The molecular feature of macrophages in tumor immune microenvironment of glioma patients.
The molecular feature of macrophages in tumor immune microenvironment of glioma patients.
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胶质瘤患者肿瘤免疫微环境中巨噬细胞的分子特征
DOI：
10.1016/j.csbj.2021.08.019
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发表时间：
2021
影响因子：
6
通讯作者：
Liu Z
中科院分区：
文献类型：
--
作者：
Zhang H;Luo YB;Wu W;Zhang L;Wang Z;Dai Z;Feng S;Cao H;Cheng Q;Liu Z
胶质瘤是中枢神经系统最常见的原发肿瘤之一。此前的研究发现，巨噬细胞积极参与肿瘤生长。采用加权基因共表达网络分析方法筛选有意义的巨噬细胞相关基因进行聚类。采用PAMR、支持向量机和神经网络对聚类结果进行验证。通过体细胞突变和甲基化来确定所鉴定的簇的特征。经弹性回归和主成分分析后，分层组之间的差异表达基因(Deg)被用于MScore的构建。基于单细胞测序分析，评估巨噬细胞特异性基因在肿瘤微环境中的表达。共有来自15个胶质瘤数据集的2365个样本和5842个泛癌样本用于MScore的外部验证。巨噬细胞被证实与胶质瘤患者的生存呈负相关。通过弹性回归和主成分分析获得的26个巨噬细胞特异性DEG在单细胞水平上在巨噬细胞中高表达。MScore在胶质瘤中的预后价值是通过浸润性微环境中活跃的促炎和代谢情况以及具有这一特征的样本对免疫治疗的反应来验证的。MScore成功地对15个外部胶质瘤数据集和泛癌症数据集的患者生存概率进行了分层，这些数据集预测了更差的生存结果。湘雅胶质瘤队列的测序数据和免疫组织化学结果证实了MScore的预后价值。基于MScore的预测模型具有较高的预测准确率。我们的发现有力地支持了巨噬细胞，特别是M2巨噬细胞在胶质瘤进展中的调节作用，并值得进一步的实验研究。
Gliomas are one of the most common types of primary tumors in central nervous system. Previous studies have found that macrophages actively participate in tumor growth. Weighted gene co-expression network analysis was used to identify meaningful macrophage-related gene genes for clustering. Pamr, SVM, and neural network were applied for validating clustering results. Somatic mutation and methylation were used for defining the features of identified clusters. Differentially expressed genes (DEGs) between the stratified groups after performing elastic regression and principal component analyses were used for the construction of MScores. The expression of macrophage-specific genes were evaluated in tumor microenvironment based on single cell sequencing analysis. A total of 2365 samples from 15 glioma datasets and 5842 pan-cancer samples were used for external validation of MScore. Macrophages were identified to be negatively associated with the survival of glioma patients. Twenty-six macrophage-specific DEGs obtained by elastic regression and PCA were highly expressed in macrophages at single-cell level. The prognostic value of MScores in glioma was validated by the active proinflammatory and metabolic profile of infiltrating microenvironment and response to immunotherapies of samples with this signature. MScores managed to stratify patient survival probabilities in 15 external glioma datasets and pan-cancer datasets, which predicted worse survival outcome. Sequencing data and immunohistochemistry of Xiangya glioma cohort confirmed the prognostic value of MScores. A prognostic model based on MScores demonstrated high accuracy rate. Our findings strongly support a modulatory role of macrophages, especially M2 macrophages in glioma progression and warrants further experimental studies.
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