Article abstract
Nature Medicine 14, 822 - 827 (2008)
Published online: 20 July 2008 | doi:10.1038/nm.1790
Gene expression–based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study
Director's Challenge Consortium for the Molecular Classification of Lung Adenocarcinoma1, Kerby Shedden2,3,17, Jeremy M G Taylor3,4,17, Steven A Enkemann5,17, Ming-Sound Tsao6,17, Timothy J Yeatman5,17, William L Gerald7,17, Steven Eschrich5,17, Igor Jurisica6,17, Thomas J Giordano8, David E Misek3,9, Andrew C Chang3,9, Chang Qi Zhu6, Daniel Strumpf6, Samir Hanash3, Frances A Shepherd6, Keyue Ding10, Lesley Seymour10, Katsuhiko Naoki11, Nathan Pennell11, Barbara Weir11, Roel Verhaak11, Christine Ladd-Acosta12, Todd Golub12, Michael Gruidl5, Anupama Sharma5, Janos Szoke7, Maureen Zakowski7, Valerie Rusch7, Mark Kris7, Agnes Viale7, Noriko Motoi7, William Travis7, Barbara Conley13, Venkatraman E Seshan14,17, Matthew Meyerson11,12,17, Rork Kuick3,17, Kevin K Dobbin15,17, Tracy Lively16,17, James W Jacobson16,17 & David G Beer3,9,17
Abstract
Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training–testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.
- The consortium consists of the Writing Committee plus additional participants as detailed in the Author Contributions section.
- Department of Statistics, 1085 South University, University of Michigan, Ann Arbor, Michigan 48109, USA.
- Cancer Center, 1500 East Medical Center Drive, University of Michigan, Ann Arbor, Michigan 48109, USA.
- Department of Biostatistics, 1420 Washington Heights, University of Michigan, Ann Arbor, Michigan 48109, USA.
- Department of Surgery, H. Lee Moffitt Cancer Center and Research Institute, University of South Florida, 12902 Magnolia Avenue, Tampa, Florida 33612, USA.
- University Health Network, Ontario Cancer Institute and Princess Margaret Hospital, 610 University Avenue, Toronto, Ontario M5G 2M9, Canada.
- Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, New York 10021, USA.
- Department of Pathology, University Hospital 2G332/0054, University of Michigan, Ann Arbor, Michigan 48109, USA.
- Department of Surgery, 1150 West Medical Center Drive, University of Michigan, Ann Arbor, Michigan 48109, USA.
- National Cancer Institute of Canada Clinical Trials Group and Queen's University, 10 Stuart Street, Kingston, Ontario K7L 3N6, Canada.
- Department of Medical Oncology, Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, 44 Binney Street, Boston, Massachusetts, 02115, USA.
- Broad Institute, 7 Cambridge Center, Cambridge, Massachusetts 02142, USA.
- Department of Medicine, B-414 Clinical Center, Michigan State University, East Lansing, Michigan 48824, USA.
- Columbia University, 722 West 168th Street, New York, New York 10032, USA.
- Biometric Research Branch National Cancer Institute, EPN 8121A, 6130 Executive Boulevard, Rockville, Maryland 20852, USA.
- Cancer Diagnosis Program, National Cancer Institute, EPN 6035A, 6130 Executive Boulevard, Rockville, Maryland 20852, USA.
- Writing Committee members.
Correspondence to: James W Jacobson16,17 e-mail: jacobsonj@ctep.nci.nih.gov
Correspondence to: David G Beer3,9,17 e-mail: dgbeer@umich.edu
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