Chapter 2 - University of British Columbia

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67 Figure 3.2 a Hypo AI CNG CNG Or Hypo Or AI Hyper LOH CNL CNL Or Hyper Or LOH b GNAS Gene Expression DNA Copy Number DNA Methylation Allelic Status CASP1 Gene Expression DNA Copy Number DNA Methylation Allelic Status HCC38 HCC1008 HCC1143 HCC1395 HCC1599 HCC1937 HCC2218 BT474 0.197 0.266 0.176 0.134 0.203 0.171 0.144 0.194 0.180 0.319 0.325 0.325 0.337 0.215 0.421 0.132 0.271 0.122 0.708 0.401 0.372 0.644 0.440 0.464 0.321 0.458 0.500 0.821 0.686 0.655 0.757 0.612 0.743 0.435 0.679 0.629 0.103 0.062 0.126 0.236 0.145 0.161 0.183 0.172 0.166 0.425 0.512 0.516 0.523 0.316 0.569 0.197 0.348 0.226 0.367 0.584 0.573 0.499 0.408 0.473 0.203 0.549 0.419 0.522 0.705 0.790 0.702 0.562 0.747 0.363 0.721 0.558 HCC38 HCC1008 HCC1143 HCC1395 HCC1599 HCC1937 HCC2218 BT474 MCF7 MCF7 0 0.2 0.4 0.6 0.8 Proportion of Overexpression Explained 0 0.2 0.4 0.6 0.8 Proportion of Underexpression Explained Legend: GE: Gene Expression: Over Under CN: DNA Copy Number: Gain Loss L: Allelic Status: LOH M: DNA Methylation: Hypo Hyper
Figure 3.3 a Proportion of genes in random simulations b 0.30 0.25 0.20 0.15 0.10 0.05 CN Or AI/LOH Or Meth CN 0 Meth AI/LOH 0 1 2 3 4 5 6 7 8 9 Disruption frequency 0 200 400 600 800 1000 1200 # of genes at 6/9 cut-o� Simulated Data Experimental Data 1400 Figure 3.3. Determination and application of a disruption frequency threshold. (a) Results of the analyses of ten simulated datasets. Aggregating the results of the simulated analyses, the proportion of random simulations at the observed frequency thresholds are shown. From these analysis, approximately 2% of the simulations were ≥ 6/9. (b) Using a frequency cut-off of 6/9, the number of genes disrupted at that frequency using a single or combination of DNA dimensions. With a single dimension alone, we can maximally identify 437 genes which are differentially expressed and exhibit a concerted change at the DNA level in a minimum of 6/9 samples. However, using all three dimensions, we find that 1162 genes are in fact differentially expressed and contain at least one concerted change in one of the DNA dimensions. This represents over a two-fold increase in the number of genes identified. 68
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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
Page 31 and 32: quantitative PCR experiments as wel
Page 33 and 34: 1.13 References 1. Jemal A, Siegel
Page 35 and 36: 33. Garber ME, Troyanskaya OG, Schl
Page 37 and 38: 71. Shivapurkar N, Gazdar AF: DNA M
Page 39 and 40: Chapter 2: SIGMA 2 : A system for t
Page 41 and 42: Here, we present SIGMA 2 , a novel
Page 43 and 44: datasets. To utilize this, the user
Page 45 and 46: 2.3.7 Analysis of data from multipl
Page 47 and 48: expression (Figure 2.8). ERBB2 has
Page 49 and 50: Figure 2.1 R -Segmentation -Statist
Page 51 and 52: Figure 2.3 numSamples
Page 53 and 54: Figure 2.5. Consensus calling and h
Page 55 and 56: Figure 2.6 HCC2218 HCC2218 HCC2218B
Page 57 and 58: Figure 2.8. Multi-dimensional persp
Page 59 and 60: Table 2.1. Features required for in
Page 61 and 62: 2.6 References 1. Garnis C, Buys TP
Page 63 and 64: Chapter 3: An integrative multi-dim
Page 65 and 66: observed gene expression deregulati
Page 67 and 68: Raw gene expression profiles from a
Page 69 and 70: screening approach to gene amplific
Page 71 and 72: many regions of frequent LOH/AI do
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: Figure 3.2. Quantitative and qualit
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 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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developed antibodies and methylated
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Histone modification states. While
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metastasis [226]. High throughput a
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Implications on sample size require
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analyzed using the "minet" package
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expression. The next challenge is t
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Figure 5.2 # of copies Total copy n
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Figure 5.4. Integration of copy num
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Figure 5.5. Integration of copy num
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Figure 5.6 SHC1 GRB2 SOS2 RRAS ER R
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Figure 5.8 a Log2 Fold Change (T vs
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Figure 5.10 (a) (b) Figure 5.10. Au
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Table 5.2. List of genomic resource
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5.5 References 1. Pinkel D, Segrave
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37. Oliphant A, Barker DL, Stuelpna
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75. Selzer RR, Richmond TA, Pofahl
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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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