Transcriptomic Signatures of Chemoprevention: RNA-seq Insights from Carcinogen-Induced Animal Models

Abstract

Cancer chemoprevention represents a critical strategy for reducing cancer incidence through the prevention, delay, or suppression of tumor development using bioactive agents. High-throughput RNA sequencing (RNA-seq) technology has revolutionized our ability to characterize transcriptomic signatures associated with carcinogen-induced transformation and chemoprevention in animal models. This review synthesizes current knowledge on how RNA-seq-derived transcriptomic profiling from carcinogen-induced animal models reveals molecular mechanisms of chemoprevention, identifies predictive biomarkers, and enables the discovery of novel therapeutic targets. We examine established animal models including the DMBA/TPA mouse skin carcinogenesis model, 4NQO-induced oral carcinogenesis, and benzo(a)pyrene exposure systems, alongside state-of-the-art RNA-seq methodologies for differential gene expression analysis, pathway enrichment, and functional annotation. Particular emphasis is placed on phytochemical chemopreventive agents including sulforaphane, curcumin, and ursolic acid, their mechanisms of action at the transcriptomic level, and the identification of key molecular pathways including NRF2-ARE antioxidant signaling, NF-κB inflammatory pathways, MAPK/ERK cascades, and apoptotic regulatory mechanisms. We discuss advanced computational approaches including weighted gene co-expression network analysis (WGCNA), machine learning classifiers, and single-cell RNA-seq for unraveling tumor microenvironment dynamics. Finally, we address challenges in translating transcriptomic discoveries from animal models to clinical biomarker development, quality control considerations, and future perspectives for precision cancer prevention.