Candidate glioblastoma development gene identification using concordance between copy number abnormalities and gene expression level changes

Abstract

Copy number abnormalities (CNAs) in tumor cells are presumed to affect expression levels of genes located in region of abnormality. To investigate this relationship we have surveyed the losses, gains and amplifications in 30 glioblastomas using array comparative genome hybridization and compared these data with gene expression changes in the same tumors using the Affymetrix U133Plus2.0 oligonucleotide arrays. The two datasets were overlaid using our in-house overlay tool which highlights concordance between CNAs and expression level changes for the same tumors. In this survey we have highlighted genes frequently overexpressed in amplified regions on chromosomes 1, 4, 11, and 12 and have identified novel amplicons on these chromosomes. Deletions of specific regions on chromosomes 9, 10, 11, 14, and 15 have also been correlated with reduced gene expression in the regions of minimal overlap. In addition we describe a novel approach for comparing gene expression levels between tumors based on the presence or absence of chromosome CNAs. This genome wide screen provides an efficient and comprehensive survey of genes which potentially serve as the drivers for the CNAs in GBM.