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胶质母细胞瘤的预后预测模型:一种铁死亡相关基因预测模型及独立外部验证

Prognostic Prediction Model for Glioblastoma: A Ferroptosis-Related Gene Prediction Model and Independent External Validation.

作者信息

Chen Wenlin, Lei Chuxiang, Wang Yuekun, Guo Dan, Zhang Sumei, Wang Xiaoxi, Zhang Zixin, Wang Yu, Ma Wenbin

机构信息

Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.

Department of Cardiac Surgery, State Key Laboratory of Cardiovascular Diseases, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.

出版信息

J Clin Med. 2023 Feb 8;12(4):1341. doi: 10.3390/jcm12041341.

Abstract

Glioblastoma (GBM) is the most common primary malignant intracranial tumor with a poor prognosis. Ferroptosis is a newly discovered, iron-dependent, regulated cell death, and recent studies suggest its close correlation to GBM. The transcriptome and clinical data were obtained for patients diagnosed with GBM from TCGA, GEO, and CGGA. Ferroptosis-related genes were identified, and a risk score model was constructed using Lasso regression analyses. Survival was evaluated by univariate or multivariate Cox regressions and Kaplan-Meier analyses, and further analyses were performed between the high- and low-risk groups. There were 45 ferroptosis-related different expressed genes between GBM and normal brain tissues. The prognostic risk score model was based on four favorable genes, and , and four unfavorable genes, , and . A significant difference in OS between high- and low-risk groups was observed in both the training cohort ( < 0.001) and the validation cohorts ( = 0.029 and 0.037). Enrichment analysis of pathways and immune cells and functioning was conducted between the two risk groups. A novel prognostic model for GBM patients was developed based on eight ferroptosis-related genes, suggesting a potential prediction effect of the risk score model in GBM.

摘要

胶质母细胞瘤(GBM)是最常见的原发性恶性颅内肿瘤,预后较差。铁死亡是一种新发现的、铁依赖性的、受调控的细胞死亡,最近的研究表明其与GBM密切相关。从TCGA、GEO和CGGA获取了被诊断为GBM的患者的转录组和临床数据。鉴定了铁死亡相关基因,并使用套索回归分析构建了风险评分模型。通过单因素或多因素Cox回归及Kaplan-Meier分析评估生存率,并在高风险组和低风险组之间进行进一步分析。GBM与正常脑组织之间存在45个铁死亡相关的差异表达基因。预后风险评分模型基于四个有利基因 和 ,以及四个不利基因 、 和 。在训练队列( < 0.001)和验证队列( = 0.029和0.037)中,高风险组和低风险组之间的总生存期均存在显著差异。对两个风险组之间的通路、免疫细胞及功能进行了富集分析。基于八个铁死亡相关基因建立了一种新的GBM患者预后模型,表明风险评分模型在GBM中具有潜在的预测作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a5c3/9960289/2fbd0c9e465f/jcm-12-01341-g001.jpg

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