Background: Most cholangiocarcinoma (CCA) patients are diagnosed at an advanced stage of disease, and the postoperational recurrence rates are high in those undergoing resection. The lack of satisfying biomarkers for early diagnoses and effective targeting of driver pathways is the leading reason for therapeutic failures. The goal of this study was to find a biomarker for making improved diagnoses with enhanced prognostic capabilities for CCA. Materials and Methods: Our study used bioinformatic analyses of microarray data from the Gene Expression Omnibus (GEO) database and investigated mitotic arrest deficient 2-like protein 1 (MAD2L1) expression in tumor and adjacent non-neoplastic biliary ducts through immunocytochemistry in 42 surgically removed primary CCAs from a single institute. In vitro and in vivo models were used to explore the function of MAD2L1. Results: In total, 297 high probability differentially expressed genes (DEGs) were obtained from overlapping the DEGs from the three individual data sets. Through enrichment assays and protein-protein interaction networks analyses, seven hub genes were identified. MAD2L1 was picked up as a novel biomarker based on hierarchical cluster analyses and Kaplan-Meier survival analyses. MAD2L1 was expressed in cancer tissues but not in the surrounding normal tissue, with 31 (73.81%) of 42 CCAs MAD2L1 positive by immunohistochemistry (IHC). MAD2L1 expression levels were significantly correlated with tumor size, pathological grade, and clinical stage. A Kaplan-Meier survival analysis demonstrated an inverse correlation with MAD2L1 expression. Real-time polymerase chain reaction and immunoblotting results further confirmed the results of IHC and bioinformatic analyses. In vitro and in vivo models demonstrated decreasing MAD2L1 could significantly suppress tumor growth, whereas increasing MAD2L1 could promote tumor growth. Conclusion: MAD2L1 could be used as a biomarker to predict prognosis and potential therapeutic target in CCA. Clinical Trial Registration Number: [2020]KY157-01.
Keywords: MAD2L1; bioinformatics; biomarker; cholangiocarcinoma.