Behavior-Guided Molecular Immunodiagnostics: A Translational Framework for Proactive Cancer Prevention in High-Risk Cohorts

Early interception of cancer hinges on marrying precise behavioral risk assessment with cutting-edge molecular and immuno-engineering tools. We outline a translational pipeline that (1) continuously captures lifestyle and environmental exposures via digital health platforms and federated machine-learning models, (2) integrates multi-omic liquid-biopsy signatures—including methylation patterns, exosomal RNAs, and circulating tumor DNA—and (3) deploys multifunctional antibody-based agents (nanobody–fluorophore conjugates, photoimmunotherapeutics, and bispecific T-cell engagers) for focused lesion detection and eradication. Case studies include thermal-risk stratified cohorts consuming hot beverages (esophageal squamous cell carcinoma), aflatoxin-exposed populations (hepatocellular carcinoma), and HPV-infected women (cervical neoplasia). We discuss feasibility in low-resource settings, regulatory considerations for in situ photoimmunotherapy, privacy-preserving analytics, and pathways toward early-phase clinical translation. This framework is shared to disseminate the concept and potentially inspire novel approaches in cancer prevention for high-risk populations.