Gene expression-based survival prediction in lung adenocarcinoma: A multi-site, blinded validation study

Kerby Shedden, Jeremy M.G. Taylor, Steven A. Enkemann, Ming Sound Tsao, Timothy J. Yeatman, William L. Gerald, Steven Eschrich, Igor Jurisica, Thomas J. Giordano, David E. Misek, Andrew C. Chang, Chang Qi Zhu, Daniel Strumpf, Samir Hanash, Frances A. Shepherd, Keyue Ding, Lesley Seymour, Katsuhiko Naoki, Nathan Pennell, Barbara WeirRoel Verhaak, Christine Ladd-Acosta, Todd Golub, Michael Gruidl, Anupama Sharma, Janos Szoke, Maureen Zakowski, Valerie Rusch, Mark Kris, Agnes Viale, Noriko Motoi, William Travis, Barbara Conley, Venkatraman E. Seshan, Matthew Meyerson, Rork Kuick, Kevin K. Dobbin, Tracy Lively, James W. Jacobson, David G. Beer

研究成果: Article査読

887 被引用数 (Scopus)


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.

ジャーナルNature medicine
出版ステータスPublished - 2008 8月

ASJC Scopus subject areas

  • 生化学、遺伝学、分子生物学(全般)


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