared to control cell conditioned media………………………………………………272 6.13 Fingerprint Metabolites increased in RA cells compared to control cells……………………………………………………………………………….274 6.14 Fingerprint Metabolites decreased in RA cells compared to control cells……………………………………………………………………………….274 6.15 Footprint Metabolites increased in RA cell conditioned media compared to control cell conditioned media………………………………………………276 6.16 Footprint Metabolites decreased in RA cell conditioned media compared to control cell conditioned media………………………………………………276 7.1 Measurements of trunk length and eye distance at stage 50 (14 days) in embryos injected with 10 ng control morpholino oligonucleotide and uninjected embryos…………………………………………………………..…284 7.2 Trunk length and eye distance measured at stage 50 (14 days) in three experiments comparing uninjected tadpoles to tadpoles injected with 10 ng MO3……………………………………………………………...……………….289 7.3 Trunk length and eye distance measured at stage 50 (14 days) in uninjected tadpoles and tadpoles injected with 0.5 ng, 1 ng, and 2 ng of MO4……....292 7.4 Trunk length and eye distance measured at stage 50 (14 days) in three experiments comparing uninjected tadpoles to tadpoles injected with 2ng MO4………………………………………………………………………………292

15 Abstract

The University of Manchester Philip George Murray PhD A Clinical and Molecular Study of the Growth Disorder 3-M syndrome 2011

3-M syndrome (named after three authors who first described the condition) is an autosomal recessive condition characterised by pre- and post-natal growth impairment, facial dysmorphism and radiological features (slender long bones and tall vertebral bodies). It is caused by loss of function mutations in the Cullin 7 (CUL7) and Obscurin-like 1 (OBSL1) genes. CUL7 is a protein involved in ubiquitination (the process of targeted protein degradation) and OBSL1 is a putative cytoskeletal adaptor protein. The mechanisms through which loss of function mutations in OBSL1 or CUL7 lead to growth impairment is unclear but previous work suggests impaired placental function and altered insulin- like growth factor 1 (IGF-1) signaling as possibilities.

The overall aim of this study was to elucidate the mechanisms underlying growth impairment in 3-M syndrome. Initially phenotypic data was collected on a cohort of patients and a genotype-phenotype comparison was undertaken. Skin fibroblast cell lines were derived from four patients with 3-M syndrome and used to study growth hormone (GH) and IGF-1 signal transduction, cell proliferation and apoptosis. Subsequently a hypothesis generating approach to identify novel mechanisms underlying 3-M growth impairment was undertaken in whole transcriptome and metabolomic studies. In addition an animal model using morpholino oligonucleotide mediated knock down of OBSL1 in Xenopus tropicalis was developed to study the effects on growth in a non placenting vertebrate to determine if the growth impairment seen in 3-M syndrome is independent of placental function.

Cell proliferation was reduced in 3-M fibroblasts while apoptosis was not different from controls. No differences in GH signal transduction were identified but reduced activation of AKT following IGF-1 stimulation was identified in 3-M fibroblast cell lines. IGF2 was identified as the top downregulated probeset in 3-M fibroblasts compared to control in the whole genome transcriptome analysis. Metabolomic changes related to energy metabolism were identified in 3-M syndrome fibroblasts. Knock down of xtOBSL1 using two independent morpholinos resulted in growth impairment at embryonic stage 50, suggesting the growth impairment seen is at least in part independent of placental function.

These studies suggest impaired placental function is not a key component of the growth impairment in 3-M syndrome. Impairment of IGF-1 signal transduction and IGF2 silencing are likely to contribute to the growth impairment in 3-M syndrome. The mechanisms relating to this IGF2 silencing require further studies.

16 Declaration Patient data: where patient data is presented the patients have been previously included in other theses – they are collected together here for the first time. The work summarising the clinical data has not previously been submitted in any thesis.

Xenopus work: preliminary data on morpholino microinjection of Xenopus oocytes was presented in a thesis by Dr D Hanson (University of Manchester 2009).

No other portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

17 Copyright Statement I. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and she has given The University of Manchester certain rights to use such Copyright, including for administrative purposes.

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18 Acknowledgements

I would like to thank my supervisors Prof. Peter Clayton and Prof. Graeme Black for all their support from preparation of my MRC fellowhip application all the way through to the submission of this thesis. I had the great pleasure and benefits of working in two labs and I am most grateful for all the technical and moral support from both labs. From the Clayton lab – Amit Sud, Ajobola Omokanye, Mattea Clarke, Tessa Coulson, Andy Whatmore and a special thanks to Imogen Butcher. From the Black lab – Emma Hilton, Forbes Manson, Helen Spencer, Alex Waite, Geoff Maher, Alice Davidson and Dan Hanson.

Lastly can I thank my parents – Iain and Marilyn Murray – for all their support and encouragement.

Attributed Work

The following individuals contributed to the research conducted:

Emma Hilton – design of morpholino oligonucleotides and assistance with Xenopus work (microinjection and obtaining Xenopus oocytes and sperm)

Forbes Manson – assistance with Xenopus work (microinjection and obtaining Xenopus oocytes and sperm)

Patient sequencing of CUL7 and OBSL1 was undertaken by Dr D Hanson and Dr A Sud.

Chapter 1: Introduction

20 1.1 Overview There are approximately 645,000 children born in the UK each year. Using a definition of small for gestational age (SGA) as a birth weight more than 2.5 standard deviations below mean birth weight, there are approximately 16,000 SGA children born each year. Around 10% will fail with catch up growth over the first two years of life, leaving 1600 children who remain short at two years of age (Clayton et al., 2007). When followed into adulthood and compared to appropriate for gestational age controls, SGA children are shorter, have lower monthly income, more psychological problems and higher rates of cardiovascular disease and type II diabetes mellitus (Saenger et al., 2007). The causes of children being born SGA are wide and include maternal, placental and foetal causes but in a large number of cases there is no obvious cause. There are a small number of monogenetic causes for a child to be born SGA and experience poor post natal growth. These include the Russell Silver Syndrome, Mulibrey nanism, Microcephalic Osteodysplastic Primordial Dwarfism, Bloom Syndrome and 3-M syndrome in addition to other skeletal dysplasias.

This project focuses on 3-M syndrome, a disorder associated with pre- and post-natal impairment and normal intelligence. This is used as a model of the SGA child with poor postnatal growth to gain insights into the mechanisms which lead to growth impairment.

Huber et al (2005) identified mutations in the Cullin 7 (CUL7) gene in 29 families affected by 3-M syndrome. CUL7, the encoded protein, forms one component of an E3 ubiquitin ligase enzyme, a part of the ubiquitin- proteasomal system (UPS), the main pathway for targeted protein degradation within the cell. It is not clear how an abnormality in ubiquitination causes the clinical phenotype of 3-M syndrome. Recent work within our own laboratory using a small number of consanguineous families with 3-M syndrome but without mutations in CUL7 has identified pathogenic sequence variants in the gene encoding obscurin like-1

21 (OBSL1), a cytoskeletal protein with multiple immunoglobulin domains whose function is unknown.

1.2 Normal Growth and Short Stature Growth is the process of increase in size by accretion of tissue and can be observed in the cellular environment, organ systems and the whole body. Accretion of tissue is a balance of hyperplasia (increase in cell number), hypertrophy (increase in cell size) and apoptosis (programmed cell death) (Patel and Clayton, 2005). Human growth can be divided into three distinct phases: infancy, childhood and puberty (Patel and Clayton, 2005). Optimal growth is dependent upon the absence of chronic disease, emotional stability, adequate nutrition, normal endocrine function and the absence of defects impairing cellular and bone growth. Infantile growth is mainly dependent upon adequate nutrition as well as GH while childhood and pubertal growth are influenced mainly by the GH-IGF-1 axis and sex steroids respectively.

Short stature is a term defined for each individual by their growth performance relative to their genetic population and parental height. One set of criteria are (Patel and Clayton, 2005): 1. Height below 0.4th Centile 2. A significant discrepancy between their height centile and mid parental height centile 3. Height curve crossing two centile lines downward Causes of short stature are listed in Table 1.1

Table 1.1 Major causes of short stature Familial short stature Constitutional delay in growth and puberty Psychosocial: physical, emotional or sexual abuse, neglect Chronic systemic disease of any cause Endocrine disorders; hypothyroidism, growth hormone deficiency, Cushing syndrome Small for gestational age with inadequate catch up growth Genetic syndromes and Skeletal Dysplasias: Chromosomal – Turner syndrome, Down syndrome Autosomal dominant – Noonan syndrome, achondroplasia Autosomal recessive – 3-M syndrome, Bloom syndrome, X-linked – Aarskog syndrome

1.3 The Small for Gestational Age Infant One common cause of short stature is to be born small for gestational age and fail with catch up growth. Currently the label of SGA is applied to these children and in many there is no clear cause for their short stature.

1.3.1 Definition Multiple definitions of small for gestational age (SGA) have been used, including a birth weight/crown-heel length less than the 10th, 5th or 3rd centiles (Jiang et al., 2004, McCowan et al., 2005, Soto et al., 2003, Lee et al., 2003). The commonest definitions used in clinical practice are birth weight less than the 10th centile (used mainly by neonatologists) or more than 2 SD below mean, equivalent to the 2.3rd centile (used by paediatric endocrinologists). Consensus guidelines have recommended the use of the latter definition (Clayton et al., 2007). Birth length has been used to

23 define SGA but in many countries including the UK this measurement is rarely taken as it is technically more difficult than weight measurement. In a study of 3650 healthy full term newborns (Albertsson-Wikland and Karlberg, 1994) 3% were found to have a birth weight <-2 SD and 3.9% a birth length SDS <-2. 1.5% of infants had birth weight and length SDS <- 2. By two years of age 88% of the SGA children had experienced catch up growth to height >-2 SD. By excluding premature infants in whom there is a high incidence of growth impairment, this study may have underestimated the prevalence of the SGA infant.

Whichever definition of SGA is used, an accurate assessment of gestational age is essential. Ideally this should be done with a first trimester ultrasound scan. Intra-uterine growth retardation (IUGR) is a term often incorrectly used synonymously with SGA. IUGR refers to growth restriction in utero while SGA refers to the size at birth. It is possible for a foetus to suffer from growth restriction without this being sufficient to result in the child being born SGA.

1.3.2 Hormonal Control of Intra-uterine Growth In utero the main hormonal influences on foetal growth are IGF-I, IGF-II and insulin. IGF-1 and IGF-II levels correlate to size at birth (Gluckman et al., 1983, Verhaeghe et al., 1993). That involvement of insulin in this process is underlined by large for gestational age infants born to diabetic mothers. The key role of IGF-II is highlighted by the Silver Russell and Beckwith Wiedemann syndromes which both involve alterations in methylation of chromosome 11p15 which affect IGF2 transcription. Low IGF2 transcription and a SGA phenotype is seen in Silver Russell Syndrome (SRS) while elevated IGF-II levels and overgrowth are seen in Beckwith Wiedemann syndrome (Gicquel et al., 2005, Sparago et al., 2004). IGF-I and IGF-II circulate bound to IGF-binding proteins (IGFBPs) of which there are six. 99% of the circulating IGF-I/II is bound to the IGFBPs which regulate the availability of the free IGF (the active component). Small size at birth is correlated with higher IGFBP-1 levels and lower IGFBP-3 levels (Lassarre et al., 1991, Osorio et al., 1996,

24 Verhaeghe et al., 1993). In mice, deletion of Igf1 or Igf2 results in a birth weight reduction of 40% compared to wild type mice while reductions of 55% of birth weight is found by deleting the Insulin-like growth factor 1 receptor (Igf1r) gene (Baker et al., 1993). Combined deletion of Igf1 + Igf1r or Insulin-like growth factor 2 receptor (Igf2) + Igf1r leads to a 70% reduction in birth weight and death from respiratory distress at birth (Liu et al., 1993). Deletion of the Igf2r leads to an increase in size to 130% of wild type. It therefore appears that in mouse the IGF2R has a role in negatively regulating the availability of IGF-II.

GH appears to have little influence on pre-natal growth with GH deficient infants having normal birth weight. In the post-natal period GH assumes a role as a major influence on growth via the GH-IGF1 axis. SGA infants have higher GH and lower IGF-1 levels than appropriate for gestational age (AGA) controls, suggesting that they may have relative GH insensitivity (Leger et al., 1996). Dynamic testing of the GH-IGF axis in later childhood falls within the normal range. This may, however, represent the failure of these tests to identify subtle forms of GH insensitivity. IGF-I and IGF-II continue to have a key role in growth. Serum IGF-1 levels are significantly lower in SGA infants who do not achieve catch up growth compared to those who did achieve catch up growth (Leger et al., 1996). Children with deletions or loss of function mutations in the IGF-1 or IGF1R genes display severe post-natal growth impairment along with pre-natal growth restriction (Abuzzahab et al., 2003, Woods et al., 1996). The major binding protein in the postnatal period is IGFBP-3 which forms a complex with the IGFs and the acid labile subunit (ALS). Mutations in the IGFBPs have not been implicated in post-natal growth impairment but total absence of functional ALS has been demonstrated to result in mild growth impairment (Hwa et al., 2006).

1.3.3 Outcomes for the SGA child In the neonatal period being born SGA is associated with increased risk of death, necrotising enterocolitis, hypotension and hypoglycaemia

25 (Bernstein et al., 2000). In later childhood those born SGA have lower cognitive performance than appropriate for gestational age children (Low et al., 1992, Paz et al., 1995, Taylor and Howie, 1989). In adolescence and later life children born SGA are at higher risk of developing hypertension, type 2 diabetes, hyperlipidaemia and cardiovascular disease (Barker, 1991b, Barker, 1991a, Barker, 1991c, Hales et al., 1991, Hinchliffe et al., 1992).

90% of infants born SGA will experience catch up growth within the first two years of life resulting in a height >-2 SD (Karlberg and Albertsson- Wikland, 1995). Children who are both preterm and SGA experience slower catch up growth (Karlberg and Albertsson-Wikland, 1995). Overall although 90% of SGA children experience spontaneous catch up growth (to >-2 SD) the final adult height is around 1 SD lower than the general population (Leger et al., 1997). Failure of catch up growth (i.e. final height <-2 SD) is associated with greater adverse neurological and cardiovascular outcomes in later life (Larroque et al., 2001, Leger et al., 1997, Leon et al., 1998).

1.3.4 Management of the SGA Child The only licensed treatment to improve height in the SGA child is recombinant human growth hormone (rhGH). The license from the European Agency for the Evaluation of Medicines allows treatment for children who have at start of treatment: 1. Age 4 years or over 2. Height SDS <-2.5 SD and >1SD below midparental height SDS 3. Growth velocity <0 SD for age The recommended starting dose for rhGH is 35 µg/kg/day. Treatment under the SGA licence is only indicated after exclusion of other causes of short stature including chronic disease, endocrinopathies such as hypothyroidism, emotional deprivation and genetic syndromes associated with poor growth. Overall rhGH is effective and produces an increase in height SDS >1 (Dahlgren and Wikland, 2005, de Zegher and Hokken- Koelega, 2005, Van Pareren et al., 2003). Improved outcomes are

26 associated earlier initiation of treatment with rhGH earlier and the use of higher doses of rhGH (de Zegher and Hokken-Koelega, 2005). Although most of the increase in height SDS occurs over the first two years of treatment, discontinuation is not recommended as this leads to catch down growth (de Zegher et al., 2000).

1.4 3-M syndrome 3-M syndrome was first described by Miller et al in 1975 and since then there have been a handful of cases reported in the literature(Cantu et al., 1981, Fehlow, 2006, Feldmann et al., 1989, Flannery, 1989, Hennekam et al., 1987, Hennekam et al., 1994, Marik et al., 2002, Meo et al., 2000, Miller et al., 1975, Mueller et al., 1992, Temtamy et al., 2006, van der Wal et al., 2001, Winter et al., 1984, Van Goethem and Malvaux, 1987). 3-M syndrome is an autosomal recessive condition characterised by intrauterine growth retardation with postnatal growth failure, relatively large head, facial dysmorphism, prominent heels and normal intelligence (see Figure 1.1). The main features found on skeletal survey are said to be slender long bones and tall vertebrae (Huber et al., 2011).

Figure 1.1 – Clinical features of 3-M syndrome. A) Facial features - upturned fleshy tipped nose, prominent full lips and broad forehead. B) Prominent heel. C) Tall vertebral bodies. D) Slender long bones.

27 The initial report described four children in two families one of which was consanguineous (Miller et al., 1975). Both families had immigrated to the United States, one from Belgium and one from Sicily. The first affected individuals were a brother and sister aged 12 and 11 years of age respectively. The boy was born at term weighing 2.159kg (-3.6 SD) and birth length of 38 cm (-6.9 SD) with a grossly normal placenta and at 12 years remained prepubertal with a height of 109 cm (-5.3 SD) and head circumference 51 cm (-1.8 SD). An arginine-stimulated growth hormone test demonstrated a subnormal peak growth hormone of 6.2 µg/l. His sister was also born at term weighing 1.864 kg (-6.1 SD), length of 39 cm (-4.2 SD) and at 11 years was 108 cm tall (-4.7 SD) with head circumference 51 cm (-1.1 SD). Upper to lower segment ratios were normal in both patients. The 11 year old girl had an arginine stimulation test with a peak GH of 21.2 µg/l. Both were treated with pituitary-derived growth hormone at 2 mg alternate days for 6 months, but had a poor response.

The second set of two affected siblings was a brother and sister aged 7.75 and 4.5 years respectively. This family was non-consanguineous and the two had an unaffected older brother and sister. The affected boy was born at term weighing 2.1 kg (-3.8 SD) with length of 41cm (-5.7 SD). The placenta was reported to be small. At 6 weeks of age he developed pyloric stenosis requiring surgical correction. At age 7.75 years his height was 98 cm (-4.6 SD) with head circumference 53.5 cm (+0.7 SD). His 4.5 year old sister was born at term weighing 1.81 kg (-4.4 SD) and with a length of 40 cm (-5.6 SD). At 4.5 years she was 80 cm (-5.3 SD) in height with a head circumference of 50 cm (+0.1 SD). Both siblings had normal endocrine function testing including assessment of the GH-IGF axis. Upper to lower segment ratios were normal for both children.

In all cases intelligence was normal. Other phenotypic features present in all cases included prominent ears, short neck with prominent trapezius, high square shoulders, short thorax, pectus deformity (excavatum or carinatum), transverse grooves of anterior chest, winging of scapula and

28 hyperextensible joints. A summary of clinical features found and their estimated relative prevalence in all reported cases is Table 1.2.

The facial features described in all four children included a triangular shape, a broad flat malar region, pointed lower segment with a prominent mouth. A number of orodental features were found including absence of downturned corners of mouth, v shaped dental arch, anterior crowding of teeth, malocclusion and numerous dental caries.

Along with the radiological findings of slender long bones and tall vertebrae additional findings on skeletal survey included relatively small pelvis, flaring of iliac wings, small ischium and pubis, small obturator foramen, pseudoepiphysis of 2nd metacarpal and retarded bone age. Bone age delay ranged from 2 to 3.1 years.

A subsequent report of children with 3-M syndrome was the first to note the fleshy tipped nose and also described children with an increased upper to lower segment ratio (Spranger et al., 1976). This group also included one child whose birth weight was 2.4 kg (-2.9 SD) and one at 2.5 kg (-2.64 SD) demonstrating a relatively normal birth weight but severe post-natal growth retardation. Weight of the 2.4 kg boy at 5 years was 11.8 kg (-4.4 SD) and with a height of 84 cm (-5.1 SD) – relatively slim for his height (BMI SDS 1.0). The finding of a raised upper to lower segment ratio was confirmed in a later report of two siblings with 3-M syndrome one of whom had a hypospadias in addition to 3-M (Feldmann et al., 1989).

An association with intracerebral aneurysm was postulated in a report (Mueller et al., 1992) which described a boy born at 850g (-3.1 SD) at 32 weeks gestation with severe postnatal growth impairment who subsequently collapsed at the age of 8.5 years. He was found on CT scan to have blood in the third, fourth and lateral ventricles with acute hydrocephalus. Cerebral angiography demonstrated a left posterior inferior cerebellar artery aneurysm with a sessile intracavernous carotid

29 aneurysm on the right side. It was suggested that screening of children with 3-M syndrome for this condition may be useful due to the lower mortality rates with elective surgery. To date there have been no further reports of intracerebral aneurysms in 3-M patients.

30 Table 1.2 Clinical Features in 3-M syndrome. Adapted from Temtamy et al (2006). Not all clinical features are commented on in each case report and thus the denominator for frequency is variable. Feature Frequency in reported literature Dolicocephaly 23/35 Triangular face 32/36 Frontal bossing 28/36 Midface hypolasia 31/36 Fleshy tip nose 33/36 Upturned nares 29/37 Long philtrum 27/34 Malocclusion of teeth 7/10 Delayed teeth erruption 7/13 High arched palate 7/10 Full everted lips 31/37 Pointed full chin 30/36 Prominent ears 15/34 Short neck 32/38 Winged scapulae 13/25 Square shoulders 26/26 Short thorax 26/33 Transverse chest groove 15/19 Pectus deformity 18/34 Hyperlordosis 27/31 Scoliosis 5/13 Hypermobility of joints 21/33 5th finger clinodactyly 25/32 Prominent heels 23/27 Pes planus 7/14 Slender long bones 32/34 Tall vertebral bodies 12/29 Spina bifida occulta 12/24 Narrow pelvis 20/27

31 1.4.1 Gloomy Face Syndrome The Gloomy Face syndrome was described in 1991 and was thought to be similar to but distinct from 3-M syndrome (Le Merrer et al., 1991). They described nine children from four affected families, three of whom were consanguineous. Gloomy face syndrome was thought by the authors to represent a distinct syndrome due to the absence of radiographic findings and a round rather than triangular shaped face. They further suggested that previous case reports of 3-M syndrome included children whose actual diagnosis was gloomy face syndrome (all cases of Feldmann et al, fourth case of Winter et al and third case of van Goethem and Mavaux). The identification of CUL7 mutations in both 3-M syndrome and Gloomy Face syndrome supports the view that Gloomy Face and 3-M syndrome are the same condition (Huber et al., 2005).

1.4.2 Yakut Short Stature Syndrome A cohort of 43 individuals from a population isolate in North East Siberia were reported to all have a nonsense mutation in CUL7 (Maksimova et al., 2007). The affected individuals had pre and post natal growth restriction with normal intelligence, normal tests of endocrine function and a facial appearance consistent with 3-M syndrome. Give the shared genetic and clinical findings it is clear Yakut Short stature syndrome is 3- M syndrome. They reported the most extensive height data available for 3-M syndrome patients with 39 patients measured on more than two occasions each. Final height was between -4 and -8 SDS (see Figure 1.2). 18 patients had a history of respiratory distress at birth with 11 requiring mechanical ventilation. In five families there was a history of neonatal deaths with the affected babies having a similar phenotype to the short family members. Histopathological examination of a 26 week foetus with 3-M phenotype demonstrated reduced cartilaginous tissue in the medium and large bronchi with increased numbers of chorionic villus and syncytial knots in the placenta (see Figure 1.3).

Figure 1.2 – Height standard deviation score for 43 patients with 3-M syndrome due to mutations in CUL7. 39 patients were measured on more than two occasions. Final height is between -4 and -8 SDS. Figure from Maksimova, N et al. J Med Genet 2007; 44:772-778. Permission for reproduction has been granted by the BMJ publishing Group, the original publishers.

Figure 1.3 – Histopathological features of lung and placenta in 3-M and normal foetus. A) and B) demonstrate bronchus in 3-M syndrome lung (A) and normal lung (B). Reduced cartilaginous tissue is seen (indicated by arrow). C) 3-M and D) normal placental histology demonstrate numerous syncytial knots (dashed arrows) (dashed arrows) and reduced lacunar space (arrows) in the 3-M placenta. Figure from Maksimova, N et al. J Med Genet 2007; 44:772-778. Permission for reproduction has been granted by the BMJ publishing Group, the original publishers.

1.4.1 Differential diagnosis of 3-M syndrome

There is a wide differential diagnosis for the primordial dwarfing conditions including Dubowitz syndrome, Rubenstein-Taybi syndrome and Coffin-Siris syndrome but these can be easily differentiated from 3-M syndrome by the presence of microcephaly and mental retardation. The differential diagnosis is with Silver-Russell syndrome (SRS), Mulibrey nanism and Bloom syndrome with microcephalic osteodysplastic primordial dwarfism (MOPD) type II and Seckel syndrome other potential diagnoses, although the latter are also associated with microcephaly.

34 Silver Russell Syndrome SRS (OMIM 180860) is a sporadic disorder characterised by intra and extra uterine growth failure with a distinctive facial appearance (triangular shaped face, broad forehead, small pointed chin and wide, thin, mouth – see figure 1.4) (Silver et al., 1953, Russell, 1954). Affected individuals are of normal or mildly impaired intelligence. For a diagnosis of SRS, the patient must exhibit five key features (Price et al., 1999): 1. Birth weight <-2SD from population mean corrected for age and gender 2. Poor postnatal growth with height <-2SD from mean at diagnosis 3. Preservation of OFC 4. Classical facial features 5. Skeletal asymmetry Additional clinical features may be present and are listed in table 1.3

Figure 1.4 – A child with typical facial features of Silver-Russell syndrome. The face is triangular in shape with a broad forehead and a pointed chin. The mouth is thin and the nasal bridge prominent. Figure taken from Price, S M et al. J Med Genet 1999;36:837-842. Permission for reproduction has been granted by the original publishers the BMJ publishing Group.

Table 1.3 – Clinical features in SRS Growth Birth Weight <-2 SD Poor Postnatal Growth Height SD <-2SD at presentation Preservation of OFC Facial Features Triangular shaped face Small pointed chin Broad forehead Thin wide mouth Genitourinary Hypospadias Posterior urethral valves Inguinal hernia Gastrointestinal Gastro-oesophageal reflux Poor feeding in Infancy Fasting hypoglycaemia Other Hemihypertrophy Developmental Delay Delayed bone age Clinodactyly Syndactyly of second and third toes Hemihypertrophy Camptodactyly + distal arthrogryposis

The genetic causes of SRS are heterogeneous but involve uniparental disomy of genes located on chromosome 7p13-p11.2, or 11p15 (Eggermann et al., 2005, Eggermann et al., 2006, Hitchins et al., 2001b). The best characterised mechanism is related to loss of paternal methylation of the H19 differentially methylated region (DMR) located on chromosome 11p15 (Gicquel et al., 2005). H19DMR controls expression

36 of IGF2 and H19 (a maternally-expressed noncoding RNA). When H19DMR is unmethylated it binds to CCCTC binding factor which blocks access to IGF2 promoters. Normally the maternal allele is unmethylated and the paternal allele is methylated. Loss of paternal methylation leads to binding of both alleles with CTCF and suppression of IGF2 expression. This mechanism is thought to be responsible for around 50% of SRS cases (Eggermann et al., 2010).

Studies of uniparental disomy (UPD) of chromosome 7 were stimulated by work demonstrating that mice with UPD of chromosome 11 (syntenic with human chromosome 7) exhibited abnormal growth. Mice with paternal UPD of chromosome 11 were 30% larger than wild type littermates while those with maternal UPD were 30% smaller (Cattanach and Kirk, 1985). Screening of a cohort of SRS children for maternal UPD chromosome 7 identified 9 affected individuals out of a total of 98 patients (Kotzot et al., 1995, Eggermann et al., 1997, Preece et al., 1997). The location of the region on chromosome 7 responsible for SRS was refined by a small number of patients (Joyce et al., 1999, Monk et al., 2000) to a 2.2 Mb interval containing only growth factor receptor-bound protein 10 (GRB10) and cordon bleu (COBL) genes. Of these genes only GRB10 is imprinted with paternal expression in the brain and maternal expression in all other tissues (Blagitko et al., 2000), however, no pathogenic changes have been identified in any of the 76 SRS patients screened (Hitchins et al., 2001a, Yoshihashi et al., 2000).

The loci on chromosomes 7 and 11 account for around 60% of children with SRS. The genetic cause in the remaining 40% is unclear but a number of additional patients with chromosomal abnormalities and a SRS phenotype have been reported. Chromosomes 1, 8, 15, 17, 18 and X have been implicated and additional SRS genes may be located there (van Haelst et al., 2002, Schinzel et al., 1994, Wilson et al., 1985, Ramirez-Duenas et al., 1992, Punnett et al., 1973, Li et al., 2004).

37 Differentiation between SRS and 3-M syndrome can be difficult but there is often asymmetry/hemihypertrophy in SRS.

Mulibrey Nanism Mulibrey (muscle-liver-brain-eye) nanism (OMIM 253520) is an autosomal recessive disorder caused by mutations in tripartile motif 37 (TRIM37, locus 17q22-23) (Avela et al., 2000, Avela et al., 1997). Affected individuals have severe intra- and extra-uterine growth failure with normal intelligence, characteristic facial appearance (triangular face, high broad forehead and low nasal bridge), high pitched voice, hypotonia, hepatomegaly, congestive heart failure due to constrictive pericarditis and cutaneous naevi flammei (Karlberg et al., 2004) (see figure 1.5). Radiographic findings include slender long bones with a relatively thick cortex and fibrous dysplasia. The incidence of Mulibrey nanism is 1:40,000 in the Finnish population, very few cases having been reported outside Finland. Diagnostic criteria are listed in table 1.3. Feeding difficulties affect around one third of babies in the newborn period and by the age of two over one half of affected children were failing to thrive. Upper respiratory tract infections were common with one half of the children diagnosed with pneumonia and one quarter suffering at least one episode of respiratory failure, induced by infection, by two years of age. Psychomotor development is reported as normal or mildly impaired. Mean birth length SDS in a Finnish cohort was -3.1. The growth failure was progressive with a mean height SDS at two years of -4.4 (Karlberg et al., 2004). Treatment with recombinant human growth hormone resulted in a modest increase in final height of +0.6 SD (Karlberg et al., 2007).

Figure 1.5 - Characteristic facial features of Mulibrey nanism; triangular face, low nasal bridge, high and broad forehead, and scaphocephaly with occipitofrontal bossing. Photograph from Karlberg, N et al. J Med Genet 2004; 41:92-9, reproduced with permission of the original publishers, the BMJ Publishing Group.

TRIM37 is a 979 amino acid protein and is a member of the RING B-box coiled-coil family of zinc finger proteins. It is widely expressed, localises to the peroxisome and has activity as a RING finger E3 ubiquitin ligase but the mechanism by which mutations in this gene lead to growth failure are unknown (Kallijarvi et al., 2005, Kallijarvi et al., 2006). Twelve mutations in TRIM37 have been identified in Mulibrey nanism (Avela et al., 2000, Jagiello et al., 2003, Doganc et al., 2007, Hamalainen et al., 2004). Of the twelve pathogenic mutations described 11 are nonsense mutation with one missense mutation (c.965G>T,p.Gly322Val) which results in abnormal localisation of TRIM37 within the cell (Hamalainen et al., 2004).

Table 1.4 Diagnostic criteria for Mulibrey nanism. For the diagnosis, three major signs with one minor sign are required, or two major signs with three minor signs

Major signs Growth failure (A or B or C) A) Small for gestational age (SGA) lacking catch up growth B) Height in children 2.5 SDS below population mean for age C) Height in adults 3.0 SDS below population mean

Characteristic radiological findings (A or B) A) Slender long bones with thick cortex and narrow medullar channels B) Low and shallow (J-shaped) sella turcica

Characteristic craniofacial features: Scaphocephaly, triangular face, high and broad forehead, low nasal bridge and telecanthus

Characteristic ocular findings: Yellowish dots in retinal mid peripheral region

Mulibrey nanism in a sibling

Minor signs Peculiar high pitched voice Hepatomegaly Cutaneous naevi flammei Fibrous dysplasia of long bone

40 Bloom Syndrome Bloom syndrome (OMIM 210900) is an autosomal recessive condition characterised by pre and post natal growth restriction and a thin face with malar hypoplasia (see figure 1.6). Other features include sun-sensitive telangiectasia, hypo- and hyperpigmented skin, predisposition to malignancy (generalised increased incidence for all types of malignant disease) and chromosomal instability. Incidence is 1:160,000 but it is rarely found outside the Ashkenazi Jewish population. Most affected individuals die in the third decade of life from malignancy. The diagnosis is made by a combination of clinical features (no formal diagnostic criteria) and demonstration of chromosomal instability or direct gene sequencing. The mutation affects the BLM gene which encodes a member of the RecQ DNA helicase enzymes which are responsible for separating complementary strands of DNA in processes such as DNA replication, transcription, genetic recombination and DNA repair (Mohaghegh and Hickson, 2001). Again the mechanisms underlying the short stature are not known but the affected gene is located at chromosome 15q26.1 near to the IGF-1 receptor at 15q25.3.

Microcephalic Osteodysplastic Dwarfism type II Microcephalic osteodysplatic dwarfism type II (MOPD II) is another autosomal recessive condition of severe intra- and extra-uterine growth impairment with affected individuals being of around 100 cm height at adulthood. Other characteristic features include normal intelligence, a high pitched voice, abnormal dentition, disproportionate shortening forearms and legs, prominent eyes and a prominent nose (Hall et al., 2004). MOPD II is caused by nonsense mutations in the pericentrin gene (Rauch et al., 2008). Pericentrin is a giant 370 kDA coiled protein that localises to the centrosomes. Lack of pericentrin results in abnormalities of the mitotic spindle (Rauch et al., 2008). It is likely this is therefore a disorder of impaired cell proliferation.

41 Seckel syndrome Seckel syndrome is phenotypically very similar to MOPD type II with severe pre and post-natal growth restriction, prominent nose, prominent eyes, micrognathia and microcephaly (see figure 1.7). In contrast to MOPD type II affected individuals have moderate to severe learning difficulties. Seckel syndrome is caused by a splice mutation ataxic telangiectasia and Rad-3 related protein and nonsense mutations in pericentrin (Griffith et al., 2008, O'Driscoll et al., 2003).

Figure 1.6 – Proportionate short stature (left) at the age of seven years and facial appearance at age of 13 years in a child with Bloom syndrome. Sun sensitive rash is present over cheeks, bridge of nose and upper lip. Lower lip is encrusted. Photograph reproduced from Balk S, Atkas D. Cancer Genetics and Cytogenetics 1999; 111:45-8 with permission from the publisher, Elsevier Ltd.

Figure 1.7 – Front and side view of a 13 year old boy with Seckel syndrome. Short stature, microcephaly and a prominent nose can be seen. Figure reproduced from Ucar B et al. Clinical Dysmorphology. 13(1):53-55, January 2004 with permission from the publisher Wolters Kluwer Health.

1.5 Identification of mutations in CUL7 in 3-M syndrome Homozygosity mapping was used by (Huber et al., 2005) in seven consanguineous families with 3-M syndrome to identify a 3.84 Mb region located at chromosome 6p21.1 which linked to the condition. This technique uses consanguineous families as a fraction of the genome of a child from consanguineous parents would be expected to be homozygous (e.g. 1/16 of the genome in a child from first cousins). These areas of homozygosity would be expected to be randomly distributed throughout the genome except at a common disease locus for the condition being studied (Sheffield et al., 1995).

43 Within the 3.84 Mb region of chromosome 6 identified there were a large number of candidate genes. Haplotype analysis narrowed the region to a 0.47 Mb region containing 10 genes. Sequencing in four affected children of distinct ethnic origin excluded serum response factor, p53 associated parkin like cytoplasmic protein and male enhanced antigen one, but sequencing of CUL7 identified mutations in these individuals. Subsequent sequencing in additional affected individuals identified 25 distinct CUL7 mutations in 29 families affected by 3-M syndrome. Of the 25 mutations 19 were nonsense mutations and 6 were missense mutations.

In a second report (Huber et al., 2009a) an additional 19 mutations in CUL7 in 3-M patients were described bringing the total number of known mutations to 44. Of these 44 mutations 10 are missense mutations and 34 nonsense mutation including seven mutations predicted to affect splicing of pre-mRNA. 17 of the mutations (~40%) lie within the Cullin domain responsible for binding to ROC1 (see figure 1.8).

1.5.1 CUL7 gene and Mouse knockout models The cullin 7 gene is composed of 26 exons and encodes a protein of 1,698 amino acids. CUL7 (also called p185 or p193) was originally identified as a binding partner of the simian virus 40 large T antigen (Tsai et al., 2000). The cullin family consists of CUL1-CUL7, pARC and anaphase promoting complex 2. They all contain highly conserved cullin and DOC domains and are thought to have a scaffold role in assembling E3 ubiquitin ligase enzymes with Skp and Fbx proteins (Dias et al., 2002). CUL7 binds to Skp1 and Fbx29 (also called Fbxw8) to form an E3 ubiquitin ligase enzyme. Cul7 knockout mice have intra uterine growth retardation and small placentas with an abnormal vascular structure (see Figure 1.9). The mice have dermal haemorrhages and die of respiratory distress at birth (Arai et al., 2003). Cul7 -/- mouse embryonic fibroblasts display impaired growth and undergo senescence at around passage 6. An Fbxw8 (Fbx29) null mouse has also been studied (Tsutsumi et al., 2007). These mice display severe pre- and post-natal growth impairment

44 again with small placentas and an abnormal trophoblast layer. They have poor respiratory drive with 70% dying soon after birth.

Tsunematsu et al (2006) also performed whole genome gene expression studies on Cul7 -/- mouse embryos. They identified up regulation of Igfbp1 – 2.2 fold in heterozygous embryos compared to wild type embryos. No data was given on the fold change in Fbxw -/- embryos compared to controls. The finding of upreguated Igfbp1 expression was confirmed with quantitative PCR but the authors were unable to detect IGFBP1 protein in mouse embryonic fibroblast lysates (Tsunematsu et al., 2006). The authors identified a significant increase in secreted IGFBP2 from Fbxw8 -/- and Cul7 -/- mouse embryonic fibroblasts but no differences in levels of IGFBP3, IGFBP4 and IGFBP5. The alteration in levels of IGFBP2 did not appear to be due to ubiquitination as neither CUL7 or FBXW8 bound to IGFBP2 and incubation of the Cul7 -/- and Fbxw8 -/- mouse embryonic fibroblasts with proteasomal inhibitors did not alter the accumulation of IGFBP2.

The only other cullin known to be involved in human disease is CUL4B where mutations cause an X-linked mental retardation syndrome with central obesity, hypogonadism, seizures and relative macrocephaly (Zou et al., 2007). Stature is short but within the normal range (final adult height mean on 5th centile).

DOC Domain Cullin Domain

1 aa 588 1120 1698 Figure 1.8 – The CUL7 gene consists of 26 exons encoding one transcript of and a protein of 1698 aa. CUL7 mutations in 3-M syndrome are present throughout the gene but with a preponderance for the Cullin domain which is responsible for ROC1 binding (mutations taken from Huber et al 2005, 2009a). 46

Figure 1.9 – Cul7 -/- mice display intrauterine growth retardation and die at birth from respiratory distress. A) Reduced embryonic and placental size B) Grossly reduced alveolar space in the Cul7 -/- mice resulting in death at birth. Figure reproduced from Arai T Proc Nat Acad Sci 2003 9895-60 in accordance with the copyright holder’s (National Academy of Sciences) policy (http://www.pnas.org/site/misc/rightperm.shtml).

1.5.2 The Ubiquitination-Proteasomal System 3-M syndrome is an example where a defect within the UPS leads to growth failure. The existence of a non-lysosomal pathway for intracellular protein degradation was identified by the demonstration that rabbit reticulocytes (terminally differentiated cells that lack any lysosomes) could degrade abnormal haemoglobin (Rabinovitz and Fisher, 1964). Two groups independently isolated a soluble cell free preparation from reticulocytes which had the capacity to degrade abnormal haemoglobin (Hershko A, 1978, Etlinger and Goldberg, 1977). This non-lysosomal pathway turned out to be the UPS. The ubiquitin molecules as well as the three main classes of enzymes in the UPS were isolated from the reticulocyte cell free preparation.

47 The UPS is now thought to be main pathway for targeted protein degradation within the cell and plays a role in a large number of diverse cellular processes including the cell cycle, control of signal transduction, modulation of the immune processes and cell differentiation (Kravtsova- Ivantsiv and Ciechanover, 2011). There are two main steps in protein degradation via the UPS: 1. Attachment of multiple ubiquitin molecules to the target protein 2. Degradation of the target protein. In most instances this is in the S26 proteasome but can also involve the lysosome.

Attachment of the ubiquitin molecule to the target protein occurs via a three step process. The first step is activation of ubiquitin by the E1 enzyme (ubiquitin activating enzyme) where ATP hydrolysis is used to form a high energy bond between the C-terminal glycine of ubiquitin and a cystine residue of the E1 enzyme (Ciechanover et al., 1982). The activated ubiquitin molecule is then transferred to an E2 enzyme (ubiquitin conjugating enzyme) (Hershko et al., 1983, Schwartz and Ciechanover, 2009). From the E2 enzyme the ubiquitin molecule can be directly transferred to the substrate protein which is bound to an E3 enzyme (ubiquitin protein ligase) (Hershko et al., 1983). An alternative pathway is for transfer of the ubiquitin molecule to the E3 enzyme prior to attachment to the substrate protein. The first ubiquitin molecule binds to a lysine residue of the substrate protein via its C-terminal domain. A polyubiquitin chain forms by linkage of new activated ubiquitin molecules to a lysine residue on the previous conjugated ubiquitin molecule. The final step in the ubiquitination systems is degradation of the polyubiquitinated target protein in the S26 proteasome (Hough et al., 1986, Waxman et al., 1987, Kravtsova-Ivantsiv and Ciechanover, 2011, Schwartz and Ciechanover, 2009) (see figure 1.10).

A single E1 enzyme exists while there are multiple E2 and E3 enzymes. Specificity within the system is provided by the very large number of E3 enzymes.

S26 Target proteasome Protein

Lys Ub Ub Ub Ub E3

Ub Cys Ub Ub

E2 Ub Ub Ub Ub E1 ATP AMP + PPi Figure 1.10 The Ubiquitination-Proteasomal System. A ubiquitin molecule is first activated by E1, a ubiquitin activating enzyme and then transferred to the E2 ubiquitin conjugating enzyme. The E2 enzyme and the target protein are bound to an E3. The E2 enzyme then transfers the ubiquitin molecule to the target protein either directly or via the E3 enzyme. Once polyubiquitinated the target protein is sent to the S26 proteasome for degradation yielding peptides and free ubiquitin molecules.

The S26 proteasome has two subunits – a 19S and 20S subunit (Ciechanover et al., 2000, Driscoll and Goldberg, 1990, Hoffman et al., 1992, Navon and Ciechanover, 2009). The 19S subunit has a regulatory function while the 20S subunit is the main site of protein degradation and consists of four stacked rings – two central β rings and two distal α rings. Each α and β ring consists of seven subunits. The sites for proteolytic cleavage are on the β rings. The 19S subunit has three main roles: recognition of ubiquitinated proteins, unfolding of the protein and opening a passage in the α ring through which the proteins can enter the central chamber where degradation takes place.

49 1.4.3 GH-IGF signal transduction and the UPS Given the known importance of the GH-IGF1 axis in human growth and that 3-M syndrome is in some cases due to mutations within a gene encoding a component of the UPS, this leads to an investigation of the interactions between the UPS and the GH-IGF axis. The GH molecule contains two binding sites, site one has a high affinity and site two low affinity and both binding sites interact with the same region of the GHR (Strous et al., 2004). Binding of both of the GH molecule’s binding sites to two separate GHRs results in GHR dimerisation and leads to GH signal transduction. The initial step is a conformational change in the GHR bringing two janus kinase two (Jak2) proteins into close proximity which facilitates transphosphorylation of tyrosine residues in the kinase domain of Jak2. Jak2 then phosphorylates tyrosine residues on the GHR and signalling molecules. There are four main pathways for GH signal transduction (se Figure 1.11) (Lanning and Carter-Su, 2006): 1. The signal transducers and activators of transcription (STAT) proteins are recruited via their SH2 domain to the phosphorylated GHR (STAT5a and 5b) or to Jak2 (STAT’s 1 and 3) and are then phosphorylated and homo- or heterodimerise with other STAT proteins and translocate to the nucleus. In the nucleus they bind to DNA promoter sequences activating transcription of several genes including c-fos and interferon-gamma-activated-sequence (GAS) like response element. 2. Jak2 binds to the Src homology domain of Shc which leads to phosphorylation of Shc and activation of the mitogen activated protein kinase (MAPK) cascade. This pathway activates the STAT’s as well as cytoskeletal proteins and transcription factors such as c-Jun and c-Myc. 3. Jak2 phosphorylates the insulin receptor substrates (IRS-1, 2 and 3) which then activate phosphatidylinositol 3 kinase (PI3-kinase) inducing translocation of the GLUT4 glucose transporter to the cell membrane. 4. Binding of GH to the GHR leads to activation of protein kinase C (PKC) via phospholipase C. Activated PKC stimulates lipogenesis,

50 c-fos expression and increases intracellular calcium levels by activating type 1 calcium channels. The mechanism of activation of phospholipase C is unknown but is independent of Jak2.

Figure 1.11 GH signal transduction Binding of GH to two GHRs leads to activation of JAK2 which in turn activates the MAPK cascade, STAT5b and IRS-1. Binding of GH to two GHRs also activates PKC via a mechanism independent of JAK2.

Downregulation of GH signalling is also achieved by a several different mechanisms (Flores-Morales et al., 2006). The tyrosine phosphatase SHP-1 binds to and dephosphorylates Jak2 in response to GH. GH stimulation also induces tyrosyl phosphorylation of transmembrane glycoprotein signal regulatory protein ,SIRPalpha1, which recruits and enhances phosphorylation of SHP-2. SHP-2 dephosphorylates SIRPalpha1, Jak2 and the GHR. Activating mutations within PTPN11, which encodes SHP-2, result in another short stature syndrome, Noonan

51 syndrome (Tartaglia et al., 2001), whilst deactivating mutations result in LEOPARD syndrome (Kontaridis et al., 2006). The suppressors of cytokine signalling (SOCS) proteins SOCS1, SOCS2, SOCS3 and CIS (cytokine inducible SH2 domain containing protein) are induced by GH via the STAT proteins. SOCS1 inhibits Jak2 activity, SOCS3 prevents Jak2 association with the GHR while CIS and SOCS2 compete with the STAT proteins for binding to phosphotyrosine residues in the c-terminal region of the GHR.

The IGF-1R is composed of two extracellular α subunits and two transmembrane β subunits. Ligand binding sites are in the α subunits while the β subunit contains three domains – a juxtamembrane domain, which is responsible for recruiting the major signaling proteins, a tyrosine kinase domain, which has an essential role in the catalytic activity of the receptor, and a carboxy terminal domain (Dupont et al., 2003). Following ligand binding the IGF-1R recruits and phosphorylates the members of the insulin receptor substrate family of proteins (IRS-1, -2. -3, -4) as well as Shc (see figure 1.12). Activation of Shc by IRS-1 leads to activation of the MAPK pathway (Oldham and Hafen, 2003). The IRS proteins activate PI3K via its p85 regulatory subunit leading to activation of Akt which acts to phosphorylate BAD, inhibiting apoptosis and to activate mTOR leading to cell survival and growth.

The UPS in known to be involved in several components of the GH signal transduction system. The presence of an intact ubiquitination system is required for GHR endocytosis but ubiquitination of the GHR itself is not required as replacement of all the lysine residues within the GHR with arginine has no effect on endocytosis (van Kerkhof et al., 2002). An intact UPS is required for signalling via the STAT proteins (Strous et al., 1997). Degradation of the downregulatory molecules SHP- 1 and SHP-2 are dependent on the UPS and a C-terminal domain called the SOCS-box present in SOCS1, SOCS2 and CIS binds to the elongin B/C complex which interacts with a cullin 2 containing E3 ubiquitin ligase (Strous et al., 2004).

Figure 1.12 – IGF-1 signal transduction. Binding of IGF-1 leads to phosphorylation of the IGF1R and in turn IRS-1. Activation of IRS-1 then leads to increased activity in the MAPK cascade via Shc and activation of AKT via PI3K. IGF-1 signal transduction results in cell survival, growth and reduced apoptosis.

1.5.4 CUL7, apoptosis and p53 Initial work on CUL7 focused on its potential interaction with p53, its role in the cell cycle and in oncogenesis. When ectopically expressed, CUL7 increased cellular proliferation in an osteosarcoma cell line (U2OS cells) which are p53 positive but had no effect on cellular proliferation of a p53 deficient cell line (Andrews et al., 2006). CUL7 is known to bind to p53 and deletion of the p53 binding domains (the N terminal 680 amino acids) resulted in loss of CUL7’s ability to induce cellular proliferation. CUL7 may have a role in antagonising p53 function as knockdown of CUL7 using siRNA augments p53 mediated inhibition of cell cycle progression

53 while ectopic expression of CUL7 inhibited p53 induction and function in cells with DNA damage induced by doxycyclin (Jung et al., 2007).

CUL7 is located in the cytoplasm, whereas p53 is located in both the nucleus and cytoplasm with constant shuttling between compartments. Possible mechanisms for antagonism of p53 involve ubiquitination and subsequent degradation of p53 or by binding to and sequestering p53 in the cytoplasm. Andrews et al (2006) demonstrated only monoubiquitination of p53 by CUL7 in an in vitro assay while Jung et al (2007) found no evidence for ubiquitination of p53 by CUL7 in an in vivo assay. Furthermore ectopic expression of CUL7 did not sequester p53 in the cytoplasm of U20S cells (Andrews et al., 2006). The mechanism through which CUL7 antagonises p53 function remains unknown.

CUL7 is known to inhibit Myc-potentiated apoptosis via a p53 dependant pathway (Kim et al., 2007) and incubation of cells ectopically expressing CUL7 along with c-Myc increased colony formation when the cells were cultured under apoptotic conditions. Colony formation was not increased by ectopic CUL7 when the cells were cultured under growth promoting conditions. Knockdown of CUL7 in the presence of N-Myc reduced colony formation in SHEP cells (a neuroblastoma cell line lacking N-Myc). This data lead to the proposal that CUL7 is an antiapoptotic oncogene.

Much of the data generated using ectopic expression of CUL7 in U20S cells and by CUL7 knockdown using siRNA is contradicted by data from a group using a dominant negative CUL7 mutant overexpressed in murine ES derived cardiomyocytes. A dominant interfering mutant CUL7 truncated after 1152 amino acids increased colony growth of NIH-3T3 cells (Pasumarthi et al., 2001). DNA extracted from these cells after incubation with MMS (an agent that promotes DNA damage and apoptosis) demonstrated no evidence of intranucleosomal cleavage leading to the suggestion that truncated CUL7 had an antiapoptotic effect. Co-expression of mutant p53 (blocks p53 mediated apoptosis) with the truncated CUL7 had a strong prosurvival effect on embryonic stem cell

54 derived cardiomyocytes which had been treated with E1A (an adenoviral E1A oncoprotein which stimulates both cell proliferation and rapid apoptosis) (Pasumarthi et al., 2001). Transgenic mice expressing the dominant negative CUL7 in heart tissue demonstrated increased cardiomyocyte DNA synthesis compared to normal control mice following ligation of the left coronary artery (Nakajima et al., 2004). Further work by the same group expressing this dominant negative CUL7 in U2OS cells demonstrated that the dominant negative CUL7 reduced MG132 and etoposide induced apoptosis (Dowell et al., 2007). The original data from which the “dominant negative” truncated CUL7 were developed, consisted of expressing the full length and truncated CUL7 proteins in 3T3 cells and performing a colony growth assay. The truncated CUL7 was determined to be dominant negative on the basis that it stimulated growth while the full length inhibited growth. The authors also stated that these results were confirmed by siRNA knockdown of CUL7 but this data has not been published. I believe the original results are incorrect and the “dominant negative” CUL7 functions in a similar manner to the full length protein. If this is correct most of this group’s results would be in keeping with other groups work.

Fbxw8 -/- mouse embryonic fibroblasts display growth arrest after passage five or six (Tsunematsu et al., 2006). Crossing of Fbxw +/- mice with TP53 -/- to generate Fbxw8-/- TP53 -/- embryos identified that the growth arrest seen in the mouse embryonic fibroblasts was reversed by loss of p53 (Tsunematsu et al., 2006). The embryo phenotype of growth restriction, abnormal placenta and neonatal lethality was, however, not reversed by loss of p53.

1.5.5 CUL7, the cell cycle and IGF-I signaling The insulin receptor substrate-1 (IRS-1) was identified as a substrate of the CUL7 containing E3 ligase using knockdown of CUL7 and FBXW8 in a human breast carcinoma cell line. Furthermore Cul7 -/- mouse embryonic fibroblasts demonstrated increased IRS-1 levels along with

55 increased activation of IRS-1’s downstream signalling molecules AKT and ERK (Xu et al., 2008). IRS-1 is a component of the signalling pathway of IGF-1 but it is not clear why increased signaling via this pathway results in growth impairment rather than increased growth. In contrast to the increased activation of Akt, activation of the IGF1R following IGF-1 stimulation is decreased in Cul7 -/- and Fbxw8 -/- mouse embryonic fibroblast compared to control fibroblasts (Tsunematsu et al., 2006).

Cyclin D1 has been identified as a target of the FBXW8 containing E3 ligase (Okabe et al., 2006). Cyclin D1 transcription is stimulated by mitogenic signaling via the MAPK pathway and accumulation results in progression of cells through the cell cycle from G1 to S-phase. Accumulation of cyclin D1 was seen following knockdown of Fbxw8 with siRNA or with transfection of a dominant negative FBXW8 (Okabe et al., 2006). In vitro ubiquitination experiments identified that FBXW8 was able to ubiquitinate phosphorylated cyclin D1 but it was able to do so with a Skp-Cullin-Fbx complex containing either CUL7 or CUL1. Knockdown of CUL7 or FBXW8 also resulted in accumulation of cyclin D.

1.5.6 Expression and methylation of CUL7 in IUGR placental tissue Gascoin-Lachambre et al (2010) examined expression of cullins 1, 4A, 4B and 7 in normal placentas and placentas from fetuses with IUGR. They identified increased expression of each of the Cullins in IUGR placentas but particularly CUL7 which was up to 10 fold overexpressed (Gascoin-Lachambre et al., 2010). Using a bioinformatic approach they identified a putative promotor site for the transcription factor SP1 upstream of CUL7 and identified a modest upregulation (~2 fold) in CUL7 mRNA following expression of SP1 in a choriocarcinoma cell line (JEG- 3). Overall SP1 mRNA levels were 6 fold upregulated in IUGR placental tissue. It is not clear from this study whether or not abnormalities in cullin levels are driving poor placental function and abnormal growth as the study did not examine changes in protein levels of any of the Cullins. Lack of CUL7 is associated with abnormal placentation in the Cul7 -/-

56 mouse (Arai et al., 2003). It therefore remains possible that the Cullins may be reduced by a post-translational mechanism and that this subsequent lack of cullins results in the abnormal placentation and IUGR with the rise in CUL7 mRNA being a partially compensatory response. It is also possible that the Cullins play no direct role in initiating the placental disease and the changes seen are a purely secondary compensatory response.

Gascoin-Lachambre et al (2010) also examined methylation of 18 consecutive CpG dinucleotides in the CUL7 promotor and while they identified hypermethylation in placentas from fetuses with IUGR secondary to pre-eclampsia, hypomethylation was identified in placentas from fetuses with idiopathic IUGR. This is discordant from the CUL7 gene expression studies where CUL7 was overexpressed in IUGR placentas irrespective of aetiology.

Further data on the role of CUL7 in placental function comes from work identifying its role in inducing epthelial-mesenchymal transition (EMT) (Fu et al., 2010). Extravillous trophoblast cells undergo EMT prior to infiltration of the endometrium and anchoring of the placenta. Fu et al identified several lines of evidence implying CUL7 played an important role in this process:  Placental cell lines highly expressing CUL7 have a fibroblast/mesenchymal cell morphology and expressed vimentin and N-cadherin, while those cells expressing low levels of CUL7 displayed a epithelial morphology and expressed E-cadherin (but not vimentin or N-cadherin)  Overexpression of CUL7 in JEG-3 cells (human choriocarcinoma cell line) induced a change in morphology to the mesenchymal/fibroblast morphology, increased cell invasion and migration and led to downregulation of E-cadherin and upregulation of vimentin and N-cadherin. These effects were reversible with administration of the proteasomal inhibitor MG132.

57 The main results in this paper focused on using JEG-3 cells, a choriocarcinoma cell line. Knockdown of CUL7 using siRNAs in other placental cell lines produced only a partial effect with some changes in morphology in one cell line, no changes in morphology in a second cell line, and a small increase in E-cadherin levels. Care must be taken in extrapolating data from an inherently abnormal cell line to normal physiology. Nevertheless these results provide further evidence that CUL7 plays an important role in placental development and function.

There are therefore a number of putative mechanisms through which loss of CUL7 may lead to short stature. These are summarized in Figure 1.13.

Figure 1.13 - Putative mechanisms through which loss of CUL7 may lead to the growth impairment seen in 3-M syndrome. 59 1.6 OBSL1 Within our own research group we identified 25 children with a clinical diagnosis of 3-M syndrome who, however, did not have mutations in CUL7. 10 of these children came from consanguineous families with several affected members. Homozygosity mapping linked one of these families to a 13Mb region on chromosome 2 containing over 115 known and putative genes. The addition of a second family and use of highly polymorphic microsatellite markers enable the locus to be refined to a 5.9Mb region of chromosome 2. Sequencing of genes within this region led to the discovery of mutations within OBSL1 in 10 patients with non- CUL7 3-M syndrome (Hanson et al., 2009). Subsequently another group also reported OBSL1 mutations in a cohort of 13 families with non-CUL7 3-M syndrome (Huber et al., 2009b) (mutations are summarized in Figure 1.14). Huber et al (2009b) identified seven nonsense and one missense mutation. Two mutations were common to both studies – c.1273insA and c.1359insA.

OBSL1 was identified in a search for genes related to obscurin (a giant 800kDa multifunctional protein with a structural role in striated myofibrils and myocytes) using a genetic sequence database (GenBank). The OBSL1 gene is located on chromosome 2q35, contains 22 exons and has a genomic span of 25kbp (Geisler et al., 2007). There are three different products produced by alternative splice sites termed OBSL1 A, B or C with molecular masses of 230, 130 and 170 kDa respectively. These products contain a variable number of carboxy-terminal immunoglobulin domains, a central fibronectin domain and four amino terminal immunoglobulin domains. All the identified mutations occur in the first eight exons of OBSL1. One potential explanation for this is that for the patient to develop 3-M syndrome all three isoforms of OBSL1 have to be affected to cause the disease. Thus mutations in exons 1-9 would result in 3-M syndrome but mutations elsewhere would leave a normal OBSL1B isoform which is sufficient to prevent the development of 3-M syndrome.

Figure 1.14 – The OBSL1 gene comprises of 22 exons encoding three isoforms consisting of a four amino terminal domains, a central fibronectin domain and a variable number of carboxy terminal immunoglobulin domains. In 3-M syndrome patients all identified mutations are in the first eight exons. Thus, as OBSL1B is encoded by exons 1-10, it is likely that all 3 isoforms of the protein have to be affected for patients to develop 3-M syndrome. Of the 14 identified mutations 13 are nonsense mutations and one (c.2086_2088dupGGC) is a missense mutation. 61 OBSL1A is highly expressed in heart with weaker expression in skeletal muscle and testis while OBSL1B is widely expressed with highest expression in heart and placenta (Geisler et al., 2007). In cardiac myocytes OBSL1 was located in the intercalated disks, perinuclear region and over the M and Z lines (Geisler et al., 2007). On the basis of its localisation it has been suggested that OBSL1 functions as a cytoskeletal adapter linking cytoskeletal elements to each other, the nuclear envelope and to complexes within the cell membrane.

OBSL1 has been identified as a binding partner of myomesin and titin (Fukuzawa et al., 2008), Both of these proteins are involved in anchoring of myosin filaments at the M-band in myocytes. Overexpression of the binding site of OBSL1 for titin and myomesin results in mislocalisation of obscurin, a process which has been implicated in several hereditary myopathies (Fukuzawa et al., 2008). Patients with 3M syndrome with nonsense mutations in OBSL1 have some signs of muscular disease including winged scapulae, scoliosis and hyperlordosis. The patients, however, do not have any symptoms of muscular disease such as muscle fatigue, weakness, difficulties with walking, running, jumping, swallowing or activities of daily living. The binding sites for myomesin and titin are within Ig3 and Ig1 domains of OBSL1 but titin and myosin can also bind to Ig1 and Ig3 of obscurin and this duplication of function may explain why loss of OBSL1 does not lead to significant symptoms. Although scoliosis can be a significant medical problem and may lead to respiratory difficulties and require complex surgery there have been no reported cases of a child with 3-M syndrome requiring spinal surgery.

Mutations in OBSL1 have also been associated with alterations in mRNA levels of IGFBP2 and IGFBP5 (Huber et al., 2009b). Studying two patient fibroblast cell lines with OBSL1 mutations (one missense and one nonsense), Huber et al identified reduced IGFBP2 mRNA levels in both cell lines, 50 fold increased IGFBP5 transcription in the missense cell line but a decrease in IGFBP5 mRNA levels in the cell line with a nonsense mutation. The finding of decreased IGFBP2 expression is apparently in

62 contrast to previous work in mouse embryonic fibroblast where IGFBP2 levels were increased in cell culture media (Tsutsumi et al., 2007). Neither Tsutsumi et al or Huber et al examined both IGFBP2 gene expression and protein levels. It is therefore possible that IGFBP2 protein levels are increased and that the reduction in gene expression seen is a response to IGFBP2 accumulation. The difference in results may also be due to the differences in samples used – Tsutsumi et al used mouse embryonic fibroblast and mouse embryos while Huber et al used postnatally derived human fibroblasts.

In summary there is evidence that OBSL1 has a role as a structural protein interacting with titin and myomesin but it is unclear how this would alter growth. Furthermore as children with 3-M syndrome do not display symptoms of muscle disease it is unclear if loss of these interactions has any functional significance. The only other functional data on OBSL1 indicates it regulates expression of IGFBP5 and IGFBP2. It is not clear whether these gene expression changes are associated with changes in the levels of the respective proteins or whether they represent a pathological pathway impairing growth or the cellular response to improve growth.

63 1.7 Aims The overall aim of this project was to investigate the mechanisms causing growth impairment in 3-M syndrome. In order to address this aim the following hypothesis driven and non-hypothesis driven approaches have been taken. 1. A cohort of 3-M syndrome patients was collected to study the phenotype of the condition and to determine if any genotype- phenotype relationship exists 2. In vitro studies using patient derived fibroblast cell lines to examine whether mutations in 3-M syndrome patients affect cell proliferation, apoptosis, GH and IGF1 signal transduction. 3. Whole transcriptome and metabolomic studies on patient derived fibroblast cell lines. 4. Develop an animal model of 3-M syndrome in the non-placental vertebrate Xenopus tropicalis. This would allow assessment of the contribution of placental function to the early growth impairment seen in 3-M syndrome as well as creating a biological model of 3- M syndrome which can be easily studied.

64 1.8 Key points  Being born small for gestational age with failure of postnatal catch up growth is common and results in significant short and long term morbidity and mortality  3-M syndrome is a rare autosomal recessive condition in which children are born small for gestational age and have poor postnatal catch up growth  Elucidating the mechanisms of growth impairment in 3-M syndrome may give insight into the mechanisms resulting in growth failure in non-3M SGA children  3-M syndrome is caused by mutations in the genes encoding CUL7 and OBSL1  CUL7 is a component of the ubiquitination system, the main pathway for targeted protein degradation in the cell. Loss of CUL7 is known to result in o Accumulation of cyclin D1 in cancer cells o Accumulation of IRS-1 and increased activation of Akt o Increased apoptosis o Impaired placental growth and function  OBSL1 is a giant putative cytoskeletal protein. It binds to other giant muscle proteins – obscurin and titin. Its role in growth is very unclear but loss of OBSL1 is known to modulate expression of IGFBP2 and IGFBP5.

Chapter 2: Materials and Methods

66 2.1 Introduction A wide variety of methods have been used In this project and they are summarized in this chapter. As with any study into human disease the starting point is the patients, which are described in detail. Much of the work presented here is based on skin fibroblasts cell lines, which have been derived from four patients. A number of techniques were used to study these cell lines including western blotting, quantitative PCR, immunoflourescence and cell proliferation/apoptosis studies. These are described in detail. A more complex systems biology approach using microarrays to study gene expression and gas chromatography mass spectrometry to study the cellular metabolome. Finally the use of morpholino oligonucleotides to create an animal model of 3-M syndrome is described.

2.2 Clinical data Patient data presented in this thesis was collected under approval from the Central Manchester and Manchester Children’s Hospital NHS Foundation Trust Research Ethics Committee. Informed consent was taken prior to the collection of blood or skin samples either from the patient or parent.

2.3 Statistical analysis All data were entered into Microsoft Excel version 11 (Microsoft, USA) and SPSS version 15 (SPSS Inc, USA). Data are presented as mean + SD or median (range). Comparisons between groups were made with students independent samples t-test, one sample t-test and ANOVA with Tukey HSD post-hoc analysis when data were normally distributed. For non-normally distributed data comparisons were made using the Mann Whitney U test, Wilcoxon signed ranks test and the Kruskall Wallis test.

67 2.4 Tissue and Cell Culture Procedures

2.4.1 Skin biopsy technique and establishing fibroblast cell lines Parental consent (and where appropriate consent from the patient) was obtained prior to any procedure. 5% EMLA topical anaesthetic cream (AstraZeneca limited, UK) was applied to an area of the forearm for 1 hour. Using aseptic technique a 2 mm punch biopsy was obtained with a Stiefel Biopsy Punch (Stiefel laboratories, Maidenhead, UK). The biopsy sample was immediately stored in growth medium (GM) consisting of Duilbecco’s Modified Eagles Medium (DMEM) supplemented with 10% foetal bovine serum (Invitrogen, Paisley, UK), 50 units/ml penicillin, 50 μg/ml streptomycin, 2 mM glutamine and 2.5 μg/ml amphoteracin B (Invitrogen, Paisley, UK). The biopsy was then transferred to a 25 cm2 cell culture flask. This flask was inverted so that the biopsy remained on the upper surface with cell culture media below the biopsy specimen.

After 48 hours in standard cell culture conditions (37°C, 5% CO2) the cell culture flask was inverted again so that the biopsy, now firmly adhered to the cell culture flask, was covered in cell culture medium. The media was changed every 3 days and the specimen observed for growth of fibroblasts out from the biopsy.

Once approximately 25% of the surface of the 25 cm2 cell culture flask was confluent with fibroblasts they were removed from the flask using trypsin-EDTA (PAA, Yeovil, UK) and split into an appropriate number of 25 cm2 cell culture flasks.

2.4.2 Routine growth culture and passaging Fibroblasts were routinely cultured in GM in 75 cm2 tissue culture flasks. Upon reaching confluency the cells were split into an appropriate number of 75 cm2 tissue culture flasks by trypsinisation. After removal of GM the cells were washed once with sterile Dulbecco’s Phosphate Buffered saline (D-PBS) (Invitrogen, Paisley, UK) before 3 ml of 1x Trypsin-EDTA solution (PAA, Yeovil, UK) was added and the fibroblast incubated at 37 C for 5 minutes. Once the cells were non-adherent 10 mL or GM was added to neutralize the trypsin, the cell solution was then spun at 5000

68 rpm for 5 minutes in a 15 mL Falcon tube and the supernatant removed. The cell pellet was then resuspended in 1 mL GM and seeded into new 75 cm2 tissue culture flasks with 10 ml GM.

2.4.3 Long term storage of cells Fibroblasts were routinely preserved by storage in liquid nitrogen. A cell pellet was generated as described above. This pellet was resuspended in 4 ml freezing medium – GM supplemented with 10% Foetal bovine serum and 10% dimethyl sulphoxide. The freezing medium and cell mix was transferred to four cryovials (Greiner bio one, UK) to be stored at -80 °C overnight prior to storage in liquid nitrogen.

2.4.4 Cell counting A cell pellet was obtained as described previously and resuspended in 1 mL GM. 10 μl of this cell suspension was added to a chamber of a Hycor glastic slide (Hycor, UK) and the number of cells per μl calculated as per the manufacturer’s instruction.

2.4.5 Generation of Cell Lysates Once fibroblasts reached 75% confluency the GM was removed and they were placed in serum free (SF) media for 24 hours. SF media consisted of DMEM supplemented with 50 units/ml penicillin, 50 μg/ml streptomycin, 2 mM glutamine and 2.5 μg/ml amphoteracin B (Invitrogen, Paisley, UK). The SF media was then removed and the cells washed in ice cold D- PBS. The cells were then scraped into 1 ml of ice cold D-PBS and this cell suspension spun for 30 seconds at 13,000 rpm. The D-PBS was then removed and the pellet resuspended in cell lysis buffer with protease inhibitors (EDTA mini, Roche, UK) and phosphatase inhibitors (Phosphatase inhibitor cocktail 1 and Phosphatase inhibitor cocktail 2, Sigma-Aldrich, UK) added to the cell lysis buffer as per the manufacturer’s instructions. After incubation for 1 hour at 4 °C cell lysate supernatant was assayed for protein concentration (as per section 2.4.1) and stored at -80 °C.

69 2.4.6 GH and IGF-1 stimulation To examine the effects of GH stimulation on normal and 3-M fibroblast cultures 200 ng/ml GH was added to SF media in 75 cm2 cell culture flasks 75% confluent with cells for 15, 30 and 60 minutes (for GH) prior to generation of cell lysates for immunoblotting. IGF-1 was added to SF media in 75 cm2 cell culture flasks 75% confluent with cells for 5, 15 and 60 minutes.

2.4.7 Generation of cell culture conditioned media Cells were seeded into new 75 cm2 cell culture flasks as per section 2.4.2 and incubated overnight in standard condition in GM. 24 hours after seeding the GM was removed, the cells washed twice with D-PBS and then incubated for 7 days in 10 ml SF media.

2.4.8 WST-8 cell growth assay Cells were seeded at a density of 1000 cells/cm2 in 96 well cell culture plates (Corning, USA) in 100 µl GM. 24, 48 and 72 hours after seeding 10 μl of WST-8 was added to each well and the plate incubated for 2 hours at 37C before measuring absorbance at 450 nm on a U.V. spectrophotometer (Bio-Rad Benchmark microplate reader, BioRad UK). For each cell line at each time measurement a minimum of 8 independent wells were examined in on three separate occasions.

2.4.9 5-ethynyl-2'-deoxyuridine (EdU) incorporation Cells were seeded at a density of 1000 cells/cm2 into 8 well chamberslides (Scientific Laboratory Supplies, UK) and incubated for 24 hours in 600 µl GM at 37°C 5% CO2. After 24 hours the medium was removed and replaced with GM containing 40 µM EdU for three hours with the cells incubated in standard conditions. The GM containing EdU was then removed, the cells washed twice in PBS for 1 minute and then fixed with 3% paraformaldehyde for 20 minutes. The cells were then washed three times in PBS for 5 minutes each wash and permebealised with 0.1% Triton X-100 in D-PBS for 30 minutes. EdU incorporation was assessed using the Click-iT™ EdU Alexa Fluor® 488 Imaging Kit *for 50 coverslips (Invitrogen, UK) as per the manufacturer’s instructions. This kit

70 fluorescently labelled cells which had incorporated EdU into the nucleus. After fluorescent labelling chambers were then removed from the slide and mounting media with DAPI applied before application of a coverslip. The slide with coverslip was then sealed with nail varnish and cells visualised on a Leica CTR 5000 light microscope. Three independent fields containing at least 50 cells per field were examined for each cell line and the experiment repeated on three occasions.

2.4.10 Terminal dUTP nick end labelling (TUNEL) staining Cells were seeded at a density of 1000 cells/cm2 into 8 well chamberslides (Scientific Laboratory Supplies, UK) and incubated for 24 hours in 600 µl GM. The GM was then removed, the cells washed twice with PBS and then fixed with 3% paraformaldehyde for 20 minutes. The cells were then washed three times in PBS for 5 minutes each wash and pemebealised by incubation with 0.1% Triton X-100 in D-PBS for 30 minutes. After this the cells were washed three times in PBS for 5 minutes each wash before incubation at 37 C for 1 hour in TUNEL labelling mix as per the In Situ Cell death Detection kit TMR (Roche, UK). This labels nicked DNA ends with dUTP linked to a fluorescent label. After fluorescent labelling chambers were then removed from the slide and mounting media with DAPI applied before application of a coverslip. The slide with coverslip was then sealed with nail varnish and cells visualised on a Leica CTR 5000 light microscope. Three independent fields containing at least 50 cells per field were examined for each cell line and the experiment repeated on three occasions.

2.5 Protein based methods

2.5.1 Bradford Assay of protein concentration 5μl of sample or standard (bovine serum albumin at 10, 5, 2, 1, 0.5 and 0.1 mg/ml) were added to 200 μl of BioRad protein assay dye reagent concentrate (BioRad, UK) diluted 1:5 with H2O. The solution was left for five minutes at room temperature to allow for maximum colour change. The absorbance readings were measured on a U.V. spectrophotometer (Bio-Rad Benchmark microplate reader, BioRad UK) at 655nm and the

71 sample protein concentration calculated by reference to the standard curve generated by the BSA standards.

2.5.2 Precipitation of protein from Conditioned cell culture media Protein concentration of conditioned cell culture media was measured as per section 2.5.1. A volume of media containing approximately 200 µg of protein was added to a 15 ml falcon tube and diluted with PBS to one mL. Subsequently 4ml methanol, one ml of chloroform and three ml of water were added to each tube (with the tube being vortexed after the addition of each component). The tube was then spun at 5000 rpm for 5 minutes and the contents separated into three layers. The upper aqueous layer was removed and three ml of methanol added. The tube was then spun at 5000 rpm for two minutes. The aqueous fluid in the tube was removed leaving a pellet of precipitated protein which was resuspended in 100 µl of SDS loading buffer.

2.5.3 SDS polyacrylamide gel electrophoresis (SDS-PAGE) and Western Immunoblotting SDS-PAGE and western blotting were used to analyse presence of proteins and their activation by phosphorylation. Cell lysates were prepared as per section 2.3.2.4, diluted 1:1 with SDS-PAGE loading buffer and heated to 95 °C for 5 minutes. A Mini-Protean III system (BioRad, UK) was used for all SDS-PAGE gels which were composed of stacking and resolving gels of the following composition:

Stacking gel: 3% acrylamide (w/v) 125 mM Tris HCL pH 6.8, 0.01% (w/v) SDS, 0.01% APS, 0.001% TEMED Resolving gel: 7.5 or 10% acrylamide (w/v), 375 mM Tris HCL pH 8.8, 0.01% (w/v) SDS, 0.001% (w/v) Ammonium persulphate

All gels were run at 40 V for 30 minutes and then at 110 V until completion. Following SDS-PAGE gels were washed in transfer buffer and protein transferred to a nitrocellulose membrane either with semi-dry blotting (15 V for 1 hour) or with wet transfer (70 V for 1 hour at room temperature). After transfer the nitrocellulose membrane was washed in

72 TBST for 10 minutes and then placed in blocking solution overnight at 4 °C (unless an overnight antibody incubation was used in which case the membrane was placed in blocking solution at room temperature for 4 hours). Membranes were then incubated in primary antibody for the time and dilution indicated in table 2.1 and washed three times in TBST for 10 minutes. The membrane was then incubated with secondary antibody as indicated in table 2.2 and following this washed three times for 15 minutes each wash in TBST. Lastly the membranes were incubated with chemuminescent substrate (Lumiglo, New England Biolabs, UK) for 1 minute and exposed to Kodak BioMAX film (Kodak, UK). Film was developed using an automatic developer.

2.5.4 Stripping of Western Blots The nitrocellulose membrane was subjected to two 10 minute washes in in western blotting stripping buffer. This was followed by three 10 minute washes in PBS and two five minute washes in TBST. Only membranes where incubation with a secondary antibody was required were subjected to stripping. Efficiency of stripping was checked by applying chemiluniescent detection reagent and exposing to film as per section 2.4.2.

2.5.5 Measurement of IGF-2 in cell culture medium Conditioned cell culture medium was obtained as described in section 2.4.7. IGF-2 levels were measured using the Active Non-Extraction IGF- II ELISA (Beckman Coulter, UK). This kit is designed to measure serum levels of IGF-II, levels in cell culture medium are much lower and this required some amendment to the standard kit protocol. 400 l of conditioned cell culture medium was added to 550 l of Sample buffer 1 and incubated at room temperature for 30 minutes. 950 l of sample buffer 2 was then added and the tube vortexted. 50 l of the treated samples were added to each well of the ELISA plate and the remainder of the process performed as per the manufacturer’s instructions. Absorbance at 450 nm was measured on a U.V. spectrophotometer (Bio- Rad Benchmark microplate reader, BioRad UK).

73 2.5.6 Measurement of serum IGF-2 and IGFBP-3 Serum IGF-2 was measured with the Active Non-Extraction IGF-II ELISA (Beckman Coulter, UK) according to the manufacturer’s instructions. Serum IGFBP-3 was measured with the Active IGFBP-3 ELISA (Beckman Coulter, UK) according to the manufacturer’s instructions. Absorbance was measured on a U.V. spectrophotometer (Bio-Rad Benchmark microplate reader, BioRad UK).

2.5.7 Immunoflourescence microscopy Cells were seeded at a density of 1000 cells/cm2 in 8 well chamberslides (Scientific Laboratory Supplies Ltd, UK) and incubated under standard cell culture conditions in GM for 24-48 hours. The GM was then removed and the cells washed in D-PBS before being fixed in 3% paraformaldehyde (room temperature) or 100% ethanol (-20 C) for 20 minutes. The cells were then washed three times in PBS for 5 minutes each wash, then quenched with 50 mM NH4Cl (in PBS) for 10 min and permebealised with 0.1% Triton X-100 in D-PBS for 30 minutes before being incubated in 5% foetal bovine serum for 30 minutes. After another three 5 minute D-PBS washes the cells were incubated with the primary antibody as indicated in table 2.1, washed with D-PBS for 5 minutes three times and then incubated with the appropriate secondary antibody as indicated in table 2.2. The chambers were then removed from the slide and mounting media with DAPI applied before application of a coverslip. The slide with coverslip was then sealed with nail varnish and cells visualised on a Leica CTR 5000 light microscope

2.5.8 Cleaved Caspase-3 ELISA Cleaved caspase-3 was measure with the PathScan Cleaved Caspase-3 ELISA (New England Biolabs, UK). Cells were seeded in 6 well plates at 1000 cells/cm2 for each cell line and covered with 3 ml GM. 48 hours after seeding the GM was removed, cells washed with PBS and 500 l cell lysis buffer added. A total of 20 g of protein in lysis buffer was diluted to a total of 100 l in sample buffer (supplied with the kit). 100 l of this diluted sample was then added to each well of the ELISA plate and

74 incubated as per the manufacturer’s instructions. Absorbance at 450 nm was measured on a U.V. spectrophotometer (Bio-Rad Benchmark microplate reader, BioRad UK).

2.6 Nucleic Acid based techniques

2.6.1 Extraction of DNA DNA was extracted from fibroblasts using the DNEasy blood and tissue kit (Qiagen, UK) as per the manufacturer’s instructions.

2.6.2 Extraction of RNA RNA was extracted from fibroblasts using the RNEasy kit (Qiagen, UK) as per the manufacturer’s instructions. Total RNA was isolated from stage 25 X. tropicalis embryos and tissue dissected from adult X. tropicalis frogs using the TRIzol® reagent (Invitrogen corporation) as per the manufacturers protocol. The extracted RNA was stored at -80°C. For adult frog tissue a tissue disruptor (TissueRuptor, Qiagen, UK) was used to homogenize the tissue with TRIzol while for stage 25 embryos a micropestle was used. Extracted RNA was DNAse treated with the DNAse treatment kit (Qiagen, UK) as per the manufacturer’s instructions.

2.6.3 Measurement of DNA and RNA concentration DNA and RNA concentration were measured on a Nanodrop 1000 spectrophotometer (ThermoScientific UK).

2.6.4 Reverse Transcription 1 g of RNA was reversed transcribe using the high capacity RNA to cDNA kit (Applied Biosystems, UK) as per the manufacturer’s instructions.

2.6.5 Polymerase chain reaction PCR was performed in 0.2 ml PCR tubes (Starlab, UK) or 96 well plates (ThermoScientific, UK) using 2x PCR MasterMix with ReddyMixtm(Abgene, UK). The standard final reaction contained 1X ReddyMix, 0.5 M forward and reverse primers and 20 ng DNA. Where required for the amplification of GC rich templates 10% DMSO (v/v) was

75 added to the final reaction mix. PCR reactions were cycled on a Gene Amp® PCR system 9700 or MJ Research Peltier Thermal Cycler PTC- 225. Standard cycling conditions are listed in table 2.1

Table 2.1 Standard cycling conditions for PCR

Step Time Temperature Number of Cycles Initial Denaturation 2 minutes 95 C 1 Denaturation 30 seconds 95 C Annealing 30 seconds X C 35 Extension 30 seconds per 500 bp 72 C Final Extension 5 minutes 72 C 1 Hold  4 C 1

2.6.6 Agarose gel electrophoresis PCR products were visualized on 2% agarose gels. 2g agarose (SeaKem® LE agarose, Lonza, USA) was added to 100ml 1x TAE/TBE with 2.5 μl ethidium bromide (10mg/ml Sigma-Aldrich, UK). The gel was allowed to solidify with a comb in place in a Bio-rad gel electrophoresis tank. 6x DNA loading buffer (see Appendix for recipe) was added to each PCR product. PCR product was added to wells in the solidified gel with Hyperladder (Bioline, UK) in one lane. 1 x TAE/TBE buffer was added to the tank and the gel was run at 100 V.

2.6.7 Purification of DNA from PCR products DNA was purified from PCR products with the Qiagen PCR purification kit (Qiagen, UK) as per the manufacturer’s instructions.

2.6.8 DNA sequencing Sequencing reactions were prepared in 0.2 ml PCR tubes (Starlab, UK) or 96 well plates (ThermoScientific, UK). 20 ng of purified DNA from a PCR product was added to 1 l of Big Dye terminator mix 3.1, 5nM sequencing primer, 1x BigDye sequencing buffer and H2O to make total volume 20 l. Reactions were cycled on a Gene Amp® PCR system 9700 or MJ Research Peltier Thermal Cycler PTC-225. Cycling conditions were 94 °C for 4 minutes followed by 25 cycles of 94 °C for 20 seconds, 55 °C for 20 seconds and 60 °C for 4 minutes.

Sequence reactions were added to a 1.5 ml Eppendorf and ethanol precipitated. 1 l of GlycoBlue (Ambion, UK), 50 l of 95% ethanol (v/v) and 2 l of 3M sodium acetate pH 5.2 were added and the mixture vortexed and spun at 13,000 rpm for 20 minutes to pellet the DNA. The pellet was then washed on 250 l 70% ethanol (v/v), spun at 13,000 rpm for 5 minutes and the 70% ethanol removed. The washed DNA pellets were then sequenced using an ABI Prism 3100 Genetic Analyser (Applied Biosystems) by the Core DNA sequencing facility (Faculty of Life Sciences, University of Manchester, UK).

2.6.9 Quantitative Reverse Transcription Polymerase Chain Reaction (QPCR) Total RNA extracted from fibroblasts in 75 cm2 cell culture flasks was prepared as per section 2.6.2 and cDNA generated as per section 2.6.4. 1 µg of RNA was reverse transcribed in a total volume of 30 µl.

QPCR with TaqMan probes Taq man assays used and their target gene are listed in table 2.2.

Table 2.2 TaqMan assays used in this project

Gene Taq Man Assay ID IGF2 Hs01005963_m1 H19 Hs00262142_g1 CUL7 Hs00207532_m1 TP53 Hs00153340_m1 OBSL1 Hs00391352_m1 IGFBP2 Hs00167151_m1 IGFBP5 Hs01052296_m1 Cyclophillin A (PPIA) 4333763T

QPCR with TaqMan probes was performed using two cyclers:  Applied Biosytems StepOne Plus  Applied Biosystems 7300 Each 20 µl reaction contained 10 µl TaqMan Gene Expression Master

Mix, 2 µl cDNA, 1 µl TaqMan assay and 7 µl H2O. Standard cycling conditions for TaqMan gene expression assays used are given in table

77 2.3. Three technical and three biological replicates were run per gene of interest. The normalisation gene was run on every plate.

Table 2.3 Standard QPCR Cycling conditions

Stage Repetitions Temperature Duration UDG inactivation 1 1 50 °C 2 minutes Enzyme Activation 2 1 95 °C 10 min PCR Cycle 3 40 95 °C 15 sec 60 °C 1 min

SYBR Green QPCR Exonic primers were designed to each target gene with each pair designed to span across an intron (to prevent amplification of any DNA contamination) and amplify a product with a size around 100 bp (to ensure a maximally efficient reaction). Each 20 l reaction contained 10 l iqSYBRgreen MasterMix (BioRad, UK), 3 l of primer mix (5 M forward and reverse primer), 5 l H20 and 2 l cDNA. Reactions were run on a BioRad CFX 96 real time thermal cycler. Standard cycling conditions were 95 °C for 3 minutes followed by 40 cycles of 95 °C 15 seconds and 60 °C for 1 minute. At the end of 40 cycles a dissociation step was added to allow melt curve analysis. To confirm amplification of target sequence a random QPCR product for each gene of interest was run on a 2% agarose gel to confirm presence of a single band at the expected size. Additionally the PCR product was sequenced as per sections 2.6.7 and 2.6.8. The melt curve for every reaction was examined and any reaction with more than one peak was discarded from the analysis.

Calculation of Relative Gene Expression Relative fold gene expression for the target gene in the 3-M cell lines was calculated as 2-ΔΔCT. Where ΔCT equals the CT for the target gene minus the CT for the “housekeeper” or normalisation gene and ΔΔCT for any given gene is equal to the ΔCT for the 3-M cell line minus the ΔCT for the control cell line. Where more than one control cell line was used the ΔCT was calculated as a mean for the control cell lines prior to calculation of

78 ΔΔCT. The normalisation genes used were Cyclophillin A for TaqMan assays and GAPDH for SYBR green based assays.

2.7 Gene Expression Microarrays

2.7.1 Preparation of RNA and hybridization to Affymetrix HU-133 plus 2.0 chip Total RNA was extracted from control and 3-M syndrome fibroblasts as per section 2.6.2 and supplied to the Microarray Facility (Faculty of Life Sciences, University of Manchester, UK). RNA quality was assessed by the Facility using an Agilent 2100 Bioanalyser. 500 ng of total RNA per cell line was reverse transcribed using a T7 Oligo dT primer. An in vitro transcription reaction was used to generate biotinylated cRNA which was purified, fragmented and hybridized to an Affymetrix HU-133 Plus 2.0 chip (Affymetrix, USA). The chip contains over 54,000 probesets representing over 47,000 transcripts. Each probeset consists of 25 base pair oligonucleotides including 11-20 perfect match and mismatch probes (one base pair mismatch to control for non-specific hybridization) are present in each probeset. Probesets are concentrated in the 3’ region of the gene.

Following hybridization the chip is then washed and treated with streptavidin conjugated to Phycoerythrin. A scanning confocal microscope is then used to image the chip and the degree of fluorescence from each probe measured.

2.7.2 Software and statistical analysis of gene expression microarrays Microarray data was summarized using PUMA (Propagating Uncertainty Microarray Analysis - http://www.bioinf.manchester.ac.uk/resources/puma/). This process obtains a value for expression for each probeset on the microarray chip and involves normalizing gene expression both within and between chips. PUMA was also used to undertake principle component analysis with PPLR (probability of positive log-ratio) to examine for any differences between gene expression between control

79 and 3-M fibroblasts. In addition to PCA quality control of the arrays were assessed with dCHIP (http://biosun1.harvard.edu/complab/dchip/).

Gene ontology and pathway analysis was performed with the use of National Institute’s Health Database for Annotation, Visualisation, Integrated Discovery (NIH DAVID) (http://david.abcc.ncifcrf.gov/),

2.8 Cellular Metabolomic Studies

2.8.1 Metabolite Extraction Fibroblasts were grown until confluent in 225 cm2 tissue culture flasks containing GM. Six 225 cm2 tissue culture flasks were prepared for each cell line examined (three control cell line and four 3-M cell lines). 24 hours prior to metabolite extraction the GM was replaced with SF media as preliminary data indicated improved metabolite detection when SF media was used rather than GM. The first step of the extraction was removal of the SF media, which was immediately placed in a 50 ml Falcon Tube (Corning, USA) and stored at -80 C. The cells were then washed twice with 5 ml ice cold PBS and scraped into 5 ml quenching solution. The quenching solution containing the scraped cells was then placed in a 15 ml falcon tube, frozen in liquid nitrogen and allowed to thaw on ice. The freeze thaw cycle was then repeated a further two occasions, the falcon tube spun at 5000 rpm for 3 minutes and the supernatant removed to a new 15 ml Falcon tube and stored at -80 C. Samples were then transported on dry ice to the Metabolomics Facility, Manchester Interdisciplinary Biocentre, University of Manchester, UK where they were analysed using gas chromatography mass spectrometry.

2.8.2 Metabolome Statistical Analysis Within Matlab® (http://www.mathworks.com), exploratory multivariate analysis was performed using principal components analysis (PCA), an unsupervised approach which transforms a large set of related variables

80 into a new, smaller set of independent variables, termed principal components (PCs) (Joliffe) . Each PC represents an axis in multidimensional space and corresponds to the direction of maximum variation of the original data. PCA was performed on data normalised to zero mean and unit variance, so that results were not dominated by a small number of high intensity peaks but gave equal weighting to peaks of low intensity.

Univariate statistical analysis was performed, using the non-parametric Mann Whitney U-test to determine those metabolites showing a statistically significant difference (p-value <0.05) between classes under observation. All missing values were replaced by NaN for univariate analysis and 0 for PCA.

2.9 Fertilisation of Xenopus tropicalis oocytes and microinjection of Morpholino Oligonucleotides

2.9.1 Obtaining Oocytes Each Xenopus tropicalis female was injected with pregnant mare serum gonadotrophin (PMSG, Calbiochem, UK) and human chorionic gonadotrophin (hCG, Sigma-Aldrich, UK) to induce ovulation. Priming injection of 15 IU PMSG and a boost injection of 150 IU PMSG are given 3 days and 4 hours respectively prior to collecting eggs. All injections are given into the dorsal lymph sac. Eggs are obtained 4 hours after the boosting injection by gentle squeezing of the abdomen while holding the cloaca over a Petri dish coated in L15 media (Sigma-Aldrich, UK) supplemented with 10% fetal bovine serum (FBS). After at least an hour of rest the female is re-squeezed to obtain further eggs. For this project all injections and squeezings were undertaken by Dr F. Manson and Dr E. Hilton.

2.9.2 Obtaining Sperm The male X. tropicalis is placed in anaesthetic solution for 30 minutes. This solution contains 500 ml dH2O with 0.5g each of MS222 and sodium

81 bicarbonate (Sigma-Aldrich, UK). The testes lie deep in the abdomen close to the aorta. Once adequately anaesthetised, the animal is euthanized and an incision is made in the abdominal wall and the testes are dissected out and placed in L-15 media supplemented with 10% FBS. The male is killed and the tested dissected only after confirming the females were laying eggs.

2.9.3 Fertilisation and Preparation for Microinjection The testes are macerated in 0.5 ml L15 media with 10% FBS using a microtube pestle in a 1.5ml eppendorf tube. The sperm are immediately pipetted over the eggs and left for 2 minutes to allow the sperm to attach to the eggs. The dish is then flooded with 0.1X Marc’s Modified Ringers (MMR) solution for 20 minutes to allow completion of fertilisation. This low salt solution helps to activate the sperm and increase fertilisation rates.

Each fertilised egg (stage 1 embryo) is coated in a protective jelly coat which is difficult to pass through with a fine bore needle. In order to de- jelly the embryos they are placed in a 2% cystine (VWR International, UK) solution in 0.1X MMR solution (pH with 10M NaOH to 7.8) for 20 minutes. After de-jellying the embryos are washed three times in 0.1X MMR solution and then placed in 0.1X MMR + 3% Ficoll DM400 (GE Healthcare, UK). The Ficoll helps to stabilise the eggs and provides an osmotic pressure to prevent leakage of cytoplasm following microinjection. The embryos are then placed in a 500 μm polypropylene mesh covered dish with 0.1 X MMR/3% Ficoll and are ready for microinjection.

2.9.4 Microinjection Needles for microinjection were obtained using 30 microlitre glass capillary pipettes (Drummond Microcaps®, Dummond Scientific, USA) which were pulled using a Narshige Model PC-10 (Narshige International, London). Each needle was back loaded with 5 μl of morpholino solution at the desired concentration. The needle was placed in a micromanipulator and connected to a Picospritzer III microinjector system (Intracel, UK). This microinjector system is connected to a cylinder of compressed

82 nitrogen gas and allows repeatable pressure pulses to be dispensed at set pressure and time. The time of pressure pulses on the Picospritzer III is altered to produce a volume with each pulse of 1 nl. A light microscope (Leica MZ6) and an additional light source (Leica CLS 100x) were used to visualize the needle and embryos (both Leica Microsystems, UK). Once microinjected the embryos are then placed in a 2% agarose coated dish (Corning, USA). The sequence of each morpholino oligonucleotide used is listed in chapter 7.

OBSL1 MOs were designed by Dr Emma Hilton, the standard control and p53 MOs were supplied by Gene Tools (Oregon, USA).

2.9.5 Embryo selection and husbandry Embryos were sorted for those in which divisions had occurred around 2 hours after microinjection. Those with divisions were placed into a 2% agarose coated well on a 24 well plate in 0.1 X MMR with gentamycin (1μg/μl) at maximum density of 10 per well. At 48 hours the embryos were transferred into a 6 well plate in 0.1 X MMR at maximum density of 30 per well. When the embryos were mobile and demonstrating feeding activity they were transferred into water and fed once daily with a spirulina based feed. Embryos were housed in an incubator at a temperature of 22°C. Embyros were staged according to (Nieuwkoop and Faber, 1994) and measured using an eyepiece micrometer. Measurements of trunk length and intra-ocular distance were taken at stage 50

2.10 Suppliers Unless otherwise stated all chemicals used were purchased from the Sigma-Aldrich Company (Poole, Dorset, UK) or Fisher Scientific (Loughborough, UK) and were of molecular biology grade. Nuclease free water was purchased from Qiagen and used for all DNA and RNA based techniques unless otherwise stated. DNA primers were synthesised by and purchased from Invitrogen (Paisley, Scotland, UK).

83 2.10.1 Antibodies Used Antibodies used during this project are listed in Tables 2.1 (primary antibodies) and Table 2.2 (secondary antibodies). Unless otherwise stated antibodies were used at the temperature, incubation time and dilution incubated in Tables 2.1 and 2.2.

2.11 Buffers and Solutions Cell Lysis Buffer 10 mM Tris ph 7.4, 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 0.5% NP40 DNA loading buffer 40% sucrose (w/v). Orange G Metabolomic Quenching solution 80% (v/v) methanol at -60C. MMR (10X)

100 nM NaCl, 20 mM KCL, 20 mM CaCl2, 10 mM MgSO4, 50 mM HEPES, pH to 7.8 Phosphate Buffered Saline (1X) 137 mM NaCl, 2.7 mM KCL, 10 mM Na2HPO4, 2 mM KH2PO4 TAE (50x) 2000mM Tris-HCl, 0.0571% glacial acetic acid, 50 mM EDTA TBE (10x) 900 mM Tris-HCl (pH 8.0), 900 mM orthoboric acid, 20 mM EDTA SDS-PAGE running buffer 25 mM Tris-HCl, 20 mM glycine, 5 % (w/v) SDS SDS-PAGE loading buffer 60 mM Tris-HCl (pH6.8), 25 % (v/v) glycerol, 2 % (w/v) SDS, 5 % (w/v) β- mercaptoethanol, 0.025 % (w/v) bromophenol blue TBS (5X) 50 mM Tris-HCL, 75 mM NaCl, pH to 7.5 TBST 10 mM Tris-HCl (pH 7.5), 15 mM NaCl, 0.1 % (v/v) Tween 20 Transfer buffer for western blots

84 25 mM Tris-HCl, 150 mM glycine, 20 % (v/v) methanol, 1 % (w/v) SDS. Western blot stripping buffer 0.2M glycine, 3.5 mM SDS, 0.1% Tween 20, pH 2.2

Table 2.4 Primary Antibodies Used in this project.

Primary Antibody Technique(s) Company Incubation Incubation Working Supplying temperature time and dilution solution Rabbit polyclonal anti-AKT WB New England Room 1 hour TBST 1/1000 Biolabs Rabbit monoclonal IgG WB New England Room 1 hour TBST 1/1000 anti-phosho-AKT (Ser743) Biolabs (clone 193H12) Rabbit polyclonal anti-β- WB New England Room 1 hour TBST 1/2000 actin Biolabs

Mouse monoclonal IgG2b WB, IF Santa Cruz Room 1 hour TBST WB: anti-CUL7 (clone AB38) Biotechnology 1/750 IF: 1/100 Rabbit monoclonal anti- WB New England Room 1 hour TBST 1/1000 CTCF (clone D31H2) Biolabs Mouse monoclonal anti- WB New England Room 1 hour TBST 1/1000 Cyclin D1 (DCS6) Biolabs Rabbit monoclonal IgG WB New England Room 1 hour TBST 1/3000 anti-GAPDH (clone Biolabs 14C10) Mouse monoclonal anti – IF BD bioscience Room 1 hour TBST 1/1,000

GM130 IgG1 Rabbit polyclonal anti- WB New England Room 1 hour TBST 1/1000 p44/42 MAP Kinase Biolabs Rabbit polyclonal anti- WB New England Room 1 hour TBST 1/1000 phospho-p44/42 MAP Biolabs Kinase (Thr202/Tyr204) Rabbit polyclonal anti- WB New Engalnd Room 1 hour TBST 1/1000 IGFBP-2 Biolabs

Mouse monoclonal IgG2b WB Santa Cruz Room 1 hour TBST 1/200 anti-IGFBP-3 (clone YY07) biotechnology Rabbit polyclonal anti- WB Millipore Room 1 hour TBST 1/1000 IGFBP-5 Rabbit polyclonal anti- WB Abcam Room 1 hour TBST 1/1000 IGFBP7 Mouse monoclonal IgG WB New England Room 1 hour TBST 1/1000 anti-IRS-1(clone L3D12) Biolabs Mouse monoclonal IgG WB New England Room 1 hour TBST 1/1000 anti-Phospho-IRS-1 Biolabs (Ser612) (L7B8)

Table 2.4 Primary Antibodies Used in this project (continued).

Primary Antibody Technique(s) Company Incubation Incubation Working Supplying temperature time and dilution solution Rabbit Polyclonal anti- WB, IF Eurogentec 4 C 16 hours WB: OBSL1 (Custom 5% Milk in 1/350 antibody) TBST IF: 1/20

Mouse monoclonal IgG2a WB Santa Cruz Room 1 Hour TBST 1/5000 anti-p53 (clone DO1) biotechnology

Mouse monoclonal IgG2a WB Zymed Room 1 hour TBST 1/1000 anti-Stat5b Laboratories

Mouse monoclonal IgG1 WB New England Room 1 hour TBST 1/1000 anti-phopho-stat5(Tyr694) Biolabs 5% BSA

Table 2.5 Secondary Antibodies used during this project

Secondary Antibody Technique Company Incubation Incubation Working dilution Supplying Temperature Time Goat anti-rabbit IgG WB New England Room 1 hour 1/1000 HPR-linked antibody Biolabs Goat anti-mouse IgG WB New England Room 1 hour 1/1000 HRP linked antibody Biolabs AlexaFluor® 594 goat IF Invitrogen 22 °C 45 minutes 1/2000 anti- mouse IgG1 AlexaFluor® 594 goat IF Invitrogen 22 °C 45 minutes 1/2,000 anti-

mouse IgG1 AlexaFluor® 488 chicken IF Invitrogen 22 °C 45 minutes 1/2,000 anti-mouse IgG (H+L) AlexaFluor® 594 goat IF Invitrogen 22 °C 45 minutes 1/2,000 anti- rabbit IgG (H+L) AlexaFluor® 488 goat IF Invitrogen 22 °C 45 minutes 1/2,000 anti- rabbit IgG (H+L)

Chapter 3: Patients

3.1 Introduction and Aims The patients presented here have been previously reported either in a case report or in the thesis of Daniel Hanson (PhD, University of Manchester, 2010), Ajiboloa Omokanye (MRes, University of Manchester, 2010) or Amit Sud (MRes, University of Manchester, 2009). Additional clinical data has been collected and the patients grouped together. Sequencing of CUL7 and OBSL1 was undertaken by D Hanson, A Sud and A Omokanye. The aims of this were: 1. To describe the clinical phenotype of a cohort of patients with 3-M syndrome 2. To compare the genetic subgroups of 3-M syndrome (CUL7 mutation patients, OBSL1 mutation patients and patients with no identified mutation) 3. To describe the response of patients with 3-M syndrome to treatment with recombinant human growth hormone

3.2 Patients with Cullin 7 mutations

Family One

The index case was referred to the clinical genetics team at 6 months of age because of short stature and dysmorphism. He was born at term by normal vaginal delivery to consanguineous parents of Pakistani ethnic origin and was markedly small weighing 1.92 kg (-4.3 SD) with a length of 40 cm (-5.8 SD) and a relatively preserved head circumference of 33 cm (-1.7 SD). At the age of 6 months he remained markedly short with a height of 54 cm (-5.8 SD) and was relatively slim with weight of 4.65 kg (- 5.8 SD) and BMI SDS -1.4. His facial appearance was classical of 3-M syndrome with a triangular shaped face, frontal bossing, midface hypoplasia, anteverted nares, full fleshy lips and prominent ears (see figure 3.1). Examination also demonstrated a transverse chest groove,

88 prominent heels and a spinal lesion. Spinal radiographs detected an underlying spina bifida occulta.

His mother became pregnant for a second time and antenatal ultrasonography identified a small fetus with spina bifida occulta. A male baby was delivered at 38 weeks gestation with a relatively normal weight of 2.57 kg (-1.5 SD) but who was markedly short with a length of 38 cm (- 5.7 SD). At 6 months of age he was 53.5 cm tall (-6.1 SD) with a weight of 4.52 kg (-5.0 SD) and head circumference 44 cm (-0.4 SD). The facial appearance was similar to his brother with a triangular shaped face, frontal bossing, midface hypoplasia, anteverted nares and full fleshy lips. Prominent heels and a transverse chest groove were also present (see figure 3.1).

Direct sequencing of CUL7 in the proband of family 1 identified a novel frameshift mutation (c.4191delC p.H1379HfsX11) in exon 22. A skin fibroblast cell line was derived from the elder sibling.

Figure 3.1 – Facial phenotype with prominent ears, fleshy tipped nose, prominent ears and fleshy lips in family one. A) 2 year old male. B) 6 month old male. Prominent heels in 2 year old (C) and 6 month old (D).

89 Family Two

The patent is a 24 year old male who presented due to short stature. He is the 4th child of consanguineous parents and was born at term by emergency caesarean section due to pre-eclampsia. The mother was 38 years old at his birth and the father was 44 years old. His birth weight was 2.30 Kg (-3.19 SD). Development milestones were normal.

On examination he had a broad forehead, triangular face, fleshy nasal tip and midface hypoplasia. Orodental examination revealed prominent premaxilla, long philtrum, thick lips, thick upper labial frenum, grooved tongue and high arched palate. He had bilateral limitation of elbow extension, bilateral hyperextensibility of wrists, metacarpophalangeal and interphalangeal joints, brachydactyly of hands and feet, prominent heels as well as bilateral clinodactyly and camptodactyly of 5th fingers and right Simian crease. His chest was short with increased transverse diameter, anterior transverse groove of lower thorax and pectus excavatum. Exaggerated lumbar lordosis was noted. Height was -3.7 SD at 24 years and head circumference was normal.

Radiological examination revealed thin long bones with narrow joint spaces, Madlung deformity, both radii showed long tapered lower ends and oblique upper ends with generalized decreased bone density and narrow pelvis. Dolichospondyly was noted mainly in lower thoracic and lumbar vertebrae. DEXA showed osteoporosis at the spine (Z-score: -3.4) and forearm (Z-score: 2.4) and normal bone density at femur.

Direct sequencing of CUL7 identified a novel 4 bp deletion in exon 22 (c.4108delGGAG, p.G1370RfsX37).

B Family Three

Two brothers aged 10 years and 9 months respectively presented to a paediatric endocrinologist in Pakistan with short stature. They were the fourth and seventh children of consanguineous parents. At presentation the elder child was 100.6 cm tall (-6.1 SD) and weighed 16kg (-6.0 SD), BMI SDS was -0.34. His facial appearance was classical of 3-M syndrome with dolicocephaly, frontal bossing, full fleshy lips and a fleshy upturned nose. He also had a marked lumbar lordosis. Both fifth fingers were markedly short and he was deaf with impairment of cognitive development (measured at 51.2 months at a chronological age of 10 years). Maternal height was 159 cm (-0.8 SD) with paternal height 149 cm (-4.3 SD), mean parental height SDS -2.6. The affected younger sibling also had a facial appearance consistent with 3-M syndrome (fleshy tipped nose, maxillary hypoplaisa, broad forehead and prominent ears) and at the age of 9 months he was 53 cm in length (-7.7 SD) and weighed 4.3 kg (-7.1 SD), BMI SDS -1.97. There were two perinatal deaths in the family the first was due to breech presentation and resulted in a stillbirth and the second was a child born at term who was delivered by a traditional birth attendant and died a few hours after birth, the cause of death is uncertain. No data on size at birth was available for either patient as no healthcare professionals were present at the birth.

Direct sequencing of CUL7 identified a known frameshift mutation (c.3379_3380delTG, p.W1127E) in exon 18.

Family Four

The proband is the second of three children born to non consanguineous parents of Phillipino ethnic origin. He was born at 36 weeks gestation by emergency caesarean section with a birth weight of 1.94 kg (-4.25 SD) requiring facial oxygen but no other form of resuscitation. At birth his head size was noted to be large but details of the measurement are not available. He was initially in the special care

91 baby unit where he required nasogastric feeding. At the age of 5 months his height was 52.5 cm (-5.8 SD) with an OFC of 42.8 cm (+0.16 SD). By three years and two months of age his height was 80.7 cm (-4.3 SD) and weight was 1.5 kg (-3.3 SD). The latest available height measurement at 4 years 4 months was 85.7 cm (-4.9 SD). On examination he had a typical facial appearance for 3-M syndrome including prominent fleshy lips, fleshy upturned nose, long philtrum and triangular shaped face with maxillary hypoplasia. He has a short neck, square shoulder and a short thorax. There was no chest groove but there was a mild pectus excavatum. On the left hand there was 5th finger clinodactyly. Prominent heels were present.

Karyotype was 46 XY and mutational analysis for hypochondroplasia was negative. Skeletal survey in the neonatal period demonstrated delayed bone maturation corresponding to a gestation of less than 30 weeks but no other abnormalities. A limited skeletal survey at 3 years of age was entirely normal.

Direct sequencing of CUL7 identified a homozygous novel sequence variant (c.4763T>C, p.L1588P) in exon 25. This variant was not found in 105 control subjects. It is important to note it was not possible either to acquire ethnically matched controls or to undertake functional studies on this sequence variant. Direct sequencing of OBSL1 did not identify any sequence variants.

DOC Domain Cullin Domain

1 aa 588 1120 1698 Figure 3.2 – Schematic representation of the Cullin 7 gene and location of the mutations identified in Families 1-4. Of the four mutations three were nonsense mutations and one (c.4763T>C) missense. Three mutations were novel with the exon 18 mutation (c.3379_3380delTG) the only previously described mutation.

93 3.3 Patients with Obscurin-Like 1 mutations

Family Five

The affected child initially presented antenatally with short limbs on the foetal anomaly ultrasonography at 22 weeks gestation. She was born at term by normal vaginal delivery, the first child of non-consanguinous Caucasian parents. Birth weight was 2.35 kg (-2.7 SD). At 15 months of age her weight was 7.2 kg (-4.1 SD), height was 62 cm (-6.4 SD) and OFC 50.4 cm (+2.7 SD). Slender long bones and relatively tall vertebral bodies were not identified on radiography. Clinical examination demonstrated a facial appearance with fleshy upturned nose, midface hypoplasia and frontal bossing (see figure 3.3). Her lips were not fleshy and she did not have prominent ears or a triangular shaped face. Head was dolicocephalic. She also had prominent heels, a marked lumbar lordosis and bilateral hip dislocation.

Compound heterozygous nonsense OBSL1 mutations were identified on OBSL1 sequencing (c.1149C>A; c.1273insA, p.C383X, p.T425NfsX40).

Figure 3.3 – A) Facial features and B) Prominent heels in the affected individual from Family Five

Family Six

The proband is a male who presented at the age of 2 years and 3 months with short stature. He was born by spontaneous vaginal delivery at 37 weeks gestation weighing 1.92 kg (-2.7 SD). At presentation he was 71.8 cm tall (-5.0 SD) with weight 7.6 kg (-5.5 SD) and OFC 47.1 cm (-1.7 SD). He has a triangular shaped face, full fleshy lips, and fleshy tipped anteverted nose. There was no maxillary hypoplasia, frontal bossing or lumbar lordosis (see figure 3.4). Heels were prominent and he did have joint hypermobility. The thorax was not short but the sternum was prominent.

He continued to grow poorly and at the age of 3 years and two months he weighed 9.1 kg (-4.8 SD) with height 76.2 cm (-4.9 SD). By the age of four years and five months he was 83 cm tall (-4.8 SD) and weighed 10.2 kg (-5.2 SD). Last available measurement was at 9 years 10 months when he weighed 17.8 kg (-5.4 SD) and was 108 cm tall (-5.0). He was treated with recombinant human growth hormone but this had little effect (see figure 3.5)

Investigations included a skeletal survey, thyroid function tests, karyotype, low dose synacthen test and gonadotrophin releasing hormone test. All of these were normal. Peak growth hormone level following an arginine stimulation test was 8.0 µg/L and IGF-1 level was 90 ng/mL (-2.7 SD). Skeletal survey was normal with no evidence of either tall vertebrae or slender long bones. Paternal height was 172 cm (-0.89 SD) and maternal height 156 cm (-1.29 SD).

The second affected sibling was a girl born at term with a birth weight of 2.60 kg (-2.0 SD). At the age of 2 years and 10 months she weighed 9.68 kg (-3.5 SD) with height of 78.4 cm (-3.5 SD) and an OFC of 47.4 cm (-1.33). She also had full fleshy lips, an upturned fleshy tipped nose and prominent heels. There was no maxillary hypoplasia, triangular shaped face, frontal

95 bossing, prominent ears or dolicocephaly. The thorax was normal but she did have an exaggerated lumbar lordosis and joint hypermobility. The third affected sibling was another girl who at the age of 13 months weighed 6.86 kg (-3.7 SD) and was 61.6 cm tall (-5.4 SD).

Direct sequencing of OBSL1 identified a homozygous nonsense mutation (c.1273insA, p.T425NfsX40).

Skin fibroblast cell lines were derived from the elder two siblings.

Figure 3.4 – Clinical phenotype and pedigree in two affected siblings from family six. A, B and C) Elder brother. Fleshy tipped nose, full fleshy lips and prominent heels are seen. D, E and F) Older of the two affected sisters. Fleshy tipped nose, full fleshy lips and prominent heels are seen.

Figure 3.5 - Growth chart from elder brother in family six. Height is well below the 3rd centile. No improvement wit recombinant human growth hormone therapy was seen.

97 Family Seven

There was one affected child, a girl, born to non consanguineous Caucasian parents. She was one of dizygotic diamniotic twins born at 33 weeks gestation to an IVF pregnancy. Birth weight was 1.66 kg (-0.7 SD) while her twin brother weighed 2.49 kg (+1.1 SD). At the age of 3 years and 2 months she weighed 10.6 kg (-3.0 SD) and her height was 78.5 cm (-4.1 SD). Paternal height is 190 cm (+1.8 SD) and maternal height 169 (+0.89 SD). The neonatal period was stormy with the requirement for prolonged ventilation secondary to bronchomalacia. Eventually a stent of the left main bronchus was required. Other past medical history included chronic lung disease of prematurity, a patent foramen ovale and aspiration of an ovarian cyst. Weight gain was poor and she has been fed via gastrostomy.

Skeletal survey was reported as normal. On examination she has a fleshy tipped nose with anteverted nares, fleshy lips, triangular shaped face, midfacial hypoplasia, frontal bossing, a long philtrum and a pointed chin. Ears were not prominent. There was a short thorax with pectus excavatum. Joints were hypermobile and there were prominent heels.

Direct sequencing of OBSL1 identified a homozygous nonsense mutation (c.1273insA, p.T425NfsX40).

Family Eight

There was one affected child who was born to non consanguineous parents; mother is of Caucasian ethnic origin and father is of Afro-Caribbean ethnic origin. The affected girl was born at 36 weeks gestation weighing 1900g (-2.0 SD) with an OFC of 34 cm (0 SD). On neonatal examination short limbs, a single palmar crease and a hypertrophic clitoris were noted. By 8 months of age she weighed 5.5 kg (-4.2 SD) with length of 58.9 cm (-4.0 SD) and an OFC of 43.5 cm (-0.7 SD). On examination she had frontal bossing with malar hypoplasia, a long smooth philtrum, an anteverted fleshy

98 tipped nose, crumpled ears, small epicanthic folds and fully fleshy lips. Prominent heels were present and the thorax was short with pectus carinatum.

Skeletal survey demonstrated slender long bones but normal vertebral bodies In view of her marked lumbar lordosis magnetic resonance imaging of the spine was undertaken which in addition to the lordosis identified disc degeneration at L4/5 and L5/S1. Other investigations included a normal Karyotype and a peak GH in response to arginine stimulation of 14.6 g/L. An IGF-1 generation test demonstrated a baseline level of 148 ng/mL (-1.1 SD) that rose to 244 ng/mL (+0.28 SD) after four days of GH therapy.

Maternal height was 162 cm (-0.2 SD) and paternal height was 193 cm (+2.3 SD). The growth chart for this patient is shown in figure 3.7. Height remained parallel to and just below the 3rd centile until 10 years of age. At this time she started her puberty and the pubertal growth spurt took her to a height, within the normal range, of 135 cm (-1.5 SD) at 11.3 years of age. Overall her growth impairment is relatively mild compared to most children with 3-M syndrome. She was treated with rhGH from the age of 6.4 years. It does not appear to have had a significant impact on height velocity (see figure 3.6).

Direct sequencing of OBSL1 demonstrated the affected girl had compound heterozygous nonsense mutations (c.1265-1274delGCACCGTGGC; c.1282insA, p.R419PfsX10; p.T425NfsX40).

Figure 3.6 – Growth chart from the affected individual in family eight. Height runs parallel to and below the third centile until the onset of puberty when a growth spurt is seen. No increase in height velocity is observed after the introduction of Growth Hormone. Weight initially runs parallel to the 10th centile but then increases and reaches the 50th centile.

100

Family Nine

The affected individual in this family is the youngest of three children born to consanguineous parents of Pakistani ethnic origin. He was born at term by spontaneous vaginal delivery with a birth weight of 2.1 kg (-3.8 SD). Antenatal ultrasound scans had identified a small fetus with a relatively large head, small hands and feet and foetal tachycardia. Femur length at 32 weeks gestation was noted to be equivalent to a 26 week gestation femur.

At the age of one year he was 66.5 cm tall (-3.6 SD) with a weight of 7.85 kg (-2.38 SD) and OFC 51.4 cm (+2.9 SD). By 2 years and 11 months he was 80.6 cm tall (-3.4 SD) with weight of 10.2 kg (-3.3 SD). Maternal height was 165.1 (+0.2 SD) and paternal height 177 cm (-0.1 SD).

On examination he has an upturned fleshy tipped nose, a long philtrum, midface hypoplasia and frontal bossing. The head shape was dolicocephalic. Ears were not prominent and face was not triangular in shape. The thorax was short with pectus carinatum. Heels were prominent and there was an exaggerated lumbar lordosis. Gross motor development was mildly delayed and at 10 months he was unable to sit unsupported.

Investigations included Karyotype, urinary organic/amino acids, urinary glycoaminoglycans and mutational analysis for hypochondroplasia. Skeletal survey was normal with no evidence of tall vertebrae or slender long bones. Direct sequencing of OBSL1 identified a homozygous nonsense mutation (c.1273insA, p.T425NfsX40).

Family Ten

This family contained two affected males born to consanguineous parents of Egyptian ethnic origin. A case report in 2006 included clinical details of the patients (Temtamy et al., 2006). Subsequent to the case report DNA was

101 sent to Manchester and direct sequencing identified a nonsense mutation in OBSL1 (c.1463C>T, p.R489X).

The first patient is a male born at term by normal vaginal delivery. He was reported to be of a small size at birth but no exact weight/length is available. Development was normal and he presented at the age of 13 years with height 122 cm (-4.6 SD), weight 25.5 kg (-1.7 SD) and OFC 54.2 cm (+0.77 SD). Facial features included malar hypoplasia, anteverted fleshy tipped nostrils, long philtrum, pointed chin, prominent ears and full fleshy lips. The thorax was short with square shoulders and an exaggerated lumbar lordosis was present. Bilateral clinodactyly of 5th finger was noted as were prominent heels. Skeletal survey demonstrated both slender long bones and tall vertebral bodies. Bone age was not delayed (TW2 method).

Investigations undertaken included an arginine-insulin GH stimulation test and Karyotype both of which were normal (but exact peak GH level was not reported).

The second case was the younger brother of the first. He was born at term by normal vaginal delivery following an uneventful pregnancy. At the age of 11 years he was 120.9 cm tall (-3.3 SD), weighed 23 kg (-1.3 SD) and had an OFC of 54.4 cm (0.9 SD). Facial features were similar to his brother included malar hypoplasia, anteverted fleshy tipped nostrils, long philtrum, pointed chin, prominent ears and full fleshy lips (see figure 3.7). On skeletal survey slender long bones and tall vertebral bodies were present.

102

Figure 3.7 – Clinical feature in two Egyptian brothers with nonsense OBSL1 Mutation. Photo taken from Temtamy SA et al Clinical Dysmorphology 2006 15(12), reproduced with permission from the publisher Wolter Kluers Health.

Family Eleven

The affected sibling is the fourth child (other three siblings not affected) of non consanguineous parents of Peruvian ethnic origin. Facial features present included a triangular shaped face, pointed chin, fleshy tipped upturned nose and a long philtrum. Prominent heels and slender long bones were also present. At the age of 3.8 years her height was 72.5 cm (-6.5 SD), weight was 10 kg (-4.2 SD) with an OFC of 48 cm (-1.5 SD). At the age of 5.5 years she was 82.3 cm tall (-5.7 SD) and weighed 11 kg (-4.9 SD).

103 Direct sequencing of OBSL1 identified a nonsense mutation (c.690insC, p.E231RfsX23).

Family Twelve

This was a large consanguineous family of Pakistani ethnic origin with four affected siblings. Some clinical details and auxology are available on two affected siblings. The youngest affected sibling is a girl who presented with short stature and dysmorphism. Face was typical for 3-M syndrome with full fleshy lips, a fleshy tipped nose and triangular shaped face. She was noted to have prominent heels, slender limbs and a relatively large head. Peak growth hormone in response to arginine stimulation was 35 µg/L. Baseline IGF-1 was 93 ng/mL (-4.0 SD) which rose after 4 days of GH therapy to 207 ng/mL (-1.8 SD). She did not have a skeletal survey. At the age of ten she weighed 16.4 kg (-4.8 SD) and she was 104 cm tall (-5.0 SD). She was treated with recombinant human growth hormone but did not appear to respond to treatment (see figure 3.12). At the age of 15 she was 131.4 cm tall (-4.9 SD) with weight 34.6 kg (-3.0 SD) on a rhGH dose of 51 µg/kg/day.

Her older brother also had short stature and facial dysmorphic features – upturned fleshy tipped nose, fleshy lips and midface hypoplasia. He also had prominent heels. Height at the age of 7 years and 10 months was 94.8 cm (-5.9 SD) and weight was 12.3 kg (-7.3 SD). He was also treated with rhGH but responded poorly and at the age of 12 years and 11 months he was 115 cm tall (-5.0 SD) and weighed 18.4 kg (-5.9 SD). The maximum dose of rhGH used was 70 µg/kg/day. Parental height was 162 cm (-1.8 SD) and maternal height was 160.5 cm (+0.1 SD). Growth chart for the youngest sibling in this family is seen in figure 3.8. Direct sequencing of OBSL1 identified a homozygous nonsense mutation (c.1273insA, p.T425NfsX40).

104

Figure 3.8 – Growth chart of the youngest siblings from family twelve. Height runs well below 0.4th centile with little improvement after treatment with recombinant human growth hormone.

105

Figure 3.9 – Schematic representation of the OBSL1 gene and the location of the mutations found in families five to twelve.

106 3.4 Patients with no identified mutation in OBSL1 or CUL7

Family Thirteen

There was one affected individual born to non-consanguinous parents of Caucasian ethnic origin. He was born at term weighing 3.3 kg (-0.6 SD) by normal vaginal delivery. The placenta was reported to be abnormal with gritty with areas of infarction. Over the first year of life he grew poorly and he received additional nutrition via a percutaneous endoscopic gastrostomy tube. On examination he had a pointed chin, upturned nose with broad tip, prominent ears and frontal bossing. Hyperextensible joints, short thorax, pectus carinatum, increased lumbar lordosis and prominent heels were present. At the age of 3 years and 10 months he was 88.6 cm tall (-3.1 SD) with weight of 12.4 kg (-2.46 SD). At the age of 7 years and 1 month he was 104 cm tall (-3.6 SD) and weighed 18.2 kg (-2.0 SD). At this point he was started on rhGH therapy reaching a dose of 50 µg/kg/day. He responded to the treatment and by the age of 13 years he had reached a height of 154 cm (-0.2 SD) and a weight of 43 kg (0 SD) (see figure 3.10).

Skeletal survey demonstrated normal long bones and vertebral height. At two years of age bone age was not delayed. Peak GH in response to arginine stimulation was 12 µg/L. Baseline IGF-1 was 93 ng/mL (-2.2 SD) and after 4 days of GH therapy it was 83 ng/mL (-2.4 SD). Short synacthen test, GnRH and TRH tests were normal. Karyotype was 46 XY.

Family Fourteen

This was another consanguineous family but with one affected individual, the eldest sibling. The affected girl was born at 32 weeks gestation weighing 1.4 kg (-1.0 SD). At the age of 6 years and eight months she weighed 12.4 kg (-4.8 kg) and was 101.6 cm tall (-2.9 SD). She was treated with rhGH and responded with a height at 10 years and four months of 131 cm (-1.2 SD)

107 and weight 22.4 kg (-2.6 SD) (see figure 3.14). Maternal height was (-0.7 SD) and paternal height was 159.5 cm (-2.3 SD).

She had a pointed chin with triangular shaped face, fleshy upturned nose, prominent heels and syndactyly of the 2nd and 3rd toes of her left foot. She also had multiple moles and café au lait macules.

Karyotype was normal, as were TRH, short synacthen and GnRH tests. Peak growth hormone was 3.6 µg/L in response to arginine stimulation and 8.5 µg/L in response to glucagon stimulation. Baseline IGF-1 was 55 ng/mL (-3.2 SD) and after 4 days GH therapy it rose to 121 ng/ml (-0.9 SD). At 5 years of age bone age was delayed by 18 months. Magnetic resonance imaging of the pituitary gland was normal. Skeletal survey demonstrated slender long bones but normal vertebral heights.

108

Figure 3.10– Growth chart from affected individual from family thirteen. Height runs parallel to but below 0.4th centile until the introduction of GH (arrow) therapy when height improves gradually until it is running below the 9th centile before the onset of puberty when growth improves to between 25th and 50th centiles.

109 Family Fifteen

There were two affected siblings in this consanguineous family of Pakistani ethnic origin. The elder of the two brothers was born at term weighing 2.2 kg (-3.0 SD) with OFC 39.1 cm (-0.2 SD) and length 52 cm (-5.0 SD). He was admitted to the special care baby unit at birth with respiratory distress. He required supplemental cot oxygen for one day and was in special care for 4 weeks to establish feeding. At the age of 2 years and 10 months he weighed 9.4 kg (-3.9 SD) with an OFC of 50 cm (0 SD) and height 81.4 cm (-3.0 SD). Skeletal survey was normal.

The younger sibling was born at term by forceps delivery weighing 2.5 kg (- 2.2 SD) with an OFC of 35 cm (-0.5 SD) and a birth length of 44 cm (-3.2 SD). At the age of 5 months he weighed 4.3 kg (-4.1 SD) with an OFC 40 cm (-0.9 SD) and height 55.8 cm (-3.5 SD). He also had bilateral dislocation of the hips. Facial features of both brothers included a fleshy tipped nose and pointed chin. Maxillary hypoplasia was present in the older sibling.

Family Sixteen

There was one affected child born to consanguineous parents of Bangladeshi ethnic origin. She was born at 38 weeks gestation by caesarean section with a birth weight of 2.4 kg (-2.6 SD). At the age of four years she weighed 10.1 kg (-4.3 SD) and was 86 cm tall (-3.3 SD). Facial appearance was consistent with 3-M syndrome (see figure 3.11) with broad forehead, triangular shaped face, maxillary hypoplaisa and full fleshy lips. Prominent heels and an exaggerated lumbar lordosis were present.

110

Figure 3.11 – Clinical phenotype for affected individual in family sixteen. Broad forehead, triangular shaped face, maxillary hypoplaisa and full fleshy lips are present.

3.5 Phenotype-Genotype comparison

Birth weight SDS and initial auxology at presentation are listed for each patient in table 3.1 Birth weight SDS was not different between the three groups (CUL7 v OBSL1 v No identified mutation; -3.3 + 1.3 SD v -2.5 + 1.2 SD v -2.7 + 0.4, p=0.52). While there was no difference in age at presentation (7.1 + 10 years v 4.7 + 4.5 years v 3.5 + 2.2 years) or in weight SDS at presentation (-5.9 SD + 0.8 v -3.9 + 1.7 SD v -3.9 + 0.8 SD) height SDS at presentation was significantly different between groups (-5.8 + 1.4 SD v -4.5 + 1.2 v -3.1 + 0.24 SD, p=0.003). Tukey post hoc analysis identified there was no significant difference between the CUL7 and OBSL1 groups height at presentation (p=0.070) or between the OBSL1 and No identified mutation groups (p=0.074), however, height at presentation was lower in the CUL7 group compared to the no identified mutation group (p=0.002).

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Individual patient radiological, facial and other clinical features of 3-M syndrome are summarised in tables 3.2 and 3.3. The features most consistently present were fleshy tipped nose (22/22, 100%), anteverted nares (20/22, 91%) and prominent heels (21/22, 95%). The least common clinical features were scoliosis (1/22, 5%), bilateral developmental dysplasia of hip (2/22, 9%) and spina bifida occulta (2/22, 9%). The prevalence of each clinical feature between each of the genetic groups (patients with CUL7 mutations, patients with OBSL1 mutations and patients with no identified mutations) was compared using Fisher’s exact test (see Table 3.4). There were no significant differences between patients with CUL7 mutations and patients with OBSL1 mutations. A long philtrum (CUL7 v no identified mutation; 4/6 v 0/5, p=0.0045) and 5th finger clinodactyly (4/6 v 0/5, p=0.0045) were significantly less prevalent in the no identified mutation patients compared to CUL7 patients. There was a trend towards reduced prevalence of full fleshy lips in the no identified mutation patients compared to CUL7 patients (5/6 v 1/5, p=0.067). Comparing the no identified mutation patients to the OBSL1 mutation patients there was a significant reduction in the prevalence of full fleshy lips (1/5 v 9/11, p=0.036) and a trend towards reduced prevalence of long philtrum (0/5 v 6/11, p=0.058) and 5th finger clinodactyly (0/5 v 6/11, p=0.058).

Table 3.4 also contains a comparison of the prevalence of each clinical feature between the patients reported here and published work summarising the clinical features of 3-M cases reported in the literature. The prevalence of slender long bones, long philtrum, winged scapulae, hyperlordosis, scoliosis, joint hypermobility and 5th finger clinodactyly was lower in the patients described in this study compared to those described in the literature. It is likely this reflects publication bias with only patients with most or all of the known clinical features reported.

112 Table 3.1 – Baseline Auxology in 22 patients from 16 families with 3-M syndrome.

Gene Mutation CUL7 OBSL1 None Identified

Family 1 1 2 3 3 4 5 6 6 7 8 9 10 10 11 12 12 13 14 15 15 16

Gender M M M M M M F M F F F M M M F M F M F M M F

Birth weight (g) 1920 2570 2300 NA NA 1940 2350 1920 2600 1660 1900 2100 NA NA NA NA NA 3300 1400 2200 2500 2400

Birth weight SDS -4.3 -1.5 -3.2 NA NA -4.3 -2.7 -3.9 -2.0 -0.7 -2.0 -3.8 NA NA NA NA NA -0.6 -1.0 -3.0 -2.2 -2.6

Age initial 0.5 0.5 24 10 0.7 0.4 1.4 2.2 2.8 3.2 0.7 1 13 11 3.8 7.8 10 3.8 6.7 2.8 0.4 4 presentation (years)

Height SDS at -5.8 -6.1 -3.7 -6.1 -7.7 -5.8 -6.4 -5.0 -3.5 -3.0 -4.0 -3.6 -4.6 -3.3 -6.5 -5.3 -5.0 -3.1 -2.9 -3.0 -3.5 -3.3 presentation

Weight SDS at -5.8 -5.0 NA -6.0 -7.1 NA -4.1 -5.5 -3.5 -4.1 -4.2 -2.38 -1.7 -1.3 -4.2 -7.5 -4.8 -2.5 -4.8 -3.9 -4.1 -4.3 presentation

OFC SDS at NA -0.4 NA NA NA +0.16 +2.4 -1.7 -1.3 NA -0.3 +2.9 +0.1 +0.9 -1.5 NA NA NA NA 0.0 -0.9 NA presentation

NA – data not available

113 Table 3.2 – Facial and radiological findings in 22 patients from 16 families with 3-M syndrome

Gene Mutation CUL7 OBSL1 None Identified

Family 1 1 2 3 3 4 5 6 6 7 8 9 10 10 11 12 12 13 14 15 15 16

Facial Features

Fleshy tipped nose + + + + + + + + + + + + + + + + + + + + + +

Anteverted nares + + + + - + + + + + + + + + + - + + + + + -

Full fleshy lips + + + + - + - + + + + - + + + + + - - - - +

Triangular face + + + + - + - + - + + - + + + - + - + + - +

Dolicocephaly - - - + + - + - - + + + + + ------+

Frontal bossing + + - + + + + + - + + + + + - - + + - + - +

Midface hypoplasia + + + - - + + + - + + + + + + + + - - + - +

Long philtrum + + - + - + - - - + + + + + + ------

Pointed chin + + + + - + - + - + - + + + + - - + + + + +

Prominent ears + - - - + + - + - - + - + + - + - + - + - -

Radiologic Features

Slender long bones - - + NA NA - - - NA - + + + + - - NA - + NA NA -

Tall Vertebral bodies - - - NA NA - + - NA - - - - - + + NA - - NA NA -

NA – data not available

114 Table 3.3 – Non-facial clinical features in 22 patients from 16 families with 3-M syndrome

Gene Mutation CUL7 OBSL1 None Identified

Family 1 1 2 3 3 4 5 6 6 7 8 9 10 10 11 12 12 13 14 15 15 16

Short neck + + - + + + + + + - - + + - + + - - + + + -

Winged scapulae ------+ + - + + - - - - -

Square shoulders + + - - - + + + + + - + + + - + + - - + + -

Short thorax + + - + + + - + - + + + + + - + + + + + + +

Transverse chest + + + - - - - + - - - - + + - + + - - + + - groove Pectus deformity - - + - - + - + - + + + - - - - - + - - - -

Hyperlordosis - - + + - - + + + - + + + + - + + + + - - +

Scoliosis ------+ ------

Hypermobility of joints - - + - - - - - + + ------+ + - - +

5th finger clinodactyly - - + + - + - + - + - - + + - + + - - - - -

Prominent heels + + - + + + + + + + + + + + + + + + + + + +

Spina bifida occulta + + ------

Developmental ------+ ------+ - - dysplasia hip

115 Table 3.4 – Comparison of phenotype between genetic groups and between all patients in this study and a previously reported summary published 3-M case reports.

Group CUL7 OBSL1 None Sig. Significance Significance All 3- All 3-M Sig identified CUL7 CUL7 v OBSL1 v M Temtamy Temtamy v None None this et al v this OBSL1 identified identified study study Radiological Features

Tall vertebrae 1/4 4/9 1/3 NS NS NS 6/16 12/29 NS

Slender long 1/4 3/9 0/3 NS NS NS 3/16 32/34 <0.001 bones Facial features

Fleshy tipped 6/6 11/11 5/5 NS NS NS 22/22 33/36 NS nose Anteverted 5/6 10/11 4/5 NS NS NS 19/22 29/37 NS nares Full fleshy lips 5/6 9/11 1/5 NS 0.067 0.036 15/22 31/37 NS Triangular face 5/6 7/11 3/5 NS NS NS 15/22 32/36 NS Dolicocephaly 2/6 6/11 1/5 NS NS NS 9/22 23/35 NS Frontal bossing 5/6 8/11 3/5 NS NS NS 16/22 28/36 NS Midface 4/6 10/11 2/5 NS NS NS 16/22 31/36 NS hypoplasia Long philtrum 4/6 6/11 0/5 NS 0.0045 0.058 10/22 27/34 0.010 Pointed chin 5/6 6/11 5/5 NS NS NS 16/22 30/36 NS Prominent ears 3/6 5/11 2/5 NS NS NS 10/22 15/34 NS

Other clinical features Short neck 5/6 7/11 3/5 NS NS NS 15/22 32/38 NS Winged 0/6 4/11 0/5 NS NS NS 4/22 13/25 0.006 scapulae Square 3/6 9/11 2/5 NS NS NS 14/22 26/26 <0.001 shoulders Short thorax 5/6 8/11 5/5 NS NS NS 18/22 26/33 NS Transverse 3/6 5/11 2/5 NS NS NS 10/22 15/19 NS chest groove Pectus 2/6 4/11 1/5 NS NS NS 7/22 18/34 NS deformity Hyperlordosis 2/6 9/11 3/5 NS NS NS 14/22 27/31 0.047 Scoliosis 0/6 1/11 0/5 NS NS NS 1/22 5/13 0.018 Hypermobility 1/6 2/11 3/5 NS NS NS 6/22 21/33 0.008 of joints 5th finger 3/6 6/11 0/5 NS 0.045 0.058 9/22 25/32 0.003 clinodactyly

Prominent 5/6 11/11 5/5 NS NS NS 21/22 23/27 NS heels Spina bifida 2/6 0/11 0/5 NS NS NS 2/22 12/24 0.003 occulta UltaDevelopmental 0/6 1/6 1/6 NS NS NS 2/22 NA NA dysplasia of hip

116 Figures 3.12 and 3.13 plot height and weight SDS against age for each of the groups of 3-M patients. It is important to note that there are multiple measurements for most patients and each patient may represent two or more data points. At birth and during the first few years of life height SDS is highly variable (~-2 to -8 SD) but over time the variability appears to be reducing to a range of around -3 to -5 SD (see figure 3.14). This is in keeping with the findings on height SDS reported by Maksimova et al (2007), where in a population isolate with 3-M syndrome due to a CUL7 mutation height SDS initially varied between -2 and -10 SD but over time height SDS appeared to centre around -6 SD. Height SDS was lower in the CUL7 mutation patients compared to both the OBSL1 patients (-5.5 + 1.0 SD v -4.1 + 1.3 SD p=0.010) and no identified mutation patients (-5.5 + 1.0 SD v -3.5 + 0.7 SD, p=0.001). There was no significant difference in height SDS between the OBSL1 mutation patients and the patients with no identified mutations (-4.1 + 1.3 SD v -3.5 + 0.7 SD, p=0.349).

For weight SDS was also highly variable in early life (range ~ -0.5 to -8 SD) but, in contrast with height SDS this variability does not appear to reduce over time. Mean weight SDS was not different between the CUL7 and OBSL1 mutation parents (-4.4 + 1.7 SD v -3.3 + 1.3 SD, p=0.125) or between the OBSL1 mutation and no identified mutation parents (-3.3 + 1.3 SD v -2.8 + 1.3 SD p=0.640). Weight SDS was, however, lower in the CUL7 mutation patients compared to the no identified mutation patients (-4.4 + 1.7 SD v -2.8 + 1.3 SD, p=0.038).

In order to quantify whether any group of 3-M syndrome patients had a more severe phenotype a disease severity score was created. To do this the total number of clinical features present in each case was calculated and divided by 25 for patients who had a skeletal survey and by 23 for those where there was no skeletal survey. There was no significant difference in this disease severity score between the three groups of 3-M patients (p-value for ANOVA 0.132).

117

Figure 3.12 – Height standard deviation score plotted against age patients with 3-M syndrome due to different gene mutations.

Figure 3.13 – Weight standard deviation score plotted against age patients with 3-M syndrome due to different gene mutations

118

3.6 Response to treatment with recombinant human growth hormone

16 patients were identified (10 from KIGS – Kabi International Growth Study, a large pharmaceutical post-marketing database - and 6 patients treated with growth hormone in Manchester). 11 patients were male; mean age was 7.3 + 2.7 years at start of treatment. Mean GH dose at 1 year after starting treatment was 49 + 15 g/kg/day. For the 10 patients identified via KIGS no information was available on mutation status, for the six attending the Manchester growth clinic four had an identified mutation in OBSL1 and two no identified mutation in either CUL7 or OBSL1.

Pre-GH height SDS was -4.2 + 1.3 SD while height SDS 1 year after GH therapy was -3.8 + 1.3 SD (p=0.001, paired sample t-test, see Figure 3.19). Pre-GH height velocity SDS was -1.5 + 1.5 SD and after one year of GH therapy increased to 1.0 + 2.0 SD (p<0.001, paired samples t-test, see Figure 3.14). Eight patients were treated with GH for four years, and the change in height SDS over four years was 0.9 + 0.7 SD.

In comparison to other SGA children the response to GH therapy in 3-M syndrome patients is poor. Van Pareren et al reported an increase in height SDS after 2 years of rhGH treatment in SGA children of +1.7SD and over 5 years of +2.4 SD (Van Pareren et al., 2003). This indicated that there may be some degree of impairment in GH signal transduction and this is examined in Chapter 4.

119

Figure 3.14 – Height and height velocity SDS before and after one year of GH therapy. There is a significant increase in height velocity SDS over one year and a small but significant increase in height SDS. *p=0.01 +p<0.001

120 3.7 IGFBP3 and IGF-I levels in 3-M syndrome patients Serum IGF-I levels were measured by the local NHS biochemistry laboratory using an in-house radioimmunoassay as part of the routine care of the patients. IGFBP3 levels were measured by ELISA using a kit from Diagnostic Systems Laboratories as part of this study. Serum was available for 5 3-M syndrome patients – one sample per patient measured in duplicate. IGF-I levels were generally low (see Table 3.5) with only one patient having an IGF-I level above -2 SD. In contrast IGFBP3 level was above the normal reference range in one patient and in the upper half of the reference range in another three. This data is limited by the availability of serum in only five patients, one of whom was receiving recombinant human GH therapy at the time of sampling. It does appear, however, that 3-M syndrome is associated with low levels of IGF-I and high levels of IGFBP3. This combination is likely to lead to low levels of free IGF-I which may contribute to the short stature seen in 3-M syndrome.

Table 3.5 – Serum IGFBP3 and IGF-I levels in five 3-M syndrome patients (four with OBSL1 mutations and one with no identified mutation) *patient receiving GH therapy at time of sampling

Family/gene with IGFBP3 (ng/ml) IGFBP3 Normal IGF-I (ng/ml) IGF-I SDS Range (ng/ml) mutation 6 OBSL1 9400 232-6595 90 -2.7 8 OBSL1* 7150 1463-7182 252 0.32 12 OBSL1 6400 1281-10000 93 -4 12 OBSL1 5200 1463-7182 87 -2.4 14 None identified 3250 232-6595 95 -2

121 3.9 Key Points  The clinical features most commonly present were a fleshy tipped anteverted nose and prominent heels  There were no differences in clinical phenotype between the CUL7 and OBSL1 mutation patients.  Patients who had no identified mutation were taller and weighed more (i.e. they had less severe growth impairment) than children with CUL7 mutations  Minor differences the prevalence of a small number of clinical features (long philtrum, 5th finger clinodactyly and full fleshy lips) were seen between the no identified mutation patients and the CUL7/OBSL1 mutation patients  The response to growth hormone therapy in 3-M syndrome is poor compared to the general SGA population  IGF-I levels are low with disproportionately high IGFBP3 levels in 3-M syndrome patients

122

Chapter 4: Functional studies on patient fibroblasts

123 4.1 Introduction Previous work on CUL7 has studied the effects of under and over-expression of CUL7 in human cancer cell lines and in mouse models. Loss of CUL7 in mouse has significantly different effects than loss of CUL7 in humans as all the mice die from respiratory distress at birth while humans do not. Studies knocking down CUL7 in immortalised cancer cell lines have yielded useful data but the applicability of the results to 3-M syndrome is unclear for two main reasons. Firstly cancer is a disorder of uncontrolled cell growth; clearly cancer cell lines are not a good model for studying normal growth as they already have genetic mutations affecting cell proliferation. Secondly these studies represent a short term and potentially incomplete knock down of CUL7 whereas in 3-M syndrome patients there is a permanent and possibly total loss of CUL7/CUL7 function. It was therefore decided to study primary cell lines derived from 3-M syndrome patients.

The easiest cell line to obtain from children is an immortalised lymphoblastoid cell line. The advantage of using lymphoblastoid cells is that they can be derived from a blood sample, however, they express very low levels of both CUL7 and OBSL1 (D. Hanson, personal communication). In addition creation of an immortalized lymphoblastoid cell line involves transforming the cell by EBV infection. This could potentially affect both gene expression and cell growth. The ideal cell line to study would be growth plate chondrocytes but it is not practical to sample these in children. It was therefore decided to develop skin fibroblast cell lines. Using skin biopsies these cell lines are easy to obtain, have previously been successfully used to study GH and IGF-1 signal transduction, and have been a good model for other growth disorders, particularly Laron syndrome (Freeth et al., 1997, Freeth et al., 1998, Silva et al., 2002). Skin fibroblasts therefore allow the study of 3-M syndrome pathogenesis in a human cell line with long term effects of loss of CUL7/OBSL1. While using primary skin fibroblast cell lines it is important to control for passage number and age, gender and pubertal status. Commonly control skin fibroblast cell lines are taken from the site of surgical incisions or removed skin tags while patient

124 biosies are taken from an arm - it is possible that this difference may affect the results.

4.2 Potential Mechanisms of Growth Failure in 3-M syndrome As outlined in chapter 1 there are several possible mechanisms suggested by previous work for how loss of CUL7 or OBSL1 may lead to growth impairment:  Impairment of placental size and function  Increased p53 mediated apoptosis  Cell cycle arrest mediated by failure to ubiquitinate cyclin D1  Failure to ubiquitinate IRS-1 leading to IRS-1 accumulation and alterations in IGF-1 signal transduction  Alterations in the levels of IGFBP2 and IGFBP5 expression

In this chapter focusing on studies using patient derived skin fibroblast cell lines all these potential mechanisms will be explored with the exception of impaired placental size/function (which will be explored in chapter 7).

4.2 Patient Fibroblast cell lines used in this study C7 – male patient with a nonsense mutation in CUL7 (c.4191delC p.H1379HfsX11) (elder sibling family 1). OBR – male patient with nonsense mutation in OBSL1 (c.1273insA, p.T425NfsX40) (family six) OBF – female patient with nonsense mutation in OBSL1 (c.1273insA, p.T425NfsX40) (family six). Patient OBF is the sister of OBR. RA – patient fibroblast cell line derived from a female patient with clinically definite 3-M syndrome but no identified mutation in either CUL7 or OBSL1 (affected individual from Family 16)

Control fibroblast cell lines used in this study were also derived from skin taken from pre-pubertal children.

4.3 Hypothesis 1. Nonsense mutations in CUL7 or OBSL1 lead to mRNA degradation and loss of the protein rather than production of a truncated protein

125 2. Loss of CUL7 or OBSL1 may lead to accumulation of p53 or cyclin D1 3. Nonsense mutations in CUL7 and OBSL1 may affect cell proliferation or apoptosis 4. Loss of CUL7 or OBSL1 may lead to mislocalisation of the other protein 5. GH or IGF-1 signal transduction may be impaired in 3-M syndrome 6. IGFBP2 and IGFBP5 expression may be altered in 3-M syndrome affecting IGF-1 availability

4.4 Aims and Objectives 1. To assess using, Q-PCR and Western Immunoblotting expression of OBSL1, CUL7, p53 and cyclin D1 in 3-M syndrome fibroblasts 2. To identify the cellular localisation of CUL7 and OBSL1 in 3-M syndrome fibroblasts 3. To quantify cell proliferation and apoptosis in 3-M syndrome fibroblasts 4. GH and IGF-1 signal transduction to be assessed in patients fibroblasts using stimulation with ligand and Western Immunoblotting 5. To measure IGFBP2 and IGFBP5 mRNA and protein expression in 3-M syndrome fibroblasts

4.5 CUL7 – gene expression, protein expression and cellular localisation in 3-M syndrome fibroblasts 4.5.1 CUL7 Gene Expression The CUL7 gene encodes a single transcript of 5254 bp and a protein of 1698 amino acids. Hanson et al (2010) identified that knockdown of OBSL1 using siRNAs resulted in a reduction in CUL7 protein. It is not known whether this effect is due to a decrease in CUL7 transcription or a post-translational effect.

34/44 (77%) mutations in CUL7 are nonsense mutations predicted to either result in production of a truncated protein or loss of CUL7 via nonsense mediated mRNA decay (Nicholson et al., 2010). Levels of CUL7 mRNA were significantly lower in the C7 fibroblasts compared to controls adjusted for control gene expression (Relative fold expression 0.28 + 0.4, p<0.001) while in the OBF and RA fibroblasts CUL7 expression was not significantly different

126 from controls adjusted for control gene expression (Relative fold expression 1.20 + 0.46, p=0.29 for OB and 0.91 + 0.12, p=0.09 for RA). Gene expression was based on examining three independent RNA samples in triplicate. Gene expression is shown in graphs as fold expression relative to control, it would be preferable to have included a bar for control gene expression –the error bars would be useful to demonstrate the variability in expression of the gene of interest in control cell lines.

4.5.2 CUL7 Protein Expression Western immunoblotting demonstrated absence of a band at 185 kDa (the known molecular weight of CUL7) in lysates generated from C7 fibroblasts with no evidence of a truncated protein (see figure 4.2). For the OBF lysates and control lysates a band at 185 kDa was identified and densitometric analysis did not identify any difference between control and OBF CUL7 protein levels (p=0.2, see figure 4.3). Western immunoblotting was carried out in triplicate on each of three independent protein samples.

In combination the findings of reduced CUL7 mRNA and the lack of any truncated protein in the C7 fibroblast cell line strongly indicates that the mRNA is undergoing nonsense mediated decay. It is probable that this occurs (as would be expected) for the rest of the known CUL7 nonsense mutations. Huber et al (2005) identified that a missense mutation in CUL7 resulted in loss of CUL7’s ability to bind to ROC1 and suggested that 3-M was a condition due to loss of CUL7 function rather than any dominant negative effects. The data shown here are in agreement with that suggestion.

Although knockdown of OBSL1 in HEK293 cells results in a decrease in CUL7 levels, in the OBF patient cell line there was no reduction in CUL7 protein or mRNA levels. It may be that this effect is cell and/or tissue specific or it could be due to the difference between the relatively acute effects of the knock down in the HEK293 model compared to the effects of long term OBSL1 loss seen in the OB cell line.

127 4.5.3 CUL7 Localisation CUL7 has been previously described as having a cytoplasmic localisation. This was using ectopic overexpression of a Myc-tagged CUL7 in U2OS cells (an osteosarcoma cell line) (Andrews et al., 2006). In skin fibroblasts using a CUL7 antibody to detect endogenous protein, in three independent experiments, staining was seen mainly around the nucleus in an asymmetrical pattern (see figure 4.4). This was thought to be consistent with localisation within the Golgi apparatus and this was confirmed by co-localisation of CUL7 with GM130 (a known marker for the Golgi apparatus). No staining for CUL7 was seen in the C7 cells while in the OBF fibroblasts staining was seen which was consistent with that of the control fibroblasts. The differing localisation may reflect cell or tissue specific effects or the effects of tagging and overexpressing CUL7.

Figure 4.1 - Expression of CUL7 mRNA in C7, OBF and RA fibroblasts normalised to control fibroblast and control gene (Cyclophillin A) expression. CUL7 expression was reduced in the C7 fibroblasts (Relative expression 0.28 + 0.04, *p<0.001).

128

Figure 4.2 Western Immunoblot for CUL7 B in lysates generated from control fibroblasts and fibroblasts from a patient with CUL7 mutation (C7) and a patient with an OBSL1 mutation (OBF). Three biological replicates per cell line are shown on the blot. The blot shown is a representative of three blots. A band is seen in the control and OBF fibroblast lanes at around 185 kDA, the known molecular weight of CUL7. No band is seen at this weight in the C7 patient fibroblast lanes with no obvious lower band down to 60 kDA. The nitrocellulose membrane was cut at 60 kDA and the lower portion blotted for GAPDH. B)

129 Second western immunoblot for CUL7 with lysate from control and C7 fibroblasts. No evidence is seen for any truncated protein product, even below 60 kDA, in the C7 lane.

Figure 4.3 – Densitometric analysis of CUL7 in Western Immunoblots from lysates generated from Control, C7 and OBF fibroblasts. No difference is seen between CUL7 protein levels in Control and OBF fibroblasts (p=0.2). Expression of CUL7 protein was absent in the C7 fibroblast cell line (p<0.001 for difference between C7 and control fibroblasts). AU = arbitrary units.

130

Figure 4.4 – CUL7 localises to the Golgi apparatus in skin fibroblasts with no mislocalisation in OBF fibroblasts.

131 4.6 OBSL1 – gene expression, protein expression and cellular localisation in 3-M syndrome fibroblasts 4.6.1 OBSL1 Gene Expression Expression of OBSL1 mRNA was significantly reduced in C7 fibroblasts (relative fold expression 0.26 + 0.07, p<0.001), the OBF fibroblasts (relative fold expression 0.27 + 0.05, p<0.001) and the RA fibroblasts (relative fold expression 0.43 + 0.08, p<0.001) in comparison to controls after adjusting for control gene expression (Cyclophillin A) (see figure 4.5). Gene expression was based on examining three independent RNA samples in triplicate. A reduction in mRNA levels was expected for the OB fibroblasts as this would be consistent with nonsense mediated decay. The reduction in both the C7 and RA fibroblasts suggests that potentially they could also lead to a reduction in OBSL1 levels and that the common pathway for all patients may involve loss of OBSL1. Huber et al (2009) reported on OBSL1 mRNA expression in two patient fibroblast cell lines. One with a nonsense mutation in OBSL1 (c.2441_2442delAT, p.H814RfsX15) in which there was a significant reduction in OBSL1 mRNA and one with a missense OBSL1 mutation (c.2086_2088dupGGC, p.F697G) in which there was no reduction in OBSL1 mRNA. The findings on OBSL1 transcription, where an OBSL1 nonsense mutation is present, are, therefore, in agreement with the findings of Huber et al (2009).

The only available clone of human OBSL1 cDNA is the short 130 kDa isoform B. Previous work within our laboratory identified that our custom anti- OBSL1 antibody was unable to detect this short isoform. The clone was V5 tagged and expressed in HEK293 cells with the protein being detected by an anti-V5 antibody but not the custom anti-OBSL1 antibody. The custom anti- OBSL1 antibody did detect a band on western blotting possibly representing isoform A or isoform C, which was reduced with the addition of a siRNA targeted to OBSL1 (Hanson et al., 2009). The antibody was generated against 4 peptides. Three of these peptide sequences are present in all three isoforms of OBSL1 and thus do not appear to have induced an immune reaction (given that OBSL1 isoform B is not identified by this antibody). The

132 fourth peptide sequence is present only in isoforms A and C thus it is feasible for the antibody to detect isoforms A/C but not isoform B.

4.6.2 OBSL1 Protein Expression Using this custom anti-OBSL1 antibody it was not possible to detect any band at an appropriate molecular weight that was present in the control fibroblasts but absent in the OB fibroblasts (see figure 4.6). The antibody was initially used under the same conditions as per the work by Hanson et al (2009) - i.e. at a dilution of 1 in 350 incubated with nitrocellulose membrane overnight at 4C in 5% milk. Neither dilution of the antibody nor use of the antibody at room temperature allowed the identification of an appropriately sized band present in controls and absent in OB fibroblasts (see figures 4.7 and 4.8). Lysing the cells direct into SDS loading buffer rather than cell lysis buffer did yield a band potentially at the correct size for isoform C (170 kDa) in HEK293 cells but this band was also present in the OBR fibroblasts (see figure 4.7). OBSL1 contains a number of immunoglobulin domains. The antibody was generated to three peptide sequences corresponding to portions of immunoglobulin domains. The antibody may therefore recognize multiple other proteins containing immunoglobulin domains in addition to OBSL1. The siRNA used to validate the antibody in HEK293 cells was also designed against an immunoglobulin domain sequence. It may be that the siRNA knocks down both OBSL1 and another immunoglobulin domain containing protein and that the protein band that disappears upon knock down represents this alternative immunoglobulin domain containing protein rather than OBSL1.

A second custom anti-OBSL1 antibody was also unable to identify any band at the correct molecular weight present in the control fibroblasts but absent in the OB fibroblasts (see figure 4.6). A small aliquot of this antibody was kindly provided by M, Gautel (Kings College, London). It was raised against recombinant OBSL1 immunoglobulin domain 1.

133 4.6.3 OBSL1 Localisation Our own custom peptide anti-OBSL1 antibody was also used for immunoflourescence in control and patient fibroblasts. There were two aims for this work:  To determine if there was any absent staining in the OB fibroblasts compared to controls. Potentially this would give some indication that the antibody was correctly identifying OBSL1.  To determine if OBSL1 is mislocalised in C7 fibroblasts

In rat cardiomyocytes OBSL1 is known to localise to the perinuclear region (Geisler et al., 2007). Initial work on human fibroblasts identified a staining with our custom anti-OBSL1 antibody in the perinuclear region (D. Hanson, Personal communication). The antibody produces a great deal of background staining with some increase around the perinuclear region but this is present in the OB fibroblasts, albeit at slightly reduced intensity (see figure 4.9). There was no evidence of any difference in OBSL1 immunoflourescence between the control and C7 fibroblasts in three independent experiments.

In summary it was possible to demonstrate that fibroblasts express OBSL1 and that in the patient fibroblasts there was a reduction in OBSL1 mRNA. It was not possible to identify and changes in protein levels of OBSL1 and it is likely this is due to the poor quality of the custom polyclonal antibodies available.

134

Figure 4.5 – Expression of OBSL1 mRNA in C7, OBF and RA fibroblasts normalised to control fibroblast and control gene (Cyclophillin A) expression. In all 3-M cell lines tested OBSL1 mRNA expression was significantly lower than control. *p<0.001.

135

Figure 4.6 – Initial Western immunoblots for OBSL1. A) 1:350 dilution custom peptide OBSL1 antibody incubated overnight at 4C in 5% non-fat milk B) 1:400 dilution of custom OBSL1 antibody incubated overnight at 4C in 5% non-fat milk kindly provided by M. Gautel. It is not possible to identify any band corresponding to the known molecular weights of the isoforms of OBSL1 (130, 170 and 210 kDa) that was present in controls and absent in the OB fibroblasts with either custom OBSL1 antibody.

136

Figure 4.7 – Western immunoblots for OBSL1. Neither dilution of the OBSL1 antibody down to a concentration of 1:2000 (A) nor the use of alternative methods for lysing cells (B) allowed identification of a band corresponding to any of the OBSL1 isoforms (i.e. a band at the correct molecular weight consistently present in control fibroblasts and absent in OB fibroblasts). In addition to patient and control fibroblasts, HEK293, 3T3 F442A and an in vitro translation of the mouse full length OBSL1 were examined.

137

Figure 4.8 - Western Immunoblots for OBSL1. Custom antibody incubated at room temperature at 1:350 (A) or 1:1000 dilution. It was not possible to identify any band corresponding to any of the OBSL1 isoforms present in control but not in OB fibroblasts.

138

Perinuclear localisation

Figure 4.9 – OBSL1 immunoflourescence in Control, C7 and OBF fibroblasts. Perinuclear localisation of OBSL1 has been previously reported. In control and C7 fibroblasts staining was seen in the perinuclear region but this also appeared in the OB fibroblasts so cannot be considered to represent specific localisation.

139 4.7 p53 – gene and protein expression in 3-M syndrome fibroblasts CUL7 is known to bind to both N and C terminal regions of p53 and regulate levels of its downstream effector p21 (Andrews et al., 2006, Jung et al., 2007). Furthermore CUL7 has been shown to monoubiquitinate p53 (Andrews et al., 2006). We therefore hypothesized that p53 levels may be affected in 3-M syndrome.

Expression of TP53 mRNA was not significantly different to control fibroblasts after adjusting for control gene expression (Cyclophillin A) for the C7 (Relative expression 1.01 + 0.21, p=0.81) and OBF fibroblasts (Relative expression 1.07 + 0.48, p=0.69) (see Figure 4.10). In the RA fibroblast cell line TP53 mRNA expression was significantly lower than controls (Relative expression 0.83 + 0.11, p=0.03). It is unlikely this small difference in gene expression has biological significance. Gene expression was based on examining three independent RNA samples in triplicate.

At the protein level p53 levels were not significantly different between control, C7 and OBF fibroblasts (see figure 4.11). In the RA cell line it has also been confirmed that p53 protein expression is not significantly different to control (work undertaken by T. Coulson, MRes student). Western immunoblotting was carried out in triplicate on each of three independent protein samples. The p53 band appeared to run at a slightly higher molecular weight in the OBF fibroblasts. This may be a post-translational modification - p53 is known to undergo phosphorylation (22 distinct phosphorylation sites), acetylation (6 different residues), ubiquitination (4 different residues), summoylation, methylation and neddylation (Dai and Gu, 2010, Hollstein and Hainaut, 2010, Kruse and Gu, 2009). While this observation is of interest it cannot be key to the pathway leading to growth impairment in 3-M syndrome as it does not occur in either C7 or RA fibroblasts.

Our finding that p53 levels are unchanged with loss of CUL7 is in keeping with previous work using RNA interference to knock down CUL7 which demonstrated no change in p53 levels. Both p53 and CUL7 are induced by

140 DNA damage and it may be that the significance of the CUL7-p53 interaction is only detectable after DNA damage. In this study the cells were not exposed to UV light, radiation or agents such as etoposide.

Figure 4.10 – Relative fold expression for TP53 in C7, OBF and RA fibroblasts normalised to control fibroblast and control gene (cyclophyllin A) expression. Expression of TP53 is unchanged compared to controls in C7 and OBF but significantly lower in RA (Relative expression 0.83 + 0.11, p=0.03).

141 A

Figure 4.11 – Western immunoblotting (A) and densitometric analysis (B) for levels of p53 protein in control, C7 and OBF lysates. No difference was seen in levels of p53 protein between groups (ANOVA p=0.82). AU = arbitrary units.

142 4.8 Cyclin D1 – No evidence for accumulation in 3-M syndrome fibroblasts Transition between different phases of the cell cycle is closely regulated by the cyclin dependant kinases. Levels of cyclin dependant kinases remain relatively constant throughout the cell cycle but their activity changes throughout the cell cycle with alterations in the level of the cyclins. Progression from G1 is regulated by a reduction in cyclin D1 levels.

Okabe et al (2006) identified that Fbxw8 was responsible for cyclin D1 degradation and that loss of Fbxw8 or CUL7 lead to both accumulation of cyclin D1 and impaired cell proliferation (presumably by increased number of cells unable to exit G1). Thus we hypothesised that loss of CUL7 in 3-M syndrome may mediate cell cycle arrest via accumulation of cyclin D1.

There was no difference between the levels of cyclin D1 in fibroblast lysates from control and C7 or OB fibroblasts (ANOVA p=0.66, see figure 4.12). Neither was there any difference for RA fibroblast lysates (T. Coulson, personal communication). Western immunoblotting was carried out in triplicate on each of three independent protein samples. The lack of any increase in levels of cyclin D1 may be the result of ubiquitination and degradation via another E3 ubiquitin ligase enzyme. Okabe et al (2010) also demonstrated that cyclin D1 was ubiquitinated via an E3 enzyme containing Skp, CUL1 and CUL7. They demonstrated that loss of either CUL7 or CUL1 (via siRNAs) led to accumulation of cyclin D1. It may be that in the longer term loss of CUL7 in 3-M syndrome leads to an upregulation of the Skp- CUL1-Fbxw8 E3 ligase and this allows normalisation of cyclin D1 levels. Additionally Fbx031 is also known to ubiquitinate cyclin D1 and loss of Fbx031 leads to cyclin D1 accumulation and cell cycle arrest in fibroblasts and melanocytes (Santra et al., 2009). This raises two possibilities firstly that many Fbx proteins may contribute to regulating cyclin D1 levels and secondly that cyclin D1 may be ubiquitinated by different Fbx proteins in a cell or tissue specific manner. Thus it remains possible that, if cyclin D1 degradation is dependent upon Fbxw8 in the growth plate, cyclin D1

143 mediated cell arrest may still play a role in the growth impairment in 3-M syndrome.

Figure 4.12 - Western immunoblotting (A) and densitometric analysis (B) for levels of Cyclin D1 protein in control, C7 and OBF lysates. No difference was seen in levels of Cyclin D1 protein between groups (ANOVA p=0.66). AU = arbitrary units.

144 4.9 Cell proliferation in 3-M syndrome fibroblasts Two separate methods were utilised to quantify cell proliferation. The first method used to quantify cell proliferation was a WST-8 (2-(2-methoxy-4- nitrophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium) assay. WST-8 is a tetrazolium salt which is reduced by cellular dehydrogenase enzymes to a water soluble formazoan dye. Incubating cells with WST-8 results in production of the orange dye in proportion to the number of cells present. The dye produces a discolouration of the media that can then be measured by a spectrophotometer. In three independent experiments (with eight samples per cell line) over the 72 hours cell proliferation increased for each cell line. At each time point (24, 48 and 72 hours after seeding) proliferation in the CUL7 and OBSL1 cell lines was reduced compared to controls with the difference between control and 3-M fibroblasts increasing over time (see figure 4.13). A reduction in cell proliferation for RA fibroblasts has also been demonstrated by WST-8 assay and EdU incorporation (T. Coulson, Personal Communication).

The second method used was measurement of incorporation of 5-ethynyl- 2’-deoxyuridine (EdU). EdU is a thymidine analogue that is incorporated into new DNA during cell division. A chemical reaction is used to bind a fluorescent dye to the incorporated EdU and the cells can then be visualised with a fluorescent microscope. A nuclear stain such as DAPI is used to quantify the total number of cells and the EdU staining to identify cells that are dividing. This is a very similar technique to incorporation of bromo- deoxyuridine except that bromo-deoxyuridine incorporation is identified by binding of an antibody to bromo-deoxyurdine and this requires an additional DNA denaturation step. Cell proliferation as measured by EdU incorporation (three independent experiments examining 5 fields containing a minimum number of 50 cells per field) was 25.1 + 17.3% in control fibroblasts, 10.8 + 5.5% in OB fibroblasts and 6.0 + 4.1% in the C7 fibroblasts. EdU incorporation was significantly less in both the C7 (p<0.001) and OBF fibroblasts (p=0.02) compared to control fibroblasts (see figure 4.14). There

145 was no significant difference in EdU incorporation between C7 and OB fibroblasts (p=0.45). No previous data are available for the effects of OBSL1 knockdown on cell proliferation. The data on the effects of loss of CUL7 are in keeping with previous work demonstrating Cul7 -/- fibroblasts display impaired cell proliferation (Tsutsumi et al., 2007).

Figure 4.13 – Cell proliferation measured over 72 hours in control and 3-M syndrome fibroblasts by the WST-8 assay. Cell proliferation at each time point (24, 48 or 72 hours) was lower in the 3-M fibroblasts than in controls and the difference increased over the 72 hours of the study. *p<0.001 compared to control at the same time point.

146

Figure 4.14 – Cell proliferation is significantly lower in 3-M syndrome fibroblasts than in control fibroblast measured by incorporation of EdU (ANOVA p<0.001).

147 4.10 Apoptosis in 3-M syndrome fibroblasts Apoptosis is the process of programmed cell death. This process allows an organism to remove unwanted cells as part of a developmental process, normal homeostasis or due to disease. There are two main pathways involved: the extrinsic and intrinsic pathways. The extrinsic pathway is initiated by binding of a pro-apoptotic ligand such as Fas to its receptor. This results in binding of the death inducting signalling complex and activation of caspase-8 (Salvesen and Duckett, 2002).

In the intrinsic pathway stress or a developmental trigger stimulates translocation of the pro-apoptotic BCL2 family members to the mitochondria. This results in release of cytochrome c into the cytosol, which binds to Apaf-1, a proapoptotic factor that activates caspase-9. Activation of either caspase-8 or caspase-9 leads to cleavage and activation of caspase-3 (Salvesen and Duckett, 2002). As caspase-3 is downstream of both the extrinsic and intrinsic pathways it is useful as a biomarker for apoptosis.

Although there are no known effects of OBSL1 on apoptosis, CUL7 is known to have an antiapoptotic effect. We therefore hypothesised that an increase in the propensity for cells to undergo apoptosis could contribute to the impairment in growth seen in 3-M syndrome. Two techniques have been used to quantify apoptosis within control and 3-M syndrome fibroblasts.

The first technique used to measure apoptosis in the 3-M and control fibroblasts was Terminal deoxy nucleotidy transferase mediated dUTP Nick End Labelling (TUNEL). During the later stages of apoptosis DNA degradation occurs leading to the presence of single stranded breaks. The enzyme Terminal deoxynucleotidyl transferase allows attachment of a labelled dUTP molecule to these nick ends. The method of detection used is dependent upon the label attached to the dUTP. In this study a red

148 fluorescent label (TMR) was used and apoptotic cells detected by fluorescence microscopy.

Three independent experiments examining 5 fields containing a minimum number of 50 cells per field were used. There was no significant difference between the number of cells staining positive in the control and C7 cells (3.1 + 1.2% v 2.3 + 0.9% p=0.41) or between the control and OB cells (3.1 + 1.2% v 4.4 + 2.3%, p=0.051) (see figure 4.15). Although there was a trend towards increased apoptosis in the OB cells the difference was very small and the trend in the C7 cells was for less apoptosis.

The second technique used to quantify apoptosis was measurement of cleaved caspase-3 by ELISA. Activation of either the intrinsic or extrinsic apoptotic pathways leads to cleavage of caspase-3, thus cleaved caspase-3 is considered a biomarker for apoptosis. There was no identified difference between cleaved caspase-3 levels in control fibroblast lysate, C7 fibroblast lysate or OB fibroblast lysate (ANOVA p=0.23) (see figure 4.16). Three independent lysates were used for each group and cleaved caspase-3 measured in triplicate on each lysate. No effect on apoptosis was seen in the RA cell line either by TUNEL or cleaved casase-3 ELISA (T. Coulson, personal communication).

The findings are not in agreement with previous work demonstrating an increase in apoptosis with knockdown of CUL7 in tumour cell lines (Kim et al., 2007). Within any tumour or tumour cell line there are likely to be multiple genetic mutations affecting growth and apoptotic pathways. It may be that a tumour cell has less capacity to compensate for the loss of CUL7 than a cell with otherwise normal physiology i.e. the loss of the antiapoptotic CUL7 may be compensated by upregulation of tumour suppressor genes. Given the known interaction between p53 and CUL7 it is possible that the increase in apoptosis would be seen if the cells were stressed by exposure to radiation, hypoxia or chemicals with DNA damaging properties such as etoposide.

149 A B

Figure 4.15 – The percentage of cells undergoing apoptosis as measured by TUNEL staining. A) There was a borderline increase in cells stained positive for TUNEL in the OB group (p=0.051) and no significant change between the control and C7 cells (p=0.41). B) Example image for TUNEL staining for control and 3-M fibroblasts. Nuclei are stained blue with DAPI; co-staining with TUNEL (red) produced a red-purple nucleus.

150

Figure 4.16 – ELISA for cleaved caspase-3 levels in control and 3-M patient fibroblasts. There was no significant difference in cleaved caspase-3 levels between control and patient fibroblasts (ANOVA p=0.23).

151 4.11 IGFBP2, IGFBP3, IGFBP5 and IGFBP7 expression in 3-M syndrome Dysregulation of IGFBP2 and IGFBP5 expression was identified by Huber et al (2009) in skin fibroblasts taken from a two patients with OBSL1 mutations (one nonsense and one missense) – downregulation of IGFBP2 and upregulation of IGFBP5 were identified. Although abnormal expression of IGFBP2 both at the RNA and protein level is present in the CUL7-/- mouse (Tsunematsu et al., 2006), in contrast to the findings in humans this was increased IGFBP2 mRNA/protein expression. Gene expression data in this section was based on examining three independent RNA samples in triplicate and protein data was based on western immunoblotting of three independent protein samples in triplicate.

Relative expression of IGFBP2 was reduced in the C7 cells (0.64 + 0.16, p<0.001), OB cells (0.11 + 0.03, p<0.001) and RA cells (0.06 + 0.01, p<0.001) compared to control cells after adjustment for control gene expression (see figure 4.17). Western immunoblotting for IGFBP2 using precipitated protein from conditioned cell culture media identified reduced levels of IGFBP2 in C7 (p=0.04), OB (p=0.022) and RA (p<0.001) conditioned media compared to conditioned media from control cells (see Figure 4.18). Expression is plotted as relative to control, it would have been preferable to include a bar for expression of the protein in controls in order to demonstrate with error bars the variability in expression within control cell lines.

Relative expression of IGFBP5 was reduced in the C7 cells (0.17 + 0.09, p<0.001), OB cells (0.03 + 0.006, p<0.001) and RA cells (0.09 + 0.02, p<0.001) compared to control cells after adjustment for control gene expression (see figure 4.17). Western immunoblotting for IGFBP5 using precipitated protein from conditioned cell culture media failed to identify any band at the appropriate size. A band at the appropriate size was, however, easily identified using whole cell lysate. Intracellular IGFBP5 levels were increased in the C7 fibroblasts (p=0.024) and unchanged in the OB and RA fibroblasts, compared to controls.

152

In addition to examining levels of IGFBP2 and IGFBP5 proteins we also examined levels of IGFBP3 in conditioned cell culture medium as IGFBP3 is the main IGFBP present in serum and responsible, with its partner the acid labile subunit, for regulating the half life and availability of free IGF-1. IGFBP3 production was increased between two and three fold in conditioned cell culture media taken from the C7 (p=0.008), OBF (p=0.027) and RA (p<0.001) fibroblast cell lines (see Figure 4.20).

IGFBP7 was identified initially with a microarray experiment and subsequently on q-pcr as being down regulated in 3-M syndrome fibroblasts (see chapter 5). Levels of IGFBP7 protein precipitated from cell culture media were significantly reduced in C7 (p<0.001) OBF (p<0.001) and RA (p=0.004) (see figure 4.21).

It is important to acknowledge that the gene expression studies were undertaken on cells cultured in media containing foetal bovine serum whereas the IGFBP proteins were examined in conditioned cell culture media prepared without the presence of foetal bovine serum (and hence without the presence of GH and the IGFs). This project was designed to investigate the pathophysiology of a growth disease and hence it was felt better to examine the fibroblasts under growing conditions with growth factor stimulation – this is best achieved with the addition of foetal bovine serum to the cell culture media. As serum contains high levels of IGFBP’s it was essential to use serum free media to prepare conditioned cell culture media for IGFBP immunoblotting.

The findings on IGFBP2 are in keeping with those of Huber et al (2009). This study confirms the findings in skin fibroblasts and extends the work to skin fibroblasts from a patient with a CUL7 mutation and a 3-M patient with no known mutation. In addition this study has examined changes in IGFBP2 protein production in 3-M skin fibroblasts unlike the study by Huber et al

153 (2009) that only examined gene expression. A reduction in IGFBP2 levels were seen for all 3-M patient cell lines most marked for the RA cell line.

The findings for IGFBP5 initially appear inconsistent with the published data on IGFBP5 expression in OBSL1 mutant skin fibroblast cell lines where Huber et al (2009) reported an increase in IGFBP5 expression. Importantly two skin fibroblast cell lines were used in their study – one with a missense mutation (p.F697G) and one with a nonsense mutation (p.H814RsfX15). While IGFBP5 expression is increased 50 fold in the cells from the missense mutation patient, it is decreased in cells from the patient with the nonsense mutation. Both of the OBSL1 patient fibroblasts cell lines used in this study contained the same nonsense mutation. The finding of reduced IGFBP5 expression is therefore in keeping with the work of Huber et al. Once again this study has extended the knowledge base to include gene expression in a CUL7 nonsense mutation patient cell line and a 3-M patient with no identified mutation cell line as well as examining changes in IGFBP5 protein levels. The lack of IGFBP5 detected in conditioned cell culture media may simply represent very low levels of IGFBP5 secreted by skin fibroblasts or it could also be due to reduced IGFBP5 secretion/production in the absence of GH/IGF1 stimulation. When originally identified IGFBP5 was found in conditioned media from skin fibroblasts only when GH was added to the cell culture media (Camacho-Hubner et al., 1992).

It is surprising that given the very significant reduction in IGFBP5 expression intracellular levels of IGFBP5 protein were normal or increased in the 3-M cell lines examined. IGFBP5 is known to bind to fibronectin (Beattie et al., 2009) so if binding of IGFBP5 to the fibronectin domain of OBSL1 is involved in its clearance this could explain the observed data with an accumulation of IGFBP5, compensated for by a decrease in IGFBP5 expression. It could also be that a decrease in IGFBP5 expression is only present under growth factor stimulation and the lack of growth factors in our conditioned media may account for the absence of IGFBP in the conditioned media and the lack of any decrease in cellular IGFBP5 proteins.

154

IGFBP5 is the most abundant IGFBP present in muscle and is also highly expressed in bone. It is known to regulate craniofacial development (Bobola and Engist, 2008) and transgenic overexpression of Igfbp5 in mouse leads to increased neonatal mortality, impaired muscle development and reduced growth (Salih et al., 2004). Targeted deletion of Igfbp5 has little effect on phenotype presumed to be due to compensatory increases in the other IGFBPs (Ning et al., 2007). IGFBP2 is the second most abundant IGFBP in the postnatal period and is widely expressed in the fetus. Targeted deletion of Igfbp2 has little effect thought to be secondary to compensatory effects from other IGFBPs (Pintar et al., 1995). Mice who over-express Igfbp2 display a reduction in whole body weight (Hoeflich et al., 1999). The data from these transgenic studies would seem to indicate that IGFBP2/5 act to impair growth but that IGFBP2/5 loss is unlikely to have significant pathological effects and that there are complex interactions between the IGFBPs. In humans serum IGFBP2 levels are decreased in acromegaly and increased in GH deficiency and generally a reverse relationship is found with IGFBP3 (Blum et al., 1993). Taking this evidence into account it is likely that the complex changes identified in IGFBP gene and protein expression represent a response to the growth disruption seen in 3-M syndrome.

IGFBP7 has significantly less capacity for binding the IGFs than IGFBPS1- 6. It functions as a tumour suppressor and induces oncogenic senescence (Suzuki et al., 2010, Vizioli et al., 2010, Wajapeyee et al., 2008). It is therefore probable that loss of IGFBP7 is a component of the cellular response to growth impairment. 2010

155

Figure 4.17 – Relative fold mRNA expression of IGFBP2 and IGFBP5 in 3-M syndrome fibroblasts. Expression changes are relative to control after adjusting for control gene expression (Cyclophyllin A). Expression of IGFBP2 is reduced in all three groups of patient cells but much less markedly for C7 cells. Expression of IGFBP5 is reduced for all three patient groups. *P<0.001.

156

Figure 4.18 – A) Western immunoblotting and B) Densitometric analysis of IGFBP2 in precipitated protein from conditioned cell culture medium normalised to control cell culture medium. IGFBP2 levels were lower in media from C7 cells (p=.004), OB cells (p=0.022) and RA cells (p<0.001).

157 A

Figure 4.19 – A) Western immunoblot for IGFBP5 and –actin in fibroblast lysate for control and 3-M patient fibroblasts. B) Densitometric analysis IGFBP5/–actin for 3-M syndrome fibroblasts normalised to control. IGFBP5 was increased significantly in C7 (p=0.024).

158 A

Figure 4.20 – Western immunoblotting (A) and Densitometric analysis (B) of IGFBP3 in precipitated protein from conditioned cell culture medium. IGFBP3 levels were significantly increased in conditioned media from C7 (p=0.008), OBF (p=0.027) and RA (p<0.001) cell lines.

159 A

Figure 4.21 – A) Western immunoblotting and B) Densitometric analysis of IGFBP7 in precipitated protein from conditioned cell culture medium normalised to control cell culture medium. IGFBP2 levels were lower in media from C7 cells (p<0.001), OBF cells (p<0.001) and RA cells (p=0.004). *p<0.001 +p=0.004

160 4.12 IGF-1 stimulation in control and 3-M syndrome fibroblasts

IGF-1 signal transduction is described in Chapter 1, see figure 1.12. Two components of the signal transduction cascade downstream of the IGF-1R were examined: AKT and the insulin substrate 1 (IRS-1). Both are phosphorylated following binding of IGF-1 to its receptor. C7 and OBF fibroblasts were cultured in serum free media for 24 hours and then stimulated with IGF-1 at a concentration of 100 ng/ml for 5, 15 and 60 minutes. Three independent IGF-1 stimulation experiments were performed for control v C7 fibroblasts and control v OBF fibroblasts. Statistical analysis of densitometry of the three independent experiments was undertaken with 2-way ANOVA in SPSS. This uses all the available data to answer three questions: 1. Is there an effect of time 2. Is outcome affected by cell line (i.e. is there a difference overall in levels of pAKT or pIRS-1 between control and 3-M cells) 3. Is there an interaction between cell line and time stimulation (i.e. is there a difference in the pattern of activation (delayed or earlier activation) of pAKT/pIRS-1 between control and 3-M cells). Western blotting presented is based on three independent stimulation experiments with each protein lysate blotted on three occasions.

On Western Immunoblotting levels of pIRS-1 in control cells appeared low at baseline rising by 5 minutes post IGF-1 stimulation with these increased levels persisting through to 60 minutes post IGF-1 stimulation (see figure 4.22). A similar pattern was seen in C7 cells with the suggestion that levels of pIRS-1 were decreasing by 60 minutes post IGF-1 stimulation. Two way ANOVA of densitometric analysis of pIRS-1 levels in control and C7 cells demonstrated a significant effect of time (p=0.033) but not of cell line (p=0.775) or the interaction of cell line and time (p=0.779). There was no evidence for any significant accumulation of total IRS-1 in CUL7 fibroblasts. There was also no evidence for an earlier decrease in pIRS-1 levels in the C7 fibroblasts on the densitometric analysis.

161

The pattern of increase in levels of pIRS-1 at 5 and 15 minutes with a subjective decrease at 60 minutes was also seen in the OBF cells (see figure 4.23). Two way ANOVA of densitometric analysis of pIRS-1 levels in control and OBF fibroblasts demonstrated an effect of time (p<0.001) but not of cell line (p=0.201) or the interaction between cell line and time (p=0.204). There was no evidence for accumulation of IRS-1 in the OBF cell line.

Western immunoblotting for levels of pAKT in control and C7 fibroblasts demonstrated low-absent baseline levels in both cell lines. For the control fibroblasts levels of pAKT increased at 5 minutes and remained elevated for the duration of the experiment. In comparison levels of pAKT were lower at 5 minutes and completely absent by 60 minutes in the C7 fibroblasts (see figure 4.24). Two-way ANOVA for densitometric analysis of pAKT demonstrated a significant effect of time, cell line and the interaction of time and cell line (all p<0.001).

In contrast OBF cells displayed similar levels of pAKT (low at baseline, increased at 5 min persisting through to 60 minutes) to control cells on western immunoblotting (see figure 4.25). Two way ANOVA for densitometric analysis of pAKT levels in OBF compared to control cells demonstrated a significant effect of time and cell line but not of the interaction between cell line and time. Although the pattern of activation remains the same between cell lines the densitometric analysis suggests there may be a persistent lower level activation in the OBF cell line.

Overall the results are not in keeping with the published work on the effect of loss of CUL7 on IRS-1 levels and IGF-1 signal transduction. The prior work suggested that the CUL7 E3 ligase was responsible for ubiquitination of IRS-1 and that depletion of CUL7 resulted in accumulation of IRS-1 and increased activation of Akt following IGF-1 stimulation. This work was undertaken in Cul7 -/- mouse embryonic fibroblasts (Xu et al., 2008). It is clear that the results of CUL7 loss are significantly different in mouse and

162 humans as the mice die at birth from respiratory distress while humans do not. The differences may therefore reflect the different species the fibroblasts are derived from. Cyclin D1 is ubiquitinated by both the CUL7-Fbxw8 and CUL1-Fbxw8 E3 ubiqutin ligases (Okabe et al., 2006). Since substrate specificity is conferred by the Fbx protein it is reasonable to hypothesize that if present the CUL1-Fbxw8 should ubiquitinate IRS-1 as well. It is possible that the CUL1-Fbxw8 is expressed and compensates for the lack of the CUL7-Fbxw8 E3 ligase in postnatal skin fibroblasts but is not expressed or expressed at low levels in mouse embryonic fibroblasts.

A reduction in IGF-1 mediated activation of Akt is in keeping with a disorder of growth impairment with a poor response to treatment with recombinant human growth hormone. The defect appears quite significant in the C7 cells but markedly less so in the OBF fibroblasts. In the RA fibroblasts a defect in activation of AKT was also identified and in terms of severity lies in between that of the C7 and OBF fibroblasts (T. Coulson Personal Communication). Due to the variability in the severity of this defect and the inconsistency between the human and mouse findings it was felt that this was unlikely to be the sole reason for the growth impairment seen in 3-M syndrome but could be contributary.

163 A

Figure 4.22 – Activation of IRS-1 following IGF-1 stimulation in control and C7 fibroblasts. A) Western immunoblot for phospho-IRS-1, total IRS-1 and GAPDH at baseline, 5, 15 and 60 minutes post stimulation with IGF-1 at 100 ng/ml. No obvious difference is seen between the control and C7 cells. B) Densitometric analysis of phospho-IRS-1 levels from three independent experiments. No significant difference is present between the C7 and control cells on 2 way ANOVA. AU = arbitrary units.

164

Figure 4.23 – Activation of IRS-1 following IGF-1 stimulation in control and OBF fibroblasts. A) Western immunoblot for phospho-IRS-1, total IRS-1 and GAPDH at baseline, 5, 15 and 60 minutes post stimulation with IGF-1 at 100 ng/ml. No obvious difference is seen between the control and OBF cells. B) Densitometric analysis of phospho-IRS-1 levels from three independent experiments. No significant difference is present between the OBF and control cells on 2 way ANOVA. AU = arbitrary units.

165

Figure 4.24 – Activation of AKT following stimulation with 100 ng/ml IGF-1 in control and C7 fibroblasts. A) Western immunoblots for phospho-AKT, total AKT and GAPDH at baseline, 5, 15 and 60 minutes following IGF-1 stimulation. Levels of phospho-AKT appear lower at 5, 15 and 60 minutes in C7 cells. Three independent stimulation experiments in control and C7 cells were performed. Lysates from each experiment were examined three times for phospho-AKT, total AKT and GAPDH. B) Densitometric analysis from the three independent stimulation experiments. Levels of phospho-AKT are significantly lower in C7 cells (2-way ANOVA, p<0.001). AU = arbitrary units.

166

Figure 4.25 - Activation of AKT following stimulation with 100 ng/ml IGF-1 in Control and OBF fibroblasts. A) Western immunoblots for phospho-AKT, total AKT and GAPDH at baseline, 5, 15 and 60 minutes following IGF-1 stimulation. Levels of phospho-AKT appears similar at all time points in both cell lines. Three independent stimulation experiments in control and C7 cells were performed. A representative blot is shown. Lysates from each experiment were examined three times for phospho-AKT, total AKT and GAPDH. B) Densitometric analysis from the three independent stimulation experiments. Activation of AKT was reduced between the OBF and control fibroblasts (2-way ANOVA, p=0.024). AU = arbitrary units.

167 4.13 – GH signal Transduction in control and 3-M fibroblasts For a summary of GH signal transduction see chapter 1 and figure 1.11. Two components of the signal transduction cascade downstream of the growth hormone receptor were examined: Mitogen Activated Protein Kinase (MAPK) and Signal Transducer and Activator of Transcription 5b (STAT5b). Both are phosphorylated following binding of the GH receptor to its ligand. C7 and OBF fibroblasts were cultured in serum free media for 24 hours and then stimulated with GH at concentrations of 200 ng/ml for 15, 30 and 60 minutes. Three independent GH stimulation experiments were performed for control v C7 fibroblasts and control v OBF fibroblasts. Statistical analysis of densitometry of the three independent experiments was undertaken with 2- way ANOVA in SPSS. This uses all the available data to answer three questions: 1. Is there an effect of time 2. Is outcome affected by cell line (i.e. is there a difference overall in levels of pMAPK or pSTAT5b between control and 3-M cells) 3. Is there an interaction between cell line and time (i.e. is there a difference in the pattern of activation (delayed or earlier activation) of pMAPK/pSTAT5b between control and 3-M cells). Western blotting presented is based on three independent stimulation experiments with each protein lysate blotted on three occasions.

On western blotting both control and C7 fibroblasts demonstrated an increase in pMAPK after GH stimulation. Levels of pMAPK appeared to decline earlier in the control fibroblasts. 2 way ANOVA on densitometric analysis of pMAPK levels, however, demonstrated a significant effect of time (p=0.007) but not cell line (p=0.149) or the interaction between cell line an time (p=0.923) (see figure 4.26). This confirms that the GH stimulation affected levels of pMAPK (as would be expected) but suggests that neither levels nor the pattern of activation of pMAPK were different between the control and C7 fibroblasts. Total MAPK levels were constant at each time point examined.

168 When comparing levels of pMAPK following GH stimulation in control and OBF fibroblasts both appeared to increase pMAPK and there did not appear to be any obvious difference between cell lines (see figure 4.27). Levels of pMAPK appeared to increase at 15 minutes and then fall back to baseline levels at 30-60 minutes. 2 way ANOVA of densitometry confirmed this impression with a significant effect of time (p=0.001) but not of cell line (p=0.474) or the interaction between cell line and time post GH treatment (p=0.599).

For pSTAT5b western blotting in control and C7 fibroblasts levels were low at baseline, increased at 15 minutes post GH and remained elevated at 60 minutes post GH (see figure 4.28). It appeared that at 60 minutes post GH pSTAT5b levels were lower in control compared to C7 fibroblasts. Two-way ANOVA for STAT5b densitometry for three independent experiments confirmed that time post GH significantly affected STAT5b levels (p=0.006), but no effect was seen for cell line (p=0.807) or the interaction of cell line and time (p=0.943). A similar pattern was seen for pSTAT5b levels comparing control to OBF fibroblasts. Levels were low at baseline, increased at 15 minutes and remained elevated at 60 minutes (see figure 4.29). Two-way ANOVA for STAT5b densitometry for three independent experiments confirmed that time post GH significantly affected STAT5b levels (p<0.001), but no effect was seen for cell line (p=0.214) or the interaction between cell line and time (p=0.782).

In summary the control and 3-M patient fibroblasts (C7 and OBF) both activated MAPK and STAT5b following stimulation with GH. There was no difference either in levels or in the pattern of activation of pMAPK and pSTAT5b activated following GH stimulation between control and 3-M fibroblasts. The response of RA fibroblasts to GH stimulation is being studied by T. Coulson (MRes student).

169 A

Figure 4.26 – Activation of MAPK following stimulation with GH at 200 ng/ml in control and C7 fibroblasts. A) Western Immunoblot for phospho-MAPK, total MAPK and GAPDH at baseline, 15, 30 and 60 minutes post GH treatment, No obvious difference is seen in phospho MAPK levels in control and C7 fibroblasts B) Densitometric analysis phospho-MAPK (controlled for either GAPDH or -actin levels) from three independent experiments did not show any difference between control and C7 fibroblasts (2-way ANOVA, p=0.149). AU = arbitrary units.

170

Figure 4.27 – Activation of MAPK following stimulation with GH at 200 ng/ml in control and OBF fibroblasts. A) Western Immunoblot for phospho-MAPK, total MAPK and GAPDH at baseline, 15, 30 and 60 minutes post GH treatment, No obvious difference is seen in phospho MAPK levels in control and OBF fibroblasts B) Densitometric analysis phospho-MAPK (controlled for either GAPDH or -actin levels) from three independent experiments did not show any difference between control and OBF fibroblasts (2-way ANOVA, p=0.599). AU = arbitrary units.

171

Figure 4.28 – Activation of STAT5b following stimulation with GH at 200 ng/ml in control and C7 fibroblasts. A) Western immunoblot for phospho- STAT5b, total STAT5b and GAPDH at baseline, 15, 30 and 60 minutes post GH treatment. No significant difference is seen between control and C7 fibroblasts. B) Densitometric analysis pSTAT5B (controlled for either GAPDH or -actin levels) in 3 independent experiments did not show any difference between control and C7 fibroblasts (2-way ANOVA, p=0.807). AU = arbitrary units.

172

Figure 4.29 – Activation of STAT5b following stimulation with GH at 200 ng/ml in control and OBF fibroblasts. A) Western immunoblot for phospho- STAT5b, total STAT5b and GAPDH at baseline, 15, 30 and 60 minutes post GH treatment. No significant difference is seen between control and OBF fibroblasts. B) Densitometric analysis pSTAT5B (controlled for either GAPDH or -actin levels) in 3 independent experiments did not show any difference between control and OBF fibroblasts (2-way ANOVA, p=0.782). AU = arbitrary units.

173 4.15 Key Points

 In C7 fibroblasts CUL7 expression was reduced, with absent rather than a truncated CUL7 protein.  In skin fibroblasts CUL7 appears to localise to the Golgi apparatus  Decreased OBSL1 mRNA expression was identified in all 3-M syndrome fibroblast cell lines. It was not possible to examine protein levels due to the poor quality of the custom anti-OBSL1 antibody.  There was no evidence of accumulation of the putative CUL7 E3 ligase targets, p53, IRS-1 or cyclin D1, in 3-M syndrome fibroblasts.  Cell proliferation is reduced in skin fibroblasts taken from patients with 3-M syndrome compared to control fibroblasts  Levels of apoptosis are unchanged under basal conditions in skin fibroblasts taken from patients with 3-M syndrome compared to control fibroblasts  IGFBP2 and IGFBP5 gene expression were reduced in 3-M syndrome fibroblasts. Expression of IGFBP2 protein in conditioned cell culture medium was reduced. IGFBP5 protein could not be detected in conditioned cull culture medium but was easily identified in whole cell lysate where there was no evidence of reduced expression.  For OBSL1 and C7 fibroblasts there was a reduction in activation of AKT (but not IRS-1) following IGF-1 stimulation  No difference in activation of signalling molecules downstream of the GHR were identified between control and C7 and OBF skin fibroblasts after GH stimulation

174

Chapter 5: Transcriptomic Studies

175 5.1 Introduction

Work outlined in chapter 4 described functional hypothesis led studies to try to gain insights into the pathogenesis of 3-M syndrome. Our central hypothesis was that given identical clinical phenotype seen in all cases of 3- M syndrome the different genes involved must be involved in the same pathway, disruption of which leads to growth impairment. Importantly this pathway must be disrupted in all 3-M syndrome patients. While the functional studies yielded useful data they did not identify a single pathway severely disrupted in all patients. We therefore decided to use a non- hypothesis driven approach to study the effects of the genetic mutations causing 3-M syndrome.

Two distinct methods were utilized: 1. Whole genome gene expression studies using Affymetrix HU 133 plus 2.0 arrays 2. Metabolomic studies utilizing gas chromatography and mass spectrometry

The primary aim of each of these studies was to develop new hypotheses for the pathogenesis of the growth impairment seen in 3-M syndrome. The data derived from the transcriptome studies are presented in this chapter and the data from the metabolome studies are presented in chapter 6.

5.2 Cell Lines used in the Transcriptomic Studies AF – control

ENF – control, female aged 7

ENM – control, male aged 11

C7 – male patient with a nonsense mutation in CUL7 (c.4191delC p.H1379HfsX11) (elder sibling family 1).

OBR – male patient with nonsense mutation in OBSL1 (c.1273insA, p.T425NfsX40) (family six)

176 OBF – female patient with nonsense mutation in OBSL1 (c.1273insA, p.T425NfsX40) (family six). Patient OBF is the sister of OBR.

RA – patient fibroblast cell line derived from a female patient with clinically definite 3-M syndrome but no identified mutation in either CUL7 or OBSL1 (affected individual from family 16)

Where data are expressed as control this represents the average of the three control cell lines, data described as 3-M represents all four 3-M cell lines and where data are described as OB this represents the average of both OBSL1 patient cell lines.

5.3 Introduction to Whole genome gene expression analysis Whole genome gene expression studies were undertaken using Affymetrix HU-133 plus 2.0 chips. Each chip consists of many thousands of oligonucleotides synthesized on a quartz wafer. For each probeset there are 11-20 pairs of oligonucleotides, each pair consists of a perfect match and mismatch probe. The mismatch probe has one base pair change compared to the perfect match probe, usually in the central region of the probe. The Affymetrix HU-133 plus 2.0 contains 54,613 probesets with some genes being covered by more than one probeset.

Total RNA is extracted from target tissue (in the case of experiments in this chapter this represents fibroblasts). The RNA is then reverse transcribed with an oligo dT primer containing a T7 polymerase binding site. This T7 polymerase binding site is then used for an in vitro translation reaction to produce cRNA. The introduction of biotinylated nucleotides allows for the cRNA generated to be biotinylated. This biotinylated cRNA is then fragmented and hybridized to the Affymetrix HU-133 plus 2.0 chip. The chips are then washed and incubated with streptavidin linked to the fluorescent phycoerythrin. The chip can then be scanned and the fluorescence represented by each oligonucleotide probe measured,

177 A variety of software programs are then used to turn the fluorescence values for each probe into a measure of gene expression with a value of expression generated for each of the 54,613 probesets. Normalisation for the array can be made for median intensity values and the intensity of perfect match probe can be adjusted for the intensity of its mismatch probe.

5.4 Design of the Transcriptome Experiment The initial design of the experiment was for extraction of three independent RNA samples per cell line with subsequent hybridization of each RNA sample to an Affymetrix HU-133 plus 2.0 chip. Due to cost issues (£690 per chip used with University of Manchester Microarray Facility) it was planned to use just four cell lines – one control (ENF), C7, OBF and RA. Two independent microarray facilities both strongly recommended against the use of multiple repeated extractions from the same cell line and instead strongly suggested maximum number of cell lines from different individuals in each group.

The final experiment involved extracting RNA from each of 7 cell lines in duplicate – 3 control cell lines (AF, ENM and ENF) and four 3-M cell lines (C7, OBF, OBR and RA). RNA from each of the duplicate extractions was pooled and hybridized to a single chip. Figure 5.1 summarizes the design of the experiment.

5.5 Quality Control, Analysis Software Used and Initial Data Processing

Scanned data from the chips was entered into dChip for normalization and quality control. Results of dChip analysis are summarized in table 5.1. Around 50% of probesets were called as present (i.e. intensity levels above background representing detection of expression of that probeset’s gene). Median intensity across the datasets varied from 67 – 101, a range that was felt to be acceptable. The percentage of probesets and single probes identified as outliers by the dChip’s algorithm is also listed. All are well below the 15% threshold for discarding the array data

178 (http://biosun1.harvard.edu/complab/dchip//model- based%20expression.htm#outlier_array).

An initial assessment of the data was made with principle component analysis (see figure 5.2). Essentially principle component analysis seeks to reduce the variability in the data set to a smaller number of components (usually two or three components) that represent the major sources of variation between datasets. The ability to separate the two groups (3-M and control) is indicative of good quality data with potential to identify biological differences between groups.

Table 5.1 - dChip analysis of the microarray data.

Cell Line Median % Probesets %Probesets %single probe Intensity called present outliers outliers AF 90 52.2 0.49 0.17 ENM 88 50.4 0.24 0.17 ENF 101 53.3 0.14 0.12 C7 67 47.7 3.07 0.30 OBF 94 52.9 0.19 0.13 OBR 80 51.2 0.15 0.14 RA 71 49.9 0.71 0.20

Further analysis of gene expression was undertaken with PUMA (propagating uncertainty in microarray analysis) (http://www.bioinf.manchester.ac.uk/resources/puma/). Most microarray analysis packages use an initial summarization step to create a single value for each probeset’s expression level. These do not, however, provide any estimate of variance in expression between the probes constituting each probeset. For this reason these methods can only be used to compare arrays with multiple replicates. PUMA derives not only a value for expression for each probeset but also the variability of expression between the probes

179 constituting the probeset. This is helpful for our experiment as we wished not only to compare control to 3-M syndrome patients but also to compare CUL7, OB and RA fibroblasts to controls. As there was only one array for C7 and RA use of conventional array methods would not have allowed any knowledge of variability in gene expression measures to be taken into account (this is not the case for control or OB cell lines since more than 1 array was present for these). The probability of their being a difference in gene expression is not expressed as a p-value in PUMA. Instead it is expressed as a probability of positive log ratio (PPLR). Probesets most likely to be up-regulated are given a PPLR value of 1, those most likely to be down-regulated have a value of -1 and everything else a value in between.

Further analysis of the gene expression data was undertaken with gene ontology analysis via NIH DAVID (http://david.abcc.ncifcrf.gov/). Gene ontology is a controlled vocabulary for describing the biology of a gene product in terms of their biological processes, cellular compartment and molecular function. Biological process refers to a biological objective to which the gene or gene product contributes and often accomplished via multiple molecular functions. Molecular function is defined as the biochemical activity (including specific binding to ligands or structures) of a gene product. Cellular component refers to the place in the cell where a gene product is active. In addition to gene ontology terms lists of probesets were also matched to KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathways.

Lists of up- and down-regulated probesets were examined to determine the presence of gene ontology terms overrepresented within that list. Calculated p-values were adjusted for multiple testing by the Benjamini-Hochberg adjustment.

180

Figure 5.1 – Design of the whole Transcriptome Experiment. 7 cell lines were included – 3 control and four 3-M fibroblast cell lines. For each cell line RNA was extracted in duplicate

181

Figure 5.2 – Principle component analysis of variance in the whole transcriptome data comparing 3-M and control fibroblasts.

182

5.6 Probesets with differential expression between Control and 3-M syndrome fibroblasts

Probesets were defined as being up- or down regulated if there was a +/- 1.5 fold difference in expression between the control and 3-M patient with expression level > 50 in at least one cell line. For C7 1280 probesets were identified as being up-regulated, 1273 probesets for OB and 1320 probesets for RA. 644 up-regulated probesets were shared between all three groups. Up-regulated probesets shared between the different groups are summarized in figure 5.3.

More probesets were identified as being down-regulated than up-regulated – 2244 in C7, 1605 in OB and 1583 for RA. 658 down-regulated probesets were shared between all groups. Down-regulated probesets shared between the different groups are summarized in figure 5.4

A relatively small proportion of probesets up or down regulated are found only in one group e.g. only 84/1583 (5%) of down-regulated probesets in RA are not found in at least one other group. This combined with the 1302 up or down-regulated in all three groups is highly suggestive that there is 3-M gene expression profile shared between patients with mutations in different genes. This altered gene expression profile is likely to include many changes occurring as part of the response to counter the growth impairment in 3-M syndrome as well as gene expression changes which are driving the growth impairment.

183

Figure 5.3 - Venn diagram for number of probesets up-regulated (defined as fold change >1.5 3M/control and expression level >50 in at least one cell line) for C7, OB and RA fibroblasts.

Figure 5.4 - Venn diagram for number of probesets down-regulated (defined as fold change >-1.5 3M/control and expression level >50 in at least one cell line) for C7, OB and RA fibroblasts.

184 The top 20 up-regulated probeset in 3-M syndrome (defined as mean of expression for all four 3-M syndrome cell lines available) compared to control (mean of three control cell lines) are listed in table 5.2. A description of each gene and its function is given below.

ZIC1 Zinc finger protein of cerebellum 1 (ZIC1) is a transcription factor which, in mouse, is predominantly expressed within the nervous system with the highest levels of expression in the cerebellum (Aruga et al., 1994). The gene is located at 3q24 and encodes a transcript of 5241 bp and a protein of 447 aa. A heterozygous continuous deletion of ZIC1 and ZIC4 has been identified in a patient with Dandy Walker syndrome (Grinberg et al., 2004). ZIC1 expression is down-regulated in gastric carcinomas (Wang et al., 2009) and increased in desmoid tumour fibroblasts (Pourebrahim et al., 2007) and in brain tumours (medulloblastomas and meningiomas) (Aruga et al., 2010, Yokota et al., 1996).

Given the paucity of data available on the function of ZIC1 it is difficult to accurately assess its potential role in 3-M syndrome. Despite its name it is clearly expressed outside nervous tissue, including in skin fibroblasts, and its expression pattern is altered in states of altered growth (Pourebrahim et al., 2007). It may therefore have a role in the pathophysiology of 3-M syndrome.

PCP4 Purkinje cell protein 4 (PCP4), like ZIC1, is predominantly expressed within the cerebellum (Cabin et al., 1996). The gene is located at 21q22, encodes a transcript of 660 bp and a protein of 62 aa. It binds to calmodulin (Johanson et al., 2000), is known to inhibit apoptosis (Erhardt et al., 2000), is overexpressed in uterine leiomyomas (Kanamori et al., 2003) and is involved in osteogenic differentiation

Although there is a paucity of data on the functions of PCP4 and its involvement with growth, given its overexpression in a benign tumour and

185 antiapoptotic effect, it is likely that overexpression of PCP4 in 3-M syndrome is an attempt to promote growth in response to the impaired growth of 3-M syndrome.

HOXC6 Homeobox C6 (HOXC6) is a transcription factor expressed in the developing spinal cord and vertebrae in the mouse embryo and in the adult mouse is expressed in kidney and testis (Sharpe et al., 1988). Overexpression of HOXC6 in mouse lead to skeletal abnormalities particularly formation of additional ribs (Jegalian and De Robertis, 1992). HOXC6 is located at 12q13 and encodes two transcripts of 1681 and 581 bp with proteins of 235 and 72 aa.

Expression of HOXC6 in a gastrointestinal carcinoid cell line leads to enhanced growth while siRNA mediated knockdown leads to impaired cell growth (Fujiki et al., 2008). HOXC6 is expressed in a wide variety of tumours including oesophageal (Chen et al., 2005), lung (Bodey et al., 2000a) and breast carcinomas (Bodey et al., 2000b), medulloblastomas (Bodey et al., 2000c) and osteosarcomas (Bodey et al., 2000d). Given the overexpression and knock down data in gastric carcinoids it is most likely HOXC6 is up- regulated in 3-M syndrome in an attempt to improve growth.

HOXA9 Homeobox A9 (HOXA9) is a transcription factor involved in myeloid differentiation. It is located at 7p15-14.2 encodes two transcripts of 2037 bp and 108 bp with proteins of 272 and 112 aa. It is widely expressed both in fetal and adult tissues (Kim et al., 1998). A translocation of chromosomes 7 and 11 commonly found in acute myeloid leukaemia results in production of a fusion protein involving HOXA9 and NUP98 (Nakamura et al., 1996). In leukaemic cells expression of HOXA9 leads to increased cell proliferation and increased expression of the IGF-1R (Whelan et al., 2008). It is overexpressed in a subset of glioblastomas and leads to increased cell proliferation and reduced apoptosis (Costa et al., 2010a). There are some

186 contrasting results in mammary epithelial cells and breast cancer where decreased HOXA9 leads to increased growth and development of a malignant phenotype (Gilbert et al., 2010).

Given the conflicting data it is difficult to accurately predict whether HOXA9 is involved in growth impairment or the cellular response to compensate for the impaired growth.

IL13RA2 Interleukin 13 receptor alpha 2 (IL3RA2) encodes one component of the interleukin 13 receptor, is located at Xq24 , encodes a transcript of 4036 bp and a protein of 427 aa. The IL-13 receptor is involved in signal transduction following stimulation with its ligand, interleukin 13. IL-13 signalling is important in the immune response to asthma, systemic sclerosis and protection from nematodes. (Granel et al., 2006, Granel et al., 2007) IL13RA2 knockout mice display no abnormalities of size or weight (Wood et al., 2003). It is overexpressed in glioblastomas, medulloblastomas (Marie et al., 2008), prostate cancer and adrenocortical tumours (Fernandez-Ranvier et al., 2008). In breast tumour cells increased expression of IL13RA2 is linked with the development of metastases (Minn et al., 2005).

It is likely that IL13RA2 overexpression is acting to promote growth given the data from studies in tumours.

COL14A1 Collagen type 14 alpha 1 (COL14A1), also known as undulin, is a large glycoprotein of the extracellular matrix. The COL14A1 gene is located at 8q23 and encodes multiple splice variants with transcripts varying in size from 697 to 6466 bp with proteins varying in size from 149 to 1796 aa. In 3T3 preadipocytes COL14A1 has an antiproliferative effect and in fibroblasts it causes the development of clusters of cells (Ruehl et al., 2005). Knockdown of COL14A1 in renal cancer cells with siRNAs resulted in increased growth (Morris et al., 2010).

187

In the context of a small number of studies examining the effects of COL14A1 on cell proliferation which have shown contrasting results, it is difficult to postulate the role COL14A1 is likely to play in 3-M syndrome but it may act to reduce growth.

GPC6 Glypican 6 is a heparan suphate proteoglycan which is linked to the extracellular surface of the cell membrane. Glypicans are expressed during development and are thought to control availability of local growth factors (Filmus, 2001). GPC6 is located at 13q32 and encodes a transcript of 2624bp and a protein of 555 aa. Loss of function mutations in GPC6 leads to impaired endochondral ossification and cause the short stature condition omodysplasia (Campos-Xavier et al., 2009).

Since loss of GPC6 function leads to growth impairment it is likely the increased GPC6 expression in 3-M syndrome serves to promote growth, potentially via increasing availability of growth factors.

CLU Clusterin (CLU) is a glycoprotein expressed in virtually all tissues with both secreted and nuclear localisation. The CLU gene is located at 8p21 and encodes a single transcript of 2903 bp and protein of 501 aa. Upregulation of clusterin has been identified in several tumour types and roles in apoptosis, DNA repair and cell cycle regulation have been identified (Shannan et al., 2006). Conflicting data exists on whether CLU acts to promote or inhibit cell growth: one hypothesis is that secreted clusterin acts to promote cell survival while nuclear clusterin acts to promote cell death (Shannan et al., 2006).

Overall further studies are required to assess changes in the levels of secreted and nuclear components of clusterin in order to elucidate its function in 3-M syndrome.

188

ABCA6 ATP binding cassette sub family A member 6 (ABCA6) is one of a family of transporter proteins responsible for translocation of a variety of substrates across cellular membranes. It is ubiquitously expressed with highest levels in heart, brain and lung (Kaminski et al., 2001). The ABCA6 gene is located at 17q24.2 and encodes transcripts of 733 and 5296 bp with proteins of 185 and 1617 aa. The function of the transporter is unknown but it is overexpressed in B-cell chronic lymphocytic leukaemia (Jelinek et al., 2003).

SCARA3 Scavenger receptor class A member 3 is involved in the protection of cells from oxidative stress by depleting reactive oxygen species within the cell. The SCRA gene is located at 8p21 and encodes transcripts of 3631 and 1909 bp with proteins of 606 and 466 aa. Limited data on function are available but SCARA3 is up-regulated in prostate tumour and appears to have a tumour suppressor role (Yu et al., 2006).

It may be that a propensity towards apoptosis in 3-M cells is compensated for by increased protection from oxidative stress mediated by upregulation of SCARA3. It is also possible that upregulation of SCRA3 with a tumour suppressor effect might directly impair cell proliferation and contribute to the growth impairment in 3-M syndrome.

SPON1 Spondin 1 (also known as F-spondin) is a secreted extracellular matrix protein responsible for regulating axon outgrowth during development (Tzarfaty-Majar et al., 2001). Spondin 1 is up-regulated in osteoarthritis (Attur et al., 2009) but its role in growth is unclear outside the developing embryo.

HOXA11, HOXA10 and TBX5 HOXA11, HOXA10 and TBX5 although in the top 20 up-regulated probesets all had a PPLR value between 0.4 – 0.6 indicating less certainly that these

189 probesets were indeed up-regulated. Examination of the expression pattern in each cell line for these probesets demonstrated expression in one control cell line for each probeset where expression was similar to that found in 3-M syndrome cells. It is likely therefore that no true difference exists in expression of these genes between control and 3-M cell lines.

190

Table 5.2 – Top 20 probesets with expression up-regulated (defined as fold change >1.5 3M/control and expression level >50 in at least one cell line) in 3-M fibroblasts (n=4) compared to control fibroblasts (n=3).

Gene title Gene Mean Mean Fold PPLR Symbol Expression expression Change control 3-M 3M/control

Zic family member 1 ZIC1 0.16 171.85 1087.41 1.00

Purkinje cell protein 4 PCP4 0.36 185.70 513.42 1.00 homeobox C6 HOXC6 2.40 615.78 256.07 0.99 homeobox A10 HOXA10 1.40 311.76 223.27 0.55 homeobox A9 HOXA9 1.83 346.95 189.98 1.00 interleukin 13 receptor, alpha 2 IL13RA2 6.27 779.20 124.27 1.00 collagen, type XIV, alpha 1 COL14A1 1.28 145.45 113.88 1.00 glypican 6 GPC6 5.51 591.28 107.25 1.00 clusterin CLU 7.84 795.86 101.45 1.00 solute carrier member 15 SLC6A15 1.42 117.15 82.29 1.00 homeobox A10 HOXA10 1.56 119.92 77.09 0.44 homeobox A11 HOXA11 1.70 110.64 64.95 0.55 ------0.92 58.79 64.19 1.00 clusterin CLU 27.67 1615.08 58.36 1.00 ------19.59 1056.75 53.95 1.00

ATP-binding cassette, sub-family A (ABC1), member 6 ABCA6 1.08 55.21 51.35 1.00 scavenger receptor class A, member 3 SCARA3 1.99 98.58 49.55 1.00 homeobox A9 HOXA9 2.83 132.41 46.71 1.00 spondin 1, extracellular matrix protein SPON1 0.90 39.95 44.36 1.00 T-box 5 TBX5 2.98 129.64 43.48 0.57

191 The top 20 probesets down regulated in 3-M syndrome (defined as mean of expression for all four 3-M syndrome cell lines available) compared to control (mean of three control cell lines) are listed in table 5.3. A description of each gene and its function is given below.

IGF2 Insulin-like growth factor 2 (IGF-II) is a 7.5 kDa secreted hormone that acts to increase cell proliferation via stimulation of the IGF1R. IGF-II is discussed in chapter 1 – it is widely expressed during development and a major regulator of intra-uterine growth. IGF2 expression is regulated by methylation of the H19 differentially methylated region with the paternally methylated allele expressing IGF2. Hypomethylation of the H19 DMR with subsequent IGF2 gene silencing leads to the short stature condition Silver-Russell syndrome (Gicquel et al., 2005). Silver Russell syndrome shares several key features with 3-M syndrome:  Intra-uterine growth retardation  Postnatal growth impairment  Relatively normal OFC  Normal or mildly impaired intelligence  Triangular shaped face Of the top 10 down-regulated probesets in 3-M syndrome fibroblasts, three of these represented IGF2. Furthermore the suppression of IGF2 expression was present in all four 3-M syndrome cell lines tested. Given the clinical overlap with Silver Russell syndrome (a short stature condition known to be caused by reduced IGF2 expression) it is highly probably that reduced IGF2 expression is a key mediator of the growth impairment seen in 3-M syndrome.

Leptin Leptin is a 16 kDa adipocyte derived hormone which plays a central role in regulating body weight both in man and mouse by inhibiting food intake and increasing energy expenditure (Montague et al., 1997, Zhang et al., 1994). The leptin gene (LEP) is located at chromosome 7q13, spans 20 kbp and

192 contains 3 exons (Isse et al., 1995). LEP expression is induced by obesity, insulin, tumour necrosis factor –α and glucocorticoids and is negatively regulated by β-adrenoreceptor agonists and thiazolidinediones (Tartaglia et al., 1995). Congenital leptin deficiency is associated with hypogonadotrophic hypogonadism, hyperinsulinaemia and abnormalities of cellular immune function with changes in both the number and function of T cells (Bray and York, 1971, Lord et al., 1998, Swerdloff et al., 1976).

Down regulation of leptin in 3-M syndrome may represent a response to the patients slim body habitus or a response to drive energy intake in order to promote growth.

BEX1 Brain expressed X-linked 1 gene is located at Xq22 and encodes a 15 kDa protein which is widely expressed (Yang et al., 2002). Bex1 knockout mice display normal growth but have a reduction in exercise performance and skeletal muscle regeneration (Koo et al., 2007). Downregulation of BEX1 in PC12 cells (a neuronal cell line) lead to increased cell proliferation (Vilar et al., 2006) and in K562 cells (a leukaemic cell line) it lead to inhibition of apoptosis (Ding et al., 2009).

While the data on BEX1 remain sparse a tentative interpretation would be a reduction in BEX1 should promote cell growth and inhibit apoptosis.

PTGDS Prostaglandin D2 synthase brain isoform is a 21kDa protein, predominantly expressed in brain that is responsible for the conversion of prostaglandin H2 to prostaglandin D2. Prostaglandin D2 is involved in platelet aggregation, smooth muscle contraction and may be involved in regulating sleep (Hayaishi, 1999). Evidence for a role in growth comes from the down regulation of PTGDS in leiomyomas (Arslan et al., 2005). PTDGS metabolites inhibit cell proliferation and development of malignant states in a

193 model of oral cancer (Banerjee et al., 2005). Although the data is limited it appears loss of PTGDS would promote growth. COL4A1 Collagen IV alpha 1 (COL4A1) is the main component of type IV collagen which forms basement membrane. Mutations in COL4A1 are linked to porencephaly and cerebral small vessel disease (Lanfranconi and Markus, 2010). It is up-regulated in brain tumours (Liu et al., 2010) and oral squamous cell carcinoma (Chen et al., 2008).

Transcriptional control of COL4A1 is under control of the CTC binding factor (more commonly known as CTCF) (Genersch et al., 1995). CTCF is also responsible for binding to the unmethylated DNA in the H19 DMR and effectively controls IGF2 transcription. A mechanism affecting CTCF or DNA methylation could result in changes in the transcription of both IGF2 and COL4A1.

LGR5 Leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5) is one member of the G protein coupled receptor superfamily. The LGR5 gene is located at 12q15 and encodes transcripts of 2880 and 2620 bp with proteins of 907 and 707 aa. It is expressed in intestinal cells, hepatocellular cacinoma and hair follicles and is a target the Wnt pathway (Barker et al., 2007, McClanahan et al., 2006, Yamamoto et al., 2003). In basal cell carcinoma cells upregulation of LGR5 is associated with increased cell proliferation and silencing of LGR5 is associated with decreased cell proliferation (Tanese et al., 2008). If these results were extrapolated to normal growth loss of LGR5 may be impairing growth in 3-M syndrome.

GRIK2 GRIK2 (glutamate receptor, ionotropic, kainite 2) is a member of the glutamate receptor family that constitute the main excitatory neurotransmitter receptors in the mammalian brain (Paschen et al., 1994). GRIK2 is located at 6q21 and encodes multiple splice variants between 520 and 4789 bp.

194 Mutations in GRIK2 are associated with autosomal recessive mental retardation (Motazacker et al., 2007). In gastric carcinomas GRIK2 is epigenetically silenced and this silencing is associated with increased colony formation and cell migration (Wu et al., 2010). The gastric cancer study provides the only data on GRIK2 and growth while extrapolating from one study is questionable it would suggest loss of GRIK2 to potentially impair growth.

WFDC1 Wap four disulphide core domain 1 (WFDC1) is a protease inhibitor. WFDC1 is located at 16q24 and encodes a single transcript of 1534 bp and protein 220 aa. It was originally identified as a homolog of rat ps20 secreted growth inhibitor (Larsen et al., 2000) and inhibits growth in cancer derived fibroblasts (Madar et al., 2009). Loss of this protein is therefore likely to promote growth but once again the available data on growth is sparse.

TFAP2A TFAP2A (transcription factor AP-2 alpha) is a transcription factor involved in skeletal development; mutations lead to brachiooculofacial syndrome (Milunsky et al., 2008). It is expressed in the developing growth plate and knockout mice display body wall, neural tube and skeletal abnormalities (Zhang et al., 1996). TFAP2A is activated following stimulation of the epidermal growth factor receptor and acts to suppress epidermal growth factor receptor mediated gene expression – i.e. as a check to regulate expression of genes involved in promoting growth (Alexandrescu et al., 2009). Loss of this transcription factor should therefore promote growth.

RARRES2 The retinoic acid receptor responder 2 (RARRES) gene encodes the adipokine chemarin. The RARRES gene is located at 7q36 encodes a transcript of 740 bp protein of 168 aa. Chemarin, a known chemokine, is present in areas of inflammation and induces leukocyte inflammation (Du and Leung, 2009). Plasma levels of chemarin are increased in obese and

195 diabetic subjects (Parlee et al., Yang et al.). One study has also identified a role for chemarin in osteoblast differentiation (Muruganandan et al.). It is likely that the same reasons underling the reduction in leptin (i.e. the slim body habitus) underlie the reduction in chemarin gene transcription. A less likely option is that lack of chemarin impairs osteoblast differentiation and this affects bone growth at the growth plate.

APOE Apolipoprotein E (APOE) is one of nine apolipoproteins which combine with lipids to form lipoprotein particles responsible for transport of lipids throughout the circulation. APOE associates with lipid to form chylomicrons, high density lipoprotein and very low density lipoprotein. Mutations in APOE lead to type III hyperlipoproteinaemia (Wardell et al., 1987) and predispose to poorer outcome following brain injury (Teasdale et al., 1997) and increased risk of Alzheimer’s disease (Saunders et al., 1993). It is not clear what role loss of APOE has in growth or 3-M syndrome.

WNT5A Wingless-type MMTV integration site family, member 5A (WNT5A) is a member of the WNT family of secreted signalling proteins. The WNT5A gene is located on chromosome 3p21 encodes several transcripts from 710 to 6042 bp and proteins of 214 to 380 aa. WNT5A binds to the frizzled-5 receptor and stimulation results in recruitment of actin and myosin IIB (Witze et al., 2008). There is evidence for both a tumour suppressing and tumour promoting role (McDonald and Silver, 2009) and that WNT5A regulates chondrocyte differentiation (McDonald and Silver, 2009). The role of WNT5A in growth remains unclear and therefore it is difficult to hypothesize whether loss in 3-M syndrome would promote or impair growth.

EDIL3 EGF-like repeats and discoidin I-like domains 3 (EDIL3) is a glycoprotein secreted by endothelial cells which is known to associate both with endothelial cell surface and the extracellular matrix. EDIL3 is known to

196 induce apoptosis in COS-7 cells (Kitano et al.) and is overexpressed in hepatoblastomas (Luo et al., 2006).

SIM2 Single minded 2 (SIM2) is a homolog of a drosophila transcription factor responsible for neurogenesis. Deletion of Sim2 in mouse results in craniofacial abnormalities (Shamblott et al., 2002). SIM2 is overexpressed in prostate, colon, breast and brain tumours (Aleman et al., 2005, Halvorsen et al., 2007, de Zegher et al., 2000, Kwak et al., 2007). In colon cells knock down of SIM2 resulted in growth inhibition and an increase in apoptosis (Aleman et al., 2005).

SYNPO2 Synaptopodin 2 (SYNPO2) is a smooth muscle protein that binds to calmodulin, actin and mysosin. It is thought to have a role in organising the cytoskeleton (Schroeter et al., 2008). Any role in growth is unclear but given OBSL1 is a cytoskeletal protein expressed in muscle it is possible that alterations in OBSL1 produce gene transcription changes in other components of the cytoskeleton.

PPP1R14A Protein phosphatase 1, regulatory (inhibitor) subunit 14A is a phosphorylase dependant inhibitor of smooth muscle myosin phosphatase. PPP1R14A is also involved in tumourigenesis and epigenetically silenced in oesophageal cancer (Jin et al., 2006, Oka et al., 2009).

197

Table 5.3 – Top 20 probesets with expression down-regulated (defined as fold change >-1.5 3M/control and expression level >50 in at least one cell line) in 3-M fibroblasts (n=4) compared to control fibroblasts (n=3).

Gene title Gene Mean Mean Fold PPLR Symbol Expressio expression Change n control 3-M 3M/control

insulin-like growth factor 2 IGF2 2118.84 0.06 -38253.37 0.00 leptin LEP 64.69 0.10 -642.51 0.00

insulin-like growth factor 2 IGF2 94.15 0.17 -549.78 0.00 ------194.80 0.61 -318.84 0.00 brain expressed, X-linked 1 BEX1 369.40 1.30 -283.28 0.00 prostaglandin D2 synthase 21kDa (brain) PTGDS 136.49 0.62 -219.06 0.00 collagen, type IV, alpha 1 COL4A1 199.37 1.09 -183.08 0.03 leucine-rich repeat-containing G protein-coupled receptor 5 LGR5 270.20 1.51 -179.24 0.01

insulin-like growth factor 2 IGF2 44.95 0.29 -157.09 0.00 glutamate receptor, ionotropic, kainate 2 GRIK2 44.54 0.35 -126.79 0.00 WAP four-disulfide core domain 1 WFDC1 37.84 0.37 -101.50 0.00 transcription factor AP-2 alpha (activating enhancer binding protein 2 alpha) TFAP2A 668.76 6.97 -95.97 0.00

retinoic acid receptor responder (tazarotene induced) 2 RARRES2 1082.00 13.55 -79.87 0.03 apolipoprotein E APOE 89.49 1.18 -76.13 0.01

wingless-type MMTV integration site family, member 5A WNT5A 832.09 13.47 -61.76 0.00 EGF-like repeats and discoidin I- like domains 3 EDIL3 767.38 13.01 -58.98 0.30 single-minded homolog 2 (Drosophila) SIM2 45.75 0.81 -56.75 0.01 ------23.67 0.42 -56.03 0.00 synaptopodin 2 SYNPO2 492.79 8.86 -55.64 0.01

protein phosphatase 1, PPP1R14 regulatory (inhibitor) subunit 14A A 39.87 0.73 -54.83 0.03

198 There were 48 biological process gene ontology terms significantly over represented in the top 500 up regulated probesets (see Table 5.4). These terms centred around skeletal development, embryogenesis with other included terms covering cell adhesion, signalling and neuron development. Molecular function gene ontology terms over represented contained many terms related to binding (polysaccharide, carbohydrate, glycoaminoglycan, calcium and heparin binding) and a significant increase in transcription factors (see Table 5.5). There were six cellular compartment terms over represented all of which related to the extracellular compartment (see Table 5.6). There were no KEGG pathways significantly over represented in the up- regulated probesets (defined as a benjamini-hochberg p-value <0.05), however, using a standard p-value <0.05 unadjusted for multiple testing identified 5 pathways including ECM interaction and Cytokine-cytokine receptor interaction (see Table 5.7).

For the top 500 downregulated probesets five biological process gene ontology terms were over represented covering cell adhesion and cell – cell signalling (see Table 5.8). For molecular function gene ontology terms there were no terms identified as being significantly over represented after adjustment for multiple testing. Five molecular function terms were over represented using an unadjusted p-value <0.05 and these included extracellular matrix constituent, cytoskeletal protein binding and actin binding (see table 5.9). Six cellular compartment gene ontology terms were over represented and these all related to the extracellular compartment (see table 5.10). Two KEGG pathways were significantly over represented after adjustment for multiple testing – cell adhesion molecules and ECM receptor interaction (see table 5.11).

199 Table 5.4 – Biological Process Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for 3-M (n=4) compared to control (n=3). Gene Ontology Term Count % Fold BH p- Change value skeletal system development 27 7.965 4.174 <0.001 Regionalization 21 6.195 5.360 <0.001 anterior/posterior pattern formation 18 5.310 6.486 <0.001 embryonic morphogenesis 26 7.670 4.219 <0.001 pattern specification process 24 7.080 4.506 <0.001 skeletal system morphogenesis 16 4.720 7.064 <0.001 cell adhesion 36 10.619 2.591 <0.001 biological adhesion 36 10.619 2.587 <0.001 cell morphogenesis involved in <0.001 differentiation 20 5.900 4.118 embryonic organ morphogenesis 14 4.130 5.319 <0.001 embryonic organ development 15 4.425 4.402 0.001 cell morphogenesis 22 6.490 3.098 0.001 neuron development 21 6.195 3.109 0.002 cartilage development 10 2.950 6.713 0.002 enzyme linked receptor protein signalling pathway 21 6.195 3.036 0.002 cell-cell signalling 29 8.555 2.417 0.003 cellular component morphogenesis 22 6.490 2.786 0.004 cell morphogenesis involved in neuron differentiation 15 4.425 3.621 0.007 neuron projection morphogenesis 15 4.425 3.569 0.007 proximal/distal pattern formation 6 1.770 12.785 0.007 appendage morphogenesis 10 2.950 5.052 0.013 limb morphogenesis 10 2.950 5.052 0.013 neuron differentiation 22 6.490 2.531 0.013 positive regulation of developmental process 17 5.015 3.008 0.013 neuron projection development 16 4.720 3.149 0.013 appendage development 10 2.950 4.852 0.015 limb development 10 2.950 4.852 0.015 axon guidance 10 2.950 4.805 0.015 positive regulation of cell differentiation 15 4.425 3.224 0.015 regulation of bone mineralization 6 1.770 9.802 0.019 cell projection morphogenesis 15 4.425 3.089 0.022 embryonic limb morphogenesis 9 2.655 5.070 0.022 embryonic appendage morphogenesis 9 2.655 5.070 0.022 epithelial to mesenchymal transition 5 1.475 13.613 0.023 negative regulation of cell differentiation 14 4.130 3.221 0.022 regulation of biomineral formation 6 1.770 9.189 0.022 Axonogenesis 13 3.835 3.407 0.022 cell part morphogenesis 15 4.425 2.952 0.028 kidney development 9 2.655 4.594 0.035 regulation of cell development 13 3.835 3.202 0.036 response to wounding 23 6.785 2.176 0.041 forelimb morphogenesis 5 1.475 11.138 0.040 embryonic skeletal system development 8 2.360 5.092 0.040 regulation of ossification 8 2.360 5.092 0.040 embryonic skeletal system morphogenesis 7 2.065 6.018 0.042 cell projection organization 18 5.310 2.457 0.044 D-aspartate transport 3 0.885 49.008 0.048 D-aspartate import 3 0.885 49.008 0.048

200 Table 5.5 – Molecular Function Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for 3-M (n=4) compared to control (n=3).

Gene ontology term Count % Fold BH p-value Change metallopeptidase activity 15 4.425 4.109 0.007 sequence-specific DNA binding 28 8.260 2.457 0.005 polysaccharide binding 13 3.835 4.212 0.008 pattern binding 13 3.835 4.212 0.008 carbohydrate binding 19 5.605 2.779 0.018 transcription factor activity 36 10.619 1.934 0.016 glycosaminoglycan binding 11 3.245 3.923 0.035 carboxypeptidase activity 6 1.770 8.040 0.049 calcium ion binding 33 9.735 1.851 0.043 exopeptidase activity 8 2.360 5.151 0.041 heparin binding 9 2.655 4.375 0.043

Table 5.6 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets in 3-M (n=4) compared to control (n=3).

Gene ontology term Count % Fold BH p-value Change extracellular region 79 23.304 2.084 <0.001 extracellular region part 46 13.569 2.413 <0.001 extracellular matrix 22 6.490 3.165 <0.001 proteinaceous extracellular matrix 20 5.900 3.107 0.001 extracellular space 30 8.850 2.220 0.003

201 Table 5.7 – Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in 3-M (n=4) compared to control. 5 pathways were identified using a significance of p-value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini-Hochberg correction.

KEGG pathway Count % Fold Change p-value BH p-value

Cytokine- cytokine receptor interaction 13 3.835 2.432 0.006 0.493 ECM-receptor interaction 7 2.065 4.023 0.007 0.331 Steroid hormone biosynthesis 5 1.475 5.420 0.013 0.376 Axon guidance 8 2.360 2.958 0.017 0.382 TGF-beta signalling pathway 6 1.770 3.407 0.030 0.489

Table 5.8 – Biological Process Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 down-regulated probesets for 3-M (n=4) compared to control (n=3).

Gene ontology term Count % Fold Change BH p-value cell adhesion 35 10.174 2.612 0.001 biological adhesion 35 10.174 2.608 0.001 positive regulation of cell communication 19 5.523 3.016 0.042 cell-cell signalling 27 7.849 2.350 0.042 cellular metal ion homeostasis 14 4.070 3.731 0.040

202 Table 5.9 – Molecular function gene ontology identified as being over represented compared to background in the top 500 down-regulated probesets in 3-M (n=4) compared to control. 5 pathways were identified using a significance of p-value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini- Hochberg correction. Gene ontology term Count % Fold Change p-value BH p- value

extracellular matrix structural constituent 9 2.616 5.328 0.000 0.122 cytoskeletal protein binding 23 6.686 2.323 0.000 0.085 endopeptidase inhibitor activity 11 3.198 3.862 0.001 0.085 peptidase inhibitor activity 11 3.198 3.660 0.001 0.096 actin binding 16 4.651 2.499 0.002 0.166

Table 5.10 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 down-regulated probesets in 3-M (n=4) compared to control (n=3). Gene Ontology Term Count % Fold BH p- Change value extracellular matrix 27 7.849 3.761 <0.001 extracellular region part 48 13.953 2.403 <0.001 proteinaceous extracellular matrix 25 7.267 3.754 <0.001 extracellular region 74 21.512 1.769 <0.001 basement membrane 11 3.198 6.777 <0.001 extracellular matrix part 13 3.779 5.339 <0.001 collagen type IV 4 1.163 32.035 0.008 external side of plasma membrane 13 3.779 3.675 0.009 sheet-forming collagen 4 1.163 27.459 0.011 cell surface 19 5.523 2.624 0.011 plasma membrane part 68 19.767 1.483 0.016 Collagen 6 1.744 8.238 0.020 contractile fiber 10 2.907 3.971 0.023 terminal button 5 1.453 9.611 0.038 cell-cell junction 12 3.488 3.035 0.044 Myofibril 9 2.616 3.896 0.043 contractile fiber part 9 2.616 3.827 0.046

203 Table 5.11 – Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in 3-M (n=4) compared to control. 13 pathways were identified using a significance of p- value <0.05. Two of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini-Hochberg correction. KEGG pathway Count % Fold p-value BH p- Change value

Cell adhesion molecules (CAMs) 13 3.779 4.173 0.000 0.006 ECM-receptor interaction 9 2.616 4.540 0.001 0.042 Pathways in cancer 18 5.233 2.325 0.001 0.058 Asthma 5 1.453 7.306 0.004 0.123 Allograft rejection 5 1.453 5.885 0.009 0.206 Small cell lung cancer 7 2.035 3.531 0.013 0.239 Vascular smooth muscle contraction 8 2.326 3.027 0.015 0.237 Type I diabetes mellitus 5 1.453 5.045 0.016 0.219 Focal adhesion 11 3.198 2.319 0.019 0.225 Intestinal immune network for IgA production 5 1.453 4.324 0.027 0.283 Systemic lupus erythematosus 7 2.035 2.996 0.028 0.268 Autoimmune thyroid disease 5 1.453 4.154 0.031 0.271 Antigen processing and presentation 6 1.744 3.063 0.044 0.345

204 5.7 Probesets with differential expression between Control and C7 fibroblasts The top 20 up regulated probesets comparing the C7 cell line (n=1) to control cell lines (n=3) are listed in table 5.12. Of these top 20 upregulated probesets 12 were shared with the control v all 3-M cell line upregulated probesets. These 12 probesets represented the genes PCP4, ZIC1, HOXA10, HOXA9, COL14A1, IL13RA2, ABCA6. The remaining eight probesets represented seven genes – thrombospondin 4 (THBS4), tenascin XB (TNXB), a potassium voltage gated channel (KCNB1), Angiotensin converting enzyme (ACE), a Wnt pathway inhibitor (WIF1), solute carrier 6 family member 15 (SLC6A15) and ST8 alpha-N-acetyl-neuraminide alpha- 2,8-sialyltransferase 1 (ST8SIA1).

THBS4 is an extracellular glycoprotein which mediates cell-cell/ cell-matrix interactions and is known to affect expression of fibroblast growth factor (Lawler et al., 1995, Liu et al., 2009). TNXB is also an extracellular matrix protein, deficiency of which causes one form of the hypermobility Ehlers- Danlos syndrome (Schalkwijk et al., 2001). KCNB1 is a potassium channel predominantly expressed in brain and variants in the region of the gene have been associated with systolic blood pressure (Barbalic et al., 2009). ACE is involved in cleavage of angiotensin II from angiotensinogen and involved in regulation of blood pressure. WIF1 is a secreted protein that binds to and inhibits activity of proteins of the Wnt pathway (Hsieh et al., 1999). It is known to have epigenetically altered expression in several tumours (Costa et al., 2010b, Huang et al., 2010). SLC6A15 is one member of a family of Na Cl neurotransmitter transporters and has large extracellular loops (Farmer et al., 2000). ST8SIA1 catalyses the formation of the GD3 ganglioside which has a role in cell-cell adhesion and growth (Sasaki et al., 1994).

ACE and KCNB1, unlike the other genes, do not fit with the overall themes of cell-matrix/adhesion, ECM, growth and transcription factors. It may be that up regulation of ACE and KCNB1 represents part of the process leading to raised blood pressure in SGA children.

205 Table 5.12 – Top 20 probesets with expression up-regulated compared to background (defined as fold change >1.5 C7/control and expression level >50 in at least one cell line) in C7 fibroblasts (n=1) compared to control fibroblasts (n=3).

Gene title Gene Mean Expression Fold PPLR Symbol Expression C7 Change control C7/control

Purkinje cell protein 4 PCP4 0.361692 447.4045 1236.975 1 Zic family member 1 (odd-paired homolog, Drosophila) ZIC1 0.158031 193.3302 1223.367 0.999999 homeobox A10 HOXA10 1.396342 381.6825 273.3446 0.560835 collagen, type XIV, alpha 1 COL14A1 1.277221 279.6671 218.9654 0.999993 homeobox A9 HOXA9 1.82627 365.3607 200.0585 0.98345 interleukin 13 receptor, alpha 2 IL13RA2 6.270284 1241.69 198.0276 1 thrombospondin 4 THBS4 2.401261 472.176 196.6367 1 ------0.915839 144.8466 158.1572 0.999998 homeobox A11 HOXA11 1.703453 199.0758 116.866 0.492884 homeobox C6 HOXC6 2.404712 260.5939 108.3681 0.833737 tenascin XB TNXB 5.563681 572.2938 102.8624 0.850316 potassium voltage-gated channel, Shab-related subfamily, member 1 KCNB1 0.750596 76.43966 101.8386 0.999961 WNT inhibitory factor 1 WIF1 0.623957 56.22644 90.11263 0.999999 glypican 6 GPC6 5.513146 454.9213 82.51574 0.999776 homeobox A10 HOXA10 1.555587 118.6742 76.28898 0.45389

ST8 alpha-N-acetyl- neuraminide alpha-2,8- sialyltransferase 1 ST8SIA1 1.560453 118.5025 75.94109 1 angiotensin I converting enzyme (peptidyl- dipeptidase A) 1 ACE 0.682751 51.69447 75.71497 0.999989 solute carrier family 6 (neutral amino acid transporter), member 15 SLC6A15 1.423607 102.8047 72.21427 0.999916 collagen, type XIV, alpha 1 COL14A1 1.528551 97.25602 63.62628 0.999994 ATP-binding cassette, sub-family A (ABC1), member 6 ABCA6 1.07529 68.19155 63.41687 0.99173

206 The top 20 down regulated probesets comparing the C7 cell line (n=1) to control cell lines (n=3) are listed in table 5.13. Of these 20 probesets 10 are shared with the control v all 3-M cell line down regulated probesets. The shared probesets represent the genes IGF2, LEP, LGR5, COL4A1, APOE, BEX1 and RARRES2. Genes represented by the other probesets represented secreted frizzled related protein 2 (SFRP2), deiodinase, iodothyronine, type II (DIO2), nidogen 2 (osteonidogen) (NID2), latexin (LXN), toll like receptor 4 (TLR4), inter-alpha (globulin) inhibitor H5 (ITIH5), prostate transmembrane protein, androgen induced 1 (PMEPA1) and pregnancy specific beta-1-glycoprotein 7 (PSG7).

SFRP2 is a secreted protein which inhibits signalling via the Wnt pathway by competing with fizzled receptors for Wnt pathway ligands. It has a tumour suppressor role and is epigenetically silenced in some tumours (Kongkham et al., 2010). DIO2 is responsible for conversion of the inactive thyroid hormone thyroxine to active triiodothyroxine (Kohrle, 2007). NID2 is a basement membrane cell adhesion protein. Nid2 -/- mice are phenotypically normal but in a model of glomerular damage Nid2 -/- mice displayed increased blood pressure compared to wild type controls (Amann et al., 2009). LXN is an inhibitor of metallocarboxipeptidase and is epigenetically silenced in melanoma (Muthusamy et al., 2006, Vendrell et al., 2000). TLR4 is involved in signalling in the innate immune response while ITIH5 is an extracellular matrix protein with decreased expression in solid tumours (Hamm et al., 2008). PMPEA is a transmembrane inhibitor of growth in prostate cancer (Richter et al., 2007). PSG7 is expressed by trophoblast and released into the circulation during pregnancy. It is one member of the carcinoembryonic antigen family.

207

Table 5.13 – Top 20 probesets with expression down-regulated compared to background (defined as fold change >-1.5 C7/control and expression level >50 in at least one cell line) in C7 fibroblasts (n=1) compared to control fibroblasts (n=3). Gene title Gene Mean Expression Fold PPLR Symbol Expressi C7 Change on C7/control control insulin-like growth factor 2 IGF2 2118.842 0.007559 -280291 0.001136 leucine-rich repeat- containing G protein- coupled receptor 5 LGR5 270.2014 0.185585 -1455.94 0.009541 collagen, type IV, alpha 1 COL4A1 199.3673 0.142072 -1403.28 0.008585 secreted frizzled-related protein 2 SFRP2 568.6704 0.501463 -1134.02 0.493696 leptin LEP 64.6945 0.066623 -971.058 0.021409 deiodinase, iodothyronine, type II DIO2 369.0105 0.410618 -898.67 0.007101 apolipoprotein E APOE 89.48754 0.147738 -605.718 0.003933 retinoic acid receptor responder (tazarotene induced) 2 RARRES2 1081.997 2.059459 -525.379 0.008205 nidogen 2 (osteonidogen) NID2 556.8959 1.098733 -506.853 0.052294 transcription factor AP-2 alpha (activating enhancer binding protein 2 alpha) TFAP2A 668.7643 1.48559 -450.167 0.001523 ------194.7965 0.541429 -359.782 0.00234 latexin LXN 193.389 0.719513 -268.777 0.042901 insulin-like growth factor 2 IGF2 94.14562 0.350825 -268.355 0.003837 toll-like receptor 4 TLR4 143.0254 0.609962 -234.483 0.003498 apolipoprotein E APOE 129.9947 0.611085 -212.728 0.18591 inter-alpha (globulin) inhibitor H5 ITIH5 88.23414 0.44593 -197.865 0.033434 prostate transmembrane protein, androgen induced 1 PMEPA1 64.21121 0.355383 -180.682 0.415501 pregnancy specific beta- 1-glycoprotein 7 PSG7 293.6689 1.650918 -177.882 0.005682 deiodinase, iodothyronine, type II DIO2 202.466 1.140875 -177.466 0.02259 brain expressed, X-linked 1 BEX1 369.403 1.304 -171.058 0.001

208 There were 53 biological process gene ontology terms over represented in the top 500 up regulated probesets for C7 compared to control (see table 5.14). The terms centred around embryogenesis, cell development/differentiation, cell adhesion and skeletal development. Eight molecular function gene ontology terms were significantly over represented and these were concerned with binding – heparin, carbohydrate, glycoaminoglycan and DNA (see table 5.15). Cellular compartment gene ontology terms significantly over represented included 6 terms all related to extracellular space (see Table 5.16). There were no KEGG pathways over represented after adjustment for multiple testing. Four pathways were significantly over represented before adjustment for multiple testing and these included cytokine-cytokine receptor interaction, axon guidance and TGF-beta signalling (see Table 5.17).

For the top 500 downregulated probesets (comparing C7 to control) there were 178 biological process gene ontology terms significantly over represented prior to adjustment for multiple testing but none of these remained significant after adjustment for multiple testing. The top 20 terms (based on unadjusted p-value) are listed in table 5.18. Although not significant the themes of these terms around cell proliferation, skeletal system and cell adhesion are consistent with other gene ontology findings in this study. There were 13 molecular function gene ontology terms over represented prior to adjustment for multiple hypothesis testing, although none were significant after adjustment (see table 5.19). These 13 terms, however, represented a number of terms related to binding in keeping with the findings for the control v all 3-M molecular function gene ontology analysis. There were three cell compartment gene ontology terms over represented and these all concerned the extracellular compartment (see table 5.20). TGF-beta signalling and Cytokine-cytokine receptor signalling were two of the five KEGG pathways significantly over represented before adjustment for multiple testing (see table 5.21) but none remained significant after adjustment for multiple testing.

209 Table 5.14 – Biological Process Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for C7 (n=1) compared to control (n=3). Gene Ontology Term Count % Fold BH p- Change value anterior/posterior pattern formation 15 4.011 4.92777 0.003856 embryonic morphogenesis 22 5.882 3.254721 0.003888 pattern specification process 20 5.348 3.423636 0.003899 Regionalization 17 4.545 3.955904 0.002945 cell morphogenesis involved in differentiation 19 5.080 3.566767 0.002435 regulation of cell development 17 4.545 3.816752 0.003098 positive regulation of cell differentiation 18 4.813 3.527246 0.00379 positive regulation of developmental process 20 5.348 3.225881 0.00342 positive regulation of cell development 10 2.674 6.475137 0.004447 enzyme linked receptor protein signalling pathway 22 5.882 2.899486 0.004543 skeletal system development 21 5.615 2.959771 0.004976 skeletal system morphogenesis 12 3.209 4.830102 0.005791 cell motion 26 6.952 2.514371 0.005763 cell morphogenesis involved in neuron differentiation 16 4.278 3.521454 0.006758 neuron development 21 5.615 2.834584 0.006666 axon guidance 11 2.941 4.818264 0.010723 cell morphogenesis 21 5.615 2.696113 0.011836 cell migration 18 4.813 2.978563 0.012393 cell-cell signalling 29 7.754 2.203529 0.012668 proximal/distal pattern formation 6 1.604 11.65525 0.012175 neuron projection morphogenesis 15 4.011 3.253285 0.019273 Behaviour 24 6.417 2.341229 0.020872 regulation of neurogenesis 13 3.476 3.585307 0.022529 cell adhesion 31 8.289 2.033821 0.022169 Axonogenesis 14 3.743 3.34491 0.021711 biological adhesion 31 8.289 2.030838 0.02107 appendage morphogenesis 10 2.674 4.606025 0.021526 limb morphogenesis 10 2.674 4.606025 0.021526 positive regulation of neurogenesis 8 2.139 6.058094 0.021652 localization of cell 18 4.813 2.689672 0.025612 cell motility 18 4.813 2.689672 0.025612 limb development 10 2.674 4.423608 0.02614 appendage development 10 2.674 4.423608 0.02614 cellular component morphogenesis 21 5.615 2.424412 0.026074 neuron projection development 16 4.278 2.870904 0.027701 transmembrane receptor protein tyrosine kinase signalling pathway 15 4.011 3.005277 0.027399 extracellular matrix organization 10 2.674 4.296004 0.0286 multicellular organismal macromolecule metabolic process 6 1.604 8.647441 0.030092 neuron differentiation 22 5.882 2.307338 0.029759 regulation of neuron differentiation 11 2.941 3.780484 0.033216 embryonic limb morphogenesis 9 2.406 4.621908 0.034689 embryonic appendage morphogenesis 9 2.406 4.621908 0.034689 positive regulation of cell proliferation 21 5.615 2.288408 0.042316 cell projection morphogenesis 15 4.011 2.815868 0.042591 regulation of nervous system development 13 3.476 3.122687 0.043208 negative regulation of cell differentiation 14 3.743 2.936611 0.043817 extracellular structure organization 12 3.209 3.289211 0.04622

210 Table 5.15 – Molecular Function Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for C7 (n=1) compared to control (n=3). Gene ontology term Count % Fold BH p-value Change metallopeptidase activity 16 4.278 3.917026 0.006398 pattern binding 14 3.743 4.054634 0.00925 polysaccharide binding 14 3.743 4.054634 0.00925 heparin binding 11 2.941 4.778676 0.014546 sequence-specific DNA binding 28 7.487 2.195961 0.020125 carbohydrate binding 20 5.348 2.614239 0.021514 glycosaminoglycan binding 12 3.209 3.825441 0.022339

Table 5.16 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets in C7 (n=1) compared to control (n=3). Gene ontology term Count % Fold BH p-value Change extracellular region 86 22.995 2.072 <0.001 extracellular region part 53 14.171 2.538 <0.001 extracellular matrix 25 6.684 3.285 <0.001 proteinaceous extracellular matrix 23 6.150 3.263 <0.001 extracellular space 33 8.824 2.231 0.001

211 Table 5.17 – Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in C7 (n=1) compared to control. Four pathways were identified using a significance of p-value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini-Hochberg correction.

KEGG pathway Count % Fold Change p-value BH p-value

Axon guidance 9 2.406 2.840 0.013 0.778 TGF-beta signalling pathway 7 1.872 3.392 0.016 0.609 O-Glycan biosynthesis 4 1.070 5.428 0.035 0.755 Cytokine- cytokine receptor interaction 12 3.209 1.916 0.045 0.739

212 Table 5.18 – Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for C7 (n=1) compared to control (n=3). No gene ontology terms were over represented using a Benjamini-Hochberg adjusted p-value of <0.05. There were 178 gene ontology terms over represented using a definition of a p- value <0.05. The top 20 are presented. Gene ontology term Count % Fold p-value BH p-value Change acute inflammatory response 11 2.75 4.924 0.000 0.159 skeletal system development 21 5.25 2.728 0.000 0.190 regulation of cell proliferation 37 9.25 1.946 0.000 0.295 negative regulation of biosynthetic process 29 7.25 2.110 0.000 0.467 negative regulation of macromolecule metabolic process 34 8.5 1.939 0.000 0.531 positive regulation of cell proliferation 23 5.75 2.310 0.000 0.619 regulation of coagulation 7 1.75 7.032 0.000 0.625 negative regulation of cellular biosynthetic process 28 7 2.082 0.000 0.632 cellular calcium ion homeostasis 14 3.5 3.203 0.000 0.639 calcium ion homeostasis 14 3.5 3.117 0.001 0.734 negative regulation of macromolecule biosynthetic process 27 6.75 2.059 0.001 0.786 heart development 15 3.75 2.900 0.001 0.798 cellular metal ion homeostasis 14 3.5 2.988 0.001 0.860 regulation of cell motion 14 3.5 2.988 0.001 0.860 negative regulation of gene expression 25 6.25 2.072 0.001 0.909 cell adhesion 31 7.75 1.875 0.001 0.924 biological adhesion 31 7.75 1.872 0.001 0.928 metal ion homeostasis 14 3.5 2.854 0.001 0.950 immune response 29 7.25 1.890 0.001 0.970 negative regulation of transcription 23 5.75 2.091 0.002 0.973

213 Table 5.19 – Molecular Function Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for C7 (n=1) compared to control (n=3). Thirteen pathways were identified using a significance of p-value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini- Hochberg correction.

Gene ontology term Count % Fold p-value BH p-value Change transcription repressor activity 20 5 2.611 0.000 0.128 extracellular matrix structural constituent 9 2.25 4.327 0.001 0.261 cytoskeletal protein binding 23 5.75 1.895 0.005 0.610 endopeptidase inhibitor activity 10 2.5 3.096 0.005 0.507 peptidase inhibitor activity 10 2.5 2.919 0.007 0.562 structural molecule activity 25 6.25 1.714 0.011 0.648 opsonin binding 3 0.75 17.515 0.011 0.605 complement binding 3 0.75 15.326 0.015 0.656 enzyme inhibitor activity 13 3.25 2.108 0.021 0.732 MHC class II receptor activity 3 0.75 11.146 0.028 0.800 cytoskeletal adaptor activity 3 0.75 9.431 0.039 0.868 calcium ion binding 31 7.75 1.433 0.041 0.860 double-stranded RNA binding 4 1 4.954 0.046 0.868

Table 5.20 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 down-regulated probesets in C7 (n=1) compared to control (n=3).

Gene ontology term Count % Fold BH p-value Change proteinaceous extracellular matrix 26 6.5 3.509 <0.001 extracellular matrix 27 6.75 3.379 <0.001 extracellular region part 45 11.25 2.024 0.001

214 Table 5.21 – Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in C7 (n=1) compared to control (n=3). Five pathways were identified using a significance of p-value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini- Hochberg correction.

KEGG pathway Count % Fold p-value BH p-value Change

Systemic lupus erythematosus 8 2 3.544 0.007 0.593

Cell adhesion molecules (CAMs) 10 2.5 2.838 0.008 0.411

Asthma 4 1 5.381 0.036 0.807 Intestinal immune network for IgA production 5 1.25 3.864 0.038 0.730 Wnt signalling pathway 9 2.25 2.209 0.048 0.736

215 5.8 Probesets with differential expression between Control and OB fibroblasts

The top 20 up regulated probesets comparing expression in the control cells (n=3) to OB cells (n=2) are listed in table 5.22. 16 out of the 20 probesets were also present in the top 20 up-regulated probesets for control v all 3-M. The remaining probesets represented three genes; synuclein, alpha (non A4 component of amyloid precursor) (SNCA), cytochrome P450, family 3, subfamily A, polypeptide 5 (CYP3A5) and sorting nexin 10 (SNX10).

SNCA is expressed in the brain with accumulations of SNCA being present in Alzheimer’s disease plaques. It has an antiapoptotic function in neurons (Alves Da Costa et al., 2002) and this may be why it is up regulated in 3-M syndrome. CYP3A5 encodes one of the enzymes of the cytochrome p450 family and variations in this gene have been shown to be associated with hypertension (Givens et al., 2003). The function of SNX10 is unclear but it may be involved in endosome transport (Qin et al., 2006).

216 Table 5.22 – Top 20 probesets with expression up-regulated compared to background (defined as fold change >1.5 OB/control and expression level >50 in at least one cell line) in OB fibroblasts (n=2) compared to control fibroblasts (n=3).

Gene title Gene Mean Expression Fold PPLR Symbol Expression OB Change control OB/control

Zic family member 1 (odd-paired homolog, Drosophila) ZIC1 0.158 143.859 910.321 1.000 Purkinje cell protein 4 PCP4 0.362 210.518 582.037 1.000 homeobox C6 HOXC6 2.405 793.266 329.880 1.000 collagen, type XIV, alpha 1 COL14A1 1.277 330.576 258.824 1.000 synuclein, alpha (non A4 component of amyloid precursor) SNCA 2.348 567.682 241.732 1.000 homeobox A10 HOXA10 1.396 299.848 214.738 0.534 homeobox A9 HOXA9 1.826 350.145 191.727 0.994 clusterin CLU 7.845 1449.264 184.740 1.000 ------0.916 155.281 169.550 1.000 cytochrome P450, family 3, subfamily A, polypeptide 5 CYP3A5 0.555 77.835 140.326 1.000 solute carrier family 6 (neutral amino acid transporter), member 15 SLC6A15 1.424 185.926 130.602 1.000 interleukin 13 receptor, alpha 2 IL13RA2 6.270 717.392 114.411 1.000 glypican 6 GPC6 5.513 599.252 108.695 1.000 clusterin CLU 27.673 2528.220 91.360 1.000 spondin 1, extracellular matrix protein SPON1 0.901 74.995 83.269 1.000 scavenger receptor class A, member 3 SCARA3 1.989 144.640 72.709 1.000 homeobox A10 HOXA10 1.556 111.696 71.803 0.423 ATP-binding cassette, sub-family A (ABC1), member 6 ABCA6 1.075 76.423 71.072 0.999 spondin 1, extracellular matrix protein SPON1 1.811 125.927 69.534 1.000 sorting nexin 10 SNX10 3.779 261.754 69.259 1.000

217 The top 20 down-regulated probesets comparing expression in the OB cells to control are listed in table 5.23. 13 of these probesets were also present in the top 20 down-regulated probesets comparing all 3-M cells to control. The remaining seven probesets; insulin like growth factor binding protein 5 (IGFBP5), insulin like growth factor binding protein 7 (IGFBP7), hyaluronan and proteoglycan link protein 1 (HAPLN1), tumour protein D52-like 1 (TPD52L1), murine retrovirus integration site 1 homolog (MRVI1) and syntaxin binding protein 6 (amisyn) (STXBP6).

IGFBP5 has previously been discussed in chapter 4. IGFBP7 has much less binding capacity for the IGF’s than IGFBP’s 1-5. It is secreted and has tumour suppressor effects and is able to induce oncogenic senescence (Nousbeck et al., 2010, Pen et al., 2008, Vizioli et al., 2010, Wajapeyee et al., 2008). HAPLN1 is a component of cartilage, is upregulated in mesotheliomas and colorectal carcinoma (Ashktorab et al., 2010, Ivanova et al., 2009). Given this is a growth plate expressed protein that it is upregulated in a situation of increased growth (cancer), HAPLN1 may be involved in 3-M pathogenesis. Little is known about the function of TPD52L1 although its expression alters with the cell cycle (Boutros and Byrne, 2005). MRVI1 encodes a homology for a murine tumour suppressor gene which is frequently disrupted by the murine leukaemia virus (Shaughnessy et al., 1999). STXBP6 is thought to bind members of the SNARE complex – proteins involved in vesicle fusion and exocytosis (Scales et al., 2002). Given the involvement of genes encoding secreted proteins in the microarray data perhaps dysregulation of STXBP6 is caused by abnormal secretion.

218 Table 5.23 – Top 20 probesets with expression down-regulated compared to background (defined as fold change >1.5 OB/control and expression level >50 in at least one cell line) in OB fibroblasts (n=2) compared to control fibroblasts (n=3). Gene title Gene Mean Expression Fold PPLR Symbol Expression OB Change control OB/control insulin-like growth factor 2 (somatomedin A) IGF2 2118.842 0.038 -55122.410 0.000 leptin LEP 64.694 0.061 -1061.971 0.004 EGF-like repeats and discoidin I-like domains 3 EDIL3 767.377 0.778 -985.738 0.021 insulin-like growth factor IGF2 /// 2 INS-IGF2 94.146 0.118 -795.847 0.000 ------194.797 0.261 -746.128 0.000 collagen, type IV, alpha 1 COL4A1 199.367 0.280 -712.892 0.000 brain expressed, X- linked 1 BEX1 369.403 1.084 -340.743 0.000 prostaglandin D2 synthase 21kDa (brain) PTGDS 136.490 0.426 -320.683 0.000 insulin-like growth factor IGF2 /// 2 (somatomedin A) INS-IGF2 44.950 0.184 -243.688 0.000 hyaluronan and proteoglycan link protein 1 HAPLN1 34.904 0.148 -236.312 0.011 insulin-like growth factor binding protein 5 IGFBP5 703.043 3.117 -225.534 0.000 retinoic acid receptor responder (tazarotene RARRES induced) 2 2 1081.997 5.113 -211.618 0.001 WAP four-disulfide core domain 1 WFDC1 37.836 0.179 -211.574 0.000 hyaluronan and proteoglycan link protein 1 HAPLN1 29.937 0.145 -205.958 0.000 synaptopodin 2 SYNPO2 492.790 2.690 -183.214 0.000 wingless-type MMTV integration site family, member 5A WNT5A 832.086 4.990 -166.751 0.000 insulin-like growth factor binding protein 7 IGFBP7 5084.495 33.001 -154.073 0.000 tumour protein D52-like 1 TPD52L1 389.240 2.600 -149.696 0.007 murine retrovirus integration site 1 homolog MRVI1 367.818 2.649 -138.830 0.000 syntaxin binding protein 6 (amisyn) STXBP6 42.889 0.317 -135.101 0.006

219

There were 31 gene ontology biological process terms significantly over represented in the top 500 probesets up regulated in OB fibroblasts compared to control fibroblasts (see Table 5.24). Terms included those related to embryo development, cartilage development, chondrocyte differentiation, cell adhesion and skeletal development. Twelve molecular function gene ontology terms were over represented containing multiple terms related to binding (carbohydrate, glycoaminoglycan, heparin, polysaccharide) (see table 5.25). Six cell compartment gene ontology terms were over represented and all related to the extracellular space (see table 5.26). Three KEGG pathways were significantly over represented – ECM receptor interaction, steroid hormone biosynthesis and Metabolism of xenobiotics by cytochrome P450 (see table 5.27).

There were 145 biological process gene ontology terms over represented before adjustment for multiple testing in the top 500 down regulated probesets comparing OB to control. These terms included cell adhesion, cell development and regulation of apoptosis. After adjustment for multiple testing none remained significantly over represented (see Table 5.28). Only one molecular function gene ontology term, cytoskeletal protein binding, was significantly over represented after adjustment for multiple testing (see Table 5.29). 25 cellular compartment gene ontology terms were significantly over represented related to extracellular compartment and components of muscle (sarcomere, Z disk, intercalated disk) (see Table 5.30). Three KEGG pathways were significantly over represented – ECM-receptor interaction, focal adhesion and cell adhesion molecules (see table 5.31).

220 Table 5.24 – Biological Process Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for OB (n=2) compared to control (n=3). Gene ontology term Count % Fold BH p- Change value Regionalization 21 6.122 5.381 0.000 anterior/posterior pattern formation 18 5.248 6.512 0.000 embryonic morphogenesis 26 7.580 4.236 0.000 pattern specification process 24 6.997 4.524 0.000 cell adhesion 40 11.662 2.890 0.000 biological adhesion 40 11.662 2.886 0.000 skeletal system development 26 7.580 4.035 0.000 skeletal system morphogenesis 13 3.790 5.762 0.001 proximal/distal pattern formation 7 2.041 14.973 0.001 regulation of chondrocyte differentiation 6 1.749 21.085 0.001 negative regulation of cell differentiation 17 4.956 3.927 0.001 embryonic organ development 15 4.373 4.419 0.001 embryonic organ morphogenesis 13 3.790 4.958 0.002 cell morphogenesis involved in differentiation 17 4.956 3.514 0.004 embryonic appendage morphogenesis 10 2.915 5.655 0.008 embryonic limb morphogenesis 10 2.915 5.655 0.008 cell morphogenesis 20 5.831 2.827 0.010 appendage morphogenesis 10 2.915 5.072 0.016 limb morphogenesis 10 2.915 5.072 0.016 appendage development 10 2.915 4.871 0.020 limb development 10 2.915 4.871 0.020 cellular component morphogenesis 20 5.831 2.543 0.032 multicellular organismal macromolecule metabolic process 6 1.749 9.522 0.032 neuron development 18 5.248 2.675 0.035 Behaviour 22 6.414 2.363 0.034 positive regulation of chondrocyte differentiation 4 1.166 24.599 0.033 positive regulation of developmental process 16 4.665 2.842 0.039 cartilage development 8 2.332 5.392 0.047 kidney development 9 2.624 4.612 0.049 steroid metabolic process 13 3.790 3.214 0.048 positive regulation of cell differentiation 14 4.082 3.021 0.048

221 Table 5.25 – Molecular Function Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for OB (n=2) compared to control (n=3). Gene ontology term Count % Fold BH p- Change value metallopeptidase activity 17 4.956 4.695 <0.001 sequence-specific DNA binding 30 8.746 2.654 0.001 transcription factor activity 38 11.079 2.058 0.005 polysaccharide binding 13 3.790 4.247 0.006 pattern binding 13 3.790 4.247 0.006 exopeptidase activity 9 2.624 5.843 0.013 carbohydrate binding 18 5.248 2.654 0.033 glycosaminoglycan binding 11 3.207 3.956 0.029 calcium ion binding 33 9.621 1.866 0.039 carboxypeptidase activity 6 1.749 8.106 0.038 tetrapyrrole binding 10 2.915 3.999 0.038 heparin binding 9 2.624 4.411 0.038

Table 5.26 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets in OB (n=2) compared to control (n=3). Gene ontology term Count % Fold BH p- Change value extracellular region 82 23.907 2.145 <0.001 extracellular region part 49 14.286 2.549 <0.001 extracellular matrix 25 7.289 3.568 <0.001 proteinaceous extracellular matrix 23 6.706 3.544 <0.001 extracellular space 31 9.038 2.276 0.002

222 Table 5.27 – Kegg pathways identified as being over represented (defined as Benjamini-Hochberg p-value<0.05) compared to background in the top 500 up-regulated probesets in OB (n=2) compared to control (n=3). KEGG pathway Count % Fold Change BH p-value

ECM-receptor interaction 10 2.915 5.747 0.005 Steroid hormone biosynthesis 7 2.041 7.588 0.014 Metabolism of xenobiotics by cytochrome P450 7 2.041 5.858 0.038

223 Table 5.28 – Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for OB (n=2) compared to control (n=3). There were 145 gene ontology terms overrepresented defined as p-value <0.05, the top 20 are shown below. Only three remained significant after adjustment for multiple testing using the Benjamini-Hochberg correction.

Gene ontology term Count % Fold p-value BH p-value Change tube development 16 4.776 3.586 0.000 0.079 cell adhesion 31 9.254 2.214 0.000 0.060 cytoskeleton organization 23 6.866 2.632 0.000 0.042 biological adhesion 31 9.254 2.210 0.000 0.032 regulation of cell morphogenesis 11 3.284 4.115 0.000 0.127 phosphoinositide- mediated signalling 9 2.687 5.089 0.000 0.118 neural crest cell development 6 1.791 9.118 0.000 0.120 neural crest cell differentiation 6 1.791 9.118 0.000 0.120 mesenchymal cell differentiation 7 2.090 6.808 0.001 0.123 mesenchymal cell development 7 2.090 6.808 0.001 0.123 mesenchyme development 7 2.090 6.675 0.001 0.122 regulation of tube size 7 2.090 6.546 0.001 0.122 regulation of blood vessel size 7 2.090 6.546 0.001 0.122 regulation of blood coagulation 6 1.791 8.105 0.001 0.133 regulation of cell development 13 3.881 3.177 0.001 0.129 negative regulation of apoptosis 18 5.373 2.508 0.001 0.124 spindle localization 4 1.194 19.452 0.001 0.124 establishment of spindle localization 4 1.194 19.452 0.001 0.124 negative regulation of programmed cell death 18 5.373 2.473 0.001 0.126 cell-cell signalling 25 7.463 2.068 0.001 0.121

224 Table 5.29 – Molecular Function Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for OB (n=2) compared to control (n=3). There were 13 gene ontology terms overrepresented defined as p-value <0.05. Only one remained significant after adjustment for multiple testing using the Benjamini-Hochberg correction.

Gene ontology term Count % Fold p-value BH p-value Change cytoskeletal protein binding 26 7.761 2.567 <0.001 0.012 actin binding 18 5.373 2.772 <0.001 0.062 endopeptidase inhibitor activity 10 2.985 3.710 0.001 0.208 extracellular matrix structural constituent 8 2.388 4.609 0.002 0.180 peptidase inhibitor activity 10 2.985 3.498 0.002 0.189 calcium ion binding 30 8.955 1.662 0.007 0.429 enzyme inhibitor activity 12 3.582 2.332 0.014 0.613 MHC class II receptor activity 3 0.896 13.357 0.020 0.695 phosphoric diester hydrolase activity 6 1.791 3.584 0.026 0.742 serine-type endopeptidase inhibitor activity 6 1.791 3.540 0.027 0.722 anion binding 6 1.791 3.265 0.036 0.794 ion channel activity 14 4.179 1.843 0.041 0.804 molecular adaptor activity 5 1.493 3.655 0.047 0.826

225 Table 5.30 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 down-regulated probesets in OB (n=2) compared to control (n=3). Gene ontology term Count % Fold BH p- Change value extracellular matrix 26 7.761 3.495 0.000 extracellular region part 46 13.731 2.254 0.000 proteinaceous extracellular matrix 24 7.164 3.483 0.000 extracellular region 71 21.194 1.750 0.000 plasma membrane 105 31.343 1.435 0.001 plasma membrane part 75 22.388 1.597 0.001 contractile fiber part 12 3.582 4.840 0.002 contractile fiber 12 3.582 4.520 0.003 collagen type IV 4 1.194 30.384 0.007 extracellular matrix part 11 3.284 4.359 0.006 basement membrane 9 2.687 5.397 0.007 Sarcomere 10 2.985 4.651 0.007 sheet-forming collagen 4 1.194 26.043 0.008 cell surface 19 5.672 2.525 0.012 Myofibril 10 2.985 4.106 0.015 Collagen 6 1.791 7.813 0.018 external side of plasma membrane 12 3.582 3.275 0.020 axon part 7 2.090 5.908 0.019 I band 7 2.090 5.800 0.020 integral to plasma membrane 42 12.537 1.637 0.024 terminal button 5 1.493 9.115 0.029 adherens junction 11 3.284 3.234 0.030 intrinsic to plasma membrane 42 12.537 1.600 0.032 Z disc 6 1.791 5.945 0.040 intercalated disc 4 1.194 12.153 0.047

226

Table 5.31 – Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in OB (n=2) compared to control (n=3). Nine pathways were identified using a significance of p-value <0.05. Two of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini- Hochberg correction.

KEGG pathway Count % Fold p-value BH p-value Change

ECM-receptor interaction 10 2.985 4.904 <0.001 0.018 Focal adhesion 14 4.179 2.893 0.001 0.048 Cell adhesion molecules (CAMs) 11 3.284 3.498 0.001 0.037 Vascular smooth muscle contraction 10 2.985 3.667 0.001 0.038 Pathways in cancer 16 4.776 1.998 0.012 0.234 Regulation of actin cytoskeleton 12 3.582 2.337 0.012 0.203 Melanogenesis 7 2.090 2.908 0.031 0.397 Arrhythmogenic right ventricular cardiomyopathy (ARVC) 6 1.791 3.346 0.032 0.361 Axon guidance 8 2.388 2.524 0.037 0.371

227

5.9 Probesets with differential expression between Control and RA fibroblasts The top 20 probesets up regulated in RA compared to control are listed in table 5.32. Eleven of these were also present in the top 20 up regulated probesets in the all 3-M fibroblasts compared to controls. Three of the remaining probesets represented X (inactive)-specific transcript (non-protein coding); this was likely up regulated in RA compared to control as RA is female and the control group consisted of one female and two male subjects. The remaining up regulated probesets represented paired box 6 (PAX6), endomucin (EMCN), thrombomodulin (THBD) and H19 non coding RNA (H19).

PAX6 is a transcription factor involved in regulating eye and brain development. EMCN is a membrane bound glycoprotein interferes with formation of focal adhesion complexes (Kinoshita et al., 2001) while THBD is an endothelial cell surface glycoprotein involved in thrombosis. H19 transcription is linked to IGF2 transcription – binding of CTCF to the H19 differentially methylated region silences IGF2 and results in an increase in H19 transcription. Although not in the top 20 up regulated probesets for C7 or OB fibroblasts H19 was up regulated on the microarray in all four 3-M cell lines. These data raises the possibility that a methylation abnormality at the H19 DMR may play a role in the pathogenesis of 3-M syndrome as well as its known role in Silver-Russell syndrome.

228 Table 5.32 – Top 20 probesets with expression up-regulated compared to background (defined as fold change >1.5 RA/control and expression level >50 in at least one cell line) in RA fibroblasts (n=1) compared to control fibroblasts (n=3). Gene title Gene Mean Expression Fold PPLR Symbol Expression RA Change control RA/control

X (inactive)-specific transcript (non-protein coding) XIST 0.621 1162.553 1871.135 0.563 Zic family member 1 (odd-paired homolog, Drosophila) ZIC1 0.158 217.959 1379.217 1.000 homeobox C6 HOXC6 2.405 876.800 364.617 1.000 homeobox A10 HOXA10 1.396 275.273 197.139 0.520 homeobox A9 HOXA9 1.826 323.493 177.133 0.979 Purkinje cell protein 4 PCP4 0.362 59.976 165.820 0.999 paired box 6 PAX6 0.582 86.842 149.151 1.000 endomucin EMCN 0.376 55.885 148.516 1.000 X (inactive)-specific transcript (non-protein coding) XIST 3.848 564.492 146.684 0.566 paired box 6 PAX6 1.016 146.078 143.803 1.000 glypican 6 GPC6 5.513 748.199 135.712 1.000 clusterin CLU 7.845 851.031 108.482 1.000 interleukin 13 receptor, alpha 2 IL13RA2 6.270 576.849 91.997 1.000 homeobox A10 HOXA10 1.556 139.693 89.801 0.469 X (inactive)-specific transcript (non-protein coding) XIST 2.303 199.066 86.427 0.558 WNT1 inducible signalling pathway protein 1 WISP1 1.816 154.322 84.977 1.000 thrombomodulin THBD 5.650 459.424 81.320 0.868 thrombomodulin THBD 3.135 254.265 81.110 0.761 H19, imprinted maternally expressed transcript (non-protein coding) H19 2.694 204.377 75.863 1.000 synuclein, alpha (non A4 component of amyloid precursor) SNCA 2.348 176.898 75.327 0.960

229

The top 20 down regulated probesets in RA compared to control are listed in table 5.33. Nine probesets were shared with the top 20 downregulated probesets for all 3-M syndrome fibroblasts and an additional two probesets (both representing ITIH5) were shared with the top 20 C7 downregulated probesets. Of the remaining 9 probesets three; ubiquitin specific peptidase 9 (Y-linked), DEAD (Asp-Glu-Ala-Asp) box polypeptide 3 (Y-linked) and ribosomal protein S4 (Y-linked) 1 are probably downregulated because of the gender issue (RA is female whereas the control cells contained two male cell lines). The remaining six probesets represented cell adhesion molecule 1 (CADM1), pregnancy specific beta glycoprotein 2 (PSG2), pregnancy specific beta glycoprotein 3 (PSG3), monoamine oxidase A (MAOA), transient receptor potential cation channel, subfamily C, member 6 (TRPC6) and family with sequence similarity 19 (chemokine (C-C motif)-like), member A5 (FAM19A5)

CADM1 is a cell adhesion molecule mediating adhesion of neurons and sertoli cells. It is downregulated in colorectal carcinoma and over expressed in lung cancer (Chen et al., 2010, Kitamura et al., 2009). PSG2 and PSG3 are expressed by trophoblast and released into the circulation during pregnancy but their exact role is not yet known. MAOA is an enzyme responsible for degrading neurotransmitters, There is no clear role in growth but a role for polymorphisms in MAOA has been established for behavioural disturbance (Brunner et al., 1993). TRPC6 is a calcium ion channel, mutations in which cause focal segmental glomerulosclerosis (Winn et al., 2005). Expression of TRPC6 is increased in hypertrophied cardiac muscle (Kuwahara et al., 2006); since OBSL1 is a muscle protein, if the mutation in RA also affected muscle protein(s) or function, changes in other muscle related genes would be expected. This phenomenon may be unrelated to the growth phenotype.

230 Table 5.33 – Top 20 probesets with expression down-regulated compared to background (defined as fold change >1.5 RA/control and expression level >50 in at least one cell line) in RA fibroblasts (n=1) compared to control fibroblasts (n=3). Gene title Gene Mean Expression Fold Change PPLR Symbol Expression RA RA/control control insulin-like growth factor 2 IGF2 2118.842 0.843 -2514.279 0.000 cell adhesion molecule 1 CADM1 361.835 0.592 -611.058 0.059 pregnancy specific beta-1- glycoprotein 2 PSG2 525.119 0.965 -543.941 0.046 insulin-like growth factor 2 IGF2 94.146 0.175 -537.491 0.003 DEAD (Asp-Glu-Ala-Asp) box polypeptide 3, Y- linked DDX3Y 38.125 0.075 -505.641 0.559 leucine-rich repeat- containing G protein- coupled receptor 5 LGR5 270.201 0.538 -502.564 0.008 prostaglandin D2 synthase 21kDa (brain) PTGDS 136.490 0.399 -342.358 0.004 pregnancy specific beta-1- glycoprotein 3 PSG3 197.287 0.606 -325.444 0.067 brain expressed, X-linked 1 BEX1 369.403 1.139 -324.226 0.001 ribosomal protein S4, Y- linked 1 RPS4Y1 377.393 1.287 -293.308 0.493 monoamine oxidase A MAOA 126.752 0.441 -287.472 0.005 glutamate receptor, ionotropic, kainate 2 GRIK2 44.536 0.236 -188.438 0.012 transcription factor AP-2 alpha (activating enhancer binding protein 2 alpha) TFAP2A 668.764 3.660 -182.698 0.001 leptin LEP 64.694 0.416 -155.616 0.027 insulin-like growth factor 2 (somatomedin A) IGF2 44.950 0.292 -154.003 0.003 transient receptor potential cation channel, subfamily C, member 6 TRPC6 36.848 0.265 -139.077 0.007 family with sequence similarity 19 (chemokine (C-C motif)-like), member A5 FAM19A5 107.545 0.802 -134.090 0.008 inter-alpha (globulin) inhibitor H5 ITIH5 88.234 0.683 -129.103 0.031 inter-alpha (globulin) inhibitor H5 ITIH5 259.565 2.044 -126.984 0.014 ubiquitin specific peptidase 9, Y-linked USP9Y 33.116 0.264 -125.235 0.483

231 There were 42 biological process gene ontology terms over represented in the top 500 upregulated probesets for RA compared to control (see Table 5.34). These included terms including adhesion, cell differentiation and embryonic development. Three molecular function gene ontology terms were over represented – calcium ion binding, sequence specific DNA binding and transcription factor activity (see Table 5.35). Six cellular compartment gene ontology terms were also over represented and all these referred to the extracellular space (see Table 5.36). No KEGG pathways were significantly over represented after adjustment for multiple hypothesis testing. Examining KEGG pathways significantly over represented before adjustment for multiple testing identified three pathways including ECM-receptor interaction and focal adhesion (see Table 5.37).

For the top 500 down regulated probesets there were no biological process or molecular function gene ontology terms over represented after adjustment for multiple testing. There were 110 biological process gene ontology terms significantly over represented prior to adjustment for multiple testing – the top 20 of these (as ranked by unadjusted p-value) are listed in table 5.38. These included terms such as cell-cell signalling and positive regulator of cell communication. In comparison to the other groups more terms appeared which did not have any role in growth or development. Of the six molecular function gene ontology terms over represented prior to adjustment for multiple testing extracellular matrix structural component and terms related to endopeptidase activity were consistent with results in other cell lines (see Table 5.39). Seven cellular compartment gene ontology terms were significantly over represented (see Table 5.40). Once again these included terms related to the extracellular space but also included terms related to the plasma membrane and cell surface. No KEGG pathways were over represented after adjustment for multiple testing but the pathway with the lowest unadjusted p-value was cellular adhesion (see table 5.41).

232 Table 5.34 – Biological Process Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for RA (n=1) compared to control (n=3). Gene ontology term Count % Fold Change BH p-value cell adhesion 42 12.317 3.058 0.000 biological adhesion 42 12.317 3.054 0.000 anterior/posterior pattern formation 18 5.279 6.563 0.000 pattern specification process 24 7.038 4.559 0.000 skeletal system development 26 7.625 4.067 0.000 regionalization 20 5.865 5.165 0.000 embryonic morphogenesis 24 7.038 3.940 0.000 skeletal system morphogenesis 15 4.399 6.701 0.000 extracellular structure organization 17 4.985 5.171 0.000 extracellular matrix organization 13 3.812 6.198 0.000 cell morphogenesis involved in differentiation 19 5.572 3.958 0.000 cell morphogenesis 22 6.452 3.135 0.001 positive regulation of developmental process 19 5.572 3.401 0.002 positive regulation of cell differentiation 17 4.985 3.697 0.002 cellular component morphogenesis 22 6.452 2.819 0.005 embryonic organ morphogenesis 12 3.519 4.612 0.007 cell morphogenesis involved in neuron differentiation 15 4.399 3.664 0.007 neuron projection morphogenesis 15 4.399 3.611 0.008 neuron development 19 5.572 2.846 0.013 embryonic organ development 13 3.812 3.860 0.013 cell surface receptor linked signal transduction 50 14.663 1.685 0.021 collagen fibril organization 6 1.760 10.259 0.022 cell-cell adhesion 16 4.692 3.028 0.022 response to wounding 24 7.038 2.297 0.025 cell projection morphogenesis 15 4.399 3.125 0.025 negative regulation of cell differentiation 14 4.106 3.259 0.027 cartilage condensation 5 1.466 13.773 0.028 axonogenesis 13 3.812 3.447 0.027 tube development 14 4.106 3.199 0.030 regulation of epithelial cell proliferation 8 2.346 5.749 0.029 cell part morphogenesis 15 4.399 2.987 0.032 neuron projection development 15 4.399 2.987 0.032 activation of phospholipase C activity by G-protein coupled receptor protein signalling pathway coupled to IP3 second messenger 7 2.053 6.806 0.031 cartilage development 8 2.346 5.434 0.037 regulation of cell development 13 3.812 3.239 0.039 protein oligomerization 12 3.519 3.439 0.040 forelimb morphogenesis 5 1.466 11.269 0.046 embryonic skeletal system development 8 2.346 5.152 0.045 tissue morphogenesis 12 3.519 3.343 0.047 embryonic skeletal system morphogenesis 7 2.053 6.089 0.046 neuron differentiation 20 5.865 2.328 0.046 axon guidance 9 2.639 4.375 0.047

233 Table 5.35 – Molecular Function Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets for RA (n=1) compared to control (n=3). Gene ontology term Count % Fold BH p- Change value calcium ion binding 38 11.144 2.114 0.009 sequence-specific DNA binding 26 7.625 2.263 0.046 transcription factor activity 36 10.557 1.918 0.035

Table 5.36 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 up-regulated probesets in RA (n=1) compared to control (n=3). Gene ontology term Count % Fold BH p-value Change extracellular region 82 24.047 2.181 <0.001 extracellular region part 53 15.543 2.803 <0.001 extracellular matrix 25 7.331 3.627 <0.001 proteinaceous extracellular matrix 23 6.745 3.603 <0.001 extracellular space 33 9.677 2.463 <0.001 extracellular matrix part 11 3.226 4.704 0.004

Table 5.37 – Kegg pathways identified as being over represented compared to background in the top 500 up-regulated probesets in RA (n=1) compared to control (n=3). Three pathways were identified using a significance of p- value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini-Hochberg correction. KEGG pathway Count % Fold P-value BH p-value Change

Arrhythmogenic right ventricular cardiomyopathy (ARVC) 8 2.346 4.748 0.001 0.132 ECM-receptor interaction 7 2.053 3.654 0.011 0.471

Focal adhesion 11 3.226 2.419 0.014 0.409

234 Table 5.38 – Biological Process Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for RA (n=1) compared to control (n=3). There were 110 gene ontology terms overrepresented defined as p-value <0.05, the top 20 are shown below. None remained significant after adjustment for multiple testing using the Benjamini-Hochberg correction.

Gene ontology term Count % Fold p-value BH p-value Change regulation of protein kinase cascade 17 4.404 3.108 <0.001 0.224 immune response 30 7.772 2.144 <0.001 0.149 positive regulation of cell communication 19 4.922 2.656 <0.001 0.192 positive regulation of protein kinase cascade 13 3.368 3.536 <0.001 0.153 antigen processing and presentation of peptide or polysaccharide antigen via MHC class II 5 1.295 14.112 <0.001 0.135 regulation of peptidyl- tyrosine phosphorylation 8 2.073 5.392 0.001 0.209 regulation of response to external stimulus 12 3.109 3.430 0.001 0.205 antigen processing and presentation 7 1.813 5.358 0.002 0.388 positive regulation of signal transduction 16 4.145 2.483 0.002 0.384 regulation of cell morphogenesis 10 2.591 3.474 0.002 0.392 defence response 25 6.477 1.923 0.003 0.406 cell-cell signalling 25 6.477 1.920 0.003 0.388 female pregnancy 9 2.332 3.729 0.003 0.370 negative regulation of acute inflammatory response 3 0.777 33.868 0.003 0.349 regulation of cell projection organization 8 2.073 4.105 0.003 0.371 regulation of tyrosine phosphorylation of STAT protein 5 1.295 7.526 0.004 0.416 regulation of neuron projection development 7 1.813 4.581 0.004 0.401 regulation of cell development 12 3.109 2.723 0.005 0.425 regulation of blood vessel size 6 1.554 5.210 0.006 0.467 regulation of tube size 6 1.554 5.210 0.006 0.467

235 Table 5.39 – Molecular Function Gene ontology terms over represented compared to background in the top 500 down-regulated probesets for RA (n=1) compared to control (n=3). There were 7 gene ontology terms overrepresented defined as p-value <0.05. None remained significant after adjustment for multiple testing using the Benjamini-Hochberg correction.

Gene ontology term Count % Fold p-value BH p-value Change

MHC class II receptor activity 4 1.036 16.054 0.002 0.597 endopeptidase inhibitor activity 9 2.332 3.010 0.010 0.940 serine-type endopeptidase inhibitor activity 7 1.813 3.723 0.011 0.872 enzyme inhibitor activity 13 3.368 2.278 0.012 0.810 peptidase inhibitor activity 9 2.332 2.838 0.014 0.791 symporter activity 8 2.073 2.676 0.030 0.940 extracellular matrix structural constituent 6 1.554 3.116 0.043 0.597

Table 5.40 – Cellular compartment Gene ontology terms over represented compared to background (defined as Benjamini Hochberg p-value <0.05) in the top 500 down-regulated probesets in RA (n=1) compared to control (n=3).

Gene ontology term Count % Fold BH p-value Change cell surface 25 6.477 3.117 0.001 external side of plasma membrane 14 3.627 3.585 0.025 axon part 8 2.073 6.336 0.028 extracellular region 66 17.098 1.527 0.027 basement membrane 9 2.332 5.065 0.026 plasma membrane part 73 18.912 1.458 0.030 extracellular region part 38 9.845 1.748 0.045

236 Table 5.41 – Kegg pathways identified as being over represented compared to background in the top 500 down-regulated probesets in RA (n=1) compared to control (n=3). Seven pathways were identified using a significance of p-value <0.05. None of these remained significantly overrepresented after adjustment for multiple testing using the Benjamini- Hochberg correction.

KEGG pathway Count % Fold P-value BH p-value Change

Cell adhesion molecules (CAMs) 11 2.850 3.170 0.002 0.225

Asthma 5 1.295 6.832 0.005 0.276 Systemic lupus erythematosus 8 2.073 3.599 0.006 0.217

Viral myocarditis 7 1.813 3.913 0.008 0.216

Allograft rejection 5 1.295 5.589 0.011 0.235 Type I diabetes mellitus 5 1.295 4.730 0.020 0.328 Autoimmune thyroid disease 5 1.295 3.925 0.037 0.469

237 5.10 Summary of Microarray Studies Four different comparisons were made in the microarray experiment: 1. Control (n=3) v all 3-M cell lines (n=4) 2. Control (n=3) v C7 cell line (n=1) 3. Control (n=3) v OB cell lines (n=2) 4. Control (n=3) v RA (n=1)

As expected a large number of probesets were identified with up and down regulation. The same probesets were often up/downregulated in multiple cell lines (see Table 5.42). For the majority of these probesets there was previous data, particularly from studies in cancer, that they are involved with growth. The up and down regulated probesets could be divided into four categories based on their postulated role: 1. Causative role in impairing growth – e.g. IGF2, ZIC1, LGR5 2. Cellular response to growth impairment to promote growth – e.g. PCP4, HOXC6, HOXA9, GPC6 3. Role in development of cardiovascular disease in SGA children – APOE, ACE, KCNB1 4. No clear role in either growth or cardiovascular consequences of being born SGA – SPON1, WNT5A

Biological process gene ontology terms up regulated centred around embryogenesis (especially skeletal development) and cell morphogenesis. Molecular function gene ontology terms centred around transcription factors and binding particularly of glycoaminoglycans, heparin and calcium ions. Cellular compartment gene ontology terms over represented mainly focused on the extracellular space. KEGG pathways over represented include Focal adhesion, cell adhesion and ECM-receptor interaction.

In view of the clinical overlap between 3-M syndrome and Silver Russell Syndrome and the known role of IGF-II in growth it was decided to focus on IGF-II in the next studies.

238 Table 5.42 – Summary of Top 20 up and down regulated probesets in each cell line group. Probesets present in all groups are highlighted in yellow, those present in three groups are highlighted in blue and those present in two groups are highlighted in green.

Up-Regulated Probesets Down-Regulated Probesets 3-M C7 OB RA 3-M C7 OB RA ZIC1 PCP4 ZIC1 XIST IGF2 IGF2 IGF2 IGF2 PCP4 ZIC1 PCP4 ZIC1 LEP LGR5 LEP CADM1 HOXC6 HOXA10 HOXC6 HOXC6 IGF2 COL4A1 EDIL3 PSG2

HOXA10 COL14A1 COL14A1 HOXA10 --- SFRP2 IGF2 IGF2 HOXA9 HOXA9 SNCA HOXA9 BEX1 LEP --- DDX3Y IL13RA2 IL13RA2 HOXA10 PCP4 PTGDS DIO2 COL4A1 LGR5

COL14A1 THBS4 HOXA9 PAX6 COL4A1 APOE BEX1 PTGDS

GPC6 --- CLU EMCN LGR5 RARRES2 PTGDS PSG3 CLU HOXA11 --- XIST IGF2 NID2 IGF2 BEX1 SLC6A15 HOXC6 CYP3A5 PAX6 GRIK2 TFAP2A HAPLN1 RPS4Y1 HOXA10 TNXB SLC6A15 GPC6 WFDC1 --- IGFBP5 MAOA

HOXA11 KCNB1 IL13RA2 CLU TFAP2A LXN RARRES2 GRIK2 --- WIF1 GPC6 IL13RA2 RARRES2 IGF2 WFDC1 TFAP2A CLU GPC6 CLU HOXA10 APOE TLR4 HAPLN1 LEP --- HOXA10 SPON1 XIST WNT5A APOE SYNPO2 IGF2 ABCA6 ST8SIA1 SCARA3 WISP1 EDIL3 ITIH5 WNT5A TRPC6

SCARA3 ACE HOXA10 THBD SIM2 PMEPA1 IGFBP7 FAM19A5 HOXA9 SLC6A15 ABCA6 THBD --- PSG7 TPD52L1 ITIH5

SPON1 COL14A1 SPON1 H19 SYNPO2 DIO2 MRVI1 ITIH5

TBX5 ABCA6 SNX10 SNCA PPP1R14A BEX1 STXBP6 USP9Y

239 5.11 Q-PCR Validation of Array findings 1 – IGF2 and H19

Real time quantitative PCR with TaqMan probes was used to examine IGF2 and H19 expression in three independent RNA extractions from each of the seven cell lines used in the microarray. CT for each gene was calculated as CT target gene – CT housekeeper gene. The CT for the three control cell lines was averaged and the CT calculated as CT patient cell line minus

CT average control cell lines. Relative fold expression was calculated as 2-CT. For all genes examined in this chapter expression was calculated on three independent RNA samples each measured in triplicate.

For all four 3-M cell lines IGF2 expression was significantly reduced (see Figure 5.5). Relative fold expression was 0.0019 + 0.0009 for the C7 (p<0.001), 0.0155 + 0.0021 for OBR (p<0.001), 0.0497 + 0.0170 for OBF (p<0.001) and 0.1355 + 0.0146 for RA (p<0.001).

H19 expression was significantly increased for all four 3-M cell lines (see figure 5.6). Relative fold expression was 2.5 + 0.8 for C7 (p<0.001), 140 + 53 for OBR (p<0.001), 72 + 12 for OBF (p<0.001) and 1106 + 435 for RA (p<0.001).

240

Figure 5.5 – IGF2 expression measured with qRT-PCR in C7, OBF, OBR and RA fibroblasts. Values given for expression are relative to control fibroblast cell line and control gene expression (cyclophillin A). IGF2 expression was significantly reduced in all four 3-M fibroblast cell lines. *p<0.0001.

241 A

Figure 5.6 – H19 expression measured with qRT-PCR in OBF, OBR, RA (A) and C7 fibroblasts (B). Values given for expression are relative to control fibroblast cell line and control gene expression (cyclophillin A). H19 expression was significantly increased in all four 3-M fibroblast cell lines. *p<0.0001. Two separate graphs are presented due to the differences in scale required to show both the CUL7 relative fold increase 2.84 + 0.76 and the RA relative fold increase 1106 + 435.

242 5.12 IGF-II levels in conditioned cell culture media and serum IGF-II is a secreted protein that, like the IGFBPs, is present in fetal bovine serum. Thus we chose to examine levels of IGF-II in serum free conditioned cell culture media that was prepared as per section 2.3.2.1. Levels of IGF-II were measured using an ELISA designed to measure IGF-II in serum. The standard protocol for this ELISA was to dilute 20 l of serum into a total of 1.95 ml of buffers for IGF-II extraction. Using this protocol we were unable to detect any IGF-II in conditioned media (control or 3-M). This was thought to be because of the high IGF-II levels found in serum compared to cell culture media. For this reason the manufacturer’s standard protocol was adapted. Instead of adding 20 l of media to 950 l of buffer 1, 400 l of media was added. Addition of 1 ml buffer 2 was unchanged but instead of adding 25 l of diluted sample or standard to each well of the microplate 50 l were added. The rest of the protocol was unchanged. The effect of these changes on the performance of the ELISA was assessed by measuring IGF-II concentrations in serum free media not exposed to cells before and after the addition of a known quantity of IGF-II. Across a range of concentrations around 30% of the IGF-II added was recovered (e.g. IGF-II added at 300 ng/ml read at a concentration of 100 ng/ml). Thus although this protocol was able to detect IGF-II levels in conditioned media it is likely to underestimate IGF-II levels.

IGF-II levels as measured by the ELISA are presented after being divided by 20 to reflect the 20 fold increase in starting material used. Levels of IGF-II were reduced in conditioned cell culture media from all four 3-M cell lines compared to control cell lines (see Figure 5.7). The mean IGF-II level for the three control cell lines was 10.2 + 2.9 ng/ml, 0.1 + 0.2 ng/ml for the C7 cell line (p<0.001 compared to control), 0.5 + 0.6 ng/ml for OBR cell line (p<0.001 compared to control), 0.4 + 0.5 ng/ml for OBF cell line (p<0.001 compared to control) and 1.8 + 1.5 ng/ml for RA cell line (p<0.001 compared to control).

243

Figure 5.7 – IGF-II concentration measured by ELISA is reduced in conditioned cell culture medium from 3-M syndrome fibroblasts compared to controls. *p<0.001 for difference with control media on Tukey post-hoc analysis after one-way ANOVA.

Serum IGF-II levels were measured in seven 3-M patients where there was serum available and in two non 3-M syndrome patients (both children with end stage renal failure on GH therapy). The very significant limitation of this work was the lack of availability of any serum from aged matched normal children combined with the lack of availability of any commercially available assay for which there is a normal reference range available. Standards supplied with the assay ranged from 2.2. to 2000 ng/ml. Serum IGF-II levels for the 3-M and non 3-M patients are listed in table 5.43. They ranged in the 3-M patients from 1540 ng/ml to 1985 ng/ml (one patient had a level of 3387 ng/ml but this sample was haemolysed). The two non 3-M patients had IGF-II levels of 984 and 901 ng/ml. While there are very significant limitations to

244 these data it is highly suggestive that there is no significant serum IGF-II deficiency in 3-M syndrome.

Table 5.43 – Serum IGF-II levels in 3-M subjects and two non-3M syndrome patients (end stage renal failure on GH therapy).*Sample significantly haemolysed.

Patient Mutation On GH IGF-II (ng/mL) 3-M None Identified – chromosome 19 region No 1540 3-M OBSL1 (c.1273insA, p.T425NfsX40) No 1987 3-M OBSL1 (c.1273insA, p.T425NfsX40) 1390 3-M None identified. No 1696 3-M OBSL1 (Het c.1265- Yes 3387* 1274delGCACCGTGGC; Het c.1282insA, p.R419PfsX10; p.T425NfsX40 ) 3-M OBSL1 (c.1273insA, p.T425NfsX40) Yes 1625 3-M None identified No 1459 Not 3-M N/A Yes 984 Not 3-M N/A Yes 901

These findings are in keeping with those in Silver-Russell syndrome where there is silencing of IGF2 expression but normal serum IGF-II levels (Binder et al., 2006).

5.13 – Levels of CTCF in 3-M syndrome fibroblasts CTCF is the transcription factor responsible for binding to unmethylated DNA at the H19 differentially methylated region. Binding of CTCF results in the reduction in IGF2 expression and an increase in H19 expression. We therefore analysed levels of CTCF protein in lysates from control and 3-M syndrome fibroblasts. CTCF levels were increased in C7 and OBF fibroblasts (both p<0.001) but were unchanged in RA fibroblasts (p=0.78) (see figure 5.8)

245 A

Figure 5.8 – CTCF is increased in C7 and OBF cells but not RA cells. A) Western immunoblotting and B) Densitometric analysis. Levels of CTCF/- actin normalized to control. *p<0.001.

246

5.14 Q-PCR validation of Array Findings 2 – BEX1, LEP, IGFBP7, ZIC1, HOXC6, HOXA9, GPC6

An additional seven genes were selected in order to validate the findings of the microarray with q-pcr. Genes were selected on the basis of their presence in the top 20 up or down regulated probesets and displayed. Genes selected were: Brain expressed x-lined 1 (BEX1), Leptin (LEP), Insulin like growth factor binding protein seven (IGFBP7), Zinc finger protein of cerebellum 1 (ZIC1), Homeobox C6 (HOXC6), Homeobox A9 (HOXA9) and glypican 6 (GPC6). IGFBP7 was included despite not being in the top 20 up or down regulated probesets due to previous work on other IGFBPs (see chapter 4).

SYBR green q-PCR was utilized to analyse expression of these genes. Primers were designed to amplify across at least one intron and optimized so only one product was visible on agarose gel electrophoresis. A dissociation curve was run with each qPCR experiment for every well. No qPCR product with more than one peak (i.e. representing amplification of more than one product) was identified. BEX1, LEP and IGFBP7 expression was significantly decreased in all four 3-M cell lines compared to control in each of three independent RNA extractions (see Figure 5.9). These RNA extractions were independent from each other and from the RNA extracted for the microarray study. There was a high degree of variation in the degree of downregulation between independent RNA samples, but all samples displayed downregulation compared to control (see Figure 5.8). ZIC1, HOXC6, HOXA9 and GPC6 expression was upregulated in all four 3-M cell lines compared to control in each of three independent RNA extractions (see Figure 5.9). Once again variance was low for technical repeats from the same RNA extraction but high between different RNA extractions (see Figure 5.10). Relative fold expression for each gene and cell line analysed are given in table 5.44.

247

Figure 5.9 – QRT-PCR validation of selected genes identified as being down-regulated in 3-M syndrome compared to control fibroblasts. A) Expression of BEX1, LEP and IGFBP7 is significantly reduced across all four 3-M cell lines in keeping with the microarray result. High variance is seen in OBF and RA cell lines for BEX1 and IGFBP7. B) BEX1 and C) IGFBP7 expression in each of the three independent experiments for each cell line. The high variance seen is due to variation between experiments rather than variance within each experiment. *p<0.001.

248

Figure 5.10 – QRT-PCR validation of selected genes identified as being up regulated in 3-M syndrome compared to control fibroblasts. A) Expression of ZIC1 and HOXA9 is significantly increased across all four 3-M cell lines in keeping with the microarray result. B) Expression of HOXC6 and GPC6 is significantly increased across all four 3-M cell lines in keeping with the microarray result. High variance is seen for ZIC1 and HOXC6. C) ZIC1 and D) HOXC6 expression in each of the three independent experiments for each cell line. The high variance seen is due to variation between experiments rather than variance within each experiment. *p<0.01.

249

Table 5.44 – Validation of gene expression identified as being up or down regulated in the microarray. Relative fold expression for each the seven genes analysed is given for each of the four 3-M cell lines. Expression was normalized to GAPDH and mean control cell line expression.

Gene C7 OBF OBR RA Relative Sig Relative Sig Relative Sig Relative Sig expression expression expression expression BEX1 0.06 + 0.01 <0.001 0.15 + 0.20 <0.001 0.03 + 0.02 <0.001 0.20 + 0.24 <0.001 LEP 0.07 + 0.04 <0.001 0.06 + 0.03 <0.001 0.01 + 0.00 <0.001 0.04 + 0.01 <0.001 IGFBP7 0.18 + 0.05 <0.001 0.27 + 0.23 <0.001 0.05 +0.01 <0.001 0.38 + 0.14 <0.001 ZIC1 946 + 462 <0.001 496 + 186 0.004 1200 + 891 <0.001 759 + 498 0.002 HOXC6 31 + 24 0.006 88 + 55 0.001 51 + 38 0.005 100 + 87 0.009 HOXA9 690 + 586 0.008 501 + 466 0.012 349 + 296 0.008 399 + 342 0.008 GPC6 35 + 6 <0.001 44 + 10 <0.001 7 + 2 <0.001 5 + 1 <0.001

5.15 – New Hypothesis for 3-M syndrome pathogenesis On the basis of the results presented a new hypothesis for the pathogenesis of 3-M syndrome is proposed. Local production of IGF-II is reduced due to decreased IGF2 expression secondary to altered methylation of the H19 DMR or levels of CTCF protein. Systemic IGF-II levels remain normal as IGF2 can be expressed from both alleles in liver (Ekstrom et al., 1995). Loss of local IGF-II in the growth plates and other tissues leads to growth impairment both pre- and post-natally. The mechanisms behind the IGF2 silencing are unclear. While there is significant phenotypic overlap between 3-M syndrome and SRS there are also phenotypic differences. These are likely to be due to additional functions of the proteins affected in 3- M syndrome.

The principle of local growth factor production being more important for growth than hepatic production is true for IGF-1. The whole body Igf1 knockout mouse displays significant growth retardation (Liu et al., 1993) while mice with a liver specific Igf1 deletion display no growth retardation despite a 75% reduction in systemic Igf1 levels (Yakar et al., 1999). While

250 no person with a liver specific IGF1 gene defect has been identified patients with mutations in the acid labile subunit display modest growth restriction with extremely low to undetectable levels of serum IGF-1 (Domene et al., 2009).

5.16 – Key points  IGF2 expression was reduced in all 3-M syndrome cell lines tested  H19 expression was increased in all 3-M syndrome cell lines tested  IGF-II levels in conditioned cell culture media taken from 3-M syndrome cell lines are lower than for conditioned media from control cell lines  Serum levels of IGF-II in 3-M syndrome patients do not appear to be reduced  Levels of CTCF binding protein are increased in C7 and OBF cells but not in RA cells  Biological process gene ontology terms over represented in all 3-M syndrome cells are related to cell differentiation, cell adhesion, embryo development and skeletal system development  Cellular compartment gene ontology terms related to the extracellular space were overrepresented in 3-M cell lines  Molecular function gene ontology terms overrepresented in 3-M cells related to binding of various components – carbohydrate, heparin, glycoaminoglycan and nucleic acid.

251

Chapter 6: Metabolomic Studies

252

6.1 Introduction

Metabolomics is the identification and quantification of the all metabolites in a cell, tissue or organism. Work outlined in chapter 4 described functional hypothesis led studies to try to gain insights into the pathogenesis of 3-M syndrome. Our central hypothesis was that given identical clinical phenotype seen in all cases of 3-M syndrome the different genes involved must be in the same pathway, disruption of which leads to growth impairment. Importantly this pathway must be disrupted in all 3-M syndrome patients. While the functional studies yielded useful data they did not identify a single pathway severely disrupted in all patients. We therefore decided to use a non-hypothesis driven approach to study the effects of the genetic mutations causing 3-M syndrome.

Two distinct methods were utilized: 3. Whole genome gene expression studies using Affymetrix HU 133 plus 2.0 arrays (described in chapter 5) 4. Metabolomic studies utilizing gas chromatography and mass spectrometry (described in this chapter)

The primary aim of each of these studies was to develop a new hypothesis for the pathogenesis of the growth impairment seen in 3-M syndrome. The data derived from the transcriptome studies are presented in chapter 5 and the data from the metabolome studies are presented in this chapter. The secondary aim of the metabolome study was as a pilot study to examine whether it is possible to identify metabolic biomarkers of growth failure in the SGA population.

6.2 Cell Lines used in the Metabolomic Studies AF – control, male prepubertal

ENF – control, female aged 7

253 ENM – control, male aged 11

C7 – male patient with a nonsense mutation in CUL7 (c.4191delC p.H1379HfsX11) (elder sibling family 1).

OBR – male patient with nonsense mutation in OBSL1 (c.1273insA, p.T425NfsX40) (family six).

OBF – female patient with nonsense mutation in OBSL1 (c.1273insA, p.T425NfsX40) (family six). Patient OBF is the sister of OBR.

RA – patient fibroblast cell line derived from a female patient with clinically definite 3-M syndrome but no identified mutation in either CUL7 or OBSL1 (affected individual from family 16).

Where data is expressed as control this represents the average of the three control cell lines, data described as 3-M represents all four 3-M cell lines and where data is described as OB this represents the average of both OBSL1 patient cell lines.

For each of the seven cell lines, six 225 cm2 tissue culture flasks at 100% confluency were used. The metabolomic fingerprint (the intracellular metabolome) generated from the cells was extracted and measured as per chapter 2.8 while the metabolomic footprint (the extracellular metabolome) was measured in the serum free media (no metabolite extraction required, content measured as per section 2.8). It was not possible to identify all metabolic peaks present on the gas chromatogram – where appropriate this is indicated in the tables presented. In addition multiple peaks can represent the same metabolite. Metabolites were identified as being increase/decreased compared to control if p<0.05.

254 6.3 Metabolomic changes in 3-M cell lines compared to control

6.3.1 Metabolomic fingerprint Metabolites Increased There were 15 metabolic peaks representing 10 distinct metabolites increased in the 3-M syndrome metabolic fingerprint when compared to control cell metabolic fingerprint (see Table 6.1).

Aspartic acid is a non-essential amino acid produced from glutamic acid. It is involved in the urea cycle, DNA metabolism and is a neurotransmitter. Creatinine is a breakdown product of creatinine phosphate, is produced at a constant rate and is filtered and excreted by the kidneys (Ronco et al.). Inositol-1-phosphate is an intermediary in the conversion of glucose-6- phosphate to myo-inositol.

The monosaccharides fructose and glucose were both increased. Both serve as energy substrates for the cell. Glucose can be stored as glycogen or can enter the glycolytic pathway to produce pyruvate for entry into the Krebs cycle. Fructose is converted either to pyruvate to enter the Krebs cycle or glucose-6-phosphate for storage as glycogen. Pyruvic acid (also known as pyruvate) is formed either from glycolysis or fructolysis and is the substrate for the energy generating Krebs cycle.

Glutamic acid (also known as glutamate) is another non-essential amino acid which is also a neurotransmitter. It is produced along with pyruvate from alanine and α-ketoglutarate.

Serine is produced from glutamine and is involved in the synthesis of the pyrimidine and purine DNA bases as well as playing a catalytic function in many enzymes. Additionally serine is commonly phosphorylated during cell signalling processes. The other amino acid commonly phosphorylated during cell signalling processes is threonine and this was also up regulated in 3-M syndrome cells. Threonine is an essential amino acid and in addition to

255 phosphorylation can also be glycosylated (as can serine). Threonine can also be converted to pyruvate via threonine dehydrogenase.

Metabolites decreased There were 14 metabolic peaks representing seven distinct metabolites decreased in the 3-M syndrome metabolic fingerprint when compared to control cell metabolic fingerprint (see Table 6.2).

Alanine is a non-essential amino acid produced either by conversion of a carbinyl group in a pyruvate molecule to an amine group or by DNA breakdown. It functions as a neurotransmitter in the brain (Schousboe et al., 2003) and also plays a role in regulating blood glucose levels. During anaerobic metabolism in muscle alanine is produced along with lactate – the alanine is transported to the liver where it is converted to glucose and alanine is also known to enhance insulin secretion (Newsholme et al., 2005). In addition alanine can be converted with α-ketoglutarate to yield glutamic acid and pyruvate – this may provide an explanation for the decreased alanine and increased pyruvate/glutamate seen in 3-M cells. Levels of alanine excretion in urine are directly related to blood pressure in humans (Holmes et al., 2008).

Lactose is a disaccharide consisting of glucose and galactose and is the major sugar present in breast milk. It is broken down by the enzyme lactase prior to absorption in the gut; deficiency of lactase can lead to gastrointestinal symptoms (Campbell et al., 2009).

Myo-inositol is a structural component of the inositol phosphates, components of the phosphatidylinositol 3-kinase (PI3K) secondary signalling pathway found downstream of several receptors including the IGF1R and insulin receptor (Kong and Yamori, 2009).

Lactic acid is produced during glucose metabolism by the conversion of pyruvate with lactate dehydrogenase. Lactic acid is cleared either by

256 conversion to glucose in the liver or via oxidation to pyruvate which then enters the Krebs cycle.

Glycine is a non-essential amino acid involved in production of DNA, phospholipids (Geiger et al., 2010) and collagen (Gordon and Hahn, 2010). Glycine is also a neurotransmitter and excess levels of glycine in the autosomal recessive condition non-ketotic hyperglycinaemia lead to seizures, apnoea and death in the neonatal period (Kahler and Fahey, 2003).

Glucose-6-phosphate, an intermediate in the glycolytic pathway, is produced either by phosphorylation of glucose or cleavage from glycogen. In addition to glycolysis glucose-6-phospahte is the first component of the pentose-phosphate pathway, the results of which are generation of NADPH and ribose-5 phosphate which is involved in nucleic acid synthesis. Glycerol- 3-phosphate is another intermediate of the glycolytic pathway downstream of glucose-6-phosphate. It therefore appears there is reduced activity of the glycolytic pathway in 3-M syndrome.

Discussion

There appears to be an increase in intracellular concentration of sugars (glucose, fructose) with a decrease in the glucose-6-phosphate, glycerol-3- phosphate, alanine and lactic acid suggesting that energy supplies are adequate for metabolic requirements without the need for anaerobic metabolism or utilization of glycogen stores. This could be either because of increased cellular glucose uptake or due to decreased metabolic requirements – given the slow growth of 3-M cell lines the latter would seem more probable. Figure 6.1 (page 262) summarises the changes in energy metabolism in 3-M syndrome and includes changes in footprint carbohydrate metabolites. There also appears to be an effect of inositol phosphate metabolism. This is of interest as the inositol phosphates are involved in signal transduction and in chapter 4 it was demonstrated that one component of the IGF-1 signal transduction system was disrupted in 3-M syndrome.

257

Additionally there are several metabolites where there is no clear role in 3-M syndrome or the small for gestational age child – these include creatinine, glycine, lactose and aspartic acid.

Table 6.1 - Fingerprint Metabolites increased in 3-M syndrome compared to control Metabolite P-value Fold change aspartic acid 0.0001500 4.12 aspartic acid 0.0000736 3.13 creatinine 0.0065040 1.90 inositol-1-phosphate 0.0016440 1.70 fructose 0.0466390 1.58 inositol-1-phosphate 0.0184350 1.57 inositol-1-phosphate 0.0196760 1.56 unidentified 0.0044730 1.49 glutamic acid and/or pyroglutamic acid 0.0365910 1.34 glucose 0.0100120 1.32 serine 0.0465170 1.31 unidentified 0.0311620 1.23 glucose 0.0389040 1.16 pyruvic acid 0.0250000 1.15 threonine 0.0196760 1.10

Table 6.2 - Fingerprint Metabolites decreased in 3-M syndrome compared to control Metabolite P-value Fold change alanine 0.0000004 0.21 lactose 0.0008860 0.31 myo-inositol 0.0184350 0.41 unidentified 0.0001130 0.44 lactic acid 0.0001870 0.45 lactic acid 0.0000769 0.47 glycerol-3-phosphate 0.0003720 0.52 lactic acid 0.0003090 0.54 glycine 0.0132030 0.55 glycine 0.0469260 0.56 glucose-6-phosphate 0.0474530 0.59 unidentified 0.0008370 0.62 unidentified 0.0437360 0.63 unidentified 0.0345330 0.66

258 6.3.2 Metabolomic footprint Metabolites Increased There were 11 metabolic peaks representing seven distinct metabolites increased in the 3-M syndrome metabolic footprint when compared to control cell metabolic footprint (see Table 6.3).

Fructose was increased in the metabolomic footprint as well in the metabolomic fingerprint. This probably represents decreased cell energy generation with concomitant decrease in intracellular transport of fructose. The increase in footprint pyruvic acid is likely to represent decreased intracellular, transport also due to decreased cell energy requirement. 2- oxopropanoic acid is another name for pyruvic acid.

Leucine and isoleucine are two essential branched chain amino acids which can be converted via transamination to Succinnyl CoA or Acetyl CoA both of which can enter the Krebs cycle. Increased levels of these in the media may also represent a lack of transport due to low cellular energy requirement/generation.

Metabolites Decreased There were 16 metabolic peaks representing 11 distinct metabolites decreased in the 3-M syndrome metabolic footprint when compared to control cell metabolic footprint (see Table 6.4).

Cystine is an oxidized dimerised form of the nonessential amino acid cysteine. In the footprint cystine was increased and cysteine decreased in 3- M syndrome compared to control indicating an increase in oxidization and dimerisation of cysteine. There are two known disorders of cystine metabolism in humans. The first cystinuria involves decreased renal tubular uptake of cystine and results in the recurrent formation of renal stones. Cystinosis is an autosomal recessive condition characterized by impairment of transport of cystine out of lysosomes and results in renal tubular acidosis

259 (leading to poor growth and rickets), cataracts, hypothyroidism, myopathy and pancreatic insufficiency (Gahl, 2003).

Lactic acid was decreased in the footprint in addition to having been decreased in the fingerprint and in addition to the other changes in metabolites involved in glycolysis would indicate decreased export of lactic acid. Similarly alanine was also decreased in the metabolomic footprint as well as having been decreased in the 3-M metabolomic fingerprint. This would be consistent with increased conversion of alanine to glutamic acid and pyruvate with subsequent increased alanine uptake from media.

Glutamine is a non-essential amino acid and can be produced by transamination of glutamic acid (and conversely glutamic acid can be produced by deamination of glutamine).

Both 3-methylpentanoic acid and 2-methyl-3-hydroxybutanoic acid are organic acids generated by isoleucine metabolism and are elevated in the blood of patients with maple syrup urine disease. Maple syrup urine disease is a disorder of branched chain amino acid metabolism which leads to accumulation of leucine, isoleucine and valine resulting in neurological degeneration, seizures, ketoacidosis and respiratory arrest (Chuang et al., 2006). Leucine, isoleucine and valine are all dysregulated in the 3-M metabolic footprint but leucine and isoleucine are increased while valine is decreased indicating that any dysregulation is more complex than that found in maple syrup urine disease.

Hexanoic acid is a medium chain triglyceride. Glycine was identified as being decreased in the metabolic fingerprint and is also decreased in the footprint – this indicating either increased glycine utilization and consequent uptake from media or decreased glycine production and decreased secretion into media. Aminomalonic acid is involved in imparting calcium binding properties to proteins.

260 Phenylalanine is an essential amino acid and is the precursor to tyrosine and the catecholamines. Accumulation of phenylalanine is seen in phenylketonuria where it leads, in left untreated, to mental retardation and seizures.

Summary There was further evidence in the footprint of altered energy metabolism with increased concentrations of fructose, pyruvate, leucine and isoleucine with decreased levels of lactic acid and alanine (see figure 6.1). There were a number of metabolites altered where the is no clear link to functional changes that can be linked to 3-M syndrome – phenylalanine, hexanoic acid, aminomalonic acid and cystine.

261

Figure 6.1 – Summary of changes in energy metabolism in 3-M syndrome. Metabolites increased are in large font while decreased metabolites are in small font. Arrows indicate increased/decreased cellular uptake/conversion based on arrow size. Overall there appears to be reduced energy uptake and generation.

262

Table 6.3 - Footprint Metabolites increased in 3-M syndrome compared to control

Metabolite P-value Fold change cystine 0.000169 1.55 pyruvic acid 0.000015 1.34 unidentified 0.00653 1.32 unidentified 0.000050 1.21 fructose 0.010737 1.17 unidentified 0.003283 1.17 2-oxopropanoic acid 0.001723 1.16 leucine 0.004826 1.15 isoleucine 0.004826 1.13 unidentified 0.005601 1.09 fructose 0.032301 1.08

Table 6.4 - Footprint Metabolites decreased in 3-M syndrome compared to control

Metabolite P-value Fold change glutamine 0.0000256 0.07 alanine 0.0000104 0.14 cysteine 0.0000001 0.23 3-methylpentanoic acid 0.0000002 0.25 unidentified 0.0000583 0.27 hexanoic acid 0.0000131 0.34 2-methyl-3- hydroxybutanoic acid 0.0041040 0.49 lactic acid 0.0000948 0.59 glycine 0.0348080 0.63 aminomalonic acid 0.0085690 0.70 unidentified 0.0217540 0.71 unidentified 0.0437360 0.83 glycine 0.0000233 0.87 valine 0.0253990 0.88 unidentified 0.0227280 0.90 phenylalalnine 0.0253990 0.92

263 6.4 Metabolomic changes in C7 cell line compared to control

6.4.1 Metabolomic fingerprint The only identified metabolites increased in the C7 fingerprint were aspartic acid and inositol-1-phosphate (see Table 6.5). These were also increased in the 3-M syndrome group and have already been discussed.

There were 12 identified metabolites decreased in the C7 fingerprint (see table 6.6), including five - alanine, glycine, lactic acid, myo-inositol and glycerol-3-phosphate – which were also decreased in the 3-M syndrome group and have already been discussed. The other metabolites decreased were phosphate, fructose, glutamine, phenylalanine, valine, isoleucine and serine. Phosphate is an inorganic chemical present both in human serum and within cells where addition of a phosphate ion to many proteins is an essential step in their activation. Serine is a non-essential amino acid synthesized from glycine or threonine, thus its reduction may be secondary to reduced glycine levels. Of note serine residues are one of three residues phosphorylated by kinases. The combination of reduced phosphate and serine may indicate an abnormality in cell signalling

In addition to being reduced in the C7 fingerprint, glutamine is also reduced in both the 3-M and C7 footprint. As already discussed it may be that glutamine is being utilized to generate pyruvate. Phenylalanine was also reduced in the 3-M footprint but the implications of reduced levels are unclear.

In contrast to the 3-M group where fructose levels were increased in both the fingerprint and footprint, in the C7 cell line fructose levels were decreased. Other metabolites involved in energy generation (glycerol-3- phosphate, lactic acid, alanine) were decreased in both 3-M and C7 cells. This overall picture is suggestive of reduced energy expenditure in C7 cells in common with 3-M cells. Isoleucine and valine are essential branched chain amino acids. Of the three branched chain amino acids isoleucine and

264 valine are the two involved in carbohydrate metabolism adding further weight to the suggestion of reduced energy expenditure in CUL7 cells.

Table 6.5 - Fingerprint Metabolites increased in C7 cells compared to control cells Metabolite P-value Fold change aspartic acid 0.020897 2.97 aspartic acid 0.034477 2.66 inositol-1-phosphate 0.029707 1.98 unidentified 0.034477 1.77 inositol-1-phosphate 0.040424 1.75

Table 6.6 - Fingerprint Metabolites decreased in C7 cells compared to control cells Metabolite P-value Fold change alanine 0.021947 0.13 phosphate 0.0035 0.23 glycine 0.003074 0.23 unidentified 0.004104 0.25 glycine 0.003179 0.28 myo-inositol 0.034477 0.29 unidentified 0.00128 0.34 lactic acid 0.00379 0.43 fructose 0.001999 0.44 lactic acid 0.004326 0.45 unidentified 0.008415 0.46 lactic acid 0.006207 0.52 glutamine 0.047219 0.55 glycerol-3-phosphate 0.029294 0.60 phenylalanine 0.029294 0.63 valine 0.047219 0.64 serine 0.020855 0.66 isoleucine 0.04154 0.69 isoleucine 0.029707 0.69 glutamine 0.017417 0.71 unidentified 0.011622 0.74 valine 0.040424 0.85

265 6.4.2 Metabolomic footprint There were six identified metabolites increased in the C7 metabolic footprint (see table 6.7). Three were also identified as increased in the 3-M metabolic footprint – pyruvic acid/2-oxopropanoic acid and fructose and have already been discussed. The role of pencillamine in metabolism is not well defined; this may be detection of the penicillin added to the media. Aspartic acid is increased in the 3-M and C7 fingerprints. Given its involvement in DNA metabolism it may be increased in the metabolic fingerprint secondary to decreased cell division with a secondary increase in the footprint due to decreased uptake.

Trimethylamine-N-oxide is an oxidation product of trimethylamine. Trimethylaminuria (also known as fish malodour syndrome) is an autosomal recessive disorder whereby there is absence of the enzyme flavin containing monooxygenase 3 and results in a build up of trimethylamine and decreased trimethylamine-N-oxide. Patients present with a fishy odour.

There were seven identified metabolites decreased in the C7 footprint (see table 6.8). All of these were also decreased in the 3-M group and have already been discussed.

266 Table 6.7 - Footprint Metabolites increased in C7 cell conditioned media compared to control cell conditioned media

Metabolite P-value Fold change pyruvic acid 0.001999 1.78 unidentified 0.003486 1.70 pencillamine 0.014697 1.66 unidentified 0.017417 1.56 unidentified 0.00379 1.54 aspartic acid 0.006207 1.53 unidentified 0.042782 1.48 unidentified 0.006934 1.42 unidentified 0.041051 1.28 fructose 0.006934 1.27 unidentified 0.04882 1.25 unidentified 0.006934 1.22 trimethylamine-N- oxide 0.045736 1.21 2-oxopropanoic acid 0.029294 1.20 unidentified 0.005691 1.20

Table 6.8 - Footprint Metabolites decreased in C7 cell conditioned media compared to control cell conditioned media

Metabolite P-value Fold change glutamine 0.006578 0.06 alanine 0.005294 0.09 unidentified 0.00729 0.20 3-methylpentanoic acid 0.000636 0.23 cysteine 0.002484 0.27 hexanoic acid 0.013711 0.33 lactic acid 0.00806 0.63 glycine 0.004326 0.83

267 6.5 - Metabolomic changes in OB cell lines compared to control

6.5.1 Metabolomic fingerprint In the OBSL1 metabolic fingerprint there were 17 metabolic peaks representing 10 identified metabolites increased compared to control (see Table 6.9). These 10 peaks included eight also increased in 3-M group metabolic fingerprint and already discussed, including metabolites involved in energy metabolism (glucose, fructose, pyruvic acid) and the signalling molecule inositol-1-phosphate. The two other metabolites increased in the OB fingerprint were glutamine and methionine.

Glutamine was identified as being decreased in the footprint in both 3-M cells and C7 cells, and also in the fingerprint of C7 cells in contrast to its increased level in the OB fingerprint. Glutamine was also identified as being decreased in the OB footprint – it may be that increased glutamine uptake is driving the high intracellular glutamine levels. Methionine is an essential amino acid which is also involved as a methyl donor in DNA methylation and can be converted to cysteine and subsequently homocysteine.

There were 10 metabolic peaks representing 5 identified metabolites decreased in the OB cell line compared to control (see figure 6.10). Four of these metabolites (alanine, myo-inositol, lactic acid and glycine) were also identified as being decreased in the 3-M cells. The other metabolic peak was the sugar lactose. Its reduction could represent decreased secretion from cells or increased uptake.

268

Table 6.9 - Fingerprint Metabolites increased in OB cells compared to control cells Metabolite P-value Fold change aspartic acid 0.003118 4.10 inositol-1-phosphate 0.016377 3.37 inositol-1-phosphate 0.004993 3.23 inositol-1-phosphate 0.014684 3.08 aspartic acid 0.003202 2.77 creatinine 0.018239 1.79 fructose 0.043071 1.67 glucose 0.000693 1.53 glutamine 0.018239 1.50 unidentified 0.018239 1.49 glutamic acid and/or pyroglutamic acid 0.006432 1.47 unidentified 0.006196 1.39 serine 0.024619 1.38 glutamine 0.014856 1.37 pyruvic acid 0.000957 1.25 methionine 0.049535 1.25 glucose 0.008329 1.24

Table 6.10 - Fingerprint Metabolites decreased in OB cells compared to control cells Metabolite P-value Fold change lactose 0.0019460 0.19 alanine 0.0000091 0.20 myo-inositol 0.0045560 0.33 unidentified 0.0000750 0.43 lactic acid 0.0013200 0.45 lactic acid 0.0009570 0.48 lactic acid 0.0031980 0.54 glycine 0.0368640 0.58 glycine 0.0083290 0.69 unidentified 0.0061320 0.77

269 6.4.2 Metabolomic footprint There were 10 metabolic peaks representing six identified metabolites increased in OB cell footprint compared to control. These six metabolites are identical to the six metabolites increased in 3-M cell footprint and have already been discussed.

There were 12 metabolic peaks representing 10 identified metabolite decreased in the OB cell footprint compared to control. Nine of these metabolites were shared with those decreased in the 3-M cell footprint. The remaining metabolite was glycerol, a constituent of triglycerides and phospholipids. When utilizing stores of fatty acids to generate energy glycerol is liberated. Potentially reduced fatty acid metabolism in OB cells may lead to reduced glycerol release (and hence lower levels in the footprint).

270 Table 6.11 - Footprint Metabolites increased in OBSL1 cell conditioned media compared to control cell conditioned media

Metabolite P-value Fold change cystine 0.000177 1.66 pyruvic acid 0.000151 1.36 unidentified 0.003671 1.28 unidentified 0.00274 1.23 fructose 0.010494 1.22 leucine 0.010494 1.20 isoleucine 0.006572 1.15 unidentified 0.011755 1.15 2-oxopropanoic acid 0.020284 1.15 unidentified 0.001958 1.13

Table 6.12 - Footprint Metabolites decreased in OB cell conditioned media compared to control cell conditioned media

Metabolite P-value Fold change glutamine 0.0007900 0.04 alanine 0.0001550 0.14 unidentified 0.0077860 0.22 cysteine 0.0000056 0.22 3-methylpentanoic acid 0.0000091 0.23 hexanoic acid 0.0002050 0.34 2-methyl-3- hydroxybutanoic acid 0.0041040 0.49 lactic acid 0.0002800 0.55 aminomalonic acid 0.0163770 0.68 glycerol 0.0080050 0.76 glycine 0.0002380 0.86 unidentified 0.0101190 0.88

271 6.6 Metabolomic changes in RA cell lines compared to control

6.6.1 Metabolomic fingerprint In the fingerprint there were 16 metabolic peaks representing 11 different metabolites significantly increased in RA cell line compared to control. Six of these metabolites (aspartic acid, creatinine, glutamic acid, inositol, serine and threonine) were increased in the 3-M fingerprint and another two (methionine and glutamine) were increased in the OB fingerprint. The inorganic ion phosphate was identified as increased in RA fingerprint having been previously identified as being decreased in the C7 fingerprint.

Ornithine and proline are the two metabolites identified as being increased in the RA fingerprint but not in any of the other cell lines metabolic fingerprints. Ornithine is an amino acid produced in the urea cycle and is a precursor of citruline and arginine. Proline is a nonessential amino acid derived from glutamate.

There were seven metabolic peaks representing five metabolites significantly decreased in the RA fingerprint compared to control. Four of these metabolites – alanine, lactic acid, glucose-6-phosphate and glycerol-3- phosphate were also decreased in the 3-M fingerprint and the fifth metabolite, lactose, was also identified as being decreased in the OB fingerprint.

272 Table 6.13 - Fingerprint Metabolites increased in RA cells compared to control cells Metabolite P-value Fold change aspartic acid 0.001911 5.73 aspartic acid 0.004267 5.61 creatinine 0.002936 3.28 phosphate 0.004193 2.83 unidentified 0.006207 2.57 proline 0.012827 2.14 glutamine 0.010284 2.10 glutamic acid 0.007301 2.01 inositol 0.016795 2.00 serine 0.001466 1.76 glutamic acid and/or pyroglutamic acid 0.012589 1.68 glutamine 0.01492 1.67 ornithine 0.016795 1.60 unidentified 0.002936 1.55 threonine 0.001995 1.50 methionine 0.030011 1.45

Table 6.14 - Fingerprint Metabolites decreased in RA cells compared to control cells Metabolite P-value Fold change lactose 0.002343 0.31 glucose-6-phosphate 0.006095 0.33 unidentified 0.04461 0.38 glycerol-3-phosphate 0.000239 0.40 alanine 0.001636 0.45 lactic acid 0.033169 0.64 lactic acid 0.048555 0.70

273 6.6.2 Metabolomic footprint There were eight metabolic peaks representing 4 identified metabolites increased in the RA footprint. Three of these were increased in the 3-M footprint (cystine, pyruvic acid and 2-oxopropanoic acid) and the other metabolite (pencillamine) was identified as being increased in the CUL7 cells.

There were 10 metabolic peaks representing eight identified metabolites decreased in RA footprint. Seven of these were also identified as being decreased in the 3-M footprint. The remaining metabolite, lysine, is a essential amino acid which is subject in proteins to multiple posttranslational modifications including acetylation, methylation and ubiquitination.

274 Table 6.15 - Footprint Metabolites increased in RA cell conditioned media compared to control cell conditioned media

Metabolite P-value Fold change unidentified 0.00617 1.68 cystine 0.001995 1.60 pencillamine 0.016795 1.56 unidentified 0.026677 1.32 unidentified 0.017073 1.30 pyruvic acid 0.041227 1.20 2-oxopropanoic acid 0.030937 1.18 unidentified 0.004267 1.17

Table 6.16 - Footprint Metabolites decreased in RA cell conditioned media compared to control cell conditioned media Metabolite P-value Fold change cysteine 0.00058 0.25 alanine 0.012589 0.28 glutamine 0.009835 0.31 unidentified 0.00128 0.35 hexanoic acid 0.008873 0.50 3-methylpentanoic acid 0.004267 0.70 lysine 0.022934 0.89 glycine 0.024338 0.91 phenylalalnine 0.030937 0.92 lysine 0.041227 0.96

275 6.7 Discussion Studying the metabolome in 3-M syndrome cells was undertaken along with the transcriptome as part of a systems biology approach to understanding the pathogenesis of the condition. The technique used (gas chromatography mass spectrometry) routinely identifies around 200 metabolic peaks – mainly amino acids and sugars. While it has been possible to identify metabolic differences between 3-M and control cell lines using this data to better understand the pathogenesis of the condition is difficult. The changes most likely to be of interest in 3-M syndrome are at the genetic and proteomic level, while it was possible to hypothesize how changes in the transcriptome might affect the proteome moving backwards from the metabolome to the proteome has proven more difficult. Data available on metabolic changes in genetic conditions are limited (other than inborn errors of metabolism) and the available bioinformatic tools to examine metabolomic data are much more limited that those available for gene expression analysis. Overall there appeared to be a reduction in cellular energy metabolism which would be in keeping with reduced cell division identified in chapter 4.

The second aim of these experiments was as part of a pilot study to determine if metabolomics may be useful in identifying biomarkers of growth failure. With 90% of SGA children achieving catch up growth it would be useful to have a biomarker identifying whether a child is likely to experience catch up growth or not. Children could then be selectively followed up and earlier intervention with growth hormone considered in those predicted to fail to show catch up growth. This study was able to identify metabolites significantly altered between the 3-M patient cell lines and control cell lines. These studies will need to be extended to other groups of SGA children with failure of catch up growth and a comparison made to children born SGA who experienced adequate catch up growth. They could then be extended from cell lines into more convenient patient samples – serum and urine. Gas- chromatography/mass spectrometry was used in this study because of its ease of identification of metabolites and because of the high throughput low cost facilities available. Liquid-chromatography mass spectrometry identifies

276 around four times more metabolic peaks than gas chromatography mass spectrometry. To be clinically useful any biomarker will require a high positive or negative predictive value. The chances of finding such a biomarker may well be improved by using liquid chromatography mass spectrometry.

6.8 Key Points  Metabolic differences between 3-M and control cell lines were identified both in the metabolic fingerprint and in the footprint.  Metabolites with significant differences between the 3-M and control cell lines were predominantly involved in cellular energy metabolism.  Future studies should address the potential of metabolomics to identify potential biomarkers of growth failure in the SGA child via comparison with SGA with catch up control and by extending studies into serum and urine.

277

Chapter 7: Modelling 3-M syndrome in the non- placental vertebrate Xenopus tropicalis

278 7.1 Xenopus tropicalis

Xenopus tropicalis, the Western clawed frog, is an inhabitant of small bodies of water in equatorial West Africa. As a species it has several advantages as a laboratory animal and in particular for developmental biology studies. Firstly it can live and maintain fertility for over 10 years with females being induced to ovulate every 1-2 months, producing several hundred to thousands of eggs per cycle (Khokha et al., 2002). X. tropicalis eggs are large enough to be easily microinjected and as the embryos develop externally, so development can be continuously and easily followed.

X. tropicalis has a diploid genome with 20 chromosomes and an estimated genome size of 1 x 109 base pairs (Amaya et al., 1998). The diploid genome makes genetic manipulation in X. tropicalis much easier than X. laevis, the most common amphibian used in developmental biology studies. As Xenopus is a non-placenting animal modelling 3-M syndrome would enable us to study the effects of reduced gene expression independent of any effects on placental function. The initial plan was to study knockdown of the X. tropicalis ortholog OBSL1using microinjection of morpholino oligonucleotides. All injections were done with Drs E. Hilton and F. Manson.

7.2 Morpholino Oligonucleotides

Morpholino antisense oligonucleotides (MO) are DNA analogues whose altered sugar backbone is resistant to degradation by RNAse and DNAse intracellular enzymes (Summerton and Weller, 1997). They are usually 25 bases in length and bind to complementary sections of RNA to achieve knockdown of gene function via two modes of action: 1. Blocking mRNA translation (Summerton, 2007) 2. Altering nuclear processing to affect splicing of pre-mRNA (Morcos, 2007, Draper et al., 2001) Design of the MOs to be complementary to sequence from 5’ to 25 bases 3’ of the AUG translational start site stops the initiation complex as it moves

279 towards the start codon. This prevents formation of the complete ribosome and mRNA translation. Using this mechanism protein from the targeted gene is not produced. Targeting of the MO to an exon-intron or intron-exon boundary of internal exons usually results in deletion of the targeted exon. Targeting of the exon-intron/intron-exon boundaries of the first or last exons leads to inclusion of an intron (Morcos, 2007). Most often intron inclusion or exon exclusion will lead to nonsense mediated mRNA decay by inclusion of a premature termination codon.

The advantage of using MOs which alter nuclear processing is that the activity of the MO can be assessed with RT-PCR. Primers designed around the region of interest should yield a product altered in size (increased for intron inclusion and decreased in exon exclusion) if the MO is functioning. Confirming the activity of a MO targeted to the start codon requires the availability of an antibody to quantify protein production or the use of an in vitro transcription/translation assay (Hilton et al., 2007). The in vitro transcription/translation assay involves the creation of an mRNA with an added sequence for a protein tag. This is transcribed with/without the presence of the appropriate MO. Quantification of gene knockdown can be assessed using western blotting with an antibody against the tag.

MOs were originally used in cell culture and introduced into cells by cell scraping (Partridge et al., 1996). They have since been widely used in developmental biology and are introduced into an embryo at the one or two cell stage by microinjection (Heasman, 2002). MOs have been shown to phenocopy known mutants with two studies reporting 100% success rate in Zebrafish (Lele et al., 2001, Nasevicius and Ekker, 2000). Side effects of morpholinos include widespread cell death and neural degeneration at higher doses (Heasman, 2002). To control for these side effects experimental protocols normally include the use of a second MO and a control MO. This allows control from non-specific and off target effects. RNA rescue is the preferred method another method to confirm correct gene specific targeting (Eisen and Smith, 2008). This involves co-injection of an RNA which is not

280 affected by the MO. For a splicing MO this can be the full length wild type mRNA. Reversal of the phenotype with RNA rescue confirms the phenotype is not due to an off target effect.

7.3 Identification of X. tropicalis OBSL1 ortholog and design of Morpholino Oligonucleotides

Blastp and tblastn searches were performed using the human protein sequence in the BLAST feature of the Joint Genome Institute X. tropicalis genome project website (http://genome.jgi-psf.org/Xentr4/Xentr4.home.html). Both searches identified a fragment on scaffold 1022 consisting of 9 exons (e_gw.1022.53.1). Analysis of exon size and boundaries identified this as the first 9 exons of xtObsl1. It was not possible to identify the ATG start site as sufficient 5’ sequence was not available for exon 1. As we were unable to identify the ATG site and did not at this stage have an OBSL1 antibody we chose to design splice site MOs. Since our human mutations are in the first 5 exons of OBSL1 we chose to design the morpholinos to splice sites of xtObsl1exons 1 – 4 (see figure 3.1). Sequences of MO’s used were as follows: MO1 5’ – ATACCTCTCACATGTAACATGACGG – 3’ MO2 5’ – GAACCGCTCCCCAACCTCTGCCCAA – 3’ MO3 5’ – TTACCTCTGACAGCGACTTCGGGCGA – 3’ MO4 5’ – AGGCAGCTTCTTGGTAATTGGGCCT – 3’ Control 5’ – CCTCTTACCTCAGTTACAATTTATA – 3’

Figure 7.1 – Site of splice site morpholinos in xtObsl1.

A second fragment of X. tropicalis genomic DNA was identified using the tblastn (e_gw1022.45.1) which contained 10 putative exons. Analysis of exon size and exon-intron boundaries demonstrated this to be exons 10-19 of

281 xtObsl1. Alignment of the protein sequences of each genomic DNA fragment with clustalW confirmed the protein sequences from e_gw1022.53.1 and e_gw1022.45.1 aligned with the N terminal and C-terminal regions respectively. The genomic DNA fragments identified encode a transcript of 5079bp and a protein with 1691 amino acids which is 37% identical (50% similar) to OBLS1.

7.4 Microinjection of Control Morpholino

Three separate experiments were performed comparing embryos microinjected with 10 ng of a standard control MO from Gene-Tools with uninjected embryos. Control injected embryos were morphologically normal throughout development. Results are summarised in Table 7.1 and Figure 7.2. There were no significant differences in trunk length and intra-ocular distance between the uninjected and control MO injected tadpoles.

The primary reason for these experiments was to establish that microinjection of a MO does not itself lead to growth impairment in X. tropicalis embryos. Given that no experiments demonstrated a reduction in size in the control MO group it was concluded that microinjection of a control MO does not reduce embryonic growth at stage 50.

282

Table 7.1 – Measurements of trunk length and eye distance at stage 50 (14 days) in embryos injected with 10 ng control morpholino oligonucleotide and uninjected embryos.

Experiment Measurement Uninjected Control MO injected Sig. (trunk or eye N Length N Length (mm) distance) (mm) 1 Trunk 42 2.38 + 0.20 20 2.35 + 0.17 0.47 1 Eye 42 1.70 + 0.17 20 1.66 + 0.11 0.41 2 Trunk 20 2.30 + 0.16 20 2.33 + 0.19 0.55 2 Eye 20 1.67 + 0.12 20 1.68 + 0.20 0.90 3 Trunk 20 2.18 + 0.16 20 2.24 + 0.21 0.31 3 Eye 20 1.59 + 0.12 20 1.64 + 0.12 0.24 All 3 combined Trunk 82 2.31+0.20 60 2.30+0.18 0.58 All 3 combined Eye 82 1.67+0.15 60 1.66+0.11 0.70

283

Figure 7.2 - Trunk length and Intra-ocular distance measured at stage 50 (14 days) in uninjected and 10 ng control morpholino injected tadpoles. No significant differences were seen between uninjected and control MO injected tadpoles. Circles represent mean and error bars represent 95% confidence interval.

284

7.5 Injection of Morpholino Oligonucleotides targeted to alter splicing of xtObsl1

7.5.1 Injection of MO1

Microinjection of 10 ng MO1 produced morphologically normal embryos with a survival rate similar to uninjected embryos. When compared to uninjected embryos there was no difference in trunk size (uninjected vs 10 ng MO1; 2.05 + 0.14 mm v 2.17 + 0.18 mm, p=0.13) or eye distance (1.52 + 0.15 mm v 1.51 + 0.15 mm, p=0.77) (n=20 embryos in each group, total number of experiments = 1, see figure 7.3). 10 ng MO was chosen as this is the maximum dose of a morpholino generally tolerated before non-specific effects such as oedema and poor mobility are seen. Additionally there was no effect seen on mRNA splicing (see figure 7.10).

285

Figure 7.3 – Comparison of uninjected tadpoles and tadpoles injected with 10 ng MO1. A) Light microscopy demonstrated morphologically normal tadpoles at stage 37-8. Magnification in both images was identical. B) Trunk length and eye distance measured at stage 50 (14 days) were not significantly different between the uninjected (n=20) and MO1 injected (n=20) groups. . Circles represent mean and error bars represent 95% confidence interval.

286

7.5.2 Injection of MO2 MO2 induced a significant effect on embryo development with very high mortality rates at doses of 10, 5 and 2 ng (number of experiments 3, >30 embryos in each group). At each of these doses there were no surviving embryos at 14 days, with the majority dying within the first 48 hours of life. Embryos appeared to be unable to elongate at higher doses (see figure 7.4). It was therefore felt that this was likely to represent an off target effect.

5 ng 10 ng

Figure 7.4 – MO2 produces severely abnormal embryos with high mortality rates at doses of 2-10 ng. Light microscopy of Stage 36-37 MO2 and uninjected embryos. Abnormalities of elongation can be seen at higher doses. Magnification in both images was identical

287 7.5.3 Injection of MO3

MO3 demonstrated a small phenotype in otherwise normal tadpoles. An injection dose of 10 ng resulted in visually small embryos (see Figure 7.5) while doses of 15 ng and 20 ng resulted in embryos with oedema and poor mobility, non-specific effects seen with injection of a high dose of any morpholino oligonucleotide. Trunk length and eye distance were consistently reduced over three experiments in the 10 ng group compared to uninjected tadpoles (see figures 7.5, 7.6 and table 7.2).

Table 7.2 – Trunk length and eye distance measured at stage 50 (14 days) in three experiments comparing uninjected tadpoles to tadpoles injected with 10 ng MO3. In each experiment trunk length and eye distance were significantly reduced in the MO3 injected tadpoles.

Experiment Measurement Uninjected MO3 10ng Sig. (trunk or intraocular N Length N Length (mm) Distance) (mm) 1 Trunk 23 2.22 + 0.14 22 1.63 + 0.22 <0.001 1 Eye 23 1.67 + 0.13 22 0.98 + 0.18 <0.001 2 Trunk 21 2.05 + 0.14 20 1.89 + 0.18 0.03 2 Eye 21 1.52 + 0.15 20 1.32 + 0.13 <0.001 3 Trunk 42 2.39 + 0.19 29 2.08 + 0.28 <0.001 3 Eye 42 1.70 + 0.17 29 1.44 + 0.26 <0.001 All3 combined Trunk 86 2.24+0.22 71 1.91+0.31 <0.001 All3 combined Eye 86 1.65+0.16 71 1.26+0.29 <0.001

7.5.4 Injection of MO4 Injection of MO4 at doses of above 2 ng was associated with morphologically abnormal tadpoles with poor survival rates (see figure 7.7). At 10 ng there were no survivors to stage 50 while at 5 ng a small number of tadpoles survived with some displaying an obvious phenotype. Due to the high death rates it was not possible to study the effects of 5 ng MO4 at 14 days post-injection. Two independent dose response experiments were undertaken to examine the effects of doses at 2 ng and below in growth (see Table 7.3). In the first experiment only 2 ng MO4 produced a reduction in trunk length (ANOVA p=0.12, Tukey post-hoc p=0.006). In this experiment

288 no significant differences were seen between the uninjected and MO4 injected tadpoles for intra-ocular distance (ANOVA p=0.09). In the second experiment all doses produced a reduction in trunk length (p<0.02) but only 0.5 ng and 2 ng also produced a reduction in intra-ocular distance (p<0.001 and p<0.006 respectively). It was therefore decided to further pursue the effects of injecting 2 ng MO4. Trunk length was significantly reduced in three independent experiments and intra-ocular distance significantly reduced in two experiments (see Table 7.4 and Figure 7.8). Combining all 3 experiments together demonstrated significant reductions in trunk length (p<0.001) and intra-ocular distance (p<0.001).

Figure 7.5 - Light micrograph of an uninjected embryo and two growth retarded MO3 10 ng injected embryos (all embryos stage 50).

289

Figure 7.6 – MO3 produces growth retarded but otherwise phenotypically normal embryos at 10 ng injection dose. Three separate experiments comparing trunk length and eye distance in stage 50 (day 14) uninjected embryos and a group injected with 10 ng MO3. Both trunk length and eye distance are significantly reduced in each experiment. Circles represent mean and error bars represent 95% confidence interval.

290 Table 7.3 Trunk length and eye distance measured at stage 50 (14 days) in uninjected tadpoles and tadpoles injected with 0.5 ng, 1 ng, and 2 ng of MO4. The only dose to produce a significant reduction in size in both experiments was 2 ng. *p<0.05 for difference to control on Tukey post-hoc analysis.

Experiment Dose MO4 N Trunk Length Intra-ocular Distance 1 Uninjected 18 2.35 + 0.36 1.67+ 0.19 2 Uninjected 20 2.21 + 0.25 1.67 + 0.15 1 0.5 ng 7 2.17 + 0.15 1.59 + 0.14 2 0.5 ng 20 2.00 + 0.13* 1.51 + 0.97* 1 1 ng 20 2.22 + 0.19 1.71 + 0.15 2 1 ng 20 2.02 + 0.15* 1.60 + 0.93 1 2 ng 20 2.08 + 0.13* 1.59 + 0.14 2 2 ng 20 2.05 + 0.15* 1.54 + 0.11*

Table 7.4 - Trunk length and eye distance measured at stage 50 (14 days) in three experiments comparing uninjected tadpoles to tadpoles injected with 2ng MO4. In each experiment trunk length was significantly reduced in the MO4 injected embryos. Eye distance was significantly reduced in the MO4 injected groups in two out of three experiments.

Experiment Measurement Uninjected MO4 2ng injected Sig. (trunk or eye distance) N Length N Length (mm) (mm) 1 Trunk 19 2.63 + 0.16 13 2.22 + 0.17 <0.001 1 Eye 19 1.79 + 0.10 13 1.59 + 0.91 <0.001 2 Trunk 20 2.21 + 0.26 20 2.05 + 0.16 0.023 2 Eye 20 1.67 + 0.16 20 1.54 + 0.12 0.006 3 Trunk 18 2.36 + 0.36 20 2.08 + 0.13 0.003 3 Eye 18 1.67 + 0.19 20 1.59 + 0.15 0.157 All 3 Trunk 57 2.39 + 0.31 53 2.10 + 0.16 <0.001 Combined All 3 Combines Eye 57 1.71 + 0.15 53 1.57 + 0.12 <0.001

291

A B

10ng MO4

5 ng MO4 and 2 uninjected

Figure 7.7 - MO4 produces abnormal tadpoles with high mortality rates at doses above 2 ng. A) Light micrograph of normal uninjected tadpoles (stage 37-8), abnormal embryos who received an injection of 10ng MO4 (stage 37- 8) and a 5ng injected embryo displaying a small phenotype (stage 50). B) Survival of tadpoles at 48 hours post-injection with increasing doses of MO4. Survival falls sharply with doses above 2ng.

292

Figure 7.8 - MO4 produces growth retarded but otherwise phenotypically normal embryos at 2 ng injection dose. Three separate experiments comparing trunk length and eye distance in uninjected embryos and a group injected with 2ng MO4 measured at stage 50 (14 days). Both trunk length and eye distance are significantly reduced in experiments one and two. In experiment three trunk length was significantly reduced but eye distance was not. Circles represent mean and error bars represent 95% confidence interval.

293

7.6 RT-PCR of xtObsl1 mRNA in uninjected and morpholino injected embryos

Five stage 25 embryos were taken for RNA extraction from several groups: 1. uninjected embryos 2. embryos injected with 10 ng xtObsl1 MO1 3. embryos injected with 5 ng xtObsl1 MO2 4. embryos injected with 10 ng xtObsl1 MO3 5. embryos injected with 2 ng xtObsl1 MO4

cDNA was generated and a fragment of xtObsl1 spanning exons 1-5 was amplified using PCR (primers designed by D. Hanson). Intron retention caused by MO1 or MO2 is predicted to lead to an amplicon size of over 2kbp which is not expected to be amplified using an extension time of 30 seconds and thus would not be visualised on the agarose gel. Retention of intron 2 or exclusion of exons 2 or three would lead to a change in amplicon size which should be visualized with agarose gel electrophoresis (see figure 7.9). Figure 7.10 shows the PCR product for each group. Intron retention and exon exclusion are clearly seen for MO3 and MO4 with the presence of additional bands at the appropriate size. A band corresponding to the appropriate size for exon 2 exclusion can be seen in the MO2 lane. There does appear to be a band of reduced size in the uninjected lane, however, the intensity of this band is greatly increased in the MO3 and MO4 injected lanes. RT-PCR of uninjected and morpholino injected xtObsl1 tadpoles was also undertaken by Dr D Hanson and is presented in his thesis.

294 Figure 7.9 – cDNA transcript of xtObsl1 amplified and the effects of MO1-4 on expected amplicon size

Normal transcript total size 693bp

Inclusion intron 1 produced by MO1 or MO2 total size over 2.9kbp

Exclusion of exon 2 produced by MO2 or MO3 total size 426bp

Inclusion intron 2 produced by MO3 or MO4 total size 793bp

Exclusion of exon 3 produced by MO4 total size 588bp

295 Figure 7.10 – PCR of a fragment spanning exons 1-5 of xtObsl1 in cDNA generated from 5 stage 25 embryos from several groups: 1. uninjected labelled U 2. embryos injected with 10ng of xtObsl1 MO1 labelled MO1 3. embryos injected with 5 ng of xtObsl1 MO2 labelled MO2 4. embryos injected with 10ng of xtObsl1 MO3 labelled MO3 5. embryos injected with 5ng xtObsl1 MO4 labelled MO4 Two lanes are seen for MO1 and MO3. Lane 1 is loaded with Hyperladder IV (10 bands in the range of 100bp – 1000bp, each band representing an increment of 100bp). Bands corresponding to intron retention and exon exclusion can be seen for MO3 and MO4. A band which may represent exon exclusion can also be seen for MO2.

Exon 2 exclusion

Intron 2 Inclusion

296 7.7 Discussion and Future Work Necessary to Confirm Initial Findings The finding that two different morpholino oligonucleotides designed to alter splicing and reduce expression of xtObsl1 resulted in growth impairment at stage 50 is highly suggestive that loss of xtObsl1 results in growth impairment which is, at least in part, independent of placental function. To confirm this finding the phenotype of growth impairment should be demonstrated to be preventable by co-injection of xtObsl1 mRNA with the morpholino. This was not possible to undertake as a) no clone of xtObsl1 is available and b) the genome of X. tropicalis had not been completely sequenced and the sequence of the 5’ region and ATG site of xtObsl1 was unavailable. A clone of the human short isoform of OBSL1 is available but given the low level of homology between the human and Xenopus Obsl1, it is highly unlikely to produce successful rescue of the phenotype.

An alternative to a RNA rescue experiment would be to demonstrate that co-injection of two morpholinos, each at a dose which individually causes no phenotype, generates a phenotype on co-injection. This would be a more promising strategy than RNA rescue given the lack of availability of a clone of xtObsl1. Additionally morpholino injections variably induce p53 activity, which could plausibly induce growth impairment (Robu et al., 2007) and it is recommended that co-injection of a p53 morpholino with the morpholino being investigated should be undertaken. Accumulation and/or activation of p53 may play a role in the pathogenesis of 3M syndrome; if that hypothesis is correct, interpreting the results of p53 co-injection would be challenging. If the phenotype resolved with p53 co-injection that could indicate the phenotype was a non-specific effect or that p53 was key to the pathogenesis.

It appears clear that injection of morpholinos directed against xtObsl1 induces early embryonic death when injected at higher doses. It is possible that this is an off target effect on another immunoglobulin containing protein with a similar sequence. Another, more likely, hypothesis is that it is loss of xtObsl1 that is directly causing the high death rate. Although loss of OBSL1 in humans does not cause death, loss of CUL7 leads to embryonic death in

297 mouse but not in humans. It is therefore possible that OBSL1 is essential for early embryonic development in some species but not others. The phenotype of embryonic death caused significant problems due to the narrow therapeutic window between survival with growth impairment and death.

As well as being limited by the high rates of death the work was also limited by the transient nature of the effects of morpholinos. Morpholino concentration reduces over time and with growth of the embryo and they are generally thought to have limited effect 7 days after injection. Given that the first 7 days of life in Xenopus consist mainly of organogenesis with limited growth, with a growth spurt in the second week of life, the technique has significant limitations for studying growth.

7.8 Key points  Two independent morpholinos designed to reduce xtObsl1 expression produced a phenotype of growth retardation indicating that the growth impairment seen in 3M syndrome is likely to be at least partially independent of placental function  This finding requires confirmation with a RNA rescue or dual morpholino co-injection experiment

298

Chapter 8: Discussion

299 The overall aim of this project was to identify the process through which loss of CUL7 and OBSL1 lead to growth impairment in the 3-M syndrome. It is hoped that better understanding this rare monogenic growth disorder might lead to an improved understanding of the pathophysiology of the SGA child with failure of postnatal catch up growth and, that this understanding, may lead to novel therapies particularly for the group who do not respond to growth hormone therapy. Initially a hypothesis driven approach was taken and in addition a systems biology hypothesis generating approach was also undertaken.

The first step in attempting to unravel the pathogenesis of 3-M syndrome was to develop fibroblast cell lines from the different genetic sub groups of the condition following a careful examination of the phenotype to confirm that these genetic sub-groups were not in fact distinct conditions. The clinical features most often present were a fleshy tipped nose and prominent heels. The presence of either of these features in combination with growth failure should raise the possibility of a diagnosis of 3-M syndrome. Only minor differences in phenotype (rates of 5th finger clinodactyly and full fleshy lips) were identified between genetic sub groups. Height SDS was lowest in CUL7 patients and highest in patients with no identified mutation. Response to growth hormone therapy was assessed in a small number of patients and appeared to be poor with a 4 year HT SDS of +0.5. IGF-1 levels were low for the given age/gender reference range. In comparison IGFBP3 levels were relatively high, in combination with the low total IGF-1 levels this may result in low free IGF-1 levels contributing to the growth impairment.

The first component of studying the fibroblast cell lines was to identify CUL7 and OBSL1 levels. For CUL7 we confirmed that it was absent in our fibroblast cell line with a CUL7 nonsense mutation and present in the OBSL1 mutation and control fibroblasts. Immunoflourescence identified that CUL7 was located in the Golgi apparatus and was normally located in the OBSL1 mutation cell line. This finding was in contrast to published work which, using an overexpressed tagged CUL7, identified a cytoplasmic localization

300 (Andrews et al., 2006). More recent work has agreed with our findings of localization in the Golgi (Litterman et al., 2011) – this study used neuronal cell lines and assessed localization of endogenous CUL7. Although it may be that the difference in localization is due to cell specific effects it is more probable that in the study by Andrews et al the localization was affected either by the tag molecule or the over expression. For OBSL1 we were unable to assess protein levels or localization in our fibroblast cell lines due to the poor quality of the custom antibody available.

Previous work has identified that CUL7 may influence apoptosis, potentially mediated via p53, in cell lines where CUL7 levels were either ectopically expressed or reduced via siRNA knock down (Andrews et al., 2006, Jung et al., 2007, Kim et al., 2007). In the work presented here two different assays were used to measure apoptosis – a cleaved caspase 3 ELISA and a TUNEL assay. Neither detected any increase in apoptosis. Rates of apoptosis in our fibroblast cell lines were low and it is possible that there is a small difference that we were unable to detect. Inducing apoptosis via chemicals, ionizing radiation or hypoxia increases apoptosis via activation of p53. An increase in apoptosis in 3-M cells may be present under these conditions but not at basal conditions and thus would not have been detected by the experiments presented here. It is however important to note that the other studies were undertaken in cancer cell lines where there may be multiple other genetic changes affecting cell proliferation and apoptosis. Changes in CUL7 levels in that genetic background may have different effects than in primary fibroblasts. Human skin fibroblasts are likely to be a more appropriate cell line, in which to study normal growth than cancerous cell lines.

A number of changes were detected in gene expression and protein levels of the IGFBPs – a reduction in expression and secretion of IGFBP2 and IGFBP7, reduced expression but no change in protein levels of IGFBP5 and increased protein levels of IGFBP3. Only for IGFBP3 was there a serum assay with a normal reference range, for 3-M patients IGFBP3 levels were

301 within the upper half of the normal reference range. Other IGFBPs were not assayed in serum due to the lack of a control serum population or an assay with a reference range. IGFBP7 is a known tumour suppressor gene (Vizioli et al., 2010) and thus a reduction may be a compensatory response to loss of function of CUL7, a known antiapoptotic oncogene. The increase in IGFBP3 may be a compensatory response to the loss of IGFBP2 and overall it is likely the changes in IGFBP levels remain part of the response to the growth disruption in 3-M syndrome rather than being involved in the pathogenesis.

Given the known involvement of the ubiquitination system in the GH-IGF-1 signal transduction system (Strous et al., 2004, Strous et al., 1997, van Kerkhof et al., 2002) and the alterations in Akt seen in Cul7 -/- mouse embryonic fibroblasts (Xu et al., 2008) we hypothesized that signal transduction in response to GH and IGF-1 may be reduced in 3-M cell lines. A reduction in AKT activation after stimulation with IGF-1 was identified in the 3-M cell lines studies. This defect was more significant in the CUL7 mutation cell line than in the OBSL1 mutation cell line or no identified mutation cell line. No significant impairment was found in GH signal transduction. It is unlikely that this defect in IGF-1 signal transduction is the sole reason for short stature but it may be contributory.

After utilizing a number of hypothesis driven studies we then used a hypothesis generating approach examining the cellular transcriptome and metabolome in 3-M syndrome. The transcriptome studies yielded the most interesting data identifying a large number of genes up/down regulated with several which may be involved in 3-M syndrome pathogenesis. The most interesting of these was IGF2, which was reduced in 3-M syndrome. Given the phenotypic overlap between 3-M and Silver Russell Syndromes, with then known involvement of IGF2 silencing in Silver Russell Syndrome, a reduction in growth-plate localized IGF-II levels could be an important pathological finding in 3-M syndrome.

302 Given the findings of IGF2 silencing with increased expression of H19 the obvious mechanism would be hypomethylation at 11p15 – the epigenetic change identified in ~50% of cases of SRS. Initial work by a collaborator did not, however, identify any differences in 11p15 methylation between control and 3-M fibroblast DNA using bisulphite sequencing and methylation specific PCR (D. Mackay, Personal Communication). Hypomethylation exerts its effect on IGF2 transcription by permitting binding of CCTC binding factor to DNA blocking access to IGF2 promotors. The next step was therefore to examine levels of CCCTC binding factor – there was a clear effect of reduced levels in the C7 and OBF fibroblasts but no identified reduction in RA fibroblasts. When comparing the C7, OBF and RA fibroblasts the reduction in IGF2 silencing and IGF-II levels in conditioned cell culture media was more modest in RA compared to the other cell lines. It is possible that there is a more modest reduction in CCCTC binding factor levels in RA but that western immunoblotting was not sensitive enough to detect this change. The findings that IGF2 silencing and protein production in RA are less severely affected fits with the clinical data where the no identified mutation patients were taller than the groups with CUL7 or OBSL1 mutations.

The studies on the cellular metabolome in 3-M syndrome did yield differences between the control and 3-M cells. Because the differences are much lower than those found in the transcriptome, and the implications of these changes less clear, it was difficult to link these changes to pathophysiological mechanisms linked to growth failure. Metabolomic studies are probably more suited to identifying novel biomarkers e.g. for growth failure in SGA infants. Further studies should examine serum and urine metabolome in SGA catch up and non-catch up infants. Overall the changes identified indicated alterations in cellular energy production/usage – this could be either that the 3-M syndrome fibroblasts are utilizing less energy due to their limited growth or it could be that the reduced energy utilization inhibits cell proliferation. In addition to changes to energy metabolism alterations in the levels of inositol-1-phosphate and myo-inositol were identified. Higher concentrations of myo-inositol have previously been

303 identified in IUGR piglets when compared to wild type littermates (Nissen et al., 2011). In addition in human subjects with diabetes urinary inositol is increased in comparison to controls (Ostlund et al., 1993). Administration of insulin resulted in an increase in plasma inositol levels in poorly controlled diabetics (Ostlund et al., 1993). It may be that the changes in inositol metabolism seem represent one component of the fetal programming responsible for the higher rated of type II diabetes seen in adult who were born SGA.

One hypothesis was that the growth impairment seen was due to alteration in placental function. There were three main sources of data suggesting that loss of CUL7 may result in impaired placental function: the small placentas with abnormal vasculature in the Cul7 -/- mouse (Arai et al., 2003), alterations in methylation of the CUL7 promoter and CUL7 expression in placentas from IUGR fetuses (Gascoin-Lachambre et al., 2010) and the data from placental derived choriocarcinoma cell line indicating that CUL7 is involved in epithelial-mesenchymal transformation (Fu et al., 2010). This hypothesis was tested by morpholino oligonucleotide knockdown of Obsl1 expression in Xenopus tropicalis. xtObsl1 was selected rather than xtCul7 as it appears CUL7 and CUL8/pARC arose as a result of a gene duplication event and in X. tropicalis this gene duplication event has not occurred and the identified xtCUL7 homolog sequence appeared to be more similar to CUL8/pARC than CUL7. As a non-placental vertebrate X. tropicalis the growth impairment seen in the xtObsl1 knock down tadpoles is highly suggestive that the growth impairment seen in 3-M syndrome is at least in part independent of placental function.

The work in Xenopus was limited by the short term effect of the morpholino – once injected the concentration is diluted as the embryo develops and the effect on gene transcription reduces. Organogenesis is completed within the first week of life but growth continues to occur after this. In this study growth impairment was observed only after 14 days of age – a time when gene transcription is unlikely to be affected by the morpholino. While morpholino

304 oligonucleotide mediated gene expression knock down may be a highly useful tool to study disorders of organogenesis it may well be less useful to study growth disorders. Furthermore the findings in Xenopus require to be confirmed by rescue of the phenotype with co-injection of xtObsl1 mRNA. This was not possible to achieve because no clone of xtObsl1 was available and the full sequence of xtObsl1 was also not available. Co-injection of alternative OBSL1 mRNA from available clones is limited to either then short human isoform or the full length mouse isoform. Given the low level of similarity between human/mouse OBSL1 and xtObsl1 it is unlikely that this strategy would be successful.

After this project work was completed work within our laboratory identified mutations within the coiled coil domain containing 8 gene (CCDC8) (Hanson et al., 2011). This is a single exon gene located on chromosome 19 and encodes transcripts of 3213 and 2097 bp with proteins of 538 and 324 aa. There is little data available of the function of CCDC8 but it has been identified to interact with OBSL1. Further work to study the interacting partners of CUL7, OBSL1 and CCDC8 may help understand the pathogenesis of 3-M syndrome.

In conclusion the studies described here have yielded valuable information on the clinical phenotype and the cellular and molecular effects of mutations within CUL7, OBSL1 and CCDC8. Several factors idnetifed may contribute to the growth impairment seen in 3-M syndrome – reduced free IGF-1 levels, impaired IGF-1 signalling and IGF2 silencing. While much further work will be required to fully understand the condition and to examine whether similar mechanisms are disrupted in other groups of SGA children a useful start has been made.

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