Identification of a fatty acid metabolism-related gene signature for prognostic prediction and immune microenvironment characterization in diffuse large B-cell lymphoma

Background: Fatty acid metabolic reprogramming is critically implicated in tumorigenesis and progression. However, the role and prognostic significance of fatty acid metabolism-related genes (FMGs) in diffuse large B-cell lymphoma (DLBCL) remain largely unexplored. Methods: We analyzed transcriptomic data from the Gene Expression Omnibus (GEO) database to identify key prognostic FMGs. Through an integrative machine learning pipeline, we developed a prognostic signature termed the FAMscore. The association of the FAMscore with tumor immunity was assessed. Furthermore, we validated the dysregulation of multiple FMGs using quantitative real-time PCR and single-cell RNA sequencing data. Among these FMGs, we further investigated the role of CPT1A in DLBCL cell proliferation and apoptosis. Results: The FAMscore effectively distinguished between high- and low-risk DLBCL patients and served as an independent prognostic factor. A higher FAMscore was associated with poorer overall survival (OS). A nomogram integrating the cell-of-origin (COO) subtype, the International Prognostic Index (IPI) score, and the FAMscore was developed and demonstrated reliable predictive performance. Tumors in the high-FAMscore group exhibited higher tumor purity and an immune infiltration profile conducive to an immunosuppressive microenvironment. Functional assays revealed that knockdown of CPT1A significantly inhibited DLBCL cell proliferation and induced apoptosis. Conclusions: Our study highlights fatty acid metabolism as a key prognostic indicator and immune regulator in DLBCL. These findings advance the framework for personalized treatment strategies in this malignancy.