Abstract
BACKGROUND: N-Nitrosodimethylamine (NDMA), classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC), is ubiquitous in drinking water, processed foods, and certain pharmaceuticals. Emerging epidemiological evidence links NDMA exposure to an increased risk of Bladder Urothelial Carcinoma (BLCA), yet the specific molecular mechanisms driving its role in BLCA initiation and progression remain unclear. OBJECTIVE: This study aimed to elucidate the mechanisms of NDMA-induced BLCA by identifying core targets, validating their expression and immune correlation, and constructing a hypothetical Adverse Outcome Pathway (AOP) framework for NDMA-associated BLCA. METHODS: We integrated network toxicology and machine learning (LASSO, SVM-RFE, Random Forest) to screen core targets from the intersection of NDMA-related and BLCA-related genes obtained from public databases. Their expression levels and diagnostic value were validated using GEO (GSE13507) and TCGA data. Immune infiltration analysis, molecular docking, and 100-ns molecular dynamics simulations were performed to assess tumor microenvironment associations and NDMA-target binding stability, followed by the establishment of an AOP framework. RESULTS: A total of 575 intersecting targets were identified, with five core targets (IL7R, BCL2, CDC20, GADD45A, NRAS) screened via machine learning. These targets exhibited significant dysregulation in BLCA samples (p < 0.01) and demonstrated strong diagnostic performance (AUC: 0.766-0.869). Furthermore, core targets showed distinct correlations with immune cell infiltration. Molecular docking confirmed stable binding of NDMA to all targets, with the highest affinity observed for BCL2, which was further validated by dynamics simulations. Based on these findings, a novel AOP framework was proposed: NDMA exposure → dysregulation of core targets → pathway disruption → immune microenvironment imbalance and epithelial cell dysfunction → BLCA progression. CONCLUSION: NDMA likely promotes BLCA through multi-target and multi-pathway mechanisms. The identified core genes serve as potential diagnostic biomarkers, and the proposed AOP provides a theoretical basis for environmental risk assessment and targeted intervention strategies.