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巨噬细胞极化相关基因特征可用于胶质瘤的风险分层和生存预后评估。

Macrophage polarization-related gene signature for risk stratification and prognosis of survival in gliomas.

机构信息

Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, People's Republic of China.

Hypothalamic-Pituitary Research Center, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.

出版信息

J Cell Mol Med. 2024 Oct;28(20):e70000. doi: 10.1111/jcmm.70000.

DOI:10.1111/jcmm.70000
PMID:39448550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11502305/
Abstract

Macrophage polarization plays an essential role in tumour immune cell infiltration and tumour growth. In this study, we selected a series of genes distinguishing between M1 and M2 macrophages and explored their prognostic value in gliomas. A total of 170 genes were included in our study. The CGGA database was used as the training cohort and the TCGA database as the validation cohort. The biological processes and functions were identified by GO and KEGG analysis. Kaplan-Meier analysis was used to compare survival differences between groups. Importantly, we built a risk score model using Cox regression analysis based on the CGGA and verified it in the TCGA database and our sequencing data. Patients with gliomas in the high-risk group were associated with high pathologic grade, IDH WT status, MGMT promoter unmethylation, 1p19q non-codeletion and prone to have a poor outcome. GEPIA results revealed that CD300C, CNRIP1 and MYO1F are the most related genes of immune infiltrations. The differential expression of these genes between low-grade gliomas and glioblastomas was confirmed by q-RT-PCR. Macrophage polarization-related gene signatures can predict the malignancy and outcome of patients with gliomas and might act as a promising target for glioma immunotherapy in the future.

摘要

巨噬细胞极化在肿瘤免疫细胞浸润和肿瘤生长中起着至关重要的作用。在本研究中,我们选择了一系列区分 M1 和 M2 巨噬细胞的基因,并探讨了它们在胶质瘤中的预后价值。我们的研究共纳入了 170 个基因。CGGA 数据库作为训练队列,TCGA 数据库作为验证队列。通过 GO 和 KEGG 分析鉴定了生物学过程和功能。通过 Kaplan-Meier 分析比较了各组之间的生存差异。重要的是,我们基于 CGGA 构建了一个风险评分模型,并在 TCGA 数据库和我们的测序数据中进行了验证。CGPA 高风险组的胶质瘤患者与高级别病理分级、IDH WT 状态、MGMT 启动子未甲基化、1p19q 非缺失和预后不良相关。GEPIA 结果表明,CD300C、CNRIP1 和 MYO1F 是与免疫浸润最相关的基因。通过 q-RT-PCR 证实了这些基因在低级别胶质瘤和胶质母细胞瘤之间的差异表达。巨噬细胞极化相关基因特征可预测胶质瘤患者的恶性程度和预后,未来可能成为胶质瘤免疫治疗的有希望的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e958/11502305/14e9b0c29e41/JCMM-28-e70000-g007.jpg
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本文引用的文献

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Construction and validation of a risk model based on the key SNARE proteins to predict the prognosis and immune microenvironment of gliomas.基于关键SNARE蛋白构建和验证风险模型以预测胶质瘤的预后和免疫微环境
Front Mol Neurosci. 2023 Dec 5;16:1304224. doi: 10.3389/fnmol.2023.1304224. eCollection 2023.
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Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma.利用与铁死亡相关的长链非编码RNA特征预测胶质瘤的预后和免疫治疗
Cancer Cell Int. 2023 Dec 8;23(1):316. doi: 10.1186/s12935-023-03147-7.
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Identification of telomere-associated gene signatures to predict prognosis and drug sensitivity in glioma.
鉴定端粒相关基因特征以预测脑胶质瘤的预后和药物敏感性。
Comput Biol Med. 2024 Jan;168:107750. doi: 10.1016/j.compbiomed.2023.107750. Epub 2023 Nov 24.
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Glioma stem cell signature predicts the prognosis and the response to tumor treating fields treatment.胶质母细胞瘤干细胞标志物可预测预后和对肿瘤治疗电场治疗的反应。
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Oncogenic Vav1-Myo1f induces therapeutically targetable macrophage-rich tumor microenvironment in peripheral T cell lymphoma.致癌性 Vav1-Myo1f 诱导外周 T 细胞淋巴瘤中具有治疗靶向性的富含巨噬细胞的肿瘤微环境。
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