Identification of key genes and pathways associated with resting mast cells in meningioma

Abstract Background To identify candidate key genes and pathways related to resting mast cells in meningioma and the underlying molecular mechanisms of meningioma. Methods Gene expression profiles of the used microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. GO and K...

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Autores principales:	Hui Xie, Ce Yuan, Xiao-hui Ding, Jin-jiang Li, Zhao-yang Li, Wei-cheng Lu
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Meningioma Resting mast cells Differentially expressed genes Pathways miRNAs Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/13342385476041d694411b9f9accd427
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spelling	oai:doaj.org-article:13342385476041d694411b9f9accd4272021-11-14T12:29:51ZIdentification of key genes and pathways associated with resting mast cells in meningioma10.1186/s12885-021-08931-01471-2407https://doaj.org/article/13342385476041d694411b9f9accd4272021-11-01T00:00:00Zhttps://doi.org/10.1186/s12885-021-08931-0https://doaj.org/toc/1471-2407Abstract Background To identify candidate key genes and pathways related to resting mast cells in meningioma and the underlying molecular mechanisms of meningioma. Methods Gene expression profiles of the used microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichments of DEGs were analyzed using the ClusterProfiler package in R. The protein-protein interaction network (PPI), and TF-miRNA- mRNA co-expression networks were constructed. Further, the difference in immune infiltration was investigated using the CIBERSORT algorithm. Results A total of 1499 DEGs were identified between tumor and normal controls. The analysis of the immune cell infiltration landscape showed that the probability of distribution of memory B cells, regulatory T cells (Tregs), and resting mast cells in tumor samples were significantly higher than those in the controls. Moreover, through WGCNA analysis, the module related to resting mast cells contained 158 DEGs, and KEGG pathway analysis revealed that the DEGs were dominant in the TNF signaling pathway, cytokine-cytokine receptor interaction, and IL-17 signaling pathway. Survival analysis of hub genes related to resting mast cells showed that the risk model was constructed based on 9 key genes. The TF-miRNA- mRNA co-regulation network, including MYC-miR-145-5p, TNFAIP3-miR-29c-3p, and TNFAIP3-hsa-miR-335-3p, were obtained. Further, 36 nodes and 197 interactions in the PPI network were identified. Conclusion The results of this study revealed candidate key genes, miRNAs, and pathways related to resting mast cells involved in meningioma development, providing potential therapeutic targets for meningioma treatment.Hui XieCe YuanXiao-hui DingJin-jiang LiZhao-yang LiWei-cheng LuBMCarticleMeningiomaResting mast cellsDifferentially expressed genesPathwaysmiRNAsNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENBMC Cancer, Vol 21, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Meningioma Resting mast cells Differentially expressed genes Pathways miRNAs Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Meningioma Resting mast cells Differentially expressed genes Pathways miRNAs Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Hui Xie Ce Yuan Xiao-hui Ding Jin-jiang Li Zhao-yang Li Wei-cheng Lu Identification of key genes and pathways associated with resting mast cells in meningioma
description	Abstract Background To identify candidate key genes and pathways related to resting mast cells in meningioma and the underlying molecular mechanisms of meningioma. Methods Gene expression profiles of the used microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichments of DEGs were analyzed using the ClusterProfiler package in R. The protein-protein interaction network (PPI), and TF-miRNA- mRNA co-expression networks were constructed. Further, the difference in immune infiltration was investigated using the CIBERSORT algorithm. Results A total of 1499 DEGs were identified between tumor and normal controls. The analysis of the immune cell infiltration landscape showed that the probability of distribution of memory B cells, regulatory T cells (Tregs), and resting mast cells in tumor samples were significantly higher than those in the controls. Moreover, through WGCNA analysis, the module related to resting mast cells contained 158 DEGs, and KEGG pathway analysis revealed that the DEGs were dominant in the TNF signaling pathway, cytokine-cytokine receptor interaction, and IL-17 signaling pathway. Survival analysis of hub genes related to resting mast cells showed that the risk model was constructed based on 9 key genes. The TF-miRNA- mRNA co-regulation network, including MYC-miR-145-5p, TNFAIP3-miR-29c-3p, and TNFAIP3-hsa-miR-335-3p, were obtained. Further, 36 nodes and 197 interactions in the PPI network were identified. Conclusion The results of this study revealed candidate key genes, miRNAs, and pathways related to resting mast cells involved in meningioma development, providing potential therapeutic targets for meningioma treatment.
format	article
author	Hui Xie Ce Yuan Xiao-hui Ding Jin-jiang Li Zhao-yang Li Wei-cheng Lu
author_facet	Hui Xie Ce Yuan Xiao-hui Ding Jin-jiang Li Zhao-yang Li Wei-cheng Lu
author_sort	Hui Xie
title	Identification of key genes and pathways associated with resting mast cells in meningioma
title_short	Identification of key genes and pathways associated with resting mast cells in meningioma
title_full	Identification of key genes and pathways associated with resting mast cells in meningioma
title_fullStr	Identification of key genes and pathways associated with resting mast cells in meningioma
title_full_unstemmed	Identification of key genes and pathways associated with resting mast cells in meningioma
title_sort	identification of key genes and pathways associated with resting mast cells in meningioma
publisher	BMC
publishDate	2021
url	https://doaj.org/article/13342385476041d694411b9f9accd427
work_keys_str_mv	AT huixie identificationofkeygenesandpathwaysassociatedwithrestingmastcellsinmeningioma AT ceyuan identificationofkeygenesandpathwaysassociatedwithrestingmastcellsinmeningioma AT xiaohuiding identificationofkeygenesandpathwaysassociatedwithrestingmastcellsinmeningioma AT jinjiangli identificationofkeygenesandpathwaysassociatedwithrestingmastcellsinmeningioma AT zhaoyangli identificationofkeygenesandpathwaysassociatedwithrestingmastcellsinmeningioma AT weichenglu identificationofkeygenesandpathwaysassociatedwithrestingmastcellsinmeningioma
_version_	1718429151171444736

Identification of key genes and pathways associated with resting mast cells in meningioma

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