Duan Yang, Ni Songjia, Zhao Kai, Qian Jing, Hu Xinyue
Department of Spine Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Department of Orthopaedic Trauma, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Front Cell Dev Biol. 2022 Aug 10;10:914781. doi: 10.3389/fcell.2022.914781. eCollection 2022.
Ligamentum flavum hypertrophy (LFH) is a common cause of spinal stenosis. The aim of the current study was to identify the differentially expressed genes (DEGs) in LFH and the molecular mechanisms underlying the development of and immune responses to LFH. The gene expression omnibus (GEO) database was used to obtain the GSE113212 dataset, and the DEGs were derived from microarray data. To identify critical genes and signaling pathways, gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network analyses were performed, followed by immune cell infiltration and Friends analyses using the retrieved datasets. The results were validated using quantitative real-time PCR. The 1530 DEGs identified comprised 971 upregulated and 559 downregulated genes. KEGG analysis revealed that DEGs were mostly enriched in the PI3K-Akt signaling pathway, while PPI network analysis identified tumor necrosis factor, interleukin (IL)-6, IL-10, epidermal growth factor receptor, and leptin as important nodes, which was validated by qPCR and IHC in human LFH tissues . A significant positive correlation was found between key LFH immune-related DEGs and several immune cell types, including T and B cells. The findings of the present study might lead to novel therapeutic targets and clinical approaches, as they provide insights into the molecular mechanisms of LFH.
黄韧带肥厚(LFH)是椎管狭窄的常见原因。本研究的目的是确定LFH中差异表达基因(DEGs)以及LFH发生发展和免疫反应的分子机制。利用基因表达综合数据库(GEO)获取GSE113212数据集,并从微阵列数据中得出DEGs。为了确定关键基因和信号通路,进行了基因本体富集分析、京都基因与基因组百科全书(KEGG)富集分析和蛋白质-蛋白质相互作用(PPI)网络分析,随后使用检索到的数据集进行免疫细胞浸润分析和Friend分析。结果通过定量实时PCR进行验证。鉴定出的1530个DEGs包括971个上调基因和559个下调基因。KEGG分析显示,DEGs主要富集于PI3K-Akt信号通路,而PPI网络分析确定肿瘤坏死因子、白细胞介素(IL)-6、IL-10、表皮生长因子受体和瘦素为重要节点,这在人LFH组织中通过qPCR和免疫组化得到了验证。发现关键的LFH免疫相关DEGs与包括T细胞和B细胞在内的几种免疫细胞类型之间存在显著正相关。本研究结果可能会带来新的治疗靶点和临床方法,因为它们为LFH的分子机制提供了见解。