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Induction of myelodysplasia by myeloid-derived suppressor cells
Xianghong Chen, … , Alan List, Sheng Wei
Xianghong Chen, … , Alan List, Sheng Wei
Published October 15, 2013
Citation Information: J Clin Invest. 2013;123(11):4595-4611. https://doi.org/10.1172/JCI67580.
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Research Article Hematology

Induction of myelodysplasia by myeloid-derived suppressor cells

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Abstract

Myelodysplastic syndromes (MDS) are age-dependent stem cell malignancies that share biological features of activated adaptive immune response and ineffective hematopoiesis. Here we report that myeloid-derived suppressor cells (MDSC), which are classically linked to immunosuppression, inflammation, and cancer, were markedly expanded in the bone marrow of MDS patients and played a pathogenetic role in the development of ineffective hematopoiesis. These clonally distinct MDSC overproduce hematopoietic suppressive cytokines and function as potent apoptotic effectors targeting autologous hematopoietic progenitors. Using multiple transfected cell models, we found that MDSC expansion is driven by the interaction of the proinflammatory molecule S100A9 with CD33. These 2 proteins formed a functional ligand/receptor pair that recruited components to CD33’s immunoreceptor tyrosine-based inhibition motif (ITIM), inducing secretion of the suppressive cytokines IL-10 and TGF-β by immature myeloid cells. S100A9 transgenic mice displayed bone marrow accumulation of MDSC accompanied by development of progressive multilineage cytopenias and cytological dysplasia. Importantly, early forced maturation of MDSC by either all-trans-retinoic acid treatment or active immunoreceptor tyrosine-based activation motif–bearing (ITAM-bearing) adapter protein (DAP12) interruption of CD33 signaling rescued the hematologic phenotype. These findings indicate that primary bone marrow expansion of MDSC driven by the S100A9/CD33 pathway perturbs hematopoiesis and contributes to the development of MDS.

Authors

Xianghong Chen, Erika A. Eksioglu, Junmin Zhou, Ling Zhang, Julie Djeu, Nicole Fortenbery, Pearlie Epling-Burnette, Sandra Van Bijnen, Harry Dolstra, John Cannon, Je-in Youn, Sarah S. Donatelli, Dahui Qin, Theo De Witte, Jianguo Tao, Huaquan Wang, Pingyan Cheng, Dmitry I. Gabrilovich, Alan List, Sheng Wei

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Figure 3

Identification of S100A9 as a native ligand for CD33.

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Identification of S100A9 as a native ligand for CD33.
(A) Coomassie blue...
(A) Coomassie blue staining of BM lysates precipitated with either control IgG or CD33-fusion. (B) Transfected SJCRH30 cells (S100A8 on top left and S100A9 lower left) stained with CD33-fusion (APC, red). (C) S100A9 capture-ELISA of lysates from untransfected (negative) or S100A9 transfected cells. Secondary antibody was either anti-S100A9 (positive control) or CD33-fusion. (D) Serial dilution of both AD293 and SJCRH30 cell lysates, either untransfected or transfected with vector or S100A9, onto a PVDF membrane and blotted with CD33-fusion. Coomassie blue staining serves as loading control. (E) S100A9 immunoprecipitation of SJCRH30 CD33/S100A9 cotransfected cell lysate blotted against CD33. (F) PBMC and BM-MNC from healthy (H) and MDS (M) samples immunoprecipitated with CD33-fusion and blotted for S100A9. (G) Immunofluorescence staining of rhS100A9-DDK incubated with either CD33-transfected (top) or vector-transfected (bottom) SJCRH30 cells at indicated time points. DAPI = nuclei, APC-DDK = rhS100A9. Treatment of SJCRH30-CD33 cells with rhS100A9 induced IL-10 (H) and TGF-β expression (I). Treatment of U937 cells (high CD33 expression myeloid cell line) with rhS100A9 also induced IL-10 (J) and TGF-β expression (K). S100A9 protein concentration in the plasma of MDS patients (n = 6) measured by ELISA (L). MDS-MDCS treated with 1 μg of rhS100A9 were stained for CD33-FITC and anti-DDK-APC (M) and immunoprecipitated with anti-CD33 antibody followed by blotting with anti–SHP-1 (N). Original magnification, ×400 (B); ×200 (G); ×600 (M). (O) BM plasma from either healthy donors (n = 3) or MDS patients (n = 3) was used to assay SHP-1 recruitment. In all experiments, error bars represent the SEM of 3 separate experiments.

Copyright © 2023 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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