Cargando…

Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods

Glioma peritumoral brain edema (GPTBE) is a frequent complication in patients with glioma. The severity of peritumoral edema endangers patients’ life and prognosis. However, there are still questions concerning the process of GPTBE formation and evolution. In this study, the patients were split into...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Yuxi, Peng, Zesheng, Wang, Haofei, Xiang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221376/
https://www.ncbi.nlm.nih.gov/pubmed/35741689
http://dx.doi.org/10.3390/brainsci12060805
_version_ 1784732606600839168
author Wu, Yuxi
Peng, Zesheng
Wang, Haofei
Xiang, Wei
author_facet Wu, Yuxi
Peng, Zesheng
Wang, Haofei
Xiang, Wei
author_sort Wu, Yuxi
collection PubMed
description Glioma peritumoral brain edema (GPTBE) is a frequent complication in patients with glioma. The severity of peritumoral edema endangers patients’ life and prognosis. However, there are still questions concerning the process of GPTBE formation and evolution. In this study, the patients were split into two groups based on edema scoring findings in the cancer imaging archive (TCIA) comprising 186 TCGA-LGG patients. Using mRNA sequencing data, differential gene (DEG) expression analysis was performed, comparing the two groups to find the key genes affecting GPTBE. A functional enrichment analysis of differentially expressed genes was performed. Then, a protein–protein interaction (PPI) network was established, and important genes were screened. Gene set variation analysis (GSVA) scores were calculated for major gene sets and comparatively correlated with immune cell infiltration. Overall survival (OS) was analyzed using the Kaplan–Meier curve. A total of 59 DEGs were found, with 10 of them appearing as important genes. DEGs were shown to be closely linked to inflammatory reactions. According to the network score, IL10 was in the middle of the network. The presence of the IL10 protein in glioma tissues was verified using the human protein atlas (HPA). Furthermore, the gene sets’ GSVA scores were favorably linked with immune infiltration, particularly, with macrophages. The high-edema group had higher GSVA scores than the low-edema group. Finally, Kaplan–Meier analysis revealed no differences in OS between the two groups, and eight genes were found to be related to prognosis, whereas two genes were not. GPTBE is linked to the expression of inflammatory genes.
format Online
Article
Text
id pubmed-9221376
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-92213762022-06-24 Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods Wu, Yuxi Peng, Zesheng Wang, Haofei Xiang, Wei Brain Sci Article Glioma peritumoral brain edema (GPTBE) is a frequent complication in patients with glioma. The severity of peritumoral edema endangers patients’ life and prognosis. However, there are still questions concerning the process of GPTBE formation and evolution. In this study, the patients were split into two groups based on edema scoring findings in the cancer imaging archive (TCIA) comprising 186 TCGA-LGG patients. Using mRNA sequencing data, differential gene (DEG) expression analysis was performed, comparing the two groups to find the key genes affecting GPTBE. A functional enrichment analysis of differentially expressed genes was performed. Then, a protein–protein interaction (PPI) network was established, and important genes were screened. Gene set variation analysis (GSVA) scores were calculated for major gene sets and comparatively correlated with immune cell infiltration. Overall survival (OS) was analyzed using the Kaplan–Meier curve. A total of 59 DEGs were found, with 10 of them appearing as important genes. DEGs were shown to be closely linked to inflammatory reactions. According to the network score, IL10 was in the middle of the network. The presence of the IL10 protein in glioma tissues was verified using the human protein atlas (HPA). Furthermore, the gene sets’ GSVA scores were favorably linked with immune infiltration, particularly, with macrophages. The high-edema group had higher GSVA scores than the low-edema group. Finally, Kaplan–Meier analysis revealed no differences in OS between the two groups, and eight genes were found to be related to prognosis, whereas two genes were not. GPTBE is linked to the expression of inflammatory genes. MDPI 2022-06-19 /pmc/articles/PMC9221376/ /pubmed/35741689 http://dx.doi.org/10.3390/brainsci12060805 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wu, Yuxi
Peng, Zesheng
Wang, Haofei
Xiang, Wei
Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods
title Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods
title_full Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods
title_fullStr Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods
title_full_unstemmed Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods
title_short Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods
title_sort identifying the hub genes of glioma peritumoral brain edema using bioinformatical methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221376/
https://www.ncbi.nlm.nih.gov/pubmed/35741689
http://dx.doi.org/10.3390/brainsci12060805
work_keys_str_mv AT wuyuxi identifyingthehubgenesofgliomaperitumoralbrainedemausingbioinformaticalmethods
AT pengzesheng identifyingthehubgenesofgliomaperitumoralbrainedemausingbioinformaticalmethods
AT wanghaofei identifyingthehubgenesofgliomaperitumoralbrainedemausingbioinformaticalmethods
AT xiangwei identifyingthehubgenesofgliomaperitumoralbrainedemausingbioinformaticalmethods