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September 10, 2025BMC ImmunologyOpen Access

Exploration of biomarkers for predicting the prognosis of patients with diffuse large B-cell lymphoma by machine-learning analysis

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Authors

SWShifen WangTHTao HongXZXingyun Zhao

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Overview

Analysis reveals key biomarkers and immune cell infiltration in diffuse large B-cell lymphoma, suggesting their impact on patient prognosis.

Key Points

  • Four hub genes (CXCL9, CCL18, C1QA, and CTSC) were identified as significant biomarkers for predicting diffuse large B-cell lymphoma prognosis.
  • Machine learning algorithms indicated a promising diagnostic model, with the receiver operating characteristic results solidifying its predictive capability.
  • Analysis of three microarray datasets highlighted inflammatory pathways associated with cancer progression and immune response.
  • The study found that immune cell infiltration levels were positively correlated with the expression of the four hub genes identified.

Cite This Study

Wang et al. (2025) studied this question.

synapsesocial.com/papers/68c242e0b210217d647a478chttps://doi.org/10.1186/s12865-025-00738-z
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  1. 1Integrated multi-omics analysis identifies prognostic risk genes and constructs a predictive signature in diffuse large B-cell lymphoma2026
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  4. 4Risk Model Based On Neutrophil-Related Genes Constructs to Assess Prognosis and Immune Landscape in Diffuse Large B-Cell Lymphoma2025
  5. 5Machine learning based survival prediction of DLBCL: Using multimodal data.2025