By analyzing the gene expression of endometrial carcinoma (EC) patients, the key factors in PI3K signaling pathway and its related genes mediating EC were explored. The EC samples and normal endometrial samples were downloaded from TCGA database and GTEx database. The R language “limma” package was used for differential analysis, and the expression level of genes in each tissue was analyzed by “gganatogram” package. Functional enrichment analysis of differential genes was carried out by KOBAS, an online bioinformatics website. The correlation between key genes and differential genes was evaluated using TCGA data and GTEx combined gene expression data. The corresponding clinical data were downloaded from TCGA database and GTEx database, and the R language “survival” package was used to assess the potential of candidate differential genes as a key factor of EC. Based on the combined differential analysis of TCGA and GTEx databases, 299 genes with significant differential in expression were finally got. Functional enrichment analysis revealed that genes were predominantly enriched in the entry of “Pathways in cancer”, including RAC2 and PIK3R3 genes which were related with the abnormal PI3K pathway in cancer. PIK3R3, a key gene in the PI3K signaling pathway, was highly-expressed in EC. SPDEF, GCNT2, KIAA1324, C9orf152, MARVELD3, and APEX2 genes were found to be positively correlated with PIK3R3 in EC, all of which were highly expressed in EC. KM survival analysis showed that SPDEF, GCNT2, KIAA1324 and C9orf152 were significantly correlated with patients’ survival. ROC analysis showed that SPDEF, GCNT2, KIAA1324 and C9orf152 gene could be used as potential markers for prognosis and survival of EC patients. It was found that PIK3R3, a key gene in the PI3K signaling pathway, was highly expressed in EC. The SPDEF, GCNT2, KIAA1324 and C9orf152 genes were also highly expressed in EC, and were positively correlated with PIK3R3 in EC. Moreover, they are significantly correlated with the patients’ survival, suggesting that they may be potential markers for the prognosis of patients with EC.

通过分析子宫内膜癌（EC）患者的基因表达，探讨PI3K信号通路的关键因素及其介导EC的相关基因。EC样本和正常子宫内膜样本从TCGA数据库和GTEx数据库下载。使用R语言“limma”包进行差异分析，通过“gganatogram”包分析各组织中基因的表达水平。差异基因的功能富集分析由在线生物信息学网站 KOBAS 进行。使用TCGA数据和GTEx组合基因表达数据评估关键基因和差异基因之间的相关性。从TCGA数据库和GTEx数据库下载相应的临床数据，并且使用R语言“survival”包来评估候选差异基因作为EC关键因素的潜力。基于TCGA和GTEx数据库的联合差异分析，最终得到299个表达差异显着的基因。功能富集分析显示，基因主要富集在“Pathways incancer”的入口，包括与癌症异常PI3K通路相关的RAC2和PIK3R3基因。PI3K 信号通路中的关键基因 PIK3R3 在 EC 中高表达。SPDEF、GCNT2、KIAA1324、C9orf152、MARVELD3和APEX2基因在EC中与PIK3R3呈正相关，均在EC中高表达。KM生存分析显示SPDEF、GCNT2、KIAA1324和C9orf152与患者生存率显着相关。ROC分析显示SPDEF、GCNT2、KIAA1324和C9orf152基因可作为EC患者预后和生存的潜在标志物。发现PI3K信号通路中的关键基因PIK3R3在EC中高表达。SPDEF、GCNT2、KIAA1324 和 C9orf152 基因在 EC 中也高表达，并与 EC 中的 PIK3R3 呈正相关。此外，它们与患者的生存率显着相关，表明它们可能是 EC 患者预后的潜在标志物。并且与 EC 中的 PIK3R3 呈正相关。此外，它们与患者的生存率显着相关，表明它们可能是 EC 患者预后的潜在标志物。并且与 EC 中的 PIK3R3 呈正相关。此外，它们与患者的生存率显着相关，表明它们可能是 EC 患者预后的潜在标志物。