A method for predicting which ovarian cancer patients are unlikely to benefit from chemotherapy was discovered by researchers from the Icahn School of Medicine at Mount Sinai in New York City, according to a study published in Cell Aug. 3.
Mount Sinai investigators used machine learning tools and a proteogenomic strategy to identify a 64-protein signature that predicted which tumors didn't respond to first-line platinum-based therapy. This study analyzed 242 HGSOC tumor samples from patients who responded and did not respond to chemotherapy.
"The work also implicates possible therapeutic targets for these patients," according to an Aug. 3 Mount Sinai news release.
More than 185,000 patients die from epithelial ovarian cancer each year; 60 percent of these deaths are caused by HGSOC. The mortality rate for this disease has not improved in the past four decades.
"Currently, there’s no way to distinguish refractory cases, leading some patients to unnecessarily experience the adverse effects of platinum-based chemotherapy without the benefits," the news release said.