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: CEACAM6, CHP2, PIK3R1, CASP10, PSMB1, PSMB8 and UBC. 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.
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http://dx.doi.org/10.2174/0109298673330894241008060309 | DOI Listing |
J Cancer
January 2025
Department of Pathology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210000, China.
Front Immunol
December 2024
School of Medical Information and Engineering, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Sci Rep
December 2024
Department of Traditional Chinese Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Heliyon
November 2024
Department of Oncology, People's Hospital of Kecheng District, Quzhou, 324000, Zhejiang, China.
Background: In recent years, the incidence of acute myeloid leukemia (AML) has increased rapidly with a suboptimal prognosis. In AML, cell death is independent of tumorigenesis, tumor invasion, and drug resistance. PANoptosis is a newly discovered form of cell death that combines pyroptosis, apoptosis, and necroptosis.
View Article and Find Full Text PDFJ Inflamm Res
November 2024
Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian Province, People's Republic of China.
Background: Ovarian cancer (OC) poses a significant health burden with high mortality rates among female reproductive malignancies. Variability in treatment responses underscores the need for reliable prognostic markers to refine risk stratification. PANoptosis, a novel form of programmed cell death, plays pivotal roles in cancer pathogenesis and therapy.
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