ATLANTA, Oct. 5 (UPI) -- Researchers at the Georgia Institute of Technology have developed a predictive model that can provide doctors with an "invasiveness index" for cancer based on blood samples from individual patients, according to a new study.
The test is based on chemical expression by specific cells in the body that help cancer move from the breast to other parts of the body.
"We want women to have more information to make a personal decision beyond the averages calculated for an entire population," said Manu Platt, an associate professor at Georgia Tech University, in a press release. "We are using our systems biology tools and predictive medicine approaches to look at potential markers we could use to help us understand the risk each woman has. This would provide information for a more educated discussion of treatment options."
The researchers have been developing a method of measuring the variability in macrophage expression of four types of cathepsin, the cathepsin inhibitor cystatin C, and kinase activation levels, which are significant to the assistance of tumors to spread beyond the breast.
Using macrophages from monocytes donated by healthy women, the researchers tested the technique using a standard breast cancer cell line. Using a gel to simulate breast tissue, they measured the levels of protein expression by the macrophages against the number of cancer cells which invaded it.
To test it with real patients, the researchers obtained blood tests from 9 women being treated for breast cancer at DeKalb Medical Center in Atlanta, finding that their method correlated with the diagnoses their doctor had made.
In addition to testing he method further, Platt said the researchers will follow the 9 women for 5 years to determine if the test also was relevant to the potential for cancer recurrence.
"We are measuring at the level of activity of these intracellular enzymes and the ultimate activity of the proteases they produce that are not only the biomarkers of the tumor, but also help the tumor grow," Platt said. "Everything about us is different. Our genetics are different and our lifestyles are different, so clinicians have to make decisions in all that variability. All of those differences can be measured and captured in this output."
The study is published in Scientific Reports.