Network Pharmacology and Bioinformatics Study of Six Medicinal Food Homologous Plants Against Colorectal Cancer.

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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.", "claims": [{"id": "claim-method", "statement": "The CIBERSORT algorithm [65] was employed to analyze the infiltration of 22 immune cell types in GSE41258 dataset samples, aiming to explore potential associations between target hub genes and immune microenvironment alterations in CRC patients.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39940699", "locator": "sections[18] \"4.8. 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