Objectives: To identify angiogenic biomarkers associated with tumor angiogenesis and clinical outcome in high-grade serous ovarian cancer (HGSC).
Methods: 51 HGSC samples were analyzed using Affymetrix HG-U133A microarray. Microvessel density (MVD) counts were determined using CD31 and CD105. Associations between mRNA expression levels and overall survival were assessed using rank score statistic. Effect size was estimated as a hazard ratio (HR) under a proportional hazard model. The Storey q-value method was used to account for multiple testing within the false-discovery rate (FDR) framework. Publicly available databases including TCGA and GSE were used for external confirmation.
Results: Thirty-one angiogenic-related genes were significantly associated with survival (q≤0.05). Of these 31 genes, 4 were also associated with outcome in the TCGA data: AKT1 (q=0.02; TCGA p=0.01, HR=0.8), CD44 (q=0.003; TCGA p=0.05, HR=0.9), EPHB2 (q=0.01; TCGA p=0.05, HR=1.2), and ERBB2 (q=0.02; TCGA p=0.05, HR=1.2). While 5 were associated with outcome in the GSE database: FLT1 (q=0.03; GSE26712 p=0.01, HR=3.1); PF4 (q=0.02; GSE26712 p=0.01, HR=3.0); NRP1 (q=0.02; GSE26712 p<0.04, HR>1.4); COL4A3 (q=0.04; GSE26712 p=0.03, HR=1.3); and ANGPTL3 (q=0.02; GSE14764 p=0.02, HR=1.5). High AKT1 and CD44 were associated with longer survival. In contrast, high expression of EPHB2, ERBB2, FLT1; PF4, NRP1, COL4A3, and ANGPTL3 were associated with shorter survival. CD105-MVD and CD31-MVD were not significantly associated with angiogenic gene expression.
Conclusions: Thirty-one angiogenic-related genes were associated with survival in advanced HGSC and nine of these genes were confirmed in independent publicly available databases.
Keywords: Angiogenesis; Biomarkers; Gene expression; High-grade serous ovarian carcinoma; Overall survival.
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