Identification of Stably Expressed Reference microRNAs in Epithelial Ovarian Cancer

Research output: Contribution to journalJournal articleResearchpeer-review

Documents

  • Fulltext

    Final published version, 1.83 MB, PDF document

Background/Aim: MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression and have been associated with the development of various cancers, including epithelial ovarian cancer (EOC). Accurate quantification of miRNA levels is important for determining their role in tumorigenesis and as biomarkers. Currently, U6 is widely used as a normalization control when investigating miRNAs in EOC; however, its variable expression across cancers has been reported. As only a few studies have been published to date on the identification of endogenous miRNA controls in EOC, our aim was to identify stable miRNAs based on global microarray profiling of 197 EOC patients and verify their stability in external datasets. Materials and Methods: We collected miRNA-microarray data from four datasets: the in-house “Pelvic Mass”, and three public datasets with primary EOC patients: The Cancer Genome Atlas, GSE47841, and GSE73581. The expression stability of endogenous control candidates was evaluated by their coefficient of variation. Results: All miRNA results in the used cohorts were produced by either Affymetrix or Agilent technologies, which show similar intra-platform patterns. Nonetheless, a clear difference in a cross-platform comparison was observed. We identified hsa-miR-92b-5p and hsa-miR-106b-3p as stable candidates shared between four datasets. Moreover, we investigated the stability performance of eight miRNAs that have been previously reported as stable endogenous controls in EOC and various performance was observed in four datasets. Conclusion: The selection of suitable endogenous miRNA normalization controls in EOC remains to be resolved, as variability in miRNA performance between platforms might have a crucial impact on the biological interpretation of data.

Original languageEnglish
JournalIn Vivo
Volume36
Issue number3
Pages (from-to)1059-1066
ISSN0258-851X
DOIs
Publication statusPublished - May 2022

Bibliographical note

Publisher Copyright:
© 2022 International Institute of Anticancer Research. All rights reserved.

    Research areas

  • epithelial ovarian cancer, normalization, Stable endogenous miRNAs

ID: 346451055