期刊
BMC CANCER
卷 12, 期 -, 页码 -出版社
BMC
DOI: 10.1186/1471-2407-12-627
关键词
Biomarker; Serum microRNA; miR-200; miR-103; Serous ovarian cancer
类别
资金
- University of Sydney Cancer Research Fund, Australia
- University of Sydney Australian Postgraduate Award
- Cancer Institute NSW, Australia
- Northern Translational Cancer Research Unit
- Australian Research Council
Background: There is a critical need for improved diagnostic markers for high grade serous epithelial ovarian cancer (SEOC). MicroRNAs are stable in the circulation and may have utility as biomarkers of malignancy. We investigated whether levels of serum microRNA could discriminate women with high-grade SEOC from age matched healthy volunteers. Methods: To identify microRNA of interest, microRNA expression profiling was performed on 4 SEOC cell lines and normal human ovarian surface epithelial cells. Total RNA was extracted from 500 mu L aliquots of serum collected from patients with SEOC (n = 28) and age-matched healthy donors (n = 28). Serum microRNA levels were assessed by quantitative RT-PCR following preamplification. Results: microRNA (miR)-182, miR-200a, miR-200b and miR-200c were highly overexpressed in the SEOC cell lines relative to normal human ovarian surface epithelial cells and were assessed in RNA extracted from serum as candidate biomarkers. miR-103, miR-92a and miR-638 had relatively invariant expression across all ovarian cell lines, and with small-nucleolar C/D box 48 (RNU48) were assessed in RNA extracted from serum as candidate endogenous normalizers. No correlation between serum levels and age were observed (age range 30-79 years) for any of these microRNA or RNU48. Individually, miR-200a, miR-200b and miR-200c normalized to serum volume and miR-103 were significantly higher in serum of the SEOC cohort (P < 0.05; 0.05; 0.0005 respectively) and in combination, miR-200b + miR-200c normalized to serum volume and miR-103 was the best predictive classifier of SEOC (ROC-AUC = 0.784). This predictive model (miR-200b + miR-200c) was further confirmed by leave one out cross validation (AUC = 0.784). Conclusions: We identified serum microRNAs able to discriminate patients with high grade SEOC from age-matched healthy controls. The addition of these microRNAs to current testing regimes may improve diagnosis for women with SEOC.
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