Colon Cancer Prognosis Prediction by Gene Expression Profiling
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Published 2005 (Sept.) in Oncogene, 24(40), pp. 6155-6164.
Abstract:
Aims. This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in stage II and III colon cancer patients. Materials and Methods. Tumour (T) and non-neoplastic mucosa (NM) mRNA samples from 18 patients (9 with a recurrence, 9 with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. The k-nearest neighbour method was used for prognosis prediction using T and NM gene expression measures. Six-fold cross-validation was applied to select the number of neighbours and the number of informative genes to include in the predictors. Based on this information, one T-based and one NM-based predictor were proposed and their accuracies estimated by double cross-validation. Results. In 6-fold cross-validation, the lowest numbers of informative genes giving the lowest numbers of false predictions (2 out of 18) were 30 and 70 with the T and NM gene expression measures, respectively. A 30-gene T-based predictor and a 70-gene NM-based predictor were then built, with estimated accuracies of 78 and 83%, respectively. Conclusion. This study suggests that one can build an accurate prognosis predictor for stage II and III colon cancer patients, based on gene expression measures, and one can use either tumour or non-neoplastic mucosa for this purpose.
Subject Area:
Disease Modeling, Medical Specialties, Multivariate Analysis
Suggested Citation:
Alain Barrier, Sandrine Dudoit, and et al., "Colon Cancer Prognosis Prediction by Gene Expression Profiling" (May 2005). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 178.
http://www.bepress.com/ucbbiostat/paper178