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Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation
Maria Isabella Sereni1, Elisa Baldelli, Guido Gambara
1Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA, USA; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
Abstract:
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.
Insights
Epithelial ovarian carcinoma (EOC) may be better classified by protein signaling networks than histology. Clear cell subtype (CCC) shows distinct signaling, suggesting a new characterization approach for this deadly cancer.
Area of Science:
- Oncology
- Molecular Biology
- Biochemistry
Background:
- Epithelial ovarian carcinoma (EOC) has a poor 5-year survival rate of 30%.
- Current classification relies on histology, which may not fully capture underlying biological mechanisms.
- Protein signaling pathways play a crucial role in cancer development and progression.
Purpose of the Study:
- To explore protein signaling activation mapping in EOC.
- To determine if EOC can be redefined based on activated protein signaling networks.
- To compare signaling profiles across different EOC histotypes.
Main Methods:
- Laser capture microdissection (LCM) isolated tumor cells from 72 EOCs.
- Reverse-phase protein microarray analyzed 117 protein drug targets.
- Unsupervised hierarchical clustering and ANOVA identified signaling patterns and differences.
Main Results:
- Unsupervised analysis revealed five distinct pathway-driven clusters irrespective of histology.
- Clear cell carcinoma (CCC) demonstrated a unique signaling network.
- CCC activation included EGFR, Syk, HER2/ErbB2, and SHP2.
Conclusions:
- Histological classification alone is insufficient for characterizing EOC's protein signaling.
- CCC exhibits distinct signaling, warranting further investigation.
- Functional signaling activation mapping could offer a more precise EOC characterization.
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