Identification of molecular clusters and a risk prognosis model for diffuse large B-cell lymphoma based on lactate metabolism-related genes

Diffuse large B-cell lymphoma (DLBCL) is a leading cause of morbidity and mortality among lymphomas in adults, with tumor cells undergoing metabolic reprogramming linked to the immune microenvironment. This study explored the relationship between lactate metabolism-related genes (LMRGs), DLBCL prognosis, and immune microenvironment interactions. Publicly available datasets (GSE10846 and GSE87371) were analyzed, with LMRGs identified using Cox regression and LASSO regression. A risk prognosis model comprising five LMRGs was developed, showing that high-risk patients had worse outcomes due to adverse clinical features, aggressive immune microenvironments, and poor treatment responses. A nomogram combining the model with clinical data predicted 1-, 3-, and 5-year survival. Single-cell RNA sequencing indicated that high LMRG risk scores in B cells may promote immunosuppression via the MIF-CD74/CXCR4 pathway. Functional validation revealed that SDHA knockdown reduced DLBCL cell proliferation in U2932 and KIS-1 cell lines. This LMRG-based model serves as a valuable tool for predicting survival, immune landscape, and clinical risk stratification in DLBCL patients, while also highlighting the crucial role of lactate metabolism in DLBCL pathogenesis. Furthermore, these findings underscore the potential of LMRGs risk scores to guide personalized therapies and improve treatment outcomes.