Identification of stably expressed microRNAs in plasma from high-grade serous ovarian carcinoma and benign tumor patients
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Published:2023-11-07
Issue:12
Volume:50
Page:10235-10247
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ISSN:0301-4851
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Container-title:Molecular Biology Reports
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language:en
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Short-container-title:Mol Biol Rep
Author:
Petersen Patrick H.D., Lopacinska-Jørgensen Joanna, Høgdall Claus K., Høgdall Estrid V.ORCID
Abstract
Abstract
Background
Ovarian cancer is a lethal gynecological cancer and no reliable minimally invasive early diagnosis tools exist. High grade serous ovarian carcinoma (HGSOC) is often diagnosed at advanced stages, resulting in poorer outcome than those diagnosed in early stage. Circulating microRNAs have been investigated for their biomarker potential. However, due to lack of standardization methods for microRNA detection, there is no consensus, which microRNAs should be used as stable endogenous controls. We aimed to identify microRNAs that are stably expressed in plasma of HGSOC and benign ovarian tumor patients.
Methods and results
We isolated RNA from plasma samples of 60 HGSOC and 48 benign patients. RT-qPCR was accomplished with a custom panel covering 40 microRNAs and 8 controls. Stability analysis was performed using five algorithms: Normfinder, geNorm, Delta-Ct, BestKeeper and RefFinder using an R-package; RefSeeker developed by our study group [1]. Among 41 analyzed RNAs, 13 were present in all samples and eligible for stability analysis. Differences between stability rankings were observed across algorithms. In HGSOC samples, hsa-miR-126-3p and hsa-miR-23a-3p were identified as the two most stable miRNAs. In benign samples, hsa-miR-191-5p and hsa-miR-27a-3p were most stable. In the combined HGSOC and benign group, hsa-miR-23a-3p and hsa-miR-27a-3p were identified by both the RefFinder and Normfinder analysis as the most stable miRNAs.
Conclusions
Consensus regarding normalization approaches in microRNA studies is needed. The choice of endogenous microRNAs used for normalization depends on the histological content of the cohort. Furthermore, normalization also depends on the algorithms used for stability analysis.
Funder
Royal Library, Copenhagen University Library
Publisher
Springer Science and Business Media LLC
Subject
Genetics,Molecular Biology,General Medicine
Reference60 articles.
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