为了探讨程序性细胞死亡(PCD)相关基因在子宫内膜癌(EC)患者中的潜在机制，并建立预后模型，我们从TCGA中下载了RNA测序数据(RNAseq)、单核苷酸变异(SNV)数据和相应的临床数据。我们筛选了预后相关的PCD相关基因，并进行一致性聚类分析。通过加权相关网络分析(WGCNA)、免疫渗透分析和其他分析方法比较了两个聚类。我们使用最小绝对收缩和选择算子(LASSO)算法构建了与PCD相关的预后模型。通过各种生物信息学方法评估了PCD相关基因标志的生物学意义。 我们确定了43个与EC患者预后显著相关的PCD相关基因，并将它们分为两个聚类。B聚类中的患者肿瘤纯度较高，T分期较高，并且预后较差，相比之下，A聚类通常表现出较高的免疫渗透。我们使用11个基因(GZMA, ASNS, GLS, PRKAA2, VLDLR, PRDX6, PSAT1, CDKN2A, SIRT3, TNFRSF1A, LRPPRC)构建了一个预后模型，并表现出良好的诊断性能。高风险评分的患者年龄较大，肿瘤分期和分级较高，并且预后较差。与预后相关的基因突变频率与风险评分相关。EC中的不良预后基因LRPPRC与增殖相关基因和多个PCD相关基因强相关。LRPPRC在临床分期较高的患者和死亡患者中表达较高。此外，LRPPRC与多种免疫细胞类型的浸润呈正相关。 我们确定了一个可以预测EC患者预后并为治疗干预提供潜在靶点的PCD相关基因标志。Copyright © 2023 Xiong, Chen, Guo, Zhang, Yuan and Gao.

To explore the underlying mechanism of programmed cell death (PCD)-related genes in patients with endometrial cancer (EC) and establish a prognostic model.The RNA sequencing data (RNAseq), single nucleotide variation (SNV) data, and corresponding clinical data were downloaded from TCGA. The prognostic PCD-related genes were screened and subjected to consensus clustering analysis. The two clusters were compared by weighted correlation network analysis (WGCNA), immune infiltration analysis, and other analyses. The least absolute shrinkage and selection operator (LASSO) algorithm was used to construct the PCD-related prognostic model. The biological significance of the PCD-related gene signature was evaluated through various bioinformatics methods.We identified 43 PCD-related genes that were significantly related to prognoses of EC patients, and classified them into two clusters via consistent clustering analysis. Patients in cluster B had higher tumor purity, higher T stage, and worse prognoses compared to those in cluster A. The latter generally showed higher immune infiltration. A prognostic model was constructed using 11 genes (GZMA, ASNS, GLS, PRKAA2, VLDLR, PRDX6, PSAT1, CDKN2A, SIRT3, TNFRSF1A, LRPPRC), and exhibited good diagnostic performance. Patients with high-risk scores were older, and had higher stage and grade tumors, along with worse prognoses. The frequency of mutations in PCD-related genes was correlated with the risk score. LRPPRC, an adverse prognostic gene in EC, was strongly correlated with proliferation-related genes and multiple PCD-related genes. LRPPRC expression was higher in patients with higher clinical staging and in the deceased patients. In addition, a positive correlation was observed between LRPPRC and infiltration of multiple immune cell types.We identified a PCD-related gene signature that can predict the prognosis of EC patients and offer potential targets for therapeutic interventions.Copyright © 2023 Xiong, Chen, Guo, Zhang, Yuan and Gao.