Diagnostic and prognostic significance of miRNA signatures in tissues and plasma of endometrioid endometrial carcinoma patients
- 17 October 2012
- journal article
- research article
- Published by Wiley in International Journal of Cancer
- Vol. 132 (7), 1633-1645
- https://doi.org/10.1002/ijc.27840
Abstract
The aim of our study was to define tissue and plasma miRNA signatures, which could potentially serve as diagnostic and prognostic markers in endometrioid endometrial cancer (EEC) and to investigate miRNA profiles in regard to clinicopathological characteristics. Tissue and plasma samples were collected from 122 women (77 EEC and 45 controls). Expression profiling of 866 human miRNAs and 89 human viral miRNAs was performed in 24 samples and was followed by qPCR validation in 104 patients. Expression of 16 miRNAs was analyzed in 48 plasma samples. Microarray study revealed regulation of 21 miRNAs in EEC tissues comparing to normal endometrium. Altered expression of 17 miRNAs was confirmed by qPCR performed in 104 tissue samples. Seven miRNAs were upregulated and two were downregulated in EEC plasma samples. Expression of a number of miRNAs was associated with International Federation of Gynecology and Obstetrics stage, grade, relapse and nodal metastases. Two miRNA signatures: miR‐92a/miR‐410 and miR‐92a/miR‐205/miR‐410 classified tumor tissues with higher accuracy in comparison to single miRNAs (AUC: 0.977, 95% CI: 0.927–0.996 and 0.984, 95% CI: 0.938–0.999, respectively). miRNA signature composed of miR‐205 and miR‐200a predicted relapse with AUC of 0.854 (95% CI: 0.691–0.951). Tissue miRNA signatures were independent prognostic markers of overall (miR‐1228/miR‐200c/miR‐429, HR: 2.98) and progression‐free survival (miR‐1228/miR‐429, HR: 2.453). Plasma miRNA signatures: miR‐9/miR‐1228 and miR‐9/miR‐92a, classified EEC plasma samples with high accuracy yielding AUCs of 0.909 (95% CI: 0.789–973) and 0.913 (95% CI: 0.794–0.976), respectively. We conclude that miRNA signatures hold a great promise to become noninvasive biomarkers for early EEC detection and prognosis.Keywords
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