摘要
目的:基于血管生成相关基因(Angiogenesis-related genes,ARGs)构建肝细胞癌(Hepatocellular carcinoma,HCC)患者预后风险模型,为肝癌的预后和治疗提供策略。方法:从TGGA数据库下载50例正常肝组织和374例HCC组织样本的表达谱和对应的临床信息,同时从ICGC数据库下载48例正常肝组织和294例HCC组织样本的表达谱和临床信息。从Harmonizome和MSigDB数据库共收集到225个ARGs作为基因集,DESeq2包筛选出差异表达基因(Differential expression genes,DEGs)。利用单因素Cox回归分析确定对患者生存预后相关基因构建预后风险模型并应用ROC曲线评估模型对于HCC患者预后的预测能力。结果:从Harmonizome和MSigDB数据库的相关通路中共筛选出225个ARGs,其中137个ARGs在TCGA-LIHC和ICGC-LIHC数据集中均表达。对2个数据集ARGs进行单因素Cox回归分析,得到11个预后相关基因(F7、NARS、EMCN、SLCO^(2)A1、EGF、ITGAV、KDR、PTPRB、SPP1、ANGPT2、BIRC5),高风险组患者的OS明显低于低风险组(P<0.05)。在TCGA-LIHC数据集和ICGC-LIHC数据集中,11个预后相关基因均与肝癌患者的预后相关(P<0.05),其中ANGPT2、BIRC5、EGF、ITGAV、SPP1和NARS高表达者预后更差,SLCO^(2)A1、EMCN、F7、KDR和PTPRB低表达者预后更差。在GSE116174中,4个预后相关基因与肝癌患者预后相关(P<0.05),其中ANGPT2、BIRC5和SPP1高表达者预后更差,SLCO^(2)A1低表达者预后更差。在GSE14520中,7个预后相关基因与肝癌患者预后相关(P<0.05),其中ANGPT2、EGF和SPP1高表达者预后更差,F7、SLCO^(2)A1、KDR和PTPRB低表达者预后更差。结论:基于TCGA和ICGC数据库筛选到11个预后相关基因,可作为肝癌研究的潜在靶点。
Objective:To construct a prognostic risk model for patients with HCC based on angiogenesis-related genes(ARGs),aiming to provide strategies for prognosis and treatment of HCC.Methods:We downloaded expression profiles and corresponding clinical information of 50 normal samples and 374 HCC samples from the TGGA database,and expression profiles and clinical information of 48 normal liver tissues and 294 HCC tissues from the ICGC database.A total of 225 ARGs were collected from the Harmonizome and MSigDB databases as a gene set and screened for differentially expressed genes(DEGs)using the DESeq2 package.Univariate Cox regression analysis were used to determine the genes significantly associated with patient survival prognosis,and finally a prognostic risk model was constructed.The model's ability to predict the prognosis of HCC patients was evaluated using ROC curves.Results:A total of 225 ARGs were screened from Harmonizome and MSigDB databases,of which 137 ARGs were significantly differential expressed in both the TCGA-LIHC and ICGC-LIHC datasets.Univariate Cox regression analysis of 82 upregulated ARGs and 55 downregulated ARGs in both datasets identified 11 prognostic genes(F7,NARS,EMCN,SLCO^(2)A1,EGF,ITGAV,KDR,PTPRB,SPP1,ANGPT2,BIRC5).The OS of high risk group was significantly lower than that of low risk group(P<0.05).In the TCGA-LIHC dataset and ICGC-LIHC dataset,11 prognostic related genes were correlated with the prognosis of HCC patients(P<0.05),among which those with high expression of ANGPT2,BIRC5,EGF,ITGAV,SPP1and NARShad worse prognosis.Those with low expression of SLCO^(2)A1,EMCN,F7,KDR and PTPRB had worse prognosis.In GSE116174,four prognostic related genes were associated with the prognosis of liver cancer patients(P<0.05),among which those with high expression of ANGPT2,BIRC5 and SPP1 had worse prognosis,and those with low expression of SLCO^(2)A1had worse prognosis.In GSE14520,7 prognostic genes were associated with the prognosis of liver cancer patients(P<0.05),among which those with high expression of ANGPT2,EGFand SPP1had worse prognosis,and those with low expression of F7,SLCO^(2)A1,KDR and PTPRB had worse prognosis.Conclusion:This study established a prognostic model comprising 11 prognostic genes based on the TCGA and ICGC databases,serving as potential targets for liver cancer research.
作者
张飞亚
刘子宣
程旭
张鹏
ZHANG Fei-ya;LIU Zi-xuan;CHENG Xu;ZHANG Peng(Gannan Innovation and Translational Medicine Research Institute,Gannan Medical University,Ganzhou,Jiangxi 341000)
出处
《赣南医学院学报》
2024年第6期556-564,共9页
JOURNAL OF GANNAN MEDICAL UNIVERSITY
关键词
肝细胞癌
基因
血管生成
预测模型
风险评分
Hepatocellular carcinoma
Genes
Angiogenesis
Prediction model
Risk score