The carcinogenic mechanism of per- and polyfluoroalkyl substances on clear cell renal cell carcinoma: a combined study of network toxicology and virtual drug screening.

Per- and polyfluoroalkyl substances (PFAS) have been implicated in various adverse health effects, but their association with clear cell renal cell carcinoma (ccRCC) - a prevalent and aggressive form of kidney cancer often diagnosed at advanced stages - remains unclear. This study employs an integrative computational approach combining network toxicology, machine learning-based prognostic modeling, and virtual drug screening to elucidate the potential mechanistic links between PFAS exposure and ccRCC pathogenesis. Network toxicology analysis identified critical intersection genes, while machine learning evaluation of The Cancer Genome Atlas (TCGA) database revealed key prognostic biomarkers. Furthermore, virtual screening identified several promising therapeutic candidates, including Ecteinascidin, Avodart, and Nilotinib, which demonstrated high binding affinity to pivotal molecular targets such as AIM2, HK3, ATP1A1, and ZAP70. Our findings suggest a potential link/role of PFAS in ccRCC development via dysregulation of specific gene pathways, and the identified compounds could serve as potential therapeutic agents. This study provides novel insights into the carcinogenic mechanisms of PFAS in ccRCC and proposes new avenues for targeted therapy. However, further experimental and clinical validation is necessary to confirm these findings and translate them into improved patient outcomes, while also addressing broader environmental health concerns related to PFAS exposure.