PLoS ONE · 2012 · 220 citations · 14 references
MedicineCancer BiologyOncologyCancer PharmacologyMolecular OncologyNeoplasiaCancer BiomarkersCancer Cell SignalingCancer ProgressionCancer Survival AnalysisCancer TranscriptomicsMolecular Tumor ProfilingCancer Prognostic ModelingCancer Risk Prediction ModelsEpidermal Growth Factor Receptor InhibitionEpidermal Growth Factor Receptor SignalingExpression SignaturesLung AdenocarcinomaPrognostic Expression SignaturesReceptor Tyrosine Kinase Activation
PURPOSE: To identify stage I lung adenocarcinoma patients with a poor prognosis who will benefit from adjuvant therapy. PATIENTS AND METHODS: Whole gene expression profiles were obtained at 19 time points over a 48-hour time course from human primary lung epithelial cells that were stimulated with epidermal growth factor (EGF) in the presence or absence of a clinically used EGF receptor tyrosine kinase (RTK)-specific inhibitor, gefitinib. The data were subjected to a mathematical simulation using the State Space Model (SSM). "Gefitinib-sensitive" genes, the expressional dynamics of which were altered by addition of gefitinib, were identified. A risk scoring model was constructed to classify high- or low-risk patients based on expression signatures of 139 gefitinib-sensitive genes in lung cancer using a training data set of 253 lung adenocarcinomas of North American cohort. The predictive ability of the risk scoring model was examined in independent cohorts of surgical specimens of lung cancer. RESULTS: The risk scoring model enabled the identification of high-risk stage IA and IB cases in another North American cohort for overall survival (OS) with a hazard ratio (HR) of 7.16 (P = 0.029) and 3.26 (P = 0.0072), respectively. It also enabled the identification of high-risk stage I cases without bronchioalveolar carcinoma (BAC) histology in a Japanese cohort for OS and recurrence-free survival (RFS) with HRs of 8.79 (P = 0.001) and 3.72 (P = 0.0049), respectively. CONCLUSION: The set of 139 gefitinib-sensitive genes includes many genes known to be involved in biological aspects of cancer phenotypes, but not known to be involved in EGF signaling. The present result strongly re-emphasizes that EGF signaling status in cancer cells underlies an aggressive phenotype of cancer cells, which is useful for the selection of early-stage lung adenocarcinoma patients with a poor prognosis. TRIAL REGISTRATION: The Gene Expression Omnibus (GEO) GSE31210.
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Ahmedin Jemal, Rebecca L. Siegel, Elizabeth Ward et al. · CA A Cancer Journal for Clinicians · 2008 · 10.2K citations · Full text
Oncogenic pathway signatures in human cancers as a guide to targeted therapies
Andrea Bild, Guang Yao, Jeffrey T. Chang et al. · Nature · 2005 · 2.1K citations
Medicine, Cancer Biology, Oncology +14
A Five-Gene Signature and Clinical Outcome in Non–Small-Cell Lung Cancer
Hsuan‐Yu Chen, Sung‐Liang Yu, Chun‐Houh Chen et al. · New England Journal of Medicine · 2007 · 952 citations · Full text