Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

Abstract

Inter-patient variability and the similarity of healthy and leukemic stem cells have impeded the characterization of leukemic stem cells (LSCs) in acute myeloid leukemia (AML), and their differentiation landscape. Here, we introduce CloneTracer, a novel method that adds clonal resolution to single-cell RNA-seq datasets. Applied to samples from 19 AML patients, CloneTracer revealed routes of leukemic differentiation. While residual healthy cells dominated the dormant stem cell compartment, active leukemic stem cells resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors were highly aberrant and constituted the disease-defining compartment: Their gene expression and differentiation state determined both chemotherapy response and the leukemia's ability to differentiate to transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers mis-regulated specifically in leukemic cells by intra-patient comparisons. Taken together, CloneTracer revealed a differentiation landscape that mimics its healthy counterpart and determines biology and therapy response in AML.

Integrative single‐cell expression and functional studies unravels a sensitization to cytarabine‐based chemotherapy through HIF pathway inhibition in AML leukemia stem cells

“…(D) Hypoxia signature score of each of the defined clusters comparing the hypoxia signature used in this study with five hypoxia signatures previously reported. (E) Hypoxia signature and HIF1A expression in AML cells from Beneyto‐Calabuig et al 59 AML cohort. (F) Hypoxia expression signature comparing each AML cytogenetic subgroup with healthy total BM cells (left plot) or healthy hematopoietic stem cells (HSCs)/LSCs (right plot).…”

An arms‐race against resistance: leukemic stem cells and lineage plasticity

“…These include the rare erythroblastic, megakaryoblastic, and mixed‐lineage leukemia, most of which are so far not considered in therapeutic decision making. However, two recent studies linking single‐cell transcriptomic and genomic DNA profiling have uncovered the surprising extent of lineage‐committed leukemia cells in individual AML patients [7,8]. Mutation‐bearing AML cells can not only be found in myeloid lineages but also in the naive stem cell compartment and in trajectories phenocopying erythroid and megakaryocyte lineages [7].…”

“…However, two recent studies linking single‐cell transcriptomic and genomic DNA profiling have uncovered the surprising extent of lineage‐committed leukemia cells in individual AML patients [7,8]. Mutation‐bearing AML cells can not only be found in myeloid lineages but also in the naive stem cell compartment and in trajectories phenocopying erythroid and megakaryocyte lineages [7]. Multilineage blasts are particularly pronounced in TP53 mutated AMLs, which are associated with poor clinical response to both chemo‐ and Venetoclax/5‐Azacytidine (VEN/AZA)‐therapies [8].…”

MuVEH and mitoMuVEH improve discovery of genetic variation from single cells

“…Importantly, this protocol functions without modification to the capture or library preparation process. Previous approaches to call mutations from scRNA-seq data have focused on the detection of small numbers of variants in one or a few genes per sample, necessitating upfront knowledge of the driver mutations present in these samples [4, 5, 19]. In contrast, MuVEH uses a panel of probes encompassing more than 100 genes of interest in one hybridization capture (Figure 1A).…”

“…Current work in the field has begun to approach the questions of somatic mutation profiles as well as clonal lineage tracing from current single-cell datasets. For single-cell somatic variation profiling, many current approaches target the cDNA molecules generated during library construction and amplify specific loci of interest [4][5][6][7][8]. These approaches yield high-resolution results for a small number of genes; however, they require a priori knowledge of the mutational landscape in the patient which is not always available.…”