衰老相关分泌表型相关的lncRNAs模型预测肝细胞癌患者预后的构建和验证

Construction and validation of a senescence-associated secretory phenotype associated lncRNAs model to predict prognosis in patients with hepatocellular carcinoma

目的构建衰老相关分泌表型(SASP)相关的可独立预测肝细胞癌(HCC)预后的风险模型,提高HCC的临床疗效。方法在癌症基因组学图谱(TCGA)数据库中获取HCC的测序数据及临床数据并分离出lncRNAs;在GeneCard网站中检索并筛选出相关系数>7的SASP相关基因,利用R语言“limma”包筛选出差异表达的SASP相关的基因及对应的lncRNAs。利用Cox回归分析和lasso构建SASP相关的lncRNAs预测模型,根据样本的风险评分中位值将HCC患者分为高风险组、低风险组,采用Kaplan-Meier曲线进行生存分析。利用单样本基因集富集分析(ssGSEA)来研究样本的风险评分和免疫状态之间的联系。结果从TCGA数据库中获取了374个肿瘤样本和50个正常组织样本,筛选出6个SASP相关的lncRNAs组成预后模型,计算出各样本的风险评分。生存分析显示,低风险组患者的预后优于高风险组患者的预后。风险模型1年生存受试者操作特征曲线的曲线下面积0.812。单因素和多因素回归分析显示,患者风险评分是HCC预后的独立危险因素(OR>1,P<0.05)。ssGSEA结果显示,高风险组免疫检查点特异性靶点和相关通路的表达水平更高。结论本研究成功构建SASP相关的lncRNAs风险模型,风险模型可独立预测HCC患者的预后情况。

Objective To construct a senescence-associated secretory phenotype(SASP)related risk model that can independently predict the prognosis of hepatocellular carcinoma(HCC),and to improve the clinical efficacy of HCC.Methods Sequencing and clinical data of HCC were obtained from the cancer genome atlas(TCGA)database,and lncRNA were isolated.SASP related genes with correlation coefficient>seven were searched and screened from the GeneCard website,and genes related to differentially expressed SASP associated lncRNAs were screened using the R language“limma”package.Cox regression analysis and lasso were used to construct the lncRNAs prediction model related to SASP.HCC patients were divided into high-risk group and low-risk group according to the median risk score of the samples.Kaplan-Meier curve was used for survival analysis.Single sample gene set enrichment analysis(ssGSEA)was used to investigate the association between risk scores and immune status in samples.Results A total of 374 tumor samples and 50 normal tissue samples were obtained from the TCGA database.Six lncRNAs associated with SASP were selected form a prognostic model,and the risk scores of each sample were calculated.Survival analysis showed that the prognosis of patients in the low-risk group was better than that in the high-risk group.Area under one-year survival receiver operating characteristic curve of risk model was 0.812.Univariate and multivariate regression analysis showed that patient risk score was an independent risk factor for HCC prognosis(OR>1,P<0.05).ssGSEA results showed higher expression levels of immune checkpoint specific targets and associated pathways in the high-risk group.Conclusion In this study,the SASP-related lncRNAs risk model is successfully constructed,and the risk model can independently predict the prognosis of HCC patients.