DNA methylome of familial breast cancer identifies distinct profiles defined by mutation status

Flanagan, James M., Cocciardi, Sibylle, Waddell, Nic, Johnstone, Cameron N., Marsh, Anna, Henderson, Stephen, Simpson, Peter, da Silva, Leonard, kConFab Investigators, Khanna, Kumkum, Lakhani, Sunil, Boshoff, Chris, Chenevix-Trench, Georgia, Brown, Melissa, Cummings, Margaret and Edwards, Stacey (2010) DNA methylome of familial breast cancer identifies distinct profiles defined by mutation status. American Journal of Human Genetics, 86 3: 420-433. doi:10.1016/j.ajhg.2010.02.008

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Author Flanagan, James M.
Cocciardi, Sibylle
Waddell, Nic
Johnstone, Cameron N.
Marsh, Anna
Henderson, Stephen
Simpson, Peter
da Silva, Leonard
kConFab Investigators
Khanna, Kumkum
Lakhani, Sunil
Boshoff, Chris
Chenevix-Trench, Georgia
Brown, Melissa
Cummings, Margaret
Edwards, Stacey
Title DNA methylome of familial breast cancer identifies distinct profiles defined by mutation status
Journal name American Journal of Human Genetics   Check publisher's open access policy
ISSN 0002-9297
Publication date 2010-03-12
Sub-type Article (original research)
DOI 10.1016/j.ajhg.2010.02.008
Volume 86
Issue 3
Start page 420
End page 433
Total pages 14
Place of publication Cambridge, MA, United States
Publisher Elsevier
Collection year 2011
Language eng
Formatted 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 19% (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. © 2010 The American Society of Human Genetics.
Keyword Estrogen-Receptor
Methylation Patterns
Promoter DNA
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: UQ Centre for Clinical Research Publications
Official 2011 Collection
School of Medicine Publications
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Citation counts: TR Web of Science Citation Count  Cited 49 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 56 times in Scopus Article | Citations
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Created: Sun, 04 Apr 2010, 00:08:13 EST