Chapter 2 - University of British Columbia

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expression of chromatin remodelling factors in cervical intraepithelial neoplasia. BMC Genomics, 9(1):64, 1-14. Cervical cancer is a major problem in developing countries. Similar to oral cancer, it is thought to go through a progression of histopathological stages and thus identifying markers at stages of intervention are crucial to the prognoses of patients with this disease. In this publication, a comparison of normal cervical tissue with cervical intraepithelial neoplasia (CIN) was performed to identify genes upregulated in CIN. It was found that genes involved in chromatin remodelling were upregulated in CIN. 22. Shadeo A, Chari R, Vatcher G, Campbell J, Lonergan KM, Matisic J, van NieKerk D, Ehlen T, Miller D, Follen M, Lam WL, MacAulay C. (2007) Comprehensive serial analysis of gene expression of the cervical transcriptome. BMC Genomics, 8(1):142, 1-11. This publication describes the transcriptome of normal cervix tissue using serial analysis of gene expression. Integrative analysis of multiple DNA and RNA dimensions 23. Wilson IM, Vucic EA, Chari R, Zhang Y-A, Starczynowski DT, Lonergan KM, Enfield KSS, Buys TPH, Yee J, Laird-Offringa I, Karsan A, Liu P, You M, Anderson M, MacAulay C, Lam S, Gazdar AF, Lam WL. (2010) EYA4 is a non-small cell lung cancer tumor suppressor located in the susceptibility locus on chromosome 6q. Chromosome arm 6q has been shown to harbor a region associated with lung cancer susceptibility based on the analysis of familial lung cancer datasets. Moreover, this specific region is also frequently lost in sporadic, non-familial lung cancers as well. Hence, many studies have been undertaken to identify the gene(s) in this region which may critical to lung tumorigenesis. In this manuscript, we detail the use of a genetic and epigenetic approach to identify key genes in this region which are frequently deregulated by concerted genetic and 179
epigenetic alteration. This led to the identification of the gene EYA4, which we further demonstrate to have tumor suppressive activity. 24. Soh J, Okumura N, Lockwood WW, Yamamoto H, Shigematsu H, Zhang W, Chari R, Shames D, Tang X, MacAulay C, Varella-Garcia M, Vooder T, Wistuba II, Lam S, Brekken R, Toyooka S, Minna JD, Lam WL, Gazdar AF. (2009) Oncogene mutations, copy number gains and mutant allele specific imbalance (MASI) frequently occur together in tumor cells. PLoS One, 4(10):e7464, 1-13. Somatic mutation of both oncogenes and tumor suppressor genes have been shown to be important in cancer. While tumor suppressor genes typically are recessive and require both alleles to harbor mutation, activating mutations of oncogenes generally only require one of the alleles to be mutated. However, it has been shown that for specific activating mutations, multiple mutated copies can exist. In this study, using some of the most commonly mutated genes in multiple cancer types, the prevalence of this phenomenon was assessed in set of cell lines and tumors representing lung, pancreatic and colorectal cancers. It was found that for the EGFR locus, mutation of the gene is accompanied with copy number increase whereby there is preferential gain of the mutated copy and for KRAS, the event observed is acquired uniparental disomy where the wild type copy is lost and the mutant copy is duplicated. 25. Campbell JM, Lockwood WW, Buys TP, Chari R, Coe BP, Lam S, Lam WL. (2008) Integrative genomic and gene expression analysis of chromosome 7 identified novel oncogene loci in non-small cell lung cancer. Genome, 51(12): 1032–1039. Genomic alteration of chromosome 7 is a frequent event in non-small cell lung cancer. While the most commonly known oncogenes on this chromosome include EGFR, MET and BRAF, there are likely other candidate genes which may have a role in lung tumorigenesis. In this manuscript, utilizing an integrative genetic and gene expression approach, novel oncogene loci are identified. 180
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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
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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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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
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: This chapter details the technologi
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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