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

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.

[1]  D. Botstein,et al.  Diversity of gene expression in adenocarcinoma of the lung , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Kenneth H Buetow,et al.  Interlaboratory comparability study of cancer gene expression analysis using oligonucleotide microarrays. , 2005, Clinical cancer research : an official journal of the American Association for Cancer Research.

[3]  E. Lander,et al.  Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[4]  S. Mukherjee,et al.  A genomic strategy to refine prognosis in early-stage non-small-cell lung cancer. , 2006, The New England journal of medicine.

[5]  Jeremy J. W. Chen,et al.  A five-gene signature and clinical outcome in non-small-cell lung cancer. , 2007, The New England journal of medicine.

[6]  David E. Misek,et al.  RANTES expression is a predictor of survival in stage I lung adenocarcinoma. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[7]  A. Jemal,et al.  Cancer Statistics, 2006 , 2006, CA: a cancer journal for clinicians.

[8]  W. Fry,et al.  Ten‐year survey of lung cancer treatment and survival in hospitals in the United States , 1999, Cancer.

[9]  W. Gerald,et al.  Integration of gene expression profiling and clinical variables to predict prostate carcinoma recurrence after radical prostatectomy , 2005, Cancer.

[10]  F. Shepherd,et al.  Adjuvant Chemotherapy for Resected Non-small Cell Lung Cancer , 2006, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[11]  C. Li,et al.  Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[12]  H. Wakelee,et al.  Adjuvant Chemotherapy of Stage I Non-small Cell Lung Cancer in North America , 2007, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[13]  Charles R. Thomas,et al.  Ethnic Disparities in Conditional Survival of Patients with Non-small Cell Lung Cancer , 2007, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[14]  C. Sotiriou,et al.  Taking gene-expression profiling to the clinic: when will molecular signatures become relevant to patient care? , 2007, Nature Reviews Cancer.

[15]  M. Tyers,et al.  Molecular profiling of non-small cell lung cancer and correlation with disease-free survival. , 2002, Cancer research.

[16]  L. Tanoue,et al.  Erlotinib in Previously Treated Non-Small-Cell Lung Cancer , 2007 .

[17]  M. Gonen,et al.  Concordance probability and discriminatory power in proportional hazards regression , 2005 .

[18]  David E. Misek,et al.  Gene-expression profiles predict survival of patients with lung adenocarcinoma , 2002, Nature Medicine.

[19]  Zhifu Sun,et al.  A Gene Expression Signature Predicts Survival of Patients with Stage I Non-Small Cell Lung Cancer , 2006, PLoS medicine.