Dr. Mark Burkard on advances in breast cancer genomics needed to optimize treatment

Dr. Mark Burkard

Mark Burkard, MD, PhD, associate professor, Hematology, Medical Oncology and Palliative Care, was interviewed about his views on the genetic landscape of breast cancer in OncLive, a media outlet for oncology professionals. 

Expanding on his presentation during the 2017 OncLive State of the Science Summit on Metastatic Breast Cancer, Dr. Burkard discussed the challenges and promise of genomic testing to identify rare subtypes. 

“One of the biggest and most exciting points is that genomic analyses of cancers, which are available to every oncologist in the United States right now, can profoundly help some patients,” he said.

Dr. Burkard placed his remarks in context by explaining that his use of the term "genetics" refers to "all of the genes that make a cancer different from the rest of the person." Identifying these differences at the molecular level is proving to be both powerful and complicated, due to the tremendous diversity of genomics in human breast cancers. 

"The incredibly exciting but frustrating thing of what we have discovered in the last decade is that almost every cancer is a little bit different. If you are trying to find another patient like the one in front of you to help them and know what’s going on, you have to sometimes look at hundreds of patients with breast cancer—and that’s a problem we need to somehow solve in the future," said Dr. Burkard.

Being able to share information about patients will be critical, says Dr. Burkard. "This is so that when 'Miss Jones' walks into the clinic one day and you have all of this genomic information, you say, 'Aha! You have this rare subtype of cancer that only 0.2 percent of people have.' You can find those 0.2 percent of people and figure out what happened to them and use that information to help her. That is something we and other people are working on."

Dr. Burkard also discussed the use of genomic testing in triple-negative breast cancer, mechanisms by which tumors become resistant to treatment, and challenges in subtyping.

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