Hayes, J, Thygesen, H, Tumilson, C et al. (8 more authors) (2015) Prediction of clinical outcome in glioblastoma using a biologically relevant nine-microRNA signature. Molecular Oncology, 9 (3). 704 - 714. ISSN 1574-7891
Abstract
Background: Glioblastoma is the most aggressive primary brain tumor, and is associated with a very poor prognosis. In this study we investigated the potential of microRNA expression profiles to predict survival in this challenging disease. Methods: MicroRNA and mRNA expression data from glioblastoma (n=475) and grade II and III glioma (n=178) were accessed from The Cancer Genome Atlas. LASSO regression models were used to identify a prognostic microRNA signature. Functionally relevant targets of microRNAs were determined using microRNA target prediction, experimental validation and correlation of microRNA and mRNA expression data. Results: A 9-microRNA prognostic signature was identified which stratified patients into risk groups strongly associated with survival (p=2.26e-09), significant in all glioblastoma subtypes except the non-G-CIMP proneural group. The statistical significance of the microRNA signature was higher than MGMT methylation in temozolomide treated tumors. The 9-microRNA risk score was validated in an independent dataset (p=4.50e-02) and also stratified patients into high- and low-risk groups in lower grade glioma (p=5.20e-03). The majority of the 9 microRNAs have been previously linked to glioblastoma biology or treatment response. Integration of the expression patterns of predicted microRNA targets revealed a number of relevant microRNA/target pairs, which were validated in cell lines. Conclusions: We have identified a novel, biologically relevant microRNA signature that stratifies high- and low-risk patients in glioblastoma. MicroRNA/mRNA interactions identified within the signature point to novel regulatory networks. This is the first study to formulate a survival risk score for glioblastoma which consists of microRNAs associated with glioblastoma biology and/or treatment response, indicating a functionally relevant signature.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved. NOTICE: this is the author’s version of a work that was accepted for publication in Molecular Oncology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Molecular Oncology, 9, 3, (2015) DOI 10.1016/j.molonc.2014.11.004 |
Keywords: | Glioblastoma; MicroRNA; Prognosis; Signature; TCGA |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Oncology and Clinical Research (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Mar 2015 15:29 |
Last Modified: | 17 Jan 2018 22:30 |
Published Version: | http://dx.doi.org/10.1016/j.molonc.2014.11.004 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.molonc.2014.11.004 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:83618 |