Department of Radiation Oncology, Tri-Service General Hospital, National Defense Medical Center, Taipei.
Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan.
Jpn J Clin Oncol. 2022 Sep 18;52(9):992-1000. doi: 10.1093/jjco/hyac077.
Few studies have focused on DNA methylation in endometrial cancer. The aim of our study is identify its role in endometrial cancer prognosis.
A publicly available dataset was retrieved from The Cancer Genome Atlas. For validation of expression alteration due to methylation, RNA sequencing data were obtained from other independent cohorts. MethSurv was used to search for candidate CpG probes, which were then filtered by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression analyses to identify final set of CpG probes for overall survival. A methylation-based risk model was developed and receiver operating characteristic analysis with area under curve was used for evaluation. Patients were divided into high- and low-risk groups using an optimal cut-off point. Comprehensive bioinformatic analyses were conducted to identify hub genes, key transcription factors, and enriched cancer-related pathways. Kaplan-Meier curve was used for survival analysis.
A 5-CpG signature score was established. Its predictive value for 5-year overall survival was high, with area under curve of 0.828, 0.835 and 0.816 for the training, testing and entire cohorts. cg27487839 and cg12885678 had strong correlation with their gene expression, XKR6 and PTPRN2, and lower PTPRN2 expression was associated with poorer survival in both The Cancer Genome Atlas and the validation datasets. Low-risk group was associated with significantly better survival. Low-risk group harboured more mutations in hub genes and key transcription factors, and mutations in SP1 and MECP2 represented favourable outcome.
We developed a methylation-based prognostic stratification system for endometrial cancer. Low-risk group was associated with better survival and harboured more mutations in the key regulatory genes.
很少有研究关注子宫内膜癌中的 DNA 甲基化。我们的研究旨在确定其在子宫内膜癌预后中的作用。
从癌症基因组图谱中检索到一个公开可用的数据集。为了验证甲基化引起的表达改变，从其他独立队列中获得了 RNA 测序数据。MethSurv 用于搜索候选 CpG 探针，然后通过最小绝对收缩和选择算子 Cox 回归和多变量 Cox 回归分析对其进行过滤，以确定用于总体生存的最终 CpG 探针集。建立了基于甲基化的风险模型，并使用曲线下面积的接收者操作特征分析进行评估。使用最佳截断点将患者分为高风险和低风险组。进行了综合的生物信息学分析，以识别枢纽基因、关键转录因子和丰富的癌症相关途径。使用 Kaplan-Meier 曲线进行生存分析。
建立了一个 5-CpG 特征评分。其对 5 年总生存率的预测价值较高，在训练、测试和整个队列中的曲线下面积分别为 0.828、0.835 和 0.816。cg27487839 和 cg12885678 与它们的基因表达 XKR6 和 PTPRN2 具有很强的相关性，而在癌症基因组图谱和验证数据集中，PTPRN2 的低表达与较差的生存相关。低风险组与显著更好的生存相关。低风险组在枢纽基因和关键转录因子中具有更多的突变，而 SP1 和 MECP2 中的突变则代表有利的结果。
我们开发了一种基于甲基化的子宫内膜癌预后分层系统。低风险组与更好的生存相关，并且在关键调节基因中具有更多的突变。
