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Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours

Paediatric brain tumors are becoming well characterized due to large genomic and epigenomic studies. Metabolomics is a powerful analytical approach aiding in the characterization of tumors. This study shows that common cerebellar tumors have metabolite profiles sufficiently different to build accura...

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Autores principales: Bennett, Christopher D., Kohe, Sarah E., Gill, Simrandip K., Davies, Nigel P., Wilson, Martin, Storer, Lisa C. D., Ritzmann, Timothy, Paine, Simon M. L., Scott, Ian S., Nicklaus-Wollenteit, Ina, Tennant, Daniel A., Grundy, Richard G., Peet, Andrew C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086878/
https://www.ncbi.nlm.nih.gov/pubmed/30097636
http://dx.doi.org/10.1038/s41598-018-30342-8
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author Bennett, Christopher D.
Kohe, Sarah E.
Gill, Simrandip K.
Davies, Nigel P.
Wilson, Martin
Storer, Lisa C. D.
Ritzmann, Timothy
Paine, Simon M. L.
Scott, Ian S.
Nicklaus-Wollenteit, Ina
Tennant, Daniel A.
Grundy, Richard G.
Peet, Andrew C.
author_facet Bennett, Christopher D.
Kohe, Sarah E.
Gill, Simrandip K.
Davies, Nigel P.
Wilson, Martin
Storer, Lisa C. D.
Ritzmann, Timothy
Paine, Simon M. L.
Scott, Ian S.
Nicklaus-Wollenteit, Ina
Tennant, Daniel A.
Grundy, Richard G.
Peet, Andrew C.
author_sort Bennett, Christopher D.
collection PubMed
description Paediatric brain tumors are becoming well characterized due to large genomic and epigenomic studies. Metabolomics is a powerful analytical approach aiding in the characterization of tumors. This study shows that common cerebellar tumors have metabolite profiles sufficiently different to build accurate, robust diagnostic classifiers, and that the metabolite profiles can be used to assess differences in metabolism between the tumors. Tissue metabolite profiles were obtained from cerebellar ependymoma (n = 18), medulloblastoma (n = 36), pilocytic astrocytoma (n = 24) and atypical teratoid/rhabdoid tumors (n = 5) samples using HR-MAS. Quantified metabolites accurately discriminated the tumors; classification accuracies were 94% for ependymoma and medulloblastoma and 92% for pilocytic astrocytoma. Using current intraoperative examination the diagnostic accuracy was 72% for ependymoma, 90% for medulloblastoma and 89% for pilocytic astrocytoma. Elevated myo-inositol was characteristic of ependymoma whilst high taurine, phosphocholine and glycine distinguished medulloblastoma. Glutamine, hypotaurine and N-acetylaspartate (NAA) were increased in pilocytic astrocytoma. High lipids, phosphocholine and glutathione were important for separating ATRTs from medulloblastomas. This study demonstrates the ability of metabolic profiling by HR-MAS on small biopsy tissue samples to characterize these tumors. Analysis of tissue metabolite profiles has advantages in terms of minimal tissue pre-processing, short data acquisition time giving the potential to be used as part of a rapid diagnostic work-up.
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spelling pubmed-60868782018-08-16 Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours Bennett, Christopher D. Kohe, Sarah E. Gill, Simrandip K. Davies, Nigel P. Wilson, Martin Storer, Lisa C. D. Ritzmann, Timothy Paine, Simon M. L. Scott, Ian S. Nicklaus-Wollenteit, Ina Tennant, Daniel A. Grundy, Richard G. Peet, Andrew C. Sci Rep Article Paediatric brain tumors are becoming well characterized due to large genomic and epigenomic studies. Metabolomics is a powerful analytical approach aiding in the characterization of tumors. This study shows that common cerebellar tumors have metabolite profiles sufficiently different to build accurate, robust diagnostic classifiers, and that the metabolite profiles can be used to assess differences in metabolism between the tumors. Tissue metabolite profiles were obtained from cerebellar ependymoma (n = 18), medulloblastoma (n = 36), pilocytic astrocytoma (n = 24) and atypical teratoid/rhabdoid tumors (n = 5) samples using HR-MAS. Quantified metabolites accurately discriminated the tumors; classification accuracies were 94% for ependymoma and medulloblastoma and 92% for pilocytic astrocytoma. Using current intraoperative examination the diagnostic accuracy was 72% for ependymoma, 90% for medulloblastoma and 89% for pilocytic astrocytoma. Elevated myo-inositol was characteristic of ependymoma whilst high taurine, phosphocholine and glycine distinguished medulloblastoma. Glutamine, hypotaurine and N-acetylaspartate (NAA) were increased in pilocytic astrocytoma. High lipids, phosphocholine and glutathione were important for separating ATRTs from medulloblastomas. This study demonstrates the ability of metabolic profiling by HR-MAS on small biopsy tissue samples to characterize these tumors. Analysis of tissue metabolite profiles has advantages in terms of minimal tissue pre-processing, short data acquisition time giving the potential to be used as part of a rapid diagnostic work-up. Nature Publishing Group UK 2018-08-10 /pmc/articles/PMC6086878/ /pubmed/30097636 http://dx.doi.org/10.1038/s41598-018-30342-8 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
Bennett, Christopher D.
Kohe, Sarah E.
Gill, Simrandip K.
Davies, Nigel P.
Wilson, Martin
Storer, Lisa C. D.
Ritzmann, Timothy
Paine, Simon M. L.
Scott, Ian S.
Nicklaus-Wollenteit, Ina
Tennant, Daniel A.
Grundy, Richard G.
Peet, Andrew C.
Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
title Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
title_full Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
title_fullStr Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
title_full_unstemmed Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
title_short Tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
title_sort tissue metabolite profiles for the characterisation of paediatric cerebellar tumours
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086878/
https://www.ncbi.nlm.nih.gov/pubmed/30097636
http://dx.doi.org/10.1038/s41598-018-30342-8
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