Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis

  • Authors:
    • Bo Wu
    • Gaojing Dou
    • Yuan Zhang
    • Jing Wang
    • Xinhui Wang
    • Shanshan Jiang
    • Sheng Zhong
    • Junan Ren
    • Zhiyun Zhang
    • Jiahui Li
    • Chunjia Sheng
    • Gang Zhao
    • Liyan Zhao
  • View Affiliations

  • Published online on: January 13, 2022     https://doi.org/10.3892/etm.2022.11141
  • Article Number: 217
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Abstract

The aim of the present study is to identify novel promising marks and targets of diagnosis, therapy and prognosis for patients with vestibular schwannoma at the molecular level. The gene expression profiles of GSE54934, GSE39645 and GSE56597 datasets were obtained respectively from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified by comparing between gene expression profiles of the vestibular schwannoma tissues and normal tissues. Subsequently, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein‑protein interaction (PPI) network analysis were performed. The function and pathway enrichment analysis were performed for DEGs with DAVID. Reverse transcription‑quantitative PCR were conducted to confirm the expression of BCL2, AGT, IL6 and ITGA2 in human Schwann cells and vestibular schwannoma cells. A total of 4,025, 1,1291 and 1,513 DEGs were identified from GSE54934, GSE56597 and GSE39645 datasets, respectively. GO and KEGG analysis showed that the mutual upregulated genes were mainly enriched in cell division, mitotic nuclear division, and transition of mitotic cell cycle, whilst mutual downregulated genes were enriched in chemical synaptic transmission, neurotransmitter transport, and synaptic vesicle membrane. Subsequently, 20 genes, including BCL2, AGT, IL6 and ITGA2 were selected as hub genes with high degrees after PPI network analysis. The significant differential expression of those genes were detected among vestibular schwannoma tissues compared with normal nerve tissues. In conclusion, BCL2, AGT, IL6 and ITGA2 are significantly higher expressed in vestibular schwannoma tissues compared with human Schwann tissues. The DEGs identified in the present study provide novel targets for the diagnosis and treatment of vestibular schwannoma.
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March-2022
Volume 23 Issue 3

Print ISSN: 1792-0981
Online ISSN:1792-1015

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Spandidos Publications style
Wu B, Dou G, Zhang Y, Wang J, Wang X, Jiang S, Zhong S, Ren J, Zhang Z, Li J, Li J, et al: Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis. Exp Ther Med 23: 217, 2022.
APA
Wu, B., Dou, G., Zhang, Y., Wang, J., Wang, X., Jiang, S. ... Zhao, L. (2022). Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis. Experimental and Therapeutic Medicine, 23, 217. https://doi.org/10.3892/etm.2022.11141
MLA
Wu, B., Dou, G., Zhang, Y., Wang, J., Wang, X., Jiang, S., Zhong, S., Ren, J., Zhang, Z., Li, J., Sheng, C., Zhao, G., Zhao, L."Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis". Experimental and Therapeutic Medicine 23.3 (2022): 217.
Chicago
Wu, B., Dou, G., Zhang, Y., Wang, J., Wang, X., Jiang, S., Zhong, S., Ren, J., Zhang, Z., Li, J., Sheng, C., Zhao, G., Zhao, L."Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis". Experimental and Therapeutic Medicine 23, no. 3 (2022): 217. https://doi.org/10.3892/etm.2022.11141