Cancer Before Cancer: Measuring the Biological Consequences of the Modern Exposome

Cancer is conventionally defined when malignant transformation can be demonstrated, yet carcinogenesis is increasingly understood as a multistep biological process extending from exposure and tissue response through clonal evolution and, in some individuals, clinically apparent malignancy. The modern exposome provides a framework for considering environmental, endogenous, metabolic, infectious, occupational, and social influences that accumulate and interact across the life course. These influences can converge on chronic inflammation, oxidative stress, immune dysregulation, metabolic dysfunction, genomic instability, and epigenetic remodeling. Importantly, these processes are not specific to cancer and may accompany many chronic diseases. Their relevance to carcinogenesis therefore depends on persistence, tissue context, interaction with inherited and acquired susceptibility, and trajectories that favor clonal selection and malignant progression. This review develops a measurement-centered framework for identifying biological states that may precede clinically detectable cancer. The framework integrates quantitative assessment of tissue physiology, longitudinal biomarkers, genetic and epigenetic information, and external and internal exposure measures. It distinguishes transient physiological variation from persistent biological deviation by emphasizing magnitude, duration, reproducibility, and trajectory rather than isolated abnormal measurements. The proposed approach does not define cancer by a pre-malignant measurement or imply deterministic progression. Instead, it identifies a research pathway in which validated quantitative measurements could characterize biological states, support causal investigation, and permit longitudinal evaluation of preventive interventions before overt malignancy. Translation will require rigorous analytical and clinical validation, causal inference, longitudinal outcome studies, assessment of overdiagnosis and clinical benefit, and demonstration that measurement improves outcomes rather than merely increasing detection.