肝细胞癌自噬相关长链非编码RNA预后模型的建立与分析
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程树杰, Email: cheng66142@163.com

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河北省重点研发计划基金资助项目(18277790D)。


Construction and analysis of prognostic model for hepatocellular carcinoma based on autophagy-related long non-coding RNAs
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    摘要:

    背景与目的:肝细胞癌(HCC)是常见的原发性肝癌,其预后较差。自噬的失调可以促进HCC的发生与进展,本研究旨在分析自噬相关长链非编码RNA(lncRNA)在HCC患者中的潜在预后作用,并构建自噬相关lncRNA风险预测模型。
    方法:利用生物信息学方法分析TCGA数据库中374例HCC及50例正常对照样本的转录组数据及临床资料,从HADb网站获取自噬基因列表。采用Person相关性分析筛选与自噬基因相关的lncRNA,采用R软件caret程序包将筛选后的342例HCC样本按70%与30%的比例随机分为训练集及验证集,在训练集中采用Kaplan-Meier法及单因素Cox回归分析筛选出具有预后意义的lncRNA,随后采用多因素Cox回归分析筛选具有独立预后意义的自噬相关lncRNA,建立构建预后模型。使用多因素Cox回归系数计算风险评分,将患者分为低风险组和高风险组,分析算风险评分与HCC患者临床特征及总体生存的关系,并使用验证集加以验证。
    结果:347个lncRNA鉴定为自噬相关lncRNA(|R2|>0.3,P<0.001),其中26个lncRNA对HCC患者具有预后价值(均P<0.05)。多因素Cox回归分析得到基于12个自噬相关lncRNA(CYTOR、DANCR、LINC01138、LUCAT1、MAPKAPK5-AS1、NRAV、NRSN2-AS1、LINC01871、LINC00864、LINC02362、TMEM220-AS1和PSMB8-AS1)的预测患者预后的风险模型。高风险组HCC患者总生存期明显低于低风险组HCC患者(P<0.05)。12-自噬相关lncRNA预后模型评分与肿瘤分级、肿瘤分期和T分期有关(均P<0.05),与患者的年龄、性别无明显关系(均P>0.05)。在训练集中该预后模型的1、3、5年生存的时间依赖性ROC曲线的曲线下面积(AUC)分别为0.801,0.819和0.787,在验证集中其1、3、5年生存的时间依赖性ROC曲线的AUC分别为0.694、0.733和0.746。
    结论:所筛选的自噬相关lncRNA在HCC的肿瘤生物学中可能起关键作用,12-自噬相关lncRNA的模型对HCC具有预后判断价值。

    Abstract:

    Background and Aims: Hepatocellular carcinoma (HCC) is the most common primary liver cancers, and has a poor prognosis. Dysregulation of autophagy can promote the occurrence and development of HCC. This study was designated to investigate the potential prognostic roles of autophagy-related long non-coding RNAs (lncRNAs) in HCC patients and construct a risk prediction model based on autophagy-related lncRNAs.  
    Methods: The transcriptomic and clinical data of 374 HCC samples and 50 normal control samples in TCGA database were analyzed using bioinformatics approaches, and the list of autophagy-related genes were obtained from HADb. The lncRNAs associated with autophagy genes were screened by Person’s correlation analysis. Three hundred and forty-two HCC samples obtained by selection were randomly assigned to train dataset and validation dataset with a ratio of 70%:30% using caret package in R. The autophagy-related lncRNAs with prognostic significance were identified by Kaplan-Meier method and univariate Cox regression analysis. Then, the autophagy-related lncRNAs with independent prognostic significance were determined by multivariate stepwise regression Cox analysis to construct a prognostic prediction model. After the risk scores were calculated using Cox regression coefficient, the patients were divided into low risk group and high risk group, the relationship between the risk score and clinicopathologic features as well as the overall survival (OS) was analyzed, and then was verified in the validation dataset. 
    Results: A total of 347 lncRNAs were identified as autophagy-related lncRNAs (|R2|>0.3, P<0.001), including 26 lncRNAs with prognostic value for HCC patients. The risk model for predicting the prognosis of the patients was derived from the multivariate stepwise regression Cox analysis based on 12 autophagy-related lncRNAs (CYTOR, DANCR, LINC01138, LUCAT1, Mapkapk5-AS1, NRAV, NRSN2-AS1, LINC01871, LINC00864, LINC02362, TMEM220-AS1 and PSMB8-AS1). The risk scores of the 12- autophagy-related lncRNAs prognostic model was sufficiently associated with tumor grade, tumor stage and T stage (all P<0.05), but irrelevant to the age and sex of the patients (both P>0.05). In this model, the area under curve (AUC) of the time-dependent ROC for the 1, 3 and 5-year overall survival were 0.801, 0.819 and 0.787 in the train dataset, and the AUC of the time-dependent ROC for the 1, 3 and 5-year overall survival were 0.694, 0.733 and 0.746 in the validation dataset. 
    Conclusion: The identified autophagy-related lncRNAs may play critical roles in the oncobioloy of HCC, and the 12- autophagy-related lncRNAs has certain predictive value for the prognosis of HCC.

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陈圣, 赵继森, 李靖华, 杨季红, 程树杰.肝细胞癌自噬相关长链非编码RNA预后模型的建立与分析[J].中国普通外科杂志,2020,29(7):839-848.
DOI:10.7659/j. issn.1005-6947.2020.07.008

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  • 收稿日期:2020-04-26
  • 最后修改日期:2020-06-17
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  • 在线发布日期: 2020-07-25