ArticleAnnals of medicine2025
Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer.
Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Tumor-Associated Macrophage Exosomal miR-142-5p Drives Prostate Cancer Neuroendocrine Differentiation via RERG/Ras/ERK Axis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Biomarkers of radioresistance in lung cancer: Current insights and future directions (Review).Molecular medicine reports · 2026Review
- Integrating WGCNA and machine learning algorithm to identify ACSM5 as a prognostic biomarker and therapeutic target for predicting immunotherapy efficacy in non-small cell lung cancer.Translational cancer research · 2026Article
- Powerful large scale inference in high dimensional mediation analysis.PLoS computational biology · 2026Article
- Construction and validation of a chemokine-related gene signature associated with prognosis, clinical significance, and immune microenvironment characteristics in cervical cancer.Discover oncology · 2025Article
- Identification and exploration of key genes associated with radioresistance in lung adenocarcinoma.Cancer cell international · 2025Article
- Integrating bioinformatics and experimental validation to reveal a novel VRK score as a prognostic and therapeutic biomarker in hepatocellular carcinoma.Frontiers in immunology · 2025Article
- Integration of Immune Cell Signatures and Diagnostic Gene Markers in Pancreatitis: A Comprehensive Study on Therapeutic Targets and Predictive Diagnosis.Human mutation · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-small cell lung cancer (NSCLC) is a fatal disease, and radioresistance is an important factor leading to treatment failure and disease progression. The objective of this research was to detect radioresistance-related genes (RRRGs) with prognostic value in NSCLC.
methodsThe weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) analysis were performed to identify RRRGs using expression profiles from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) regression and random survival forest (RSF) were used to screen for prognostically relevant RRRGs. Multivariate Cox regression was used to construct a risk score model. Then, Immune landscape and drug sensitivity were evaluated. The biological functions exerted by the key gene
resultsNinety-nine RRRGs were screened by intersecting the results of DEGs and WGCNA, then 11 hub RRRGs associated with survival were identified using machine learning algorithms (LASSO and RSF). Subsequently, an eight-gene (
conclusionOur study developed an eight-gene risk score model with potential clinical value that can be adopted for choice of drug treatment and prognostic prediction. Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. These findings also provide references for the development of potential therapeutic targets.
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