Prognostic DNA Methylation Biomarkers in Ovarian Cancer
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...
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Published in | Clinical cancer research Vol. 12; no. 9; pp. 2788 - 2794 |
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Main Authors | , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Philadelphia, PA
American Association for Cancer Research
01.05.2006
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Subjects | |
Online Access | Get full text |
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Summary: | 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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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1078-0432 1557-3265 |
DOI: | 10.1158/1078-0432.CCR-05-1551 |