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Molecular Biology and Genetics |
Cellular and Molecular Research [S. T. T., K. Y., A. A., C. H. L., K. W., P. T.], Division of Medical Sciences [S. H. L., J. V., D. L., K. C. S., O. L. K.], and Defence Medical Research Institute [P. T.], National Cancer Centre, Singapore 169610, Republic of Singapore; Department of Pathology and Laboratory Medicine, Tan Tock Seng Hospital, Singapore 308433, Republic of Singapore [S. Y. T.]; and Department of General Surgery, Singapore General Hospital, Singapore, Republic of Singapore [W. K. W.]
Comparative genomic hybridization (CGH), microsatellite instability (MSI) assays, and expression microarrays were used to molecularly subclassify a common set of gastric tumor samples. We identified a number of novel genomic aberrations associated with gastric cancer and discovered that gastric tumors could be grouped by their expression profiles into three broad classes: "tumorigenic," "reactive," and "gastric-like." Patients with gastric-like tumors exhibited a significantly better overall survival than patients belonging to the other two classes (P < 0.05). A novel supervised learning methodology for multiclass prediction was used to identify optimal predictor gene sets that accurately predicted the class of an unknown tumor sample. These predictor sets may prove useful in the development of new diagnostic applications for gastric cancer staging and prognostication.
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