ArticleJournal of inflammation research2024
Identification of PANoptosis-Related Genes in Community-Acquired Pneumonia Diagnosis.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Identification of ribosomal stress related signature genes and immune microenvironment analysis in ovarian cancer based on multi-machine learning.Discover oncology · 2026Article
- Diagnostic and prognostic value of LINC00278 in patients with severe pneumonia and its regulatory role.Journal of inflammation (London, England) · 2026Article
- Integrative single-cell and bulk transcriptomic profiling identify peripheral T-cell-associated candidate biomarkers in community-acquired pneumonia.International journal of medical sciences · 2026Article
- Targeting PANoptosis in Bacterial-Induced Inflammatory Diseases: Mechanisms and Therapeutic Interventions.Journal of inflammation research · 2025Review
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4 authors.
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Abstract
Background: This study aimed to identify and characterize novel PANoptosis biomarkers for community-acquired pneumonia (CAP) diagnosis. Methods: Transcriptomic data from training set GSE196399 and validation sets GSE94916 and GSE202947 were utilized. A PANoptosis gene set was identified by intersecting DEGs linked to CAP, WGCNA hub genes, and PANoptosis-related genes. GO and KEGG analyses were conducted for enrichment analysis. PANoptosis scores were calculated via ssGSEA. Feature genes were identified using SVM-RFE, LASSO regression, and RF methods. Diagnostic performance was assessed via ROC analysis. Immune cell infiltration was evaluated using CIBERSORT. A PPI network was constructed, and a nomogram was developed for CAP prediction. Drug-gene interactions were investigated. qRT-PCR was conducted to confirm feature gene alterations in clinical samples. Results: We identified 7555 DEGs associated with CAP from the GSE196399 dataset. Through WGCNA, a PANoptosis gene set of 39 genes was found, showing significant enrichment in pathways related to apoptosis and inflammation. CAP patients exhibited significantly reduced PANoptosis scores compared to healthy controls, with a marked upregulation in the majority of the PANoptosis gene set in high-score individuals. Four feature genes ( Conclusion: The identified PANoptosis feature genes demonstrate high diagnostic accuracy for CAP, serving as potential biomarkers and therapeutic targets for CAP.
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