Exploration of DNA methylation markers for diagnosis and prognosis of patients with endometrial cancer

The accurate diagnosis of endometrial cancer (EC) holds great promise for improving its treatment choice and prognosis prediction. This work aimed to identify diagnostic biomarkers for differentiating EC tumors from tumors in other tissues, as well as prognostic signatures for predicting survival in EC patients. We identified 48 tissue-specific markers using a cohort of genome-wide methylation data from three common gynecological tumors and their corresponding normal tissues. A diagnostic classifier was constructed based on these 48 CpG markers that could predict cancerous versus normal tissue with an overall correct rate of 98.3% in the entire repository. Fifteen CpG markers associated with the overall survival (OS) and development of EC were also identified based on the methylation patterns of the EC samples. A prognostic model that aggregated these prognostic CpG markers was established and shown to have a higher discriminative ability to distinguish EC patients with an elevated risk of mortality than the FIGO staging system and several other clinical prognostic variables. This study presents the utility of DNA methylation in identifying biomarkers for the diagnosis and prognosis of EC and will help improve our understanding of the underlying mechanisms involved in the development of EC.

子宫内膜癌（endometrial cancer, EC）的精准诊断，对于优化其治疗方案选择与预后预测具有重要价值。本研究旨在筛选可区分子宫内膜癌组织与其他组织肿瘤的诊断生物标志物，以及可预测子宫内膜癌患者生存结局的预后特征。研究团队基于包含3种常见妇科肿瘤及其对应正常组织的全基因组甲基化数据队列，筛选得到48个组织特异性标志物。基于这48个CpG位点标志物构建的诊断分类器，在全数据集整体分类准确率达98.3%，可准确区分癌组织与正常组织。此外，基于子宫内膜癌样本的甲基化表达模式，研究还筛选出15个与子宫内膜癌患者总生存期（overall survival, OS）及疾病进展相关的CpG位点标志物。本研究构建了整合上述预后CpG位点标志物的预后模型，结果显示，相较于国际妇产科联盟（FIGO）分期系统及其他多项临床预后变量，该模型对高死亡风险子宫内膜癌患者的判别能力更优。本研究证实了DNA甲基化在筛选子宫内膜癌诊断及预后生物标志物中的应用潜力，有助于加深我们对子宫内膜癌发生发展潜在分子机制的理解。