Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Comb Chem High Throughput Screen. 2023;26(8):1488-1502. doi: 10.2174/1386207325666221005122554.
Endometrial cancer (EC) is one of the most normal malignancies globally. Growing evidence suggests epithelial-mesenchymal transition (EMT) related markers are closely correlated with poor prognosis of EC. However, the relationship between multiple EMT-associated long non-coding RNAs (lncRNAs) and the prognosis of EC has not yet been studied.
The transcriptome data and clinical information of EC cases were obtained from The Cancer Genome Atlas (TCGA). Then, we identified differentially expressed EMT-associated lncRNAs between tumor and normal tissue. Univariate cox regression analysis and multivariate stepwise Cox regression analysis were applied to identify EMT-associated lncRNAs related to overall survival (OS). Kaplan-Meier curve, receiver operating characteristic (ROC), nomograms and multi-index ROC curves were further established to evaluate the performance of the prognostic signature. In addition, we also investigated the distribution of immune cell characteristics, sensitivity to immune checkpoint inhibitor (ICI) and chemotherapeutics, and tumor mutation burden (TMB) between high- and low-risk scores predicated on a prognostic model.
We established nine EMT-associated lncRNA signatures to predict the OS of EC, the area under the ROC curve (AUC) of the risk score has better values than other clinical characteristics, indicating the accuracy of the prognostic signature. As revealed by multivariate Cox regression, the prognosis model independently predicted EC prognosis. Moreover, the signature and the EMTassociated lncRNAs showed significant correlations with other clinical characteristics,including. Multi-index ROC curves for estimating 1-, 3- and 5-year overall survival (OS) of EC patients showed good predictive accuracy with AUCs of 0.731, 0.791, and 0.782, respectively. The highrisk group had specific tumor immune infiltration, insensitive to ICI, higher chemotherapeutics sensitivity and higher expression of TP53 mutation. Finally, the five lncRNAs of signature were further verified by qRT-PCR.
We constructed an EMT-associated lncRNA signature that can predict the prognosis of EC effectively, and the prognostic signature also played an essential role in the TME; thus, the establishment of an EMT-associated lncRNA signature may provide new perspectives for the treatment of EC.
子宫内膜癌（EC）是全球最常见的恶性肿瘤之一。越来越多的证据表明上皮-间充质转化（EMT）相关标志物与 EC 的预后不良密切相关。然而，多种 EMT 相关长链非编码 RNA（lncRNA）与 EC 预后之间的关系尚未得到研究。
从癌症基因组图谱（TCGA）中获取 EC 病例的转录组数据和临床信息。然后，我们鉴定了肿瘤组织和正常组织之间差异表达的 EMT 相关 lncRNA。应用单因素 cox 回归分析和多因素逐步 Cox 回归分析鉴定与总生存期（OS）相关的 EMT 相关 lncRNA。进一步建立 Kaplan-Meier 曲线、受试者工作特征（ROC）曲线、列线图和多指标 ROC 曲线，以评估预后模型的性能。此外，我们还研究了基于预后模型的高、低风险评分之间免疫细胞特征、免疫检查点抑制剂（ICI）和化疗药物敏感性以及肿瘤突变负荷（TMB）的分布。
我们建立了 9 个 EMT 相关 lncRNA 标志物来预测 EC 的 OS，ROC 曲线下面积（AUC）的风险评分值优于其他临床特征，表明预后模型的准确性。多因素 Cox 回归显示，该预后模型独立预测了 EC 的预后。此外，该标志物和 EMT 相关 lncRNA 与其他临床特征显著相关，包括肿瘤分期、组织学分级、肌层浸润深度、淋巴结转移和肿瘤大小。多指标 ROC 曲线用于估计 EC 患者 1、3 和 5 年总生存率（OS），AUC 值分别为 0.731、0.791 和 0.782，具有良好的预测准确性。高危组具有特定的肿瘤免疫浸润，对 ICI 不敏感，化疗药物敏感性更高，TP53 突变表达更高。最后，通过 qRT-PCR 进一步验证了该signature 中的 5 个 lncRNA。
我们构建了一个 EMT 相关 lncRNA 标志物，可以有效地预测 EC 的预后，并且该预后模型在 TME 中也发挥了重要作用；因此，建立 EMT 相关 lncRNA 标志物可能为 EC 的治疗提供新视角。
