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A novel analytical model of MGMT methylation pyrosequencing offers improved predictive performance in patients with gliomas

机译:MgMT甲基化焦肌肉术的新型分析模型为Gliomas患者提供了改进的预测性能

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The methylation status of the promoter of MGMT gene is a crucial factor influencing clinical decision-making in patients with gliomas. MGMT pyrosequencing results are often dichotomized by a cut-off value based on an average of several tested CpGs. However, this method frequently results in a gray zone, representing a dilemma for physicians. We therefore propose a novel analytical model for MGMT methylation pyrosequencing. MGMT CpG heterogeneity was investigated in 213 glioma patients in two tested cohorts: cohort A in which CpGs 7582 were tested and cohort B in which CpGs 7278 were tested. The predictive performances of the novel and traditional averaging models were compared in 135 patients who received temozolomide using receiver operating characteristic curves and KaplanMeier curves, and in patients stratified according to isocitrate dehydrogenase gene mutation status. The results were validated in an independent cohort of 65 consecutive patients with high-grade gliomas from the Chinese Glioma Genome Atlas database. Heterogeneity of MGMT promoter CpG methylation level was observed in most gliomas. The optimal cut-off value for each individual CpG varied from 416%. The current analysis defined MGMT promoter methylation as occurring when at least three CpGs exceeded their respective cut-off values. This novel analysis could accurately predict the prognosis of patients in the methylation gray zone according to the standard averaging method, and improved the area under the curves from 0.67, 0.76, and 0.67 to 0.70, 0.84, and 0.72 in cohorts A, B, and the validation cohort, respectively, demonstrating superiority of this analytical method in all three cohorts. Furthermore, the advantages of the novel analysis were retained regardless of WHO grade and isocitrate dehydrogenase gene mutation status. In conclusion, this novel analytical model offers an improved clinical predictive performance for MGMT pyrosequencing results and is suitable for clinical use in patients with gliomas.
机译:MGMT基因启动子的甲基化状态是影响胶质瘤患者临床决策的关键因素。 MgMT焦磷酸测序结果通常通过截止值基于几个测试的CPG的平均值二分。然而,这种方法经常导致灰色区域,代表医生的困境。因此,我们提出了一种新的分析模型,用于MgMT甲基化焦肌肉。在213名胶质瘤患者中研究了MGMT CpG异质性,在两种测试的队列中:COHORT A,其中测试CPG 7582,并测试CPGS 7278的队列B.在使用接收器操作特征曲线和Kaplanmeier曲线的135名接受替替唑胺的患者中,以及根据异柠檬酸脱氢酶基因突变状态分层的患者进行了比较了新颖的和传统平均模型的预测性能。结果在来自中国胶质瘤基因组Atlas数据库的65名患有65名的独立患者的65名患者的独立队列中验证。在大多数胶质瘤中观察到MgMT启动子CpG甲基化水平的异质性。每个单独的CPG的最佳截止值不同于416%。当前分析定义了MgMT启动子甲基化,当时至少三个CPG超过它们各自的截止值时发生。这种新的分析可以根据标准平均方法准确地预测甲基化灰色区域中患者的预后,并改善了0.67,0.76和0.67至0.70,0.84和0.72的曲线下的面积在群组A,B和0.72中。验证队列分别在所有三个队列中展示了这种分析方法的优越性。此外,无论世卫组织等级和异柠檬酸脱氢酶基因突变状态如何,保留了新分析的优点。总之,这一新型分析模型为MgMT焦磷酸测序结果提供了改进的临床预测性能,适用于胶质瘤患者的临床应用。

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