细胞外基质(ECM)在胶质瘤的进展和转移中起着至关重要的作用,是肿瘤微环境的重要组成部分。基质组由ECM组分和相关蛋白质组成。已经有一些关于矩阵对神经胶质瘤免疫微环境的影响的研究,但这些研究大多是针对个体神经胶质瘤免疫相关矩阵而非积分分析进行的.因此,需要对神经胶质瘤中所有潜在的免疫相关矩阵进行全面分析.这里,我们将癌症基因组图谱(TCGA)数据库中的667例胶质瘤患者分为低,中度,和高免疫浸润组。分析三组间差异表达的免疫相关矩阵,并建立了风险签名。筛选了8个与免疫相关的母系,即,LIF,LOX,MMP9、S100A4、SRPX2、SLIT1、SMOC1和TIMP1。卡普兰·迈耶分析,构建工作特征曲线(ROC)分析和列线图,分析脑胶质瘤患者的风险特征与预后的关系.风险特征与神经胶质瘤患者的总生存期(OS)显着相关。高风险和低风险特征也与一些免疫检查点相关。此外,对高危组和低危组的体细胞突变和抗PD1/L1免疫治疗反应的分析显示,高危组的预后较差,抗PD1/L1免疫治疗反应较高..我们对免疫相关矩阵的分析可能会提高对脑胶质瘤免疫微环境特征的理解,并为未来脑胶质瘤免疫治疗的发展提供方向。
The extracellular matrix (ECM) plays a vital role in the progression and metastasis of glioma and is an important part of the tumor microenvironment. The
matrisome is composed of ECM components and related proteins. There have been several studies on the effects of matrisomes on the glioma immune microenvironment, but most of these studies were performed on individual glioma immune-related matrisomes rather than integral analysis. Hence, an overall analysis of all potential immune-related matrisomes in gliomas is needed. Here, we divided 667 glioma patients in The Cancer Genome Atlas (TCGA) database into low, moderate, and high immune infiltration groups. Immune-related matrisomes differentially expressed among the three groups were analyzed, and a risk signature was established. Eight immune-related matrisomes were screened, namely, LIF, LOX, MMP9, S100A4, SRPX2, SLIT1, SMOC1, and TIMP1. Kaplan-Meier analysis, operating characteristic curve analysis, and nomogram were constructed to analyze the relationships between risk signatures and the prognosis of glioma patients. The risk signature was significantly correlated with the overall survival of glioma patients. Both high- and low-risk signatures were also associated with some immune checkpoints. In addition, analysis of somatic mutations and anti-PD1/L1 immunotherapy responses in the high- and low-risk groups showed that the high-risk group had worse prognosis and a higher response to anti-PD1/L1 immunotherapy. Our analysis of immune-related matrisomes may improve understanding of the characteristics of the glioma immune microenvironment and provide direction for glioma immunotherapy development in the future.