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

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Abstract
Global gene expression analysis provides a comprehensive molecular characterization of non-small cell lung cancer (NSCLC). 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. 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. 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-beta, one of the key prognostic genes, was further validated by immunohistochemistry on 508 independent tumor samples. 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.