SynthesisPLoS medicine2006
A gene expression signature predicts survival of patients with stage I non-small cell lung cancer.
Synthesis in PLoS medicine, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 162 papers, 3 of them syntheses that pooled it.
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Who cites it
162 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.Briefings in bioinformatics · 2016Pooled it
- Gene-expression signature predicts postoperative recurrence in stage I non-small cell lung cancer patients.PloS one · 2012Pooled it
- Identification of SERPINA1 as single marker for papillary thyroid carcinoma through microarray meta analysis and quantification of its discriminatory power in independent validation.BMC medical genomics · 2011Pooled it
- Development and validation of a quantitative real-time polymerase chain reaction classifier for lung cancer prognosis.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2011Trial
- Apoptosis gene expression analysis identifies biologically distinct AML clusters and BIK as an independent prognostic marker.Annals of hematology · 2026Article
- A Urinary Three-Metabolite Signature Enables Noninvasive Identification of Patients with High-Risk Ovarian Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Joint analysis of sQTL and Hi-C reveals spatial proximity between sQTLs and target genes in cancer tissues.Scientific reports · 2025Article
- Integrated systems biology reveals an 8-gene signature predicting early-stage lung adenocarcinoma progression and patient survival.Scientific reports · 2025Article
- A novel classification method for LUAD that guides personalized immunotherapy on the basis of the cross-talk of coagulation- and macrophage-related genes.Frontiers in immunology · 2025Article
- Cancer-AssociatedInternational journal of medical sciences · 2025Review
- MyoD1 promotes the transcription of BIK and plays an apoptosis-promoting role in the development of gastric cancer.Cell cycle (Georgetown, Tex.) · 2024Article
- Combination Analysis ofJournal of Korean medical science · 2024Article
- A comparative study of clustering methods on gene expression data for lung cancer prognosis.BMC research notes · 2023Article
- Deregulation of apoptotic proteins by induction ofIranian journal of basic medical sciences · 2023Article
- Prognostic biomarkers of pancreatic cancer identified based on a competing endogenous RNA regulatory network.Translational cancer research · 2022Article
- RNA-seq and ChIP-seq Identification of Unique and Overlapping Targets of GLI Transcription Factors in Melanoma Cell Lines.Cancers · 2022Article
- Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma.BMC medical genomics · 2022Article
- Identification of an inflammatory response signature associated with prognostic stratification and drug sensitivity in lung adenocarcinoma.Scientific reports · 2022Article
- Molecular Radiobiology in Non-Small Cell Lung Cancer: Prognostic and Predictive Response Factors.Cancers · 2022Review
- Article
102 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundLung cancer is the leading cause of cancer-related death in the United States. Nearly 50% of patients with stages I and II non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection. No reliable clinical or molecular predictors are currently available for identifying those at high risk for developing recurrent disease. As a consequence, it is not possible to select those high-risk patients for more aggressive therapies and assign less aggressive treatments to patients at low risk for recurrence. METHODS AND
findingsIn this study, we applied a meta-analysis of datasets from seven different microarray studies on NSCLC for differentially expressed genes related to survival time (under 2 y and over 5 y). A consensus set of 4,905 genes from these studies was selected, and systematic bias adjustment in the datasets was performed by distance-weighted discrimination (DWD). We identified a gene expression signature consisting of 64 genes that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Kaplan-Meier analysis of the overall survival of stage I NSCLC patients with the 64-gene expression signature demonstrated that the high- and low-risk groups are significantly different in their overall survival. Of the 64 genes, 11 are related to cancer metastasis (APC, CDH8, IL8RB, LY6D, PCDHGA12, DSP, NID, ENPP2, CCR2, CASP8, and CASP10) and eight are involved in apoptosis (CASP8, CASP10, PIK3R1, BCL2, SON, INHA, PSEN1, and BIK).
conclusionsOur results indicate that gene expression signatures from several datasets can be reconciled. The resulting signature is useful in predicting survival of stage I NSCLC and might be useful in informing treatment decisions.
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