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中华肝脏外科手术学电子杂志 ›› 2023, Vol. 12 ›› Issue (02) : 185 -189. doi: 10.3877/cma.j.issn.2095-3232.2023.02.012

临床研究

基于生物信息学分析构建肝内胆管细胞癌患者铁死亡相关lncRNA预后模型
莫建涛1, 杨沛泽1, 曹瑞奇1, 马清涌1, 王铮1, 仵正1, 周灿灿1,()   
  1. 1. 710061 西安交通大学第一附属医院肝胆外科
  • 收稿日期:2022-12-20 出版日期:2023-03-28
  • 通信作者: 周灿灿
  • 基金资助:
    陕西省自然科学基础研究计划(2020JQ-510); 陕西省创新能力支撑计划(2022PT-35); 西安交通大学第一附属医院科研发展基金(2021QN-24)

Establishment of a ferroptosis-related lncRNA prognostic model for patients with intrahepatic cholangiocarcinoma based on bioinformatics analysis

Jiantao Mo1, Peize Yang1, Ruiqi Cao1, Qingyong Ma1, Zheng Wang1, Zheng Wu1, Cancan Zhou1,()   

  1. 1. Department of Hepatobiliary Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
  • Received:2022-12-20 Published:2023-03-28
  • Corresponding author: Cancan Zhou
引用本文:

莫建涛, 杨沛泽, 曹瑞奇, 马清涌, 王铮, 仵正, 周灿灿. 基于生物信息学分析构建肝内胆管细胞癌患者铁死亡相关lncRNA预后模型[J]. 中华肝脏外科手术学电子杂志, 2023, 12(02): 185-189.

Jiantao Mo, Peize Yang, Ruiqi Cao, Qingyong Ma, Zheng Wang, Zheng Wu, Cancan Zhou. Establishment of a ferroptosis-related lncRNA prognostic model for patients with intrahepatic cholangiocarcinoma based on bioinformatics analysis[J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2023, 12(02): 185-189.

目的

基于生物信息学分析建立肝内胆管细胞癌(ICC)患者的铁死亡相关长链非编码RNA(lncRNA)预后模型。

方法

从癌症基因组图谱(TCGA)数据库获取36例ICC和9例正常人群基因表达数据及相应临床信息,提取与预后相关的铁死亡lncRNA并构建预后模型。通过Cox回归模型和ROC曲线验证铁死亡相关lncRNA预后模型的预测能力。生存分析采用Kaplan-Meier法和Log-rank检验。

结果

多因素Cox回归分析筛选出AL161431.1和LINC01587两个铁死亡相关lncRNA为ICC生存预后的独立预测因子(HR=2.99,7.23;P<0.05)。建立ICC患者lncRNA预后模型,风险评分=1.096×AL161431.1+1.979×LINC01587。Kaplan-Meier生存曲线显示高风险组与低风险组的总体生存期差异有统计学意义(χ2=6.54,P<0.05)。多因素Cox回归分析显示,铁死亡相关lncRNA风险评分是一个独立的预后指标(HR=1.12,P<0.05)。该模型1、2、3年生存的时间依赖性ROC曲线下面积(AUC)分别为0.883,0.837和0.853;而肿瘤分级、分期的1年生存的时间依赖性ROC曲线AUC分别为0.598、0.637,该模型生存预后预测能力明显优于肿瘤分级和分期。

结论

本研究构建的铁死亡相关lncRNA预测模型能有效预测ICC患者的生存。

Objective

To establish a ferroptosis-related long non-coding RNA (lncRNA) prognostic model for patients with intrahepatic cholangiocarcinoma (ICC) based on bioinformatics analysis.

Methods

The gene expression data and clinical information of 36 patients with ICC and9 healthy counterparts were obtained from The Cancer Genome Atlas (TCGA) database, and the ferroptosis-related lncRNAs which were associated with clinical prognosis were extracted to establish the prognostic model. The predictive performance of ferroptosis-related lncRNA prognostic model was assessed by Cox's regression model and ROC curve. Survival analysis was carried out by Kaplan-Meier method andLog-rank test.

Results

Multivariate Cox's regression analysis revealed that two ferroptosis-related lncRNAs, AL161431.1 and LINC01587, were the independent prognostic factors of ICC (HR=2.99, 7.23; P<0.05). The lncRNA prognostic model was established for patients with ICC. The risk score =1.096×AL161431.1+1.979×LINC01587. Significant difference was observed in the overall survival between high-risk and low-risk groups by Kaplan-Meier survival curve (χ2=6.54, P<0.05). Multivariate Cox's regression analysis demonstrated that the risk score of ferroptosis-related lncRNA was an independent prognostic factor (HR=1.12, P<0.05). The area under time-dependent ROC curve (AUC) of the 1-, 2- and 3-year survival of this model was 0.883, 0.837 and 0.853, respectively. However, 1-year survival AUC of time-dependent ROC curve of tumor grading and staging was 0.598 and 0.637. The prognostic prediction ability of this model was significantly better than those of tumor grading and staging.

Conclusions

The prognostic model based on ferroptosis-related lncRNA can effectively predict the survival of patients with ICC.

图1 铁死亡相关lncRNA的共表达网络注:lncRNA为长链非编码RNA,FRG为铁死亡相关基因,FDR为错误发现率
图2 肝内胆管细胞癌预后相关铁死亡lncRNA单因素Cox回归森林图注:lncRNA为长链非编码RNA
图3 铁死亡相关lncRNA风险评分预测肝内胆管细胞癌患者生存的时间依赖性ROC曲线注:lncRNA为长链非编码RNA,AUC为曲线下面积
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