TY - JOUR
T1 - Characterization of myelodysplastic syndromes hematopoietic stem and progenitor cells using mass cytometry
AU - Bachas, Costa
AU - Duetz, Carolien
AU - van Spronsen, Margot F
AU - Verhoeff, Jan
AU - Garcia Vallejo, Juan J
AU - Jansen, Joop H
AU - Cloos, Jacqueline
AU - Westers, Theresia M
AU - van de Loosdrecht, Arjan A
N1 - Funding Information: This work was funded by an AMC‐VUMC Cancer Center Amsterdam grant (#CCA2016‐5‐28). Arjan van de Loosdrecht and Carolien Duetz are supported in part by research funding from MDS‐RIGHT, which has received funding from the European Union's Horizon 2020 Research and Innovation Program under grant agreement No ‐ “Providing the right care to the right patient with MyeloDysplastic Syndrome at the right time”. We thank Dr. Shahram Kordasti (Systems Cancer Immunology, Guy's Hospital, King's College London, London, UK) for valuable discussions on technical aspects of the mass cytometry experiments. We thank Sofie van Gassen and Yvan Saeys (Data Mining and Modeling for Biomedicine Group, VIB, Belgium) for fruitful discussions. Publisher Copyright: © 2022 The Authors. Cytometry Part B: Clinical Cytometry published by Wiley Periodicals LLC on behalf of International Clinical Cytometry Society.
PY - 2022/3/15
Y1 - 2022/3/15
N2 - Background: Myelodysplastic syndromes (MDS) at risk of transformation to acute myeloid leukemia (AML) are difficult to identify. The bone marrows of MDS patients harbor specific hematopoietic stem and progenitor cell (HSPC) abnormalities that may be associated with sub-types and risk-groups. Leukemia-associated characteristics of such cells may identify MDS patients at risk of progression to AML and provide insight in the pathobiology of MDS. Methods: Bone marrow samples from healthy donors (n = 10), low risk (n = 12) and high risk (n = 13) MDS patients were collected, in addition, AML samples for 5 out of 6 MDS patients that progressed. Mass cytometry was applied to assess expression of stem cell subset and leukemia-associated immunophenotype markers. Results: We analyzed the data using FlowSOM to cluster cells with similar expression of 10 commonly used stem cell markers. Metaclusters (n = 20) of these clusters represented populations of cells with a related phenotype, largely resembling known stem cell subsets. Within specific subsets, intra-cellular expression levels of pCREB, IkBα, or pS6 differed significantly between healthy bone marrow (HBM) and MDS or consecutive secondary AML samples. CD34, CD44, and CD49f expression was significantly increased in high risk MDS and AML-associated metaclusters. We identified MDS/sAML cells with aberrant phenotypes when compared to HBM. Such cells were observed in clusters of both primary MDS and secondary AML samples. Conclusions: High-dimensional mass cytometry and computational data analyses enabled characterization of HSPC subsets in MDS and identification of leukemia stem cell populations based on their immunophenotype. Stem cells in MDS that display leukemia-associated features may predict the risk of developing AML.
AB - Background: Myelodysplastic syndromes (MDS) at risk of transformation to acute myeloid leukemia (AML) are difficult to identify. The bone marrows of MDS patients harbor specific hematopoietic stem and progenitor cell (HSPC) abnormalities that may be associated with sub-types and risk-groups. Leukemia-associated characteristics of such cells may identify MDS patients at risk of progression to AML and provide insight in the pathobiology of MDS. Methods: Bone marrow samples from healthy donors (n = 10), low risk (n = 12) and high risk (n = 13) MDS patients were collected, in addition, AML samples for 5 out of 6 MDS patients that progressed. Mass cytometry was applied to assess expression of stem cell subset and leukemia-associated immunophenotype markers. Results: We analyzed the data using FlowSOM to cluster cells with similar expression of 10 commonly used stem cell markers. Metaclusters (n = 20) of these clusters represented populations of cells with a related phenotype, largely resembling known stem cell subsets. Within specific subsets, intra-cellular expression levels of pCREB, IkBα, or pS6 differed significantly between healthy bone marrow (HBM) and MDS or consecutive secondary AML samples. CD34, CD44, and CD49f expression was significantly increased in high risk MDS and AML-associated metaclusters. We identified MDS/sAML cells with aberrant phenotypes when compared to HBM. Such cells were observed in clusters of both primary MDS and secondary AML samples. Conclusions: High-dimensional mass cytometry and computational data analyses enabled characterization of HSPC subsets in MDS and identification of leukemia stem cell populations based on their immunophenotype. Stem cells in MDS that display leukemia-associated features may predict the risk of developing AML.
KW - acute myeloid leukemia
KW - leukemic transformation
KW - mass cytometry
KW - myelodysplastic syndromes
KW - stem cells
UR - http://www.scopus.com/inward/record.url?scp=85126226844&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/cyto.b.22066
DO - https://doi.org/10.1002/cyto.b.22066
M3 - Article
C2 - 35289472
SN - 1552-4949
JO - Cytometry Part B - Clinical Cytometry
JF - Cytometry Part B - Clinical Cytometry
ER -