Investigating cellular hierarchies in acute myeloid leukemia using single-cell genomics

Acute myeloid leukemia is an aggressive type of blood cancer with a poor survival rate. Leukemic stem cells (LSCs) govern the disease by producing rapidly dividing progenitor cells and driving relapse. Molecular characterization of leukemic stem cells and downstream hierarchies has been hampered by the lack of methods to unambiguously identify LSCs at single-cell level. In the first part of this thesis, we presented an approach to identify and molecularly profile LSCs with the addition of clonal resolution to single-cell multi-omics data. We showed that LSCs resemble active healthy hematopoietic stem cells (HSCs) and can robustly be distinguished from dormant HSCs and leukemic progenitors. Downstream of LSCs, immature progenitors had a high patient-to-patient variability and its phenotype was associated with chemotherapy response. As a complementary strategy, we demonstrated that combining functional experiments with single-cell RNA sequencing is a suitable approach for the identification of LSCs which transcriptomically do not resemble HSCs. In the last part of the thesis, we showed how computational methods to annotate flow cytometry datasets using single-cell genomics atlases, is a promising avenue for translating findings from single-cell omics to the clinics. Together, the work presented in this thesis underscore the potential of single-cell technologies to advance our knowledge on acute myeloid leukemia.