Chapter 2 - University of British Columbia

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92. Lockwood WW, Chari R, Coe BP, Girard L, Macaulay C, Lam S, Gazdar AF, Minna JD, Lam WL: DNA amplification is a ubiquitous mechanism of oncogene activation in lung and other cancers. Oncogene 2008, 27(33):4615-4624. 93. Myllykangas S, Himberg J, Bohling T, Nagy B, Hollmen J, Knuutila S: DNA copy number amplification profiling of human neoplasms. Oncogene 2006, 25(55):7324- 7332. 94. Teschendorff AE, Caldas C: The breast cancer somatic 'muta-ome': tackling the complexity. Breast Cancer Res 2009, 11(2):301. 95. Chin SF, Teschendorff AE, Marioni JC, Wang Y, Barbosa-Morais NL, Thorne NP, Costa JL, Pinder SE, van de Wiel MA, Green AR et al: High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer. Genome Biol 2007, 8(10):R215. 96. Coe BP, Lockwood WW, Girard L, Chari R, Macaulay C, Lam S, Gazdar AF, Minna JD, Lam WL: Differential disruption of cell cycle pathways in small cell and non-small cell lung cancer. Br J Cancer 2006, 94(12):1927-1935. 97. Bass AJ, Watanabe H, Mermel CH, Yu S, Perner S, Verhaak RG, Kim SY, Wardwell L, Tamayo P, Gat-Viks I et al: SOX2 is an amplified lineage-survival oncogene in lung and esophageal squamous cell carcinomas. Nat Genet 2009, 41(11):1238-1242. 98. Garraway LA, Widlund HR, Rubin MA, Getz G, Berger AJ, Ramaswamy S, Beroukhim R, Milner DA, Granter SR, Du J et al: Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 2005, 436(7047):117-122. 99. Weir BA, Woo MS, Getz G, Perner S, Ding L, Beroukhim R, Lin WM, Province MA, Kraja A, Johnson LA et al: Characterizing the cancer genome in lung adenocarcinoma. Nature 2007, 450(7171):893-898. 100. Kwei KA, Kim YH, Girard L, Kao J, Pacyna-Gengelbach M, Salari K, Lee J, Choi YL, Sato M, Wang P et al: Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer. Oncogene 2008, 27(25):3635-3640. 101. Plomin R, Haworth CM, Davis OS: Common disorders are quantitative traits. Nat Rev Genet 2009, 10(12):872-878. 102. Savas S, Liu G: Genetic variations as cancer prognostic markers: review and update. Hum Mutat 2009, 30(10):1369-1377. 103. Ansorge WJ: Next-generation DNA sequencing techniques. N Biotechnol 2009, 25(4):195-203. 104. Shah SP, Kobel M, Senz J, Morin RD, Clarke BA, Wiegand KC, Leung G, Zayed A, Mehl E, Kalloger SE et al: Mutation of FOXL2 in granulosa-cell tumors of the ovary. N Engl J Med 2009, 360(26):2719-2729. 105. Greenman C, Stephens P, Smith R, Dalgliesh GL, Hunter C, Bignell G, Davies H, Teague J, Butler A, Stevens C et al: Patterns of somatic mutation in human cancer genomes. Nature 2007, 446(7132):153-158. 106. Stratton MR, Campbell PJ, Futreal PA: The cancer genome. Nature 2009, 458(7239):719-724. 107. Cavenee WK, Hansen MF, Nordenskjold M, Kock E, Maumenee I, Squire JA, Phillips RA, Gallie BL: Genetic origin of mutations predisposing to retinoblastoma. Science 1985, 228(4698):501-503. 108. Knudson AG, Jr.: Mutation and cancer: statistical study of retinoblastoma. Proc Natl Acad Sci U S A 1971, 68(4):820-823. 109. Benz CC, Fedele V, Xu F, Ylstra B, Ginzinger D, Yu M, Moore D, Hall RK, Wolff DJ, Disis ML et al: Altered promoter usage characterizes monoallelic transcription arising with ERBB2 amplification in human breast cancers. Genes Chromosomes Cancer 2006, 45(11):983-994. 110. LaFramboise T, Weir BA, Zhao X, Beroukhim R, Li C, Harrington D, Sellers WR, Meyerson M: Allele-specific amplification in cancer revealed by SNP array analysis. PLoS Comput Biol 2005, 1(6):e65. 149
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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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observed gene expression deregulati
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Raw gene expression profiles from a
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screening approach to gene amplific
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many regions of frequent LOH/AI do
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approach to examining the whole gen
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PTEN expression [44]. Using this pa
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mechanisms at the DNA and RNA level
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In this study, three DNA dimensions
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Figure 3.2. Quantitative and qualit
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Figure 3.3 a Proportion of genes in
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70 Figure 3.5 -log(pvalue) 5.0 4.0
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72 Figure 3.7 Sample: HCC1008 Copy
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Figure 3.8 a b Proportion of random
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16. Chari R, Lockwood WW, Coe BP, C
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50. Giovane A, Pintzas A, Maira SM,
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4.1 Introduction Genetic alteration
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4.2.3 Determining frequent regions
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etween loss and UPD (Figure 4.3). S
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obtained, profiled and used as the
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Figure 4.1. Detection of UPD using
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Figure 4.2. Comparison of frequent
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Figure 4.3 Gain Loss 642 441 7 Figu
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94 Figure 4.4 1 2 3 4 5 6 7 8 9 10
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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 and 116: Chr BPStart BPEnd # of Chr BPStart
Page 117 and 118: Table 4.3. Overlap of oncogenes in
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
Page 133 and 134: developed antibodies and methylated
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
Page 141 and 142: analyzed using the "minet" package
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: 75. Selzer RR, Richmond TA, Pofahl
Page 167 and 168: 145. Takai D, Yagi Y, Wakazono K, O
Page 169 and 170: 179. Kondo M, Suzuki H, Ueda R, Osa
Page 171 and 172: alterations in human prostate cance
Page 173 and 174: 248. Xi L, Feber A, Gupta V, Wu M,
Page 175 and 176: 281. Fernandez-Ranvier GG, Weng J,
Page 177 and 178: Chapter 6: Conclusions 162
Page 179 and 180: can identify nearly three times as
Page 181 and 182: was identified in a small set of sa
Page 183 and 184: will be done at the pathway level a
Page 185 and 186: previously described genetic and ep
Page 187 and 188: 16. Zhang K, Li JB, Gao Y, Egli D,
Page 189 and 190: APPENDIX I: List of publications Th
Page 191 and 192: This publication is described in se
Page 193 and 194: This chapter details the technologi
Page 195 and 196: epigenetic alteration. This led to
Page 197 and 198: This manuscript describes the curre
Page 199 and 200: APPENDIX III: Sources of data Sampl
Page 201 and 202: APPENDIX V: Kaplan-Meier and Oncomi
Page 203 and 204: APPENDIX VI: Summary of Kaplan-Meie
Page 205: University of British Columbia - Br
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