背景：肺腺癌（LUAD）是全球发生率最高的肺癌，死亡率不断增加。它属于非小细胞肺癌（NSCLC）类型，与先前吸烟史有很强的关联。越来越多的证据表明，腺苷酸-肌醇转换RNA编辑（ATIRE）失调在癌症中的重要性。本研究旨在评估可能具有临床用途或肿瘤生成作用的ATIRE事件。 方法：为了探索与 LUAD 生存相关的 ATIRE 事件，我们从癌症基因组图谱（TCGA）和 synapse 数据库中下载其 ATIRE 概况、基因表达数据和对应患者的临床信息。我们在 TCGA 数据库中评估了 440 名 LUAD 患者的 10441 个 ATIRE。将 ATIRE 概况与 TCGA 生存数据合并。我们使用单因素 Cox 分析（p < 0.001）选择预后 ATIRE 位点。使用 Cox 比例风险回归和 Lasso 回归分析，确定与生存相关的 ATIRE 位点，为这些位点创建风险评分，并构建评估总生存期（OS）的预后模型和诊断表。预后模型构建使用了六个 ATIRE 位点，并将患者随机分为验证队列（n = 176）和训练队列（n = 264）。使用 “Pheatmap” 程序创建包括风险评分、生存时间和 ATIRE 位点表达的风险曲线。我们还确定了临床预测模型的区分能力。同时使用决策曲线分析和 1、2、3 年的校正曲线来评估诊断表。我们还评估了 ATIRE 位点数量与宿主基因表达之间的关系，以及 ATIRE 表达对转录组表达的影响。 结果：在预后模型构建中，使用了 pyroglutamyl-peptidase I（PGPEP1）chr19:18476416A > I、ankyrin repeat domain 36B pseudogene 1（ANKRD36BP1）（距离=3,795）、T-box 转录因子（TBX19）（距离=29815）chr1：168220463A>I、syntrophin beta 2（SNTB2）chr16:69338598A > I、hook 微管连接蛋白 3（HOOK3）chr8:42883441A > I、NADH 氧化酶黄素蛋白 3（NDUFV3）chr21:44329452A > I 和 FK506 结合蛋白 11（FKBP11）chr12:49316769A > I。高风险评分水平与较差的 OS 和无进展生存率显著相关。肿瘤分期和风险评分与 LUAD 患者的 OS 相关。预测因子包括预后诊断表模型的风险评分、年龄、性别和肿瘤分期。校准图和 C-index（0.718）显示，诊断表的预测具有显著准确性。ATIRE 水平在肿瘤组织中明显升高，在患者之间高度变异。 结论：与 LUAD 有关的 ATIRE 事件具有很高的功能和临床相关性。RNA 编辑基础模型为进一步研究非编码区域的 RNA 编辑功能提供了坚实的框架，并可用作预测 LUAD 存活的独特方法。版权所有©2023年Shi、Chen、Wang、Guo、He 和 Chen。

Background: Lung adenocarcinoma (LUAD) is the most frequently occurring lung cancer worldwide, with increasing death rates. It belongs to the non-small cell lung cancer (NSCLC) type and has a strong association with previous smoking history. Growing evidence has demonstrated the significance of adenosine-to-inosine RNA editing (ATIRE) dysregulation in cancer. The aim of the present study was to evaluate ATIRE events that might be clinically useful or tumorigenic. Methods: To explore survival-related ATIRE events in LUAD, its ATIRE profiles, gene expression data, and corresponding patients' clinical information were downloaded from the Cancer Genome Atlas (TCGA) and the synapse database. We evaluated 10441 ATIRE in 440 LUAD patients from the TCGA database. ATIRE profiles were merged with TCGA survival data. We selected prognostic ATIRE sites, using a univariate Cox analysis (p < 0.001). Cox proportional hazards regression and lasso regression analysis were used to determine survival-related ATIRE sites, create risk ratings for those sites, and build a prognostic model and a nomogram for assessing overall survival (OS). Six ATIRE sites were used in the prognostic model construction and patients were randomly divided into a validation cohort (n = 176) and a training cohort (n = 264). The "Pheatmap" program was used to create risk curves that included risk score, survival time, and expression of ATIRE sites. We also determined the clinical prediction model's discrimination. The decision curve analysis and the 1-, 2-, and 3-year corrective curves were simultaneously used to evaluate the nomogram. We also evaluated the relationship between the amount of ATIRE sites and host gene expression and the impact of ATIRE expression on transcriptome expression. Results: The pyroglutamyl-peptidase I (PGPEP1) chr19:18476416A > I, ankyrin repeat domain 36B pseudogene 1 (ANKRD36BP1) (dist = 3,795), T-box transcription factor (TBX19) (dist = 29815) chr1:168220463A > I, Syntrophin Beta 2 (SNTB2) chr16:69338598A > I, hook microtubule-tethering protein 3 (HOOK3) chr8:42883441A > I, NADH dehydrogenase flavoprotein 3 (NDUFV3) chr21:44329452A > I, and FK506-binding protein 11 (FKBP11) chr12:49316769A > I were used in the prognostic model construction. High levels of risk score were significantly associated with worse OS and progression-free survival. Tumour stage and risk score were related to OS in LUAD patients. The predictors were among the prognostic nomogram model's risk score, age, gender, and tumor stage. The calibration plot and C-index (0.718) demonstrated the significant accuracy of nomogram's predictions. ATIRE level was markedly elevated in tumor tissues and was highly variable between patients. Conclusion: Events involving ATIRE in LUAD were highly functional and clinically relevant. The RNA editing-based model provides a solid framework for further investigation of the functions of RNA editing in non-coding areas and may be used as a unique method for predicting LUAD survival.Copyright © 2023 Shi, Chen, Wang, Guo, He and Chen.