Cargando…

Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis

Ependymomas (EPNs) are one of the most common types of malignant neuroepithelial tumors. In an effort to identify potential biomarkers involved in the pathogenesis of EPN, the mRNA expression profiles of the GSE25604, GSE50161, GSE66354, GSE74195 and GSE86574 datasets, in addition to the microRNA (m...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Biao, Dai, Jun-Xi, Pan, Yuan-Bo, Ma, Yan-Bin, Chu, Sheng-Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865127/
https://www.ncbi.nlm.nih.gov/pubmed/31788082
http://dx.doi.org/10.3892/ol.2019.10941
_version_ 1783472029561782272
author Yang, Biao
Dai, Jun-Xi
Pan, Yuan-Bo
Ma, Yan-Bin
Chu, Sheng-Hua
author_facet Yang, Biao
Dai, Jun-Xi
Pan, Yuan-Bo
Ma, Yan-Bin
Chu, Sheng-Hua
author_sort Yang, Biao
collection PubMed
description Ependymomas (EPNs) are one of the most common types of malignant neuroepithelial tumors. In an effort to identify potential biomarkers involved in the pathogenesis of EPN, the mRNA expression profiles of the GSE25604, GSE50161, GSE66354, GSE74195 and GSE86574 datasets, in addition to the microRNA (miRNA/miR) expression profiles of GSE42657 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between EPN and normal brain tissue samples were identified using the Limma package in R and GEO2R, respectively. Functional and pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed using the Search Tool for Retrieval of Interacting Genes database, which was visualized using Cytoscape. The targeted genes of DEMs were predicted using miRWalk2.0 and a miRNA-mRNA regulatory network was constructed. Following analysis, a total of 948 DEGs and 129 DEMs were identified. Functional enrichment analysis revealed that 609 upregulated DEGs were significantly enriched in ‘PI3K-Akt signaling pathway’, while 339 downregulated DEGs were primarily involved in ‘cell junction’ and ‘retrograde endocannabinoid signaling’. In addition, 6 hub genes [cyclin dependent kinase 1, CD44 molecule (Indian blood group) (CD44), proliferating cell nuclear antigen (PCNA), MYC, synaptotagmin 1 (SYT1) and kinesin family member 4A] and 6 crucial miRNAs [homo sapiens (hsa)-miR-34a-5p, hsa-miR-449a, hsa-miR-106a-5p, hsa-miR-124-3p, hsa-miR-128-3p and hsa-miR-330-3p] were identified as biomarkers and potential therapeutic targets for EPN. Furthermore, a microRNA-mRNA regulatory network was constructed to highlight the interactions between DEMs and their target DEGs; this included the hsa-miR-449a-SYT1, hsa-miR-34a-5p-SYT1, hsa-miR-330-3p-CD44 and hsa-miR-124-3p-PCNA pairs, whose expression levels were confirmed using reverse transcription-quantitative polymerase chain reaction. In conclusion, the present study may provide important data for the investigation of the molecular mechanisms of EPN pathogenesis.
format Online
Article
Text
id pubmed-6865127
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher D.A. Spandidos
record_format MEDLINE/PubMed
spelling pubmed-68651272019-11-30 Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis Yang, Biao Dai, Jun-Xi Pan, Yuan-Bo Ma, Yan-Bin Chu, Sheng-Hua Oncol Lett Articles Ependymomas (EPNs) are one of the most common types of malignant neuroepithelial tumors. In an effort to identify potential biomarkers involved in the pathogenesis of EPN, the mRNA expression profiles of the GSE25604, GSE50161, GSE66354, GSE74195 and GSE86574 datasets, in addition to the microRNA (miRNA/miR) expression profiles of GSE42657 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between EPN and normal brain tissue samples were identified using the Limma package in R and GEO2R, respectively. Functional and pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed using the Search Tool for Retrieval of Interacting Genes database, which was visualized using Cytoscape. The targeted genes of DEMs were predicted using miRWalk2.0 and a miRNA-mRNA regulatory network was constructed. Following analysis, a total of 948 DEGs and 129 DEMs were identified. Functional enrichment analysis revealed that 609 upregulated DEGs were significantly enriched in ‘PI3K-Akt signaling pathway’, while 339 downregulated DEGs were primarily involved in ‘cell junction’ and ‘retrograde endocannabinoid signaling’. In addition, 6 hub genes [cyclin dependent kinase 1, CD44 molecule (Indian blood group) (CD44), proliferating cell nuclear antigen (PCNA), MYC, synaptotagmin 1 (SYT1) and kinesin family member 4A] and 6 crucial miRNAs [homo sapiens (hsa)-miR-34a-5p, hsa-miR-449a, hsa-miR-106a-5p, hsa-miR-124-3p, hsa-miR-128-3p and hsa-miR-330-3p] were identified as biomarkers and potential therapeutic targets for EPN. Furthermore, a microRNA-mRNA regulatory network was constructed to highlight the interactions between DEMs and their target DEGs; this included the hsa-miR-449a-SYT1, hsa-miR-34a-5p-SYT1, hsa-miR-330-3p-CD44 and hsa-miR-124-3p-PCNA pairs, whose expression levels were confirmed using reverse transcription-quantitative polymerase chain reaction. In conclusion, the present study may provide important data for the investigation of the molecular mechanisms of EPN pathogenesis. D.A. Spandidos 2019-12 2019-09-30 /pmc/articles/PMC6865127/ /pubmed/31788082 http://dx.doi.org/10.3892/ol.2019.10941 Text en Copyright: © Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Yang, Biao
Dai, Jun-Xi
Pan, Yuan-Bo
Ma, Yan-Bin
Chu, Sheng-Hua
Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis
title Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis
title_full Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis
title_fullStr Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis
title_full_unstemmed Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis
title_short Identification of biomarkers and construction of a microRNA-mRNA regulatory network for ependymoma using integrated bioinformatics analysis
title_sort identification of biomarkers and construction of a microrna-mrna regulatory network for ependymoma using integrated bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865127/
https://www.ncbi.nlm.nih.gov/pubmed/31788082
http://dx.doi.org/10.3892/ol.2019.10941
work_keys_str_mv AT yangbiao identificationofbiomarkersandconstructionofamicrornamrnaregulatorynetworkforependymomausingintegratedbioinformaticsanalysis
AT daijunxi identificationofbiomarkersandconstructionofamicrornamrnaregulatorynetworkforependymomausingintegratedbioinformaticsanalysis
AT panyuanbo identificationofbiomarkersandconstructionofamicrornamrnaregulatorynetworkforependymomausingintegratedbioinformaticsanalysis
AT mayanbin identificationofbiomarkersandconstructionofamicrornamrnaregulatorynetworkforependymomausingintegratedbioinformaticsanalysis
AT chushenghua identificationofbiomarkersandconstructionofamicrornamrnaregulatorynetworkforependymomausingintegratedbioinformaticsanalysis