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Prognostic Value of DNA Methylation-Driven Genes in Clear Cell Renal Cell Carcinoma: A Study Based on Methylation and Transcriptome Analyses.
Disease Markers ( IF 3.464 ) Pub Date : 2020-07-11 , DOI: 10.1155/2020/8817652
Maolin Hu 1, 2 , Jiangling Xie 3 , Huiming Hou 2 , Ming Liu 2 , Jianye Wang 1, 2
Affiliation  

Background. Few previous studies have comprehensively explored the level of DNA methylation and gene expression in ccRCC. The purpose of this study was to identify the key clear cell renal cell carcinoma- (ccRCC-) related DNA methylation-driven genes (MDG) and to build a prognostic model based on the level of DNA methylation. Methods. RNA-seq transcriptome data and DNA methylation data were obtained from The Cancer Genome Atlas. Based on the MethylMix algorithm, we obtain ccRCC-related MDG. The univariate and multivariate Cox regression analyses were employed to investigate the correlation between patient overall survival and the methylation level of each MDG. Finally, a prognosis risk score was established based on a linear combination of the regression coefficient derived from the multivariate Cox regression model () multiplied with the methylation level of the gene. Results. 19 ccRCC-related MDG were identified. Three MDG (NCKAP1L, EVI2A, and BATF) were further screened and integrated into a prognostic risk score model, . The risk model was independent from conventional clinical characteristics as a prognostic factor for ccRCC (, 95% confidence interval: 1.063–1.402, and ). The joint survival analysis showed that the gene expression and methylation levels of the prognostic genes EVI2A and BATF were significantly related with prognosis. Conclusion. This study provided an important bioinformatics foundation for in-depth studies of ccRCC DNA methylation.

中文翻译:

DNA 甲基化驱动基因在透明细胞肾细胞癌中的预后价值:基于甲基化和转录组分析的研究。

背景。以往很少有研究全面探讨 ccRCC 中 DNA 甲基化水平和基因表达水平。本研究的目的是确定关键的透明细胞肾细胞癌(ccRCC-)相关的 DNA 甲基化驱动基因(MDG),并建立基于 DNA 甲基化水平的预后模型。方法. RNA-seq 转录组数据和 DNA 甲基化数据来自 The Cancer Genome Atlas。基于 MethylMix 算法,我们得到了 ccRCC 相关的 MDG。采用单变量和多变量 Cox 回归分析来研究患者总生存期与每个 MDG 甲基化水平之间的相关性。最后,基于从多变量 Cox 回归模型 ( )得出的回归系数与基因甲基化水平相乘的线性组合,建立了预后风险评分。结果。确定了 19 个与 ccRCC 相关的千年发展目标。进一步筛选了三个 MDG(NCKAP1L、EVI2A 和 BATF)并将其整合到预后风险评分模型中,. 风险模型独立于作为 ccRCC 预后因素的常规临床特征(, 95% 置信区间: 1.063–1.402, 和)。联合生存分析显示预后基因EVI2A和BATF的基因表达和甲基化水平与预后显着相关。结论。该研究为深入研究ccRCC DNA甲基化提供了重要的生物信息学基础。
更新日期:2020-07-13
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