Abstract:

Lung cancer has the highest mortality rate among malignant tumors worldwide, posing a severe threat to human health. Traditional Chinese medicine (TCM) offers unique advantages in treating lung cancer, with disease-syndrome-integrated animal models serving as a critical component of TCM lung cancer research. According to TCM pathogenesis, lung cancer is classified as a pattern of underlying deficiency with superficial excess. Clinically, it is often categorized into syndromes such as qi and yin deficiency, lung-spleen qi deficiency, lung yin deficiency, qi stagnation and blood stasis, and phlegm-heat obstructing the lungs. Treatment should fundamentally adhere to the principle of "strengthening the healthy qi and expelling pathogenic factors". This paper systematically reviews literature from 2005 to 2025 on disease-syndrome-integrated animal models for lung cancer. It summarizes the theoretical basis and establishment methods of four core disease-syndrome-integrated models: qi-yin deficiency pattern, spleen qi deficiency pattern, qi stagnation and blood stasis pattern, and kidney deficiency pattern. Further discussion covers their evaluation systems and limitations. Additionally, modeling approaches for other patterns including yang deficiency, spleen deficiency, and qi deficiency with blood stasis are summarized, with evaluation methods categorized by behavioral characteristics and biochemical indicators. Analysis reveals that current models predominantly use C57BL/6 mice, exhibiting issues such as insufficient clinical relevance, complex modeling procedures, numerous confounding factors, and a low degree of standardization. Future improvements to disease-syndrome-integrated lung cancer animal models could include using clustered regularly interspaced short palindromic repeats (CRISPR) technology to establish organoid–patient-derived xenograft models; developing controllable composite stress systems and standardized stimulus models, such as gradient-controlled alternating cold/heat chambers and programmed dietary regulation systems, to reduce nonspecific interference; and developing multidimensional dynamic modeling techniques by integrating clinical big data, including metabolomics and imaging features, to design dynamic intervention protocols, thereby providing more precise and reliable experimental tools for elucidating the mechanisms of TCM in lung cancer prevention and treatment.

Key words: Lung cancer, Disease-syndrome integration, Mouse model, Traditional Chinese medicine syndrome