Glycolysis-Driven Immune Subtypes in the Tumor Microenvironment Determine Clinical Outcomes in Diffuse Large B-Cell Lymphoma

<b>Background:</b> Diffuse large B-cell lymphoma (DLBCL), the most common B-cell non-Hodgkin lymphoma, remains challenging because more than one-third of patients fail to achieve durable remission with frontline therapy; therefore, a systematic and comprehensive understanding of its underlying biology is essential to improve risk stratification and treatment outcomes. <b>Methods:</b> Based on 30 glycolysis-related genes selected from 72 candidates in the MSigDB database, we comprehensively evaluated glycolysis-related modification patterns in 562 DLBCL samples and analyzed their associations with immune cell infiltration and patient prognosis in the tumor microenvironment (TME). In vivo, we identified three immune subtypes in DLBCL mouse models and accessed their correlation with glycolytsis-related patterns and outcomes using histopathological evaluation (H&E) staining, Kaplan-Meier survival analysis, Western blotting, and immunohistochemistry. <b>Results:</b> Four distinct glycolysis modification patterns were identified, which correlated with three immune subtypes: immune-inflamed, immune-desert, and immune-excluded. The immune-inflamed subtype, characterized by prominent immune infiltration, was associated with favorable survival. In contrast, the immune-excluded subtype, defined by stromal activation, did not confer a survival advantage. The immune-desert subtype, marked by a lack of immune infiltration, was linked to poor survival outcomes. Finally, using the DLBCL mouse model, we validated these three immune subtypes and demonstrated their corresponding associations with glycolytic patterns and prognosis. <b>Conclusions:</b> Our work demonstrated that glycolysis-related modification patterns have correlations with the immune cell infiltration within the TME of DLBCL and that distinct glycolytic states are associated with different clinical outcomes. These findings provide a framework for improved prognostic stratification and may inform new therapeutic decision-making in DLBCL.