From Bench to Biomarkers: RNA-seq-Driven Discovery of Chemoprevention Biomarkers in Animal Models

Abstract

The successful clinical development of cancer chemopreventive agents critically depends on mechanistic understanding and accompanying pharmacodynamic (PD) biomarkers providing early readouts of biological activity in target tissues and circulation. RNA sequencing (RNA-seq) has revolutionized biomarker discovery in preclinical cancer chemoprevention models, enabling unbiased transcriptomic analysis identifying mechanism-informed molecular signatures substantially more sensitive than traditional phenotypic endpoints. This comprehensive review synthesizes knowledge on RNA-seq-driven biomarker discovery in animal models for cancer prevention, emphasizing translational validation strategies bridging bench to clinic. We examine cross-species conservation of transcriptomic signatures derived from rodent chemoprevention models to human disease, discuss practical validation methodologies including quantitative PCR (qPCR), immunohistochemistry (IHC), and emerging liquid biopsy approaches, and address critical challenges in establishing clinical relevance of preclinically discovered biomarkers. Specific emphasis is placed on tissue versus circulating biomarkers, temporal dynamics of biomarker changes during prevention interventions, context-dependent biomarker effectiveness, and integration of tumor microenvironment factors influencing biomarker interpretation. Case studies demonstrate successful biomarker translation including withaferin A-induced p21 expression, oral squamous cell carcinoma transcriptional signatures predicting metastatic risk, and circulating nucleic acid biomarkers for non-invasive cancer monitoring. The review discusses FDA biomarker qualification processes, window-of-opportunity clinical trial designs leveraging preclinical insights, and emerging machine learning approaches for biomarker interpretation and patient stratification in prevention trials.