Center of Reproductive Medicine, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Department of Gynecology and The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
DNA Cell Biol. 2020 Jun;39(6):975-991. doi: 10.1089/dna.2019.5313. Epub 2020 May 12.
DNA methylation has been implicated as an important mechanism for the development of uterine corpus endometrial carcinoma (UCEC), indicating that methylation-driven genes may be potential biomarkers for survival prediction. In this study, we aimed to identify a new prognostic methylation signature for UCEC based on differentially expressed genes (DEGs) and long noncoding RNAs (lncRNAs) (DELs). Sample-matched RNA-sequencing and methylation-array data were downloaded from The Cancer Genome Atlas database, by analysis of which a total of 269 DEGs and 4 DELs were identified to be methylation driven. Least absolute shrinkage and selection operator analysis screened that 14 methylation-driven genes were significantly associated with overall survival (OS) and thus were used as a signature to establish a prognostic risk model. Based on the median threshold, the patients were divided into the low-risk and the high-risk groups, which showed significantly different survival periods under the Kaplan-Meier curve. The area under receiver operating characteristic curve (AUC) was 0.934, 0.919, and 0.952 for the training, validation, and entire cohort, respectively. Stratification analysis showed that the established risk model may add prognostic values to conventional clinical factors (age, neoplasm histologic grade, and clinical stage). A nomogram was constructed based on the risk model and clinical parameters, with the AUC of 0.978 and c-index of 0.8079. Database for Annotation, Visualization, and Integrated Discovery (DAVID) function enrichment and Human Protein Atlas (HPA) protein expression validation showed 5 of these 14 genes may be especially important for UCEC (hypermethylated lowly expressed: and ; hypomethylated highly expressed: ). Comparison with breast cancer in the methylation level indicated and may be specific methylation-driven genes for UCEC. LncRNA HCG11 may function by coexpressing with . In conclusion, this 14-DNA methylation signature combined with clinical factors may a potentially effective biomarker in predicting OS for UCEC patients.
DNA 甲基化已被认为是子宫体子宫内膜癌 (UCEC) 发展的重要机制，表明甲基化驱动的基因可能是生存预测的潜在生物标志物。在这项研究中，我们旨在基于差异表达基因 (DEGs) 和长非编码 RNA (lncRNA) (DELs) 为 UCEC 确定新的预后甲基化特征。从癌症基因组图谱 (TCGA) 数据库中下载了样本匹配的 RNA 测序和甲基化阵列数据，通过分析，共鉴定出 269 个 DEGs 和 4 个 DEL 是由甲基化驱动的。最小绝对收缩和选择算子分析筛选出 14 个与总生存期 (OS) 显著相关的甲基化驱动基因，作为建立预后风险模型的特征。基于中位数阈值，患者被分为低风险组和高风险组，在 Kaplan-Meier 曲线下显示出明显不同的生存期。训练、验证和整个队列的接受者操作特征曲线 (AUC) 分别为 0.934、0.919 和 0.952。分层分析表明，建立的风险模型可能为传统临床因素 (年龄、肿瘤组织学分级和临床分期) 增加预后价值。基于风险模型和临床参数构建了一个列线图，AUC 为 0.978，C 指数为 0.8079。数据库注释、可视化和综合发现 (DAVID) 功能富集和人类蛋白质图谱 (HPA) 蛋白表达验证表明，这 14 个基因中的 5 个可能对 UCEC 特别重要 (高甲基化低表达：和；低甲基化高表达：)。与乳腺癌在甲基化水平上的比较表明，和可能是 UCEC 的特异性甲基化驱动基因。lncRNA HCG11 可能通过与共同表达发挥作用。总之，该 14-DNA 甲基化特征与临床因素相结合，可能是预测 UCEC 患者 OS 的一种潜在有效生物标志物。
