基于多组学孟德尔随机化的胃癌关键血浆蛋白靶标发现与药物预测OA北大核心

Background and Aims:Gastric cancer is a common and highly lethal malignancy of the digestive system.The efficacy of current treatment strategies remains limited,highlighting the urgent need to identify novel therapeutic targets.This study employed a Mendelian randomization(MR)approach to integrate GWAS data with pQTL data,aiming to systematically identify and validate plasma proteins that are causally associated with gastric cancer,thereby providing a theoretical basis for targeted therapy. Methods:A two-sample Mendelian randomization analysis was conducted using GWAS data on gastric cancer and plasma pQTL datasets to infer causal relationships.External independent datasets were used for validation.Multi-dimensional sensitivity analyses-including reverse causality testing,Bayesian colocalization,and phenome-wide scans-were performed to ensure the robustness of the findings.Protein-protein interaction networks were constructed via the STRING database to elucidate the biological pathways of candidate proteins,and the DrugBank database was utilized to predict potential therapeutic agents. Results:A total of 16 plasma proteins were initially identified as causally associated with the risk of gastric cancer.After external validation and sensitivity analyses,ICAM2,IGF1R,LIFR,and MET were confirmed as key candidate targets.Drug database analysis indicated that dalotuzumab(targeting IGF1R)and efalizumab(potentially modulating the ICAM2 pathway)may have therapeutic potential. Conclusion:Through a multi-omics Mendelian randomization framework,this study systematically identified four plasma proteins-ICAM2,IGF1R,LIFR,and MET-that exhibit stable causal associations with gastric cancer.These targets offer novel insights into the molecular pathogenesis of gastric cancer and provide a theoretical foundation for developing targeted drugs and personalized treatment strategies.