肝细胞癌失巢凋亡相关长链非编码RNA预后风险模型的建立与验证

Construction and evaluation of a prognostic risk model for hepatocellular carcinoma based on dithiolethione-related long non-coding RNA

目的:基于肿瘤基因组图谱(TCGA)建立肝细胞癌失巢凋亡相关长链非编码RNA(lncRNA)预后风险模型的预后风险模型。方法:从TCGA数据库中下载377例肝细胞癌(HCC)患者的RNA测序数据以及临床数据(包括374个HCC组织和50个癌旁组织);从GeneCards网站获取919个失巢凋亡相关的基因;使用"R"软件对失巢凋亡相关基因进行差异分析,并与lncRNA共表达分析确定失巢凋亡相关lncRNA。然后,通过单因素、多因素Cox分析和LASSO回归建立肝细胞癌失巢凋亡相关lncRNA预后风险模型,另外,通过计算出风险评分并根据风险评分的中位值将患者分为高、低风险组,对两组患者进行生存分析并绘制ROC曲线进行效能评估,分析高、低风险组间生存时间和免疫相关功能的差异。两组间比较通过Wilcoxon检验完成。结果:差异分析后共得到320个差异表达的失巢凋亡相关基因,与lncRNA共表达分析之后和临床样本合并,最终研究确定出7个失巢凋亡相关lncRNA用来构建预后风险模型,模型中患者1年、3年和5年的生存预测性能曲线下面积(AUC)值分别为0.771、0.747、0.686,生存分析显示低风险组患者生存率明显高于高风险组(77.0%比50.9%, P<0.01),并且免疫细胞和功能在高、低风险组中的差异有统计学意义( P<0.05)。 结论:成功构建以7个失巢凋亡相关lncRNA组成的预后风险模型,可有效预测HCC患者的生存预后。

Objective:To establish a prognostic risk model for anoikis-related long non-coding RNAs(lncRNAs)in hepatocellular carcinoma(HCC)based on the Cancer Genome Atlas(TCGA).Methods:RNA sequencing data and clinical data(including 374 HCC tissues and 50 adjacent non-tumor tissues)from 377 HCC patients were downloaded from the TCGA database.A total of 919 anoikis-related genes were retrieved from the GeneCards website.Differential analysis of anoikis-related genes was performed using"R"software,and co-expression analysis with lncRNAs was conducted to identify anoikis-related lncRNAs.Subsequently,a prognostic risk model for HCC anoikis-related lncRNAs was built through univariate and multivariate Cox analysis and LASSO regression.Patients were classified into high and low risk groups based on their risk scores,and survival analysis was performed on both groups.The ROC curve was plotted for efficacy evaluation,and differences in survival time and immune-related functions between the two risk groups were analyzed.Comparisons between the two groups were made using the Wilcoxon test.Results:After differential analysis,320 differentially expressed anoikis-related genes were identified.These genes were combined with lncRNAs through co-expression analysis and clinical samples,ultimately determining 7 anoikis-related lncRNAs for the construction of the prognostic risk model.The survival rate of patients in the high-risk group of the model was significantly lower than that of the low-risk group(P<0.05).The area under the curve(AUC)values for 1-year,3-year,and 5-year survival prediction performance in the training set were 0.771,0.747,and 0.686,respectively.Survival analysis showed that the survival rate of patients in the low-risk group(77.0%)was significantly higher than that of the high-risk group(50.9%,P<0.01).Additionally,differences in immune cells and functions between the high-and low-risk groups were statistically significant(P<0.05).Conclusion:A prognostic risk model composed of 7 anoikis-related lncRNAs was successfully established,which can effectively predict the survival prognosis of HCC patients.