Abstract
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a malignant neoplasm characterized by intermediate to high aggressiveness and heterogeneity. Chemokines and their receptors are involved in various antitumor and protumor immune processes in vivo and influence patient prognosis and treatment response. Therefore, investigating the potential associations between chemotactic cytokine-related genes (CCRGs) and prognosis, as well as the immune microenvironment in DLBCL holds significant importance. METHODS: Differentially expressed and prognosis-related CCRGs in DLBCL were extracted from the GEO database. A prognostic risk model was constructed using Lasso-Cox regression analysis, followed by internal and external cohort validation to assess the model's predictive independence. This risk model was then applied to immunological analysis, enrichment analysis, and drug prediction analysis. Single-cell sequencing was employed to investigate the correlation between genes in the prognostic model and immune cell types. RESULTS: We identified 23 prognosis-related CCRGs and revealed two CCRG-associated subtypes exhibiting distinct immune processes. Subsequently, a six-gene prognostic model was established using LASSO-Cox regression analysis. Univariate and multivariate prognostic analyses demonstrated that the risk model serves as an independent prognostic factor, and both the CCRG prognostic model and signature genes showed a significant correlation with the tumor immune microenvironment (TIME). CONCLUSION: The CCRG risk model proposed in this study can accurately and stably predict the prognosis of DLBCL patients and is closely associated with the TIME, providing new targets and theoretical support for DLBCL patients.