Endometrial cancer (EC) is one of the most common malignancies in the female genital system, characterized by high mortality and recurrence rates. This study attempted to screen key genes and potential prognostic biomarkers for EC using bioinformatics analysis. Twenty‐seven normal endometrial tissues and 135 EC samples were collected from four Gene Expression Omnibus (GEO) databases, then we identified the differentially expressed genes (DEGs) and conducted downstream analyses. Moreover, we screened hub genes by constructing a protein‐protein interaction (PPI) network. Finally, we assessed the prognostic values and molecular mechanism of the potential prognostic genes using the Kaplan‐Meier curve and Gene Set Enrichment Analysis (GSEA). As a result, 28 upregulated and 94 downregulated genes were determined after gene integration of these four GEO data sets. Gene Ontology analysis indicated that DEGs were mainly involved in transcriptional regulation and cell proliferation. The Kyoto Encyclopedia of Gene and Genome pathway analysis primarily related to transcriptional misregulation and apoptosis. Moreover, the PPI analysis revealed 10 hub genes (JUN, UBE2I, GATA2, WT1, PIAS1, FOXL2, RUNXI, EZR, TCF4, and NR2F2) with a high degree of connectivity, among them, the expression tendency of nine genes except UBE2I were consistent with messenger RNA level from The Cancer Genome Atlas data. Furthermore, only FOXL2, TCF4, and NR2F2 were significantly correlated with prognosis of EC patients, and their low expression associated biological pathways were enriched in the cell cycle and fatty acid metabolism. In conclusion, this study identified three key genes as biomarkers and potential therapeutic targets of EC on the basis of integrated bioinformatics analysis. The findings will improve our comprehension of the molecular mechanisms underlying the pathogenesis and prognosis of EC.

中文翻译：

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使用生物信息学分析鉴定与子宫内膜癌的诊断和预后相关的生物标志物。

子宫内膜癌（EC）是女性生殖系统最常见的恶性肿瘤之一，具有高死亡率和复发率的特点。本研究试图利用生物信息学分析筛选 EC 的关键基因和潜在的预后生物标志物。从四个基因表达综合（GEO）数据库中收集了 27 个正常子宫内膜组织和 135 个 EC 样本，然后我们鉴定了差异表达基因（DEG）并进行了下游分析。此外，我们通过构建蛋白质-蛋白质相互作用（PPI）网络来筛选枢纽基因。最后，我们使用 Kaplan-Meier 曲线和基因集富集分析（GSEA）评估了潜在预后基因的预后价值和分子机制。结果，在这四个GEO数据集的基因整合后，确定了28个上调基因和94个下调基因。基因本体分析表明DEGs主要参与转录调控和细胞增殖。京都基因百科全书和基因组通路分析主要与转录失调和细胞凋亡有关。此外，PPI分析显示10个枢纽基因（JUN​​、UBE2I、GATA2、WT1、PIAS1、FOXL2、RUNXI、EZR、TCF4和NR2F2）具有高度连通性，其中除UBE2I外的9个基因的表达趋势为与癌症基因组图谱数据中的信使 RNA 水平一致。此外，只有FOXL2、TCF4和NR2F2与EC患者的预后显着相关，并且它们的低表达相关的生物学途径富集在细胞周期和脂肪酸代谢中。总之，本研究在综合生物信息学分析的基础上，确定了三个关键基因作为 EC 的生物标志物和潜在的治疗靶点。这些发现将提高我们对 EC 发病机制和预后的分子机制的理解。