ArticleJournal of translational medicine2025
An integrative analysis reveals cancer risk associated with artificial sweeteners.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research on the association between beverages consumption and cancer.Frontiers in medicine · 2025Pooled it
- Decoding the Neuroinflammatory Potential of Non-Nutritive Sweeteners Through An Integrative Computational Approach.Neurotoxicity research · 2026Article
- Role of immune dysregulation in aristolochic acid-induced multisystem toxicities: an insight from systems toxicology.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Functional role of long non-coding RNA MALAT1 and HOTAIR in lung cancer.Non-coding RNA research · 2026Review
- Unveiling the comorbidity hub: WT1 drives renal cancer progression in chronic kidney disease and confers sirolimus vulnerability.Experimental and therapeutic medicine · 2026Article
- Long-term artificial sweetener exposure increases the risk of atherosclerosis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Multi-omics analysis reveals that puerarin modulates the gut-liver axis to improve hepatic health in aged laying hens.BMC genomics · 2026Article
- Dysosma versipellis is associated with cholestatic hepatotoxicity potentially involving FXR-SHP-CYP7A1/BSEP-MRP2 axis disruption: A multi-omics-driven mechanistic investigation based on the toxicological evidence chain (TEC) concept.Journal of molecular histology · 2026Article
- The role of senescence indicators in the linkage between high-glycemic food intake and lung cancer: a Mendelian randomization study.Journal of clinical biochemistry and nutrition · 2026Article
- Deciphering pathogenic mechanisms of BDCPP exposure in endometrial cancer progression via an integrated approach combining network toxicology, machine learning, and molecular docking.International journal of surgery (London, England) · 2026Article
- Exploring the causal role and mechanism of galanin in glioblastoma: integration of mendelian randomization, network analysis, molecular docking and experimental validation.Frontiers in pharmacology · 2026Article
- C17orf75 (Njmu-R1) promotes hepatocellular carcinoma progression: a pan-cancer analysis and experimental validation.Frontiers in immunology · 2026Article
- Luteolin Disrupts Keratinocyte-Dendritic Cell Communication in Psoriasis by Targeting Rh Family C Glycoprotein.Mediators of inflammation · 2026Article
- Exploring the Role of Radix Polygalae in Melanogenesis Related to Vitiligo: A Network Pharmacology Analysis with in vitro Validation.Clinical, cosmetic and investigational dermatology · 2026Article
- Molecular Mechanisms of Aspartame-Induced Kidney Renal Papillary Cell Carcinoma Revealed by Network Toxicology and Molecular Docking Techniques.International journal of molecular sciences · 2025Article
- Analysis of toxicity and mechanisms of aspartame in kidney stones with network toxicology and molecular docking strategy.Scientific reports · 2025Article
- Article
- Metagenomics and transcriptomics analysis of aspartame's impact on gut microbiota and glioblastoma progression in a mouse model.Scientific reports · 2025Article
- Mechanistic study of plastic monomers in gestational diabetes mellitus: A network toxicology and molecular docking approach.PloS one · 2025Article
- Unveiling the hidden risk of caspofungin: insights from three adverse event reporting systems and network pharmacology integration.Frontiers in pharmacology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundArtificial sweeteners (AS) have been widely utilized in the food, beverage, and pharmaceutical industries for decades. While numerous publications have suggested a potential link between AS and diseases, particularly cancer, controversy still surrounds this issue. This study aims to investigate the association between AS consumption and cancer risk.
methodsTargets associated with commonly used AS were screened and validated using databases such as CTD, STITCH, Super-PRED, Swiss Target Prediction, SEA, PharmMapper, and GalaxySagittarius. Cancer-related targets were sourced from GeneCards, OMIM, and TTD databases. AS-cancer targets were identified through the intersection of these datasets. A network visualization ('AS-targets-cancer') was constructed using Cytoscape 3.9.0. Protein-protein interaction analysis was conducted using the STRING database to identify significant AS-cancer targets. GO and KEGG enrichment analyses were performed using the DAVID database. Core targets were identified from significant targets and genes involved in the 'Pathways in cancer' (map05200). Molecular docking and dynamics simulations were employed to verify interactions between AS and target proteins. Pan-cancer and univariate Cox regression analyses of core targets across 33 cancer types were conducted using GEPIA 2 and SangerBox, respectively. Gene chip datasets (GSE53757 for KIRC, GSE21354 for LGG, GSE42568 for BRCA, and GSE46602 for PRAD) were retrieved from the GEO database, while transcriptome and overall survival data were obtained from TCGA. Data normalization and identification of differentially expressed genes (DEGs) were performed on these datasets using R (version 4.3.2). Gene Set Enrichment Analysis (GSEA) was employed to identify critical pathways in the gene expression profiles between normal and cancer groups. A cancer risk prognostic model was constructed for key targets to further elucidate their significance in cancer initiation and progression. Finally, the HPA database was utilized to investigate variations in the expression of key AS-cancer target proteins across KIRC, LGG, BRCA, PRAD, and normal tissues.
resultsSeven commonly used AS (Aspartame, Acesulfame, Sucralose, NHDC, Cyclamate, Neotame, and Saccharin) were selected for study. A total of 368 AS-cancer intersection targets were identified, with 48 notable AS-cancer targets, including TP53, EGFR, SRC, PIK3R1, and EP300, retrieved. GO biological process analysis indicated that these targets are involved in the regulation of apoptosis, gene expression, and cell proliferation. Thirty-five core targets were identified from the intersection of the 48 significant AS-cancer targets and genes in the 'Pathways in cancer' (map05200). KEGG enrichment analysis of these core targets revealed associations with several cancer types and the PI3K-Akt signaling pathway. Molecular docking and dynamics simulations confirmed interactions between AS and these core targets. HSP90AA1 was found to be highly expressed across the 33 cancer types, while EGF showed the opposite trend. Univariate Cox regression analysis demonstrated strong associations of core targets with KIRC, LGG, BRCA, and PRAD. DEGs of AS-cancer core targets across these four cancers were analyzed. GSEA revealed upregulated and downregulated pathways enriched in KIRC, LGG, BRCA, and PRAD. Cancer risk prognostic models were constructed to elucidate the significant roles of key targets in cancer initiation and progression. Finally, the HPA database confirmed the crucial function of these targets in KIRC, LGG, BRCA, and PRAD.
conclusionThis study integrated data mining, machine learning, network toxicology, molecular docking, molecular dynamics simulations, and clinical sample analysis to demonstrate that AS increases the risk of kidney cancer, low-grade glioma, breast cancer, and prostate cancer through multiple targets and signaling pathways. This paper provides a valuable reference for the safety assessment and cancer risk evaluation of food additives. It urges food safety regulatory agencies to strengthen oversight and encourages the public to reduce consumption of foods and beverages containing artificial sweeteners and other additives.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.