Analysis of differentially expressed mRNAs and the prognosis of cholangiocarcinoma based on TCGA database

Background: The effective evaluation of cholangiocarcinoma (CCA) is challenging due to a lack of accurate screening tools. Consequently, there is an urgent need to screen out effective biomarkers. Bioinformatics analysis on a substantial amount of transcriptomic data to screen biomolecules allows for the verification of histological samples, and can provide a new method for CCA biomolecule screening in diagnosis and prognosis.

Methods: EdgeR model was used to analyze The Cancer Genome Atlas (TCGA)-extracted CCA data set, and to determine the differential expression of mRNAs. Based on this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to perform functional and pathway enrichment analysis. Subsequently, a protein interaction network was also established to identify the key differential node genes. Then, the previously determined differential genes were analyzed to establish a link between these genes and clinical prognosis. Finally, we used tissue samples to realize our results via IHC, Western blot and qRT-PCR.

Results: A total of 5,561 differential mRNAs were screened, including 3,473 upregulated genes and 2,088 downregulated genes. GO and KEGG enrichment analysis showed that the upregulated genes had significantly enriched cell adhesion, concentrated chromosomal motility, and microtubule motility. Downregulated genes were significantly enriched in heterologous metabolism and exosomes. Furthermore, we found upregulated genes were significantly enriched in the cancer pathways and cell cycle. Downregulated genes were enriched in the metabolic pathways and biosynthesis of antibiotics. Ten hub genes were screened out through the protein interaction network; among these, the AURKB and PLK1 genes were closely related to the clinical prognosis of patients. Results of the immunohistochemical staining, Western blot and qRT-PCR all showed that the expression of AURKB and PLK1 in cancer tissues was higher than that in the adjacent tissues, and this difference was statistically significant (P<0.05).

Conclusions: The upregulated genes were significantly enriched in the biological processes of cell division, cell cycle, and related cell components. AURKB and PLK1 play a key role in differentially expressed gene nodes. These genes are closely related to the prognosis of patients and can be used as potential diagnostic tools and prognostic biomarkers.