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Synapse
March 5, 20260 citations

Neutrophil extracellular trap-related genes in PTCL: identification, prognosis and drug interaction prediction via bioinformatics-machine learning.

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JCJianzhong ChenYJYang JinJFJun Fang

Key Points

  • This research aims to identify neutrophil extracellular trap-related genes and assess their prognostic value in peripheral T-cell lymphoma (PTCL).
  • Employ bioinformatics approaches to analyze NET-related genes
  • Utilize machine learning algorithms for interaction predictions
  • Evaluate the role of lenalidomide as a treatment option
  • Identified key NET-related genes associated with PTCL prognosis
  • Demonstrated the potential of lenalidomide as an initial treatment option
  • Highlighted the importance of the tumor microenvironment in disease management

Abstract

NET-RGs play crucial roles in diagnosis, prognosis, and TME regulation, and lenalidomide, a putative TNF-targeting agent, may represent a feasible initial treatment option in PTCL.

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Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/69a91d7cd6127c7a504c0421https://doi.org/10.1080/16078454.2026.2631219
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

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  4. 4Analysis of neutrophil extracellular trap‐related genes in Crohn's disease based on bioinformatics2024 · 7 citations
  5. 5Constructing a Neutrophil Extracellular Trap Model Based on Machine Learning to Predict Clinical Outcomes and Immunotherapy Response in Renal Cell Carcinoma2024