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Network Pharmacology and Bioinformatics Study of Six Medicinal Food Homologous Plants Against Colorectal Cancer
by
Jin, Yue
, Zhao, Xinyue
, Xiu, Jian
, Yang, Hengzheng
, Han, Weiwei
in
Algorithms
/ Apoptosis
/ Artificial intelligence
/ Bioinformatics
/ Cancer
/ Cancer therapies
/ Cell cycle
/ Cell growth
/ Chemotherapy
/ Clinical outcomes
/ Colorectal cancer
/ Colorectal Neoplasms - drug therapy
/ Colorectal Neoplasms - genetics
/ Colorectal Neoplasms - metabolism
/ Computational Biology - methods
/ Datasets
/ Food
/ Gene Expression Regulation, Neoplastic - drug effects
/ Gene Regulatory Networks
/ Herbs
/ Humans
/ Machine learning
/ Medical prognosis
/ Microbiota
/ Molecular Docking Simulation
/ Mortality
/ Network Pharmacology - methods
/ Ontology
/ Patients
/ Pharmacology
/ Phase transitions
/ Plants, Medicinal - chemistry
/ Protein synthesis
/ Proteins
/ Research methodology
/ Support vector machines
/ Traditional Chinese medicine
/ Tumor Microenvironment - drug effects
2025
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Network Pharmacology and Bioinformatics Study of Six Medicinal Food Homologous Plants Against Colorectal Cancer
by
Jin, Yue
, Zhao, Xinyue
, Xiu, Jian
, Yang, Hengzheng
, Han, Weiwei
in
Algorithms
/ Apoptosis
/ Artificial intelligence
/ Bioinformatics
/ Cancer
/ Cancer therapies
/ Cell cycle
/ Cell growth
/ Chemotherapy
/ Clinical outcomes
/ Colorectal cancer
/ Colorectal Neoplasms - drug therapy
/ Colorectal Neoplasms - genetics
/ Colorectal Neoplasms - metabolism
/ Computational Biology - methods
/ Datasets
/ Food
/ Gene Expression Regulation, Neoplastic - drug effects
/ Gene Regulatory Networks
/ Herbs
/ Humans
/ Machine learning
/ Medical prognosis
/ Microbiota
/ Molecular Docking Simulation
/ Mortality
/ Network Pharmacology - methods
/ Ontology
/ Patients
/ Pharmacology
/ Phase transitions
/ Plants, Medicinal - chemistry
/ Protein synthesis
/ Proteins
/ Research methodology
/ Support vector machines
/ Traditional Chinese medicine
/ Tumor Microenvironment - drug effects
2025
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Network Pharmacology and Bioinformatics Study of Six Medicinal Food Homologous Plants Against Colorectal Cancer
by
Jin, Yue
, Zhao, Xinyue
, Xiu, Jian
, Yang, Hengzheng
, Han, Weiwei
in
Algorithms
/ Apoptosis
/ Artificial intelligence
/ Bioinformatics
/ Cancer
/ Cancer therapies
/ Cell cycle
/ Cell growth
/ Chemotherapy
/ Clinical outcomes
/ Colorectal cancer
/ Colorectal Neoplasms - drug therapy
/ Colorectal Neoplasms - genetics
/ Colorectal Neoplasms - metabolism
/ Computational Biology - methods
/ Datasets
/ Food
/ Gene Expression Regulation, Neoplastic - drug effects
/ Gene Regulatory Networks
/ Herbs
/ Humans
/ Machine learning
/ Medical prognosis
/ Microbiota
/ Molecular Docking Simulation
/ Mortality
/ Network Pharmacology - methods
/ Ontology
/ Patients
/ Pharmacology
/ Phase transitions
/ Plants, Medicinal - chemistry
/ Protein synthesis
/ Proteins
/ Research methodology
/ Support vector machines
/ Traditional Chinese medicine
/ Tumor Microenvironment - drug effects
2025
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Network Pharmacology and Bioinformatics Study of Six Medicinal Food Homologous Plants Against Colorectal Cancer
Journal Article
Network Pharmacology and Bioinformatics Study of Six Medicinal Food Homologous Plants Against Colorectal Cancer
2025
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Overview
Integrating network pharmacological analysis and bioinformatic techniques, this study systematically investigated the molecular mechanisms of six medicinal food homologous plants (Astragalus membranaceus, Ganoderma lucidum, Dioscorea opposite, Curcuma longa, Glycyrrhiza uralensis, and Pueraria lobata) against colorectal cancer. Through screening the TCMSP database, 303 active compounds and 453 drug targets were identified. By integrating differential expression gene analysis with WGCNA on the GSE41258 dataset from the GEO database, 49 potential therapeutic targets were identified. GO and KEGG enrichment analyses demonstrated that these targets are primarily involved in drug response, fatty acid metabolism, and key cancer-related pathways. Cross-validation using three machine learning algorithms—LASSO regression, SVM-RFE, and Random Forest—pinpointed four critical target genes: CA1, CCND1, CXCL2, and EIF6. Further, CIBERSORT immune infiltration analysis revealed strong associations between these core genes and the tumor immune microenvironment in colorectal cancer patients, notably in modulating M0 macrophage infiltration and mast cell activity. Molecular docking analyses confirmed robust binding interactions between active compounds and core target proteins. This study systematically elucidated the molecular mechanisms of six medicinal food homologous plants against colorectal cancer, providing scientific evidence for their rational clinical application.
Publisher
MDPI AG,MDPI
Subject
/ Cancer
/ Colorectal Neoplasms - drug therapy
/ Colorectal Neoplasms - genetics
/ Colorectal Neoplasms - metabolism
/ Computational Biology - methods
/ Datasets
/ Food
/ Gene Expression Regulation, Neoplastic - drug effects
/ Herbs
/ Humans
/ Molecular Docking Simulation
/ Network Pharmacology - methods
/ Ontology
/ Patients
/ Plants, Medicinal - chemistry
/ Proteins
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