DLLP: a deep learning-based layer prediction network for three-dimensional fluorescence microscopy.

Genomic profiling plays a central role in risk stratification and therapeutic decision-making in acute myeloid leukemia (AML), yet the clinical implications of population-specific genomic architectures remain incompletely defined. We conducted a prospective, multicenter study of 603 adults with newly diagnosed AML in Korea, integrating targeted sequencing of 83 recurrently mutated genes with comprehensive clinical annotation across treatment intensities, including allogeneic hematopoietic stem cell transplantation (allo-HSCT). For contextual comparison, genomic profiles were evaluated against the Beat AML cohort. The overall genomic landscape was broadly conserved, supporting shared core disease biology across populations. However, RUNX1::RUNX1T1, CEBPA, GATA2, KIT, and DDX41 mutations were more frequent in the Korean cohort, whereas FLT3 and NPM1 mutations were less common. These differences translated into a distinct distribution of European LeukemiaNet (ELN) 2022 risk categories, with implications for therapeutic stratification. Notably, most DDX41 alterations were germline (3.2%), highlighting the need for systematic germline evaluation with implications for genetic counseling and donor selection. Although unadjusted overall survival appeared longer in the Korean cohort, this difference was not significant after adjustment for key clinical variables. These findings indicate that population-specific genomic distributions reshape the clinical application of risk stratification and support population-aware precision medicine strategies in AML.