Joanna Lopacinska-Joergensen1, Douglas V N P Oliveira1, Claus K Hoegdall2, Estrid V Hoegdall3. 1. Department of Pathology, Herlev Hospital, University of Copenhagen, Herlev, Denmark. 2. Department of Gynaecology, Juliane Marie Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark. 3. Department of Pathology, Herlev Hospital, University of Copenhagen, Herlev, Denmark; estrid.hoegdall@regionh.dk.
Abstract
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.
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.
Authors: Fabian Benz; Christoph Roderburg; David Vargas Cardenas; Mihael Vucur; Jérémie Gautheron; Alexander Koch; Henning Zimmermann; Jörn Janssen; Lukas Nieuwenhuijsen; Mark Luedde; Norbert Frey; Frank Tacke; Christian Trautwein; Tom Luedde Journal: Exp Mol Med Date: 2013-09-20 Impact factor: 8.718
Authors: Patrick H D Petersen; Joanna Lopacinska-Jørgensen; Douglas V N P Oliveira; Claus K Høgdall; Estrid V Høgdall Journal: In Vivo Date: 2022 Jul-Aug Impact factor: 2.406