| 耿雯,卢倩,李莉.基于铜死亡相关长链非编码 RNA构建肝细胞癌预后模型[J].安徽医药,2026,30(5):933-938. |
| 基于铜死亡相关长链非编码 RNA构建肝细胞癌预后模型 |
| Construction of prognostic model of hepatocellular carcinoma based on cuproptosis-related lncRNA |
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| DOI：10.3969/j.issn.1009-6469.2026.05.017 |
| 中文关键词: 癌，肝细胞 生物信息学 铜死亡 长链非编码 RNA 肝细胞癌 预后模型 免疫学 |
| 英文关键词: Carcinoma,hepatocellular Bioinformatics Cuproptosis Long non-coding RNA Hepatocellular carcinoma Prog. nostic model Immunology |
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| 中文摘要: |
| 目的基于生物信息学方法构建铜死亡相关长链非编码 RNA(lncRNA)预后模型，为肝细胞癌( HCC)病人的生存预测提供参考。方法在 2022年 8月至 2023年 8月从癌症基因组( TCGA)数据库获取肝细胞癌病人转录组和临床数据，首先通过共表达分析筛选铜死亡相关 lncRNA，进而采用单因素 Cox回归、最小绝对值选择与收缩算子( Lasso)回归及多因素 Cox回归分析建立铜死亡相关 lncRNA预后风险模型，并通过 Kaplan-Meier(KM)生存曲线、主成分分析( PCA)、受试者操作特征曲线( ROC曲线)对模型进行评价。此外，综合分析了高低风险组在信号通路、免疫细胞浸润、免疫检查点方面的差异，最后通过 qPCR验证铜死亡相关 lncRNA在肝细胞癌组织中的表达情况。结果最终筛选出 4个 lncRNA(AL451069.3、MKLN1-AS、AL031985.3、 AL117336.2)用于构建预后模型， ROC曲线表明该模型具有较高准确度，单因素及多因素 Cox回归分析表明风险评分是肝癌病人独立预后因子，基因富集分析( GSEA)显示一些肿瘤相关信号通路在高风险组中显著富集；调节性 T(Treg)细胞、中性粒细胞、 M2型巨噬细胞及免疫检查点在高风险组中表达较高。结论铜死亡相关 lncRNA风险模型对肝细胞癌病人预后具有较好的预测价值，可能为肝细胞癌病人免疫相关个性化治疗和评估提供一定帮助。 |
| 英文摘要: |
| Objective To establish a cuproptosis-related long non-coding RNA (lncRNA) prognostic model that can predict the sur.vival of hepatocellular carcinoma (HCC) patients based on bioinformatics.Methods The gene expression profiles and clinical data ofHCC patients were obtained from the The Cancer Genome Atlas (TCGA) database from August 2022 to August 2023. Cuproptosis-relat. ed lncRNA was screened by co-expression analysis, and then one-factor Cox regression, Least absolute selection and shrinkage operator(Lasso) regression and multifactorial Cox regression to establish a prognostic risk model for cuproptosis-related lncRNA and evaluated the model by Kaplan-Meier (KM) survival curves, Principal Component Analysis (PCA), and subject operating characteristic curves(ROC curves) were used to evaluate the model. In addition, the differences in signalling pathways, immune cell infiltration, and immunecheckpoints between high-and low-risk groups were comprehensively analyzed, and the expression of cuproptosis-related lncRNA in HCC tissues was finally verified by qPCR. Results Four cuproptosis-related lncRNA (AL451069.3, MKLN1-AS, AL031985.3,AL117336.2) were finalized to construct prognostic model. ROC curves proved that the prognostic model had high accuracy. Univariateand multivariate Cox analysis indicated that the risk score was an independent prognostic factor for HCC patients. Gene Set EnrichmentAnalysis (GSEA) enrichment analysis revealed that some tumor associated pathways were significantly enriched in the high-risk group. The expression levels of Treg cells, neutrophils, M2 macrophages, and immune checkpoint were higher in the high-risk group.Conclu. sion Cuproptosis-related lncRNA risk model can better predict the prognosis of patients with HCC, and may provide certain help for immune-related personalized treatment and evaluation for HCC patients. |
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