Identification of therapeutic targets and prognostic biomarkers in cholangiocarcinoma via WGCNA

BACKGROUND: Cholangiocarcinoma (CCA) is a highly aggressive malignant tumor for which limited treatment methods and prognostic signatures are available. This study aims to identify potential therapeutic targets and prognostic biomarkers for CCA. METHODS: Based on differentially expressed genes (DEGs) identified from The Cancer Genome Atlas (TCGA) data, our study identified key gene modules correlated with CCA patient survival by weighted gene coexpression network analysis (WGCNA). Cox regression analysis identified survival-related genes in the key gene modules. The biological properties of the survival-related genes were evaluated by CCK-8 and transwell assays. Then, these genes were used to construct a prognostic signature that was internally and externally validated. Additionally, by combining clinical characteristics with the gene−based prognostic signature, a nomogram for survival prediction was built. RESULTS: WGCNA divided the 1531 DEGs into four gene modules, and the yellow gene module was significantly associated with overall survival (OS) and histologic neoplasm grade. Our study identified the lncRNA AGAP2−AS1 and a novel gene, GOLGA7B, that are closely related to survival. GOLGA7B downregulation promoted the invasion, migration and proliferation of CCA cells, but AGAP2−AS1 had the opposite effect. AGAP2−AS1 and GOLGA7B were integrated into a gene−based prognostic signature, and both internal and external validation studies confirmed that this two-gene prognostic signature and nomogram could accurately predict CCA patient prognosis. CONCLUSION: AGAP2−AS1 and GOLGA7B are potential therapeutic targets and prognostic biomarkers for CCA.