ArticleNaunyn-Schmiedeberg's archives of pharmacology2026
Integrated network toxicology and experimental validation to investigate potential mechanisms associated with aspartame-induced malignant phenotypic changes in colorectal cancer.
Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
To investigate the potential molecular mechanisms underlying aspartame (APM)-induced malignant phenotypic changes in colorectal cancer (CRC). Candidate targets of APM were identified by integrating the ChEMBL, SwissTargetPrediction, and SEA databases. Differential expression analysis was performed using transcriptomic data from The Cancer Genome Atlas (TCGA) CRC cohort, followed by weighted gene co-expression network analysis (WGCNA) to identify key modules associated with CRC. The intersection of differentially expressed genes (DEGs), key module genes, and candidate APM targets was used to identify shared APM-CRC candidate genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, machine learning, SHAP-based interpretability analysis, molecular docking, and molecular dynamics simulations were then conducted to identify key feature genes and evaluate their potential interactions with APM. Finally, EdU, CCK-8, ROS fluorescence staining, and Western blot assays were performed in HCT116 and SW480 cells to validate the effects of APM on CRC cell proliferation, oxidative stress, and epithelial-mesenchymal transition (EMT)-related molecular alterations. A total of 4790 DEGs were identified between CRC and normal tissues, and WGCNA further identified key modules significantly associated with the tumor phenotype. Intersection analysis yielded 1003 CRC-related candidate genes and 26 shared APM-CRC candidate genes. Enrichment analysis indicated that these genes were mainly involved in extracellular matrix remodeling, regulation of cell adhesion, glutathione metabolism, and xenobiotic metabolism. Machine learning combined with SHAP analysis ultimately identified SLC7A5, MMP3, ITGA2, CAPN2, and BACE2 as key feature genes. Molecular docking and molecular dynamics simulations suggested that APM could potentially interact with all five key proteins, with MMP3 and ITGA2 showing relatively stronger binding affinity. In vitro experiments showed that APM increased the proliferation of HCT116 and SW480 cells, elevated intracellular ROS levels, and was associated with decreased E-cadherin expression and increased N-cadherin and Vimentin expression. These findings suggest that APM exposure may be associated with increased CRC cell proliferation and EMT-related molecular alterations, accompanied by changes in oxidative stress-related processes, extracellular matrix remodeling, and abnormal cell adhesion. SLC7A5, MMP3, ITGA2, CAPN2, and BACE2 may represent APM-responsive candidate molecules involved in these cellular responses.
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