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. 2006 May 1;12(9):2788-94.
doi: 10.1158/1078-0432.CCR-05-1551.

Prognostic DNA methylation biomarkers in ovarian cancer

Susan H Wei  1 , Curtis Balch, Henry H Paik, Yoo-Sung Kim, Rae Lynn Baldwin, Sandya Liyanarachchi, Lang Li, Zailong Wang, Joseph C Wan, Ramana V Davuluri, Beth Y Karlan, Gillian Gifford, Robert Brown, Sun Kim, Tim H-M Huang, Kenneth P Nephew
Affiliations

Prognostic DNA methylation biomarkers in ovarian cancer

Susan H Wei et al. Clin Cancer Res. .

Abstract

Purpose: Aberrant DNA methylation, now recognized as a contributing factor to neoplasia, often shows definitive gene/sequence preferences unique to specific cancer types. Correspondingly, distinct combinations of methylated loci can function as biomarkers for numerous clinical correlates of ovarian and other cancers.

Experimental design: We used a microarray approach to identify methylated loci prognostic for reduced progression-free survival (PFS) in advanced ovarian cancer patients. Two data set classification algorithms, Significance Analysis of Microarray and Prediction Analysis of Microarray, successfully identified 220 candidate PFS-discriminatory methylated loci. Of those, 112 were found capable of predicting PFS with 95% accuracy, by Prediction Analysis of Microarray, using an independent set of 40 advanced ovarian tumors (from 20 short-PFS and 20 long-PFS patients, respectively). Additionally, we showed the use of these predictive loci using two bioinformatics machine-learning algorithms, Support Vector Machine and Multilayer Perceptron.

Conclusion: In this report, we show that highly prognostic DNA methylation biomarkers can be successfully identified and characterized, using previously unused, rigorous classifying algorithms. Such ovarian cancer biomarkers represent a promising approach for the assessment and management of this devastating disease.

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