Aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma

This study aimed to explore aberrantly methylated-differentially expressed genes and related pathways in cholangiocarcinoma (CCA). The mRNA expression data (GSE26566) and methylation profiling data (GSE44965) were collected from the Gene Expression Omnibus (GEO) Datasets. Differentially expressed genes and differentially methylated genes were identified using GEO2R. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using clusterprofiler in R. MCODE clustering tool was used to screen modules of the protein-protein interaction network in Cytoscape. Related pathways of hub gene by using gene set enrichment analysis. Eighty-one hypermethylated, lowly expressed genes (Hyper-LGs) and 76 hypomethylated, highly expressed genes (Hypo-HGs) were identified in this study. Hyper-LGs were enriched in ion channel binding and transcription factor activity, which was associated with Mineral absorption and Cell adhesion molecules. Hypo-HGs were enriched in cysteine-type endopeptidase activity, which was associated with Sphingolipid signaling pathway and T cell receptor signaling pathway. Based on protein-protein interaction networks, MYC and VWF were identified as hub genes for Hyper-LGs, and no hub genes for Hypo-HGs. This study found methylated-differentially expressed genes and signaling pathways that are connected with the CCA by using a series of bioinformatics databases and tools. MYC and VWF act as hub genes of CCA, which can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of CCA.

Automated summary

This study identified aberrantly methylated-differentially expressed genes and related pathways involved in cholangiocarcinoma (CCA). The analysis of mRNA expression and methylation profiling data revealed a number of genes that showed differential expression and methylation in CCA. Functional enrichment analysis and protein-protein interaction network analysis identified several pathways and hub genes associated with these genes. The findings of this study provide potential biomarkers for the accurate diagnosis and treatment of CCA.