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.
PURPOSE: This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in Stage II and III colon cancerpatients. METHODS:Tumor and nonneoplastic mucosa mRNA samples from 12 colon cancerpatients 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 cancerpatients, based on microarray gene expression measures, and suggests the potential usefulness of nonneoplastic mucosa for this purpose.
Authors: Gregory Lucien Bellot; Wei Han Tan; Ling Lee Tay; Dean Koh; Xueying Wang Journal: J Cancer Res Clin Oncol Date: 2011-12-21 Impact factor: 4.553
Authors: Wendy L Allen; Leanne Stevenson; Vicky M Coyle; Puthen V Jithesh; Irina Proutski; Gail Carson; Michael A Gordon; Heinz-Josef D Lenz; Sandra Van Schaeybroeck; Daniel B Longley; Patrick G Johnston Journal: Mol Cancer Ther Date: 2011-10-25 Impact factor: 6.261
Authors: Axel Walther; Elaine Johnstone; Charles Swanton; Rachel Midgley; Ian Tomlinson; David Kerr Journal: Nat Rev Cancer Date: 2009-06-18 Impact factor: 60.716
Authors: Beatriz Carvalho; Anke H Sillars-Hardebol; Cindy Postma; Sandra Mongera; Jochim Terhaar Sive Droste; Askar Obulkasim; Mark van de Wiel; Wim van Criekinge; Bauke Ylstra; Remond J A Fijneman; Gerrit A Meijer Journal: Cell Oncol (Dordr) Date: 2012-01-26 Impact factor: 6.730