Stratification of colorectal cancer into subgroups with different response to therapy was initially guided by descriptive associations between specific biomarkers and treatment outcome. Recently, preclinical models based on propagatable patient-derived tumor samples have yielded an improved understanding of disease biology, which has facilitated the functional validation of correlative information and the discovery of novel response determinants, therapeutic targets, and mechanisms of tumor adaptation and drug resistance. We review the contribution of patient-derived models to advancing colorectal cancer characterization, discuss their influence on clinical decision-making, and highlight emerging challenges in the interpretation and clinical transferability of results obtainable with such approaches. SIGNIFICANCE: Association studies in patients with colorectal cancer have led to the identification of response biomarkers, some of which have been implemented as companion diagnostics for therapeutic decisions. By enabling biological investigation in a clinically relevant experimental context, patient-derived colorectal cancer models have proved useful to examine the causal role of such biomarkers in dictating drug sensitivity and are providing fresh knowledge on new actionable targets, dynamics of tumor evolution and adaptation, and mechanisms of drug resistance.
©2021 American Association for Cancer Research.