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Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis
Exosomes are nano-sized extracellular vesicles released by many cells that contain molecules characteristic of their cell of origin, including microRNA. Exosomes released by glioblastoma cross the blood–brain barrier into the peripheral circulation and carry molecular cargo distinct to that of “free...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290767/ https://www.ncbi.nlm.nih.gov/pubmed/30564636 http://dx.doi.org/10.1038/s41698-018-0071-0 |
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author | Ebrahimkhani, Saeideh Vafaee, Fatemeh Hallal, Susannah Wei, Heng Lee, Maggie Yuk T. Young, Paul E. Satgunaseelan, Laveniya Beadnall, Heidi Barnett, Michael H. Shivalingam, Brindha Suter, Catherine M. Buckland, Michael E. Kaufman, Kimberley L. |
author_facet | Ebrahimkhani, Saeideh Vafaee, Fatemeh Hallal, Susannah Wei, Heng Lee, Maggie Yuk T. Young, Paul E. Satgunaseelan, Laveniya Beadnall, Heidi Barnett, Michael H. Shivalingam, Brindha Suter, Catherine M. Buckland, Michael E. Kaufman, Kimberley L. |
author_sort | Ebrahimkhani, Saeideh |
collection | PubMed |
description | Exosomes are nano-sized extracellular vesicles released by many cells that contain molecules characteristic of their cell of origin, including microRNA. Exosomes released by glioblastoma cross the blood–brain barrier into the peripheral circulation and carry molecular cargo distinct to that of “free-circulating” miRNA. In this pilot study, serum exosomal microRNAs were isolated from glioblastoma (n = 12) patients and analyzed using unbiased deep sequencing. Results were compared to sera from age- and gender-matched healthy controls and to grade II–III (n = 10) glioma patients. Significant differentially expressed microRNAs were identified, and the predictive power of individual and subsets of microRNAs were tested using univariate and multivariate analyses. Additional sera from glioblastoma patients (n = 4) and independent sets of healthy (n = 9) and non-glioma (n = 10) controls were used to further test the specificity and predictive power of this unique exosomal microRNA signature. Twenty-six microRNAs were differentially expressed in serum exosomes from glioblastoma patients relative to healthy controls. Random forest modeling and data partitioning selected seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p, and miR-543) as the most stable for classifying glioblastoma. Strikingly, within this model, six iterations of these miRNA classifiers could distinguish glioblastoma patients from controls with perfect accuracy. The seven miRNA panel was able to correctly classify all specimens in validation cohorts (n = 23). Also identified were 23 dysregulated miRNAs in IDH(MUT) gliomas, a partially overlapping yet distinct signature of lower-grade glioma. Serum exosomal miRNA signatures can accurately diagnose glioblastoma preoperatively. miRNA signatures identified are distinct from previously reported “free-circulating” miRNA studies in GBM patients and appear to be superior. |
format | Online Article Text |
id | pubmed-6290767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-62907672018-12-18 Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis Ebrahimkhani, Saeideh Vafaee, Fatemeh Hallal, Susannah Wei, Heng Lee, Maggie Yuk T. Young, Paul E. Satgunaseelan, Laveniya Beadnall, Heidi Barnett, Michael H. Shivalingam, Brindha Suter, Catherine M. Buckland, Michael E. Kaufman, Kimberley L. NPJ Precis Oncol Article Exosomes are nano-sized extracellular vesicles released by many cells that contain molecules characteristic of their cell of origin, including microRNA. Exosomes released by glioblastoma cross the blood–brain barrier into the peripheral circulation and carry molecular cargo distinct to that of “free-circulating” miRNA. In this pilot study, serum exosomal microRNAs were isolated from glioblastoma (n = 12) patients and analyzed using unbiased deep sequencing. Results were compared to sera from age- and gender-matched healthy controls and to grade II–III (n = 10) glioma patients. Significant differentially expressed microRNAs were identified, and the predictive power of individual and subsets of microRNAs were tested using univariate and multivariate analyses. Additional sera from glioblastoma patients (n = 4) and independent sets of healthy (n = 9) and non-glioma (n = 10) controls were used to further test the specificity and predictive power of this unique exosomal microRNA signature. Twenty-six microRNAs were differentially expressed in serum exosomes from glioblastoma patients relative to healthy controls. Random forest modeling and data partitioning selected seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p, and miR-543) as the most stable for classifying glioblastoma. Strikingly, within this model, six iterations of these miRNA classifiers could distinguish glioblastoma patients from controls with perfect accuracy. The seven miRNA panel was able to correctly classify all specimens in validation cohorts (n = 23). Also identified were 23 dysregulated miRNAs in IDH(MUT) gliomas, a partially overlapping yet distinct signature of lower-grade glioma. Serum exosomal miRNA signatures can accurately diagnose glioblastoma preoperatively. miRNA signatures identified are distinct from previously reported “free-circulating” miRNA studies in GBM patients and appear to be superior. Nature Publishing Group UK 2018-12-12 /pmc/articles/PMC6290767/ /pubmed/30564636 http://dx.doi.org/10.1038/s41698-018-0071-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ebrahimkhani, Saeideh Vafaee, Fatemeh Hallal, Susannah Wei, Heng Lee, Maggie Yuk T. Young, Paul E. Satgunaseelan, Laveniya Beadnall, Heidi Barnett, Michael H. Shivalingam, Brindha Suter, Catherine M. Buckland, Michael E. Kaufman, Kimberley L. Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis |
title | Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis |
title_full | Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis |
title_fullStr | Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis |
title_full_unstemmed | Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis |
title_short | Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis |
title_sort | deep sequencing of circulating exosomal microrna allows non-invasive glioblastoma diagnosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290767/ https://www.ncbi.nlm.nih.gov/pubmed/30564636 http://dx.doi.org/10.1038/s41698-018-0071-0 |
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