Yan Pingzhao, Yang Xiaohua, Wang Jianhua, Wang Shichang, Ren Hong
Department of General Surgery, People's Hospital of Tongchuan, Tongchuan, Shaanxi 727000, P.R. China.
Department of Respiratory and Hematology Medicine, People's Hospital of Tongchuan, Tongchuan, Shaanxi 727000, P.R. China.
Oncol Lett. 2019 Aug;18(2):1011-1022. doi: 10.3892/ol.2019.10431. Epub 2019 Jun 4.
The lack of clinically useful biomarkers compromise the personalized management of lung adenocarcinomas (ADCs); epigenetic events and DNA methylation in particular have exhibited potential value as biomarkers. By comparing genome-wide DNA methylation data of paired lung ADCs and normal tissues from 6 public datasets, cancer-specific CpG island (CGI) methylation changes were identified with a pre-specified criterion. Correlations between DNA methylation and expression data for each gene were assessed by Pearson correlation analysis. A prognostically relevant CGI methylation signature was constructed by risk-score analysis, and was validated using a training-validation approach. Survival data were analyzed by log-rank test and Cox regression model. In total, 134 lung ADC-specific CGI CpGs were identified, among which, a panel of 9 CGI loci were selected as prognostic candidates, and were used to construct a risk-score signature. The novel CGI methylation signature was identified to classify distinct prognostic subgroups across different datasets, and was demonstrated to be a potent independent prognostic factor for overall survival time of patients with lung ADCs. In addition, it was identified that cancer-specific CGI hypomethylation of , along with the corresponding gene expression, provided optimized prognostication of lung ADCs. In summary, cancer-specific CGI methylation aberrations are optimal candidates for novel biomarkers of lung ADCs; the 9-CpG methylation panel and hypomethylation of exhibited particularly promising significance.
缺乏具有临床实用性的生物标志物不利于肺腺癌（ADC）的个性化管理；表观遗传事件，尤其是DNA甲基化，已显示出作为生物标志物的潜在价值。通过比较来自6个公共数据集的配对肺ADC和正常组织的全基因组DNA甲基化数据，以预先设定的标准确定癌症特异性CpG岛（CGI）甲基化变化。通过Pearson相关分析评估每个基因的DNA甲基化与表达数据之间的相关性。通过风险评分分析构建与预后相关的CGI甲基化特征，并采用训练-验证方法进行验证。通过对数秩检验和Cox回归模型分析生存数据。总共鉴定出134个肺ADC特异性CGI CpG，其中，选择9个CGI位点组成的一组作为预后候选指标，并用于构建风险评分特征。已鉴定出这种新的CGI甲基化特征可对不同数据集中不同的预后亚组进行分类，并被证明是肺ADC患者总生存时间的有力独立预后因素。此外，已确定特定于癌症的CGI低甲基化以及相应的基因表达可优化肺ADC的预后。总之，癌症特异性CGI甲基化异常是肺ADC新型生物标志物的最佳候选指标；9-CpG甲基化组和 的低甲基化表现出特别有前景的意义。
