Identification of phenotype deterministic genes using systemic analysis of transcriptional response

Abstract

Systemic identification of deterministic genes for different phenotypes is a primary application of high-throughput expression profiles. However, gene expression differences cannot be used when the differences between groups are not significant. Therefore, novel methods incorporating features other than expression differences are required. We developed a promising method using transcriptional response as an operational feature, which is quantified as the correlation between expression levels of pathway genes and target genes of the pathway. We applied this method to identify causative genes associated with chemo-sensitivity to tamoxifen and epirubicin. Genes whose transcriptional response was dysregulated only in the drug-resistant patient group were chosen for in vitro validation in human breast cancer cells. Finally, we discovered two genes responsible for tamoxifen sensitivity and three genes associated with epirubicin sensitivity. The method we propose here can be widely applied to identify deterministic genes for different phenotypes with only minor differences in gene expression levels.