Shi Si, Chen Shibin, Wang Menghang, Guo Bingchen, He Yaowu, Chen Hong
The Respiratory Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Medical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Front Genet. 2023 Mar 10;14:1084869. doi: 10.3389/fgene.2023.1084869. eCollection 2023.
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. 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 ( < 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 ( = 176) and a training cohort ( = 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. 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. 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.
肺腺癌(LUAD)是全球最常见的肺癌,死亡率不断上升。它属于非小细胞肺癌(NSCLC)类型,与既往吸烟史密切相关。越来越多的证据表明,腺苷到次黄苷RNA编辑(ATIRE)失调在癌症中具有重要意义。本研究的目的是评估可能具有临床实用性或致瘤性的ATIRE事件。为了探索LUAD中与生存相关的ATIRE事件,从癌症基因组图谱(TCGA)和突触数据库下载了其ATIRE图谱、基因表达数据以及相应患者的临床信息。我们评估了来自TCGA数据库的440例LUAD患者中的10441个ATIRE。将ATIRE图谱与TCGA生存数据合并。我们使用单变量Cox分析(<0.001)选择预后性ATIRE位点。使用Cox比例风险回归和套索回归分析来确定与生存相关的ATIRE位点,为这些位点创建风险评分,并构建用于评估总生存期(OS)的预后模型和列线图。在预后模型构建中使用了6个ATIRE位点,并将患者随机分为验证队列(=176)和训练队列(=264)。使用“Pheatmap”程序创建风险曲线,包括风险评分、生存时间和ATIRE位点的表达。我们还确定了临床预测模型的辨别力。同时使用决策曲线分析以及1年、2年和3年校正曲线来评估列线图。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。在预后模型构建中使用了焦谷氨酰肽酶I(PGPEP1)chr19:18476416A>I、锚蛋白重复结构域36B假基因1(ANKRD36BP1)(距离=3795)、T盒转录因子(TBX19)(距离=29815)chr1:168220463A>I、肌养蛋白β2(SNTB2)chr16:69338598A>I、钩状微管束缚蛋白3(HOOK3)chr8:42883441A>I、NADH脱氢酶黄素蛋白3(NDUFV3)chr21:44329452A>I和FK506结合蛋白11(FKBP11)chr12:49316769A>I。高风险评分与较差的OS和无进展生存期显著相关。肿瘤分期和风险评分与LUAD患者的OS相关。预测因素包括预后列线图模型的风险评分、年龄、性别和肿瘤分期。校准图和C指数(0.718)证明了列线图预测的显著准确性。肿瘤组织中ATIRE水平明显升高,且患者之间差异很大。LUAD中涉及ATIRE的事件具有高度功能性且与临床相关。基于RNA编辑的模型为进一步研究非编码区域RNA编辑的功能提供了坚实的框架,并且可作为预测LUAD生存的独特方法。