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Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis
Background: Glioblastoma multiforme (GBM) is a most common aggressive malignant brain tumor. In recent years, targeted therapy has been increasingly applied in GBM treatment. Methods: In the present study, GSE22866 was downloaded from gene expression omnibus (GEO). The genomic and clinical data were...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284326/ https://www.ncbi.nlm.nih.gov/pubmed/32412599 http://dx.doi.org/10.1042/BSR20200516 |
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author | Yu, Cheng Yin, Jianxing Wang, Xiefeng Chen, Lijiu Wei, Yutian Lu, Chenfei You, Yongping |
author_facet | Yu, Cheng Yin, Jianxing Wang, Xiefeng Chen, Lijiu Wei, Yutian Lu, Chenfei You, Yongping |
author_sort | Yu, Cheng |
collection | PubMed |
description | Background: Glioblastoma multiforme (GBM) is a most common aggressive malignant brain tumor. In recent years, targeted therapy has been increasingly applied in GBM treatment. Methods: In the present study, GSE22866 was downloaded from gene expression omnibus (GEO). The genomic and clinical data were obtained from TCGA. The differentially expressed genes (DEGs) were identified and functional analysis was performed using clusterprofiler. Then, the co-expression network for the DEGs was established using the “WGCNA” package. Next, the protein–protein interaction (PPI) was assessed using Search Tool for the Retrieval of Interacting Genes Database (STRING) and hub modules in Cytoscape were screened. The Venn diagram was plotted to showcase the overlapped hub DEGs in PPI network and TCGA. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the risk score of each patient. Validations of the hub gene were completed in other databases. Results: Functional analysis of the DEGs verified the involvement of DEGs in growth factor binding and gated channel activity. Among the 10 GBM-related modules, the red one displayed the strongest tie with GBM. VAMP2 was filtered out as the most intimate protein. The PPI network and TCGA were comprehensively analyzed. Finally, SNAP25 was identified as a real hub gene positively correlated with GBM prognosis. The result was validated by GEPIA, ONCOMINE database and qRT-PCR. Conclusions: SNAP25 might act as a GBM suppressor and a biomarker in GBM treatment. |
format | Online Article Text |
id | pubmed-7284326 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72843262020-06-16 Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis Yu, Cheng Yin, Jianxing Wang, Xiefeng Chen, Lijiu Wei, Yutian Lu, Chenfei You, Yongping Biosci Rep Bioinformatics Background: Glioblastoma multiforme (GBM) is a most common aggressive malignant brain tumor. In recent years, targeted therapy has been increasingly applied in GBM treatment. Methods: In the present study, GSE22866 was downloaded from gene expression omnibus (GEO). The genomic and clinical data were obtained from TCGA. The differentially expressed genes (DEGs) were identified and functional analysis was performed using clusterprofiler. Then, the co-expression network for the DEGs was established using the “WGCNA” package. Next, the protein–protein interaction (PPI) was assessed using Search Tool for the Retrieval of Interacting Genes Database (STRING) and hub modules in Cytoscape were screened. The Venn diagram was plotted to showcase the overlapped hub DEGs in PPI network and TCGA. Univariate and multivariate Cox proportional hazards regression analyses were performed to predict the risk score of each patient. Validations of the hub gene were completed in other databases. Results: Functional analysis of the DEGs verified the involvement of DEGs in growth factor binding and gated channel activity. Among the 10 GBM-related modules, the red one displayed the strongest tie with GBM. VAMP2 was filtered out as the most intimate protein. The PPI network and TCGA were comprehensively analyzed. Finally, SNAP25 was identified as a real hub gene positively correlated with GBM prognosis. The result was validated by GEPIA, ONCOMINE database and qRT-PCR. Conclusions: SNAP25 might act as a GBM suppressor and a biomarker in GBM treatment. Portland Press Ltd. 2020-06-09 /pmc/articles/PMC7284326/ /pubmed/32412599 http://dx.doi.org/10.1042/BSR20200516 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY). |
spellingShingle | Bioinformatics Yu, Cheng Yin, Jianxing Wang, Xiefeng Chen, Lijiu Wei, Yutian Lu, Chenfei You, Yongping Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
title | Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
title_full | Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
title_fullStr | Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
title_full_unstemmed | Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
title_short | Association between SNAP25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
title_sort | association between snap25 and human glioblastoma multiform: a comprehensive bioinformatic analysis |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284326/ https://www.ncbi.nlm.nih.gov/pubmed/32412599 http://dx.doi.org/10.1042/BSR20200516 |
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