Identification of candidate genes for the diagnosis and treatment of cholangiocarcinoma using a bioinformatics approach

Oncol Lett. 2019 Nov;18(5):5459-5467. doi: 10.3892/ol.2019.10904. Epub 2019 Sep 20.

Abstract

Cholangiocarcinoma (CCA) is a biliary epithelial tumor with poor prognosis. As the key genes and signaling pathways underlying the disease have not been fully elucidated, the aim of the present study was to improve the understanding of the molecular mechanisms associated with CCA. The microarray datasets GSE26566 and GSE89749 were downloaded from the Gene Expression Omnibus and differentially expressed genes (DEGs) between CCA and normal bile duct samples were identified. Gene and pathway enrichment analyses were performed, and a protein-protein interaction network was constructed and analyzed. A total of 159 DEGs and 10 hub genes were identified. The functions and pathways of the DEGs were mainly enriched in 'heparin binding', 'serine-type endopeptidase activity', 'calcium ion binding', 'pancreatic secretion', 'fat digestion and absorption' and 'protein digestion and absorption'. Survival analysis revealed that the upregulated expression of carboxypeptidase B1 and Kruppel like factor 4 was significantly associated with lower overall survival rate. In summary, the present study identified DEGs and hub genes associated with CCA, which may serve as potential diagnostic and therapeutic targets for the disease.

Keywords: Kaplan-Meier curves; bioinformatics analysis; cholangiocarcinoma; differentially expressed genes.