Integrated analysis of network toxicology, machine learning, and multi-dimensional bioinformatics reveals the toxicological mechanisms of ochratoxin A in gastric carcinogenesis

Gastric cancer (GC) is a multifactorial malignancy closely linked to environmental risk factors. Ochratoxin A (OTA), a widely distributed mycotoxin, has been classified as a probable human carcinogen. This study systematically elucidates the molecular mechanisms underlying OTA-induced gastric carcinogenesis. For the first time, through an integrated approach combining network toxicology, machine learning, and Mendelian randomization analysis, four key pathogenic genes (ESR1, GSK3β, MET, and MMP2) were identified and validated. The research further clarifies how OTA disrupts hormone signaling, metabolic homeostasis, and the tumor immune microenvironment, thereby driving cancer development through multi-pathway synergy. Notably, GSK3β was genetically confirmed for the first time to have a causal relationship with gastric cancer. These gene markers play a central regulatory role in gastric carcinogenesis and demonstrate significant diagnostic potential, providing novel biomarkers and a theoretical foundation for risk prediction and targeted intervention in OTA-associated gastric cancer.