ArticleDiscover oncology2025
Molecular classification and construction of the risk signature for diffuse large B-cell lymphoma based on vitamin B6 metabolism.
Article in Discover oncology, 2025. 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 AND
objectivesDiffuse large B-cell lymphoma (DLBCL), characterized by high heterogeneity, shows significant differences in treatment responses and prognosis among patients. The underlying mechanisms of vitamin B6 metabolism in DLBCL remain unclear. This study aims to explore vitamin B6 metabolism characteristics, identify novel DLBCL molecular subtypes, and establish a predictive signature for prognosis.
methodsWe first conducted Mendelian randomization (MR) analysis to investigate the genetic association between the vitamin B6 metabolism gene and lymphoma. Subsequently, we utilized weighted gene co-expression network analysis (WGCNA) to identify vitamin B6 metabolism-related genes in DLBCL, combined with non-negative matrix factorization (NMF) to distinguish different molecular subtypes. On this basis, we constructed a risk signature using univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression. External validation of the signature was performed. Finally, we integrated clinical features to establish a nomogram to predict survival probabilities precisely.
resultsThe vitamin B6 metabolism gene PSAT1 may play a protective role in lymphoma. Based on vitamin B6 metabolism features, we successfully identified four distinct DLBCL molecular subtypes. The constructed risk signature effectively assessed patients' risk status and combined clinical features to establish a nomogram. This signature can precisely predict 1-year, 3-year, and 5-year survival probabilities for DLBCL patients, providing essential references for individualized management.
conclusionThis study identified novel DLBCL molecular subtypes based on vitamin B6 metabolism characteristics and established a risk signature with clinical application value. These findings provide a new direction for the precise management of DLBCL patients.
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