ArticleExperimental and therapeutic medicine2022
Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis.
Article in Experimental and therapeutic medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 3 citations in OpenAlex.
- Multiple databases analyzed the prognosis prediction of renin secretion pathway-related genes in renal clear cell carcinoma and immunotherapy.Translational cancer research · 2024Article
- Exploring the Role of Inflammatory Genes and Immune Infiltration in Vestibular Schwannomas Pathogenesis.Journal of inflammation research · 2024Article
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13 authors at 6 institutions in 1 country.
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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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