Integrative multiomics analysis of platelet-related genes unveils molecular subtypes and prognostic signatures in acute myeloid leukemia.

ABSTRACT: Acute myeloid leukemia (AML) remains challenging due to molecular heterogeneity and limited prognostic models integrating tumor microenvironment dynamics. While thrombocytopenia correlates with poor outcomes, the roles of platelet-related genes (PRGs) in AML pathogenesis are unclear. We integrated multiomics data to analyze platelet-clinicopathological associations, identify PRGs via weighted gene coexpression network analysis, and define molecular subtypes through unsupervised clustering. A machine learning-derived PRGScore model was developed and validated. Immune features were assessed using CIBERSORT, and drug responses via ex vivo profiling. The results showed that low platelet counts predicted a poor prognosis and were inversely correlated with blast proportions, suggesting suppressi

SUBMITTER: Zhong F 

PROVIDER: S-EPMC12623774 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature