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跨癌症类型探索预后相关的 microRNA 和转录因子协同调控网络。

Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types.

机构信息

a Department of Biotechnology , Beijing Institute of Radiation Medicine , Beijing , P.R.China.

出版信息

RNA Biol. 2019 Aug;16(8):1010-1021. doi: 10.1080/15476286.2019.1607714. Epub 2019 May 3.

Abstract

The study of cancer prognosis serves as an important part of cancer research. Large-scale cancer studies have identified numerous genes and microRNAs (miRNAs) associated with prognosis. These informative genes and miRNAs represent potential biomarkers to predict survival and to elucidate the molecular mechanism of tumour progression. MiRNAs and transcription factors (TFs) can work cooperatively as essential mediators of gene expression, and their dysregulation affects cancer prognosis. A panoramic view of cancer prognosis at the system level, considering the co-regulation roles of miRNA and TF, remains elusive. Here, we establish 12 prognosis-related miRNA-TF co-regulatory networks. The characteristics of prognostic target genes and their regulators in the network are depicted. Although the target genes and co-regulatory patterns exhibit cancer-specific properties, some miRNAs and TFs are highly conserved across cancers. We illustrate and interpret the roles of these conserved regulators by building a model associated with cancer hallmarks, functional enrichment analysis, network community detection, and exhaustive literature research. The elaborated system-level prognostic miRNA-TF co-regulation landscape, including the highlighted roles of conserved regulators, provides a novel and powerful insights into further biological and medical discoveries.

摘要

癌症预后研究是癌症研究的重要组成部分。大规模的癌症研究已经确定了许多与预后相关的基因和 microRNAs(miRNAs)。这些有信息的基因和 miRNAs 代表了潜在的生物标志物,可以预测生存并阐明肿瘤进展的分子机制。miRNAs 和转录因子(TFs)可以作为基因表达的重要调节剂协同工作,它们的失调会影响癌症的预后。考虑到 miRNA 和 TF 的共同调节作用,在系统水平上对癌症预后进行全景式观察仍然难以实现。在这里,我们建立了 12 个与预后相关的 miRNA-TF 共同调节网络。描绘了网络中预后靶基因及其调节剂的特征。尽管靶基因和共同调节模式表现出癌症特异性,但一些 miRNAs 和 TFs 在癌症之间是高度保守的。我们通过构建与癌症特征相关的模型、功能富集分析、网络社区检测和详尽的文献研究,说明了并解释了这些保守调节剂的作用。详细阐述的系统水平预后 miRNA-TF 共同调节景观,包括保守调节剂的突出作用,为进一步的生物学和医学发现提供了新的有力见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c0e/6602415/0970f246d3ce/krnb-16-08-1607714-g001.jpg

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