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Updated: Sep 9, 2025

Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants
Published on: June 6, 2025
Genetic risk classification in acute myeloid leukemia patients treated with hematopoietic cell transplantation and
Marta Villalba1, Juan Montoro2, Aitana Balaguer-Roselló3
1Hematology Department, Hospital Universitari i Politècnic La Fe, València, Spain; Instituto de Investigación Sanitaria La Fe, València.
Abstract:
We analyzed the outcomes of 217 acute myeloid leukemia patients in complete remission who underwent allogeneic hematopoietic cell transplantation (HCT) with myeloablative conditioning and post-transplant cyclophosphamide-based graftversus- host disease prophylaxis, aiming to assess the prognostic significance of genetic risk categories. In the overall cohort, the 2-year overall survival (OS) and event-free survival (EFS) were 77% (95% confidence interval [CI]: 71-83) and 72% (95% CI: 66-78), respectively. European LeukemiaNet (ELN)2022 risk stratification lacked prognostic value in HCT. Instead, we identified four risk categories with distinct impact on OS: standard risk (ELN2022 favorable/intermediate and adverse risk without high-risk genetic risk under the defined subcategories), intermediate risk (≥2 myelodysplasia-related gene mutations) (hazard ratio [HR]=2.23; 95% confidence interval [CI]: 1.14-4.92), adverse risk (complex karyotype, monosomal karyotype, inv(3)/t(3;3), KMT2A rearrangement) (HR=4.24; 95% CI: 2.00-9.02), and very adverse risk (TP53 mutations) (HR=6.81; 95% CI: 3.00-15.5). These categories demonstrated similar predictive power for EFS and cumulative incidence of relapse. Moreover, integrating pre-transplant measurable residual disease (MRD) refined risk stratification, identified MRD-negative patients with ≥2 myelodysplasia-related gene mutations whose OS and EFS were comparable to standard-risk patients. This refined classification improves the prognostic value of ELN2022 for acute myeloid leukemia patients undergoing allogeneic HCT with modern platform by integrating genetic features and MRD status to better guide post-transplant management.
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