Using a novel proteogenomic strategy and a variety of machine learning tools, investigators from the Icahn School of Medicine at Mount Sinai and colleagues have identified a 64-protein signature that may predict a subset of ovarian cancer patients who are unlikely to respond to chemotherapy.
The multicenter study, published online August 3 in Cell [DOI#: 10.1016/j.cell.2023.07.004], reports on a pioneering analysis of chemo-refractoriness in high-grade serous ovarian cancer (HGSOC). The work also implicates possible therapeutic targets for these patients.