利用生物信息学分析和实验验证鉴定参与主动脉夹层的关键免疫浸润相关基因

Identification of Key Immune Infiltration Related Genes Involved in Aortic Dissection Using Bioinformatic Analyses and Experimental Verification.

作者信息

Zheng Lin, Yang Yusi, Liu Jie, Zhao Tianliang, Zhang Xin, Chen Lihua

机构信息

Department of Vascular Surgery, the Second Hospital, Shanxi Medical University, Taiyuan, 030001, People's Republic of China.

Department of Cardiology, Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences Tongji Shanxi Hospital, Taiyuan, 030032, People's Republic of China.

出版信息

J Inflamm Res. 2024 Apr 5;17:2119-2135. doi: 10.2147/JIR.S434993. eCollection 2024.

PURPOSE

Immune microenvironment plays an important role in aortic dissection (AD). Therefore, novel immune biomarkers may facilitate AD prevention, diagnosis, and treatment. This study aimed at mining key immune-related genes and relevant mechanisms involved in AD pathogenesis.

PATIENTS AND METHODS

Key immune cells in AD were identified by ssGESA algorithm. Next, genes associated with key immune cells were screened by weighted gene coexpression network analysis (WGCNA). Then hub immune genes were picked from protein-protein interaction network of overlapped genes from differential expression and WGCNA analyses by cytohubba plug-in. Their diagnostic potential was evaluated in two independent cohorts from GEO database. In addition, the expressions of hub immune genes were determined by quantitative RT-PCR, immunohistochemistry, and Western blotting in dissected and normal aortic tissues.

RESULTS

Activated B cells, CD56dim natural killer cells, eosinophils, gamma delta T cells, immature B cells, natural killer cells and type 17 T helper cells were identified as key immune cells in AD. Thereafter, a gene module significantly correlated with key immune cells were found by WGCNA method. Subsequently, KDR, IGF1, NOS3, PECAM1, GAPDH, FLT1, DLL4, CDH5, VWF, and TEK were identified as hub immune cell related genes by PPI network analysis, which may be potential diagnostic markers for AD, as evidenced by ROC curves. Moreover, the decreased expression of VWF in AD was validated at both mRNA and protein levels, and its expression was significantly positive correlated with the marker of smooth muscle cells, ACTA2, in AD. Further immunofluorescent results showed that VWF was colocalized with ACTA2 in aortic tissues.

CONCLUSION

We identified key immune cells and hub immune cell-related genes involved in AD. Moreover, we found that VWF was co-expressed with the smooth muscle cell marker ACTA2, indicating the important role of VWF in smooth muscle cell loss in AD pathogenesis.

目的

免疫微环境在主动脉夹层（AD）中起重要作用。因此，新型免疫生物标志物可能有助于AD的预防、诊断和治疗。本研究旨在挖掘参与AD发病机制的关键免疫相关基因及相关机制。

患者和方法

通过单样本基因集富集分析（ssGESA）算法鉴定AD中的关键免疫细胞。接下来，通过加权基因共表达网络分析（WGCNA）筛选与关键免疫细胞相关的基因。然后，通过Cytohubba插件从差异表达分析和WGCNA分析重叠基因的蛋白质-蛋白质相互作用网络中挑选出核心免疫基因。在来自基因表达综合数据库（GEO）的两个独立队列中评估它们的诊断潜力。此外，通过定量逆转录聚合酶链反应（qRT-PCR）、免疫组织化学和蛋白质印迹法检测核心免疫基因在夹层主动脉组织和正常主动脉组织中的表达。

结果

活化B细胞、CD56dim自然杀伤细胞、嗜酸性粒细胞、γδT细胞、未成熟B细胞、自然杀伤细胞和17型辅助性T细胞被鉴定为AD中的关键免疫细胞。此后，通过WGCNA方法发现一个与关键免疫细胞显著相关的基因模块。随后，通过蛋白质-蛋白质相互作用网络分析确定血管内皮生长因子受体2（KDR）、胰岛素样生长因子1（IGF1）、一氧化氮合酶3（NOS3）、血小板内皮细胞黏附分子1（PECAM1）、甘油醛-3-磷酸脱氢酶（GAPDH）、血管内皮生长因子受体1（FLT1）、三角洲样蛋白4（DLL4）、血管内皮钙黏蛋白（CDH5）、血管性血友病因子（VWF）和内皮酪氨酸激酶（TEK）为核心免疫细胞相关基因，ROC曲线证实这些基因可能是AD的潜在诊断标志物。此外，AD中VWF在mRNA和蛋白质水平的表达均降低，且其表达与AD中平滑肌细胞标志物平滑肌肌动蛋白2（ACTA2）显著正相关。进一步的免疫荧光结果显示，VWF与ACTA2在主动脉组织中共定位。