Analysis of differentially expressed geExpression of notch signaling pathway recenes in breast cancer : BRCA1- induced gene expression profiles and meta-analysis gene signature
Author(s)
Advisor
Yuluğ, Işık G.Date
2009Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
159
views
views
39
downloads
downloads
Abstract
The aim of the first part of this study was to find out the expression profiles of the
genes, which were selected from the former BRCA1-induced gene list (OVCA1,
OVCA2, ERBIN, RAD21, XRN2, RENT2, SMG1 and MAC30) in normal-matched
primary breast tumors and to correlate the gene expression profiles of selected
candidate genes with BRCA1 and various pathology parameters. Among the target
genes, the expression of ERBIN, SMG1 and RAD21 were found to be highly
correlated with that of BRCA1 both in BRCA1 up- and down-regulated cells and this
result was validated with qRT-PCR expression profiling of the eight genes in 32
normal-matched primary breast tumor samples. These genes were found to be
discriminative between ER(-) and ER(+) tumors as well as grade 1 and grade 3
tumors. Target genes were also analyzed in independent microarray datasets to assess
their predictive power for breast tumor grade, subtype and patient survival. ERBIN,
SMG1 and RAD21 were found to have predictive roles in these datasets.
The aim of the second part of the study was to found appropriate reference genes
(RGs) for accurate quantification of target gene expressions in breast tumor tissues.
The expression patterns of fifteen widely-used endogenous RGs and three candidate
genes that were selected through analysis of two independent microarray datasets
were determined in 23 primary breast tumors and their matched normal tissues using
qRT-PCR. Additionally, 18S rRNA, ACTB, and SDHA were tested using randomly
primed cDNAs from 13 breast tumor pairs to assess the rRNA/mRNA ratio. The
tumors exhibited significantly lower rRNA/mRNA ratio when compared to their normals. Among the eighteen tested endogenous reference genes, ACTB and SDHA
were identified as the most suitable reference genes for the normalization of qRTPCR
data in the analysis of normal-matched tumor breast tissue pairs.
The aim of the third part of this study was to develop a resampling-based metaanalysis
strategy. Two independent microarray datasets that contain normal breast,
invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples
were used for the meta-analysis. The resampling-based meta-analysis has led to the
identification of a highly stable set of genes for classification of normal breast
samples and breast tumors encompassing both the ILC and IDC subtypes. A subset
of this meta-gene list was shown to predict well-established molecular tumor
subtypes, e.g., basal vs luminal or ER+/ER-, with high accuracy and sensitivity based
on class prediction analysis of existing breast cancer microarray datasets. Expression
of selected genes, tested on 10 independent primary IDC samples and matched nontumor
controls by real-time qRT-PCR, supported the meta-analysis results.