Prognostic significance of neutrophil extracellular trap-related genes in childhood acute lymphoblastic leukemia: insights from multi-omics and in vitro experiment
Background This study aimed to develop a prognostic model based on extracellular trap-related genes (NETRGs) for patients with cALL.Methods Data from the TARGET-ALL-P2 and TARGET-ALL-P3 cohorts in the Genomic Data Commons database, the transcriptome dataset GSE26713, the single-cell transcriptome da...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Hematology |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/16078454.2025.2452701 |
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| Summary: | Background This study aimed to develop a prognostic model based on extracellular trap-related genes (NETRGs) for patients with cALL.Methods Data from the TARGET-ALL-P2 and TARGET-ALL-P3 cohorts in the Genomic Data Commons database, the transcriptome dataset GSE26713, the single-cell transcriptome dataset GSE130116 from the Gene Expression Omnibus database and 306 NETRGs identified were analysed. Differentially expressed genes (DEGs) were identified from GSE26713 and differentially expressed NETRGs (DE-NETRGs) were obtained by overlapping DEGs with NETRGs. Functional analyses were conducted. Key feature genes were identified through univariate and least absolute shrinkage and selection operator (LASSO) regression. Prognostic genes were determined via multivariate Cox regression analysis, followed by the construction and validation of a risk model and nomogram. Additional analyses included immune profiling, drug sensitivity, functional differences, cell-type-specific expression, enrichment analysis and RT-qPCR.Results A total of 1,270 DEGs were identified in GSE26713, of which 74 overlapped with NETRGs. Seven prognostic genes were identified using univariate, LASSO and multivariate Cox regression analyses. Survival analysis revealed lower survival rates in the high-risk group. Independent prognostic analysis identified risk scores and primary diagnosis as independent predictors of prognosis. Immune cell profiling showed significant differences in cell populations such as aDCs, eosinophils and Th2 cells between risk groups. Six cell subtypes were annotated, with prognostic genes predominantly expressed in myeloid cells. RT-qPCR revealed that PTAFR, FCGR2A, RETN and CAT were significantly downregulated, while TLR2 and S100A12 were upregulated in cALL.Conclusion TLR2, PTAFR, FCGR2A, RETN, S100A12 and CAT may serve as potential therapeutic targets. |
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| ISSN: | 1607-8454 |