Li Shifu, Zhang Qian, Weng Ling, Li Jian
Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
National Clinical Research Center for Geriatric Disorders, Central South University, Changsha, China.
Front Genet. 2022 Oct 10;13:1014264. doi: 10.3389/fgene.2022.1014264. eCollection 2022.
Inflammatory responses have drawn more attention to atherosclerosis; however, the immune-related genes (IRGs) as a prognostic factor in atherosclerotic plaque remain to be fully elucidated. Here, the purpose of this study was to investigate whether the IRGs could be identified as a reliable biomarker for predicting ischemic events in patients undergoing carotid endarterectomy (CEA). Two datasets GSE97210 and GSE21545 were downloaded from the Gene Expression Omnibus (GEO) database. The dataset GSE97210 was used to explore the significant pathways and differentially expressed IRGs (DEIRGs) between plaques and controls, which were further screened to identify the prognostic DEIRGs in the GSE21545 dataset. The identification of molecular subgroups with the prognostic gene expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. Functional analyses including GO, KEGG, GSVA, and GSEA analyses, and immune analyses including xCell and ssGSEA algorithms were conducted to elucidate the underlying mechanisms. The prognostic risk model was constructed using the LASSO algorithm and multivariate Cox regression analysis. A total of 796 DEIRGs (including 588 upregulated and 208 downregulated) were identified. Nine prognostic DEIRGs were further screened with univariate Cox regression analysis. Two clusters with different prognosis were grouped based on the prognostic DEIRGs. Immune infiltration analysis shows that cluster 2 with a better prognosis presented with a higher immune response than cluster 1. A prognostic model based on seven IRGs (IL2RA, NR4A2, DES, ERAP2, SLPI, RASGRP1, and AGTR2) was developed and verified. Consistent with the immune analysis of the cluster, the immune infiltration in the low-risk group with a better prognosis was also more active than that in the high-risk group. Finally, a nomogram based on the seven genes was constructed, which might have future implications in clinical care. The expression of immune-related genes is correlated with the immune microenvironment of atherosclerotic patients and could be applied to predict the ischemic events in patients undergoing CEA accurately.
炎症反应已使动脉粥样硬化受到更多关注；然而，免疫相关基因（IRGs）作为动脉粥样硬化斑块的一个预后因素仍有待充分阐明。在此，本研究的目的是调查IRGs是否可被鉴定为预测接受颈动脉内膜切除术（CEA）患者缺血事件的可靠生物标志物。从基因表达综合数据库（GEO）下载了两个数据集GSE97210和GSE21545。数据集GSE97210用于探索斑块与对照之间的显著通路和差异表达的IRGs（DEIRGs），进一步筛选这些DEIRGs以鉴定GSE21545数据集中的预后DEIRGs。通过非负矩阵分解（NMF）聚类实现具有预后基因表达模式的分子亚组的鉴定。进行了包括GO、KEGG、GSVA和GSEA分析的功能分析，以及包括xCell和ssGSEA算法的免疫分析以阐明潜在机制。使用LASSO算法和多变量Cox回归分析构建预后风险模型。共鉴定出796个DEIRGs（包括588个上调和208个下调）。通过单变量Cox回归分析进一步筛选出9个预后DEIRGs。基于预后DEIRGs将两个具有不同预后的簇进行分组。免疫浸润分析表明，预后较好的簇2比簇1呈现出更高的免疫反应。开发并验证了基于7个IRGs（IL2RA、NR4A2、DES、ERAP2、SLPI、RASGRP1和AGTR2）的预后模型。与簇的免疫分析一致，预后较好的低风险组中的免疫浸润也比高风险组更活跃。最后，构建了基于这7个基因的列线图，这可能对临床护理具有未来意义。免疫相关基因的表达与动脉粥样硬化患者的免疫微环境相关，并且可应用于准确预测接受CEA患者的缺血事件。
