Modeling Combination Therapies and T Cell Exhaustion Dynamics in the Tumor Under Immune Checkpoint Blockade.

Abstract

Chronic antigen exposure in the tumor microenvironment drives CD $8^{+}$ T cell exhaustion, marked by increased inhibitory receptors and diminished effector functions. Immune checkpoint blockade seeks to prevent or reverse exhaustion, but its success relies on the pre-existing state of tumor-infiltrating T cells. To investigate this, we developed a mathematical model examining: (1) how T cell exhaustion disrupts tumor-immune equilibrium, (2) anti-PD-L1 efficacy across exhaustion states, and (3) efficacy of next-generation therapies (e.g., IFN $\alpha$ -anti-PD-L1, PD1-IL2v). Stability analysis and simulations reveal that tumor PD-L1 expression critically influences immune dynamics, particularly the bistability of tumor-free and tumorous states. High PD-1 expression and exhaustion rates correlate with growth of tumor and impaired expansion of less-exhausted CD $8^{+}$ T cells. While anti-PD-L1 efficacy depends on baseline exhaustion, severe exhaustion enables immune escape. Next-generation therapies enhancing cytotoxicity and sustaining less-exhausted T cell populations show improved tumor control, suggesting combination strategies may overcome resistance.