期刊
CELL
卷 176, 期 6, 页码 1265-+出版社
CELL PRESS
DOI: 10.1016/j.cell.2019.01.031
关键词
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资金
- NCI K99
- Leukemia & Lymphoma Society
- HFSP postdoctoral fellowship
- EMBO postdoctoral fellowship
- Searle Scholars Program
- Beckman Young Investigator Program
- Pew-Stewart Scholars Program
- Sloan Fellowship
- Bill and Melinda Gates Foundation
- NIH
- NCI ESI MERIT award
- Doris Duke Charitable Foundation
- NIH Common Fund
- NCI
- NHGRI
- Ludwig Center at Harvard University
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.
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