ArticleJournal of inflammation research2025
Identification of Anoikis-Related Genes in Chronic Kidney Disease Based on Bioinformatics Analysis Combined with Experimental Validation.
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 2 papers.
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Who cites it
2 citing papers in PubMed.
- Integrative UHPLC-HRMS and computational biology reveal ferroptosis and anoikis targeting by Wenpitongluo decoction in cardiorenal syndrome.Frontiers in chemistry · 2025Article
- Integrative Bulk and Single-Cell Transcriptome Analyses Reveal Mitochondrial Metabolism-Related Biomarkers in IgA Nephropathy with Experimental Validation.Journal of inflammation research · 2025Article
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Authors and funding
7 authors.
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Abstract
Background: Chronic kidney disease (CKD) is a progressive condition that arises from diverse etiological factors, resulting in structural alterations and functional impairment of the kidneys. We aimed to establish the Anoikis-related gene signature in CKD by bioinformatics analysis. Methods: We retrieved 3 datasets from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) of them, which were intersected with Anoikis-related genes (ARGs) to derive Anoikis-related differentially expressed genes (ARDEGs). Besides, we conducted weighted gene co-expression network analysis (WGCNA) to identify hub genes. And then, we adopted the quantitative real-time PCR (RT-qPCR) assay to validate the hub genes among several CKD animal models. Furthermore, we constructed a competitive endogenous RNA (ceRNA) network for the hub genes utilizing the ENCORI and miRDB databases, while also calculating Spearman correlation coefficients. Ultimately, we applied the CIBERSORTx algorithm to conduct immune infiltration analysis, classifying immune characteristics based on the abundance of 22 immune cell types. Results: To summarize, we identified 13 ARDEGs. WGCNA yielded 6 hub genes, all of which demonstrated significant diagnostic potential in univariate logistic regression analysis ( Conclusion: We identified 6 hub genes that may serve as potential key biomarkers of Anoikis-related progression in CKD.
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