Identification of potential biomarkers and candidate small molecule drugs in glioblastoma
Abstract 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 microarra...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-08-01
|
Series: | Cancer Cell International |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12935-020-01515-1 |
id |
doaj-926693042db2423085907e59f62e855b |
---|---|
record_format |
Article |
spelling |
doaj-926693042db2423085907e59f62e855b2020-11-25T03:41:19ZengBMCCancer Cell International1475-28672020-08-0120111410.1186/s12935-020-01515-1Identification of potential biomarkers and candidate small molecule drugs in glioblastomaWei-cheng Lu0Hui Xie1Ce Yuan2Jin-jiang Li3Zhao-yang Li4An-hua Wu5Department of Neurosurgery, First Affiliated Hospital of China Medical UniversityDepartment of Histology and Embryology, College of Basic Medicine, Shenyang Medical CollegeGraduate Program in Bioinformatics and Computational Biology, University of MinnesotaDepartment of Neurosurgery, General Hospital of Northern Theater CommandDepartment of Laboratory Animal Center, China Medical UniversityDepartment of Neurosurgery, First Affiliated Hospital of China Medical UniversityAbstract 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.http://link.springer.com/article/10.1186/s12935-020-01515-1GlioblastomaDifferentially expressed genesHub genesPrognosisSmall molecular drugs |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wei-cheng Lu Hui Xie Ce Yuan Jin-jiang Li Zhao-yang Li An-hua Wu |
spellingShingle |
Wei-cheng Lu Hui Xie Ce Yuan Jin-jiang Li Zhao-yang Li An-hua Wu Identification of potential biomarkers and candidate small molecule drugs in glioblastoma Cancer Cell International Glioblastoma Differentially expressed genes Hub genes Prognosis Small molecular drugs |
author_facet |
Wei-cheng Lu Hui Xie Ce Yuan Jin-jiang Li Zhao-yang Li An-hua Wu |
author_sort |
Wei-cheng Lu |
title |
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_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_sort |
identification of potential biomarkers and candidate small molecule drugs in glioblastoma |
publisher |
BMC |
series |
Cancer Cell International |
issn |
1475-2867 |
publishDate |
2020-08-01 |
description |
Abstract 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. |
topic |
Glioblastoma Differentially expressed genes Hub genes Prognosis Small molecular drugs |
url |
http://link.springer.com/article/10.1186/s12935-020-01515-1 |
work_keys_str_mv |
AT weichenglu identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma AT huixie identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma AT ceyuan identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma AT jinjiangli identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma AT zhaoyangli identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma AT anhuawu identificationofpotentialbiomarkersandcandidatesmallmoleculedrugsinglioblastoma |
_version_ |
1724530404009967616 |