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2025, 12, v.66 1217-1221+1256
基于伏邪理论探析休眠癌细胞的形成、激活、消亡机制及中医干预策略
基金项目(Foundation): 国家自然科学基金(82074402,82274608); 中央高水平中医医院临床研究和成果转化能力提升项目(HLCMHPP2023085,HLCMHPP2023001,HLCMHPP2023097); 中国中医科学院科技创新工程(CI2023C012YL); 北京市科技计划课题(Z221100003522021); 国家资助博士后研究人员计划(GZC20233128)
邮箱(Email): qfm2020jieli@yeah.net;
DOI: 10.13288/j.11-2166/r.2025.12.005
摘要:

基于休眠癌细胞“潜伏性”“伺机而发”的特点,将其归属于中医学“伏邪”范畴,并据伏邪理论探讨休眠癌细胞的形成、激活与消亡机制。认为气虚是休眠癌细胞形成、生长的关键内因,气郁为休眠癌细胞激活的诱因,气复为休眠癌细胞消亡的契机。并据伏邪理论制定干预休眠癌细胞的中医策略,一方面,通过固本培元、固护卫气、升提大气扶正之法令正气充盈,以阻止休眠癌细胞的潜伏积聚;另一方面,通过疏理肝气、温阳化气之法使气机调畅,以抑制休眠癌细胞激活并破坏其赖以生存的环境。

Abstract:

Based on the characteristics of dormant cancer cells, which are "latency" and "opportunistic activation", this paper classifies them within the scope of "latent pathogen" in traditional Chinese medicine(TCM). It explores the mechanisms of formation, activation, and elimination of dormant cancer cells based on the latent pathogen theory. It is proposed that qi deficiency is the fundamental internal cause for the formation and growth of dormant cancer cells, qi stagnation is the inducing factor for their activation, and qi restoration presents an opportunity for their elimination. Guided by the latent pathogen theory, the TCM strategy for inhibiting dormant cancer cells includes two aspects. On one hand, methods such as strengthening the root, securing defensive qi, and lifting and supporting the body's upright qi are used to reinforce healthy qi and prevent the latency and accumulation of dormant cancer cells. On the other hand, regulating liver qi and warming yang to promote qi transformation are employed to ensure smooth qi movement, thereby inhibiting the activation of dormant cancer cells and disrupting their survival environment.

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基本信息:

DOI:10.13288/j.11-2166/r.2025.12.005

中图分类号:R273

引用信息:

[1]王新苗,朱潇雨,李杰.基于伏邪理论探析休眠癌细胞的形成、激活、消亡机制及中医干预策略[J].中医杂志,2025,66(12):1217-1221+1256.DOI:10.13288/j.11-2166/r.2025.12.005.

基金信息:

国家自然科学基金(82074402,82274608); 中央高水平中医医院临床研究和成果转化能力提升项目(HLCMHPP2023085,HLCMHPP2023001,HLCMHPP2023097); 中国中医科学院科技创新工程(CI2023C012YL); 北京市科技计划课题(Z221100003522021); 国家资助博士后研究人员计划(GZC20233128)

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