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New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis

BACKGROUND: Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors co...

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Autores principales: Chen, Desheng, Yao, Jiawei, Hu, Bowen, Kuang, Liangwen, Xu, Binshun, Liu, Haiyu, Dou, Chao, Wang, Guangzhi, Guo, Mian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118678/
https://www.ncbi.nlm.nih.gov/pubmed/35585639
http://dx.doi.org/10.1186/s41016-022-00278-0
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author Chen, Desheng
Yao, Jiawei
Hu, Bowen
Kuang, Liangwen
Xu, Binshun
Liu, Haiyu
Dou, Chao
Wang, Guangzhi
Guo, Mian
author_facet Chen, Desheng
Yao, Jiawei
Hu, Bowen
Kuang, Liangwen
Xu, Binshun
Liu, Haiyu
Dou, Chao
Wang, Guangzhi
Guo, Mian
author_sort Chen, Desheng
collection PubMed
description BACKGROUND: Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors contributing to gliomas, the role of single genes as diagnostic and prognostic biomarkers is limited. The aim of the current study is to discover the predictive and prognostic genetic markers for LGG. METHODS: Transcriptome data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We first performed the tumor microenvironment (TME) survival analysis using the Kaplan-Meier method. An analysis was undertaken to screen for differentially expressed genes. The function of these genes was studied by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Following which a protein-protein interaction network (PPI) was constructed and visualized. Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes. The key genes were selected by an intersection of core and prognostic genes. A clinical correlation analysis of single-gene expression was undertaken. GSEA enrichment analysis was performed to identify the function of key genes. Finally, a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG. RESULTS: A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA. Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment. The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified. Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG. Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration, positively related to macrophage M1 phenotype, and negatively related to activation of NK cells. CONCLUSIONS: HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients. It may also be associated with the immune infiltration phenotype in LGG.
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spelling pubmed-91186782022-05-20 New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis Chen, Desheng Yao, Jiawei Hu, Bowen Kuang, Liangwen Xu, Binshun Liu, Haiyu Dou, Chao Wang, Guangzhi Guo, Mian Chin Neurosurg J Research BACKGROUND: Low-grade gliomas (LGG) are WHO grade II tumors presenting as the most common primary malignant brain tumors in adults. Currently, LGG treatment involves either or a combination of surgery, radiation therapy, and chemotherapy. Despite the knowledge of constitutive genetic risk factors contributing to gliomas, the role of single genes as diagnostic and prognostic biomarkers is limited. The aim of the current study is to discover the predictive and prognostic genetic markers for LGG. METHODS: Transcriptome data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We first performed the tumor microenvironment (TME) survival analysis using the Kaplan-Meier method. An analysis was undertaken to screen for differentially expressed genes. The function of these genes was studied by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Following which a protein-protein interaction network (PPI) was constructed and visualized. Univariate and multivariate COX analyses were performed to obtain the probable prognostic genes. The key genes were selected by an intersection of core and prognostic genes. A clinical correlation analysis of single-gene expression was undertaken. GSEA enrichment analysis was performed to identify the function of key genes. Finally, a single gene-related correlation analysis was performed to identify the core immune cells involved in the development of LGG. RESULTS: A total of 529 transcriptome data and 515 clinical samples were obtained from the TCGA. Immune cells and stromal cells were found to be significantly increased in the LGG microenvironment. The top five core genes intersected with the top 38 prognostically relevant genes and two key genes were identified. Our analysis revealed that a high expression of HLA-DRA was associated with a poor prognosis of LGG. Correlation analysis of immune cells showed that HLA-DRA expression level was related to immune infiltration, positively related to macrophage M1 phenotype, and negatively related to activation of NK cells. CONCLUSIONS: HLA-DRA may be an independent prognostic indicator and an important biomarker for diagnosing and predicting survival in LGG patients. It may also be associated with the immune infiltration phenotype in LGG. BioMed Central 2022-05-19 /pmc/articles/PMC9118678/ /pubmed/35585639 http://dx.doi.org/10.1186/s41016-022-00278-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Chen, Desheng
Yao, Jiawei
Hu, Bowen
Kuang, Liangwen
Xu, Binshun
Liu, Haiyu
Dou, Chao
Wang, Guangzhi
Guo, Mian
New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis
title New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis
title_full New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis
title_fullStr New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis
title_full_unstemmed New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis
title_short New biomarker: the gene HLA-DRA associated with low-grade glioma prognosis
title_sort new biomarker: the gene hla-dra associated with low-grade glioma prognosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118678/
https://www.ncbi.nlm.nih.gov/pubmed/35585639
http://dx.doi.org/10.1186/s41016-022-00278-0
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