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探讨脂肪酸代谢相关基因特征以预测胶质瘤患者预后和辅助免疫治疗。

Characterization of Fatty Acid Metabolism-Related Genes Landscape for Predicting Prognosis and Aiding Immunotherapy in Glioma Patients.

机构信息

Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.

Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, China.

出版信息

Front Immunol. 2022 Jul 12;13:902143. doi: 10.3389/fimmu.2022.902143. eCollection 2022.

Abstract

Glioma is a highly malignant brain tumor with a poor survival rate. The involvement of fatty acid metabolism in glioma was examined to find viable treatment options. The information was gathered from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. A prognostic signature containing fatty acid metabolism-dependent genes (FAMDs) was developed to predict glioma outcome by multivariate and most minor absolute shrinkage and selection operator (LASSO) regression analyses. In the TCGA cohort, individuals with a good score had a worse prognosis than those with a poor score, validated in the CGGA cohort. According to further research by "pRRophetic" R package, higher-risk individuals were more susceptible to crizotinib. According to a complete study of the connection between the predictive risk rating model and tumor microenvironment (TME) features, high-risk individuals were eligible for activating the immune cell-associated receptor pathway. We also discovered that anti-PD-1/PD-L1 and anti-CTLA4 immunotherapy are more effective in high-risk individuals. Furthermore, we demonstrated that CCNA2 promotes glioma proliferation, migration, and invasion and regulates macrophage polarization. Therefore, examining the fatty acid metabolism pathway aids our understanding of TME invasion properties, allowing us to develop more effective immunotherapies for glioma.

摘要

脑胶质瘤是一种高度恶性的脑肿瘤,患者的生存率较低。本研究旨在探讨脂肪酸代谢在脑胶质瘤中的作用,以期寻找可行的治疗方法。研究数据来源于癌症基因组图谱(TCGA)和中国脑胶质瘤基因组图谱(CGGA)数据库。通过多变量和最小绝对值收缩和选择算子(LASSO)回归分析,构建了一个包含脂肪酸代谢相关基因(FAMDs)的预后signature,用于预测脑胶质瘤的预后。在 TCGA 队列中,高评分患者的预后比低评分患者差,这一结果在 CGGA 队列中得到了验证。进一步通过“pRRophetic”R 包研究发现,高风险个体对克唑替尼更为敏感。通过对预测风险评分模型与肿瘤微环境(TME)特征之间关系的全面研究,发现高风险个体有激活免疫细胞相关受体通路的资格。我们还发现抗 PD-1/PD-L1 和抗 CTLA4 免疫疗法在高风险个体中更为有效。此外,我们证实 CCNA2 可促进脑胶质瘤的增殖、迁移和侵袭,并调节巨噬细胞极化。因此,研究脂肪酸代谢通路有助于我们了解 TME 的浸润特性,从而为脑胶质瘤的免疫治疗提供新的思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4f9/9315048/42ac9101e55b/fimmu-13-902143-g012.jpg

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