Gene expression profiling of nonneoplastic mucosa may predict clinical outcome of colon cancer patients

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 cellsignaling 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.