Gene-expression profiles predict survival of patients with lung adenocarcinoma

Nature Medicine volume 8, pages816–824(2002)Cite this article

Abstract

Histopathology 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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Figure 1: Unsupervised classification analysis of lung adenocarcinomas.
Figure 2: Validation analyses of gene-expression profiling.
Figure 3: Gene-expression profiles and patient survival.
Figure 4: Gene expression patterns of top survival genes
Figure 5: Gene amplification and protein expression of survival-related genes.

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Acknowledgements

We thank D. Sanders for technical assistance; D. Sing for assistance with the figures; and G. Omenn for critical reading of this manuscript. This work was supported by National Cancer Institute grant: U19 CA-85953 and the Tissue Core of the University of Michigan Comprehensive Cancer Center (NIH CA-46952).

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Affiliations

  1. Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA

    David G. Beer, Lin Lin, Guoan Chen, Tarek G. Gharib, Mark D. Iannettoni & Mark B. Orringer

  2. Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA

    Sharon L.R. Kardia & Albert M. Levin

  3. Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA

    Chiang-Ching Huang, Satoru Hayasaka & Jeremy M.G. Taylor

  4. Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA

    Thomas J. Giordano, Dafydd G. Thomas & Michelle L. Lizyness

  5. Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA

    David E. Misek, Rork Kuick & Samir Hanash

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  1. David G. Beer
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Correspondence to David G. Beer.

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Beer, D., Kardia, S., Huang, C. et al. Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med 8, 816–824 (2002). https://doi.org/10.1038/nm733

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