In Silico Promoter Analysis can Predict Genes of Functional Relevance in Cell Proliferation: Validation in a Colon Cancer Model.

Abstract

Specific combinations of transcription-factor binding sites in the promoter regions of genes regulate gene expression, and thus key functional processes in cells. Analysis of such promoter regions in specific functional contexts can be used to delineate novel disease-associated genes based on shared phenotypic properties. The aim of this study was to utilize promoter analysis to predict cell proliferation-associated genes and to test this method in colon cancer cell lines. We used freely-available bioinformatic techniques to identify cell-proliferation-associated genes expressed in colon cancer, extract a shared promoter module, and identify novel genes that also contain this module in the human genome. An EGRF/ETSF promoter module was identified as prevalent in proliferation-associated genes from a colon cancer cDNA library. We detected 30 other genes, from the known promoters of the human genome, which contained this proliferation-associated module. This group included known proliferation-associated genes, such as HERG1 and MCM7, and a number of genes not previously implicated in cell proliferation in cancer, such as TSPAN3, Necdin and APLP2. Suppression of TSPAN3 and APLP2 by siRNA was performed and confirmed by RT-PCR. Inhibition of these genes significantly inhibited cell proliferation in colon cancer cell lines. This study demonstrates that promoter analysis can be used to identify novel cancer-associated genes based on shared functional processes.