This Article Full Text Full Text (PDF) Supplementary Data Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by McCabe, M. T. Articles by Vertino, P. M. Search for Related Content PubMed PubMed Citation Articles by McCabe, M. T. Articles by Vertino, P. M.

A Multifactorial Signature of DNA Sequence and Polycomb Binding Predicts Aberrant CpG Island Methylation

¹ Department of Radiation Oncology and ² Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia; ³ School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia

Requests for reprints: Paula M. Vertino, Emory University School of Medicine, 1365C Clifton Road, Room 4086 Atlanta, GA 30322. Phone: 404-778-3119; Fax: 404-778-5530; E-mail: pvertin{at}emory.edu.

Key Words: DNA methylation • supervised learning • DNMT1 • PRC2 • polycomb • H3K27me3

Aberrant CpG island methylation is associated with transcriptional silencing of regulatory genes in human cancer. Although most CpG islands remain unmethylated, a subset accrues aberrant methylation in cancer via unknown mechanisms. Previously, we showed that CpG islands differ in their intrinsic propensity towards hypermethylation. We developed a classifier (PatMAn) based on the frequencies of seven DNA sequence patterns that discriminated methylation-prone (MP) and methylation-resistant (MR) CpG islands. Here, we report on the genome-wide application and direct testing of PatMAn in cancer. Although trained on data from a cell culture model of de novo methylation involving the overexpression of DNMT1, PatMAn accurately predicted CpG islands at increased risk of hypermethylation in cancer cell lines and primary tumors. Analysis of CpG islands predicted to be MP revealed a strong association with embryonic targets of polycomb-repressive complex 2 (PRC2), indicating that PatMAn predicts not only aberrant methylation, but also PRC2 binding. A second classifier (SUPER-PatMAn) that integrates the seven PatMAn DNA patterns with SUZ12 enriched regions as a marker of PRC2 occupancy showed improved performance (prediction accuracy, 81–88%). In addition to many non-PRC2 targets, SUPER-PatMAn identified a subset of PRC2 targets that were more likely to be hypermethylated in cancer. Genome-wide, CpG islands predicted to be MP were enriched in genes known to undergo hypermethylation in cancer, genes functioning in transcriptional regulation, and components of developmental pathways. These findings show that hypermethylation of certain gene loci is controlled in part by an underlying susceptibility influenced by both local sequence context and trans-acting factors. [Cancer Res 2009;69(1):282–91]

This article has been cited by other articles:

				W. G. Nelson, A. M. De Marzo, and S. Yegnasubramanian Epigenetic Alterations in Human Prostate Cancers Endocrinology, September 1, 2009; 150(9): 3991 - 4002. [Abstract] [Full Text] [PDF]

				M. T. McCabe, J. C. Brandes, and P. M. Vertino Cancer DNA Methylation: Molecular Mechanisms and Clinical Implications Clin. Cancer Res., June 15, 2009; 15(12): 3927 - 3937. [Abstract] [Full Text] [PDF]