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A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets
BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis and optimal patient management. According to the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565364/ https://www.ncbi.nlm.nih.gov/pubmed/33059718 http://dx.doi.org/10.1186/s12916-020-01748-x |
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author | Nguyen, H. D. Allaire, A. Diamandis, P. Bisaillon, M. Scott, M. S. Richer, M. |
author_facet | Nguyen, H. D. Allaire, A. Diamandis, P. Bisaillon, M. Scott, M. S. Richer, M. |
author_sort | Nguyen, H. D. |
collection | PubMed |
description | BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis and optimal patient management. According to the cIMPACT-NOW update 3, diffuse isocitrate dehydrogenase-wild type (IDH-WT) gliomas should be graded as grade IV glioblastomas (GBM) if they possess one or more of the following molecular markers that predict aggressive clinical course: EGFR amplification, TERT promoter mutation, and whole-chromosome 7 gain combined with chromosome 10 loss. METHODS: The Cancer Genome Atlas (TCGA) glioma expression datasets were reanalyzed in order to identify novel tumor subcategories which would be considered as GBM-equivalents with the current diagnostic algorithm. Unsupervised clustering allowed the identification of previously unrecognized transcriptomic subcategories. A supervised machine learning algorithm (k-nearest neighbor model) was also used to identify gene signatures specific to some of these subcategories. RESULTS: We identified 14 IDH-WT infiltrating gliomas displaying a “normal-like” (NL) transcriptomic profile associated with a longer survival. Genes such as C5AR1 (complement receptor), SLC32A1 (vesicular gamma-aminobutyric acid transporter), MSR1 (or CD204, scavenger receptor A), and SYT5 (synaptotagmin 5) were differentially expressed and comprised in gene signatures specific to NL IDH-WT gliomas which were validated further using the Chinese Glioma Genome Atlas datasets. These gene signatures showed high discriminative power and correlation with survival. CONCLUSION: NL IDH-WT gliomas represent an infiltrating glioma subcategory with a superior prognosis which can only be detected using genome-wide analysis. Differential expression of genes potentially involved in immune checkpoint and amino acid signaling pathways is providing insight into mechanisms of gliomagenesis and could pave the way to novel treatment targets for infiltrating gliomas. |
format | Online Article Text |
id | pubmed-7565364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75653642020-10-16 A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets Nguyen, H. D. Allaire, A. Diamandis, P. Bisaillon, M. Scott, M. S. Richer, M. BMC Med Research Article BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis and optimal patient management. According to the cIMPACT-NOW update 3, diffuse isocitrate dehydrogenase-wild type (IDH-WT) gliomas should be graded as grade IV glioblastomas (GBM) if they possess one or more of the following molecular markers that predict aggressive clinical course: EGFR amplification, TERT promoter mutation, and whole-chromosome 7 gain combined with chromosome 10 loss. METHODS: The Cancer Genome Atlas (TCGA) glioma expression datasets were reanalyzed in order to identify novel tumor subcategories which would be considered as GBM-equivalents with the current diagnostic algorithm. Unsupervised clustering allowed the identification of previously unrecognized transcriptomic subcategories. A supervised machine learning algorithm (k-nearest neighbor model) was also used to identify gene signatures specific to some of these subcategories. RESULTS: We identified 14 IDH-WT infiltrating gliomas displaying a “normal-like” (NL) transcriptomic profile associated with a longer survival. Genes such as C5AR1 (complement receptor), SLC32A1 (vesicular gamma-aminobutyric acid transporter), MSR1 (or CD204, scavenger receptor A), and SYT5 (synaptotagmin 5) were differentially expressed and comprised in gene signatures specific to NL IDH-WT gliomas which were validated further using the Chinese Glioma Genome Atlas datasets. These gene signatures showed high discriminative power and correlation with survival. CONCLUSION: NL IDH-WT gliomas represent an infiltrating glioma subcategory with a superior prognosis which can only be detected using genome-wide analysis. Differential expression of genes potentially involved in immune checkpoint and amino acid signaling pathways is providing insight into mechanisms of gliomagenesis and could pave the way to novel treatment targets for infiltrating gliomas. BioMed Central 2020-10-16 /pmc/articles/PMC7565364/ /pubmed/33059718 http://dx.doi.org/10.1186/s12916-020-01748-x Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Research Article Nguyen, H. D. Allaire, A. Diamandis, P. Bisaillon, M. Scott, M. S. Richer, M. A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
title | A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
title_full | A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
title_fullStr | A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
title_full_unstemmed | A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
title_short | A machine learning analysis of a “normal-like” IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
title_sort | machine learning analysis of a “normal-like” idh-wt diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565364/ https://www.ncbi.nlm.nih.gov/pubmed/33059718 http://dx.doi.org/10.1186/s12916-020-01748-x |
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