大理大学学报 ›› 2022, Vol. 7 ›› Issue (10): 52-59.

• 基础医学 • 上一篇    下一篇

基于焦亡相关基因的肝细胞癌临床预后模型的建立和评估

刘川铭,李 谢,卢熙奎,曾点点,陈 洁*   

  1. 1.大理大学药学院,云南大理 6710002.大理大学公共卫生学院,云南大理 671000

    3.昆明市第三人民医院药学部,昆明 650041

  • 收稿日期:2022-04-20 修回日期:2022-05-22 出版日期:2022-10-15 发布日期:2022-11-15
  • 通讯作者: 陈洁,主任药师,E-mail:386981562@qq.com。
  • 作者简介:刘川铭,硕士研究生,主要从事临床药学研究。
  • 基金资助:

    云南省地方本科高校基础研究联合专项资金项目(202001BA070001-092

Establishment and Evaluation of Clinical Prognostic Model of Hepatocellular Carcinoma Based on Pyroptosis-Related Genes

Liu ChuanmingLi XieLu XikuiZeng DiandianChen Jie*   

  1. 1.College of PharmacyDali UniversityDaliYunnan 671000China2.College of Public HealthDali UniversityDaliYunnan 671000China3.Department of PharmacyThe Third People's Hospital of KunmingKunming 650041China

  • Received:2022-04-20 Revised:2022-05-22 Online:2022-10-15 Published:2022-11-15

摘要:

[摘要] 目的:探究与肝细胞癌(HCC)预后密切相关的焦亡相关基因(PRGs),构建相应的预后风险模型以评估HCC患者的生存和预后情况。方法:利用TCGA数据库获取HCC的转录组数据和临床数据,筛选出差异表达的PRGs。采用COX分析确定与HCC预后相关的PRGs并构建风险评分模型,通过K-M生存曲线、受试者操作特征曲线(ROC曲线)和列线图分析该模型的准确性及预后价值。结果:筛选得到58个差异表达的PRGsGO功能富集分析结果显示其主要涉及细胞焦亡,KEGG信号通路分析显示其主要富集在NOD样受体信号传导途径、非酒精性脂肪性肝病和Toll样受体信号传导途径等信号通路。COX分析确定了8个与HCC预后相关的PRGs并构建了预后风险评分模型,ROC曲线显示该风险评分的曲线下面积值为0.802,高于其他临床数据,可作为一个独立的预后因素。结论:8PRGs构建的预后风险模型可有效预测HCC患者的预后情况。

关键词:

"> font-size:10.5pt, ">肝细胞癌, 焦亡相关基因, 预后模型, TCGA数据库, 生物信息学

Abstract:

AbstractObjectiveTo explore the pyroptosis-related genesPRGsthat are closely related to the prognosis of hepatocellular carcinomaHCC), and construct a corresponding prognostic risk model to evaluate the survival and prognosis of HCC patients. MethodsThe transcriptome data and clinical data of HCC were downloaded from TCGA databaseand the differentially expressed PRGs were screened out. COX analysis was used to determine the PRGs related to the prognosis of HCC and construct a prognostic risk score modelwhile K-M survival curvereceiver operator characteristic curveROC curveand nomogram were plotted to analyze and verify the accuracy of the model and its prognostic value. Results58 differentially expressed PRGs were screened. GO function enrichment analysis showed that these genes were involved in pyroptosisand KEGG signal pathway analysis showed that these genes were mainly enriched in non-alcohdic fatty liver disease and Toll-like receptor signal pathways. Eight PRGs significantly related to the prognosis of HCC were identified by COX analysisand a prognostic risk score model was constructed. ROC curve showed that the area under the curve value of this risk score was 0.802which was higher than other clinical data and could be as an independent prognostic factor. ConclusionThe prognostic risk model constructed by 8 PRGs can effectively predict the prognosis of patients with HCC.

Key words:

"> font-size:10.5pt, ">hepatocellular carcinoma, pyroptosis-related genes, prognostic model, TCGA database, bioinformaticsfont-size:10.5pt, ">

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