Unveiling medication patterns in traditional Chinese medicine for the prevention of colorectal cancer recurrence: from potential combinations to validation of components and targets

  • Chin Med. 2026 Jun 4;21(1):160. doi: 10.1186/s13020-026-01438-5.
Qianqian Bu  #  1  2 Shaoxun Yuan  #  3  4 Xiaoman Wei  #  1  2  5  6 Junyi Wang  1  2  5 Liu Li  1  2 Pan Chen  1  2 Weixing Shen  1  2 Dongdong Sun  1  2 Lingyu Linda Ye  2  6  7  8 Yun Yang  9 Luying Xu  7 Sicheng Lu  10  11  12 Dayue Darrel Duan  13  14  15  16  17 Haibo Cheng  18  19
Affiliations
  • 1. The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
  • 2. Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210023, China.
  • 3. School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
  • 4. Jiangsu Province Engineering Research Center of TCM Intelligence Health Service, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
  • 5. Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210029, China.
  • 6. The Academy of Phenomics of Traditional Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, 210030, China.
  • 7. School of Integrative Medicine of Nanjing University of Chinese Medicine, Nanjing, 210023, China.
  • 8. Research Institute of TCM Zhenghou Phenomics, School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, China.
  • 9. Department of Stomatology, Nanjing Drum Tower Hospital, Nanjing, 210008, China.
  • 10. Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210023, China. [email protected].
  • 11. The Academy of Phenomics of Traditional Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, 210030, China. [email protected].
  • 12. School of Integrative Medicine of Nanjing University of Chinese Medicine, Nanjing, 210023, China. [email protected].
  • 13. Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210023, China. [email protected].
  • 14. The Academy of Phenomics of Traditional Chinese Medicine, Nanjing University of Chinese Medicine, Nanjing, 210030, China. [email protected].
  • 15. School of Integrative Medicine of Nanjing University of Chinese Medicine, Nanjing, 210023, China. [email protected].
  • 16. Research Institute of TCM Zhenghou Phenomics, School of Traditional Chinese Medicine, Hunan University of Chinese Medicine, Changsha, 410208, China. [email protected].
  • 17. Department of Pharmacology, University of Nevada Reno School of Medicine, Reno, NV, 89557, USA. [email protected].
  • 18. The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, China. [email protected].
  • 19. Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210023, China. [email protected].
  • # Contributed equally.
Abstract

Colorectal Cancer (CRC) is a prevalent malignant tumor with high incidence and mortality rates, with recurrence being the primary cause of death among patients. Traditional Chinese Medicine (TCM) utilizes a holistic cognitive approach to develop herbal treatment strategies, displaying significant efficacy in slowing tumor progression and improving patients' quality of life. However, discrepancies in herbal prescription strategies arise from variations in clinicians' syndrome differentiation and experiential knowledge, leading to a lack of systematic understanding of compound prescription compatibility rules. This study aims to identify TCM prescriptions that are effective in preventing or treating CRC recurrence through evidence-supported and clinically applied prescriptions. By employing Apriori association rule mining and graph convolutional network analysis, a core herb spectrum associated with anti-recurrence prescriptions was identified, emphasizing a high-confidence herbal combination for further mechanistic exploration. Subsequent network pharmacology analysis revealed quercetin and kaempferol as representative active compounds with PTGS2 identified as a potential key target. Molecular docking, molecular dynamics simulation, public database analysis, and in vitro experiments provided initial evidence supporting their interaction and biological effects in CRC cells. Overall, this study reveals the compatibility characteristics of TCM prescriptions for preventing CRC recurrence and offers a scientific foundation for the continued use of TCM-based strategies in managing CRC recurrence.

Keywords
Colorectal cancer; Compatibility rules; Network analysis; Recurrence; Traditional Chinese medicine.
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