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与微卫星高度不稳定相关的长链非编码RNA的基因组不稳定性在肺腺癌中的预后价值

Prognostic Value of Genomic Instability of mA-Related lncRNAs in Lung Adenocarcinoma.

作者信息

Li Rui, Li Jian-Ping, Liu Ting-Ting, Huo Chen, Yao Jie, Ji Xiu-Li, Qu Yi-Qing

机构信息

Shandong Key Laboratory of Infectious Respiratory Diseases, Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.

Department of Pulmonary Disease, Traditional Chinese Medicine Hospital of Jinan, Jinan, China.

出版信息

Front Cell Dev Biol. 2022 Mar 3;10:707405. doi: 10.3389/fcell.2022.707405. eCollection 2022.

Abstract

Genomic instability of N6-methyladenosine (mA)-related long noncoding RNAs (lncRNAs) plays a pivotal role in the tumorigenesis of lung adenocarcinoma (LUAD). Our study identified a signature of genomic instability of mA-associated lncRNA signature and revealed its prognostic role in LUAD. We downloaded RNA-sequencing data and somatic mutation data for LUAD from The Cancer Genome Atlas (TCGA) and the GSE102287 dataset from the Gene Expression Omnibus (GEO) database. The "Limma" R package was used to identify a network of regulatory mA-related lncRNAs. We used the Wilcoxon test method to identify genomic-instability-derived mA-related lncRNAs. A competing endogenous RNA (ceRNA) network was constructed to identify the mechanism of the genomic instability of mA-related lncRNAs. Univariate and multivariate Cox regression analyses were performed to construct a prognostic model for internal testing and validation of the prognostic mA-related lncRNAs using the GEO dataset. Performance analysis was conducted to compare our prognostic model with the previously published lncRNA models. The CIBERSORT algorithm was used to explore the relationship of mA-related lncRNAs and the immune microenvironment. Prognostic mA-related lncRNAs in prognosis, the tumor microenvironment, stemness scores, and anticancer drug sensitivity were analyzed to explore the role of prognostic mA-related lncRNAs in LUAD. A total of 42 genomic instability-derived mA-related lncRNAs were differentially expressed between the GS (genomic stable) and GU (genomic unstable) groups of LUAD patients. Four differentially expressed lncRNAs, 17 differentially expressed microRNAs, and 75 differentially expressed mRNAs were involved in the genomic-instability-derived mA-related lncRNA-mediated ceRNA network. A prediction model based on 17 prognostic mA-associated lncRNAs was constructed based on three TCGA datasets (all, training, and testing) and validated in the GSE102287 dataset. Performance comparison analysis showed that our prediction model (area under the curve [AUC] = 0.746) could better predict the survival of LUAD patients than the previously published lncRNA models (AUC = 0.577, AUC = 0.681). Prognostic mA-related-lncRNAs have pivotal roles in the tumor microenvironment, stemness scores, and anticancer drug sensitivity of LUAD. A signature of genomic instability of mA-associated lncRNAs to predict the survival of LUAD patients was validated. The prognostic, immune microenvironment and anticancer drug sensitivity analysis shed new light on the potential novel therapeutic targets in LUAD.

摘要

N6-甲基腺苷(m⁶A)相关长链非编码RNA(lncRNA)的基因组不稳定性在肺腺癌(LUAD)的肿瘤发生中起关键作用。我们的研究确定了m⁶A相关lncRNA基因组不稳定性特征,并揭示了其在LUAD中的预后作用。我们从癌症基因组图谱(TCGA)下载了LUAD的RNA测序数据和体细胞突变数据,并从基因表达综合数据库(GEO)下载了GSE102287数据集。使用“Limma”R包来识别调控m⁶A相关lncRNA的网络。我们使用Wilcoxon检验方法来识别基因组不稳定性衍生的m⁶A相关lncRNA。构建了一个竞争性内源性RNA(ceRNA)网络,以确定m⁶A相关lncRNA基因组不稳定性的机制。进行单变量和多变量Cox回归分析,以构建一个预后模型,用于使用GEO数据集对预后性m⁶A相关lncRNA进行内部测试和验证。进行性能分析,以将我们的预后模型与先前发表的lncRNA模型进行比较。使用CIBERSORT算法来探索m⁶A相关lncRNA与免疫微环境的关系。分析预后性m⁶A相关lncRNA在预后、肿瘤微环境、干性评分和抗癌药物敏感性方面的作用,以探讨预后性m⁶A相关lncRNA在LUAD中的作用。在LUAD患者的基因组稳定(GS)组和基因组不稳定(GU)组之间,共有42个基因组不稳定性衍生的m⁶A相关lncRNA差异表达。17个差异表达的lncRNA、4个差异表达的微小RNA和75个差异表达的mRNA参与了基因组不稳定性衍生的m⁶A相关lncRNA介导的ceRNA网络。基于三个TCGA数据集(全部、训练和测试)构建了一个基于17个预后性m⁶A相关lncRNA的预测模型,并在GSEl02287数据集中进行了验证。性能比较分析表明,我们的预测模型(曲线下面积[AUC]=0.746)比先前发表的lncRNA模型(AUC=0.577,AUC=0.681)能更好地预测LUAD患者的生存情况。预后性m⁶A相关lncRNA在LUAD的肿瘤微环境、干性评分和抗癌药物敏感性中起关键作用。验证了一个用于预测LUAD患者生存情况的m⁶A相关lncRNA基因组不稳定性特征。预后、免疫微环境和抗癌药物敏感性分析为LUAD潜在的新型治疗靶点提供了新的线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f9b/8928224/69c0f6f25ff0/fcell-10-707405-g001.jpg

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