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November 8, 2025Frontiers in Bioscience-LandmarkOpen Access

Identification of Diagnostic Biomarkers Associated With M1 Macrophage in Lung Squamous Cell Carcinoma via Machine Learning

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Authors

HDHuiting DengZWZhenling WangQZQiangzhe Zhang

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Overview

Analysis reveals promising diagnostic biomarkers in lung squamous cell carcinoma, demonstrating significant predictive accuracy via a machine learning model.

Key Points

  • M1 macrophage-related diagnostic biomarkers improve clinical outcomes in lung squamous cell carcinoma.
  • Support vector machine model showed high predictive accuracy with AUC values of 0.995 and 1.000 in validation datasets.
  • Differential gene expression analysis highlighted key genes and biological functions associated with macrophage infiltration.
  • Identified biomarkers, including matrix metalloproteinase-7 and CXCL13, may enhance early detection and treatment strategies.

Cite This Study

Deng et al. (2025) studied this question.

synapsesocial.com/papers/690e8b6ca5b062d7a4e73675https://doi.org/10.31083/fbl44661
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