评估凝血相关基因模型在胶质瘤中的预测价值。

Ming Cao, Jie Chen, Rong-Zeng Guo
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引用次数: 0

摘要

目的:胶质瘤是中枢神经系统中最常见的恶性肿瘤,其预后需要识别更多的标记物:从TCGA和CGGA数据库下载胶质瘤的mRNA表达和临床数据。凝血相关基因从 KEGG 数据库下载。采用 LASSO 回归法构建表达模型。根据中位风险评分,将GBM数据分为高风险和低风险表达组,并计算出两组间总生存期和无进展生存期的差异。预后模型分别通过TCGA-LGG和CGGA胶质瘤数据库进一步验证。通过ROC分析计算了1年和3年风险评分的准确性:结果:确定了四个模型基因,即SERPINA5、PLAUR、BDKRB1和PTGIR,风险评分分别为SERPINA5*0.126264111304559 + PLAUR*0.288587629696211 + BDKRB1*0.349215422945011 + PTGIR*0.17334527969703。根据三组胶质瘤数据,按照中位风险评分将患者分为高危和低危组。高风险评分组的总生存期、无进展生存期和风险评分均差于低风险组。ROC曲线分析显示,凝血相关基因模型在1年、3年和5年的AUC值均大于0.65,验证了预后模型的可靠性:该研究建立了凝血相关基因模型与胶质瘤预后的相关性,为胶质瘤的发病机制和治疗提供了更深入的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the Predictive Value of a Coagulation-Related Gene Model in Glioma.

Aim: To evaluate coagulation related gene model as a biomarker for predicting prognosis of gliomas.

Material and methods: The mRNA expression and clinical data of glioma were downloaded from the TCGA and CGGA databases. Coagulation-related genes were downloaded from the KEGG database. The expression model was constructed using LASSO regression. The GBM data were divided into high and low-risk expression groups based on the median risk score, and the differences in overall survival and progression-free survival between them were calculated. The prognostic model was further validated using the TCGA-LGG and CGGA glioma databases, respectively. The accuracy of the risk score was calculated by ROC analysis for 1 year and 3 years.

Results: Four model genes, namely the SERPINA5, PLAUR, BDKRB1, and PTGIR, were identified, and the risk score was calculated as follows: risk score= SERPINA5*0.126264111304559 + PLAUR*0.288587629696211 + BDKRB1*0.349215422945011 + PTGIR*0.17334527969703, respectively. Based on glioma data from three groups, patients were divided into high and low-risk groups according to the median risk score. The overall survival, progression-free survival, and risk scores of the high-risk score group were worse than the low-risk group. The ROC curve analysis showed that the AUC values of the coagulation-related gene model at 1 year, 3 years, and 5 years were more than 0.65, validating the reliability of the prognostic model.

Conclusion: This study established the correlation between the coagulation-related gene model and glioma prognosis, providing deeper insight into the mechanism and treatment of glioma.

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