Originally published as JCO Early Release 10.1200/JCO.2008.20.0386 on September 21 2009

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Identification and Validation of a Gene Expression Signature That Predicts Outcome in Adult Men With Germ Cell Tumors

From the Cell Biology Program, Sloan-Kettering Institute for Cancer Research, New York; and Departments of Medicine, Epidemiology and Biostatistics, and Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY.

Corresponding author: R.S.K. Chaganti, PhD, 1275 York Ave, Box 30, Memorial Sloan-Kettering Cancer Center, New York, NY 10021; e-mail: chagantr{at}mskcc.org.

Purpose Germ cell tumor (GCT) is the most common malignancy in young adult men. Currently, patients are risk-stratified on the basis of clinical presentation and serum tumor markers. The introduction of molecular markers could improve outcome prediction.

Patients and Methods Expression profiling was performed on 74 nonseminomatous GCTs (NSGCTs) from cisplatin-treated patients (ie, training set) and on 34 similarly treated patients with NSGCTs (ie, validation set). A gene classifier was developed by using prediction analysis for microarrays (PAM) for the binary end point of 5-year overall survival (OS). A predictive score was developed for OS by using the univariate Cox model.

Results In the training set, PAM identified 140 genes that predicted 5-year OS (cross-validated classification rate, 60%). The PAM model correctly classified 90% of patients in the validation set. Patients predicted to have good outcome had significantly longer survival than those with poor predicted outcome (P < .001). For the OS end point, a 10-gene model had a predictive accuracy (ie, concordance index) of 0.66 in the training set and a concordance index of 0.83 in the validation set. Dichotomization of the samples on the basis of the median score resulted in significant differences in survival (P = .002). For both end points, the gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification (P < .01 for both).

Conclusion We have identified gene expression signatures that accurately predict outcome in patients with GCTs. These predictive genes should be useful for the prediction of patient outcome and could provide novel targets for therapeutic intervention.

This work was supported by grants from the Lance Armstrong Foundation and by the Memorial Sloan-Kettering Cancer Center Byrne Fund.

Presented in part at the 44th Annual Meeting of the American Society of Clinical Oncology, Chicago, IL, May 30- June 3, 2008; the 6th Copenhagen Workshop on CIS Testis and Germ Cell Cancer, Copenhagen, Denmark, October 26-28, 2006; and the 96th Annual Meeting of the American Association for Cancer Research, Anaheim, CA, April 16-20, 2005.

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

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