Cancer researchers studying 44 known genetic variants associated with breast cancer have found the way to identify why they increase cancer risk, opening the door to future therapeutic applications based on personalized medicine.
The findings, published online today ahead of print in Nature Genetics, (http://dx.doi.org/10.1038/NG.2416) fill a gap that will expand the reach of genetic profiling beyond merely screening, says principal investigator Dr. Mathieu Lupien, a scientist at Ontario Cancer Institute, the research arm of the Princess Margaret Cancer Centre at University Health Network. Dr. Lupien, who specializes in epigenetics in cancer, is also an Assistant Professor in the Department of Medical Biophysics, University of Toronto.
"Our work has identified the mechanisms altered by genetic risk variants in regions believed for a long time to be 'junk DNA'; that is, DNA outside the genes with no known function - until now. This moves us one step closer to translating genetic profiling into patient care and advancing personalized cancer medicine," says Dr. Lupien.
"We discovered that genetic variants promoting breast cancer are found in elements with a regulatory role that modulate genes expression," he says. The team discovered the changes affecting the activity of two well known drivers of breast cancer - the estrogen receptor ESR1 and the transcription factor FOXA1 - that work together in breast cancer cells. Dr. Lupien talks about this research at https://vimeo.com/49570739 .
Dr. Lupien and co-investigator Dr. Jason Moore, a computational biologist at Dartmouth Medical School in Lebanon, New Hampshire, developed a methodology that identified the target of genetic predisposition by merging existing maps of the genome - one cataloguing predisposition to breast cancer and others annotating the functional components from breast cancer cells.
"The pattern emerged revealing why genetic variants can promote breast cancer" says Dr. Lupien. "The beauty is that our methodology can be applied to any disease with known genetic predispositions. We anticipate it will be of broad benefit to other research."
Evo model set to transform synthetic biology and disease diagnosis