Two-pronged approach may improve personalized breast cancer treatment

Researchers from multiple institutions have combined two methods of cancer detection to develop a new way of personalizing breast cancer treatment.

The study, published in Nature Communications, included researchers from Baylor College of Medicine, Washington University School of Medicine in St. Louis and the Broad Institute of MIT and Harvard. By analyzing the proteins responsible for tumor growth in patient-derived xenografts, the team identified which treatment methods may work for individual patients.

"Here we study the problem of how to design more effective cancer treatments with a two-pronged approach," said co-senior author Matthew Ellis, MB, PhD, professor and director of the Lester and Sue Smith Breast Center and McNair Scholar at Baylor. "We combine patient-derived xenografts and proteogenomic integration."

Using patient-derived xenografts of human tumors in mice, the method allowed researchers to view how tumors reacted to drug treatments in living samples. When paired with proteogenomic integration, the analysis of cancer proteins responsible for tumor growth allowed researchers to pinpoint exactly which cells to target.

The study used mass spectrometry to identify proteins in 24 patient-derived xenografts of breast cancer. The study identified 10,000 proteins from the tumors. By targeting these proteins, specific treatments could be given to stop the growth of tumors.

"Eventually, with this new approach scientists will be able to answer questions such as why a certain drug that induced one tumor to shrink in one patient did not affect the growth of a similar tumor in another patient," said Ellis. "The idea behind this approach is to find out what are the driving pathways of each person's cancer. Once we know these pathways, the next step is to use drugs to interrupt these pathways and lead to outcomes that are better than giving patients non-specific therapy. The mouse work is promising enough to adapt these technologies for real time analysis of patient samples so that clinical trials can be designed to test this new diagnostic and drug selection approach. The National Cancer Institute has agreed to invest in this next phase of the project."