Chapter 2 - University of British Columbia

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Figure 2.2 a Omics Assay Platform b Combinatorial Integration Genome Epigenome Transcriptome DNA Copy Number Allelic Imbalance (LOH) DNA Methylation Histone modification BAC array CGH Single sample Oligo array CGH Multiple samples (one group) Multiple samples (two groups) SNP Microsatellite Arrays markers Segmentation analysis for array CGH to identify regions of gain A and loss Moving average thresholding for affinity based approaches B (MeDIP for DNA methylation, ChIP-on-chip for histone modification states) C Regions of loss of heterozygosity (LOH) D Regions of copy number change and LOH E Regions of copy number neutrality and LOH (e.g. UPD) F Regions of copy number AND methylation alteration ("two" hit) Regions of copy number OR methylation alteration G (compensatory change with same net effect) Epigenetic interplay between DNA methylation and various H modification states of histones Correlation of copy number and gene expression (dataset with I matched copy number and expression profiles) Statistical comparison of samples with copy number change J versus without copy number change (dataset with matched copy number and expression profiles) using Mann Whitney U-test MeDIP - Bisulphite- array CGH based methods Single Platform / Single Assay 35 ChIP-onchip Single ‘omics (Multiple assays) A,B,C,Q,R,S D,E,H A,B,C,L,Q,R,S A,B,C,L,M,Q,R,S D,E,H D,E,H Gene & MicroRNA Expression SAGE Microarrays Combinatorial Integration (Multiple ‘omics) F,G,O,P F,G,I,J,K,O,P F,G,I,J,K,N,O,P Correlation of DNA methylation and gene expression (dataset K with matched DNA methylation and expression profiles) Identify recurrent changes (copy number alterations, common L enrichment patterns [MeDIP, ChIP], regions of LOH) Statistical comparison of patters of recurrent changes between M two groups using Fisher's exact test Two-dimensional two-group comparisons (statistical comparison N of expression profiles of genes in regions of difference identified by Fisher's exact comparison) Identify "And" events between three or more DNA-based O dimensions (copy number, LOH, DNA methylation, histone modification states) Identify "Or" events between three or more DNA-based P dimensions (copy number, LOH, DNA methylation, histone modification states) Q Cancer gene discovery R Lists of genes for systems/function/pathway analysis Linking to public biological databases (PubMed, NCBI Gene, S OMIM, NCBI GEO Profiles, UCSC Genome Browser, Database of Genomic Variants) Figure 2.2. Data structure hierarchy. (a) Data hierarchy describing the relationship between platforms, assays and 'omics disciplines. (b) Functionality map of SIGMA2. List of the various functions and the output from that function that can be performed given the number of samples or sample groups and dimensions. Multiple sample analysis (single group and two group) are microarray platform independent. Functions listed in boxes are in addition to those listed in the box preceding the arrows.
Figure 2.3 numSamples
Page 1 and 2: DEVELOPMENT AND APPLICATION OF AN I
Page 3 and 4: Table of Contents Abstract ........
Page 5 and 6: 3.3.2 Multi-dimensional analysis (M
Page 7 and 8: List of Tables Table 2.1. Features
Page 9 and 10: Figure 5.3. Overlay of chromosomal
Page 11 and 12: RB1 Retinoblastoma 1 RNA Ribonuclei
Page 13 and 14: Dedication To my family. xiii
Page 15 and 16: Chapter 5: Chari R, Thu KL, Wilson
Page 17 and 18: 1.1 Lung cancer Lung cancer has the
Page 19 and 20: expression changes are reactive to
Page 21 and 22: number of different cancer types. M
Page 23 and 24: large number of tumors, that a give
Page 25 and 26: (B) By using an integrative approac
Page 27 and 28: platforms, with one of the latest s
Page 29 and 30: 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: Figure 2.1 R -Segmentation -Statist
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 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
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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
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Figure 4.7 a b 6p25.3 Log2 fold cha
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Chr BPStart BPEnd # of Chr BPStart
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Table 4.3. Overlap of oncogenes in
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Table 4.5. Cell lines and oncogene
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Table 4.7. RefSeq genes in focal re
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4.6 References 1. Bell DW: Our chan
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33. Garnis C, Coe BP, Lam SL, MacAu
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5.1 Introduction In the past decade
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polymorphism (SNP) arrays with over
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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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Chapter 2 - University of British Columbia

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