A network toxicology approach to elucidate shared oncogenic pathways of Aristolochic acids in prostate, kidney, and bladder cancers.

Extensive clinical and epidemiological studies have shown that Aristolochic acids (AA) exhibit significant nephrotoxicity, mutagenicity, and carcinogenicity. This study aimed to systematically explore the potential molecular mechanisms by which AA induce urinary system tumors using a network toxicology approach.The carcinogenic potential of AA was predicted using ProTox, ADMETlab, and admetSAR. Potential targets of AA were identified via SEA, SwissTargetPrediction, and TargetNet, and then intersected with urinary tract tumor related genes obtained from the GeneCards database to yield common targets. A protein-protein interaction network was constructed, and GO and KEGG enrichment analyses were performed to determine their functional characteristics. LASSO regression models were built using TCGA datasets for prostate cancer, clear cell renal cell carcinoma, and bladder cancer to screen survival related hub genes. Finally, molecular docking of AA with the key targets was conducted using the CB-Dock2 platform. A total of 27 overlapping targets between AA and the three urinary tract tumors were identified. Enrichment analysis indicated that these targets are significantly involved in apoptosis, inflammatory responses, and cancer related pathways such as PI3K-Akt and MAPK. The LASSO regression models exhibited good prognostic performance across all three tumor types, with CASP3 identified as a common and significant core gene. Molecular docking analysis showed that AA can stably bind to the active pocket of CASP3.CASP3 may serve as a common key target in AA-induced urinary tract tumorigenesis. These findings provide novel theoretical insights into the molecular mechanisms by which AA promote the development of urinary system cancers.