Cargando…

Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis

Meningioma is one of the most common primary tumors in the central nervous system (CNS). A deeper understanding of its molecular characterization could provide potential therapeutic targets to reduce recurrence. In this study, we attempted to identify specific gene mutations in meningioma for immuno...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Lijian, Wang, Luxuan, Tan, Yanli, Li, Chunhui, Fang, Chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768007/
https://www.ncbi.nlm.nih.gov/pubmed/36538194
http://dx.doi.org/10.1007/s12032-022-01869-8
_version_ 1784854080291602432
author Zhang, Lijian
Wang, Luxuan
Tan, Yanli
Li, Chunhui
Fang, Chuan
author_facet Zhang, Lijian
Wang, Luxuan
Tan, Yanli
Li, Chunhui
Fang, Chuan
author_sort Zhang, Lijian
collection PubMed
description Meningioma is one of the most common primary tumors in the central nervous system (CNS). A deeper understanding of its molecular characterization could provide potential therapeutic targets to reduce recurrence. In this study, we attempted to identify specific gene mutations in meningioma for immunotherapy. One GSE43290 dataset was obtained from the Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs) between meningioma tissues and normal meninges. In total, 420 DEGs were identified, including 15 up-regulated and 405 down-regulated genes. Functional enrichment analysis showed that these DEGs were mainly enriched in PI3K-Akt signaling pathway, Focal adhesion, and MAPK signaling pathway. We identified 20 hub genes by protein–protein interaction (PPI) analysis. Among the hub genes, the expression of FLT1, CXCL8, JUN, THBS1, FECAM1, CD34, and FGF13 were negatively correlated with Programmed Death Ligand-1 (PD-L1). Additionally, the expression of those genes was co-regulated by miR‐155‐5p. The findings suggest that miR-155-5p play an important role in the pathogenesis of meningioma and may represent potential therapeutic targets for its anti-PD-L1 immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12032-022-01869-8.
format Online
Article
Text
id pubmed-9768007
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-97680072022-12-22 Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis Zhang, Lijian Wang, Luxuan Tan, Yanli Li, Chunhui Fang, Chuan Med Oncol Original Paper Meningioma is one of the most common primary tumors in the central nervous system (CNS). A deeper understanding of its molecular characterization could provide potential therapeutic targets to reduce recurrence. In this study, we attempted to identify specific gene mutations in meningioma for immunotherapy. One GSE43290 dataset was obtained from the Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs) between meningioma tissues and normal meninges. In total, 420 DEGs were identified, including 15 up-regulated and 405 down-regulated genes. Functional enrichment analysis showed that these DEGs were mainly enriched in PI3K-Akt signaling pathway, Focal adhesion, and MAPK signaling pathway. We identified 20 hub genes by protein–protein interaction (PPI) analysis. Among the hub genes, the expression of FLT1, CXCL8, JUN, THBS1, FECAM1, CD34, and FGF13 were negatively correlated with Programmed Death Ligand-1 (PD-L1). Additionally, the expression of those genes was co-regulated by miR‐155‐5p. The findings suggest that miR-155-5p play an important role in the pathogenesis of meningioma and may represent potential therapeutic targets for its anti-PD-L1 immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12032-022-01869-8. Springer US 2022-12-20 2023 /pmc/articles/PMC9768007/ /pubmed/36538194 http://dx.doi.org/10.1007/s12032-022-01869-8 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/) .
spellingShingle Original Paper
Zhang, Lijian
Wang, Luxuan
Tan, Yanli
Li, Chunhui
Fang, Chuan
Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
title Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
title_full Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
title_fullStr Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
title_full_unstemmed Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
title_short Identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
title_sort identification of key genes of anti-programmed death ligand 1 for meningioma immunotherapy by bioinformatic analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768007/
https://www.ncbi.nlm.nih.gov/pubmed/36538194
http://dx.doi.org/10.1007/s12032-022-01869-8
work_keys_str_mv AT zhanglijian identificationofkeygenesofantiprogrammeddeathligand1formeningiomaimmunotherapybybioinformaticanalysis
AT wangluxuan identificationofkeygenesofantiprogrammeddeathligand1formeningiomaimmunotherapybybioinformaticanalysis
AT tanyanli identificationofkeygenesofantiprogrammeddeathligand1formeningiomaimmunotherapybybioinformaticanalysis
AT lichunhui identificationofkeygenesofantiprogrammeddeathligand1formeningiomaimmunotherapybybioinformaticanalysis
AT fangchuan identificationofkeygenesofantiprogrammeddeathligand1formeningiomaimmunotherapybybioinformaticanalysis