Modified Wumei Pills: Network Pharmacology and Bioinformatics in Colon Cancer Treatment

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.

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Publication Details

Journal
Trends in Immunotherapy
Published
2025-02-28
DOI
https://doi.org/10.54963/ti.v9i1.989
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Modified Wumei Pills: Network Pharmacology and Bioinformatics in Colon Cancer Treatment

Guancheng Liu, Chen Li, Rui Zhang, Shichao Liu
Trends in Immunotherapy
Computational Drug Discovery Methods
article

Modified Wumei Pills: Network Pharmacology and Bioinformatics in Colon Cancer Treatment

Guancheng Liu, Chen Li, Rui Zhang, Shichao Liu
article en

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.

Trends in ImmunotherapyVol. 9(1)
Harbin Medical University (CN), Northeast Agricultural University (CN), Heilongjiang University (CN)
Openalex Percentile: Top 95%
Computational Drug Discovery Methods
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