The synergistic effect of c-Myb hyperactivation and Pu.1 deficiency induces Pelger–Huët anomaly and promotes sAML

Abstract

Approximately 30% of patients with myelodysplastic syndrome (MDS) progress to secondary acute myeloid leukemia (sAML) via accumulating gene mutations. Genomic analyses reveal a complex interplay among mutant genes, with co-occurring and mutually exclusive patterns. Hyperactivation of c-MYB and deficiency of PU.1 have been linked to myeloid disorders. We report a case of AML with concurrent PU.1 and c-MYB mutations, exhibiting early onset, high blast count, chemo-resistance, indicating high-risk features, along with elevated Pelger–Huët anomaly (PHA). However, the synergistic mechanism of c-MYB and PU.1 in sAML remains unclear. Using c-Myb-hyperactivation and Pu.1-deficient double-strain ( c-myb hyper ;pu.1 G242D/G242D ) zebrafish, we investigated MDS/sAML progression. Surprisingly, the double mutant exhibited a distinct type of neutrophil resembling clinical PHA cells and demonstrated a higher rate of MDS/sAML transformation. Further expression analysis revealed reduced lmnb1 expression in double-mutant zebrafish. Knockdown of lmnb1 resulted in PHA and increased blast cells, while overexpression of lmnb1 in c-myb hyper ;pu.1 G242D/G242D reduced PHA cell level. This suggests that c-Myb hyperactivation and Pu.1 deficiency synergistically reduce lmnb1 expression, inducing the development of PHA-like neutrophils and promoting MDS/sAML progression in zebrafish. Moreover, coadministration of cell cycle inhibitor cytarabine (Ara-C) and the differential inducer all-trans retinoic acid (ATRA) could effectively relieve the neutrophil expansion and PHA symptoms in c-myb hyper ;pu.1 G242D/G242D zebrafish. Our findings revealed that c-Myb hyperactivation and Pu.1 deficiency played a synergistic role in sAML development and suggests a phenotypic association between the emergence of PH-like cells and the transformation to sAML. Furthermore, c-myb hyper ;pu.1 G242D/G242D zebrafish might serve as a suitable sAML model for drug screening.