Novel functional proteomics approach to defining ovarian cancer molecular heterogeneity

5502 Background: A number of clinicopathologic risk factors are used for survival prediction and clinical decision-making in epithelial ovarian cancer (EOC). Information from novel technologies such as gene arrays has not had an impact on patient management. We studied EOC protein signaling profiles to determine if their addition to accepted clinicopathologic factors improves their accuracy in predicting individual patient outcomes. Methods: We applied a novel functional proteomics technology, reverse phase protein array (RPPA), to quantify expression and activation of 42 steroid and kinase signaling pathway proteins in 106 high-grade EOCs from patients with stages 1–4 tumors managed with surgery and platinum-based chemotherapy. Cox regression analysis and a novel committee modeling approach were used to study the impact of functional proteomics on patient outcomes. Results: In a Cox model using only clinical variables, stage and residual disease were significantly related to overall survival. By adding t...