Modified Wumei Pills: Network Pharmacology and Bioinformatics in Colon Cancer Treatment
Year: 2025
Type: article
Abstract: This study investigates the therapeutic mechanisms of modified Wumei pills in colon cancer treatment, utilizing network pharmacology and bioinformatics to uncover the active ingredients and their corresponding targets that intersect with colon cancer-related genes.We identified the active components of Wumei pills using the TCMSP database and predicted their targets with Swiss Target Prediction. Disease-related targets were identified through GeneCards and Disgenet. Network analysis, GO, KEGG, and PPI network construction were performed. Immunohistochemical assessments validated gene expression patterns, and ROC curve and Cox regression analyses evaluated the prognostic significance and patient prognosis correlation.The study revealed 112 common targets associated with colon cancer, with six key genes (ADRA2B, CXCR3, CYP19A1, NR1H2, PAPPA, PGR) prioritized. Functional enrichment analyses indicated significant associations with biological processes and pathways related to colon cancer. Immunohistochemical assessments confirmed the expression patterns of these genes within colon cancer tissues. ROC curve analysis highlighted the prognostic significance of the PGR gene, while molecular docking and molecular dynamics simulation studies demonstrated robust binding affinity of active components to their targets, particularly Diop with CXCR3.The research provides a scientific framework for the application of modified Wumei pills in colon cancer management, identifying potential key genes and pathways. The findings suggest that these pills could influence tumor growth and the immune microenvironment, offering novel insights for targeted therapy and immunotherapy in colon cancer treatment.
Source: Trends in Immunotherapy
DOI: 10.54963/ti.v9i1.989
Authors: Shichao Liu, Guancheng Liu, Chen Li, Rui Zhang
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408010042
