PAGE 9 OF 11 ampliﬁed very frequently in breast cancer and ovarian tumors. It is possible that MTSS1 loss is important to the tumor growth as suggested by its role in cytoskeletal rearrangement (62) and its correlation with the disease state (51), so that in order to ensure lack of transcription within a region of genomic ampliﬁcation the gene is silenced by methylation. It will be interesting to associate CGH data with methylation data and incorporate expres- sion analysis to identify genes that are methylated and suppressed and determine if they are ampliﬁed or deleted genomically. Of the genes identiﬁed, those that are functionally inter- esting should have their methylation validated by other means such as bisulﬁte sequencing or McrBC PCR. Those that pass can be functionally validated as candi- dates with possible tumor-suppressive activity. In conclu- sion, we have developed a powerful method to proﬁle genome-wide DNA methylation. We have demonstrated that there is very low system noise from either the repre- sentational process or the labeling and hybridization. We then legitimatized the method’s ability to detect methyla- tion by bisulﬁte sequence validating over 15 fragments. We went on to analyze a number of samples that have been analyzed by others either by bisulﬁte sequencing or by other genome-wide approaches for methylation detec- tion (43,45). In the case of Maeta et al., we have validated speciﬁc methylation events and in the case of Sato et al. we have reproduced the majority of their ﬁndings using our methodology. We then used this method to develop meth- ods for the analysis of tumors with unmatched normals, which will be of interest to the greater community since many tumor banks do not have matched normals. We plan on using this methodology to identify methylation events that correlate to clinical parameters to determine if tumor sub-classiﬁcation can be achieved, markers from this type of analysis being very valuable. In addition, this methodology will have utility in the study of other pathol- ogies, such as imprinting, development, or tissue speciﬁ- city, which all are aﬀected by epigenetic modiﬁcations. SUPPLEMENTARY DATA Supplementary Data are available at NAR Online. ACKNOWLEDGEMENTS We thank Scott Powers, Scott Lowe, Michael Wigler and Michael Zhang for critical comments on the manuscript. We also thank Christopher Johns for assistance in design of the arrays. Some tumor samples were supplied by the Cooperative Human Tissue Network, which is funded by the National Cancer Institute. Other investigators may have received samples from these same tissues. FUNDING National Institutes of Health and National Cancer Institute [K01CA93634-01 to R.L.]; Department of Defense [W81XWH-05-1-0068 to R.L.] as well as by grants awarded to Michael Wigler from the Simons Nucleic Acids Research, 2009, Vol. 37, No. 12 e89 Foundation and the Breast Cancer Research Foundation. Funding for open access charge: awarded to to RL and Michael Wigler from Philips Research North America. Conﬂict of interest statement. None declared. REFERENCES 1. Gardiner-Garden,M. and Frommer,M. (1987) CpG islands in vertebrate genomes. J. Mol. Biol., 196, 261–282. 2. Takai,D. and Jones,P.A. (2002) Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proc. Natl Acad. Sci. USA, 99, 3740–3745. 3. Herman,J.G. and Baylin,S.B. (2003) Gene silencing in cancer in association with promoter hypermethylation. N. Engl. J. Med., 349, 2042–2054. 4. Baylin,S.B., Herman,J.G., Graﬀ,J.R., Vertino,P.M. and Issa,J.P. 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