Published ahead of print on October 15, 2009, doi:10.1164/rccm.200812-1807OC
© 2010 American Thoracic Society doi: 10.1164/rccm.200812-1807OC
Gene Profiling of Clinical Routine Biopsies and Prediction of Survival in Non–Small Cell Lung Cancer1 Department of Pneumology, Kantonsspital St. Gallen, St. Gallen, Switzerland; 2 Department of Biomedicine, 5 Institute for Pathology, and 7 Department of Pneumology, University Hospital Basel, Basel, Switzerland; 3 Biomarker Development, Novartis AG, Basel, Switzerland; 4 Medical Oncology, Kantonsspital Winterthur, Winterthur, Switzerland; and 6 Department of Oncology, Claraspital Basel, Basel, Switzerland Correspondence and requests for reprints should be addressed to Prof. Martin H. Brutsche, M.D., Ph.D., Pneumologie, Kantonsspital St. Gallen, CH-9007 St. Gallen, Switzerland. E-mail: martin.brutsche{at}kssg.ch Rationale: Global gene expression analysis provides a comprehensive molecular characterization of non–small cell lung cancer (NSCLC). Objectives: To evaluate the feasibility of integrating expression profiling into routine clinical work-up by including both surgical and minute bronchoscopic biopsies and to develop a robust prognostic gene expression signature. Methods: Tissue samples from 41 chemotherapy-naive patients with NSCLC and 15 control patients with inflammatory lung diseases were obtained during routine clinical work-up and gene expression profiles were gained using an oligonucleotide array platform (NovaChip; 34'207 transcripts). Gene expression signatures were analyzed for correlation with histological and clinical parameters and validated on independent published data sets and immunohistochemistry. Measurements and Main Results: Diagnostic signatures for adenocarcinoma and squamous cell carcinoma reached a sensitivity of 80%/80% and a specificity of 83%/94%, respectively, dependent on the proportion of tumor cells. Sixty-seven of the 100 most discriminating genes were validated with independent observations from the literature. A 13-gene metagene refined on four external data sets was built and validated on an independent data set. The metagene was a strong predictor of survival in our data set (hazard ratio = 7.7, 95% CI [2.8–21.2]) and in the independent data set (hazard ratio = 1.6, 95% CI [1.2–2.2]) and in both cases independent of the International Union against Cancer staging. Vascular endothelial growth factor-β, one of the key prognostic genes, was further validated by immunohistochemistry on 508 independent tumor samples. Conclusions: Integration of functional genomics from small bronchoscopic biopsies allows molecular tumor classification and prediction of survival in NSCLC and might become a powerful adjunct for the daily clinical practice.
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