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Three-Gene Prognostic Classifier for Early-Stage Non–Small-Cell Lung Cancer

Suzanne K. Lau, Paul C. Boutros, Melania Pintilie, Fiona H. Blackhall, Chang-Qi Zhu, Dan Strumpf, Michael R. Johnston, Gail Darling, Shaf Keshavjee, Thomas K. Waddell, Ni Liu, Davina Lau, Linda Z. Penn, Frances A. Shepherd, Igor Jurisica, Sandy D. Der, Ming-Sound Tsao

From the University Health Network, Ontario Cancer Institute, Princess Margaret Hospital and Toronto General Hospital; Departments of Medical Biophysics, Thoracic Surgery, Computer Science, Medicine, and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada; and Department of Medical Oncology, Christie Hospital National Health Service Trust, Manchester, United Kingdom

Address reprint requests to Ming-Sound Tsao, MD, Princess Margaret Hospital, 610 University Ave, Toronto, Ontario, Canada M5G 2M9; e-mail: Ming.Tsao{at}uhn.on.ca

Purpose Several microarray studies have reported gene expression signatures that classify non–small-cell lung carcinoma (NSCLC) patients into different prognostic groups. However, the prognostic gene lists reported to date overlap poorly across studies, and few have been validated independently using more quantitative assay methods.

Patients and Methods The expression of 158 putative prognostic genes identified in previous microarray studies was analyzed by reverse transcription quantitative polymerase chain reaction in the tumors of 147 NSCLC patients. Concordance indices and risk scores were used to identify a stage-independent set of genes that could classify patients with significantly different prognoses.

Results We have identified a three-gene classifier (STX1A, HIF1A, and CCR7) for overall survival (hazard ratio = 3.8; 95% CI, 1.7 to 8.2; P < .001). The classifier was also able to stratify stage I and II patients and further improved the predictive ability of clinical factors such as histology and tumor stage. The predictive value of this three-gene classifier was validated in two large independent microarray data sets from Harvard and Duke Universities.

Conclusion We have identified a new three-gene classifier that is independent of and improves on stage to stratify early-stage NSCLC patients with significantly different prognoses. This classifier may be tested further for its potential value to improve the selection of resected NSCLC patients in adjuvant therapy.

Supported by Grant No. 015184 from the National Cancer Institute of Canada (M.-S.T.); Grant No. RGPIN 203833-02 from the National Science and Engineering Research Council; grants from IBM, the Institute for Robotics and Intelligence Systems, and the Fireman and Younger Foundation (I.J.); Genome Canada (I.J., S.D.D.); and Pre-Competitive Applied Research Network, Natural Sciences and Engineering Research Council, and Excellence in Radiation Research for the 21st Century Fellowships (P.C.B.).

S.K.L., P.C.B., and M.P. contributed equally to this work.

Presented in part at the 11th World Conference of the International Association for the Study of Lung Cancer, July 3-6, 2005, Barcelona, Spain; and 97th Annual Meeting of the American Association of Cancer Research, April 1-5, 2006, Washington, DC.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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