Background. Cancer stem cells play an important role in endometrial cancer (EC). It is closely related to self-renewal and therapeutic resistance of EC. Methods. In this study, WGCNA (weighted gene coexpression network analysis) was used to analyze the relationship between genes and clinical features. We also performed immune cell infiltration analysis of a key module by using ImmuCellAI (Immune Cell Abundance Identifier). Then, key genes were verified in the GEO database. Finally, causal relationship analysis and protein-protein interaction analysis were performed in DisNor tool and STRING. Result. The mRNA expression-based stemness index (mRNAsi) is significantly lower in normal tissues and is significantly higher in individuals with stage IV or high-grade cancer and those who are obese or postmenopausal. Nineteen key genes (ORC6, C1orf112, RAD54L, SGO2, BUB1, PLK4, KIF18B, BUB1B, TTK, NCAPG, XRCC2, CENPF, KIF15, RACGAP1, ARHGAP11A, TPX2, KIF14, KIF4A, and NCAPH) that were enriched mainly in terms related to the cell cycle and DNA replication were selected by weighted gene coexpression network analysis (WGCNA). Based on the key modules, the numbers of NKT cells, NK cells, and neutrophils in the normal group were significantly higher than those in the cancer group. PLK1, CDK1, and MAD2L1, which were correlated with upstream genes, may be an regulated upstream of key genes. Conclusion. PLK1, CDK1, and MAD2L1 which were strongly correlated with upstream genes may be a regulated upstream of key genes.

中文翻译：

---

网络分析综合分析子宫内膜癌中癌干细胞特性的调控

背景。癌症干细胞在子宫内膜癌（EC）中发挥着重要作用。它与EC的自我更新和治疗抵抗密切相关。方法。本研究采用WGCNA（加权基因共表达网络分析）分析基因与临床特征的关系。我们还使用 ImmuCellAI（免疫细胞丰度标识符）对关键模块进行了免疫细胞浸润分析。然后，在 GEO 数据库中验证关键基因。最后，在DisNor工具和STRING中进行了因果关系分析和蛋白质-蛋白质相互作用分析。结果. 基于 mRNA 表达的干性指数 (mRNAsi) 在正常组织中显着降低，在 IV 期或高级别癌症个体以及肥胖或绝经后个体中显着升高。19 个关键基因（ORC6、C1orf112、RAD54L、SGO2、BUB1、PLK4、KIF18B、BUB1B、TTK、NCAPG、XRCC2、CENPF、KIF15、RACGAP1、ARHGAP11A、TPX2、KIF14、KIF4A 和 NCAPH），主要在相关方面富集通过加权基因共表达网络分析（WGCNA）选择细胞周期和DNA复制。从关键模块来看，正常组的NKT细胞、NK细胞和中性粒细胞的数量显着高于癌症组。与上游基因相关的PLK1、CDK1和MAD2L1可能是关键基因的上游调控。结论. 与上游基因密切相关的PLK1、CDK1和MAD2L1可能是关键基因的上游调控。