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Cell Press, American Journal of Human Genetics, 3(86), p. 420-433, 2010

DOI: 10.1016/j.ajhg.2010.02.008

BioMed Central, Breast Cancer Research, Suppl 1(12), p. O4

DOI: 10.1186/bcr2495

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DNA Methylome of Familial Breast Cancer Identifies Distinct Profiles Defined by Mutation Status

Journal article published in 2010 by Jm M. Flanagan, Sibylle Cocciardi, S. Kugler, Nic Waddell, Cn N. Johnstone, Anna Marsh, Stephen Henderson, Peter Simpson, kConFab Investigators, Leonard da Silva, Kumkum Khanna, Melissa Brown, Sunil Lakhani ORCID, Chris Boshoff, Georgia Chenevix-Trench and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

It is now understood that epigenetic alterations occur frequently in sporadic breast carcinogenesis, but little is known about the epigenetic alterations associated with familial breast tumors. We performed genome-wide DNA-methylation profiling on familial breast cancers (n = 33) to identify patterns of methylation specific to the different mutation groups (BRCA1, BRCA2, and BRCAx) or intrinsic subtypes of breast cancer (basal, luminal A, luminal B, HER2-amplified, and normal-like). We used methylated DNA immunoprecipitation (MeDIP) on Affymetrix promoter chips to interrogate methylation profiles across 25,500 distinct transcripts. Using a support vector machine classification algorithm, we demonstrated that genome-wide methylation profiles predicted tumor mutation status with estimated error rates of 19016 (BRCA1), 31% (BRCA2), and 36% (BRCAx) but did not accurately predict the intrinsic subtypes defined by gene expression. Furthermore, using unsupervised hierarchical Clustering, we identified a distinct subgroup of BRCAx tumors defined by methylation profiles. We validated these findings in the 33 tumors in the test set, as well as in an independent validation set of 47 formalin-fixed, paraffin-embedded familial breast tumors, by pyrosequencing and Epityper. Finally, gene-expression profiling and SNP CGH array previously performed on the same samples allowed full integration of methylation, gene-expression, and copy-number data sets, revealing frequent hypermethylation of genes that also displayed loss of heterozygosity, as well as of genes that show copy-number gains, providing a potential mechanism for expression dosage compensation. Together, these data show that methylation profiles for familial breast cancers are defined by the mutation status and are distinct from the intrinsic subtypes.