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. 2020 Aug 28:20:419.
doi: 10.1186/s12935-020-01515-1. eCollection 2020.

Identification of potential biomarkers and candidate small molecule drugs in glioblastoma

Wei-Cheng Lu  1 , Hui Xie  2 , Ce Yuan  3 , Jin-Jiang Li  4 , Zhao-Yang Li  5 , An-Hua Wu  1
Affiliations

Identification of potential biomarkers and candidate small molecule drugs in glioblastoma

Wei-Cheng Lu et al. Cancer Cell Int. .

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.

Keywords: Differentially expressed genes; Glioblastoma; Hub genes; Prognosis; Small molecular drugs.

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Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
A flow chart of this study protocol
Fig. 2
Fig. 2
Identification of DEGs in three GEO datasets. A: Volcano plot. Green indicates down-regulated DEGs, and red indicates up-regulated DEGs. B: PCA plot. Red represents control sample, and blue represents GBM sample. C: VENN diagram of DEGs identified from three datasets (a: up-regulated DEGs, b: down-regulated DEGs). D: The DEGs identified by three statistical methods
Fig. 3
Fig. 3
Functional enrichment analysis of prognosis-related DEGs. a: Top 13 clusters from Metascape pathway enrichment analysis of prognosis-related DEGs. b: Network of GO and KEGG enriched terms colored by clusters. Nodes of the same color belong to the same cluster. Terms with Kappa similarity score > 0.3 are linked by an edge
Fig. 4
Fig. 4
The PPI network of survival related DEGs. The color depth of nodes represents the corrected P-value. The size of nodes represents the number of genes involved
Fig. 5
Fig. 5
The mRNA expression level of hub genes according to the TCGA database. Blue box indicates normal tissue, and red box indicates GBM tissue
Fig. 6
Fig. 6
Immunohistochemistry images of hub genes in GBM tissues and normal tissues derived from the HPA database
Fig. 7
Fig. 7
The top 10 small molecule drugs identified by CMAP database. The bubble size represents p value, the smaller the p value, the larger the bubble
See this image and copyright information in PMC

References

    1. Lukas RV, Rodon J, Becker K, Wong ET, Shih K, Touat M, et al. Clinical activity and safety of atezolizumab in patients with recurrent glioblastoma. J Neurooncol. 2018;140(2):317–328. - PubMed
    1. Alexander BM, Cloughesy TF. Adult glioblastoma. J Clin Oncol. 2017;35(21):2402–2409. - PubMed
    1. Delgado-López P, Corrales-García E. Survival in glioblastoma: a review on the impact of treatment modalities. Clin Transl Oncol. 2016;18(11):1062–1071. - PubMed
    1. Shergalis A, Bankhead A, Luesakul U, Muangsin N, Neamati N. Current challenges and opportunities in treating glioblastoma. Pharmacol Rev. 2018;70(3):412–445. - PMC - PubMed
    1. Stangeland B, Mughal AA, Grieg Z, Sandberg CJ, Joel M, Nygård S, et al. Combined expressional analysis, bioinformatics and targeted proteomics identify new potential therapeutic targets in glioblastoma stem cells. Oncotarget. 2015;6(28):26192–26215. - PMC - PubMed

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