Single-cell transcriptional mapping reveals genetic and hierarchy-based determinants of aberrant differentiation in AML

Therapeutic targeting of acute myeloid leukemia (AML) has in part been hampered by profound cell state heterogeneity among leukemia cells. To develop a more precise understanding of leukemia cell states in AML, we constructed a reference atlas of human hematopoiesis from 263,519 single cell transcriptomes spanning 55 cellular states. Using this atlas, we mapped over 1.2 million single-cell transcriptomes spanning 318 myeloid leukemia samples. This uncovered twelve recurrent patterns of aberrant differentiation in AML and additional leukemia cell states involving lymphoid and erythroid progenitors. Systematic mapping of genotype-to-phenotype associations revealed specific differentiation landscapes associated with >45 genetic drivers. Importantly, AML samples sharing common genetic driver alterations can have distinct cellular origins which inform the cellular identity of their disease-sustaining leukemia stem cell (LSC). Further, distinct LSC-driven hierarchies can co-exist within individual patients. Thus, precise mapping of malignant cell states provides insights into leukemogenesis, refines disease classification, and informs therapy development.

Type: RNASeq
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset

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Dataset ID	Description	Technology	Samples
EGAD50000001346	This dataset includes single cell (sc)RNA-seq of N=13 AML patients. The dataset includes bam files that have been purged of reads mapping to cells where a majority of the reads from that cell mapped to the human genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.	Illumina NovaSeq 6000	13