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基于自噬相关长链非编码RNA的肝细胞癌预后预测特征及列线图

Prognosis-Predictive Signature and Nomogram Based on Autophagy-Related Long Non-coding RNAs for Hepatocellular Carcinoma.

作者信息

Jia Yu, Chen Yan, Liu Jiansheng

机构信息

Department of General Surgery, First Hospital of Shanxi Medical University, Taiyuan, China.

First Clinical Medical College, Shanxi Medical University, Taiyuan, China.

出版信息

Front Genet. 2020 Dec 23;11:608668. doi: 10.3389/fgene.2020.608668. eCollection 2020.

Abstract

Autophagy plays a vital role in hepatocellular carcinoma (HCC) pathogenesis. Long non-coding RNAs (lncRNAs) are considered regulators of autophagy, and the aim of the present study was to investigate the prognostic value of autophagy-related lncRNA (ARlncRNA) and develop a new prognostic signature to predict the 1-year and 3-year overall survival (OS) of HCC patients. Transcriptome and clinical survival information of HCC patients was obtained from The Cancer Genome Atlas database. A set of ARlncRNAs was identified by co-expression analysis, from which seven ARlncRNAs (AC005229.4, AL365203.2, AL117336.3, AC099850.3, ELFN1-AS1, LUCAT1, and AL031985.3) were selected for use as a predictive signature. Risk scores were derived for each patient, who were then divided into high-risk and low-risk groups according to the median risk value. The OS of high-risk patients was significantly lower than that of low-risk patients ( < 0.0001). The 1- and 3-year time-dependent ROC curves were used to evaluate the predictive ability of the risk score (AUC = 0.785 of 1 year, 0.710 of 3 years), and its predictive ability was found to be better than TNM stage. Moreover, the risk score was significantly, linearly related to pathological grade and TNM stage ( < 0.05). Overall, a novel nomogram to predict the 1-year and 3-year OS of HCC patients was developed, which shows good reliability and accuracy, for use in improved treatment decision-making.

摘要

自噬在肝细胞癌(HCC)发病机制中起着至关重要的作用。长链非编码RNA(lncRNAs)被认为是自噬的调节因子,本研究的目的是探讨自噬相关lncRNA(ARlncRNA)的预后价值,并开发一种新的预后特征来预测HCC患者的1年和3年总生存期(OS)。HCC患者的转录组和临床生存信息来自癌症基因组图谱数据库。通过共表达分析鉴定出一组ARlncRNAs,从中选择了7种ARlncRNAs(AC005229.4、AL365203.2、AL117336.3、AC099850.3、ELFN1-AS1、LUCAT1和AL031985.3)作为预测特征。计算每位患者的风险评分,然后根据中位风险值将患者分为高风险组和低风险组。高风险患者的OS显著低于低风险患者(<0.0001)。使用1年和3年时间依赖性ROC曲线评估风险评分的预测能力(1年时AUC = 0.785,3年时AUC = 0.710),发现其预测能力优于TNM分期。此外,风险评分与病理分级和TNM分期显著线性相关(<0.05)。总体而言,开发了一种用于预测HCC患者1年和3年OS的新型列线图,其显示出良好的可靠性和准确性,可用于改善治疗决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/674c/7793718/ea1ab9c2dd8c/fgene-11-608668-g001.jpg

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