Multi-omics integration of molecular genetics, cytogenetics and immunophenotyping: a novel prognostic model for immune landscape characterization and outcome prediction in Chinese patients with acute myeloid leukemia.

Background: Current genetic risk stratification systems for acute myeloid leukemia (AML), including the 2017 European Leukemia Network (ELN), 2022 ELN, and 2023 China (CN) stratifications, inconsistently categorize key genetic variants such as Methods: We retrospectively enrolled 378 Chinese AML patients (298 for training, 80 for external validation) and compared the prognostic performance of the 2017/2022 ELN and 2023 CN systems (both integrating molecular genomic and cytogenetic data). Controversial genetic variants were re-evaluated to establish a novel 2023 CN (n-2023 CN) classification. A multi-omics model was constructed by combining n-2023 CN classification with CD15 positivity (leukemic immunophenotype), del(7q) (cytogenetic abnormality), and age ≥ 60 years (clinical factor). The model underwent external validation, was assessed for use in guiding hematopoietic stem cell transplantation (HSCT), and was compared with a published model. Results: The 2023 CN demonstrated superior efficacy in predicting AML relapse and 3-year relapse-free survival compared to 2017/2022 ELN systems. The n-2023 CN reclassified Conclusions: The n-2023 CN resolves uncertainty in genetic risk stratification for Chinese AML patients. The novel multi-omics model incorporates immunophenomics and clinical and cytogenetic factors, captures comprehensive AML characteristics, enhances prognostic precision, and provides reliable guidance for personalized treatment, including HSCT selection.