Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation mapping: Implications for personalized cancer therapy

Epithelial ovarian carcinoma (EOC) is a deadly disease, with a 5-year survival of 30%. The aim of the study was to perform broad-scale protein signaling activation mapping to evaluate if EOC can be redefined based on activated protein signaling network architecture rather than histology. Tumor cells were isolated using laser capture microdissection (LCM) from 72 EOCs. Tumors were classified as serous (n = 38), endometrioid (n = 13), mixed (n = 8), clear cell (CCC; n = 7), and others (n = 6). LCM tumor cells were lysed and subjected to reverse-phase protein microarray to measure the expression/activation level of 117 protein drug targets. Unsupervised hierarchical clustering analysis was utilized to explore the overall signaling network. ANOVA was used to detect significant differences among the groups (p < 0.05). Regardless of histology, unsupervised analysis revealed five pathway-driven clusters. When the EOC histotypes were compared by ANOVA, only CCC showed a distinct signaling network, with activation of EGFR, Syk, HER2/ErbB2, and SHP2 (p = 0.0007, p = 0.0021, p < 0.0001, and p = 0.0410, respectively). The histological classification of EOC fails to adequately describe the underpinning protein signaling network. Nevertheless, CCC presents unique signaling characteristics compared to the other histotypes. EOC may need to be characterized by functional signaling activation mapping rather than pure histology.