用于预测肺腺癌预后的铁死亡相关长链非编码RNA特征的鉴定与验证
Identification and Validation of a Ferroptosis-Related Long Non-coding RNA Signature for Predicting the Outcome of Lung Adenocarcinoma.
作者信息
Zheng Zhiyuan, Zhang Qian, Wu Wei, Xue Yan, Liu Shuhan, Chen Qiaoqian, Lin Donghong
机构信息
Medical Technology and Engineering College of Fujian Medical University, Fuzhou, China.
出版信息
Front Genet. 2021 Jul 22;12:690509. doi: 10.3389/fgene.2021.690509. eCollection 2021.
BACKGROUND
Ferroptosis is a recently recognized type of programmed cell death that is involved in the biological processes of various cancers. However, the mechanism of ferroptosis in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the role of ferroptosis-associated long non-coding RNAs (lncRNAs) in LUAD and to establish a prognostic model.
METHODS
We downloaded ferroptosis-related genes from the FerrDb database and RNA sequencing data and clinicopathological characteristics from The Cancer Genome Atlas. We randomly divided the data into training and validation sets. Ferroptosis-associated lncRNA signatures with the lowest Akaike information criteria were determined using COX regression analysis and the least absolute shrinkage and selection operator. The risk scores of ferroptosis-related lncRNAs were calculated, and patients with LUAD were assigned to high- and low-risk groups based on the median risk score. The prognostic value of the risk scores was evaluated using Kaplan-Meier curves, Cox regression analyses, and nomograms. We then explored relationships between ferroptosis-related lncRNAs and the immune response using gene set enrichment analysis (GSEA).
RESULTS
Ten ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that the risk scores were independent predictors of LUAD outcome in the training and validation sets (all < 0.05). The area under the curve confirmed that the signatures could determine the prognosis of LUAD. The predictive accuracy of the established nomogram model was verified using the concordance index and calibration curve. The GSEA showed that the 10 ferroptosis-related lncRNAs might be associated with tumor immune response.
CONCLUSION
We established a novel signature involving 10 ferroptosis-related lncRNAs (LINC01843, MIR193BHG, AC091185.1, AC027031.2, AL021707.2, AL031667.3, AL606834.1, AC026355.1, AC124045.1, and AC025048.4) that can accurately predict the outcome of LUAD and are associated with the immune response. This will provide new insights into the development of new therapies for LUAD.
背景
铁死亡是一种最近被认识到的程序性细胞死亡类型，参与多种癌症的生物学过程。然而，肺腺癌（LUAD）中铁死亡的机制仍不清楚。本研究旨在确定铁死亡相关长链非编码RNA（lncRNA）在LUAD中的作用，并建立一个预后模型。
方法
我们从FerrDb数据库下载了铁死亡相关基因，从癌症基因组图谱下载了RNA测序数据和临床病理特征。我们将数据随机分为训练集和验证集。使用COX回归分析和最小绝对收缩和选择算子确定具有最低赤池信息准则的铁死亡相关lncRNA特征。计算铁死亡相关lncRNA的风险评分，并根据中位风险评分将LUAD患者分为高风险组和低风险组。使用Kaplan-Meier曲线、COX回归分析和列线图评估风险评分的预后价值。然后，我们使用基因集富集分析（GSEA）探索铁死亡相关lncRNA与免疫反应之间的关系。
结果
在训练组中鉴定出10个铁死亡相关lncRNA特征，Kaplan-Meier和COX回归分析证实，风险评分是训练集和验证集中LUAD结局的独立预测因子（均<0.05）。曲线下面积证实这些特征可以确定LUAD的预后。使用一致性指数和校准曲线验证了所建立列线图模型的预测准确性。GSEA显示，这10个铁死亡相关lncRNA可能与肿瘤免疫反应相关。
结论
我们建立了一个包含10个铁死亡相关lncRNA（LINC01843、MIR193BHG、AC091185.1、AC027031.2、AL021707.2、AL031667.3、AL606834.1、AC026355.1、AC124045.1和AC025048.4）的新特征，该特征可以准确预测LUAD的结局，并与免疫反应相关。这将为LUAD新疗法的开发提供新的见解。
Zotero 插件