DNA methylation changes in murine breast adenocarcinomas allow the identification of candidate genes for human breast carcinogenesis

Deanna Acosta, Masako Suzuki, Diana Connolly, Reid F. Thompson, Melissa J. Fazzari, John M. Greally, Cristina Montagna

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Epigenetic inactivation due to aberrant promoter methylation is a key process in breast tumorigenesis. Murine models for human breast cancer have been established for nearly every important human oncogene or tumor suppressor gene. Mouse-to-human comparative gene expression and cytogenetic profiling have been widely investigated for these models; however, little is known about the conservation of epigenetic alterations during tumorigenesis. To determine if this key process in human breast tumorigenesis is also mirrored in a murine breast cancer model, we mapped cytosine methylation changes in primary adenocarcinomas and paired lung metastases derived from the polyomavirus middle T antigen mouse model. Global changes in methylcytosine levels were observed in all tumors when compared to the normal mammary gland. Aberrant methylation and associated gene silencing was observed for Hoxa7, a gene that is differentially methylated in human breast tumors, and Gata2, a novel candidate gene. Analysis of HOXA7 and GATA2 expression in a bank of human primary tumors confirms that the expression of these genes is also reduced in human breast cancer. In addition, HOXA7 hypermethylation is observed in breast cancer tissues when compared to adjacent tumor-free tissue. Based on these studies, we present a model in which comparative epigenetic techniques can be used to identify novel candidate genes important for human breast tumorigenesis, in both primary and metastatic tumors.

Original languageEnglish (US)
Pages (from-to)249-259
Number of pages11
JournalMammalian Genome
Volume22
Issue number3-4
DOIs
StatePublished - Apr 2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Genetics

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