A model of intra-tumor and inter-patient heterogeneity explains clinical trials of curative combination therapy for lymphoma.

Abstract

Models of tumor drug response have illuminated important concepts in oncology, but there remains a need for theory that combines intra-tumor and inter-patient heterogeneity to explain patient outcomes, especially for curative treatments. We present a mathematical model of multi-drug 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 circulating tumor DNA observed under standard therapy, and accurately predicted success or failure of nine randomized trials of first-line combinations based on drugs' 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.