A hybrid multiscale model for predicting CAR-T therapy outcomes in solid tumors

Abstract

Abstract T cell distribution within tumors (“tumor hotness”) critically determines the success of immunotherapy. However, despite numerous strategies to enhance intratumoral T cell accumulation – such as multi-target CAR-Ts and combinatorial approaches – limited mechanistic understanding of T cell–microenvironment interactions has constrained progress. To address this, we developed a mechanistic physiological model of the 3D tumor microenvironment (TME) to evaluate CAR-T performance under environmental fluctuations and across different infusion strategies. The model integrates key vascular (rolling, firm adhesion, endothelial suppression) and interstitial (ECM density, metabolic competition, chemokine sensitivity) barriers. Our simulations reveal that collagen density and metabolic competition are dominant factors in CAR-T efficacy. Enhancing vascular rolling and firm adhesion improves infiltration but remains limited by collagen and metabolism. Endothelial suppression markedly reduces tumor hotness, while its alleviation enhances response. Systemic infusion yields higher tumor hotness than intratumoral delivery, but combined routes or reduced collagen density restore efficacy, even in dense tumors. This mechanistic framework enables rational optimization of CAR-T strategies.