ArticlePloS one2010
Gene expression-based classification of non-small cell lung carcinomas and survival prediction.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 491 papers, 2 of them syntheses that pooled it.
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Who cites it
491 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- Meta-Analysis Based on Nonconvex Regularization.Scientific reports · 2020Pooled it
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- Preoperative CT-Based Habitat Radiomics Classifiers Predict Recurrence in Non-Small Cell Lung Cancer.medRxiv : the preprint server for health sciences · 2026Article
- Sortilin exhibits tumor suppressor-like activity by limiting EGFR transduction function.Oncogene · 2026Article
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- A hybrid feature extraction framework combining PCA and mutual information for gene expression based lung cancer classification.PloS one · 2026Article
- RAB3A-mediated BAG6 translocation promotes non-small cell lung cancer tumorigenesis and progression.Cellular oncology (Dordrecht, Netherlands) · 2025Article
- HMGB3 promotes brain metastasis of lung adenocarcinoma by recruiting SSBP1 for nuclear translocation to remodel mitochondrial metabolism.Cancer communications (London, England) · 2025Article
- Multi-omic data integration and exploiting metabolic models using systems biology approach increase precision in subtyping and early diagnosis of cancer.Quantitative biology (Beijing, China) · 2025Article
- The GGH/HuR Complex Binds and Stabilizes mRNAs to Maintain Tumor Cell Cycle and DNA Replication.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Aberrant DNA methylation and overexpression of NR0B1 are prognostic biomarkers in KEAP1-mutant lung adenocarcinomas.Discover oncology · 2025Article
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- Article
431 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCurrent clinical therapy of non-small cell lung cancer depends on histo-pathological classification. This approach poorly predicts clinical outcome for individual patients. Gene expression profiling holds promise to improve clinical stratification, thus paving the way for individualized therapy. METHODOLOGY AND PRINCIPAL
findingsA genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples. We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of non-small cell lung cancer. Correlation analysis identified 17 genes which showed the best association with post-surgery survival time. This signature was used for stratification of all patients in two risk groups. Kaplan-Meier survival curves show that the two groups display a significant difference in post-surgery survival time (p = 5.6E-6). The performance of the signatures was validated using a patient cohort of similar size (Duke University, n = 96). Compared to previously published prognostic signatures for NSCLC, the 17 gene signature performed well on these two cohorts.
conclusionsThe gene signatures identified are promising tools for histo-pathological classification of non-small cell lung cancer, and may improve the prediction of clinical outcome.
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