Wang Kunhao, Xu Zhiwen, Wang Ning, Xu Ting, Zhu Minghui
Department of Computer Science and Technology, Jilin University, Changchun, Jilin 130012, P.R. China ; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, P.R. China ; Department of Economics, Changchun University, Changchun, Jilin 130022, P.R. China.
Department of Computer Science and Technology, Jilin University, Changchun, Jilin 130012, P.R. China ; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130012, P.R. China.
Oncol Lett. 2014 Nov;8(5):2225-2232. doi: 10.3892/ol.2014.2438. Epub 2014 Aug 12.
Molecular biologists have collected considerable data regarding the involvement of genes and microRNAs (miRNAs) in cancer. However the underlying mechanisms of cancer with regard to genes and miRNAs remain unclear. The aim of the present study was to evaluate diffuse large B-cell lymphoma (DLBCL) and construct regulatory networks of genes and miRNAs to gradually reveal the underlying mechanisms of DLBCL development. The first differential expression network that is presented is an experimentally validated network of miRNAs and genes. This network presents known biological regulatory associations among miRNAs and genes in the human body. The second network is a DLBCL differential expression network. Differentially expressed gene and miRNA data regarding DLBCL were collected and, based on the first network and the differentially expressed data, the second network was inferred, which demonstrates the irregular regulatory associations that may lead to the occurrence of DLBCL. The third network is a DLBCL-associated network. This network is comprised of non-differentially expressed genes and miRNAs that contribute to numerous DLBCL processes. The similarities and differences among the three networks were extracted and compared to distinguish key regulatory associations; furthermore, important signaling pathways in DLBCL were identified. The present study partially clarified the pathogenesis of DLBCL and provided an improved understanding of the underlying molecular mechanisms, as well as a potential treatment for DLBCL.
分子生物学家已经收集了大量有关基因和微小RNA（miRNA）参与癌症的相关数据。然而，关于基因和miRNA在癌症发生发展中的潜在机制仍不清楚。本研究旨在评估弥漫性大B细胞淋巴瘤（DLBCL），构建基因和miRNA调控网络，逐步揭示DLBCL发生发展的潜在机制。首先呈现的差异表达网络是一个经过实验验证的miRNA和基因网络。该网络展示了人体中miRNA和基因之间已知的生物调控关联。第二个网络是DLBCL差异表达网络。收集了有关DLBCL的差异表达基因和miRNA数据，并基于第一个网络和差异表达数据推断出第二个网络，该网络展示了可能导致DLBCL发生的异常调控关联。第三个网络是DLBCL相关网络。该网络由非差异表达的基因和miRNA组成，它们参与众多DLBCL相关过程。提取并比较了这三个网络之间的异同，以区分关键调控关联；此外，还确定了DLBCL中的重要信号通路。本研究部分阐明了DLBCL的发病机制，增进了对潜在分子机制的理解，并为DLBCL提供了潜在的治疗方法。
