Chapter 2 - University of British Columbia

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Table 4.2. List of major oncogenes and tumor suppressor genes assessed Gene Chr Gene Chr Gene Chr ABL1 9 EVI1 3 NF2 22 ABL2 1 FBXW7 4 NKX2-1 14 AKT1 14 FEV 2 NOTCH1 9 AKT2 19 FGFR1 8 NRAS 1 ALK 2 FGFR2 10 NTRK1 1 APC 5 FGFR3 4 NTRK3 15 ATM 11 FH 1 PDGFB 22 BCL2 18 FHIT 3 PDGFRA 4 BCL3 19 FLT3 13 PDGFRB 5 BCL6 3 FOXO1A 13 PHOX2B 4 BMPR1A 10 FOXO3A 6 PIK3CA 3 BRAF 7 FOXP1 3 PIK3R1 5 BRCA1 17 GNAS 20 PIM1 6 BRCA2 13 GSTP1 11 PRKAR1A 17 BUB1B 15 HRAS 11 PTCH 9 CAV1 7 HRPT2 1 PTEN 10 CBL 11 ITK 5 PTPN11 12 CCND1 11 JAK2 9 RARB 3 CCND2 12 JAK3 19 RASSF1A 3 CCND3 6 KIT 4 RB1 13 CD44 11 KRAS 12 REL 2 CDH1 16 LCK 1 RET 10 CDH11 16 MAF 16 RUNX1 21 CDH13 16 MAFB 20 SEMA3B 3 CDK4 12 MAML2 11 SMO 7 CDK6 7 MAP2K4 17 STK11 19 CDKN2A 9 MDM2 12 SUFU 10 CEBPA 11 MEN1 11 SYK 9 CHEK2 22 MET 7 TCF1 12 CRK 17 MLH1 3 TIMP3 22 CTNNB1 3 MLL 11 TP53 17 CYLD 16 MPL 1 TSC1 9 DAPK1 9 MSH2 2 TSC2 16 EGFR 7 MSH6 2 TSHR 14 ERBB2 17 MYC 8 VHL 3 ERCC2 19 MYCL1 1 WT1 11 ERG 21 MYCN 2 ETV6 12 NF1 17 101
Table 4.3. Overlap of oncogenes in frequent regions of genomic alteration Gene Symbol Location Gain Loss UPD ABL1 9q34.1 X ABL2 1q24-q25 X AKT1 14q32.32 X AKT2 19q13.1q13.2 X BCL6 3q27 X CCND1 11q13 X CCND3 6p21 X CD44 11p13 X CDK4 12q14 X CEBPA 19q13.11 X CRK 17p13.3 X EGFR 7p12.3-p12.1 X ERBB2 17q21.1 X ETV6 12p13 X FEV 2q36 X FGFR3 4p16.3 X FLT3 13q12 X GNAS 20q13.2 X HRAS 11p15.5 X ITK 5q31-q32 X KRAS 12p12.1 X LCK 1p35-p34.3 X MAFB 20q11.2q13.1 X MDM2 12q15 X MEN1 11q13 X MPL 1p34 X MYC 8q24.12q24.13 X MYCL1 1p34.3 X NOTCH1 9q34.3 X NTRK1 1q21-q22 X PDGFB 22q12.3q13.1 X PDGFRB 5q31-q32 X PIK3CA 3q26.3 X PIM1 6p21.2 X PRKAR1A 17q23-q24 X SMO 7q31-q32 X 102
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DEVELOPMENT AND APPLICATION OF AN I
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Table of Contents Abstract ........
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3.3.2 Multi-dimensional analysis (M
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List of Tables Table 2.1. Features
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Figure 5.3. Overlay of chromosomal
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RB1 Retinoblastoma 1 RNA Ribonuclei
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Dedication To my family. xiii
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Chapter 5: Chari R, Thu KL, Wilson
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1.1 Lung cancer Lung cancer has the
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expression changes are reactive to
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number of different cancer types. M
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large number of tumors, that a give
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(B) By using an integrative approac
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platforms, with one of the latest s
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1.12.1 Development of tools for gen
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quantitative PCR experiments as wel
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1.13 References 1. Jemal A, Siegel
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33. Garber ME, Troyanskaya OG, Schl
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71. Shivapurkar N, Gazdar AF: DNA M
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Chapter 2: SIGMA 2 : A system for t
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Here, we present SIGMA 2 , a novel
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datasets. To utilize this, the user
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2.3.7 Analysis of data from multipl
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expression (Figure 2.8). ERBB2 has
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Figure 2.1 R -Segmentation -Statist
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Figure 2.3 numSamples
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Figure 2.5. Consensus calling and h
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Figure 2.6 HCC2218 HCC2218 HCC2218B
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Figure 2.8. Multi-dimensional persp
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Table 2.1. Features required for in
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2.6 References 1. Garnis C, Buys TP
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Chapter 3: An integrative multi-dim
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Page 67 and 68: Raw gene expression profiles from a
Page 69 and 70: screening approach to gene amplific
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Page 73 and 74: approach to examining the whole gen
Page 75 and 76: PTEN expression [44]. Using this pa
Page 77 and 78: mechanisms at the DNA and RNA level
Page 79 and 80: In this study, three DNA dimensions
Page 81 and 82: Figure 3.2. Quantitative and qualit
Page 83 and 84: Figure 3.3 a Proportion of genes in
Page 85 and 86: 70 Figure 3.5 -log(pvalue) 5.0 4.0
Page 87 and 88: 72 Figure 3.7 Sample: HCC1008 Copy
Page 89 and 90: Figure 3.8 a b Proportion of random
Page 91 and 92: 16. Chari R, Lockwood WW, Coe BP, C
Page 93 and 94: 50. Giovane A, Pintzas A, Maira SM,
Page 95 and 96: 4.1 Introduction Genetic alteration
Page 97 and 98: 4.2.3 Determining frequent regions
Page 99 and 100: etween loss and UPD (Figure 4.3). S
Page 101 and 102: obtained, profiled and used as the
Page 103 and 104: Figure 4.1. Detection of UPD using
Page 105 and 106: Figure 4.2. Comparison of frequent
Page 107 and 108: Figure 4.3 Gain Loss 642 441 7 Figu
Page 109 and 110: 94 Figure 4.4 1 2 3 4 5 6 7 8 9 10
Page 111 and 112: Figure 4.6 a b c Percent of cases A
Page 113 and 114: Figure 4.7 a b 6p25.3 Log2 fold cha
Page 115: Chr BPStart BPEnd # of Chr BPStart
Page 119 and 120: Table 4.5. Cell lines and oncogene
Page 121 and 122: Table 4.7. RefSeq genes in focal re
Page 123 and 124: 4.6 References 1. Bell DW: Our chan
Page 125 and 126: 33. Garnis C, Coe BP, Lam SL, MacAu
Page 127 and 128: 5.1 Introduction In the past decade
Page 129 and 130: polymorphism (SNP) arrays with over
Page 131 and 132: substitutions) and UV exposure (C t
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Page 135 and 136: Histone modification states. While
Page 137 and 138: metastasis [226]. High throughput a
Page 139 and 140: Implications on sample size require
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Page 143 and 144: expression. The next challenge is t
Page 145 and 146: Figure 5.2 # of copies Total copy n
Page 147 and 148: Figure 5.4. Integration of copy num
Page 149 and 150: Figure 5.5. Integration of copy num
Page 151 and 152: Figure 5.6 SHC1 GRB2 SOS2 RRAS ER R
Page 153 and 154: Figure 5.8 a Log2 Fold Change (T vs
Page 155 and 156: Figure 5.10 (a) (b) Figure 5.10. Au
Page 157 and 158: Table 5.2. List of genomic resource
Page 159 and 160: 5.5 References 1. Pinkel D, Segrave
Page 161 and 162: 37. Oliphant A, Barker DL, Stuelpna
Page 163 and 164: 75. Selzer RR, Richmond TA, Pofahl
Page 165 and 166: 111. Melcher R, Al-Taie O, Kudlich
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145. Takai D, Yagi Y, Wakazono K, O
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179. Kondo M, Suzuki H, Ueda R, Osa
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alterations in human prostate cance
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248. Xi L, Feber A, Gupta V, Wu M,
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281. Fernandez-Ranvier GG, Weng J,
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Chapter 6: Conclusions 162
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can identify nearly three times as
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was identified in a small set of sa
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will be done at the pathway level a
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previously described genetic and ep
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16. Zhang K, Li JB, Gao Y, Egli D,
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APPENDIX I: List of publications Th
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This publication is described in se
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This chapter details the technologi
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epigenetic alteration. This led to
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This manuscript describes the curre
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APPENDIX III: Sources of data Sampl
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APPENDIX V: Kaplan-Meier and Oncomi
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APPENDIX VI: Summary of Kaplan-Meie
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University of British Columbia - Br
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