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microRNA and gene networks in human pancreatic cancer

机译：人类胰腺癌中的microRNA和基因网络

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摘要

To date, scientists have obtained a substantial amount of knowledge with regard to genes and microRNAs (miRNAs) in pancreatic cancer (PC). However, deciphering the regulatory mechanism of these genes and miRNAs remains difficult. In the present study, three regulatory networks consisting of a differentially-expressed network, a related network and a global network, were constructed in order to identify the mechanisms and certain key miRNA and gene pathways in PC. The interactions between transcription factors (TFs) and miRNAs, miRNAs and target genes and an miRNA and its host gene were investigated. The present study compared and analyzed the similarities and differences between the three networks in order to distinguish the key pathways. Certain pathways involving the differentially-expressed genes and miRNAs demonstrated specific features. TP53 and hsa-miR-125b were observed to form a self-adaptation association. A further 16 significant differentially-expressed miRNAs were obtained and it was observed that an miRNA and its host gene exhibit specific features in PC, for example, hsa-miR-196a-1 and its host gene, HOXB7, form a self-adaptation association. The differentially-expressed network partially illuminated the mechanism of PC. The present study provides comprehensive data that is associated with PC and may aid future studies in obtaining pertinent data results with regards to PC. In the future, an improved understanding of PC may be obtained through an increased knowledge of the occurrence, mechanism, improvement, metastasis and treatment of the disease.
机译：迄今为止，科学家已经获得了有关胰腺癌（PC）中的基因和microRNA（miRNA）的大量知识。但是，破译这些基因和miRNA的调控机制仍然很困难。在本研究中，构建了由差异表达网络，相关网络和全球网络组成的三个调控网络，以鉴定PC中的机制以及某些关键的miRNA和基因途径。研究了转录因子（TFs）与miRNA，miRNA与靶基因以及miRNA及其宿主基因之间的相互作用。本研究比较并分析了三个网络之间的异同，以区分关键路径。涉及差异表达基因和miRNA的某些途径表现出特定特征。观察到TP53和hsa-miR-125b形成了自我适应协会。获得了另外16个显着差异表达的miRNA，并且观察到miRNA及其宿主基因在PC中表现出特定特征，例如hsa-miR-196a-1及其宿主基因HOXB7形成了自我适应性关联。差异表达的网络部分阐明了PC的机制。本研究提供了与PC相关的综合数据，可以帮助将来的研究获得有关PC的相关数据结果。将来，可以通过对疾病的发生，机制，改善，转移和治疗的了解增加对PC的了解。

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