ArticleCombinatorial chemistry & high throughput screening2024
A Six-gene Prognostic Model Based on Neutrophil Extracellular Traps (NETs)-related Gene Signature for Lung Adenocarcinoma.
Article in Combinatorial chemistry & high throughput screening, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- From Gene to Enzyme: Multidimensional Decoding of the GGT Molecular Family and Its Clinical Tumor Diagnosis.Cancer medicine · 2025Pooled it
- Tumor-associated neutrophils and neutrophil extracellular traps in lung cancer: antitumor/protumor insights and therapeutic implications.Medical oncology (Northwood, London, England) · 2025Review
- Identification and construction of a novel NET-related gene signature for predicting prognosis in multiple myeloma.Clinical and experimental medicine · 2025Article
- [Dual Roles of Neutrophil Extracellular Traps in Lung Cancer: Mechanism Exploration and Therapeutic Prospects].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Review
- Article
- ERH Impacts Patient Prognosis and Tumor Immune Microenvironment: A Pan-Cancer Analysis.Combinatorial chemistry & high throughput screening · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundLung adenocarcinoma (LUAD) is one of the most common malignant cancers. Neutrophil extracellular traps (NETs) have been discovered to play a crucial role in the pathogenesis of LUAD. We aimed to establish an innovative prognostic model for LUAD based on the distinct expression patterns of NETs-related genes.
methodsThe TCGA LUAD dataset was utilized as the training set, while GSE31210, GSE37745, and GSE50081 were undertaken as the verification sets. The patients were grouped into clusters based on the expression signature of NETs-related genes. Differentially expressed genes between clusters were identified through the utilization of the random forest and LASSO algorithms. The NETs score model for LUAD prognosis was developed by multiplying the expression levels of specific genes with their corresponding LASSO coefficients and then summing them. The validity of the model was confirmed by analysis of the survival curves and ROC curves. Additionally, immune infiltration, GSEA, mutation analysis, and drug analysis were conducted. Silencing ABCC2 in A549 cells was achieved to investigate its effect.
resultsWe identified six novel NETs-related genes, namely
conclusionAltogether, this study has identified a novel NET-score signature based on six novel NET-related genes to predict the prognosis of LUAD and ABCC2 and has also explored a new method for personalized chemo-/immuno-therapy of LUAD.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.