ArticlePloS one2024
Molecular characterization of PANoptosis-related genes in chronic kidney disease.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Integrated bioinformatics and clinical validation of oxidative stress-associated genes in atrial fibrillation and chronic kidney disease.Experimental and therapeutic medicine · 2026Article
- Recent advances in PANoptosis research in kidney disease: mechanistic networks, pathological roles, and potential intervention strategies.Frontiers in immunology · 2026Review
- Emerging role of PANoptosis in pathogen infection and systemic diseases.Cell biology and toxicology · 2025Review
- PANoptosis: A novel therapeutic target in kidney disease (Review).International journal of molecular medicine · 2025Review
- Targeting panoptosis: a narrative review of its therapeutic potential in kidney disease.BMC nephrology · 2025Review
- Integrating UHPLC-QE-MS and Bioinformatics with Experimental Validation Reveals MAPK/FOS-Mediated Podocyte Apoptosis as the Key Mechanism ofPharmaceuticals (Basel, Switzerland) · 2025Article
- Targeted multi-layer analysis of PANoptosis-associated genes in the etiology of chronic kidney disease.Human genomics · 2025Article
- PANoptosis in urological diseases: molecular mechanisms, pathological roles, and emerging therapeutic opportunities.Frontiers in immunology · 2025Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic kidney disease (CKD) is characterized by fibrosis and inflammation in renal tissues. Several types of cell death have been implicated in CKD onset and progression. Unlike traditional forms of cell death, PANoptosis is characterized by the crosstalk among programmed cell death pathways. However, the interaction between PANoptosis and CKD remains unclear. Here, we used bioinformatics methods to identify differentially expressed genes and differentially expressed PANoptosis-related genes (DE-PRGs) using data from the GSE37171 dataset. Following this, we further performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and gene set enrichment analysis using the data. We adopted a combined approach to select hub genes, using the STRING database and CytoHubba plug-in, and we used the GSE66494 as a validation dataset. In addition, we constructed ceRNA, transcription factor (TF)-gene, and drug-gene networks using Cytoscape. Lastly, we conducted immunohistochemical analysis and western blotting to validate the hub genes. We identified 57 PANoptosis-associated genes as DE-PRGs. We screened nine hub genes from the 57 DE-PRGs. We identified two hub genes (FOS and PTGS2) using the GSE66494 database, Nephroseq, immunohistochemistry, and western blotting. A common miRNA (Hsa-miR-101-3p) and three TFs (CREB1, E2F1, and RELA) may play a crucial role in the onset and progression of PANoptosis-related CKD. In our analysis of the drug-gene network, we identified eight drugs targeting FOS and 52 drugs targeting PTGS2.
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