Chapter 2 - University of British Columbia

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Table 4.8. Genes overexpressed in focal regions of UPD Probe ID Gene Symbol 107 Frequency of Overexpression merck-NM_001508_a_at GPR39 13 merck-AJ270693_at PLEKHA5 12 merck-NM_014331_at SLC7A11 10 merck-NM_001949_at E2F3 10 merck-C17174_at CUL3 9 merck-AA651853_at ARRDC3 7 merck-AF336376_a_at PDGFD 6 merck-CR624190_a_at KIF21A 6 merck-NM_016522_at HNT 5 merck-NM_003854_at IL1RL2 5 merck-NM_000845_at GRM8 5 merck-AY358331_s_at HNT 5 merck-CR625009_at ZNF140 5 merck-X52332_a_at ZNF10 5 merck-AK127693_s_at PLCB1 4 merck-NM_020226_at PRDM8 4
4.6 References 1. Bell DW: Our changing view of the genomic landscape of cancer. J Pathol 2010, 220(2):231-243. 2. Chari R, Thu KL, Wilson IM, Lockwood WW, Lonergan KM, Coe BP, Malloff CA, Gazdar AF, Lam S, Garnis C et al: Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer. Cancer Metastasis Rev 2010. 3. Zhu X, Dunn JM, Goddard AD, Squire JA, Becker A, Phillips RA, Gallie BL: Mechanisms of loss of heterozygosity in retinoblastoma. Cytogenet Cell Genet 1992, 59(4):248-252. 4. Tuna M, Knuutila S, Mills GB: Uniparental disomy in cancer. Trends Mol Med 2009, 15(3):120-128. 5. Li C, Beroukhim R, Weir BA, Winckler W, Garraway LA, Sellers WR, Meyerson M: Major copy proportion analysis of tumor samples using SNP arrays. BMC Bioinformatics 2008, 9:204. 6. Yamamoto G, Nannya Y, Kato M, Sanada M, Levine RL, Kawamata N, Hangaishi A, Kurokawa M, Chiba S, Gilliland DG et al: Highly sensitive method for genomewide detection of allelic composition in nonpaired, primary tumor specimens by use of affymetrix single-nucleotide-polymorphism genotyping microarrays. Am J Hum Genet 2007, 81(1):114-126. 7. Andersen CL, Wiuf C, Kruhoffer M, Korsgaard M, Laurberg S, Orntoft TF: Frequent occurrence of uniparental disomy in colorectal cancer. Carcinogenesis 2007, 28(1):38-48. 8. Darbary HK, Dutt SS, Sait SJ, Nowak NJ, Heinaman RE, Stoler DL, Anderson GR: Uniparentalism in sporadic colorectal cancer is independent of imprint status, and coordinate for chromosomes 14 and 18. Cancer Genet Cytogenet 2009, 189(2):77- 86. 9. Fitzgibbon J, Iqbal S, Davies A, O'Shea D, Carlotti E, Chaplin T, Matthews J, Raghavan M, Norton A, Lister TA et al: Genome-wide detection of recurring sites of uniparental disomy in follicular and transformed follicular lymphoma. Leukemia 2007, 21(7):1514-1520. 10. Kawamata N, Ogawa S, Seeger K, Kirschner-Schwabe R, Huynh T, Chen J, Megrabian N, Harbott J, Zimmermann M, Henze G et al: Molecular allelokaryotyping of relapsed pediatric acute lymphoblastic leukemia. Int J Oncol 2009, 34(6):1603-1612. 11. Gondek LP, Tiu R, O'Keefe CL, Sekeres MA, Theil KS, Maciejewski JP: Chromosomal lesions and uniparental disomy detected by SNP arrays in MDS, MDS/MPD, and MDS-derived AML. Blood 2008, 111(3):1534-1542. 12. Sanada M, Suzuki T, Shih LY, Otsu M, Kato M, Yamazaki S, Tamura A, Honda H, Sakata-Yanagimoto M, Kumano K et al: Gain-of-function of mutated C-CBL tumour suppressor in myeloid neoplasms. Nature 2009, 460(7257):904-908. 13. Tiu RV, Gondek LP, O'Keefe CL, Huh J, Sekeres MA, Elson P, McDevitt MA, Wang XF, Levis MJ, Karp JE et al: New lesions detected by single nucleotide polymorphism array-based chromosomal analysis have important clinical impact in acute myeloid leukemia. J Clin Oncol 2009, 27(31):5219-5226. 14. Teh MT, Blaydon D, Chaplin T, Foot NJ, Skoulakis S, Raghavan M, Harwood CA, Proby CM, Philpott MP, Young BD et al: Genomewide single nucleotide polymorphism microarray mapping in basal cell carcinomas unveils uniparental disomy as a key somatic event. Cancer Res 2005, 65(19):8597-8603. 15. Suzuki M, Kato M, Yuyan C, Takita J, Sanada M, Nannya Y, Yamamoto G, Takahashi A, Ikeda H, Kuwano H et al: Whole-genome profiling of chromosomal aberrations in hepatoblastoma using high-density single-nucleotide polymorphism genotyping microarrays. Cancer Sci 2008, 99(3):564-570. 108
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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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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 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: Table 4.7. RefSeq genes in focal re
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 and 164: 75. Selzer RR, Richmond TA, Pofahl
Page 165 and 166: 111. Melcher R, Al-Taie O, Kudlich
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
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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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