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Gene Expression Profiling Reveals Reproducible Human Lung Adenocarcinoma Subtypes in Multiple Independent Patient Cohorts

D. Neil Hayes, Stefano Monti, Giovanni Parmigiani, C. Blake Gilks, Katsuhiko Naoki, Arindam Bhattacharjee, Mark A. Socinski, Charles Perou, Matthew Meyerson

From the Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge; Departments of Medical Oncology and Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston; Agilent Technologies, Andover, MA; Department of Biostatistics, The Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pathology and Laboratory Medicine, Vancouver General Hospital and University of British Columbia, Vancouver, British Columbia, Canada; and Yokohama Municipal Hospital, Yokohama, Japan

Address reprint requests to D. Neil Hayes, MD, MPH, Assistant Professor of Medicine, University of North Carolina, Lineberger Comprehensive Cancer Center, CB #7295, Chapel Hill, NC 27599-7295; e-mail: hayes{at}med.unc.edu

Purpose Published reports suggest that DNA microarrays identify clinically meaningful subtypes of lung adenocarcinomas not recognizable by other routine tests. This report is an investigation of the reproducibility of the reported tumor subtypes.

Methods Three independent cohorts of patients with lung cancer were evaluated using a variety of DNA microarray assays. Using the integrative correlations method, a subset of genes was selected, the reliability of which was acceptable across the different DNA microarray platforms. Tumor subtypes were selected using consensus clustering and genes distinguishing subtypes were identified using the weighted difference statistic. Gene lists were compared across cohorts using centroids and gene set enrichment analysis.

Results Cohorts of 31, 72, and 128 adenocarcinomas were generated for a total of 231 microarrays, each with 2,553 reliable genes. Three adenocarcinoma subtypes were identified in each cohort. These were named bronchioid, squamoid, and magnoid according to their respective correlations with gene expression patterns from histologically defined bronchioalveolar carcinoma, squamous cell carcinoma, and large-cell carcinoma. Tumor subtypes were distinguishable by many hundreds of genes, and lists generated in one cohort were predictive of tumor subtypes in the two other cohorts. Tumor subtypes correlated with clinically relevant covariates, including stage-specific survival and metastatic pattern. Most notably, bronchioid tumors were correlated with improved survival in early-stage disease, whereas squamoid tumors were associated with better survival in advanced disease.

Conclusion DNA microarray analysis of lung adenocarcinomas identified reproducible tumor subtypes which differ significantly in clinically important behaviors such as stage-specific survival.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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