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Gene Expression Profiling of Nonneoplastic Mucosa May Predict Clinical Outcome of Colon Cancer Patients
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Original Contribution
Gene Expression Profiling of Nonneoplastic Mucosa May Predict Clinical Outcome of Colon Cancer Patients
Alain Barrier1, 2, 3 , Pierre-Yves Boelle2 , Antoinette Lemoine4, Chantal Tse5, Didier Brault5, Franck Chiappini4, François Lacaine1, Sidney Houry1, Michel Huguier1, Antoine Flahault2 and Sandrine Dudoit3
| (1) |
Service de Chirurgie Digestive, Hôpital Tenon, Université Pierre et Marie Curie, Assistance Publique, Paris, France |
| (2) |
INSERM U444, Faculté de Médecine Saint-Antoine, Université Pierre et Marie Curie, Paris, France |
| (3) |
Division of Biostatistics, School of Public Health, University of California, Berkeley, California, France |
| (4) |
INSERM U602, Hôpital Paul Brousse, Université Paris XI, Villejuif, France |
| (5) |
Service de Biochimie, Hôpital Tenon, Université Pierre et Marie Curie, Assistance Publique, Paris, France |
Published online: 3 October 2005
PURPOSE This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in Stage
II and III colon cancer patients.
METHODS Tumor and nonneoplastic mucosa mRNA samples from 12 colon cancer patients were profiled using the Affymetrix HGU133A GeneChip. Six of 12 patients experienced a metachronous metastasis, whereas the 6 others remained disease-free for more than
five years. Three datasets were constituted, including, respectively, the gene expression measures in tumor samples (T), in
adjacent nonneoplastic mucosa samples (A), and the log-ratio of the gene expression measures (L). The step-down procedure
of Westfall and Young and the k-nearest neighbor class prediction method were applied on T, A, and L. Leave-one-out cross-validation
was used to estimate the generalization error of predictors based on different numbers of genes and neighbors.
RESULTS The most frequent results were one false prediction with the A-based predictors (95 percent) and two false predictions with
the T- and l-based predictors (65 and 60 percent, respectively). A-based predictors were more stable ( i.e., less sensitive to changes of parameters, such as numbers of genes and neighbors) than T- and l-based predictors. Informative genes in A-based predictors included genes involved in the oxidative and phosphorylative mitochondrial
metabolism and genes involved in cell-signaling pathways and their receptors.
CONCLUSIONS This study suggests that one can build a prognosis predictor for Stage II and III colon cancer patients, based on microarray
gene expression measures, and suggests the potential usefulness of nonneoplastic mucosa for this purpose.
Key words Functional genomics - Colon cancer - Prognosis prediction - Nonneoplastic mucosa
Supported by a grant from the Fondation de France/Fédération Nationale des Centres de Lutte Contre le Cancer for a stay in the Division of Biostatistics at the University of California, Berkeley (AB).
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