WGCNA联合机器学习算法鉴定慢性鼻窦炎伴鼻息肉氧化应激相关标志物

Identification of oxidative stress-related biomarkers in chronic rhinosinusitis with nasal polyps using WGCNA combined with machine learning algorithms

目的:通过分析慢性鼻窦炎伴鼻息肉(CRSwNP)的转录组测序数据,鉴定与氧化应激相关的诊断标志物,并初步探究其在CRSwNP中的作用。方法:使用4个CRSwNP测序数据集,运用差异表达基因(differentially expressed genes,DEGs)分析、加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)和3种机器学习方法筛选Hub基因,并通过外部数据集、临床样本实时荧光定量聚合酶链反应(real-time quantitative polymerase chain reaction,Real-time qPCR)及免疫荧光染色进行验证,通过受试者工作特征曲线(ROC)评估基因诊断效能,并对这些基因进行功能和通路富集分析、免疫相关性分析及细胞群定位,构建竞争性内源RNA(competing endogenous RNA,CeRNA)网络并预测潜在靶向药物。采用SPSS 26.0和Graphpad Prism9软件进行统计分析及作图。结果:通过数据分析和临床验证,我们在4138个DEGs中发现CP、SERPINF1和GSTO2是与CRSwNP相关的氧化应激标志物。CRSwNP中CP和SERPINF1表达上升,GSTO2表达下降,差异具有统计学意义(P<0.05);曲线下面积(AUC)>0.7,显示其为有效诊断指标。功能分析表明,这些基因主要与脂质代谢、细胞黏附迁移、免疫等功能相关。单细胞数据分析及免疫荧光染色发现SERPINF1主要分布在上皮细胞、基质细胞和成纤维细胞,CP主要分布在上皮细胞,GSTO2在鼻息肉的上皮细胞及成纤维细胞中仅有少量分布。随后,我们构建了CP和GSTO2的CeRNA调控网络,并预测了靶向CP的潜在药物。结论:本研究鉴定并通过临床样本验证发现CP、SERPINF1和GSTO2可作为CRSwNP氧化应激相关的诊疗标志物。

Objective To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal polyps(CRSwNP)by analyzing transcriptome sequencing data,and to investigate their roles in CRSwNP.Methods Utilizing four CRSwNP sequencing datasets,differentially expressed genes(DEGs)analysis,weighted gene co-expression network analysis(WGCNA),and three machine learning methods for Hub gene selection were performed in this study.Subsequent validation was carried out using external datasets,as well as real-time quantitative polymerase chain reaction(Real-time qPCR),and immunofluorescence staining of clinical samples.Moreover,the diagnostic efficacy of the genes was assessed by receiver operating characteristic(ROC)curve,followed by functional and pathway enrichment analysis,immune-related analysis,and cell population localization.Additionally,a competing endogenous RNA(CeRNA)network was constructed to predict potential drug targets.Statistical analysis and plotting were conducted using SPSS 26.0 and Graphpad Prism9 software.Results Through data analysis and clinical validation,CP,SERPINF1 and GSTO2 were identified among 4138 DEGs as oxidative stress markers related to CRSwNP.Specifically,the expression of CP and SERPINF1 increased in CRSwNP,whereas that of GSTO2 decreased,with statistically significant differences(P<0.05).Additionally,an area under the curve(AUC)>0.7 indicated their effectiveness as diagnostic indicators.Importantly,functional analysis indicated that these genes were mainly related to lipid metabolism,cell adhesion migration,and immunity.Single-cell data analysis revealed that SERPINF1 was mainly distributed in epithelial cells,stromal cells,and fibroblasts,while CP was primarily located in epithelial cells,and GSTO2 was minimally present in the epithelial cells and fibroblasts of nasal polyps.Consequently,a CeRNA regulatory network was constructed for the genes CP and GSTO2.This construction allowed for the prediction of potential drugs that could target CP.Conclusion This study successfully identifies CP,SERPINF1 and GSTO2 as diagnostic and therapeutic markers related to oxidative stress in CRSwNP.