铜死亡相关lncRNA预测骨肉瘤患者预后及免疫途径

Cuproptosis-related lncRNA predicts prognosis and immune pathways in osteosarcoma pa⁃tients

目的:鉴定铜死亡相关的lncRNAs,并利用其构建模型预测骨肉瘤(OS)患者的生存状况。方法:从TARGET数据库下载OS患者的RNA-seq数据以及相关临床资料。从相关研究报告中获取铜死亡相关基因集。使用共表达分析以及单因素Cox回归,筛选出OS生存相关的铜死亡相关lncRNA。在LASSO-Cox回归构建OS预后模型,并通过受试者工作特征曲线(ROC)和Kaplan-Meier(K-M)生存分析评估模型效能。利用单样本基因集富集分析(ssGSEA),探讨铜死亡相关的lncRNAs模型评分与OS中信号通路的关系。通过基因本体(GO)和京都基因组百科全书(KEGG)进行不同风险组OS患者的功能与通路富集分析。通过ESTIMATE算法,推测OS患者肿瘤样本中免疫细胞浸润水平。利用实时荧光定量聚合酶链式反应(RT-qPCR)实验验证4个铜死亡相关的lncRNAs在不同细胞系中的表达情况。结果:在85例OS患者中,与10个铜死亡相关RNA共表达的lncRNA共有374个。根据Cox回归分析结果,鉴定出62个与OS患者预后相关的铜死亡相关的lncRNAs。共识聚类分析发现OS患者具有2种铜死亡相关的lncRNAs表达模式,并且2种铜死亡相关的lncRNAs表达模式的患者预后有显著差异。采用LASSO-Cox回归分析构建铜死亡相关的lncRNAs预后模型。t-ROC曲线评估模型效能,结果显示,1年、3年和5年的AUC值分别为0.78、0.83和0.85,并且高、低风险组间的K-M生存分析结果具有显著差异(P<0.05)。GSEA功能富集分析显示,抗原受体介导的信号传导途径、B淋巴细胞活化以及阳性T淋巴细胞选择在高风险组中富集。GO与KEGG富集分析发现,不同风险组中肿瘤相关通路在呈现差异。在3种铜死亡相关的lncRNAs细胞系中验证了预后模型中的铜死亡相关的lncRNAs表达水平。结论:铜死亡相关lncRNA与OS患者预后密切相关;基于铜死亡相关的lncRNAs构建的预后模型能够准确预测OS患者的预后,进一步深入研究铜死亡相关的lncRNAs在OS中的作用可能有助于开发更可靠的个性化治疗方案。

Objective:To identify cuproptosis-related lncRNAs(CRLs)and use them to construct models to pre-dict survival in osteosarcoma(OS)patients.Methods:RNA-seq data of OS patients were downloaded from the TARGET database along with relevant clinical information.Cuproptosis-related gene sets were obtained from re-lated studies.(CRLs)associated with OS survival were screened using co-expression analysis as well as univari-ate Cox regression.The OS prognostic models were constructed using LASSO-Cox regression,and the model ef-ficacy was assessed by receiver operating characteristic curve(ROC)and Kaplan-Meier(KM)survival analysis.Single-sample gene set enrichment analysis(ssGSEA)was utilized to explore the relationship between CRLs model scores and signaling pathways in OS.Functional and pathway enrichment analyses were performed by Gene Ontology(GO)and Kyoto Encyclopedia of Genomes(KEGG)in OS patients of different risk groups.The level of immune cell infiltration in tumor samples from OS patients was inferred by the ESTIMATE algorithm.Reverse transcription-quantitative polymerase chain reaction(RT-qPCR)was used to verify the expression of the four CRLs in different cell lines.Results:A total of 374 lncRNAs co-expressed with 10 cuproptosis-related RNAs were identified in 85 OS patients.Based on the results of Cox regression analysis,62 CRLs associated with the prognosis of OS patients were identified.Consensus clustering analysis revealed that OS patients had two CRLs expression patterns,and there was a significant difference in the prognosis of patients with 2 CRLs ex-pression patterns.LASSO-Cox regression analysis was used to construct a prognostic model for CRLs.The t-ROC curves were used to assess the model’s efficacy,and the results showed AUC values of 0.78,0.83,and 0.85 for years 1,3,and 5,respectively,and the results of the KM survival analyses differed significantly between the high-and low-risk groups(P<0.05).GSEA functional enrichment analysis found antigen receptor-mediated sig-naling pathway,B lymphocyte activation,and positive T lymphocytes were enriched in the high-risk group.GO and KEGG enrichment analyses revealed that the tumor-related pathways were presenting differences in different risk groups.The expression levels of CRLs in prognostic models were verified in three OS cell lines.Conclu-sion:CRLs are closely associated with the prognosis of OS patients.A prognostic model constructed based on CRLs accurately predicts the prognosis of OS patients,and further in-depth study of the role of CRLs in OS may contribute to the development of more reliable and personalized therapeutic regimens.