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01.12.2005 | Original Contribution | Ausgabe 12/2005

Diseases of the Colon & Rectum 12/2005

Gene Expression Profiling of Nonneoplastic Mucosa May Predict Clinical Outcome of Colon Cancer Patients

Zeitschrift:
Diseases of the Colon & Rectum > Ausgabe 12/2005
Autoren:
M.D. Alain Barrier, Ph.D. Pierre-Yves Boelle, Ph.D. Antoinette Lemoine, Ph.D. Chantal Tse, Ph.D. Didier Brault, Ph.D. Franck Chiappini, M.D. François Lacaine, M.D. Sidney Houry, M.D. Michel Huguier, M.D., Ph.D. Antoine Flahault, Ph.D. Sandrine Dudoit
Wichtige Hinweise
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).

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.

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