School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
School of Continuation Education, Tianjin Medical University, Tianjin, China.
BMC Bioinformatics. 2019 Sep 2;20(1):449. doi: 10.1186/s12859-019-3041-9.
Hodgkin Lymphoma (HL) is a type of aggressive malignancy in lymphoma that has high incidence in young adults and elderly patients. Identification of reliable diagnostic markers and efficient therapeutic targets are especially important for the diagnosis and treatment of HL. Although many HL-related molecules have been identified, our understanding on the molecular mechanisms underlying the disease is still far from complete due to its complex and heterogeneous characteristics. In such situation, exploring the molecular mechanisms underlying HL via systems biology approaches provides a promising option. In this study, we try to elucidate the molecular mechanisms related to the disease and identify potential pharmaceutical targets from a network-based perspective.
We constructed a series of network models. Based on the analysis of these networks, we attempted to identify the biomarkers and elucidate the molecular mechanisms underlying HL. Initially, we built three different but related protein networks, i.e., background network, HL-basic network and HL-specific network. By analyzing these three networks, we investigated the connection characteristic of the HL-related proteins. Subsequently, we explored the miRNA regulation on HL-specific network and analyzed three kinds of simple regulation patterns, i.e., co-regulation of protein pairs, as well as the direct and indirect regulation of triple proteins. Finally, we constructed a simplified protein network combined with the regulation of miRNAs on proteins to better understand the relation between HL-related proteins and miRNAs.
We find that the HL-related proteins are more likely to connect with each other compared to other proteins. Moreover, the HL-specific network can be further divided into five sub-networks and 49 proteins as the backbone of HL-specific network make up and connect these 5 sub-networks. Thus, they may be closely associated with HL. In addition, we find that the co-regulation of protein pairs is the main regulatory pattern of miRNAs on the protein network in the HL-specific network. According to the regulation of miRNA on protein network, we have identified 5 core miRNAs as the potential biomarkers for diagnostic of HL. Finally, several protein pathways have been identified to closely associated with HL, which provides deep insights into underlying mechanism of HL.
霍奇金淋巴瘤（HL）是淋巴瘤中一种侵袭性恶性肿瘤，在青年人和老年患者中发病率较高。识别可靠的诊断标志物和有效的治疗靶点对于 HL 的诊断和治疗尤为重要。尽管已经鉴定出许多与 HL 相关的分子，但由于其复杂和异质性的特征，我们对疾病背后的分子机制的理解还远远不够。在这种情况下，通过系统生物学方法探索 HL 背后的分子机制提供了一个有前途的选择。在这项研究中，我们试图从网络的角度阐明与疾病相关的分子机制，并确定潜在的药物靶点。
我们构建了一系列网络模型。基于这些网络的分析，我们试图识别生物标志物并阐明 HL 背后的分子机制。首先，我们构建了三个不同但相关的蛋白质网络，即背景网络、HL 基础网络和 HL 特异性网络。通过分析这三个网络，我们研究了 HL 相关蛋白的连接特征。随后，我们探讨了 miRNA 对 HL 特异性网络的调控，并分析了三种简单的调控模式，即蛋白质对的共调控，以及三重蛋白质的直接和间接调控。最后，我们构建了一个简化的蛋白质网络，结合 miRNA 对蛋白质的调控，以更好地理解 HL 相关蛋白和 miRNA 之间的关系。
我们发现与其他蛋白相比，HL 相关蛋白更倾向于相互连接。此外，HL 特异性网络可以进一步分为五个子网络，而 49 个蛋白作为 HL 特异性网络的骨干组成并连接这 5 个子网络。因此，它们可能与 HL 密切相关。此外，我们发现蛋白质网络中 miRNA 对蛋白质的共调控是主要调控模式。根据 miRNA 对蛋白质网络的调控，我们确定了 5 个核心 miRNA 作为 HL 诊断的潜在生物标志物。最后，确定了几个与 HL 密切相关的蛋白质途径，为 HL 发病机制提供了深入的见解。
