自噬相关长链非编码RNA在肝细胞癌中的功能分析及预后模型构建

Function analysis and prognostic model construction of autophagy-related long non-coding RNA in hepatocellular carcinoma

目的:筛选在肝细胞癌(HCC)中具有预后价值的核心自噬相关长链非编码RNA(lncRNA)。方法:选择癌症基因组图谱数据库(TCGA)和人类自噬数据库(HADb)进行生物信息学分析。以多因素Cox回归,最小绝对收缩和选择算子(Lasso)回归构建风险评分模型。模型的特异度和敏感度由受试者工作特征曲线(ROC)评估。相关生物学功能由Metascape数据库和基因集富集分析(GSEA)鉴定。结果:共鉴定了10个关键lncRNAs并据此构建风险评分模型。生存分析显示高风险组患者总生存期显著低于低风险组(P<0.001)。该模型在预测HCC患者一年、三年、五年生存率方面表现良好,曲线下面积分别是0.810、0.751、0.736。多因素Cox回归表明,该模型是HCC的独立预后因素(HR=3.666,P<0.001)。结论:本研究鉴定了10个自噬相关lncRNAs,并以之构建了1个用于HCC的预后风险模型,有望成为潜在的治疗靶点和新的预测指标。

Objective:To screen the core autophagy-related long non-coding RNA(lncRNA)with prognostic value in hepatocellular carcinoma(HCC).Methods:The Cancer Genome Atlas Database(TCGA)and Human Autophagy Database(HADb)were used for bioinformatics analysis. Multi-factor Cox regression,least absolute shrinkage and selection operator(Lasso)regression were used to construct a risk scoring model. The specificity and sensitivity of the model were evaluated by the receiver operating characteristic curve(ROC). Related biological functions was identified by Metascape database and gene set enrichment analysis(GSEA).Results:A total of 10 key lncRNAs were identified by Lasso Cox regression and a risk scoring model was constructed. Survival analysis showed that the overall survival of HCC patients in the high-risk group was significantly lower than that in the low-risk group(P<0.001). The model predicts the area under the 1,3,and 5 year survival rate curves of HCC patients to be 0.810,0.751 and 0.736,respectively.Multivariate Cox regression results showed that the risk model based on autophagy-related lncRNAs is an independent prognostic factor of HCC(HR=3.666,P<0.001).Conclusion:This study identified 10 key autophagy-related lncRNAs in HCC and used them to construct a prognostic model that can be used as an independent prognostic factor for HCC,which is expected to become a potential therapeutic target and new predictive indicator.