Literature DB >> 31353030

The Value of Plasma-Based MicroRNAs as Diagnostic Biomarkers for Ovarian Cancer.

Weiwei Wang1, Yin Yin2, Xia Shan3, Xin Zhou4, Ping Liu4, Quan Cao1, Danxia Zhu5, JinYing Zhang6, Wei Zhu7.   

Abstract

BACKGROUND: Ovarian cancer (OC) is one of the most threatening diseases among women in the world. Plasma microRNAs (miRNAs) may serve as promising diagnostic biomarkers for patients with OC.
MATERIALS AND METHODS: Using quantitative reverse transcription polymerase chain reaction (qRT-PCR) based on Exiqon panel, we identified 27 differentially expressed miRNAs from 2 OC pool samples and 1 normal control (NC) pool in the initial screening phase. Then we further validated the identified miRNAs through the training (32 OC vs. 34 NCs) and validation stages (69 OC vs. 66 NCs) using qRT-PCR. The expression levels of the miRNAs were also assessed in tissues and exosomes.
RESULTS: Five plasma miRNAs (miR-205-5p, miR-145-5p, miR-10a-5p, miR-346 and miR-328-3p) were significantly overexpressed in OC in comparison with NCs. The areas under the receiver operating characteristic curve of the 5-miRNA panel were 0.788 for the training stage and 0.763 for the validation stage. The level of miR-205-5p has significantly different expression in patients with well-moderate histological grade compared with those with a poor grade (P = 0.012). The expression levels of the 5 miRNAs were also significantly upregulated in the exosomes of OC plasma samples (32 OC vs. 32 NCs). However, the expression of the 4 miRNAs (miR-145-5p, miR-10a-5p, miR-346 and miR-328-3p) was significantly lower in tumor samples than in normal tissues (22 OC vs. 22 NCs).
CONCLUSIONS: The 5 plasma miRNAs may be noninvasive diagnostic biomarkers of OC. The plasma miR-205-5p level may reflect the change trend of the histological grade of OC patients.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Biomarker; Diagnosis; MicroRNA; Ovarian cancer; Quantitative reverse transcription polymerase chain reaction

Year:  2019        PMID: 31353030     DOI: 10.1016/j.amjms.2019.07.005

Source DB:  PubMed          Journal:  Am J Med Sci        ISSN: 0002-9629            Impact factor:   2.378


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