Department of Otorhinolaryngology Head and Neck Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Medicine (Baltimore). 2023 Dec 15;102(50):e36696. doi: 10.1097/MD.0000000000036696.
Neurofibromatosis type 2 (NF2)-related vestibular schwannoma (NF2-VS) is a rare genetic disorder that results in bilateral acoustic neuromas. However, the exact pathogenesis of the disease is still unclear. This study aims to use bioinformatics analyses to identify potential hub genes and therapeutic. We retrieved the mRNA expression profiles (GSE108524 and GSE141801) of NF2-VS from the database, and selected the leading 25% genes with the most variance across samples for weighted correlation network analysis. Subsequently, we conducted gene ontology term and Kyoto Encyclopedia of Genes and Genomes signaling network enrichment analyses. The STRING database was employed for protein-protein interaction (PPI) axis construction. The mRNA-miRNA modulatory network was generated via the miRTarBase database. Differentially expressed genes (DEGs) were identified via the R package "limma" in both datasets, and hub genes were screened via intersection of common DEGs, candidate hub genes from the PPI axis, and candidate hub genes from the key module. Finally, common DEGs were uploaded onto the connectivity map database to determine drug candidates. Based on our observations, the blue module exhibited the most significant relation to NF2-VS, and it included the NF2 gene. Using enrichment analysis, we demonstrated that the blue modules were intricately linked to modulations of cell proliferation, migration, adhesion, junction, and actin skeleton. Overall, 356 common DEGs were screened in both datasets, and 33 genes carrying a degree > 15 were chosen as candidate hub genes in the PPI axis. Subsequently, 4 genes, namely, GLUL, CAV1, MYH11, and CCND1 were recognized as real hub genes. In addition, 10 drugs with enrichment scores < -0.7 were identified as drug candidates. Our conclusions offered a novel insight into the potential underlying mechanisms behind NF2-VS. These findings may facilitate the identification of novel therapeutic targets in the future.
神经纤维瘤病 2 型(NF2)相关听神经瘤(NF2-VS)是一种罕见的遗传性疾病,导致双侧听神经瘤。然而,疾病的确切发病机制仍不清楚。本研究旨在使用生物信息学分析鉴定潜在的关键基因和治疗靶点。我们从数据库中检索了 NF2-VS 的 mRNA 表达谱(GSE108524 和 GSE141801),并选择了前 25%样本间方差最大的基因进行加权相关网络分析。随后,我们进行了基因本体论术语和京都基因与基因组百科全书信号网络富集分析。STRING 数据库用于构建蛋白质-蛋白质相互作用(PPI)轴。通过 miRTarBase 数据库生成 mRNA-miRNA 调节网络。在两个数据集的 R 包“limma”中识别差异表达基因(DEGs),通过交集共同 DEGs、PPI 轴中的候选关键基因和关键模块中的候选关键基因筛选关键基因。最后,将共同 DEGs 上传到连接图谱数据库以确定候选药物。基于我们的观察,蓝色模块与 NF2-VS 关系最密切,其中包含 NF2 基因。通过富集分析,我们证明了蓝色模块与细胞增殖、迁移、黏附、连接和肌动蛋白骨架的调节密切相关。总的来说,在两个数据集中共筛选出 356 个共同 DEGs,在 PPI 轴中选择了 33 个度数大于 15 的基因作为候选关键基因。随后,确定了 4 个基因,即 GLUL、CAV1、MYH11 和 CCND1 为真实的关键基因。此外,还确定了 10 种具有富集分数<-0.7 的药物作为候选药物。我们的结论为 NF2-VS 的潜在机制提供了新的见解。这些发现可能有助于未来确定新的治疗靶点。