Cholangiocarcinoma-associated genes identified by integrative analysis of gene expression data

Cholangiocarcinoma (CCA) is characterized by delayed diagnosis and poor survival rate. Research efforts have focused on novel diagnostic technologies for this type of cancer. Transcriptomic microarray technology is a useful research strategy for investigating the molecular properties of CCA. The objective of the present study was to identify candidate biomarkers with high potential for clinical application in CCA using a meta-analysis-based approach. Gene expression profiles of CCA were downloaded from the Gene Expression Omnibus database for integrated analysis. All differentially expressed genes (DEGs) were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Protein-protein interaction (PPI) networks were further constructed, hub proteins were identified and functional modules were extracted. Following integrated analysis of the seven eligible datasets (428 cases and 46 controls), a set of 1,080 DEGs was identified, including 710 upregulated and 370 downregulated genes. Functional enrichment analysis demonstrated that ‘chromosome organization’ was a significantly enriched GO term in the biological process category. ‘DNA replication’, ‘influenza A’, and ‘lysosome’ were the top three significantly enriched KEGG pathways. Furthermore, PPI network analysis indicated that the significant hub proteins were histone deacetylase 1, cullin-associated NEDD8-dissociated protein 1, ubiquitin D, early growth response protein 1 and glycogen synthase kinase 3β. The majority of these proteins are involved in CCA. These results provided a set of targets that may help researchers to clarify further the underlying mechanisms of CCA tumorigenesis.