Researchers May Be Able to Identify Survival Rate of Breast Cancer Patients
Canadian researchers have reported that better understanding of how proteins interact in tumors could lead to new customized treatments for patients based on their symptoms.
“We approached cancer as a problem in how proteins communicate with each other — or how proteins interact with each other in networks,” Jeff Wrana of Mount Sinai Hospital in Toronto, who led a study published in the journal Nature Biotechnology, told Reuters Health.
Researchers examined “the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome,” they wrote.
While studying these interactomes in breast cancer tissue from about 350 women in the US and Europe, researchers found that survivors had a different organization of the interactome within the cancer cells than those who did not survive the disease.
Their study allowed them to accurately predict which patients would be able to survive breast cancer and which ones would not in 82 percent of patients based on their observed network of proteins.
“It could help to direct the appropriate therapies for individual patients.”
Researchers said their discovery suggests that the process could be used to help doctors of newly diagnosed patients know if a more aggressive treatment process may be needed.
According to Reuters, Mount Sinai Hospital has a patent on the process and the researchers have formed a Toronto-based company called DyNeMo Biosystems to explore commercial applications.
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