Department of Physics, Alzahra University, Tehran, Iran.
School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
Sci Rep. 2024 Aug 12;14(1):18666. doi: 10.1038/s41598-024-69705-9.
Brain cancer is one of the deadliest diseases, although many efforts have been made to treat it, there is no comprehensive and effective treatment approach yet. In recent years, the use of network-based analysis to identify important biological genes and pathways involved in various complex diseases, including brain cancer, has attracted the attention of researchers. The goal of this manuscript is to perform a comprehensive analysis of the various results presented related to brain cancer. For this purpose, firstly, based on the CORMINE medical database, collected all the genes related to brain cancer with a valid P-value. Then the structural and functional relationships between the above gene sets have been identified based on the STRING database. Next, in the PPI network, hub centrality analysis was performed to determine the proteins that have many connections with other proteins. After the modularization of the network, the module with the most hub vertices is considered as the most relevant module to the formation and progression of brain cancer. Since the driver vertices play an important role in biological systems, the edges of the selected module were oriented, and by analyzing the controllability of complex networks, a set of five proteins with the highest control power has been identified. Finally, based on the drug-gene interaction, a set of drugs effective on each of the driver genes has been obtained, which can potentially be used as new combination drugs. Validation of the hub and driver proteins shows that they are mainly essential proteins in the biological processes related to the various cancers and therefore the drugs that affect them can be considered as new combination therapy. The presented procedure can be used for any other complex disease.
脑癌是最致命的疾病之一，尽管已经做出了许多努力来治疗它，但目前还没有全面有效的治疗方法。近年来，利用基于网络的分析方法来识别涉及各种复杂疾病（包括脑癌）的重要生物基因和途径，引起了研究人员的关注。本文的目的是对与脑癌相关的各种结果进行全面分析。为此，首先基于 CORMINE 医学数据库，收集了所有具有有效 P 值的与脑癌相关的基因。然后，基于 STRING 数据库，识别了上述基因集之间的结构和功能关系。接下来，在 PPI 网络中，进行了枢纽中心度分析，以确定与其他蛋白质有许多连接的蛋白质。在网络模块化之后，将具有最多枢纽顶点的模块视为与脑癌的形成和进展最相关的模块。由于驱动顶点在生物系统中起着重要作用，因此选择模块的边缘被定向，并且通过分析复杂网络的可控性，确定了一组具有最高控制能力的五个蛋白质。最后，基于药物-基因相互作用，获得了针对每个驱动基因的一组有效药物，这些药物可能被用作新的联合药物。枢纽和驱动蛋白的验证表明，它们主要是与各种癌症相关的生物过程中的必需蛋白，因此，影响它们的药物可以被认为是新的联合治疗方法。所提出的程序可用于任何其他复杂疾病。
