Chen Mei, Nie Zhenyu, Li Yan, Gao Yuanhui, Wen Xiaohong, Cao Hui, Zhang Shufang
Central Laboratory, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, China.
Front Cell Dev Biol. 2021 Nov 16;9:699804. doi: 10.3389/fcell.2021.699804. eCollection 2021.
Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients. We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed. We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel. The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.
铁死亡与癌症的发生和发展密切相关。越来越多的研究已将诱导铁死亡作为一种癌症治疗策略。然而,铁死亡相关长链非编码RNA(lncRNA)在膀胱癌(BC)中的预测价值仍有待进一步阐明。本研究的目的是构建一种基于铁死亡相关lncRNA的预测标志物,以预测BC患者的预后。我们从癌症基因组图谱(TCGA)数据库下载了RNA测序数据以及相应的临床和预后数据,并进行单因素和多因素Cox回归分析,以获得铁死亡相关lncRNA来构建预测标志物。采用Kaplan-Meier方法分析高风险组和低风险组的总生存率(OS)。进行基因集富集分析(GSEA)以探索高风险组和低风险组之间的功能差异。采用单样本基因集富集分析(ssGSEA)来探索预测标志物与免疫状态之间的关系。最后,分析预测标志物与BC患者治疗反应之间的相关性。我们构建了一个由9个铁死亡相关lncRNA组成的标志物(AL031775.1、AL162586.1、AC034236.2、LINC01004、OCIAD1-AS1、AL136084.3、AP003352.1、Z84484.1、AC022150.2)。与低风险组相比,高风险组的预后更差。铁死亡相关lncRNA标志物能够独立预测BC患者的预后。与临床病理变量相比,铁死亡相关lncRNA标志物具有更高的诊断效率,受试者工作特征曲线下面积为0.707。当根据不同临床病理变量对患者进行分层时,高风险组患者的OS短于低风险组患者。GSEA显示肿瘤和免疫相关通路主要在高风险组中富集。ssGSEA显示预测标志物与BC患者的免疫状态显著相关。高风险患者对抗PD-1/L1免疫疗法以及传统化疗药物舒尼替尼、紫杉醇、顺铂和多西他赛更敏感。该预测标志物能够独立预测BC患者的预后,为铁死亡相关lncRNA在BC中的作用机制提供了依据,并为BC患者提供临床治疗指导。