Abstract
Background: Acute myeloid leukemia (AML) remains an incurable hematological malignancy characterized by significant treatment resistance. Necroptosis, a newly recognized form of programmed cell death, has been implicated in tumor development and progression; however, its specific role in AML is not yet fully understood. Materials and Methods: We integrated transcriptomic and clinical data from TCGA and GEO database (GSE37642) to identify differentially expressed necroptosis-related genes (NRGs) between AML and normal samples from GTEx. Consensus clustering was performed to classify AML samples based on NRG expression profiles. Kaplan-Meier survival analysis, GSVA, and ssGSEA were employed to assess survival differences, biological functions, and immune cell infiltration between clusters. Differentially expressed genes (DEGs) identified between NRG clusters underwent LASSO and Cox proportional hazards regression analyses to develop a prognostic risk model. A nomogram integrating age and risk score was constructed and validated in independent cohorts (GSE12417). A nomogram integrating age and risk score was developed. CNV, TMB, immune profiles, and drug sensitivity were also analyzed. Importantly, qRT-PCR was performed using THP-1 and normal PBMCs to experimentally validate the expression levels of three key NRGs identified by the model (STAT5B, MAP3K7, and BCL2L11). Results: Two distinct NRG clusters were identified. Cluster B exhibited poorer prognosis, higher immune cell infiltration, and enriched signaling pathways, including TGF-β, JAK-STAT, ERBB, MAPK, and VEGF. The developed prognostic nomogram demonstrated robust predictive capability (integrated AUC = 0.645). The high-risk group displayed positive correlations with naive B cells, eosinophils, activated/resting memory CD4(+) T cells, and CD8(+) T cells, while negatively associated with memory B cells, resting mast cells, and follicular helper T cells. Drug sensitivity analysis indicated increased sensitivity to Bcl-2 inhibitors, checkpoint kinase inhibitors, and MAPK-MEK pathway inhibitors in the high-risk group. qRT-PCR results confirmed that STAT5B was significantly upregulated, while MAP3K7 and BCL2L11 were significantly downregulated in AML cells compared to normal PBMCs, consistent with bioinformatic predictions. Conclusion: Our study elucidates a significant association between suppressed necroptosis and adverse prognosis in AML. We highlight the role of NRGs in modulating the immune microenvironment of AML and identify potential therapeutic targets and drugs, providing valuable insights for improving clinical outcomes in AML patients.