Experimental models of chemical carcinogenesis: bridging toxicology and preclinical pharmacology

Those experimental animals that tend to develop primary malignancies as a result of direct exposures to synthetic cancer agents can very well represent early stages of human cancers as compared to transplanted as well as genetically engineered tumor models. Generally, malignant growth resulting due to cancer agents tends to undergo three phases: initiation, promotion, as well as progression. On the basis of genetic alteration, agents can be divided into genotoxgents as well as non-genotoxgents. Carcinogens that tend to be complete, incomplete, as well as specified towards a target organ are classified into the other categories. These agents can be found through environmental pollutants, meat products, food additives, as well as anticancer agents. The advantages associated with the primary models created in animals by using chemicals include relevance to human clinical models, ease of production, and efficiency. However, it is difficult to track these tumors in small animals without damaging their bodies. As in human models, they grow randomly concerning site, timing, and number in animal models too. Non-invasive application of magnetic resonance imaging techniques has however shown promise in the diagnosis and follow-up of these models of cancer. This is because there are a number of advantages associated with the use of the MRI technology, among them being that this technology does not carry the hazards of ionizing radiation. This review evaluates the unique translational utility of chemically induced primary cancer models, which, unlike traditional xenografts, allow for the study of the entire carcinogenic spectrum—from initiation to progression. The aim of this work is to highlight the novelty of these models in bridging the gap between toxicology and clinical pharmacology, specifically their role in validating non-invasive imaging biomarkers and screening chemopreventive agents—such as Rapamycin and Resveratrol—currently under clinical investigation. By integrating these models with advanced MRI techniques, researchers can achieve more accurate preclinical staging and treatment monitoring. Ultimately, we argue that these models are essential for the development of targeted therapies and diagnostic agents that more faithfully replicate the sporadic nature of human clinical oncology.