基于WGCNA构建的免疫相关基因模型对皮肤黑素瘤及免疫微环境的影响  

Effects of Immune Related Gene Model Constructed Based on WGCNA on Skin Melanoma and Immune Microenvironment

作　　者：凌晨 宋攀 叶金茂 张海洋 孙敏 LING Chen;SONG Pan;YE Jinmao;ZHANG Haiyang;SUN Min(Department of General Surgery,Taihe Hospital,Hubei University of Medicine,Shiyan 442000,Hubei,China)

机构地区：[1]十堰市太和医院(湖北医药学院附属医院)普外科,湖北十堰430072

出　　处：《中国美容医学》2025年第2期7-14,共8页Chinese Journal of Aesthetic Medicine

基　　金：国家自然科学基金项目(编号:81902498);湖北省教育厅中青年人才项目(编号:Q20182105);湖北陈孝平科技发展基金会肝胆胰恶性肿瘤研究基金(编号:CXPJJH11800001-2018333);湖北省科技厅湖北省自然科学基金(编号:2019CFB177,2023AFB1008);湖北省卫生健康委青年人才项目(编号:WJ2021Q007)。

摘　　要：目的:基于加权基因共表达网络分析(WGCNA)构建免疫相关基因预后模型,筛选预后标记物,探索与肿瘤微环境的关系。方法:黑素瘤基因表达数据和相关临床数据从癌症基因组图谱(TCGA)和表达综合(GEO)数据库中下载。采用加权基因共表达网络分析、单因素Cox回归分析和LASSO回归分析对黑素瘤预后进行分类。采用ESTIMATE和CIBERSORT算法探讨风险评分与肿瘤免疫微环境的关系。GSEA分析用于探索生物信号通路。结果:共获得1793个标志性的免疫相关基因,其中与黑素瘤的总生存期相关的基因有246个。五个免疫相关基因的风险评分模型显示了很强的预测能力。与当前临床特征对疾病预后预测能力相比,该评分模型具有更好的预测能力。同时高、低风险评分组之间基因集富集分析(GSEA)存在多种差异信号通路。此外,风险评分模型基因作为生物标志物与肿瘤微环境中的多种免疫细胞和免疫浸润息息相关。结论:基于加权基因共表达网络分析构建了皮肤黑色素免疫相关基因预后评估模型,为预测预后提供参考,且可能通过影响肿瘤微环境中的免疫细胞的生物学功能发挥作用。Objective To construct an immune related gene prognosis model,screen prognostic markers,and explore the relationship with tumor microenvironment based on weighted gene co-expression network analysis.Methods Melanoma gene expression data and related clinical data were downloaded from the Cancer Genome Map(TCGA)and Expression Synthesis(GEO)databases.The prognosis of melanoma was classified using weighted gene co-expression network analysis,univariate Cox regression analysis,and LASSO regression analysis.The relationship between risk score and tumor immune microenvironment was investigated using ESTIMATE and CIBERSORT algorithms.GSEA analysis was used to explore signaling pathways.Results A total of 1793 significantly immune related genes were obtained,of which 246 genes were associated with the overall survival of melanoma.The risk scores model for five immune related genes showed strong predictive power.Compared to the current clinical features'ability to predict prognosis,this risk scores model had a better predictive capability.At the same time,there were multiple different signaling pathways in gene set enrichment analysis(GSEA)between high and low risk scores groups.In addition,five immune related genes were closely related to multiple immune cells and infiltration in the tumor microenvironment.Conclusion Based on weighted gene co-expression network analysis and immune related genes,a prognostic evaluation model for skin melanoma was constructed,which provided a reference for predicting prognosis and might play a role by influencing the biological functions of immune cells in the tumor microenvironment.

关 键 词：皮肤黑素瘤 免疫 预后 肿瘤微环境 免疫浸润 

分 类 号：R739.5[医药卫生—肿瘤]