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Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles
The inhibition of alpha-ketoglutarate (α-KG)-dependent dioxygenases is thought to contribute to isocitrate dehydrogenase (IDH) mutation-derived malignancy. Herein, we aim to thoroughly investigate the expression pattern and prognostic significance of genes encoding α-KG-dependent enzymes for lower-g...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363673/ https://www.ncbi.nlm.nih.gov/pubmed/35965532 http://dx.doi.org/10.3389/fonc.2022.840394 |
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author | Zhang, Tan Yuan, Liqun Sheng, Minfeng Chen, Yanming Wang, Ji Lan, Qing |
author_facet | Zhang, Tan Yuan, Liqun Sheng, Minfeng Chen, Yanming Wang, Ji Lan, Qing |
author_sort | Zhang, Tan |
collection | PubMed |
description | The inhibition of alpha-ketoglutarate (α-KG)-dependent dioxygenases is thought to contribute to isocitrate dehydrogenase (IDH) mutation-derived malignancy. Herein, we aim to thoroughly investigate the expression pattern and prognostic significance of genes encoding α-KG-dependent enzymes for lower-grade glioma (LGG) patients. In this retrospective study, a total of 775 LGG patients were enrolled. The generalized linear model, least absolute shrinkage and selection operator Cox regression, and nomogram were applied to identify the enzyme-based signature. With the use of gene set enrichment analysis and Gene Ontology, the probable molecular abnormalities underlying high-risk patients were investigated. By comprehensively analyzing mRNA data, we observed that 41 genes were differentially expressed between IDH(MUT) and IDH(WT) LGG patients. A risk signature comprising 10 genes, which could divide samples into high- and low-risk groups of distinct prognoses, was developed and independently validated. This enzyme-based signature was indicative of a more malignant phenotype. The nomogram model incorporating the risk signature, molecular biomarkers, and clinicopathological parameters proved the incremental utility of the α-KG-dependent signature by achieving a more accurate prediction impact. Our study demonstrates that the α-KG-dependent enzyme-encoding genes were differentially expressed in relation to the IDH phenotype and may serve as a promising indicator for clinical outcomes of LGG patients. |
format | Online Article Text |
id | pubmed-9363673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93636732022-08-11 Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles Zhang, Tan Yuan, Liqun Sheng, Minfeng Chen, Yanming Wang, Ji Lan, Qing Front Oncol Oncology The inhibition of alpha-ketoglutarate (α-KG)-dependent dioxygenases is thought to contribute to isocitrate dehydrogenase (IDH) mutation-derived malignancy. Herein, we aim to thoroughly investigate the expression pattern and prognostic significance of genes encoding α-KG-dependent enzymes for lower-grade glioma (LGG) patients. In this retrospective study, a total of 775 LGG patients were enrolled. The generalized linear model, least absolute shrinkage and selection operator Cox regression, and nomogram were applied to identify the enzyme-based signature. With the use of gene set enrichment analysis and Gene Ontology, the probable molecular abnormalities underlying high-risk patients were investigated. By comprehensively analyzing mRNA data, we observed that 41 genes were differentially expressed between IDH(MUT) and IDH(WT) LGG patients. A risk signature comprising 10 genes, which could divide samples into high- and low-risk groups of distinct prognoses, was developed and independently validated. This enzyme-based signature was indicative of a more malignant phenotype. The nomogram model incorporating the risk signature, molecular biomarkers, and clinicopathological parameters proved the incremental utility of the α-KG-dependent signature by achieving a more accurate prediction impact. Our study demonstrates that the α-KG-dependent enzyme-encoding genes were differentially expressed in relation to the IDH phenotype and may serve as a promising indicator for clinical outcomes of LGG patients. Frontiers Media S.A. 2022-07-27 /pmc/articles/PMC9363673/ /pubmed/35965532 http://dx.doi.org/10.3389/fonc.2022.840394 Text en Copyright © 2022 Zhang, Yuan, Sheng, Chen, Wang and Lan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhang, Tan Yuan, Liqun Sheng, Minfeng Chen, Yanming Wang, Ji Lan, Qing Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
title | Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
title_full | Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
title_fullStr | Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
title_full_unstemmed | Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
title_short | Identifying α-KG-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
title_sort | identifying α-kg-dependent prognostic signature for lower-grade glioma based on transcriptome profiles |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363673/ https://www.ncbi.nlm.nih.gov/pubmed/35965532 http://dx.doi.org/10.3389/fonc.2022.840394 |
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