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与胶质瘤临床结局和肿瘤免疫微环境相关的血管生成相关基因表达特征的构建与验证

Construction and validation of an angiogenesis-related gene expression signature associated with clinical outcome and tumor immune microenvironment in glioma.

作者信息

Hu Tianhao, Wang Yutao, Wang Xiaoliang, Wang Run, Song Yifu, Zhang Li, Han Sheng

机构信息

Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, China.

Department of Urology, The First Hospital of China Medical University, Shenyang, China.

出版信息

Front Genet. 2022 Aug 11;13:934683. doi: 10.3389/fgene.2022.934683. eCollection 2022.

Abstract

Glioma is the most prevalent malignant intracranial tumor. Many studies have shown that angiogenesis plays a crucial role in glioma tumorigenesis, metastasis, and prognosis. In this study, we conducted a comprehensive analysis of angiogenesis-related genes (ARGs) in glioma. RNA-sequencing data of glioma patients were obtained from TCGA and CGGA databases. V consensus clustering analysis, ARGs in the sequencing data were distinctly classified into two subgroups. We performed univariate Cox regression analysis to determine prognostic differentially expressed ARGs and least absolute shrinkage and selection operator Cox regression to construct a 14-ARG risk signature. The CIBERSORT algorithm was used to explore immune cell infiltration, and the ESTIMATE algorithm was applied to calculate immune and stromal scores. We found that the 14-ARG signature reflected the infiltration characteristics of different immune cells in the tumor immune microenvironment. Additionally, total tumor mutational burden increased significantly in the high-risk group. We combined the 14-ARG signature with patient clinicopathological data to construct a nomogram for predicting 1-, 3-, and 5-year overall survival with good accuracy. The predictive value of the prognostic model was verified in the CGGA cohort. was a potential biomarker of glioma risk and was involved in the proliferation, invasion, and angiogenesis of glioma cells. In conclusion, we established and validated a novel ARG risk signature that independently predicted the clinical outcomes of glioma patients and was associated with the tumor immune microenvironment.

摘要

胶质瘤是最常见的颅内恶性肿瘤。许多研究表明,血管生成在胶质瘤的发生、转移和预后中起着关键作用。在本研究中,我们对胶质瘤中与血管生成相关的基因(ARGs)进行了全面分析。从TCGA和CGGA数据库中获取了胶质瘤患者的RNA测序数据。通过一致性聚类分析,测序数据中的ARGs被明确分为两个亚组。我们进行单变量Cox回归分析以确定预后差异表达的ARGs,并采用最小绝对收缩和选择算子Cox回归构建了一个包含14个ARGs的风险特征。使用CIBERSORT算法探索免疫细胞浸润情况,并应用ESTIMATE算法计算免疫和基质评分。我们发现,14个ARGs的特征反映了肿瘤免疫微环境中不同免疫细胞的浸润特征。此外,高危组的肿瘤总突变负担显著增加。我们将14个ARGs的特征与患者临床病理数据相结合,构建了一个列线图,用于预测1年、3年和5年总生存率,准确率较高。在CGGA队列中验证了该预后模型的预测价值。它是胶质瘤风险的潜在生物标志物,参与了胶质瘤细胞的增殖、侵袭和血管生成。总之,我们建立并验证了一种新的ARGs风险特征,该特征可独立预测胶质瘤患者的临床结局,并与肿瘤免疫微环境相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/23cf/9403517/f94db08657ce/fgene-13-934683-g001.jpg

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