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Molecular classification of IDH-mutant glioblastomas based on gene expression profiles
Isocitrate dehydrogenase (IDH) mutant glioblastoma (GBM), accounts for ~10% GBMs, arises from lower grade diffuse glioma and preferentially appears in younger patients. Here, we aim to establish a robust gene expression-based molecular classification of IDH-mutant GBM. A total of 33 samples from the...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642368/ https://www.ncbi.nlm.nih.gov/pubmed/30877769 http://dx.doi.org/10.1093/carcin/bgz032 |
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author | Wu, Fan Chai, Rui-Chao Wang, Zhiliang Liu, Yu-Qing Zhao, Zheng Li, Guan-Zhang Jiang, Hao-Yu |
author_facet | Wu, Fan Chai, Rui-Chao Wang, Zhiliang Liu, Yu-Qing Zhao, Zheng Li, Guan-Zhang Jiang, Hao-Yu |
author_sort | Wu, Fan |
collection | PubMed |
description | Isocitrate dehydrogenase (IDH) mutant glioblastoma (GBM), accounts for ~10% GBMs, arises from lower grade diffuse glioma and preferentially appears in younger patients. Here, we aim to establish a robust gene expression-based molecular classification of IDH-mutant GBM. A total of 33 samples from the Chinese Glioma Genome Atlas RNA-sequencing data were selected as training set, and 21 cases from Chinese Glioma Genome Atlas microarray data were used as validation set. Consensus clustering identified three groups with distinguished prognostic and molecular features. G1 group, with a poorer clinical outcome, mainly contained TERT promoter wild-type and male cases. G2 and G3 groups had better prognosis differed in gender. Gene ontology analysis showed that genes enriched in G1 group were involved in DNA replication, cell division and cycle. On the basis of the differential genes between G1 and G2/G3 groups, a six-gene signature was developed with a Cox proportional hazards model. Kaplan–Meier analysis found that the acquired signature could differentiate the outcome of low- and high-risk cases. Moreover, the signature could also serve as an independent prognostic factor for IDH-mutant GBM in the multivariate Cox regression analysis. Gene ontology and gene set enrichment analyses revealed that gene sets correlated with high-risk group were involved in cell cycle, cell proliferation, DNA replication and repair. These finding highlights heterogeneity within IDH-mutant GBMs and will advance our molecular understanding of this lethal cancer. |
format | Online Article Text |
id | pubmed-6642368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-66423682019-07-24 Molecular classification of IDH-mutant glioblastomas based on gene expression profiles Wu, Fan Chai, Rui-Chao Wang, Zhiliang Liu, Yu-Qing Zhao, Zheng Li, Guan-Zhang Jiang, Hao-Yu Carcinogenesis Cancer Biomarkers and Molecular Epidemiology Isocitrate dehydrogenase (IDH) mutant glioblastoma (GBM), accounts for ~10% GBMs, arises from lower grade diffuse glioma and preferentially appears in younger patients. Here, we aim to establish a robust gene expression-based molecular classification of IDH-mutant GBM. A total of 33 samples from the Chinese Glioma Genome Atlas RNA-sequencing data were selected as training set, and 21 cases from Chinese Glioma Genome Atlas microarray data were used as validation set. Consensus clustering identified three groups with distinguished prognostic and molecular features. G1 group, with a poorer clinical outcome, mainly contained TERT promoter wild-type and male cases. G2 and G3 groups had better prognosis differed in gender. Gene ontology analysis showed that genes enriched in G1 group were involved in DNA replication, cell division and cycle. On the basis of the differential genes between G1 and G2/G3 groups, a six-gene signature was developed with a Cox proportional hazards model. Kaplan–Meier analysis found that the acquired signature could differentiate the outcome of low- and high-risk cases. Moreover, the signature could also serve as an independent prognostic factor for IDH-mutant GBM in the multivariate Cox regression analysis. Gene ontology and gene set enrichment analyses revealed that gene sets correlated with high-risk group were involved in cell cycle, cell proliferation, DNA replication and repair. These finding highlights heterogeneity within IDH-mutant GBMs and will advance our molecular understanding of this lethal cancer. Oxford University Press 2019-07 2019-02-13 /pmc/articles/PMC6642368/ /pubmed/30877769 http://dx.doi.org/10.1093/carcin/bgz032 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Cancer Biomarkers and Molecular Epidemiology Wu, Fan Chai, Rui-Chao Wang, Zhiliang Liu, Yu-Qing Zhao, Zheng Li, Guan-Zhang Jiang, Hao-Yu Molecular classification of IDH-mutant glioblastomas based on gene expression profiles |
title | Molecular classification of IDH-mutant glioblastomas based on gene expression profiles |
title_full | Molecular classification of IDH-mutant glioblastomas based on gene expression profiles |
title_fullStr | Molecular classification of IDH-mutant glioblastomas based on gene expression profiles |
title_full_unstemmed | Molecular classification of IDH-mutant glioblastomas based on gene expression profiles |
title_short | Molecular classification of IDH-mutant glioblastomas based on gene expression profiles |
title_sort | molecular classification of idh-mutant glioblastomas based on gene expression profiles |
topic | Cancer Biomarkers and Molecular Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6642368/ https://www.ncbi.nlm.nih.gov/pubmed/30877769 http://dx.doi.org/10.1093/carcin/bgz032 |
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