ArticleJournal of the National Cancer Institute2017
Development of a RNA-Seq Based Prognostic Signature in Lung Adenocarcinoma.
Article in Journal of the National Cancer Institute, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers.
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Who cites it
123 citing papers in PubMed, 189 citations in OpenAlex.
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- Gene Expression Clustering of Lung Adenocarcinoma Tumors as a Prognosis Tool to Infer Progression-Free Survival.JTO clinical and research reports · 2026Article
- Using an integrated omics approach to uncover the mechanisms underlying chemotherapy-induced peripheral neuropathy (CIPN).Communications medicine · 2026Review
- Discovery of Novel RASGRF2 Fusions as a Therapeutic Target in Lung Adenocarcinoma of Never or Light Smokers.Cancer science · 2025Article
- Deciphering functional landscape and clinical implications of enhancer RNAs in lung adenocarcinoma.Scientific reports · 2025Article
- Intra-tumor microbiome-based tumor survival indices predict immune interaction and drug sensitivity on pan-cancer scale.mSystems · 2025Article
- Comprehensive analysis of telomere and aging-related signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.Journal of cardiothoracic surgery · 2025Article
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- Identification of PANoptosis Subtypes to Assess the Prognosis and Immune Microenvironment of Lung Adenocarcinoma Patients: A Bioinformatics Combined Machine Learning Study.Current cancer drug targets · 2025Article
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- Integration analysis ofBiochemistry and biophysics reports · 2024Article
- Multiregional transcriptomic profiling provides improved prognostic insight in localized non-small cell lung cancer.NPJ precision oncology · 2024Article
- Unraveling the immune landscape of lung adenocarcinoma: insights for tailoring therapeutic approaches.Discover oncology · 2024Article
- DeepCG: A cell graph model for predicting prognosis in lung adenocarcinoma.International journal of cancer · 2024Article
- Integrating the analysis of human biopsies using post-translational modifications proteomics.Protein science : a publication of the Protein Society · 2024Review
- Integrating single-cell and bulk expression data to identify and analyze cancer prognosis-related genes.Heliyon · 2024Article
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- Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.Scientific reports · 2024Article
- Clinical Impact of Genomic and Pathway Alterations in Stage I EGFR-Mutant Lung Adenocarcinoma.Cancer research and treatment · 2024Article
- Transcriptomic era of cancers in females: new epigenetic perspectives and therapeutic prospects.Frontiers in oncology · 2024Review
63 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Precision therapy for lung cancer will require comprehensive genomic testing to identify actionable targets as well as ascertain disease prognosis. RNA-seq is a robust platform that meets these requirements, but microarray-derived prognostic signatures are not optimal for RNA-seq data. Thus, we undertook the first prognostic analysis of lung adenocarcinoma RNA-seq data and generated a prognostic signature. Methods: Lung adenocarcinoma RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) were divided chronologically into training (n = 255) and validation (n = 157) cohorts. In the training cohort, prognostic association was assessed by univariate Cox analysis. A prognostic signature was built with stepwise multivariable Cox analysis. Outcomes by risk group, stage, and mutation status were analyzed with Kaplan-Meier and multivariable Cox analyses. All the statistical tests were two-sided. Results: In the training cohort, 96 genes had prognostic association with P values of less than or equal to 1.00x10 Conclusions: Here, we present the first RNA-seq prognostic signature for lung adenocarcinoma that can provide a powerful prognostic tool for precision oncology as part of an integrated RNA-seq clinical sequencing program.
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