Single-Cell RNA-Seq Reveals AML Hierarchies Relevant to Disease Progression and Immunity

Cell. 2019 Mar 7;176(6):1265-1281.e24. doi: 10.1016/j.cell.2019.01.031. Epub 2019 Feb 28.


Acute myeloid leukemia (AML) is a heterogeneous disease that resides within a complex microenvironment, complicating efforts to understand how different cell types contribute to disease progression. We combined single-cell RNA sequencing and genotyping to profile 38,410 cells from 40 bone marrow aspirates, including 16 AML patients and five healthy donors. We then applied a machine learning classifier to distinguish a spectrum of malignant cell types whose abundances varied between patients and between subclones in the same tumor. Cell type compositions correlated with prototypic genetic lesions, including an association of FLT3-ITD with abundant progenitor-like cells. Primitive AML cells exhibited dysregulated transcriptional programs with co-expression of stemness and myeloid priming genes and had prognostic significance. Differentiated monocyte-like AML cells expressed diverse immunomodulatory genes and suppressed T cell activity in vitro. In conclusion, we provide single-cell technologies and an atlas of AML cell states, regulators, and markers with implications for precision medicine and immune therapies. VIDEO ABSTRACT.

Keywords: acute myeloid leukemia; cancer genetics; genotyping; immunity; leukemia stem cells; single-cell RNA-sequencing.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Base Sequence / genetics
  • Bone Marrow
  • Bone Marrow Cells / cytology
  • Cell Line, Tumor
  • Disease Progression
  • Exome Sequencing / methods
  • Female
  • Genotype
  • Humans
  • Leukemia, Myeloid, Acute / genetics*
  • Leukemia, Myeloid, Acute / immunology
  • Leukemia, Myeloid, Acute / physiopathology
  • Machine Learning
  • Male
  • Middle Aged
  • Mutation
  • Prognosis
  • RNA
  • Signal Transduction
  • Single-Cell Analysis / methods
  • Transcriptome / genetics*
  • Tumor Microenvironment


  • RNA