Using advanced machine learning techniques, researchers analyzed thousands of breast tissue samples to detect a phenomenon called “stromal disruption.” This refers to changes in the supportive tissue surrounding breast cells, including signs of inflammation and immune activity. These changes were found not only in cancerous tissue, but also in normal and benign breast conditions.
The study, which examined data from over 9,000 women, found that stromal disruption was strongly linked to known risk factors for aggressive breast cancer, such as younger age, obesity, having multiple children, being Black, and having a family history of the disease.
Importantly, women with benign breast disease who showed signs of stromal disruption were four times more likely to develop high-grade breast cancer and did so about three years earlier than those without these tissue changes.
The findings also revealed that stromal disruption was associated with worse outcomes in patients with estrogen receptor-positive breast cancer, a common subtype. This suggests that these tissue changes may play an active role in how aggressive breast cancers develop and progress.
Researchers say this discovery opens the door to new ways of identifying women at higher risk and tailoring prevention or treatment strategies that focus on the breast tissue environment, not just the cancer cells themselves.