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Open Access Research article

Elevated levels of circulating microRNA-200 family members correlate with serous epithelial ovarian cancer

Casina WS Kan1, Michael A Hahn1, Gregory B Gard2, Jayne Maidens2, Jung Yoon Huh1, Deborah J Marsh1 and Viive M Howell1*

Author affiliations

1 Hormones and Cancer Division, Kolling Institute of Medical Research, University of Sydney E25, Royal North Shore Hospital, St Leonards, NSW, 2065, Australia

2 Department of Obstetrics and Gynecology, Royal North Shore Hospital, St Leonards, Australia

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Citation and License

BMC Cancer 2012, 12:627  doi:10.1186/1471-2407-12-627

Published: 28 December 2012

Abstract

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 μL 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.

Keywords:
Biomarker; Serum microRNA; miR-200; miR-103; Serous ovarian cancer