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首页> 外文期刊>Cellular Physiology and Biochemistry >Integrative Analysis of DNA Methylation and Gene Expression Identify a Three-Gene Signature for Predicting Prognosis in Lower-Grade Gliomas
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Integrative Analysis of DNA Methylation and Gene Expression Identify a Three-Gene Signature for Predicting Prognosis in Lower-Grade Gliomas

机译：DNA甲基化和基因表达的综合分析确定了三基因签名，可预测低级胶质瘤的预后。

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Background/Aims In the current study, we performed an integrated analysis of genome-wide methylation and gene expression data to find novel prognostic genes for lower-grade gliomas (LGGs). Methods First, TCGA methylation data were used to identify prognostic genes associated with promoter methylation. Second, candidate genes that were stably regulated by promoter methylation were explored. Third, Cox proportional hazards regression analysis was used to generate a prognostic signature, and the signature genes were used to construct a survival risk score system. Results Three genes (EMP3, GSX2 and EMILIN3) were selected as signature genes. These three signature genes were used to construct a survival risk score system. The high-risk group exhibited significantly worse overall survival (OS) and relapse-free survival (RFS) as compared to the low-risk group in the TCGA dataset. The association of the three-gene prognostic signature with patient’ survival was then validated using the CGGA dataset. Moreover, Kaplan-Meier plots showed that the three-gene prognostic signature risk remarkably stratified grade II and grade III patients in terms of both OS and RFS in the TCGA cohort. There was also a significant difference between the low- and high-risk groups in IDH wild-type glioma patients, indicating that the three-gene signature may be able to help in predicting prognosis for patients with IDH wild-type gliomas. Conclusion We identified and validated a three-gene (EMP3, GSX2 and EMILIN3) prognostic signature in LGGs by integrating multidimensional genomic data from the TCGA and CGGA datasets, which may help in fine-tuning the current histology-based tumors classification system and providing better stratification for future clinical trials.
机译：背景/目的在本研究中，我们对全基因组甲基化和基因表达数据进行了综合分析，以发现低级神经胶质瘤（LGGs）的新预后基因。方法首先，使用TCGA甲基化数据鉴定与启动子甲基化相关的预后基因。其次，探索了受启动子甲基化稳定调节的候选基因。第三，使用Cox比例风险回归分析生成预后签名，并使用签名基因构建生存风险评分系统。结果选择了3个基因（EMP3，GSX2和EMILIN3）作为签名基因。这三个签名基因被用来构建生存风险评分系统。与TCGA数据集中的低风险组相比，高风险组的总体生存期（OS）和无复发生存期（RFS）明显更差。然后使用CGGA数据集验证了三基因预后标记与患者生存率之间的关联。此外，Kaplan-Meier图显示，在TCGA队列中，就OS和RFS而言，三基因预后标志物风险对II级和III级患者显着分层。 IDH野生型神经胶质瘤患者的低风险和高风险组之间也存在显着差异，表明三基因标记可能有助于预测IDH野生型神经胶质瘤患者的预后。结论我们通过整合来自TCGA和CGGA数据集的多维基因组数据，在LGG中鉴定并验证了三基因（EMP3，GSX2和EMILIN3）的预后签名，这可能有助于微调当前基于组织学的肿瘤分类系统并提供更好的分层以用于将来的临床试验。

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