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DNA methylation signatures for breast cancer classification and prognosis

期刊

GENOME MEDICINE
卷 4, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/gm325

关键词

DNA methylation; epigenetics; hypermethylation; hypomethylation; breast cancer metastasis; breast cancer stages; whole-genome methods

资金

  1. Canadian Institute for Health Research
  2. National Cancer Institute of Canada
  3. Ministere du Developpement Economique, de l'Innovation et de l'Exportation (MDEIE) program of the Government of Quebec [215004]
  4. Sackler Program in Epigenetics and Psychobiology at McGill University
  5. Canadian Institute for Advanced Research

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Changes in gene expression that reset a cell program from a normal to a diseased state involve multiple genetic circuitries, creating a characteristic signature of gene expression that defines the cell's unique identity. Such signatures have been demonstrated to classify subtypes of breast cancers. Because DNA methylation is critical in programming gene expression, a change in methylation from a normal to diseased state should be similarly reflected in a signature of DNA methylation that involves multiple gene pathways. Whole-genome approaches have recently been used with different levels of success to delineate breast-cancer-specific DNA methylation signatures, and to test whether they can classify breast cancer and whether they could be associated with specific clinical outcomes. Recent work suggests that DNA methylation signatures will extend our ability to classify breast cancer and predict outcome beyond what is currently possible. DNA methylation is a robust biomarker, vastly more stable than RNA or proteins, and is therefore a promising target for the development of new approaches for diagnosis and prognosis of breast cancer and other diseases. Here, I review the scientific basis for using DNA methylation signatures in breast cancer classification and prognosis. I discuss the role of DNA methylation in normal gene regulation, the aberrations in DNA methylation in cancer, and candidate-gene and whole-genome approaches to classify breast cancer subtypes using DNA methylation markers.

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