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Background and objectives <p>Diffuse 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.</p> Methods <p>We 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.</p> Results <p>The vitamin B6 metabolism gene <i>PSAT1</i> 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.</p> Conclusion <p>This 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.</p>

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Molecular classification and construction of the risk signature for diffuse large B-cell lymphoma based on vitamin B6 metabolism

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月11日

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  • Wen Wei,
  • Dao Xin,
  • Huawei Weng,
  • Le Yu,
  • Lingxi Jiang,
  • Yuxin Man

摘要

Background and objectives

Diffuse 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.

Methods

We 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.

Results

The 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.

Conclusion

This 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.