Transcriptomic analysis and identification of prognostic biomarkers in cholangiocarcinoma.

Abstract

Cholangiocarcinoma (CCA) is acknowledged as the second most commonly diagnosed primary liver tumor and is associated with a poor patient prognosis. The present study aimed to explore the biological functions, signaling pathways and potential prognostic biomarkers involved in CCA through transcriptomic analysis. Based on the transcriptomic dataset of CCA from The Cancer Genome Atlas (TCGA), differentially expressed protein-coding genes (DEGs) were identified. Biological function enrichment analysis, including Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, was applied. Through protein-protein interaction (PPI) network analysis, hub genes were identified and further verified using open-access datasets and qRT-PCR. Finally, a survival analysis was conducted. A total of 1,463 DEGs were distinguished, including 267 upregulated genes and 1,196 downregulated genes. For the GO analysis, the upregulated DEGs were enriched in ‘cadherin binding in cell-cell adhesion’, ‘extracellular matrix (ECM) organization’ and ‘cell-cell adherens junctions’. Correspondingly, the downregulated DEGs were enriched in the ‘oxidation-reduction process’, ‘extracellular exosomes’ and ‘blood microparticles’. In regards to the KEGG pathway analysis, the upregulated DEGs were enriched in ‘ECM-receptor interactions’, ‘focal adhesions’ and ‘small cell lung cancer’. The downregulated DEGs were enriched in ‘metabolic pathways’, ‘complement and coagulation cascades’ and ‘biosynthesis of antibiotics’. The PPI network suggested that CDK1 and another 20 genes were hub genes. Furthermore, survival analysis suggested that CDK1, MKI67, TOP2A and PRC1 were significantly associated with patient prognosis. These results enhance the current understanding of CCA development and provide new insight into distinguishing candidate biomarkers for predicting the prognosis of CCA.