The paradigm shift: re-evaluating preclinical animal models for colorectal cancer in the precision medicine era

TL;DR

This paper reviews how current animal models for colorectal cancer fail to accurately predict treatment outcomes and highlights the need for better models that reflect human tumor biology and immune responses.

Contribution

The paper provides a critical evaluation of CRC animal models and proposes a framework for developing more immunologically relevant models for precision medicine.

Findings

Current CRC models poorly replicate human tumor immune microenvironment and anatomical features.

Discrepancies in immune cell composition and host immunity limit the predictive accuracy of animal models for immunotherapies.

Advanced models are needed to better mirror human CRC for effective translational research.

Abstract

Colorectal cancer (CRC) remains a major global health burden. While precision therapies like anti-PD-1 and anti-EGFR antibodies show remarkable efficacy, their application is constrained by stringent biomarker requirements, limiting patient benefit. Diverse animal models—including chemically induced, genetically engineered, and transplantation-based systems—have advanced our understanding of CRC pathogenesis but exhibit limited power in predicting therapeutic outcomes for defined patient subgroups. A central challenge is their imperfect recapitulation of key aspects of human CRC biology, specifically anatomical tumor localization, faithful representation of the tumor immune microenvironment (TME), and a frequent lack of rigorous molecular characterization. This gap underscores the urgent need for advanced models that better mirror human disease to support translational research. This review critically evaluates the establishment, advantages, and limitations of prevalent CRC models, focusing on their capacity to replicate key immunological features of human CRC, such as the complex immune landscape and response to immunotherapies. We examine how discrepancies in anatomical site, immune cell composition, and host immunity between animal models and human patients compromise predictive accuracy, particularly for evaluating immune-checkpoint inhibitors (ICIs) in microsatellite-stable (MSS) tumors. By synthesizing these critiques, we aim to provide a framework for developing immunologically relevant models to accelerate the discovery of effective, personalized immunotherapies for CRC.

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