Identification of novel therapeutic targets and effective anticancer agents for gallbladder cancer by integrating bioinformatics analysis and experimental validation

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Background: Although significant progress has been made in the treatment of biliary tract tumors (BTC), most patients still respond poorly to existing therapies. Therefore, the development of new therapeutic targets and drugs remains an urgent need. Previous studies have extensively applied multi-omics approaches to identify pathogenic targets and drug candidates; however, experimental validation has often been insufficient. Methods: To identify therapeutic targets associated with biliary tract tumors (BTC), we performed Mendelian randomization (MR) analyses integrating cis-eQTL data of druggable genes with BTC GWAS datasets to determine potential therapeutic targets. Subsequently, drug repurposing analyses were conducted to identify candidate compounds corresponding to these druggable gene targets, which were further validated through molecular docking and experimental verification. Single-cell transcriptomic analysis was used to explore the effects of key targets on the tumor microenvironment and tumor progression. Results: MR analysis identified eight genes associated with biliary tract tumors. Among them, NT5E and C4B were prioritized as key regulatory nodes through protein-protein interactions (PPI) network analysis. Drug prediction and molecular docking identified myricetin as a candidate molecule targeting NT5E with strong binding affinity, which was subsequently confirmed in cellular and patient-derived organoid (PDO) models. Single-cell transcriptomic analysis revealed that NT5E was predominantly expressed in C4_CD8-CD8A T cells, which exhibited cytotoxic yet immunosuppressive phenotypes, contributing to immune evasion and poor prognosis. Conclusion: This study identifies potential therapeutic targets for BTC. Drugs designed to target these genes have a higher likelihood of clinical success and are expected to facilitate BTC drug development while reducing associated costs.

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