ME1 Programs Latent Effector Capacity and Grounds a Mathematical Model of Reversible T Cell Exhaustion

Abstract

A central paradox in cancer immunotherapy is that patients harboring apparently exhausted or dysfunctional CD8+ T cells can exhibit rapid and durable responses to immune checkpoint inhibition (ICI). Although such rebound responses do not occur in all ICI-treated patients, resolving this paradox is essential for identifying and therapeutically maximizing reversible T cell exhaustion before clinical benefit is achieved. Here, we identify malic enzyme 1 (ME1) as a key molecular determinant of a latent, epigenetically poised effector CD8+ T cell state that is both necessary and sufficient for responsiveness to ICI. Genetic loss of ME1 abolishes therapeutic efficacy despite intact checkpoint blockade, whereas enforced ME1 expression enables robust antitumor responses even in otherwise ICI-resistant tumor models. Chromatin accessibility profiling, together with bulk and single-cell transcriptomic analyses, demonstrates that ME1 preserves effector readiness by maintaining latent effector capacity as a measurable biological state. These findings also experimentally ground a mechanistically interpretable dynamical model of T cell exhaustion, in which latent effector capacity, E(t), evolves according to a first-order differential equation shaped by activation history and decay. By defining latent effector capacity as a quantifiable, history-dependent state variable, our findings further enable the rational design of AI-driven models to predict patient-specific responsiveness and optimize therapeutic strategies in T cell-based immunotherapy. Together, our results redefine exhaustion as a state of masked potential governed by history-dependent latent effector capacity and provide a unified framework explaining rapid functional rebound, therapeutic heterogeneity, and the boundary between reversible and irreversible T cell exhaustion.