Yao Ninghua, Zuo Ling, Yan Xiaodi, Qian Jing, Sun Jie, Xu Huawei, Zheng Feifei, Efird Jimmy T, Kawagoe Izumi, Wang Yan, Ni Sujie
Department of Cancer Center, Affiliated Hospital of Nantong University, Nantong, China.
Department of Oncology, Nantong University, Nantong, China.
Transl Lung Cancer Res. 2022 Apr;11(4):632-646. doi: 10.21037/tlcr-22-224.
Ferroptosis is a novel iron-dependent cell death, and an increasing number of studies have shown that long non-coding RNA (lncRNAs) are involved in the ferroptosis process. However, studies on ferroptosis-related lncRNAs in lung squamous cell carcinoma (LUSC) are limited. In addition, the prognostic role of ferroptosis-related lncRNAs and their relationship with the immune microenvironment and methylation of LUSC is unclear. This study aimed to investigate the potential prognostic value of ferroptosis-related lncRNAs and their involved biological functions in LUSC.
The Cancer Genome Atlas (TCGA) database and the FerrDb website were used to obtain ferroptosis-related genes for LUSC. The "limma" R package and Pearson analysis were used to find ferroptosis-related lncRNAs. The biological functions of the characterized lncRNAs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We evaluated the prognostic power of this model using Kaplan-Meier analysis, receiver operating characteristic (ROC), and decision curve analysis (DCA). Univariate and multifactor Cox (proportional-hazards) risk model and a nomogram were produced using risk models and clinicopathological parameters for further verification. In addition, the relationship between characterized lncRNAs and tumor immune infiltration and methylation was also discussed.
We identified 29 characterized lncRNAs to produce prognostic risk models. Kaplan-Meier analysis revealed the high-risk group was associated with poor prognosis in LUSC (P<0.001), and ROC (AUC =0.658) and DCA suggested that risk models could predict prognosis. Univariate and multifactorial Cox as well as nomogram further validated the prognostic model (P<0.001). Gene set enrichment analysis (GSEA) showed that the high-risk group was associated with pro-tumor pathways and high-frequency mutations in TP53 were present in both groups. Single sample gene set enrichment analysis (ssGSEA) showed significant differences in immune cell infiltration subtypes and corresponding functions between the two groups. Some immune checkpoint and methylation-related genes were significantly different between the two groups (P<0.05).
We investigated the potential mechanisms of LUSC development from the perspective of ferroptosis-related lncRNAs, providing new insights into LUSC research, and identified 29 lncRNAs as biomarkers to predict the prognosis of LUSC patients.
铁死亡是一种新型的铁依赖性细胞死亡，越来越多的研究表明长链非编码RNA（lncRNAs）参与了铁死亡过程。然而，关于肺鳞状细胞癌（LUSC）中铁死亡相关lncRNAs的研究有限。此外，铁死亡相关lncRNAs的预后作用及其与LUSC免疫微环境和甲基化的关系尚不清楚。本研究旨在探讨铁死亡相关lncRNAs在LUSC中的潜在预后价值及其涉及的生物学功能。
利用癌症基因组图谱（TCGA）数据库和FerrDb网站获取LUSC的铁死亡相关基因。使用“limma”R包和Pearson分析来寻找铁死亡相关lncRNAs。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析所鉴定lncRNAs的生物学功能。我们使用Kaplan-Meier分析、受试者工作特征（ROC）和决策曲线分析（DCA）评估该模型的预后能力。使用风险模型和临床病理参数构建单因素和多因素Cox（比例风险）风险模型和列线图进行进一步验证。此外，还讨论了所鉴定lncRNAs与肿瘤免疫浸润和甲基化之间的关系。
我们鉴定出29个特征性lncRNAs以构建预后风险模型。Kaplan-Meier分析显示，高危组与LUSC的预后不良相关（P<0.001），ROC（AUC =0.658）和DCA表明风险模型可以预测预后。单因素和多因素Cox分析以及列线图进一步验证了预后模型（P<0.001）。基因集富集分析（GSEA）表明，高危组与促肿瘤通路相关，两组均存在TP53高频突变。单样本基因集富集分析（ssGSEA）显示两组之间免疫细胞浸润亚型和相应功能存在显著差异。两组之间一些免疫检查点和甲基化相关基因存在显著差异（P<0.05）。
我们从铁死亡相关lncRNAs的角度研究了LUSC发生发展的潜在机制，为LUSC研究提供了新的见解，并鉴定出29个lncRNAs作为预测LUSC患者预后的生物标志物。
