Molecular data helps specialists predict chance of breast cancer recurrence
Molecular data from a patient’s breast cancer cells can help predict if they are at an increased risk for recurrence, according to new findings published in Nature.
The research, a collaboration of the Stanford University School of Medicine and the Cancer Research UK Cambridge Institute, built on previous work published by the team from Stanford and included tracking the medical histories of more than 3,000 breast cancer patients. It revealed that approximately one in four patients with ER-positive, HER2-negative tumors are at a higher risk of recurrence for up to 20 years after diagnosis.
“We found that about 25 percent of women whose tumors express the estrogen receptor and not HER2 have an exceedingly high risk of late distant relapse and account for the vast majority of these events,” co-author Christina Curtis, PhD, assistant professor of medicine and genetics at Stanford and co-director of the Stanford Cancer Institute’s Molecular Tumor Board, said in a prepared statement. “These are the women who seem to be cured but then present with systemic disease many years later. Until now, there has been no good way to identify this subset of women who might benefit from ongoing screening or treatment.”
Another subgroup of patients with triple-negative breast tumors, according to the team’s work, is unlikely to see its cancer return after five years.
“A clinical challenge in breast cancer management has been distinguishing which tumors pose greatest risk of late recurrence,” Harold Burstein, MD, PhD, associate professor of medicine at Harvard Medical School in Boston, said in the same statement. Burstein was not an author of the study. “This important scientific paper identifies molecular features that determine the timing of cancer recurrence. In the future, this type of genomic classification should help us separate patients who remain at jeopardy—and might warrant additional or ongoing treatment—and those who do not.”
The research team’s next step is to conduct clinical trials to investigate if these findings can help improve patient outcomes.
Michael has more than 18 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.