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胃癌前病变动物模型研究现状及其评价

Summary and evaluation of animal models for precancerous gastric lesions
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摘要 胃癌前病变是胃癌二级预防的关键。构建操作简单、可控性强、稳定性高的胃癌前病变动物模型是深入研究本病发病机制,开展药物干预研究的基础和前提。本文总结、归纳了常用胃癌前病变动物模型造模方法,包括螺杆菌属感染、化学致癌剂诱导、多因素复合诱导以及基因编辑小鼠模型等,并对各种模型的特征、优缺点以及动物模型评价关键问题做简要评述,为胃癌前病变动物模型的建立和应用提供参考。 The development of precancerous lesions in the stomach marks a pivotal juncture for the secondary prevention of gastric cancer. The establishment of animal models for these precancerous conditions, characterized by simplicity of manipulation, robust controllability, and high stability, constitutes the cornerstone for advancing our understanding of the disease's etiology and for pioneering therapeutic interventions. This paper synthesizes and categorizes prevalent methodologies employed in the generation of such animal models, including Helicobacter species infection, induction by chemical carcinogens, multifactorial combination inductions, and gene-editing techniques. Additionally, it offers a concise review of the distinct features, advantages, and limitations of each model, alongside a discussion on the critical considerations for evaluating these animal models. The insights provided aim to serve as a comprehensive reference for the conceptualization and utilization of animal models in the study of precancerous gastric lesions.
作者 张泰 胡蓝烁 刘炯 王萍 王凤云 唐旭东 ZHANG Tai;HU Lanshuo;LIU Jiong;WANG Ping;WANG Fengyun;TANG Xudong(Peking University Traditional Chinese Medicine Clinical Medical School,Beijing,100091,China;Graduate College,Beijing University of Traditional Chinese Medicine;Department of Pathology,Xiyuan Hospital,China Academy of Chinese Medical Sciences;Institute of Digestive Diseases,Xiyuan Hospital,China Academy of Chinese Medical Sciences)
出处 《中国中西医结合消化杂志》 CAS 2024年第5期412-419,共8页 Chinese Journal of Integrated Traditional and Western Medicine on Digestion
基金 提升高水平中医医院临床研究和成果转化能力试点建设项目(No:XYZX0204-03) 中国中医科学院科技创新工程创新团队项目(No:CI2021B005) 国家中医药管理局国家中医药传承与创新团队项目(No:ZYYCXTD-C-202010)。
关键词 胃癌前病变 动物模型 模型评价 precancerous gastric lesions animal models model evaluation
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