Abstract
In acute myeloid leukemia (AML), leukemia stem cells (LSCs) have self-renewal potential and are responsible for relapse. We previously showed that, in Mll-AF9/NRASG12V murine AML, CD69 expression marks an LSC-enriched subpopulation with enhanced in vivo self-renewal capacity. Here, we used CyTOF to define activated signaling pathways in LSC subpopulations in Mll-AF9/NRASG12V AML. Furthermore, we compared the signaling activation states of CD69High and CD36High subsets of primary human AML. The human CD69High subset expresses low levels of Ki67 and high levels of NFκB and pMAPKAPKII. Additionally, the human CD69High AML subset also has enhanced colony-forming capacity. We applied Bayesian network modeling to compare the global signaling network within the human AML subsets. We find that distinct signaling states, distinguished by NFκB and pMAPKAPKII levels, correlate with divergent functional subsets, defined by CD69 and CD36 expression, in human AML. Targeting NFκB with proteasome inhibition diminished colony formation.
Highlights
Immunophenotypically-defined murine AML stem cells harbor self-renewing and non-self-renewing subsets that display unique signaling characteristics.
CD69, an NFκB target gene, marks a subset of human AML with increased colony forming capacity and reduced proliferation.
NFκB activation correlates with the global signaling pathway activation state in human AML.
Acknowledgements
Michael Franklin, a scientific writing editor provided editorial assistance. We extend our appreciation to the core resources at the University of Minnesota that were instrumental in this project: The Hematological Malignancies Tissue Bank which is supported by the National Cancer Institute (5P30CA077598-18); Minnesota Masonic Charities, and the Killebrew-Thompson Memorial Fund through the Cancer Experimental Therapeutics Initiative (CETI); the Flow Cytometry Resource and other services of the Masonic Cancer Center (which is supported by NIH P30 CA77598); the Mass Cytometry Shared Resource at the University of Minnesota which is supported by the Office of the Vice President for Research at the University of Minnesota, and the Minnesota Supercomputing Institute.
Disclosure statement
No potential conflict of interest was reported by the author(s).