Deep sequencing of breast cancer tumors predict outcomes after single dose of therapy

Results showed that through deep genome sequencing, a reduction in the most commonly mutated genes in breast cancer could be observed after just one dose of preoperative therapy. Deep sequencing is a process that involves sequencing the same region multiple times to identify mutations within tumors that have an importance in cancer evolution. These new findings were presented during the 2013 San Antonio Breast Cancer Symposium.

"Genomics is the new frontier of cancer research, and this study shows that we may be able to accurately determine what treatment methods will and will not be effective for individual patients after just one dose of medicine," said Lyndsay Harris, MD, study investigator and Director, Breast Cancer Program, UH Seidman Cancer Center and Professor of Medicine at Case Western Reserve University School of Medicine. "The ability to understand potential clinical outcomes for patients earlier in the treatment process would provide physicians with better opportunity to personalize patients' medicines according to their own tumor responses."

More than 209,000 patients in the U.S. are diagnosed with breast cancer each year. The anticipated outcome of studying the genetic makeup of breast cancer patients is to determine who will benefit most from certain drug therapies and to use that information to create a personalized treatment plan for each patient involved. Dr. Harris and team are currently integrating whole genome profiles with deep sequencing data as they spearhead a new study at UH Seidman Cancer Center to validate these initial findings presented in San Antonio.