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 âcadherin binding in cell-cell adhesionâ, âextracellular matrix (ECM) organizationâ and âcell-cell adherens junctionsâ. Correspondingly, the downregulated DEGs were enriched in the âoxidation-reduction processâ, âextracellular exosomesâ and âblood microparticlesâ. In regards to the KEGG pathway analysis, the upregulated DEGs were enriched in âECM-receptor interactionsâ, âfocal adhesionsâ and âsmall cell lung cancerâ. The downregulated DEGs were enriched in âmetabolic pathwaysâ, âcomplement and coagulation cascadesâ and âbiosynthesis of antibioticsâ. 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.