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Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup

Medulloblastoma is the most common type of solid brain tumor in children. This type of embryonic tumor is highly heterogeneous and has been classified into 4 molecular subgroups based on their gene expression profiles: WNT, SHH, Group 3 (G3) and Group 4 (G4). WNT and SHH tumors exhibit the specific...

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Autores principales: Castillo-Rodríguez, Rosa Angélica, Dávila-Borja, Víctor Manuel, Juárez-Méndez, Sergio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876455/
https://www.ncbi.nlm.nih.gov/pubmed/29616106
http://dx.doi.org/10.3892/ol.2018.8094
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author Castillo-Rodríguez, Rosa Angélica
Dávila-Borja, Víctor Manuel
Juárez-Méndez, Sergio
author_facet Castillo-Rodríguez, Rosa Angélica
Dávila-Borja, Víctor Manuel
Juárez-Méndez, Sergio
author_sort Castillo-Rodríguez, Rosa Angélica
collection PubMed
description Medulloblastoma is the most common type of solid brain tumor in children. This type of embryonic tumor is highly heterogeneous and has been classified into 4 molecular subgroups based on their gene expression profiles: WNT, SHH, Group 3 (G3) and Group 4 (G4). WNT and SHH tumors exhibit the specific dysregulation of genes and pathways, whereas G3 and G4 tumors, two of the more frequent subtypes, are the least characterized. Thus, novel markers to aid in the diagnosis, prognosis and management of medulloblastoma are required. In the present study, microarray gene expression data was downloaded from the Gene Expression Omnibus database, including data from the 4 subgroups of medulloblastoma and healthy cerebellum tissue (CT). The data was utilized in an in silico analysis to characterize each subgroup at a transcriptomic level. Using Partek Genomics Suite software, the data were visualized via hierarchical clustering and principal component analysis. The differentially expressed genes were uploaded to the MetaCore portal to perform enrichment analysis using CT gene expression as baseline, with fold change thresholds of <-5 and >5 for differential expression. The data mining analysis of microarray gene expression data enabled the identification of a range of dysregulated molecules associated with each subgroup of medulloblastoma. G4 is the most heterogeneous subgroup, as no definitive pathway defines its pathogenesis; analysis of the gene expression profiles were associated with the G4α and G4β subcategories. TOX high mobility group box family member 3, synuclein α interacting protein and, potassium voltage-gated channel interacting protein 4 were identified as three novel potential markers for distinguishing the α and β subcategories of G4. These genes may be associated with medulloblastoma pathogenesis, and thus may provide a basis for researching novel targeted treatment strategies for G4 medulloblastoma.
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spelling pubmed-58764552018-04-03 Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup Castillo-Rodríguez, Rosa Angélica Dávila-Borja, Víctor Manuel Juárez-Méndez, Sergio Oncol Lett Articles Medulloblastoma is the most common type of solid brain tumor in children. This type of embryonic tumor is highly heterogeneous and has been classified into 4 molecular subgroups based on their gene expression profiles: WNT, SHH, Group 3 (G3) and Group 4 (G4). WNT and SHH tumors exhibit the specific dysregulation of genes and pathways, whereas G3 and G4 tumors, two of the more frequent subtypes, are the least characterized. Thus, novel markers to aid in the diagnosis, prognosis and management of medulloblastoma are required. In the present study, microarray gene expression data was downloaded from the Gene Expression Omnibus database, including data from the 4 subgroups of medulloblastoma and healthy cerebellum tissue (CT). The data was utilized in an in silico analysis to characterize each subgroup at a transcriptomic level. Using Partek Genomics Suite software, the data were visualized via hierarchical clustering and principal component analysis. The differentially expressed genes were uploaded to the MetaCore portal to perform enrichment analysis using CT gene expression as baseline, with fold change thresholds of <-5 and >5 for differential expression. The data mining analysis of microarray gene expression data enabled the identification of a range of dysregulated molecules associated with each subgroup of medulloblastoma. G4 is the most heterogeneous subgroup, as no definitive pathway defines its pathogenesis; analysis of the gene expression profiles were associated with the G4α and G4β subcategories. TOX high mobility group box family member 3, synuclein α interacting protein and, potassium voltage-gated channel interacting protein 4 were identified as three novel potential markers for distinguishing the α and β subcategories of G4. These genes may be associated with medulloblastoma pathogenesis, and thus may provide a basis for researching novel targeted treatment strategies for G4 medulloblastoma. D.A. Spandidos 2018-05 2018-02-21 /pmc/articles/PMC5876455/ /pubmed/29616106 http://dx.doi.org/10.3892/ol.2018.8094 Text en Copyright: © Castillo-Rodríguez 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
Castillo-Rodríguez, Rosa Angélica
Dávila-Borja, Víctor Manuel
Juárez-Méndez, Sergio
Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup
title Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup
title_full Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup
title_fullStr Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup
title_full_unstemmed Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup
title_short Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup
title_sort data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the group 4 molecular subgroup
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5876455/
https://www.ncbi.nlm.nih.gov/pubmed/29616106
http://dx.doi.org/10.3892/ol.2018.8094
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