Gene expression patterns combined with bioinformatics analysis identify genes associated with cholangiocarcinoma.

To explore the molecular mechanisms of cholangiocarcinoma (CC), microarray technology was used to find biomarkers for early detection and diagnosis. The gene expression profiles from 6 patients with CC and 5 normal controls were downloaded from Gene Expression Omnibus and compared. As a result, 204 differentially co-expressed genes (DCGs) in CC patients compared to normal controls were identified using a computational bioinformatics analysis. These genes were mainly involved in coenzyme metabolic process, peptidase activity and oxidation reduction. A regulatory network was constructed by mapping the DCGs to known regulation data. Four transcription factors, FOXC1, ZIC2, NKX2-2 and GCGR, were hub nodes in the network. In conclusion, this study provides a set of targets useful for future investigations into molecular biomarker studies.