Cell
Volume 162, Issue 1, 2 July 2015, Pages 184-197
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Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

https://doi.org/10.1016/j.cell.2015.05.047Get rights and content
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Highlights

  • PhenoGraph partitions high-dimensional single-cell data into subpopulations

  • PhenoGraph plus mass cytometry elucidate intra- and intertumor heterogeneity in AML

  • Surface phenotypes and regulatory intercellular signaling are decoupled in leukemia

  • Signaling-based definition of primitive cells correlates with clinical outcome

Summary

Acute myeloid leukemia (AML) manifests as phenotypically and functionally diverse cells, often within the same patient. Intratumor phenotypic and functional heterogeneity have been linked primarily by physical sorting experiments, which assume that functionally distinct subpopulations can be prospectively isolated by surface phenotypes. This assumption has proven problematic, and we therefore developed a data-driven approach. Using mass cytometry, we profiled surface and intracellular signaling proteins simultaneously in millions of healthy and leukemic cells. We developed PhenoGraph, which algorithmically defines phenotypes in high-dimensional single-cell data. PhenoGraph revealed that the surface phenotypes of leukemic blasts do not necessarily reflect their intracellular state. Using hematopoietic progenitors, we defined a signaling-based measure of cellular phenotype, which led to isolation of a gene expression signature that was predictive of survival in independent cohorts. This study presents new methods for large-scale analysis of single-cell heterogeneity and demonstrates their utility, yielding insights into AML pathophysiology.

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