An Immune Exhaustion Signature Predicts Prognosis and Identifies diffuse large B cell lymphoma (DLBCL) Patients Who Derive Preferential Benefit from chimeric antigen receptor (CAR)-T cell Therapy

The tumor microenvironment (TME) is a key determinant of prognosis in diffuse large B cell lymphoma (DLBCL). While T-cell exhaustion is implicated in therapeutic failure, its precise molecular hallmarks and utility for predicting response to modern immunotherapies, such as chimeric antigen receptor (CAR)-T cell therapy, remain unclear. We performed an integrative analysis of transcriptomic and clinical data from multiple DLBCL cohorts (TCGA, GSE181063, GSE10846, GSE248835, GSE182434). We used unsupervised clustering, exploratory analysis of single-cell RNA sequencing data, and LASSO-Cox regression to characterize the exhausted TME, construct a prognostic model, and evaluate its predictive value for CAR-T cell therapy. The model's dynamic behavior was assessed in a proof-of-concept longitudinal cohort of patients treated with the T-cell-engaging bispecific antibody glofitamab. We identified a "high-exhaustion" subtype associated with significantly poorer overall survival (OS; log-rank P= 0.016). Based on this, we developed a five-gene Immune Exhaustion-Related Prognostic Score (IERPS) that served as a robust independent predictor of poor OS across multiple cohorts (multivariate HR=1.49, P< 0.001). Critically, in a cohort of 256 relapsed/refractory patients, the IERPS was strongly prognostic for event-free survival (EFS) in the standard-of-care (SOC) arm (HR=2.02, 95% CI: 1.07–3.81, P= 0.029) but lost prognostic significance in the CAR-T arm (HR=0.70, 95% CI: 0.35–1.40, P= 0.314). This significant interaction ( P< 0.0001) suggests that CAR-T cell Therapy may abrogates the poor prognosis associated with a high IERPS. Biologically, exploratory single-cell analysis ( n= 4) defined the high-IERPS state by hallmarks of classical T-cell exhaustion, and a descriptive case study showed the score dynamically tracked clinical response to glofitamab. A state of active T-cell exhaustion and a suppressive TME drives the adverse immune phenotype in DLBCL. Our IERPS model captures this dysfunctional state, acting as a powerful prognostic tool and, more importantly, as a predictive biomarker to identify high-risk patients who appear to overcome their inherently poor prognosis through CAR-T cell therapy. • Single-cell analysis defines the adverse diffuse large B cell lymphoma tumor microenvironment (DLBCL TME) as a state of classical T-cell exhaustion rather than immune quiescence. • A robust five-gene score (Immune Exhaustion-Related Prognostic Score, IERPS) independently predicts poor survival across multiple cohorts. • IERPS is a predictive biomarker for substantial clinical benefit from chimeric antigen receptor (CAR)-T cell therapy. • IERPS dynamically tracks clinical response to the T-cell engager glofitamab.