Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Center of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Cancer Med. 2020 May;9(10):3522-3536. doi: 10.1002/cam4.2956. Epub 2020 Mar 14.
Endometrial cancer (EC) is a fatal female reproductive tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. In this study, GSE17025 and GSE40032 were obtained from Gene Expression Omnibus (GEO). "limma" package and Venn diagram tool were used to identify hub genes. FunRich was used for functional analysis. Retrieval of Interacting Genes Database (STRING) was used to analyze protein-protein interaction (PPI) complex. Cancer Genome Atlas (TCGA), GEPIA, immunohistochemistry staining, and ROC curve analysis were carried out for validation. Univariate and multivariate regression analyses were performed to predict the risk score. Compound muscle action potential (CMap) was used to find potential drugs. GSEA was also done. We retrieved seven oncogenes which were upregulated and hypomethylated and 12 tumor suppressor genes (TSGs) which were downregulated and hypermethylated. The upregulated and hypomethylated genes were strikingly enriched in term "immune response" while the downregulated and hypermethylated genes were mainly focused on term "aromatic compound catabolic process." TCGA and GEPIA were used to screen out EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1. Among them, ESPL1 and ROR2 were identified by Cox regression analysis and were used to construct prognostic risk model. The result showed that ESPL1 was a negative independent prognostic factor. Cmap identified aminoglutethimide, luteolin, sulfadimethoxine, and maprotiline had correlation with EC. GSEA results showed that "hedgehog signaling pathway" was enriched. This research inferred potential aberrantly methylated DEGs and dysregulated pathways may participate in EC development and firstly reported eight hub genes, including EDNRB, CDO1, NDN, PLCD1, ROR2, ESPL1, PRAME, and PTTG1 that could be used to predict EC prognosis. Aminoglutethimide and luteolin may be used to fight against EC.
子宫内膜癌（EC）是一种致命的女性生殖系统肿瘤。生物信息学工具的不断发展，有助于筛选出与 EC 相关的分子靶标。本研究从基因表达综合数据库（GEO）中获取 GSE17025 和 GSE40032 数据集。使用“limma”包和韦恩图工具来识别关键基因。使用 FunRich 进行功能分析。检索互作基因数据库（STRING）分析蛋白质-蛋白质相互作用（PPI）复合物。通过癌症基因组图谱（TCGA）、GEPIA、免疫组织化学染色和 ROC 曲线分析进行验证。进行单变量和多变量回归分析以预测风险评分。使用复合肌肉动作电位（CMap）寻找潜在药物。还进行了 GSEA。我们检索到 7 个上调且低甲基化的癌基因和 12 个下调且高甲基化的肿瘤抑制基因（TSG）。上调且低甲基化基因在术语“免疫反应”中显著富集，而下调且高甲基化基因主要集中在术语“芳香族化合物分解代谢过程”。TCGA 和 GEPIA 筛选出 EDNRB、CDO1、NDN、PLCD1、ROR2、ESPL1、PRAME 和 PTTG1。其中，ESPL1 和 ROR2 通过 Cox 回归分析确定，并用于构建预后风险模型。结果表明，ESPL1 是一个负独立预后因素。Cmap 鉴定出氨苯蝶啶、木犀草素、磺胺二甲氧嘧啶和马普替林与 EC 具有相关性。GSEA 结果表明“hedgehog 信号通路”富集。本研究推断潜在异常甲基化的 DEGs 和失调的通路可能参与 EC 的发展，并首次报道了 8 个关键基因，包括 EDNRB、CDO1、NDN、PLCD1、ROR2、ESPL1、PRAME 和 PTTG1，可用于预测 EC 的预后。氨苯蝶啶和木犀草素可能用于对抗 EC。
