Data from A Model of Intratumor and Interpatient Heterogeneity Explains Clinical Trials of Curative Combination Therapy for Lymphoma

Models of tumor drug response have illuminated important concepts in oncology, but there remains a need for theory that combines intratumor and interpatient heterogeneity to explain patient outcomes, especially for curative treatments. In this study, we present a mathematical model of multidrug therapy that describes both cell-to-cell and patient-to-patient heterogeneity as distributions of drug sensitivity and apply it to simulate curative combination therapies for diffuse large B-cell lymphoma (DLBCL). Simulated trials reproduced progression-free survival and changes in ctDNA observed under standard therapy and accurately predicted success or failure of nine randomized trials of first-line combinations based on drug efficacies in relapsed/refractory DLBCL. Finally, we used the model to explore how drug synergies, biomarkers, and subtype-specific endpoints could improve the chance of success of targeted combination therapies. This study offers a quantitative model of curative drug combinations and suggests that predictive simulations could aid the design of new regimens with curative intent.

A new model of intratumor and interpatient heterogeneity in response to drug combinations explains and predicts the results of clinical trials of curative-intent treatments for DLBCL. This model can be used to understand and inform optimal design of curative drug combinations and clinical trials.

See related commentary by Goldstein et al., p. 153