Classification of acute myeloid leukemia based on multi-omics and prognosis prediction value.

ABSTRACT: Acute myeloid leukemia (AML) is a heterogeneous cancer, making outcomes prediction challenging. Several predictive and prognostic models are used but have considerable inaccuracy at individual level. We tried to increase prediction accuracy using a multi-omics strategy. We interrogated data from 1391 consecutive, newly diagnosed subjects with AML, integrating information on mutation topography, DNA methylation, and transcriptomics. We developed an unsupervised multi-omics classification system (UAMOCS) with these data. UAMOCS provides a multidimensional understanding of AML heterogeneity and stratifies subjects into three cohorts: (a) UAMOCS1 [high lymphocyte activating 3 (LAG3) expression, chromosome instability, myelodysplasia-related mutations]; (b) UAMOCS2 (monocytic-like profile, immu

SUBMITTER: Song Y 

PROVIDER: S-EPMC12161470 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature