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September 10, 2025Discover OncologyOpen Access

Development and validation of a hypoxia-immune-based microenvironment gene signature for predicting survival in non-small cell lung cancer

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Authors

XZXiangwu ZhangRZRong ZhouGZGuangqiang Zhao

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Overview

Observational analysis identifies a gene signature predicting prognosis in non-small cell lung cancer, indicating potential for personalized treatment.

Key Points

  • The established hypoxia-immune gene signature accurately predicts survival outcomes for patients with non-small cell lung cancer.
  • The model achieved AUC values of 0.643, 0.649, and 0.620 at 1, 3, and 5 years respectively, demonstrating significant predictive accuracy.
  • Multivariate Cox regression analyses identified the risk score as an independent prognostic factor, further validating its clinical relevance.
  • High immune activity correlates with improved survival outcomes in non-small cell lung cancer patients, suggesting a potential therapeutic target.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/68c240deb210217d6479d189https://doi.org/10.1007/s12672-025-03319-z
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Also Consider

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  1. 1Development and Validation of a Prognostic Model for Lung Cancer Based on Machine Learning and Immune Microenvironment Analysis2025
  2. 2A Novel Hypoxia-Immune Signature for Gastric Cancer Prognosis and Immunotherapy: Insights from Bulk and Single-Cell RNA-Seq2025
  3. 3Hypoxia-anoikis-related genes in LUAD: machine learning and RNA sequencing analysis of immune infiltration and therapy response2025
  4. 4Integrated systems biology reveals an 8-gene signature predicting early-stage lung adenocarcinoma progression and patient survival2025
  5. 5Transcriptomic Signatures in TP53 Positive and Negative Tumor Samples in NSCLC2025