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DNA methylation profiling to predict recurrence risk in stage Ι lung adenocarcinoma: Development and validation of a nomogram to clinical management

机译:DNA甲基化图谱预测I期肺腺癌的复发风险:诺模图的开发和临床验证

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摘要

Increasing evidence suggested DNA methylation may serve as potential prognostic biomarkers; however, few related DNA methylation signatures have been established for prediction of lung cancer prognosis. We aimed at developing DNA methylation signature to improve prognosis prediction of stage I lung adenocarcinoma (LUAD). A total of 268 stage I LUAD patients from the Cancer Genome Atlas (TCGA) database were included. These patients were separated into training and internal validation datasets. was used as an external validation set. A 13‐DNA methylation signature was identified to be crucially relevant to the relapse‐free survival (RFS) of patients with stage I LUAD by the univariate Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox proportional hazard analysis in the training dataset. The Kaplan‐Meier analysis indicated that the 13‐DNA methylation signature could significantly distinguish the high‐ and low‐risk patients in entire TCGA dataset, internal validation and external validation datasets. The receiver operating characteristic (ROC) analysis further verified that the 13‐DNA methylation signature had a better value to predict the RFS of stage I LUAD patients in internal validation, external validation and entire TCGA datasets. In addition, a nomogram combining methylomic risk scores with other clinicopathological factors was performed and the result suggested the good predictive value of the nomogram. In conclusion, we successfully built a DNA methylation‐associated nomogram, enabling prediction of the RFS of patients with stage I LUAD.
机译:越来越多的证据表明DNA甲基化可以作为潜在的预后生物标志物。然而,很少有相关的DNA甲基化标记可以预测肺癌的预后。我们旨在开发DNA甲基化标记,以改善I期肺腺癌(LUAD)的预后预测。纳入了来自癌症基因组图谱(TCGA)数据库的268位I期LUAD患者。这些患者被分为训练和内部验证数据集。用作外部验证集。通过单变量Cox比例风险分析和最小绝对收缩与选择算子(LASSO)Cox回归分析和多元分析,发现13-DNA甲基化标记与I期LUAD患者的无复发生存(RFS)至关重要。训练数据集中的Cox比例风险分析。 Kaplan-Meier分析表明,13-DNA甲基化标记可以在整个TCGA数据集,内部验证和外部验证数据集中显着区分高危和低危患者。接收者操作特征(ROC)分析进一步验证了13-DNA甲基化标记在内部验证,外部验证和整个TCGA数据集中具有更好的预测I期LUAD患者RFS的价值。此外,进行了将甲基组学风险评分与其他临床病理因素相结合的列线图,结果表明该图具有良好的预测价值。总之,我们成功建立了DNA甲基化相关的列线图,从而能够预测I期LUAD患者的RFS。

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