基于生物信息学识别和分析慢性鼻窦炎新的生物标志物
Identification and Analysis of Novel Biomarkers for Chronic Sinusitis Based on Bioinformatics
DOI: 10.12677/hjbm.2025.154074, PDF,   
作者: 刘 聪:大理大学临床医学院,云南 大理;毛春鹏:昆明医科大学公共卫生学院,云南 昆明;陈银忠*:大理大学第一附属医院耳鼻咽喉头颈外科,云南 大理
关键词: 慢性鼻窦炎生物标志物治疗靶点生物信息学GEO数据库差异表达基因加权基因共表达网络分析Chronic Rhinosinusitis Biomarker Therapeutic Target Bioinformatics GEO Database DEGs WGCNA
摘要: 目的:采用生物信息学方法系统筛选慢性鼻窦炎(CRS)的新型治疗靶点。方法:从GEO数据库获取GSE36830、GSE179265和GSE136825三个独立数据集,分别对其进行差异表达分析并得到差异表达基因(DEGs),对DEGs进行GO功能注释和KEGG通路富集分析,整合Cytoscape软件的cytoHubba插件和加权基因共表达网络(WGCNA)分析筛选关键基因,在GSE136825数据集中验证关键基因的表达情况。结果:三个数据集分别鉴定出428、1896和1263个DEGs,富集分析表示这些基因显著富集于免疫相关通路。WGCNA分析确定蓝绿色模块(turquoise module)与CRS相关性最高,筛选出7个核心基因:CD209、CD86、CSF1R、IL2RA、ITGAM、SIGLEC1和CD33。结论:CD209、CD86、CSF1R、IL2RA、ITGAM、SIGLEC1参与了CRS疾病的发病机制,且CD209、IL2RA、SIGLEC1具有作为CRS诊断标志物和靶向治疗靶点的潜力,为CRS的诊断标志物和治疗靶点。
Abstract: Objective: To systematically identify novel therapeutic targets for chronic rhinosinusitis (CRS) using bioinformatics approaches. Methods: Three independent datasets (GSE36830, GSE179265, and GSE136825) were obtained from the GEO database. Differential expression analysis was performed to identify differentially expressed genes (DEGs). Functional annotation (GO) and pathway enrichment (KEGG) analyses were conducted on the DEGs. Key genes were screened by integrating the cytoHubba plugin in Cytoscape and weighted gene co-expression network analysis (WGCNA). The expression patterns of key genes were validated in the GSE136825 dataset. Results: A total of 428, 1896, and 1263 DEGs were identified in the three datasets, respectively. Enrichment analysis revealed that these genes were significantly associated with immune-related pathways. WGCNA identified the turquoise module as the most correlated with CRS, leading to the selection of 7 core genes: CD209, CD86, CSF1R, IL2RA, ITGAM, SIGLEC1, and CD33. Conclusion: CD209, CD86, CSF1R, IL2RA, ITGAM, and SIGLEC1 are involved in the pathogenesis of CRS. CD209, IL2RA, and SIGLEC1 show potential as diagnostic biomarkers and targeted therapeutic candidates for CRS.
文章引用:刘聪, 毛春鹏, 陈银忠. 基于生物信息学识别和分析慢性鼻窦炎新的生物标志物[J]. 生物医学, 2025, 15(4): 665-680. https://doi.org/10.12677/hjbm.2025.154074

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