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用于预测人类子宫内膜癌预后及免疫微环境的焦亡相关基因panel

A Pyroptosis-Related Gene Panel in Prognosis Prediction and Immune Microenvironment of Human Endometrial Cancer.

作者信息

Zhang Xiaocui, Yang Qing

机构信息

Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.

出版信息

Front Cell Dev Biol. 2021 Oct 14;9:705828. doi: 10.3389/fcell.2021.705828. eCollection 2021.

Abstract

As the second common diagnosed cancer among gynecological tumors, endometrial cancer (EC) has heterogeneous pathogenesis and clinical manifestations. Therefore, prognosis prediction that considers gene expression value and clinical characteristics, is helpful to patients with EC. We downloaded RNA expression and clinical data from the TCGA database. We achieved 4 DEPRGs and constructed the PRG panel by univariate, lasso and multivariate Cox analysis. Based on the median value of the risk score, patients were divided into two groups. The Kaplan-Meier curve suggested that the patients with lower risk scores had better clinical outcomes of EC. AUC of ROC curves suggested the panel can be used as an independent predictor. Future analysis indicated the positive correlations between risk score and clinical characteristics. What's more, we performed GO and KEGG functional analysis and immune environment exploration to get an understanding of the potential molecular mechanism and immunotherapeutic target. To future validate the panel, we found that the relapse-free and overall survival probability of 4 prognostic DEPRGs between high-expression group and low-expression group were different through the Kaplan-Meier plotter in UCEC. In addition, GEPIA database and RT-PCR experiment indicated GPX4 and GSDMD were highly expressed in UCEC compared to normal endometrial tissue, and TIRAP and ELANE were downregulated. This study identified a PRG panel to predict the prognosis immune microenvironment in human EC. Then, Kaplan-Meier analysis and AUC below the ROC curves was used to validate the panel. In addition, Chi-square was used to show the clinical significance. GO, KEGG and GSEA were used to show the functional differences. Different immune-related databases were used to analyze the immune characteristics. The Kaplan-Meier plotter website was used to assess the effect of genes on survival. GEPIA and RT-PCR were used to analyze the expression level. In summary, we identified 4 prognosis-associated pyroptosis-related genes (ELANE, GPX4, GSDMD, and TIRAP). The panel can also predict prognosis prediction and immune microenvironment in human endometrial cancer.

摘要

作为妇科肿瘤中第二常见的诊断癌症,子宫内膜癌(EC)具有异质性的发病机制和临床表现。因此,考虑基因表达值和临床特征的预后预测,对子宫内膜癌患者有帮助。我们从TCGA数据库下载了RNA表达和临床数据。我们获得了4个差异表达的程序性死亡相关基因(DEPRG),并通过单变量、套索和多变量Cox分析构建了程序性死亡相关基因(PRG)面板。根据风险评分的中位数,将患者分为两组。Kaplan-Meier曲线表明,风险评分较低的患者子宫内膜癌的临床结局更好。ROC曲线的AUC表明该面板可作为独立预测指标。进一步分析表明风险评分与临床特征之间存在正相关。此外,我们进行了基因本体(GO)和京都基因与基因组百科全书(KEGG)功能分析以及免疫环境探索,以了解潜在的分子机制和免疫治疗靶点。为了进一步验证该面板,我们通过UCEC中的Kaplan-Meier绘图仪发现,高表达组和低表达组之间4个预后性DEPRG的无复发生存率和总生存率存在差异。此外,基因表达谱交互分析(GEPIA)数据库和逆转录聚合酶链反应(RT-PCR)实验表明,与正常子宫内膜组织相比,GPX4和GSDMD在UCEC中高表达,而TIRAP和ELANE下调。本研究确定了一个PRG面板来预测人类子宫内膜癌的预后免疫微环境。然后,使用Kaplan-Meier分析和ROC曲线下的AUC来验证该面板。此外,卡方检验用于显示临床意义。GO、KEGG和基因集富集分析(GSEA)用于显示功能差异。使用不同的免疫相关数据库分析免疫特征。Kaplan-Meier绘图仪网站用于评估基因对生存的影响。GEPIA和RT-PCR用于分析表达水平。总之,我们确定了4个与预后相关的焦亡相关基因(ELANE、GPX4、GSDMD和TIRAP)。该面板还可以预测人类子宫内膜癌的预后和免疫微环境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/491d/8551636/d857ba8950b4/fcell-09-705828-g001.jpg

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