摘要
目的鉴定食管鳞状细胞癌(esophageal squamous cell carcinoma,ESCC)甲基化生物标志物,预测ESCC患者预后。方法从癌症基因组图谱数据库(the cancer genome atlas,TCGA)下载ESCC和正常样本基因组甲基化数据及临床信息。所有ESCC样本随机分为验证组和训练组。采用Cox比例风险回归模型和随机生存森林算法在训练组中鉴定甲基化生物标志物。并使用时间依赖性ROC曲线来评估该模型的性能。在验证组中对该模型进行验证。通过GO功能注释,探讨DNA甲基化标志物的生物学功能。结果鉴定出差异甲基化基因283个,并从中筛选出与生存相关的4个甲基化基因(RRAGB、SYP、ERCC6L和RNASEH2CP1)作为预后的生物标志物。训练组和验证组ROC曲线下面积(AUC)分别为0.984和0.83。该生物标志物能够将训练组患者分为高风险组、低风险组,并在验证组中得到相似的结果。多因素Cox回归分析表明,甲基化基因生物标志物是ESCC患者预后的独立预测因素。功能分析表明,这些标志物基因参与转录调控与DNA结合。结论筛选出预测ESCC预后的甲基化基因标志物,是独立的预后预测因子。
Objective To identify prognostic biomarkers for ESCC patients in order to ensure good outcomes.Methods The DNA methylation profile data on 96 ESCC tissues and 3 normal tissues was downloaded from the Cancer Genome Atlas Database(TCGA).Cox proportional hazards regression and random survival forest-variable hunting were used to identify DNA methylated gene biomarkers in the samples that were randomly assigned to the training group,with other samples as the test subset.GO annotation was performed to explore the biological function of DNA methylated gene signatures.Results A total of 283 different methylation genes were identified in the ESCC data.Finally,4 methylation genes(RRAGB,SYP,ERCC6 L and RNASEH2 CP1)that were significantly associated with patients’survival time were identified as biomarkers.As the most accurate predictor,the area under the curve(AUC)in the training and test groups was 0.984 and 0.83,respectively.The signature was able to sort patients into high-and low-risk groups with meaningful survival rates in the training group,and its predictive ability was validated in the test dataset.Multivariable Cox regression analysis showed the methylation gene biomarker was an independent prognostic factor for ESCC patients.Functional analysis suggested that these signature genes might be related to the regulation of transcription and DNA binding.Conclusions DNA methylation gene signatures could be novel prognostic biomarkers and can help predict the survival of ESCC patients independently.
作者
赵明
陈思禹
王钰琦
ZHAO Ming;CHEN Siyu;WANG Yuqi(Department of Thoracic Surgery,the First Medical Center of PLA General Hospital,Beijing 100048,China)
出处
《武警医学》
CAS
2020年第1期38-42,46,共6页
Medical Journal of the Chinese People's Armed Police Force
基金
吴阶平基金会课题(320.6750.17300)
解放军总医院大数据课题.
