Dose-Dependent Transcriptomic Responses to Chemopreventive Agents in Rodent Cancer Models

Abstract

The efficacy of cancer chemopreventive agents depends critically on dose, yet the mechanistic relationship between concentration and transcriptomic response remains incompletely characterized. This comprehensive review synthesizes current knowledge on dose-dependent transcriptomic responses to chemopreventive agents in rodent cancer models, examining how RNA-seq-derived gene expression patterns change across concentration ranges. We examine biphasic and hormetic dose-response curves, the concept of transcriptomic points of departure (tPOD), and benchmark dose (BMD) modeling approaches for identifying threshold doses. Particular emphasis is placed on phytochemical agents including sulforaphane, resveratrol, and garlic-derived organosulfur compounds, as well as synthetic chemopreventive agents evaluated in carcinogen-induced models including DMBA/TPA-initiated skin carcinogenesis, 4NQO-induced oral carcinogenesis, and lung adenocarcinoma models. The review discusses how dose-dependent transcriptomic analysis reveals threshold effects for pathway activation, identifies optimal dose ranges for chemoprevention efficacy, and establishes molecular mechanisms underlying dose escalation and dose-limiting toxicity. Critical considerations including sample size requirements, dose spacing strategies, statistical modeling approaches, and mechanistic interpretation of nonlinear dose-response relationships are addressed. Finally, we discuss applications of dose-response transcriptomics to personalized chemoprevention strategies and regulatory safety assessment based on transcriptomic points of departure.