ArticleFrontiers in immunology2026
A palmitoylation-related signature predicts prognosis and immune microenvironment features in diffuse large B-cell lymphoma.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma and remains highly heterogeneous in prognosis. Palmitoylation, an important post-translational modification, has been implicated in tumor biology, but its role in DLBCL, particularly in relation to the immune microenvironment, remains unclear. Methods: Transcriptomic and clinical data from 706 patients with DLBCL were obtained from the Gene Expression Omnibus database. Prognosis-associated palmitoylation-related genes were identified by differential expression and univariate Cox regression analyses. An optimal prognostic model was developed by comparing 101 machine learning algorithm combinations and was further integrated with clinical variables to construct a nomogram. The tumor immune microenvironment was evaluated using immune infiltration, immune function, immune checkpoint, and Tumor Immune Dysfunction and Exclusion analyses. Weighted gene co-expression network analysis (WGCNA) and Mendelian randomization (MR) were performed to identify key genes, followed by experimental validation. Results: A 33-gene palmitoylation-related signature (PRS) was established and evaluated across multiple cohorts. PRS was an independent prognostic factor of DLBCL and showed consistent prognostic performance across datasets. Low-risk patients showed higher immune cell infiltration and more active immune function, whereas high-risk patients showed a greater predicted potential to respond to immune checkpoint inhibitor therapy. A nomogram integrating PRS with clinical characteristics also showed favorable predictive accuracy. In addition, two palmitoylation-related molecular subtypes with distinct transcriptomic features, survival outcomes, and immune microenvironment characteristics were identified in DLBCL. Conclusion: The PRS captures prognostic heterogeneity and distinct immune microenvironment features in DLBCL. PRS may provide a useful tool for risk stratification, and
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