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.

Epithelial-to-mesenchymal transition (EMT) affects the invasion and migration of cancer cells. Here, we show that FBXO11 recognizes and promotes ubiquitin-mediated degradation of ZEB1. There is a strong association between FBXO11 and ZEB1 in non-small cell lung cancer (NSLC) in a clinical database. FBXO11 interacts with ZEB1, a core inducer of EMT. FBXO11 leads to increased ubiquitination and proteasomal degradation of ZEB1. Depletion of endogenous FBXO11 causes ZEB1 protein accumulation and EMT in A549 and H1299 cells, while overexpression of FBXO11 reduces ZEB1 protein abundance and cellular invasiveness. Importantly, the depletion of ZEB1 suppresses the increased migration and invasion of A549 and H1299 cells promoted by the depletion of FBXO11. The same results are shown in xenograft tumors. High FBXO11 expression is associated with a favorable prognosis in NSLC. Collectively, our study demonstrates that FBXO11 modulates EMT by mediating the stability of ZEB1 in lung cancer cells.

The rise in human activity has intensified environmental pollution, posing a global public health challenge. Understanding the intricate mechanisms by which pollutants impact health is crucial. Traditional research, often limited to specific techniques and short-term exposures, fails to capture the full complexity of these interactions. This study integrates machine-learning, quantum chemical computing, physicochemical properties, target prediction, KEGG and GO pathway analyses and survival analysis to examine the effects of air and water pollutants on human health. We chose knowledge-guided pre-trained graph transformer (KPGT) framework with an AUC of 0.83 knowledge bootstrap to predict the carcinogenic potential of pollutants and clustered environmental pollutants into seven different groups. For each group, quantum chemical and physicochemical properties, target prediction, KEGG and GO pathway analyses further revealed links between pollutants and cancer-related factors, such as MicroRNA, PD-L1, the PD-1 checkpoint pathway, and HIF-1 signaling. Survival analysis identified key proteins associated with poor cancer prognosis. These findings provide insights into the complex effects of pollutants on health and contribute to public health research.