Background: Acute myeloid leukemia (AML) is an aggressive hematological neoplasm. Little improvement in survival rates has been achieved over the past few decades. Necroptosis has relationship with certain types of malignancies outcomes. Here, we evaluated the diagnostic ability, prognostic capacity of necroptosis-related genes (NRGs) and the effect of their copy number variations (CNVs) in AML.
Methods: Necroptosis-related differentially expressed genes (NRDEGs) were identified after intersecting differentially expressed genes (DEGs) from the Gene Expression Omnibus(GEO) database with NRGs from GeneCards, the Molecular Signatures Database (MSigDB) and literatures. Machine learning was applied to obtain hub-NRDEGs. The expression levels of the hub-NRDEGs were validated in vitro. The mRNA-miRNA and mRNA-TF interaction networks with the hub-NRDEGs were screened using Cytoscape. Single-sample gene set enrichment analysis (ssGSEA) was utilized to calculate correlations between the hub-NRDEGs and immune cells. CNV analysis of the hub-NRDEGs was carried out on the TCGA-LAML datasets from the TCGA database. Kaplan-Meier (K-M) survival analyses were utilized to evaluate the prognostic values along with Cox model.
Results: Six hub-NRDEGs (SLC25A5, PARP1, CTSS, ZNF217, NFKB1, and PYGL) were obtained and their expression changes derived from CNVs in AML were visualized. In total, 65 mRNA-miRNA and 80 mRNA-TF interaction networks with hub-NRDEGs were screened. The ssGSEA result showed the expression of RAPR1 was inversely related to CD56 natural killer cells and the expression of CTSS was positive related to Myeloid-derived suppressor cells (MDSCs) in AML. The K-M results demonstrated that ZNF217 had significant difference in the duration of survival in AML patients. Cox regression models revealed that the hub-NRDEGs had better predictive power at year-1 and year-5.
Conclusion: These screened NRDEGs can be exploited as clinical prognostic predictions in AML patients, as well as potential biomarkers for diagnosis and therapeutic targeting.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11727709 | PMC |
http://dx.doi.org/10.1186/s12885-025-13439-y | DOI Listing |
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