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Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra

METHODS: We quantified 378 HRMAS (1)H NMR spectra of human brain tumours (132 glioblastomas, 101 astrocytomas, 75 meningiomas, 37 oligodendrogliomas and 33 metastases) from the eTumour database and looked for metabolic interactions by metabolite-metabolite correlation analysis (MMCA). RESULTS: All t...

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Autores principales: Madhu, Basetti, Jauhiainen, Alexandra, McGuire, Sean, Griffiths, John R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656327/
https://www.ncbi.nlm.nih.gov/pubmed/29069098
http://dx.doi.org/10.1371/journal.pone.0185980
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author Madhu, Basetti
Jauhiainen, Alexandra
McGuire, Sean
Griffiths, John R.
author_facet Madhu, Basetti
Jauhiainen, Alexandra
McGuire, Sean
Griffiths, John R.
author_sort Madhu, Basetti
collection PubMed
description METHODS: We quantified 378 HRMAS (1)H NMR spectra of human brain tumours (132 glioblastomas, 101 astrocytomas, 75 meningiomas, 37 oligodendrogliomas and 33 metastases) from the eTumour database and looked for metabolic interactions by metabolite-metabolite correlation analysis (MMCA). RESULTS: All tumour types showed remarkably similar metabolic correlations. Lactate correlated positively with alanine, glutamate with glutamine; creatine + phosphocreatine (tCr) correlated positively with lactate, alanine and choline + phosphocholine + glycerophosphocholine (tCho), and tCho correlated positively with lactate; fatty acids correlated negatively with lactate, glutamate + glutamine (tGlut), tCr and tCho. Oligodendrogliomas had fewer correlations but they still fitted that pattern. CONCLUSIONS: Possible explanations include (i) glycolytic tumour cells (the Warburg effect) generating pyruvate which is converted to lactate, alanine, glutamate and then glutamine; (ii) an association between elevated glycolysis and increased choline turnover in membranes; (iii) an increase in the tCr pool to facilitate phosphocreatine-driven glutamate uptake; (iv) lipid signals come from cytosolic lipid droplets in necrotic or pre-necrotic tumour tissue that has lower concentrations of anabolic and catabolic metabolites. Additional metabolite exchanges with host cells may also be involved. If tumours co-opt a standard set of biochemical mechanisms to grow in the brain, then drugs might be developed to disrupt those mechanisms.
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spelling pubmed-56563272017-11-09 Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra Madhu, Basetti Jauhiainen, Alexandra McGuire, Sean Griffiths, John R. PLoS One Research Article METHODS: We quantified 378 HRMAS (1)H NMR spectra of human brain tumours (132 glioblastomas, 101 astrocytomas, 75 meningiomas, 37 oligodendrogliomas and 33 metastases) from the eTumour database and looked for metabolic interactions by metabolite-metabolite correlation analysis (MMCA). RESULTS: All tumour types showed remarkably similar metabolic correlations. Lactate correlated positively with alanine, glutamate with glutamine; creatine + phosphocreatine (tCr) correlated positively with lactate, alanine and choline + phosphocholine + glycerophosphocholine (tCho), and tCho correlated positively with lactate; fatty acids correlated negatively with lactate, glutamate + glutamine (tGlut), tCr and tCho. Oligodendrogliomas had fewer correlations but they still fitted that pattern. CONCLUSIONS: Possible explanations include (i) glycolytic tumour cells (the Warburg effect) generating pyruvate which is converted to lactate, alanine, glutamate and then glutamine; (ii) an association between elevated glycolysis and increased choline turnover in membranes; (iii) an increase in the tCr pool to facilitate phosphocreatine-driven glutamate uptake; (iv) lipid signals come from cytosolic lipid droplets in necrotic or pre-necrotic tumour tissue that has lower concentrations of anabolic and catabolic metabolites. Additional metabolite exchanges with host cells may also be involved. If tumours co-opt a standard set of biochemical mechanisms to grow in the brain, then drugs might be developed to disrupt those mechanisms. Public Library of Science 2017-10-25 /pmc/articles/PMC5656327/ /pubmed/29069098 http://dx.doi.org/10.1371/journal.pone.0185980 Text en © 2017 Madhu et al http://creativecommons.org/licenses/by/4.0/ 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 author and source are credited.
spellingShingle Research Article
Madhu, Basetti
Jauhiainen, Alexandra
McGuire, Sean
Griffiths, John R.
Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra
title Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra
title_full Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra
title_fullStr Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra
title_full_unstemmed Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra
title_short Exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (MMCA) of HR-MAS (1)H NMR spectra
title_sort exploration of human brain tumour metabolism using pairwise metabolite-metabolite correlation analysis (mmca) of hr-mas (1)h nmr spectra
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5656327/
https://www.ncbi.nlm.nih.gov/pubmed/29069098
http://dx.doi.org/10.1371/journal.pone.0185980
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