Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis

Levine, Jacob H.; Simonds, Erin F.; Bendall, Sean C.; Davis, Kara L.; Amir, El-ad D.; Tadmor, Michelle; Litvin, Oren; Fienberg, Harris; Jager, Astraea; Zunder, Eli; Finck, Rachel; Gedman, Amanda L.; Radtke, Ina; Downing, James R.; Pe’er, Dana; Nolan, Garry P.

doi:10.1016/j.cell.2015.05.047

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Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis

Published Date:

Jun 18 2015

Publisher's site:

http://dx.doi.org/10.1016/j.cell.2015.05.047 New Site Icon

Source:

Cell. 2015; 162(1):184-197.

[PDF - 4.17 MB]

Details:

Personal Authors:

Levine, Jacob H. ; Simonds, Erin F. ; Bendall, Sean C. ; Davis, Kara L. ; Amir, El-ad D. ; ... More ▼

Keywords:

[+]

Pubmed ID:

26095251

Pubmed Central ID:

PMC4508757

Description:

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.

Document Type:

Journal Article

Collection(s):

CDC Public Access

Funding:

1R00-GM104148/GM/NIGMS NIH HHS/United States
1R01CA130826/CA/NCI NIH HHS/United States
5U54CA143907/CA/NCI NIH HHS/United States
DP1 HD084071/HD/NICHD NIH HHS/United States
DP1-HD084071/DP/NCCDPHP CDC HHS/United States
DP2 OD002414/OD/NIH HHS/United States
DP2-OD002414/OD/NIH HHS/United States
HHSF223201210194C/PHS HHS/United States
HHSN272200700038C/PHS HHS/United States
N01-HV-00242/HV/NHLBI NIH HHS/United States
P01 CA034233/CA/NCI NIH HHS/United States
R00 GM104148/GM/NIGMS NIH HHS/United States
R01 CA164729/CA/NCI NIH HHS/United States
R01-CA164729/CA/NCI NIH HHS/United States
T32 AI007328/AI/NIAID NIH HHS/United States
T32 GM008798/GM/NIGMS NIH HHS/United States
U19 AI057229/AI/NIAID NIH HHS/United States
U19 AI057229/AI/NIAID NIH HHS/United States
U54-CA121852/CA/NCI NIH HHS/United States
U54CA149145/CA/NCI NIH HHS/United States

Supporting Files:

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