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癌症网络药理学:多网络调控机制与未来方向。

Cancer network pharmacology: multi-network regulatory mechanisms and future directions.

作者信息

Zhao Zixuan, Le Jiahan, Fu Zhenjie, Yang Shenshen, Chen Yitao

机构信息

State Key Laboratory of Chinese Medicine Modernization, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, People's Republic of China.

School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, People's Republic of China.

出版信息

Med Oncol. 2025 Jun 12;42(7):255. doi: 10.1007/s12032-025-02811-4.

DOI:10.1007/s12032-025-02811-4
PMID:40506575
Abstract

Cancer is a medical problem that has been difficult to overcome on a global scale. Owing to the sharing of single or multiple genes or regulatory modules, cancer treatment often faces severe challenges. The core of network pharmacology lies in constructing human disease gene regulation networks and multi-pharmacology network. With the continuous updating and iteration of new technologies, it is helpful for us to systematically understand the occurrence and development mechanism behind complex diseases and elucidate the pharmacological mechanisms from the perspective of biological network balance. This review aims to clarify the application of network pharmacology in exploring the pharmacological treatment mechanism of natural products, drug repositioning, and new technology combinations in the context of complex pathogenesis of cancer, so as to help realize the full potential of network pharmacology. Additionally, we discuss the future development of network pharmacology to guide clinical diagnosis and treatment.

摘要

癌症是一个在全球范围内都难以攻克的医学难题。由于单个或多个基因或调控模块的共享,癌症治疗常常面临严峻挑战。网络药理学的核心在于构建人类疾病基因调控网络和多药理学网络。随着新技术的不断更新迭代,有助于我们系统地理解复杂疾病背后的发生发展机制,并从生物网络平衡的角度阐明药理机制。本综述旨在阐明网络药理学在探索天然产物的药理治疗机制、药物重新定位以及在癌症复杂发病机制背景下的新技术组合方面的应用,以帮助实现网络药理学的全部潜力。此外,我们还讨论了网络药理学的未来发展,以指导临床诊断和治疗。

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本文引用的文献

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Predicting protein-protein interaction with interpretable bilinear attention network.使用可解释双线性注意力网络预测蛋白质-蛋白质相互作用。
Comput Methods Programs Biomed. 2025 Jun;265:108756. doi: 10.1016/j.cmpb.2025.108756. Epub 2025 Mar 30.
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NP-TCMtarget: a network pharmacology platform for exploring mechanisms of action of traditional Chinese medicine.NP-TCMtarget:一个用于探索中药作用机制的网络药理学平台。
Brief Bioinform. 2024 Nov 22;26(1). doi: 10.1093/bib/bbaf078.
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Network pharmacology: a crucial approach in traditional Chinese medicine research.
网络药理学:中医药研究的关键方法。
Chin Med. 2025 Jan 12;20(1):8. doi: 10.1186/s13020-024-01056-z.
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Protein-protein interaction detection using deep learning: A survey, comparative analysis, and experimental evaluation.使用深度学习进行蛋白质-蛋白质相互作用检测:一项综述、对比分析与实验评估
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Harnessing network pharmacology in drug discovery: an integrated approach.利用网络药理学进行药物发现:一种综合方法。
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Exploration of compatibility rules and discovery of active ingredients in TCM formulas by network pharmacology.基于网络药理学探索中药方剂的配伍规律并发现活性成分。
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