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基于7个铁死亡相关基因构建预测低级别胶质瘤预后和免疫治疗的风险模型。

Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes.

作者信息

Sun Liwei, Li Bing, Wang Bin, Li Jinduo, Li Jing

机构信息

Department of Intervention, Tianjin Huanhu Hospital, Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Disease, Tianjin Neurosurgical Institute, Tianjin, People's Republic of China.

Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin Neurosurgical Institute, Tianjin, People's Republic of China.

出版信息

Int J Gen Med. 2022 May 5;15:4697-4716. doi: 10.2147/IJGM.S352773. eCollection 2022.

Abstract

PURPOSE

Ferroptosis is closely associated with tumors. The purpose of this study was to investigate the correlation between ferroptosis and prognosis of low grade glioma (LGG) via construction and verification of a risk model.

PATIENTS AND METHODS

The data of LGG were downloaded from public databases. Through LASSO analysis of characteristic genes, a gene signature was constructed. Patients into were divided two groups based on risk score. Subsequently, survival, clinical phenotype, functional enrichment, immune cell infiltration and somatic mutation analysis were performed. In addition, whether ferroptosis-related genes (FRGs) signature can predict the patient's response to anti-PD-1/PD-L1 immunotherapy was also investigated.

RESULTS

FRGs signature had strong prognostic assessment ability, and high risk score was associated with poor overall survival (OS) of LGG. The high risk score group had higher degree of immune cell infiltration, stronger stromal activity, higher immune score, and high expression of immune checkpoint. In low risk score group anti-PD-1/PD-L1 immunotherapy has significant therapeutic advantages and clinical response. Genes and frequency of somatic mutations and clinical phenotypes in the high and low risk score groups were significantly different.

CONCLUSION

A prognostic model based on 7 FRGs can be used to predict the prognosis and immunotherapeutic response of LGG.

摘要

目的

铁死亡与肿瘤密切相关。本研究旨在通过构建和验证风险模型来探讨铁死亡与低级别胶质瘤(LGG)预后之间的相关性。

患者与方法

从公共数据库下载LGG数据。通过对特征基因进行LASSO分析,构建基因特征。根据风险评分将患者分为两组。随后,进行生存分析、临床表型分析、功能富集分析、免疫细胞浸润分析和体细胞突变分析。此外,还研究了铁死亡相关基因(FRGs)特征是否能够预测患者对抗PD-1/PD-L1免疫治疗的反应。

结果

FRGs特征具有较强的预后评估能力,高风险评分与LGG患者较差的总生存期(OS)相关。高风险评分组免疫细胞浸润程度更高、基质活性更强、免疫评分更高且免疫检查点表达高。在低风险评分组中,抗PD-1/PD-L1免疫治疗具有显著的治疗优势和临床反应。高、低风险评分组的体细胞突变基因及频率和临床表型存在显著差异。

结论

基于7个FRGs的预后模型可用于预测LGG的预后和免疫治疗反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/966b/9085428/ef20fffd6f21/IJGM-15-4697-g0001.jpg

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