Zhu Minghui, Xu Zhiwen, Wang Kunhao, Wang Ning, Li Yang
College of Computer Science and Technology, Jilin University, Changchun, Jilin 130012, P.R. China ; Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, Changchun, Jilin 130012, P.R. China.
Oncol Lett. 2013 Oct;6(4):1133-1139. doi: 10.3892/ol.2013.1521. Epub 2013 Aug 9.
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.
迄今为止，科学家们已经获得了大量关于胰腺癌（PC）中基因和微小RNA（miRNA）的知识。然而，解读这些基因和miRNA的调控机制仍然困难重重。在本研究中，构建了由差异表达网络、相关网络和全局网络组成的三个调控网络，以识别PC中的机制以及某些关键的miRNA和基因通路。研究了转录因子（TF）与miRNA、miRNA与靶基因以及miRNA与其宿主基因之间的相互作用。本研究对这三个网络之间的异同进行了比较和分析，以区分关键通路。某些涉及差异表达基因和miRNA的通路表现出特定特征。观察到TP53和hsa-miR-125b形成了一种自适应关联。还获得了另外16个显著差异表达的miRNA，并且观察到一个miRNA与其宿主基因在PC中呈现出特定特征，例如，hsa-miR-196a-1及其宿主基因HOXB7形成了一种自适应关联。差异表达网络部分阐明了PC的机制。本研究提供了与PC相关的全面数据，可能有助于未来的研究获得有关PC的相关数据结果。未来，通过增加对该疾病的发生、机制、改善、转移和治疗的了解，可能会对PC有更深入的认识。
