期刊
NATURE COMMUNICATIONS
卷 11, 期 1, 页码 -出版社
NATURE RESEARCH
DOI: 10.1038/s41467-020-19119-8
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资金
- Cancer Prevention and Research Institute of Texas [R120501]
- Welch Foundation [G-0040]
- University of Texas System STARS Award [PS100149]
- Leukemia and Lymphoma Society [NIH CA193235]
- Lyda Hill Foundation
- Charif Souki Cancer Research Fund
- MD Anderson Cancer Center Leukemia SPORE grant [NIH P50 CA100632]
- Physician Scientist Program at MD Anderson
- MD Anderson Cancer Center Support Grant [NIH/NCI P30 CA016672]
- S10 shared instrumentation grant for NovaSeq 6000 [NIH 1S10OD02497701]
- Leukemia Research Fund
- Japan Society for the Promotion of Science Research Fellowships for Young Scientists
- Japan Society for the Promotion of Science Overseas Research Fellowships
Clonal diversity is a consequence of cancer cell evolution driven by Darwinian selection. Precise characterization of clonal architecture is essential to understand the evolutionary history of tumor development and its association with treatment resistance. Here, using a single-cell DNA sequencing, we report the clonal architecture and mutational histories of 123 acute myeloid leukemia (AML) patients. The single-cell data reveals cell-level mutation co-occurrence and enables reconstruction of mutational histories characterized by linear and branching patterns of clonal evolution, with the latter including convergent evolution. Through xenotransplantion, we show leukemia initiating capabilities of individual subclones evolving in parallel. Also, by simultaneous single-cell DNA and cell surface protein analysis, we illustrate both genetic and phenotypic evolution in AML. Lastly, single-cell analysis of longitudinal samples reveals underlying evolutionary process of therapeutic resistance. Together, these data unravel clonal diversity and evolution patterns of AML, and highlight their clinical relevance in the era of precision medicine. Understanding the evolutionary trajectory of cancer samples may enable understanding resistance to treatment. Here, the authors used single cell sequencing of a cohort of acute myeloid leukemia tumours and identify features of linear and branching evolution in tumours.
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