Background <p>This research tried to identify a PANoptosis-related gene marker for sepsis early diagnosis and treatment.</p> Methods <p>We collected transcriptional datasets from the Gene Expression Omnibus (GEO) database and performed differential expression analysis using the R language and the "limma" package. Functional enrichment analysis was conducted using the "clusterProfiler" package, and Protein–Protein Interaction (PPI) analysis was carried out. Transcription factor (TF) binding sites were predicted using FIMO tool. Gene set enrichment analysis (GSEA) and disease ontology (DO) analysis were performed. Immune infiltration analysis was conducted using CIBERSORT, ssGSEA, and the xCell algorithm.</p> Results <p>A total of 18 PANoptosis-related genes were found to express significantly differentially between sepsis and normal samples, and APAF1 was selected as the target gene. APAF1 expressed higher in sepsis compared to normal samples. ROC analysis indicated its diagnostic value. TF HIF1A and 4 miRNAs might be regulators of APAF1. APAF1 was negatively related to CD8 T cells and resting NK cells, and positively related neutrophils, macrophages M0, T cells gamma delta, and plasma cells. Many target drugs were detected high sensitivity to APAF1 and its related TFs.</p> Conclusion <p>PANoptosis-related gene APAF1 was identified to highly express in sepsis and it was valuable in diagnosis.</p>

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PANoptosis-related gene APAF1 may contribute to the progression of sepsis

  • Zhiqin Kang,
  • Jing Huang,
  • Hongxuan Liu

摘要

Background

This research tried to identify a PANoptosis-related gene marker for sepsis early diagnosis and treatment.

Methods

We collected transcriptional datasets from the Gene Expression Omnibus (GEO) database and performed differential expression analysis using the R language and the "limma" package. Functional enrichment analysis was conducted using the "clusterProfiler" package, and Protein–Protein Interaction (PPI) analysis was carried out. Transcription factor (TF) binding sites were predicted using FIMO tool. Gene set enrichment analysis (GSEA) and disease ontology (DO) analysis were performed. Immune infiltration analysis was conducted using CIBERSORT, ssGSEA, and the xCell algorithm.

Results

A total of 18 PANoptosis-related genes were found to express significantly differentially between sepsis and normal samples, and APAF1 was selected as the target gene. APAF1 expressed higher in sepsis compared to normal samples. ROC analysis indicated its diagnostic value. TF HIF1A and 4 miRNAs might be regulators of APAF1. APAF1 was negatively related to CD8 T cells and resting NK cells, and positively related neutrophils, macrophages M0, T cells gamma delta, and plasma cells. Many target drugs were detected high sensitivity to APAF1 and its related TFs.

Conclusion

PANoptosis-related gene APAF1 was identified to highly express in sepsis and it was valuable in diagnosis.