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Plasma proteomic signatures link environmental exposures to lung cancer risk

Journal of Hazardous Materials Advances, 2026

Zhu Y., Wu Y., Tang Y., Chang Q., Lin F., Pan P., Liu H., Guo Y., Zhang Y.

Disease areaApplication areaSample typeProducts
Oncology
Environmental Heath & Toxicology
Pathophysiology
Plasma
Olink Explore 3072/384

Olink Explore 3072/384

Abstract

Mounting evidence indicates that environmental factors such as air pollution, resideal neighborhood greenness, traffic emissions, and socioeconomic conditions may influence lung cancer development, yet the molecular correlates underlying these associations remain incompletely characterized. Proteomics provides an innovative approach to map circulating protein signatures linked to environmental exposures and lung cancer. This prospective cohort study, utilizing data from the UK Biobank, integrated 14 environmental exposures with plasma proteomic data comprising 2923 proteins measured in 42,058 participants. Exposure-related proteins were identified and analyzed for functional pathway enrichment. Proteomic scores were generated using LASSO regression. Cox regression and counterfactual-based mediation analyses were conducted to assess the association with lung cancer risk and explore potential indirect association patterns of both proteomic scores and specific proteins in the exposure-disease pathways. Significant variations were observed in circulating proteins associated with environmental changes. Environment-associated proteins were mainly enriched in pathways related to inflammation and immune regulation. These exposures (PM2.5, PM10, benzene, NDVI, EVI, and TDI) and their related proteomic scores showed significant associations with lung cancer risk. Mediation analyses revealed that proteomic scores explained substantial proportions of the exposure–cancer associations, and several individual proteins, including ANGPT2, CEACAM5, and TNFSF13B, emerged as candidate proteins showing consistent indirect associations across multiple exposures. This large-scale cohort study demonstrates that environmental exposure data are associated with distinct proteomic alterations and that these exposure-related proteomic signatures are associated with lung cancer risk. By mapping pathway-level signals and candidate proteins potentially involved in these associations, our findings provide hypothesis-generating insights into links between environmental exposures and lung cancer risk and offer valuable insights for environmental carcinogenesis research and precision prevention strategies.

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