MicroRNA expression in human endometrial adenocarcinoma
2014 (English)In: Cancer Cell International, E-ISSN 1475-2867, Vol. 14, no 1, article id 88
Article in journal (Refereed) Published
Abstract [en]
BACKGROUND: MicroRNAs are small non-coding RNAs that play crucial roles in the pathogenesis of different cancer types. The aim of this study was to identify miRNAs that are differentially expressed in endometrial adenocarcinoma compared to healthy endometrium. These miRNAs can potentially be used to develop a panel for classification and prognosis in order to better predict the progression of the disease and facilitate the choice of treatment strategy.
METHODS: Formalin fixed paraffin embedded endometrial tissue samples were collected from the Örebro university hospital. QPCR was used to quantify the expression levels of 742 miRNAs in 30 malignant and 20 normal endometrium samples. After normalization of the qPCR data, miRNAs differing significantly in expression between normal and cancer samples were identified, and hierarchical clustering analysis was used to identify groups of miRNAs with coordinated expression profiles.
RESULTS: In comparisons between endometrial adenocarcinoma and normal endometrium samples 138 miRNAs were found to be significantly differentially expressed (p < 0.001) among which 112 miRNAs have not been previous reported for endometrial adenocarcinoma.
CONCLUSION: Our study shows that several miRNAs are differentially expressed in endometrial adenocarcinoma. These identified miRNA hold great potential as target for classification and prognosis of this disease. Further analysis of the differentially expressed miRNA and their target genes will help to derive new biomarkers that can be used for classification and prognosis of endometrial adenocarcinoma.
Place, publisher, year, edition, pages
London: BioMed Central (BMC), 2014. Vol. 14, no 1, article id 88
Keywords [en]
Endometrial adenocarcinoma, MicroRNA, Quantitative polymerase chain reaction
National Category
Cancer and Oncology
Research subject
Medical sciences; Bioinformatics; Infection Biology
Identifiers
URN: urn:nbn:se:his:diva-10451DOI: 10.1186/s12935-014-0088-6ISI: 000346199300001PubMedID: 25419182Scopus ID: 2-s2.0-84988672626OAI: oai:DiVA.org:his-10451DiVA, id: diva2:773347
Funder
Knowledge Foundation, 2009/091
Note
CC BY 4.0
© 2014 Jurcevic et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
2014-12-182014-12-182023-09-08Bibliographically approved
In thesis