Single-cell analysis of UNC13D-mediated immune and dedifferentiation heterogeneity in acute myeloid leukemia and development of a prognostic model.

BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy, with its pathogenesis closely associated with cellular states at various stages of differentiation. Existing clinical prognostic models often fail to account for this heterogeneity and lack integration of key molecular pathways. This study aimed to characterize AML differentiation-associated heterogeneity at the single-cell level, investigate the role of UNC13D in immune and dedifferentiation states, and develop a prognostic model integrating these features.

METHODS: This study combined single-cell RNA sequencing data (GSE178910) with bulk RNA-sequencing (RNA-seq) datasets [The Cancer Genome Atlas-Acute Myeloid Leukemia (TCGA-LAML) and Oregon Health & Science University (OHSU)]. Seurat and Harmony were used for batch correction and unsupervised clustering, followed by cell state annotation using AddModuleScore-based scoring of lineage-specific gene sets. UNC13D expression was assessed to infer its association with differentiation stage and pathway activity. Prognostic genes within the MYC proto-oncogene signaling pathway were identified using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression. An eight-gene risk model was then constructed and validated across two cohorts.

RESULTS: We identified eleven AML cellular subpopulations, grouped into five functional differentiation states. UNC13D was predominantly expressed in common myeloid progenitor-like (CMP-like) cells and correlated with multiple oncogenic and immune-related pathways. The resulting eight-gene prognostic model (PRDX4, KPNB1, DEK, ABCE1, ODC1, GLO1, MCM5, CCNA2) demonstrated good predictive performance in both the training and validation cohorts, with stable 1- and 3-year area under the curve (AUC) values. Differential pathway enrichment revealed marked biological divergence between high- and low-risk groups, including immune signaling and cell cycle regulation.

CONCLUSIONS: Our study delineates the differentiation landscape of AML and identifies UNC13D as a potential biomarker of cellular plasticity and immune modulation. The constructed model provides a reliable prognostic tool and offers novel insights for AML stratification and precision therapy development.