宫颈癌焦亡、凋亡和坏死性凋亡联合预后模型的构建和实验验证

Construction and experimental verification of the combined prognostic signature of pyroptosis, apoptosis and necroptosis for cervical cancer

  • 摘要: 目的:构建一个与联合程序性细胞死亡(PCD)相关的宫颈癌(CC)预后模型。方法:分别筛选出焦亡、凋亡和坏死性凋亡在CC 中的差异表达基因(DEGs),经交集后得到联合PCD DEGs(PANDEGs)。采用单因素、LASSO、逐步多因素Cox 回归模型筛选出与预后相关的PANDEGs,建立预后模型。根据中位风险评分将CC 患者分为高危组和低危组,绘制生存曲线,验证模型对患者预后的作用,通过实时荧光定量聚合酶链式反应(RT-qPCR)证实预后基因在组织标本中的表达差异。绘制列线图,并进行与该模型相关的功能富集分析。结果:最终从65 个PANDEGs 中筛选出4 个具有预后价值的关键基因(NOD1TNFBCL2NDRG2)。Kaplan-Meier分析显示,低危组患者的总生存期(OS)明显长于高危组。列线图的建立表明预测生存与实际观察结果一致性较好。NOD1、TNF、BCL2 和NDRG2 在CC 组织与正常宫颈组织中的表达差异均有统计学意义(P<0.05)。结论:该预后模型可作为预测CC患者预后的有效工具;NOD1、TNF、BCL2和NDRG2有可能成为CC新的治疗靶点。

     

    Abstract: Objective: To construct a prognostic signature of cervical cancer(CC)associated with combined programmed cell death(PCD).Methods: The differentially expressed genes(DEGs)of pyroptosis(P), apoptosis(A)and necroptosis (N) in CC were screened respectively.DEGs related to combined PCD (PANDEGs) were obtained after intersection.Univariate, LASSO and stepwise multivariate Cox regression models were used to screen out PANDEGs related to prognosis and a prognostic signature was established.CC patients were divided into high and low risk groups according to the median risk score.The survival curve was drawn to verify the effect of the signature on the prognosis of patients.The expression differences of prognostic genes in tissue samples were confirmed by real-time fluorescence quantitative polymerase chain reaction(RT-qPCR).In addition, a nomogram was drawn and functional enrichment analysis related to the model was performed.Results: Finally, four key genes with prognostic value(NOD1, TNF, BCL2 and NDRG2)were screened out from the 65 PANDEGs.Kaplan-Meier analysis showed that the overall survival(OS)of the low-risk group was significantly longer than that of the high-risk group.The nomogram showed that the predicted survival was in good agreement with the actual observation.The expression levels of NOD1, TNF, BCL2 and NDRG2 between CC tissues and normal cervical tissues were significantly different (P<0.05).Conclusion: This prognostic signature can be used as an effective tool to predict the prognosis of CC patients.NOD1, TNF, BCL2 and NDRG2 may become new therapeutic targets for CC.

     

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