实用肝脏病杂志 ›› 2022, Vol. 25 ›› Issue (4): 558-562.doi: 10.3969/j.issn.1672-5069.2022.04.026

• 肝癌 • 上一篇    下一篇

基于网络铁死亡相关的长非编码RNA预测肝细胞癌患者预后研究*

布凡, 柴剑波, 白冰, 王万宇, 赵永厚   

  1. 150036 哈尔滨市 黑龙江中医药大学(布凡,王万宇);黑龙江神志医院(赵永厚,柴剑波,白冰)
  • 收稿日期:2021-12-17 出版日期:2022-07-10 发布日期:2022-07-14
  • 通讯作者: 赵永厚,E-mail: zyszbx2020@126.com
  • 作者简介:布凡,男,25岁,硕士研究生。E-mail:547782560@qq.com
  • 基金资助:
    *国家自然科学基金资助项目(编号:81572939)

Cyber-based study on ferroptosis-related long non-coding RNA signature predicting prognosis of patients with hepatocellular carcinoma

Bu Fan, Chai Jianbo, Bai Bing, et al   

  1. Heilongjiang University of Chinese Medicine,Harbin 150036,Heilongjiang Province, China
  • Received:2021-12-17 Online:2022-07-10 Published:2022-07-14

摘要: 目的 探讨构建基于铁死亡相关长链非编码RNA(lncRNA)的预后风险模型预测肝细胞癌(HCC)患者预后的价值。方法 自癌症基因组图谱TCGA数据库下载HCC患者RNA测序数据。基于HCC差异水平的铁死亡相关lncRNAs构建预后风险模型。结果 鉴定了5个基于HCC差异水平的铁死亡相关lncRNAs;Kaplan-Meier分析显示,高风险lncRNAs与HCC预后不良相关,预测3 a生存率的ROC曲线下面积(AUC)为0.873;单样本基因集富集分析(ssGSEA)发现低风险组与高风险组细胞溶解活性、MHCI类分子、I型INF反应、II型INF反应存在显著性差异(P<0.05);免疫检查点显示,两组CD44、TNFRSF4和CD276等水平也存在显著性差异(P<0.05)。结论 通过生物信息学方法筛选出5个基于HCC差异水平的铁死亡相关lncRNAs构建的预后风险模型为HCC防治研究奠定了一定的基础。

关键词: 肝细胞癌, 铁死亡, 长链非编码RNA, TCGA数据库

Abstract: Objective The purpose of this study was to investigate the prognosis of patients with hepatocellular carcinoma (HCC) by a prognostic risk model we constructed based on the cyber-arisen materials on ferroptosis-related long non-coding RNAs (lncRNAs). Methods The RNA sequencing data from patients with HCC were downloaded from the Cancer Genome Atlas TCGA database. A prognostic risk model was constructed based on differentially expressed iron death-associated lncRNAs in HCC tissues. Results Five differentially expressed lncRNAs associated with HCC prognosis were identified, and the Kaplan-Meier analysis showed that the high-risk lncRNAs were associated with poor prognosis in patients with HCC, with an area under the ROC curve (AUC) of 0.873 for 3-year survival;the single sample gene set enrichment analysis (ssGSEA) revealed immuno- and tumor-related pathways in low-risk populations; the differential analysis of immune functions showed that there were significant differences in cytolytic activity, type I INF response and type II INF response between patients with low and high risk; the immune checkpoint showed that there were also significant differences in the expression of CD44, TNFRSF4 and CD276 between the two groups. Conclusion Five ferroptosis-related lncRNAs impacting the prognosis of patients with HCC are selected by bioinformatics, and we thereby construct a prognostic risk model, which might lay the foundation for the further prevention and therapeutic study on HCC.

Key words: Hepatocellular carcinoma, Ferroptosis, Long non-coding RNA, TCGA database