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与T2哮喘相关的lncRNA介导的竞争性内源性RNA网络的构建

Construction of lncRNA-Mediated Competing Endogenous RNA Networks Correlated With T2 Asthma.

作者信息

Wang Zihan, Zhang Jintao, Feng Tao, Zhang Dong, Pan Yun, Liu Xiaofei, Xu Jiawei, Qiao Xinrui, Cui Wenjing, Dong Liang

机构信息

Department of Respiratory, Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.

Department of Respiratory Medicine, Shengli Oilfield Central Hospital, Dongying, China.

出版信息

Front Genet. 2022 Apr 11;13:872499. doi: 10.3389/fgene.2022.872499. eCollection 2022.

Abstract

Precise classification has been reported as a central challenge in the clinical research on diagnosis and prediction of treatment efficacy in asthma. In this study, the aim was to investigate the underlying competing endogenous RNA network mechanism of asthma, especially T2 asthma, as well as to find more diagnostic biomarkers and effective therapeutic targets. Multiple sets of T2 asthma airway biopsy transcription profiles were collected, which involved long non-coding RNA (lncRNA), mRNA, and microRNA (miRNA). DIANA-LncBase, targetscan, mirwalk, and miRDB databases were employed to predict interactions between lncRNAs, miRNAs and target mRNAs. To identify mRNAs correlated with T2 asthma, differential expression and network analyses were conducted through weighted gene co-expression network analysis (WGCNA). Subsequently, the expressions of potential biomarkers were examined through qRT-PCR analysis in the T2 asthma coreinteracting cellular factor (IL-13/IL-33) induced experimental model. Lastly, the ceRNA network was confirmed by plasmid transfection and RNAi experiments in a 16HBE cell line. 30 lncRNAs, 22 miRNAs and 202 mRNAs were differentially expressed in airway biopsies from T2 asthma patients. As indicated by the ROC analysis, the lncRNA, PCAT19, had high diagnostic accuracy (AUC >0.9) in distinguishing T2 asthma patients from non-T2 asthma patients and healthy controls. Furthermore, a competing ceRNA network was established, consisting of 13 lncRNAs, 12 miRNAs, as well as eight mRNAs. The reliability of this network was verified by testing several representative interactions in the network. To the best of our knowledge, this study has been the first to establish an lncRNA-mediated ceRNA regulatory network for studying T2 asthma. The findings of this study may elucidate the pathogenesis and help find potential therapeutic targets for T2 asthma. In T2 asthma, -dominated ceRNA regulation networks may play a critical role, and may serve as a potential immune-related biomarker for asthma and other respiratory diseases correlated with eosinophilic inflammation.

摘要

精确分类已被报道为哮喘诊断和治疗疗效预测临床研究中的核心挑战。本研究旨在探讨哮喘,尤其是2型哮喘潜在的竞争性内源性RNA网络机制,并寻找更多诊断生物标志物和有效的治疗靶点。收集了多组2型哮喘气道活检转录谱,其中包括长链非编码RNA(lncRNA)、信使核糖核酸(mRNA)和微小核糖核酸(miRNA)。利用DIANA-LncBase、targetscan、mirwalk和miRDB数据库预测lncRNAs、miRNAs与靶标mRNAs之间的相互作用。为了鉴定与2型哮喘相关的mRNAs,通过加权基因共表达网络分析(WGCNA)进行差异表达和网络分析。随后,在2型哮喘核心相互作用细胞因子(IL-13/IL-33)诱导的实验模型中,通过qRT-PCR分析检测潜在生物标志物的表达。最后,通过质粒转染和RNA干扰实验在16HBE细胞系中证实了ceRNA网络。在2型哮喘患者的气道活检中,有30个lncRNAs、22个miRNAs和202个mRNAs差异表达。ROC分析表明,lncRNA PCAT19在区分2型哮喘患者与非2型哮喘患者及健康对照方面具有较高的诊断准确性(AUC>0.9)。此外,还建立了一个竞争性ceRNA网络,由13个lncRNAs、12个miRNAs和8个mRNAs组成。通过测试网络中的几个代表性相互作用,验证了该网络的可靠性。据我们所知,本研究首次建立了lncRNA介导的ceRNA调控网络用于研究2型哮喘。本研究结果可能阐明其发病机制,并有助于找到2型哮喘的潜在治疗靶点。在2型哮喘中,以……为主的ceRNA调控网络可能起关键作用,并且可能作为哮喘和其他与嗜酸性粒细胞炎症相关的呼吸系统疾病的潜在免疫相关生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f43/9035528/4786034eef39/fgene-13-872499-g001.jpg

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