ArticleScientific reports2022
A prognostic model of non small cell lung cancer based on TCGA and ImmPort databases.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Implementing trust in non-small cell lung cancer diagnosis with a conformalized uncertainty-aware AI framework.Nature biomedical engineering · 2026Article
- Clinical phenotype identification based on inflammation-nutrition-coagulation biomarkers in advanced non-small cell lung cancer.Frontiers in nutrition · 2026Article
- Integrated bioinformatics analysis identifies an immune-related gene signature associated with non-obstructive azoospermia.PloS one · 2026Article
- Tumor prognostic risk stratification based on pseudo-time analysis of single-cell sequencing for patients with lung adenocarcinoma.Journal of thoracic disease · 2025Article
- Development and validation of an immune-related gene set (IRGS) model for prognostic and immunotherapeutic assessment in lung adenocarcinoma (LUAD).Journal of thoracic disease · 2025Article
- Review
- The Regulatory Role of LncRNAs in Modulating Autophagy and Drug Resistance in Non-Small-Cell Lung Cancer: Focus on Targeted Therapeutic Approaches.Biomolecules · 2025Review
- Identification of prognostic-related tumor microenvironment genes in lung adenocarcinoma and establishment of a prognostic prediction model.Translational lung cancer research · 2025Article
- G0S2: a potential target for NSCLC identified through prognostic models from multi-Omic analysis of regulatory T cell metabolic genes.NPJ precision oncology · 2025Article
- Construction of an immune-related gene prognostic model with experimental validation and analysis of immune cell infiltration in lung adenocarcinoma.Oncology letters · 2024Article
- Prognostic mutation signature would serve as a potential prognostic predictor in patients with diffuse large B-cell lymphoma.Scientific reports · 2024Article
- MicroRNAs expression profile in chemotherapy-induced cardiotoxicity in NSCLC using a co-culture model.Biomolecules & biomedicine · 2024Article
- A potential novel biomarker: comprehensive analysis of prognostic value and immune implication of CES3 in colonic adenocarcinoma.Journal of cancer research and clinical oncology · 2023Article
- Article
- Current treatments for non-small cell lung cancer.Frontiers in oncology · 2022Review
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3 authors.
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Abstract
Bioinformatics methods are used to construct an immune gene prognosis assessment model for patients with non-small cell lung cancer (NSCLC), and to screen biomarkers that affect the occurrence and prognosis of NSCLC. The transcriptomic data and clinicopathological data of NSCLC and cancer-adjacent normal tissues were downloaded from the Cancer Genome Atlas (TCGA) database and the immune-related genes were obtained from the IMMPORT database ( http://www.immport.org/ ); then, the differentially expressed immune genes were screened out. Based on these genes, an immune gene prognosis model was constructed. The Cox proportional hazards regression model was used for univariate and multivariate analyses. Further, the correlations among the risk score, clinicopathological characteristics, tumor microenvironment, and the prognosis of NSCLC were analyzed. A total of 193 differentially expressed immune genes related to NSCLC were screened based on the "wilcox.test" in R language, and Cox single factor analysis showed that 19 differentially expressed immune genes were associated with the prognosis of NSCLC (P < 0.05). After including 19 differentially expressed immune genes with P < 0.05 into the Cox multivariate analysis, an immune gene prognosis model of NSCLC was constructed (it included 13 differentially expressed immune genes). Based on the risk score, the samples were divided into the high-risk and low-risk groups. The Kaplan-Meier survival curve results showed that the 5-year overall survival rate in the high-risk group was 32.4%, and the 5-year overall survival rate in the low-risk group was 53.7%. The receiver operating characteristic model curve confirmed that the prediction model had a certain accuracy (AUC = 0.673). After incorporating multiple variables into the Cox regression analysis, the results showed that the immune gene prognostic risk score was an independent predictor of the prognosis of NSCLC patients. There was a certain correlation between the risk score and degree of neutrophil infiltration in the tumor microenvironment. The NSCLC immune gene prognosis assessment model was constructed based on bioinformatics methods, and it can be used to calculate the prognostic risk score of NSCLC patients. Further, this model is expected to provide help for clinical judgment of the prognosis of NSCLC patients.
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