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2000
Volume 32, Issue 42
  • ISSN: 0929-8673
  • E-ISSN: 1875-533X
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Abstract

Background

PANoptosis plays an important role in many inflammatory diseases. However, there are no reports on the association between PANoptosis and CD.

Materials and Methods

This study used five machine learning algorithms - least absolute shrinkage and selection operator, support vector machine, random forest, decision tree and Gaussian mixture models - to construct CD’s PANoptosis signature. Unsupervised hierarchical clustering analysis was used to identify PANoptosis-associated subgroups of CD. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were conducted to compare the PANoptosis-associated subgroups of CD among the potential biological mechanisms. Single sample GSEA was used to assess immune microenvironmental differences among the subgroups. The potential role of PANoptosis in CD was further explored using single-cell RNA-Seq (scRNA-Seq) for PANoptosis scoring, differential analysis, pseudotime analysis, cellular communication analysis and weighted gene co-expression network analysis (WGCNA) analysis.

Results

CD’s PANoptosis signature consisted of seven genes: , , , , , and . The PANoptosis signature in multiple cohorts had a strong ability to recognise CD. The levels of immune cell infiltration and the vigour of the immune responses significantly varied between the two subpopulations of CD associated with PANoptosis. Multiple lines of evidence from the GO, KEGG, GSEA, GSVA, scRNA-Seq and WGCNA analyses suggested that I-kappaB kinase/NF-kappaB signalling, mitogen-activated protein kinase (MAPK), leukocyte activation and leukocyte migration were mechanisms closely associated with PANoptosis in CD.

Conclusion

This study is the first to construct a PANoptosis signature with excellent efficacy in recognising CD. PANoptosis may mediate the process of CD through inflammatory and immune mechanisms, such as NF- kappaB, MAPK and leukocyte migration.

© 2025 The Author(s). Published by Bentham Science Publishers.
This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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Multiple Machine Learning Models, Molecular Subtyping and Single- cell Analysis Identify PANoptosis-related Core Genes and their Association with Subtypes in Crohn’s Disease
Curr. Med. Chem. 32, 9707 (2025); https://doi.org/10.2174/0109298673330894241008060309
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  • Article Type:     Research Article
Keyword(s): Crohn's disease; leukocyte activation; machine learning; MAPK; NF-kappaB; PANoptosis

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