ArticleJournal of inflammation research2025
Identification of Anoikis-Related Genes in Driving Immune-Inflammatory Responses in Ulcerative Colitis Based on Bioinformatics Analysis and Machine Learning.
Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Identification of IL1RN, MUC1, and SERPINA1 as key NET-related biomarkers in ulcerative colitis-associated intestinal fibrosis via bioinformatics and experimental validation.BMC gastroenterology · 2026Article
- Hepatic lipid accumulation induced by mono-(2-ethylhexyl) phthalate and potential ERBB2-associated inflammatory signaling in NAFLD.Frontiers in pharmacology · 2026Article
- Polyethylene terephthalate microplastics exposure enhances the risk of ulcerative colitis: insights from multiomics integration, machine learning, and molecular docking reveal intestinal toxicity mechanisms.International journal of surgery (London, England) · 2026Article
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Authors and funding
8 authors.
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Abstract
Background: Ulcerative colitis (UC) is a challenging chronic intestinal inflammation. Anoikis, a type of programmed cell death triggered by detachment from the extracellular matrix, is crucial in various physiological and pathological contexts. This study aims to explore the biological and clinical implications of anoikis-related genes (ARGs) in UC. Methods: Gene expression microarrays from normal and UC mucosal tissues focused on ARGs. Differentially expressed genes (DEGs) related to anoikis in UC were identified. Weighted gene co-expression network analysis (WGCNA) screened UC-related module genes. GO, KEGG, GSEA, and GSVA analyses were used to uncover mechanisms. Machine learning identified hub ARG-DEGs highly correlated with UC, and diagnostic nomograms assessed their diagnostic potential. The CIBERSORT algorithm analyzed changes in the UC immune microenvironment related to hub UC-ARGs. Potential drugs, miRNAs, and transcription factors (TFs) interacting with these hub UC-ARGs were investigated, and animal experiments verified their expression. Results: 49 ARG-DEGs were identified, mainly linked to the PI3K-AKT signaling pathway, inflammatory signal regulation, and extracellular matrix (ECM)-receptor interactions. Notably, CDH3 and SERPINA1 showed significant diagnostic potential for UC, confirmed by the Wilcoxon rank-sum test, independent validation sets, Western blot, and immunohistochemical staining. Significant variations in immune cell infiltration and activation within UC samples correlated with hub UC-ARGs were observed using the CIBERSORT algorithm. Conclusion: Anoikis may drive UC progression by initiating an immune inflammatory response. CDH3 and SERPINA1 are promising biomarkers and therapeutic targets for UC.
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