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Published ahead of print on October 15, 2009, doi:10.1164/rccm.200812-1807OC
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American Journal of Respiratory and Critical Care Medicine Vol 181. pp. 181-188, (2010)
© 2010 American Thoracic Society
doi: 10.1164/rccm.200812-1807OC


Original Article

Gene Profiling of Clinical Routine Biopsies and Prediction of Survival in Non–Small Cell Lung Cancer

Florent Baty1, Michaël Facompré2, Sergio Kaiser3, Martin Schumacher3, Miklos Pless4, Lukas Bubendorf5, Spasenija Savic5, Estelle Marrer3, Wolfgang Budach3, Martin Buess6, Jeanne Kehren3, Michael Tamm7 and Martin H. Brutsche1

1 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.


AT A GLANCE COMMENTARY

Scientific Knowledge on the Subject
Gene expression microarrays have been successfully used for the diagnosis and prognosis of patients with non–small cell lung cancer (NSCLC). However, most studies investigated tumor samples obtained from surgical specimens only, which limits their findings to operable early-stage patients.

What This Study Adds to the Field
The proposed strategy of integrating functional genomics from small bronchoscopic biopsies allows molecular tumor classification and prediction of survival in patients with NSCLC of all stages and has the potential to become a powerful adjunct for the daily clinical practice.

 






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