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Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer

BACKGROUND: MEF2 family was associated with the pathogenesis of cancers. The crucial roles of MEF2 family members in gastric cancer (GC) have been demonstrated. However, the underlying mechanisms remain unclear. METHODS: Our study profiles the variance of four MEF2 genes in GC from genomic, epigenom...

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Autores principales: Zhu, Hongkai, Luo, Ming, Wang, Peilong, Peng, Hongling, Cheng, Zhao, Li, Heng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745365/
https://www.ncbi.nlm.nih.gov/pubmed/36523311
http://dx.doi.org/10.21037/tcr-22-373
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author Zhu, Hongkai
Luo, Ming
Wang, Peilong
Peng, Hongling
Cheng, Zhao
Li, Heng
author_facet Zhu, Hongkai
Luo, Ming
Wang, Peilong
Peng, Hongling
Cheng, Zhao
Li, Heng
author_sort Zhu, Hongkai
collection PubMed
description BACKGROUND: MEF2 family was associated with the pathogenesis of cancers. The crucial roles of MEF2 family members in gastric cancer (GC) have been demonstrated. However, the underlying mechanisms remain unclear. METHODS: Our study profiles the variance of four MEF2 genes in GC from genomic, epigenomic, and transcriptome angles. Iterative weight gene co-expression network analysis (WGCNA) was applied to identify the MEF2-related module and hub genes. enrichment analysis was conducted for MEF2-related hub genes using Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS: the transcriptome level of MEF2 genes were dysregulated in GC patients. The overall copy number status for MEF2 genes is copy number gain except for MEF2C with copy number loss. Besides, we screened out two sets of MEF2 related hub genes that enrichment analysis separates them into “intranuclear set” and “extracellular set”. By analyzing the “intranuclear set”, we screened out 6 miRNAs and 5 miRNA modulators that co-expressed with the MEF2 family and prognostic significance. CONCLUSIONS: our study investigated the variance of MEF2 family genes in the aspect of transcriptome and genomic and its clinical relevance. We found two sets of MEF2-related genes with different biological functions and 6 miRNAs targeting the MEF2 genes. Further research is required for validation and clarifying the deep underlying mechanism.
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spelling pubmed-97453652022-12-14 Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer Zhu, Hongkai Luo, Ming Wang, Peilong Peng, Hongling Cheng, Zhao Li, Heng Transl Cancer Res Original Article BACKGROUND: MEF2 family was associated with the pathogenesis of cancers. The crucial roles of MEF2 family members in gastric cancer (GC) have been demonstrated. However, the underlying mechanisms remain unclear. METHODS: Our study profiles the variance of four MEF2 genes in GC from genomic, epigenomic, and transcriptome angles. Iterative weight gene co-expression network analysis (WGCNA) was applied to identify the MEF2-related module and hub genes. enrichment analysis was conducted for MEF2-related hub genes using Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS: the transcriptome level of MEF2 genes were dysregulated in GC patients. The overall copy number status for MEF2 genes is copy number gain except for MEF2C with copy number loss. Besides, we screened out two sets of MEF2 related hub genes that enrichment analysis separates them into “intranuclear set” and “extracellular set”. By analyzing the “intranuclear set”, we screened out 6 miRNAs and 5 miRNA modulators that co-expressed with the MEF2 family and prognostic significance. CONCLUSIONS: our study investigated the variance of MEF2 family genes in the aspect of transcriptome and genomic and its clinical relevance. We found two sets of MEF2-related genes with different biological functions and 6 miRNAs targeting the MEF2 genes. Further research is required for validation and clarifying the deep underlying mechanism. AME Publishing Company 2022-11 /pmc/articles/PMC9745365/ /pubmed/36523311 http://dx.doi.org/10.21037/tcr-22-373 Text en 2022 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Zhu, Hongkai
Luo, Ming
Wang, Peilong
Peng, Hongling
Cheng, Zhao
Li, Heng
Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer
title Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer
title_full Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer
title_fullStr Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer
title_full_unstemmed Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer
title_short Comprehensive bioinformatics analysis for MEF2 family genes in gastric cancer
title_sort comprehensive bioinformatics analysis for mef2 family genes in gastric cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745365/
https://www.ncbi.nlm.nih.gov/pubmed/36523311
http://dx.doi.org/10.21037/tcr-22-373
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