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

Author:
van Galen, Peter, Hovestadt, Volker, Wadsworth II, Marc H., Hughes, Travis K., Griffin, Gabriel K., Battaglia, Sofia, Verga, Julia A., Stephansky, Jason, Pastika, Timothy J., Lombardi Story, Jennifer, Pinkus, Geraldine S., Pozdnyakova, Olga, Galinsky, Ilene, Stone, Richard M., Graubert, Timothy A., Shalek, Alex K., Aster, Jon C., Lane, Andrew A., Bernstein, Bradley E.
Source:
Cell 2019 v.176 no.6 pp. 1265-1281.e24
ISSN:
0092-8674
Subject:
T-lymphocytes, artificial intelligence, bone marrow, disease course, genes, genotyping, immunity, myeloid leukemia, patients, precision medicine, sequence analysis, transcription (genetics)
Abstract:
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.[Display omitted]
Agid:
6333026