Baseline immune state and T-cell clonal kinetics are associated with durable response to CAR-T therapy in large B-cell lymphoma

• A lower circulating lymphocyte-to-monocyte ratio and proportion of B cells at apheresis predict a reduced likelihood of response to CAR-T.

• On exploratory analysis, axicabtagene ciloleucel products enriched for CD8 T effector memory cells were associated with durable response.

Engineered cellular therapy with CD19-targeting chimeric antigen receptor T cells (CAR-Ts) has revolutionized outcomes for patients with relapsed/refractory large B-cell lymphoma (LBCL), but the cellular and molecular features associated with response remain largely unresolved. We analyzed serial peripheral blood samples ranging from the day of apheresis (day –28/baseline) to 28 days after CAR-T infusion from 50 patients with LBCL treated with axicabtagene ciloleucel by integrating single-cell RNA and T-cell receptor sequencing, flow cytometry, and mass cytometry to characterize features associated with response to CAR-T. Pretreatment patient characteristics associated with response included the presence of B cells and increased absolute lymphocyte count to absolute monocyte count ratio (ALC/AMC). Infusion products from responders were enriched for clonally expanded, highly activated CD8⁺ T cells. We expanded these observations to 99 patients from the ZUMA-1 cohort and identified a subset of patients with elevated baseline B cells, 80% of whom were complete responders. We integrated B-cell proportion ≥0.5% and ALC/AMC ≥1.2 into a 2-factor predictive model and applied this model to the ZUMA-1 cohort. Estimated progression-free survival at 1 year in patients meeting 1 or both criteria was 65% vs 31% for patients meeting neither criterion. Our results suggest that patients’ immunologic state at baseline affects the likelihood of response to CAR-T through both modulation of the T-cell apheresis product composition and promoting a more favorable circulating immune compartment before therapy. These baseline immunologic features, measured readily in the clinical setting before CAR-T, can be applied to predict response to therapy.