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• W1995911541 abstract "We investigated whether prognostic information is reflected in the expression patterns of ovarian carcinoma samples. RNA obtained from seven FIGO stage I without recurrence, seven platin-sensitive advanced-stage (III or IV), and six platin-resistant advanced-stage ovarian tumors was hybridized on a complementary DNA microarray with 21,372 spotted clones. The results revealed that a considerable number of genes exhibit nonaccidental differential expression between the different tumor classes. Principal component analysis reflected the differences between the three tumor classes and their order of transition. Using a leave-one-out approach together with least squares support vector machines, we obtained an estimated classification test accuracy of 100% for the distinction between stage I and advanced-stage disease and 76.92% for the distinction between platin-resistant versus platin-sensitive disease in FIGO stage III/IV. These results indicate that gene expression patterns could be useful in clinical management of ovarian cancer." @default.
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• W1995911541 date "2006-02-01" @default.
• W1995911541 modified "2023-10-17" @default.
• W1995911541 title "Predicting the clinical behavior of ovarian cancer from gene expression profiles" @default.
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• W1995911541 doi "https://doi.org/10.1111/j.1525-1438.2006.00321.x" @default.
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