Nature Medicine
8, 816 - 824 (2002)
Published online: 15 July 2002; | doi:10.1038/nm733
Gene-expression profiles predict survival of patients with lung adenocarcinomaDavid G. Beer1, Sharon L.R. Kardia2, Chiang-Ching Huang3, Thomas J. Giordano4, Albert M. Levin2, David E. Misek5, Lin Lin1, Guoan Chen1, Tarek G. Gharib1, Dafydd G. Thomas4, Michelle L. Lizyness4, Rork Kuick5, Satoru Hayasaka3, Jeremy M.G. Taylor3, Mark D. Iannettoni1, Mark B. Orringer1
& Samir Hanash51
Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA
2
Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
3
Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
4
Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
5
Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA
Correspondence should be addressed to David G. Beer dgbeer@umich.eduHistopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy.
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