Polychlorinated biphenyls (PCBs) are persistent organic pollutants linked to elevated cancer risk, including breast cancer. PCB118, a widely detected congener with reported endocrine-disrupting activity, is frequently found in industrial and environmental samples. However, the molecular mechanisms underlying its carcinogenic potential remain poorly understood. A multidisciplinary strategy integrating network toxicology, molecular docking, and bioinformatics was applied to characterize the predicted toxicological profiles and potential molecular targets of PCB118 in the context of breast cancer. Toxicity predictions using ProTox 3.0 and ADMETlab 3.0 indicated that PCB118 possesses neurotoxic, hepatotoxic, and carcinogenic properties, with a strong association with estrogen receptor–mediated signaling pathways. Network toxicology analysis identified 51 overlapping targets between PCB118 and breast cancer, among which ESR1, STAT3, MAPK3, NFKB1, and PTGS2 were recognized as key hub genes. KEGG and GO enrichment analyses revealed that these targets are primarily involved in chemical carcinogenesis, microRNA regulation in cancer, and oxidative stress–related pathways. Gene expression profiling using GEPIA showed significant upregulation of ESR1 and downregulation of PTGS2 in breast cancer tissues. Kaplan–Meier survival analysis confirmed the prognostic relevance of these genes. Molecular docking further predicted a favorable binding affinity between PCB118 and ESR1, with a docking score of − 7.36 kcal/mol, suggesting a potential direct interaction that warrants further experimental investigation. This study provides a hypothesis-generating computational profile predicting a theoretical interaction between PCB118 and ESR1. These purely computational associations do not establish biological mechanisms and strictly require future in vitro and in vivo experimental validation to determine any potential role in breast cancer risk. The findings offer a hypothesis-generating scientific foundation for toxicity assessment and may inform future preventive or therapeutic strategies targeting PCB-related breast cancer risk.
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Kong et al. (2026) studied this question.
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