Chapter 2 - University of British Columbia

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While overall therapeutic strategies have provided limited benefit to prolonging patient survival, there has been moderate success in the application of targeted therapeutics. Specifically, pharmacological agents against the epidermal growth factor receptor (EGFR) tyrosine kinase have shown selective efficacy in a subset of lung AC patients [6-12]. Hence, in addition to improving early detection strategies, another main focus of lung cancer research is the identification of novel therapeutic targets. One such approach that can be used to identify targets is through the application of genomic tools to clinical lung cancer specimens. 1.2 Genomic profiling of lung cancer 1.2.1 Gene expression analysis One of the first applications of high throughput genome technologies was to the assessment of messenger RNA (mRNA) levels [13, 14]. While the first, landmark cancer-related studies were done in breast and hematological malignancies [15-17], substantial findings were made in the analysis of lung cancer. Specifically, lung cancer gene expression studies have identified genes differentially expressed in tumors, genes associated with angiogenic potential, genes associated with chemoresistance, expression signatures defining subclasses of lung cancer, expression signatures associated with patient prognosis, and expression signatures from normal bronchial epithelium samples to detect lung cancer [18-34]. In addition, much work has also been done to understand baseline gene expression in non-malignant lung tissue as well its changes with respect to heavy smoke exposure [35-38]. These studies are as important as studies involving lung cancer samples as they provide an important reference level of gene expression to decipher the dysregulated gene expression in tumors. However, from a given analysis of differential expression in tumors, there are typically hundreds, if not thousands, of genes which may show aberrant gene expression in tumors when compared to non-malignant tissue. Moreover, it is likely that a proportion of the genes which are aberrantly expressed are not integral or causal to tumor development as many gene 3
expression changes are reactive to changes in expression of other genes. In addition, using gene expression alone, one cannot discern which changes are causal and which changes are reactive. One approach to assign causality with gene expression changes is to identify alterations at the DNA level such as somatic mutation, changes in gene dosage (DNA copy number), or epigenetic changes such aberrant DNA methylation or histone modification which can explain the observed differential expression. 1.2.2 DNA copy number analysis Alterations in gene dosage, whereby segments of DNA in the genome are either replicated or lost, have shown to be important in lung cancer [39-41]. Typically, these gains and losses of DNA are detected through the comparison of a genome from a tumor sample with a genome that is normal or non-malignant. It is thought that these increases or decreases in amounts of specific gene sequence could allow for increased or decreased expression of that gene. Technological advances have allowed for the high throughput assessment of DNA copy number changes in the cancer genome namely through microarray comparative genomic hybridization (CGH) [42, 43]. Briefly, this technology capitalizes on differential fluorescence labelling where DNA from the tumor sample and DNA from the normal sample, each labelled with different fluorescent dyes, are hybridized together on the same chip and differences in fluorescent intensities are measured. Moreover, array CGH profiling of both lung cancer cell lines and tumors have identified areas of the genome which are frequently gained or lost [44-52]. Specifically, these areas of copy number alteration have targeted known oncogenes such as MYC, EGFR, MDM2, TERT, and tumor suppressor genes such as CDKN2A, TP53 and RB1. However, these alterations typically do not occur in 100% of lung tumors (e.g. the EGFR locus is gained/amplified in 10-20% of cases). In addition, the amplification and deletion events typically encompass multiple genes and as such, more often than not, only a subset of those genes will have a downstream consequence at the gene expression level. Hence, integration of 4
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: 1.1 Lung cancer Lung cancer has the
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 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
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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
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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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