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利用整合生物信息学研究构建复发性植入失败发病机制中的 circRNA-miRNA-mRNA 网络。

Construction of circRNA-miRNA-mRNA network in the pathogenesis of recurrent implantation failure using integrated bioinformatics study.

机构信息

Student Research Committee, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.

Department of Medical Genetics, Faculty of Medicine, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.

出版信息

J Cell Mol Med. 2022 Mar;26(6):1853-1864. doi: 10.1111/jcmm.16586. Epub 2021 May 7.

Abstract

This research attempted to elucidate the molecular components are involved in the pathogenesis of recurrent implantation failure (RIF). We initially identified that 386 mRNAs, 144 miRNAs and 2548 circRNAs were differentially expressed (DE) in RIF and then investigated the genetic cause of the observed abnormal expression by constructing a circRNA-miRNA-mRNA network considering the competing endogenous RNA theory. We further analysed the upstream transcription factors and related kinases of DEmRNAs (DEMs) and demonstrated that SUZ12, AR, TP63, NANOG, and TCF3 were the top five TFs binding to these DEMs. Besides, protein-protein interaction analysis disclosed that ACTB, CXCL10, PTGS2, CXCL12, GNG4, AGT, CXCL11, SST, PENK, and FOXM1 were the top 10 hub genes in the acquired network. Finally, we performed the functional enrichment analysis and found that arrhythmogenic right ventricular cardiomyopathy (ARVC), hypertrophic cardiomyopathy (HCM), pathways in cancer, TNF signalling pathway and steroid hormone biosynthesis were the potentially disrupted pathways in RIF patients. Optimistically, our findings may deepen our apprehensions about the underlying molecular and biological causes of RIF and provide vital clues for future laboratory and clinical experiments that will ultimately bring a better outcome for patients with RIF.

摘要

这项研究试图阐明与复发性植入失败(RIF)发病机制相关的分子成分。我们最初确定了 386 个 mRNAs、144 个 miRNAs 和 2548 个 circRNAs 在 RIF 中存在差异表达(DE),然后通过构建一个基于竞争内源性 RNA 理论的 circRNA-miRNA-mRNA 网络,研究观察到的异常表达的遗传原因。我们进一步分析了 DEMs 的上游转录因子和相关激酶,结果表明 SUZ12、AR、TP63、NANOG 和 TCF3 是与这些 DEMs 结合的前五个 TF。此外,蛋白质-蛋白质相互作用分析揭示了 ACTB、CXCL10、PTGS2、CXCL12、GNG4、AGT、CXCL11、SST、PENK 和 FOXM1 是获得网络中的前 10 个枢纽基因。最后,我们进行了功能富集分析,发现心律失常性右心室心肌病(ARVC)、肥厚型心肌病(HCM)、癌症途径、TNF 信号通路和类固醇激素生物合成是 RIF 患者中可能受到干扰的途径。乐观地说,我们的研究结果可能加深我们对 RIF 潜在分子和生物学原因的理解,并为未来的实验室和临床实验提供重要线索,最终为 RIF 患者带来更好的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dfb/8918409/b24f4d024d6a/JCMM-26-1853-g004.jpg

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