Researchers developed a blood test that detects early-stage breast cancer with 95 percent accuracy and predicts recurrence risk with 81 percent accuracy.
An international team has developed a liquid biopsy that spots early-stage breast cancer and assesses the likelihood of disease recurrence, according to a study published in Nature.
The method analyzes chemical markers on free-floating nucleosomes—segments of DNA wrapped around proteins—released into the bloodstream by dying cells.
Investigators attached fluorescent markers to dozens of different epigenetic tags and examined them using single-molecule microscopy.
Researchers analyzed tumor tissue collected from patients undergoing surgical removal to establish a baseline.
“Once the tumor is removed, there is only a narrow window of time during which the epigenetic tags remain intact. So whenever a surgery began, the doctors called me. I quickly transported the biopsy sample on ice from the hospital to the laboratory, and we began analyzing it that same day,” said Noa Furth, a researcher at the Weizmann Institute of Science.
Ron, a physicist at the Hebrew University, approached the mapping as an experimental physics problem, using computational tools to isolate diagnostic patterns.
The team tested the approach on blood samples obtained from 77 women treated at the Mayo Clinic in Florida who had been monitored for at least five years, alongside samples from 30 healthy women.
Artificial intelligence models trained on these samples achieved 95 percent accuracy in identifying early-stage cancer when the tumor was localized and measured no more than two centimeters.
Routine mammography reduces mortality by 22 percent, but dense breast tissue can obscure tumors.
Shema said that the blood test maintained diagnostic performance regardless of tissue density.
The database was expanded to 188 patients with help from Sheba and Kaplan medical centers.
The test also addresses the challenge of recurrence, which affects 20 percent to 40 percent of patients diagnosed early.
Laboratory models of breast cancer demonstrated that aggressive cell subpopulations consistently emerged from nonaggressive cells.
The differences appear to be primarily epigenetic. When we grew breast cancer models in the laboratory from nonaggressive cells, a group of aggressive cells always emerged at some point. Shema said
Ron described how tracking this signature in blood samples correlated with clinical outcomes.
“When we searched the blood samples for the epigenetic signature of the aggressive cell population we had identified in the tumors, we found that the more prevalent this signature was, the greater the risk of the disease returning,” Ron said.
Combining this signature with additional epigenetic markers allowed researchers to predict recurrence with 81 percent accuracy.