Identification of key genes and immune infiltration based on weighted gene co-expression network analysis in vestibular schwannoma

Abstract

Vestibular schwannomas are the most common tumors of the cerebellopontine angle, but their pathogenesis is still unclear. This study aimed to explore the molecular mechanisms and potential therapeutic target biomarkers in vestibular schwannoma. Two datasets (GSE141801 and GSE54934) were downloaded from the Gene Expression Omnibus database. Weighted gene coexpression network analysis was performed to find the key modules associated with vestibular schwannoma (VS). Functional enrichment analysis was applied to evaluate the gene enrichment signaling pathway in key modules. Protein-protein interaction networks in key modules were constructed using the STRING website. Hub genes were identified by intersecting candidate hub genes in protein-protein interaction network and candidate hub genes in key modules. Single-sample gene set enrichment analysis was utilized to quantify the abundance of tumor-infiltrating immune cells in VSs and normal control nerves. A Random forest classifier was developed based on hub genes identified in this study and validated on an independent dataset (GSE108524). Results of immune cell infiltration were also validated on GSE108524 by gene set enrichment analysis. Eight genes from coexpression modules were identified as hub genes, that is, CCND1, CAV1, GLI1, SOX9, LY86, TLR3, TREM2, and C3AR1, which might be potential therapeutic targets for VS. We also found that there were distinct differences in the infiltration levels of immune cells between VSs and normal control nerves. Overall, our findings may be useful for investigating the mechanisms underlying VS and provide noteworthy directions for future research.