Ferroptosis is closely linked to various cancers, including lung adenocarcinoma (LUAD); however, the factors involved in the regulation of ferroptosis-related genes are not well established. In this study, we identified and characterized ferroptosis-related long noncoding RNAs (lncRNAs) in LUAD. In particular, a coexpression network of ferroptosis-related mRNAs and lncRNAs from The Cancer Genome Atlas (TCGA) was constructed. Univariate and multivariate Cox proportional hazards analyses were performed to establish a prognostic ferroptosis-related lncRNA signature (FerRLSig). We obtained a prognostic risk model consisting of 10 ferroptosis-related lncRNAs: AL606489.1, AC106047.1, LINC02081, AC090559.1, AC026355.1, FAM83A-AS1, AL034397.3, AC092171.5, AC010980.2, and AC123595.1. High risk scores according to the FerRLSig were significantly associated with poor overall survival (hazard ratio (HR) = 1.412, 95% CI = 1.271–1.568; P < 0.001). Receiver operating characteristic (ROC) curves and a principal component analysis further supported the accuracy of the model. Next, a prognostic nomogram combining FerRLSig with clinical features was established and showed favorable predictive efficacy for survival risk stratification. In addition, gene set enrichment analysis (GSEA) revealed that FerRLSig is involved in many malignancy-associated immunoregulatory pathways. Based on the risk model, we found that the immune status and response to immunotherapy, chemotherapy, and targeted therapy differed significantly between the high-risk and low-risk groups. These results offer novel insights into the pathogenesis of LUAD, including the contribution of ferroptosis-related lncRNAs, and reveal a prognostic indicator with the potential to inform immunological research and treatment.

铁死亡与多种癌症密切相关，包括肺腺癌（LUAD）；然而，参与调控铁死亡相关基因的因素尚未确定。在这项研究中，我们鉴定并表征了 LUAD 中与铁死亡相关的长链非编码 RNA (lncRNA)。特别是，构建了来自癌症基因组图谱 (TCGA) 的铁死亡相关 mRNA 和 lncRNA 的共表达网络。进行单变量和多变量 Cox 比例风险分析以建立预后铁死亡相关的 lncRNA 特征 (FerRLSig)。我们获得了一个由 10 种铁死亡相关的 lncRNA 组成的预后风险模型：AL606489.1、AC106047.1、LINC02081、AC090559.1、AC026355.1、FAM83A-AS1、AL034397.3、AC10105.3、AC10205.5 .1.磷 < 0.001)。接受者操作特征 (ROC) 曲线和主成分分析进一步支持模型的准确性。接下来，建立了结合 FerRLSig 与临床特征的预后列线图，并显示出对生存风险分层的良好预测功效。此外，基因集富集分析 (GSEA) 显示 FerRLSig 参与许多恶性肿瘤相关的免疫调节途径。基于风险模型，我们发现高危组和低危组之间的免疫状态和对免疫治疗、化疗和靶向治疗的反应存在显着差异。这些结果为 LUAD 的发病机制提供了新的见解，包括与铁死亡相关的 lncRNA 的贡献，并揭示了一个有可能为免疫学研究和治疗提供信息的预后指标。