Computational study links PCB118 to estrogen receptor ESR1 in breast cancer

A new computational study published in BMC Pharmacology and Toxicology predicts a theoretical association between the environmental pollutant PCB118 and the estrogen receptor gene ESR1 in breast cancer. The work, released as an open access research article on 23 October 2026, relies entirely on network toxicology, molecular docking and bioinformatics, and its authors are explicit that the findings are hypothesis-generating rather than proof of a biological mechanism.

PCB118 is a polychlorinated biphenyl congener, a member of a class of persistent organic pollutants that have been linked to elevated cancer risk, including breast cancer. The congener is widely detected in industrial and environmental samples and has reported endocrine-disrupting activity. According to the study’s background, however, the molecular mechanisms underlying its carcinogenic potential remain poorly understood, which motivated the team to build a purely computational profile of its possible targets.

The researchers applied a multidisciplinary strategy combining network toxicology, molecular docking and bioinformatics to characterize predicted toxicological profiles and potential molecular targets of PCB118 in the context of breast cancer. Toxicity predictions using the tools 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 these, five genes were recognized as key hubs: ESR1, STAT3, MAPK3, NFKB1 and PTGS2. ESR1 encodes the estrogen receptor alpha, a protein long central to the biology of many breast tumors, which is why a predicted interaction between a persistent pollutant and this receptor draws attention.

Enrichment analyses using KEGG and GO revealed that the identified targets are primarily involved in chemical carcinogenesis, microRNA regulation in cancer, and oxidative stress–related pathways. These pathway-level results are computational annotations of the shared gene set, not measurements of biological effects in cells or patients, and the authors frame them accordingly.

Gene expression profiling using the GEPIA platform showed significant upregulation of ESR1 and downregulation of PTGS2 in breast cancer tissues compared with non-cancerous tissue. Kaplan–Meier survival analysis confirmed the prognostic relevance of these genes, meaning their expression levels correlate with patient outcomes in the datasets examined. Such associations describe patterns in existing data and do not by themselves establish causal roles for PCB118.

The most striking technical result came from molecular docking, a method that computationally models how a small molecule fits into a protein’s binding site. The docking of PCB118 against ESR1 predicted a favorable binding affinity, with a docking score of −7.36 kcal/mol. The authors suggest this indicates a potential direct interaction between the pollutant and the estrogen receptor, but they stress that the prediction warrants further experimental investigation before any conclusion can be drawn.

The study’s conclusions are carefully bounded. The authors state that the work provides a hypothesis-generating computational profile predicting a theoretical interaction between PCB118 and ESR1, and that these purely computational associations do not establish biological mechanisms. They write that the findings strictly require future in vitro and in vivo experimental validation to determine any potential role in breast cancer risk. The team also notes that the results may offer a scientific foundation for toxicity assessment and could inform future preventive or therapeutic strategies targeting PCB-related breast cancer risk, though such strategies remain speculative at this stage.

For readers, the practical takeaway is about the state of the evidence rather than any immediate health guidance. The study does not measure PCB118 exposure in patients, does not test the compound in laboratory models, and does not demonstrate that PCB118 causes or worsens breast cancer. What it does deliver is a ranked set of candidate targets and pathways, anchored by a predicted PCB118–ESR1 interaction, that experimental laboratories can now test directly in cell and animal models. Until those experiments are done, the link between PCB118 and ESR1 remains a computational prediction, published openly so that other researchers can scrutinize, replicate or refute it.

Subject of Research: Computational prediction of a PCB118–ESR1 association in breast cancer

Article Title: Integrative network toxicology and molecular docking predict a theoretical association between PCB118 and ESR1 in breast cancer

Article References: Kong, W., Hui, X., Shao, Z., Wang, K., Liu, Q., Wu, Y., Li, X., Zhang, X., Yang, J., Yang, K., Niu, J., & Lu, Y. (2026). Integrative network toxicology and molecular docking predict a theoretical association between PCB118 and ESR1 in breast cancer. BMC Pharmacology and Toxicology. https://doi.org/10.1186/s40360-026-01232-x

Image Credits: AI Generated

DOI: 10.1186/s40360-026-01232-x

Keywords: PCB118, ESR1, breast cancer, network toxicology, molecular docking, endocrine disruption, persistent organic pollutants, bioinformatics, ProTox 3.0, GEPIA, Kaplan-Meier analysis, BMC Pharmacology and Toxicology