Cargando…

Identification of potential biomarkers and candidate small molecule drugs in glioblastoma

BACKGROUND AND AIMS: Glioblastoma (GBM) is a common and aggressive primary brain tumor, and the prognosis for GBM patients remains poor. This study aimed to identify the key genes associated with the development of GBM and provide new diagnostic and therapies for GBM. METHODS: Three microarray datas...

Descripción completa

Detalles Bibliográficos
Autores principales: Lu, Wei-cheng, Xie, Hui, Yuan, Ce, Li, Jin-jiang, Li, Zhao-yang, Wu, An-hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455906/
https://www.ncbi.nlm.nih.gov/pubmed/32874133
http://dx.doi.org/10.1186/s12935-020-01515-1
_version_ 1783575713369030656
author Lu, Wei-cheng
Xie, Hui
Yuan, Ce
Li, Jin-jiang
Li, Zhao-yang
Wu, An-hua
author_facet Lu, Wei-cheng
Xie, Hui
Yuan, Ce
Li, Jin-jiang
Li, Zhao-yang
Wu, An-hua
author_sort Lu, Wei-cheng
collection PubMed
description BACKGROUND AND AIMS: Glioblastoma (GBM) is a common and aggressive primary brain tumor, and the prognosis for GBM patients remains poor. This study aimed to identify the key genes associated with the development of GBM and provide new diagnostic and therapies for GBM. METHODS: Three microarray datasets (GSE111260, GSE103227, and GSE104267) were selected from Gene Expression Omnibus (GEO) database for integrated analysis. The differential expressed genes (DEGs) between GBM and normal tissues were identified. Then, prognosis-related DEGs were screened by survival analysis, followed by functional enrichment analysis. The protein–protein interaction (PPI) network was constructed to explore the hub genes associated with GBM. The mRNA and protein expression levels of hub genes were respectively validated in silico using The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases. Subsequently, the small molecule drugs of GBM were predicted by using Connectivity Map (CMAP) database. RESULTS: A total of 78 prognosis-related DEGs were identified, of which10 hub genes with higher degree were obtained by PPI analysis. The mRNA expression and protein expression levels of CETN2, MKI67, ARL13B, and SETDB1 were overexpressed in GBM tissues, while the expression levels of CALN1, ELAVL3, ADCY3, SYN2, SLC12A5, and SOD1 were down-regulated in GBM tissues. Additionally, these genes were significantly associated with the prognosis of GBM. We eventually predicted the 10 most vital small molecule drugs, which potentially imitate or reverse GBM carcinogenic status. Cycloserine and 11-deoxy-16,16-dimethylprostaglandin E2 might be considered as potential therapeutic drugs of GBM. CONCLUSIONS: Our study provided 10 key genes for diagnosis, prognosis, and therapy for GBM. These findings might contribute to a better comprehension of molecular mechanisms of GBM development, and provide new perspective for further GBM research. However, specific regulatory mechanism of these genes needed further elaboration.
format Online
Article
Text
id pubmed-7455906
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-74559062020-08-31 Identification of potential biomarkers and candidate small molecule drugs in glioblastoma Lu, Wei-cheng Xie, Hui Yuan, Ce Li, Jin-jiang Li, Zhao-yang Wu, An-hua Cancer Cell Int Primary Research BACKGROUND AND AIMS: Glioblastoma (GBM) is a common and aggressive primary brain tumor, and the prognosis for GBM patients remains poor. This study aimed to identify the key genes associated with the development of GBM and provide new diagnostic and therapies for GBM. METHODS: Three microarray datasets (GSE111260, GSE103227, and GSE104267) were selected from Gene Expression Omnibus (GEO) database for integrated analysis. The differential expressed genes (DEGs) between GBM and normal tissues were identified. Then, prognosis-related DEGs were screened by survival analysis, followed by functional enrichment analysis. The protein–protein interaction (PPI) network was constructed to explore the hub genes associated with GBM. The mRNA and protein expression levels of hub genes were respectively validated in silico using The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases. Subsequently, the small molecule drugs of GBM were predicted by using Connectivity Map (CMAP) database. RESULTS: A total of 78 prognosis-related DEGs were identified, of which10 hub genes with higher degree were obtained by PPI analysis. The mRNA expression and protein expression levels of CETN2, MKI67, ARL13B, and SETDB1 were overexpressed in GBM tissues, while the expression levels of CALN1, ELAVL3, ADCY3, SYN2, SLC12A5, and SOD1 were down-regulated in GBM tissues. Additionally, these genes were significantly associated with the prognosis of GBM. We eventually predicted the 10 most vital small molecule drugs, which potentially imitate or reverse GBM carcinogenic status. Cycloserine and 11-deoxy-16,16-dimethylprostaglandin E2 might be considered as potential therapeutic drugs of GBM. CONCLUSIONS: Our study provided 10 key genes for diagnosis, prognosis, and therapy for GBM. These findings might contribute to a better comprehension of molecular mechanisms of GBM development, and provide new perspective for further GBM research. However, specific regulatory mechanism of these genes needed further elaboration. BioMed Central 2020-08-28 /pmc/articles/PMC7455906/ /pubmed/32874133 http://dx.doi.org/10.1186/s12935-020-01515-1 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Primary Research
Lu, Wei-cheng
Xie, Hui
Yuan, Ce
Li, Jin-jiang
Li, Zhao-yang
Wu, An-hua
Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
title Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
title_full Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
title_fullStr Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
title_full_unstemmed Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
title_short Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
title_sort identification of potential biomarkers and candidate small molecule drugs in glioblastoma
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455906/
https://www.ncbi.nlm.nih.gov/pubmed/32874133
http://dx.doi.org/10.1186/s12935-020-01515-1
work_keys_str_mv AT luweicheng identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma
AT xiehui identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma
AT yuance identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma
AT lijinjiang identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma
AT lizhaoyang identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma
AT wuanhua identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma