A multi-omics approach elucidates the link between artificial food colorings and common cancers

Artificial food colorings (AFCs) are widely used, yet their potential links to cancer remain unclear. We investigated associations between commonly used AFCs and cancer-related molecular networks and prognosis.

AFCs-related targets were collected from CTD, ChEMBL, SEA, and TargetNet, and cancer-related targets from GeneCards, OMIM, and CTD. Overlapping targets were subjected to STRING-based PPI analysis and Cytoscape visualization, followed by GO/KEGG enrichment. Core targets were evaluated for differential expression in GEO datasets of non-small cell lung cancer (NSCLC), colon adenocarcinoma (COAD), gastric cancer (GC), and breast cancer (BRCA), with GSEA for pathway characterization. Expression patterns were examined using GEPIA2. TCGA transcriptomic and clinical data were used to construct prognostic models via univariate Cox regression, LASSO selection, and multivariate Cox regression. Key genes were assessed using the Human Protein Atlas (HPA) and qPCR, and in vivo experiments evaluated tumor growth under AFCs exposure.

Four high-exposure AFCs were analyzed. We identified 108 shared AFCs-cancer targets and prioritized 50 core targets. Enrichment analyses highlighted cancer-relevant functional themes, including cell-cycle regulation (cyclin-dependent protein kinase holoenzyme complex) and oncogenic signaling (PI3K-Akt pathway). Multiple core targets were dysregulated in GEO tumor datasets, and GSEA identified consistently enriched pathways across cancer types. TCGA-derived signatures stratified patients into distinct risk groups with significantly different overall survival. HPA supported protein-level differences for selected targets, qPCR indicated that Allura Red AC or Tartrazine modulated prognostic gene expression in cancer cell lines, and AFCs exposure was associated with accelerated LLC tumor growth in mice.

This integrative analysis suggests that commonly used AFCs may be associated with cancer-related molecular networks and adverse prognosis in NSCLC, COAD, GC, and BRCA, informing future safety evaluation and regulation.