肝细胞癌坏死性凋亡相关长链非编码RNA预后风险模型的建立与评估

Construction and evaluation of a prognostic risk model for necroptosis-related long non-coding RNA in hepatocellular Carcinoma

目的:基于肿瘤基因组图谱(TCGA)数据库建立肝细胞癌(HCC)的坏死性凋亡相关长链非编码RNA(NRlncRNA)预后风险模型。方法:从TCGA中下载377例HCC患者样本转录组数据和临床资料(包括374个HCC组织和50个癌旁组织),通过对坏死性凋亡相关基因和lncRNA进行共表达分析确定NRlncRNA;筛选两种组织的差异性,用于后续分析。对377例临床资料进行预处理共筛选到合格的343例样本,随机分组为训练集(172例)和测试集(171例)。在训练集中通过单因素Cox、LASSO、多因素Cox分析确定预后风险模型,计算风险评分,按照风险评分的中位值分为高、低风险组;采用Kaplan-Meier法对两组患者进行生存分析,通过绘制受试者工作特征(ROC)曲线对预后风险模型进行效能评估。在测试集和整个队列进一步验证。分析高、低风险模型组间生物学通路富集和免疫相关功能的差异。两组间比较通过Wilcoxon检验完成。结果:共筛选到362个NRlncRNA,差异分析筛选出85个差异NRlncRNA,最终筛选出6个NRlncRNA组成的预后风险模型,该模型对训练集患者1年、3年和5年的生存预测性能曲线下面积(AUC)值分别为0.833、0.790和0.803;高风险组患者的总生存期明显低于低风险组(P<0.05)。测试集和整个队列中也具有良好的预测效能。进一步分析表明免疫细胞及功能在高、低风险组中存在不同程度的差异。结论:基于6个NRlncRNA建立预后风险模型可以有效的预测HCC患者的生存预后,风险评分为HCC独立的预后因素。

Objective Based on the cancer genome atlas(TCGA)database,we developed a prognostic risk model for necroptosis-related long non-coding RNA(NRlncRNA)in hepatocellular carcinoma(HCC).Methods Transcriptomic data and clinical profiles of 377 HCC patient samples(including 374 HCC tissues and 50 paraneoplastic tissues)were downloaded from TCGA and NRlncRNAs were identified by co-expression analysis of necroptosis-related genes and lncRNAs;the two tissues were screened for differences for subsequent analysis.A total of 343 eligible samples were screened by pre-processing 377 clinical data and randomly grouped into a training set(172 cases)and a test set(171 cases).The prognostic risk model was determined by single-factor Cox,LASSO and multi-factor Cox analyses in the training set,and risk scores were calculated and divided into high and low risk groups according to the median value of the risk scores;the Kaplan-Meier method was used to analyse the survival of patients in both groups,and the efficacy of the prognostic risk model was assessed by plotting receiver operating characteristic(ROC)curves.Further validation in the test set and across the cohort.Analysis of differences in biological pathway enrichment and immune-related function between high and low risk model groups.Comparisons between the two groups were completed by the Wilcoxon test.Results A total of 362 NRlncRNAs were screened,and 85 differential NRlncRNAs were screened by differential analysis,resulting in a prognostic risk model consisting of 6 NRlncRNAs,which had an area under curve(AUC)value of 0.833,0.790 and 0.803 for the survival prediction performance of patients in the training set at 1,3 and 5 years,respectively;the overall survival of patients in the high-risk group was significantly lower than that of the low-risk group(P<0.05).There was also good predictive efficacy in the test set and in the whole cohort.Further analysis showed that immune cells and function differed to varying degrees in the high and low risk groups.Conclusion A prognostic risk model based on six NRlncRNAs can effectively predict the survival prognosis of HCC patients,with the risk score being an independent prognostic factor for HCC.