Toward Personalized Prevention of Environmentally Induced Cancers: A Conceptual Model Coupling Exposure Biomarkers with Individual Susceptibility

Abstract

Population-average exposure guidance protects communities but does not explain why people with comparable external exposures experience different internal doses, biological damage, and disease risk. This conceptual study develops a personalized-prevention framework for environmentally induced cancers. The framework integrates three input domains: congener-resolved exposure and internal dose; biological response, including oxidative-stress and DNA-damage markers; and individual susceptibility, including metabolic, repair, epigenetic, nutritional, and behavioral modifiers. An interpretable inference layer converts these inputs into a calibrated risk estimate with explicit uncertainty, an attribution of modifiable and non-modifiable drivers, and a feasibility-weighted ranking of preventive actions. Framework development followed a requirements-first synthesis that linked every construct to an observable measure, a defined prevention decision, an ethical constraint, and a falsifiable validation criterion. Translation is organized across research-cohort validation, clinical evaluation, and public-health prioritization. Advancement requires external calibration, stable attribution, subgroup performance, decision benefit, and evidence that recommendations reduce exposure or biological harm without widening disparities. The framework treats privacy, consent, non-discrimination, source-reduction primacy, fairness auditing, and community governance as design requirements. It does not propose clinical thresholds or claim current readiness for routine individual prediction. Its contribution is a testable architecture for connecting exposure science, susceptibility, and prevention while preserving uncertainty and accountability. Comparative prospective studies should determine whether the integrated model improves calibration, net benefit, and equitable risk reduction beyond exposure-only baselines and standard population guidance.