Analysis of animal models of breast cancer based on clinical symptoms of Traditional Chinese and Western Medicine
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Henan University of Chinese Medicine, Zhengzhou 450046, China

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R-33

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    Abstract:

    Objective Breast cancer is the malignant tumor with the highest incidence in women in China, which seriously affects the physical and mental health of patients. The preparation of animal models of breast cancer conforming to clinical characteristics is of great importance to the study of its pathogenesis and treatment. Methods Using “ breast cancer” and “animal model” as search terms, we searched China National Knowledge Infrastructure (CNKI),Wanfang, VIP and PubMed databases’ entries describing models of Chinese and Western Medicine clinical diagnostic criteria for breast cancer. We summarized breast cancer animal models of existing varieties, characteristics, and modeling method. Then we evaluated the consistency according to the clinical symptoms of Traditional Chinese and Western Medicine for breast cancer. Results We found that the existing animal model preparation method are relatively simple and mostly based on chemotherapy-induced cancer modeling method. Accordingly, these method ignore the etiology of Traditional Chinese Medicine and lack of combination model of Traditional Chinese Medicine disease. This result in large differences from clinical multi-factor disease observations, limiting research and clinical application of Traditional Chinese Medicine for the prevention and treatment of breast cancer. Conclusions Evaluation of breast cancer models is mainly based on pathological diagnosis and the formation of tumor strain (body), which is different from the Western and Chinese diagnostic criteria of breast cancer. Therefore, it is necessary to further improve the evaluation system of animal models of breast cancer, improve existing models, and make the basic research of Traditional Chinese Medicine more suitable for clinical practice.

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History
  • Received:November 01,2021
  • Revised:
  • Adopted:
  • Online: January 16,2023
  • Published: