Mysona D, et al. - Researchers analyzed 71 women at Augusta University diagnosed with ovarian cancer to determine the usefulness of a combined panel of protein biomarkers and clinical factors in predicting recurrence in serous ovarian cancer patients. Analysis of patient serum collected at remission using the SOMAscan array (n = 35) was done to measure levels of 1,129 proteins; confirmation of the best 26 proteins was done using Luminex assays in the same 35 patients and in an additional 36 patients as orthogonal validation. Using the elastic net algorithm, they combined all 26 proteins with clinical factors. They determined 10 components to predict progression-free survival and named this model as serous high grade ovarian cancer (SHOC) score and identified it as capable of predicting patient prognosis in remission.