Chapter 2 - University of British Columbia

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APPENDIX IV: MCD strategy and Kaplan-Meier analysis of TUSC3 185
APPENDIX V: Kaplan-Meier and Oncomine expression analysis of frequent MCD genes Symbol (+) (-) Total Survival Associated* 186 **Status in Tumors (p-value) SH3TC1 0 6 6 No - CCNA1 0 5 5 Yes - COL7A1 0 5 5 No - KCTD4 0 5 5 N/A Not tested LMCD1 5 0 5 Yes O3(6.3E-4), O5(3.1E-10) LYAR 0 5 5 Yes U5(3.8E-4), O3(2.6E-4) MTMR9 0 5 5 No U3(1.8E-7) SYT8 0 5 5 N/A Not tested TUSC3 0 5 5 Yes U5(7.4E-5) ASAM 0 4 4 N/A Not tested B3GALNT1 4 0 4 No O3(1.1E-7) COL17A1 0 4 4 No U1(6.8E-5), U3(1.4E-8) ELK3 0 4 4 Yes - FGFR1 0 4 4 Yes U1(2.6E-8),U3(4.2E-6),U4(1.3E-7) KRT17 0 4 4 No U1 (2.3E-11),U2 (1.1E-7), U3(3.9E-7) LCP1 0 4 4 Yes - OSBPL5 0 4 4 N/A Not tested PSD3 0 4 4 Yes - SFXN3 0 4 4 N/A Not tested SH3BGRL3 0 4 4 No O2(2.8E-4) SNRPN 0 4 4 No U3(5.4E-10), U5(2.7E-5) TNFRSF10D 0 4 4 No O5(5.2E-4), U3(9.7E-4) TNS4 0 4 4 N/A Not tested *Survival associated if gene expression was significant associated with survival in at least one of the two datasets tested (based on p < 0.05 using the log rank test). **U=underexpressed between tumor and normal, O=overexpressed between tumor and normal in the particular dataset; The numbers 1-5 indicate the reports from which the data originated, 1= [1], 2= [2], 3=[3], 4=[4], 5=[5], 6=[6]; “-“ indicates gene was either not represented or not statistically differentially expressed based on group-wise analysis. (+) represents two-fold overexpression, copy number gain, hypomethylation and allelic imbalance; (-) represents twofold underexpression, copy number loss, hypermethylation, and LOH in the same sample and the number of samples in our dataset which met this criteria.
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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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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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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 and 194: This chapter details the technologi
Page 195 and 196: epigenetic alteration. This led to
Page 197 and 198: This manuscript describes the curre
Page 199: APPENDIX III: Sources of data Sampl
Page 203 and 204: APPENDIX VI: Summary of Kaplan-Meie
Page 205: University of British Columbia - Br
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