Originally published as JCO Early Release 10.1200/JCO.2005.05.0229 on September 11 2006

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Stage II Colon Cancer Prognosis Prediction by Tumor Gene Expression Profiling

Alain Barrier, Pierre-Yves Boelle, François Roser, Jennifer Gregg, Chantal Tse, Didier Brault, François Lacaine, Sidney Houry, Michel Huguier, Brigitte Franc, Antoine Flahault, Antoinette Lemoine, Sandrine Dudoit

From the Service de Chirurgie digestive, Hôpital Tenon, Assistance Publique—Hôpitaux de Paris; Epidemiologie, Systèmes d’information et Modélisation (U707), INSERM; UMR-S 707, Université Pierre et Marie Curie; Service de Biochimie, Hôpital Tenon, Assistance Publique–Hôpitaux de Paris, Paris; Micro-environnement et physiopathologie de la différenciation (U602), INSERM, Villejuif; Service d’Anatomie Pathologique, Hôpital Ambroise Paré, Assistance Publique Hôpitaux de Paris, Boulogne; Université Versailles Saint Quentin, Boulogne, France; Division of Biostatistics, School of Public Health, University of California Berkeley, Berkeley; J. David Gladstones Institute, University of California–San Francisco, San Francisco, CA

Address reprint requests to Alain Barrier, MD, Service de Chirurgie digestive, Hôpital Tenon, 4 rue de la Chine, 75020 Paris, France; e-mail: alain.barrier{at}tnn.ap-hop-paris.fr or barrier{at}stat.Berkeley.edu

PURPOSE: This study mainly aimed to identify and assess the performance of a microarray-based prognosis predictor (PP) for stage II colon cancer. A previously suggested 23-gene prognosis signature (PS) was also evaluated.

PATIENTS AND METHODS: Tumor mRNA samples from 50 patients were profiled using oligonucleotide microarrays. PPs were built and assessed by random divisions of patients into training and validation sets (TSs and VSs, respectively). For each TS/VS split, a 30-gene PP, identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Two schemes were considered: single-split validation, based on a single random split of patients into two groups of equal size (group 1 and group 2), and Monte Carlo cross validation (MCCV), whereby patients were repeatedly and randomly divided into TS and VS of various sizes.

RESULTS: The 30-gene PP, identified from group 1 patients, yielded an 80% prognosis prediction accuracy on group 2 patients. MCCV yielded the following average prognosis prediction performance measures: 76.3% accuracy, 85.1% sensitivity, and 67.5% specificity. Improvements in prognosis prediction were observed with increasing TS size. The 30-gene PS were found to be highly-variable across TS/VS splits. Assessed on the same random splits of patients, the previously suggested 23-gene PS yielded a 67.7% mean prognosis prediction accuracy.

CONCLUSION: Microarray gene expression profiling is able to predict the prognosis of stage II colon cancer patients. The present study also illustrates the usefulness of resampling techniques for honest performance assessment of microarray-based PPs.

published online ahead of print at www.jco.org on September 11, 2006.

Supported by the J. David Gladstone Institutes and General Clinical Research Center at San Francisco General Hospital, and by a grant from the California Institute for Quantitative Biomedical Research, University of California Berkeley (A.B.).

Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org.

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

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