Cai Luya, Hu Chuan, Yu Shanshan, Liu Lixiao, Zhao Jinduo, Zhao Ye, Lin Fan, Du Xuedan, Yu Qiongjie, Xiao Qinqin
Department of Obstetrics and Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Department of Orthopaedic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Front Genet. 2020 Dec 2;11:582274. doi: 10.3389/fgene.2020.582274. eCollection 2020.
Endometrial cancer (EC) is one of the most common gynecological cancers. Epithelial-mesenchymal transition (EMT) is believed to be significantly associated with the malignant progression of tumors. However, there is no relevant study on the relationship between EMT-related gene (ERG) signatures and the prognosis of EC patients.
We extracted the mRNA expression profiles of 543 tumor and 23 normal tissues from The Cancer Genome Atlas database. Then, we selected differentially expressed ERGs (DEERGs) among these mRNAs. Next, univariate and multivariate Cox regression analyses were performed to select the ERGs with predictive ability for the prognosis of EC patients. In addition, risk score models were constructed based on the selected genes to predict patients' overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Finally, nomograms were constructed to estimate the OS and PFS of EC patients, and pan-cancer analysis was performed to further analyze the functions of a certain gene.
Six OS-, ten PFS-, and five DFS-related ERGs were obtained. By constructing the prognostic risk score model, we found that the OS, PFS, and DFS of the high-risk group were notably poorer. Last, we found that AQP5 appeared in all three gene signatures, and through pan-cancer analysis, it was also found to play an important role in immunity in lower grade glioma (LGG), which may contribute to the poor prognosis of LGG patients.
We constructed ERG signatures to predict the prognosis of EC patients using bioinformatics methods. Our findings provide a thorough understanding of the effect of EMT in patients with EC and provide new targets and ideas for individualized treatment, which has important clinical significance.
子宫内膜癌（EC）是最常见的妇科癌症之一。上皮-间质转化（EMT）被认为与肿瘤的恶性进展密切相关。然而，关于EMT相关基因（ERG）特征与EC患者预后之间的关系尚无相关研究。
我们从癌症基因组图谱数据库中提取了543个肿瘤组织和23个正常组织的mRNA表达谱。然后，在这些mRNA中筛选出差异表达的ERG（DEERG）。接下来，进行单因素和多因素Cox回归分析，以选择对EC患者预后具有预测能力的ERG。此外，基于所选基因构建风险评分模型，以预测患者的总生存期（OS）、无进展生存期（PFS）和无病生存期（DFS）。最后，构建列线图以估计EC患者的OS和PFS，并进行泛癌分析以进一步分析某个基因的功能。
获得了6个与OS相关、10个与PFS相关和5个与DFS相关的ERG。通过构建预后风险评分模型，我们发现高危组的OS、PFS和DFS明显较差。最后，我们发现水通道蛋白5（AQP5）出现在所有三个基因特征中，并且通过泛癌分析还发现它在低级别胶质瘤（LGG）的免疫中起重要作用，这可能导致LGG患者预后不良。
我们使用生物信息学方法构建了ERG特征来预测EC患者预后。我们的研究结果为深入了解EMT在EC患者中的作用提供了依据，并为个体化治疗提供了新的靶点和思路，具有重要的临床意义。
