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具有四个自噬相关基因的风险特征可预测多形性胶质母细胞瘤的生存。

A risk signature with four autophagy-related genes for predicting survival of glioblastoma multiforme.

机构信息

Department of Neurosurgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.

Wuxi School of Medicine, Jiangnan University, Wuxi, China.

出版信息

J Cell Mol Med. 2020 Apr;24(7):3807-3821. doi: 10.1111/jcmm.14938. Epub 2020 Feb 17.

Abstract

Glioblastoma multiforme (GBM) is a devastating brain tumour without effective treatment. Recent studies have shown that autophagy is a promising therapeutic strategy for GBM. Therefore, it is necessary to identify novel biomarkers associated with autophagy in GBM. In this study, we downloaded autophagy-related genes from Human Autophagy Database (HADb) and Gene Set Enrichment Analysis (GSEA) website. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were performed to identify genes for constructing a risk signature. A nomogram was developed by integrating the risk signature with clinicopathological factors. Time-dependent receiver operating characteristic (ROC) curve and calibration plot were used to evaluate the efficiency of the prognostic model. Finally, four autophagy-related genes (DIRAS3, LGALS8, MAPK8 and STAM) were identified and were used for constructing a risk signature, which proved to be an independent risk factor for GBM patients. Furthermore, a nomogram was developed based on the risk signature and clinicopathological factors (IDH1 status, age and history of radiotherapy or chemotherapy). ROC curve and calibration plot suggested the nomogram could accurately predict 1-, 3- and 5-year survival rate of GBM patients. For function analysis, the risk signature was associated with apoptosis, necrosis, immunity, inflammation response and MAPK signalling pathway. In conclusion, the risk signature with 4 autophagy-related genes could serve as an independent prognostic factor for GBM patients. Moreover, we developed a nomogram based on the risk signature and clinical traits which was validated to perform better for predicting 1-, 3- and 5-year survival rate of GBM.

摘要

多形性胶质母细胞瘤(GBM)是一种破坏性的脑肿瘤,目前尚无有效的治疗方法。最近的研究表明,自噬是治疗 GBM 的一种很有前途的治疗策略。因此,有必要确定与 GBM 自噬相关的新型生物标志物。在这项研究中,我们从人类自噬数据库(HADb)和基因集富集分析(GSEA)网站下载了自噬相关基因。使用最小绝对收缩和选择算子(LASSO)回归和多变量 Cox 回归分析来确定用于构建风险特征的基因。通过将风险特征与临床病理因素相结合,开发了一个列线图。时间依赖性接收器操作特征(ROC)曲线和校准图用于评估预测模型的效率。最后,确定了 4 个与自噬相关的基因(DIRAS3、LGALS8、MAPK8 和 STAM),并用于构建风险特征,该特征被证明是 GBM 患者的独立危险因素。此外,基于风险特征和临床病理因素(IDH1 状态、年龄和放疗或化疗史),开发了一个列线图。ROC 曲线和校准图表明,该列线图可以准确预测 GBM 患者的 1、3 和 5 年生存率。功能分析表明,风险特征与细胞凋亡、坏死、免疫、炎症反应和 MAPK 信号通路有关。总之,该列线图具有 4 个与自噬相关的基因,可作为 GBM 患者的独立预后因素。此外,我们基于风险特征和临床特征开发了一个列线图,验证结果表明该列线图在预测 GBM 患者 1、3 和 5 年生存率方面表现更好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b43e/7171404/fdba3284bcd4/JCMM-24-3807-g001.jpg

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