A four-DNA methylation signature as a novel prognostic biomarker for survival of patients with gastric cancer
A four-DNA methylation signature as a novel prognostic biomarker for survival of patients with gastric cancer
复制标题
四 DNA 甲基化特征作为胃癌患者生存的新型预后生物标志物。
DOI：
10.1186/s12935-020-1156-8
复制
发表时间：
2020-03-20
影响因子：
5.8
通讯作者：
Zhou, Yongning
中科院分区：
文献类型：
--
作者：
Li, Chunmei;Zheng, Ya;Zhou, Yongning
背景 胃癌（GC）是第五大最常诊断的癌症，也是癌症相关死亡的第三大原因。缺乏患者生存的预后指标会阻碍GC治疗和生存。方法和结果分析从癌症基因组图谱（TCGA）数据库中获得的GC患者的甲基化谱数据，以确定甲基化位点作为GC预后的生物标志物。该队列分为训练集和验证集。单变量 Cox、LASSO 回归和多变量 Cox 分析揭示了作为风险评分模型的四 DNA 甲基化特征与 GC 患者的总体生存率密切相关。高危评分与低危评分的GC患者的生存率存在显着差异。对接受者操作特征的分析揭示了 GC 患者的四 DNA 甲基化特征的高预后准确性。亚组分析表明，准确性包括解剖部位、组织学分级、TNM分期、病理分期和性别。基于四 DNA 甲基化特征的 GC 预后比基于已知生物标志物的GC 预后更精确。结论 四DNA甲基化特征可以作为一种新型的独立预后因素，成为预测GC患者预后的重要工具。这种潜力必须通过大规模人群队列研究和基础研究来验证。
Background Gastric cancer (GC) is the fifth most frequently diagnosed cancer and the third leading cause of cancer-related mortality. Lack of prognostic indicators for patient survival hinders GC treatment and survival. Methods and results Methylation profile data of patients with GC obtained from The Cancer Genome Atlas (TCGA) database were analyzed to identify methylation sites as biomarkers for GC prognosis. The cohort was divided into training and validation sets. Univariate Cox, LASSO regression,and multivariate Cox analyses revealed a close correlation of a four-DNA methylation signature as a risk score model with the overall survival of patients with GC. The survival between high-risk and low-risk score patients with GC was significantly different. Analyses of receiver operating characteristics revealed a high prognostic accuracy of the four-DNA methylation signature in patients with GC. The subgroup analysis indicated that the accuracy included that for anatomical region, histologic grade, TNM stage, pathological stage, and sex. The GC prognosis based on the four-DNA methylation signature was more precise than that based on known biomarkers. Conclusions The four-DNA methylation signature could serve as a novel independent prognostic factor that could be an important tool to predict the prognostic outcome of GC patients. This potential must be verified in a large-scale population cohort study and through basic research studies.