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 Weir; Roel 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

doi:10.1038/nm.1790

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

Research output: Contribution to journal › Article › peer-review

765 Scopus citations

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.

Original language	English (US)
Pages (from-to)	822-827
Number of pages	6
Journal	Nature medicine
Volume	14
Issue number	8
DOIs	https://doi.org/10.1038/nm.1790
State	Published - Aug 2008
Externally published	Yes

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology

Access to Document

10.1038/nm.1790

Cite this

Shedden, K., Taylor, J. M. G., Enkemann, S. A., Tsao, M. S., Yeatman, T. J., Gerald, W. L., Eschrich, S., Jurisica, I., Giordano, T. J., Misek, D. E., Chang, A. C., Zhu, C. Q., Strumpf, D., Hanash, S., Shepherd, F. A., Ding, K., Seymour, L., Naoki, K., Pennell, N., ... Beer, D. G. (2008). Gene expression-based survival prediction in lung adenocarcinoma: A multi-site, blinded validation study. Nature medicine, 14(8), 822-827. https://doi.org/10.1038/nm.1790

Shedden, K, Taylor, JMG, Enkemann, SA, Tsao, MS, Yeatman, TJ, Gerald, WL, Eschrich, S, Jurisica, I, Giordano, TJ, Misek, DE, Chang, AC, Zhu, CQ, Strumpf, D, Hanash, S, Shepherd, FA, Ding, K, Seymour, L, Naoki, K, Pennell, N, Weir, B, Verhaak, R, Ladd-Acosta, C, Golub, T, Gruidl, M, Sharma, A, Szoke, J, Zakowski, M, Rusch, V, Kris, M, Viale, A, Motoi, N, Travis, W, Conley, B, Seshan, VE, Meyerson, M, Kuick, R, Dobbin, KK, Lively, T, Jacobson, JW & Beer, DG 2008, 'Gene expression-based survival prediction in lung adenocarcinoma: A multi-site, blinded validation study', Nature medicine, vol. 14, no. 8, pp. 822-827. https://doi.org/10.1038/nm.1790

@article{a21f24a21ce046b7890b17610ad532cb,

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

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.",

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

year = "2008",

month = aug,

doi = "10.1038/nm.1790",

language = "English (US)",

volume = "14",

pages = "822--827",

journal = "Nature medicine",

issn = "1078-8956",

publisher = "Nature Publishing Group",

number = "8",

}

TY - JOUR

T1 - Gene expression-based survival prediction in lung adenocarcinoma

T2 - A multi-site, blinded validation study

AU - Shedden, Kerby

AU - Taylor, Jeremy M.G.

AU - Enkemann, Steven A.

AU - Tsao, Ming Sound

AU - Yeatman, Timothy J.

AU - Gerald, William L.

AU - Eschrich, Steven

AU - Jurisica, Igor

AU - Giordano, Thomas J.

AU - Misek, David E.

AU - Chang, Andrew C.

AU - Zhu, Chang Qi

AU - Strumpf, Daniel

AU - Hanash, Samir

AU - Shepherd, Frances A.

AU - Ding, Keyue

AU - Seymour, Lesley

AU - Naoki, Katsuhiko

AU - Pennell, Nathan

AU - Weir, Barbara

AU - Verhaak, Roel

AU - Ladd-Acosta, Christine

AU - Golub, Todd

AU - Gruidl, Michael

AU - Sharma, Anupama

AU - Szoke, Janos

AU - Zakowski, Maureen

AU - Rusch, Valerie

AU - Kris, Mark

AU - Viale, Agnes

AU - Motoi, Noriko

AU - Travis, William

AU - Conley, Barbara

AU - Seshan, Venkatraman E.

AU - Meyerson, Matthew

AU - Kuick, Rork

AU - Dobbin, Kevin K.

AU - Lively, Tracy

AU - Jacobson, James W.

AU - Beer, David G.

PY - 2008/8

Y1 - 2008/8

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=49149129916&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=49149129916&partnerID=8YFLogxK

U2 - 10.1038/nm.1790

DO - 10.1038/nm.1790

M3 - Article

C2 - 18641660

AN - SCOPUS:49149129916

SN - 1078-8956

VL - 14

SP - 822

EP - 827

JO - Nature medicine

JF - Nature medicine

IS - 8

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this