Abstract
Following primary debulking surgery, the presence of a residual tumor mass is one of the most important prognostic factors in ovarian cancer. In a previous study, we established the OVSCORE, an algorithm to predict surgical outcome, based on the clinical factors of nuclear grading and ascitic fluid volume, plus the cancer biomarkers, kallikrein-related peptidases (KLKs), KLK6 and KLK13. In the present study, OVSCORE performance was tested in an independent ovarian cancer patient cohort consisting of 87 patients. The impact of KLKs, KLK5, 6, 7 and 13 and other clinical factors on patient prognosis and outcome was also evaluated. The OVSCORE proved to be a strong and statistically significant predictor of surgical success in terms of area under the receiver operating characteristic curve (ROC AUC, 0.777), as well as positive and negative predictive value in this independent study group. KLK6 and 13 individually did not show clinical relevance in this cohort, but two other KLKs, KLK5 and KLK7, were associated with advanced FIGO stage, higher nuclear grade and positive lymph node status. In the multivariate Cox regression analysis for overall survival (OS), KLK7 had a protective impact on OS. This study confirms the role of KLKs in ovarian cancer for surgical success and survival, and validates the novel OVSCORE algorithm in an independent collective. As a key clinical application, the OVSCORE could aid gynecological oncologists in identifying those ovarian cancer patients unlikely to benefit from radical surgery who could be candidates for alternative therapeutic approaches.