A comprehensive transcriptomic landscape of cholangiocarcinoma based on bioinformatics analysis from large cohort of patients

• Main Authors: Hongguang Li, Lingxin Qu, Haibin Zhang, Jun Liu, Xiaolu Zhang
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-07-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-021-93250-4

Abstract Cholangiocarcinoma (CCA) is a group of malignancies emerging in the biliary tree and is associated with a poor patient prognosis. Although the anatomical location is the only worldwide accepted classification basis, it still has bias. The current study integrates the whole-genome expression data from several big cohorts in the literature, to screen and provide a comprehensive bioinformatic analysis, in order to better classify molecular subtypes and explore an underlying cluster mechanism related to anatomy and geographical regions. Differentially expressed protein-coding genes (DEGs) were identified for CCA as well as subtypes. Biological function enrichment analysis—Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis—was applied and identified different DEGs enriched signaling pathways in CCA subtypes. A co-expression network was presented by Weighted gene co-expression network analysis package and modules related to specific phenotypes were identified. Combined with DEGs, hub genes in the given module were demonstrated through protein–protein interaction network analysis. Finally, DEGs which significantly related to patient overall survival and disease-free survival time were selected, including ARHGAP21, SCP2, UBIAD1, TJP2, RAP1A and HDAC9.