8/8/2019 A tics Meta-Analysis of Differ en Ti Ally Expressed Genes in Colorectal Cancer

1/109

A BIOINFORMATICS META-ANALYSIS OF DIFFERENTIALLY EXPRESSED

GENES IN COLORECTAL CANCER

by

SIMON KIT CHAN

B.Sc. First Class Honours, Cell and Molecular Biology,

Simon Fraser University, 2005

A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

MASTER OF SCIENCE

in

THE FACULTY OF GRADUATE STUDIES

(Bioinformatics)

THE UNIVERSITY OF BRITISH COLUMBIA

December 2007

Simon Kit Chan, 2007

8/8/2019 A tics Meta-Analysis of Differ en Ti Ally Expressed Genes in Colorectal Cancer

2/109

ii

Abstract

BACKGROUND: Elucidation of candidate colorectal cancer biomarkers often

begins by comparing the expression profiles of cancerous and normal tissue by

performing high throughput gene expression profiling. While many such studies

have been performed, the resulting lists of differentially expressed genes tend to

be inconsistent with each other, suggesting that there are some false positives

and negatives. One logical solution to this problem is to determine the

intersection of the lists of differentially expressed genes from independent

studies. It is expected that genes that are biologically relevant to cancer

tumorigenesis will be reported most often, while sporadically reported genes are

due to the inherent biases and limitations of each of the profiling platforms used.

However, the statistical significance of the observed intersection among many

independent studies is usually not considered. PURPOSE: To address these

issues, we developed a computational meta-analysis method that ranked

differentially expressed genes based on the following criteria, which are

presented in order of importance: the amount of intersection among studies, total

tissue sample sizes, and average fold change in expression. We applied this

meta-analysis method to 25 independent colorectal cancer profiling studies that

compared cancer versus normal, adenoma versus normal, and cancer versus

adenoma tissues. RESULTS: We observed that some genes were consistently

reported as differentially expressed with a statistically significant frequency (P