Exon expression arrays as a tool to identify new cancer genes.

ABSTRACT:

Background

Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples.

Principal findings

As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes

SUBMITTER: Schutte M 

PROVIDER: S-EPMC2500185 | biostudies-literature | 2007 Aug

REPOSITORIES: biostudies-literature