Identification of the prognostic effect of mitophagy-related genes in acute myeloid leukemia

Background Mitophagy has been implicated in the pathogenesis of acute myeloid leukemia (AML), yet its precise molecular mechanisms remain poorly understood. Understanding the roles of mitophagy-related genes (MRGs) may provide new insights into AML classification, prognosis, and therapeutic response. Methods We analyzed 72 MRGs using three independent AML datasets (TCGA-LAML, GSE24395, and GSE146173). Consensus clustering based on MRG expression was used to identify AML molecular subtypes. Differentially expressed genes (DEGs) common to AML subtypes and GSE24395 were identified. Prognostic genes were screened using univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses. A prognostic risk model was constructed and validated. Functional enrichment, immune infiltration, and drug sensitivity analyses were conducted to explore the biological relevance of the model. In addition, regulatory elements including microRNAs, lncRNAs, and transcription factors targeting model genes were predicted. Results Twenty-six overlapping DEGs were identified between AML subtypes and GSE24395. Five MRG-associated genes ( ITGB2 , VIP , PTK2 , FHL2 , BAG3 ) were selected to construct a prognostic model that stratified patients into high- and low-risk groups with significantly different overall survival. Multivariate Cox analysis confirmed that risk score, age, and treatment status were independent prognostic indicators. Gene set enrichment analysis (GSEA) revealed 731 significantly enriched pathways, including mononuclear cell migration. Immune cell infiltration analysis showed a positive correlation between risk score and monocytes, and negative correlations with plasma B cells and activated mast cells. Drug sensitivity prediction identified 84 compounds with differential responses between risk groups. Regulatory network prediction highlighted hsa-miR-135b-5p, FTX, and SOX11 as potential upstream regulators of the prognostic genes. Conclusion This study identified five mitophagy-related genes as prognostic biomarkers in AML and developed a robust risk model that correlates with survival outcome, immune infiltration, and drug sensitivity. These findings offer new insights into mitophagy-related mechanisms in AML and may guide personalized therapeutic strategies.