Mass Cytometry Discovers Two Discrete Subsets of CD39−Treg Which Discriminate MGUS From Multiple Myeloma

Multiple Myeloma (MM) is preceded by the clinically stable condition monoclonal gammopathy of undetermined significance (MGUS). Critical immune events that discriminate MGUS from newly diagnosed MM (ND)MM patients remain unknown, but may involve changes in the regulatory T cell (Treg) compartment that favor myeloma growth. To address this possibility, we used mass cytometry and the unsupervised clustering algorithm Flow self-organizing map (FlowSOM) to interrogate the distribution of multiple subsets within CD25+CD127low/negTreg in matched bone marrow (BM) and peripheral blood (PB) of MGUS and NDMM patients. Both mass cytometry and flow cytometry confirmed a trend toward prevalence of CD39−Treg within the Treg compartment in BM and PB of NDMM patients compared to CD39−Treg in MGUS patients. FlowSOM clustering displayed a phenotypic organization of Treg into 25 metaclusters that confirmed Treg heterogeneity. It identified two subsets which emerged within CD39−Treg of NDMM patients that were negligible or absent in CD39−Treg of MGUS patients. One subset was found in both BM and PB which phenotypically resembled activated Treg based on CD45RO, CD49d, and CD62L expression; another subset resembled BM-resident Treg based on its tissue-resident CD69+CD62L−CD49d− phenotype and restricted location within the BM. Both subsets co-expressed PD-1 and TIGIT, but PD-1 was expressed at higher levels on BM-resident Treg than on activated Treg. Within BM, both subsets had limited Perforin and Granzyme B production, whilst activated Treg in PB acquired high Perforin and Granzyme B production. In conclusion, the use of mass cytometry and FlowSOM clustering discovered two discrete subsets of CD39−Treg which are discordant in MGUS and NDMM patients and may be permissive of myeloma growth which warrants further study. Understanding the regulatory properties of these subsets may also advance MGUS and MM diagnosis, prognosis, and therapeutic implications for MM patients.

[1]  Thomas S. Watkins,et al.  Bone marrow transplantation generates T cell–dependent control of myeloma in mice , 2018, The Journal of clinical investigation.

[2]  P. Campbell,et al.  Genomic patterns of progression in smoldering multiple myeloma , 2018, Nature Communications.

[3]  G. Morgan,et al.  Subclonal evolution in disease progression from MGUS/SMM to multiple myeloma is characterised by clonal stability , 2018, Leukemia.

[4]  Jinlong Li,et al.  ICOS signal facilitates Foxp3 transcription to favor suppressive function of regulatory T cells , 2018, International journal of medical sciences.

[5]  P. L. Bergsagel,et al.  Blocking IFNAR1 inhibits multiple myeloma–driven Treg expansion and immunosuppression , 2018, The Journal of clinical investigation.

[6]  Y. Lou,et al.  Next generation of immune checkpoint therapy in cancer: new developments and challenges , 2018, Journal of Hematology & Oncology.

[7]  K. Davis,et al.  Identity and Diversity of Human Peripheral Th and T Regulatory Cells Defined by Single-Cell Mass Cytometry , 2018, The Journal of Immunology.

[8]  V. Sasidharan Nair,et al.  Immune checkpoint inhibitors in cancer therapy: a focus on T‐regulatory cells , 2018, Immunology and cell biology.

[9]  A. Larbi,et al.  Markers of T Cell Senescence in Humans , 2017, International journal of molecular sciences.

[10]  D. Ferrari,et al.  Roles and Modalities of Ectonucleotidases in Remodeling the Multiple Myeloma Niche , 2017, Front. Immunol..

[11]  C. Benoist,et al.  T Regulatory Cells Support Plasma Cell Populations in the Bone Marrow. , 2017, Cell reports.

[12]  M. Dhodapkar MGUS to myeloma: a mysterious gammopathy of underexplored significance. , 2016, Blood.

[13]  A. Palumbo,et al.  Targeting CD38 with Daratumumab Monotherapy in Multiple Myeloma. , 2015, The New England journal of medicine.

[14]  S. Heck,et al.  Phenotypic Complexity of the Human Regulatory T Cell Compartment Revealed by Mass Cytometry , 2015, The Journal of Immunology.

[15]  Piet Demeester,et al.  FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data , 2015, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[16]  L. Antonioli,et al.  Immunity, inflammation and cancer: a leading role for adenosine , 2013, Nature Reviews Cancer.

[17]  R. Hájek,et al.  Contribution of regulatory T cells to immunosuppression and disease progression in multiple myeloma patients , 2013, Oncoimmunology.

[18]  Lisa J. Murray,et al.  Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms , 2013, Leukemia.

[19]  J. Eliaou,et al.  ENTPD1/CD39 is a promising therapeutic target in oncology , 2013, Oncogene.

[20]  B. Evans,et al.  An emerging role for adenosine and its receptors in bone homeostasis , 2012, Front. Endocrin..

[21]  G. Scott,et al.  Tumour Cell Generation of Inducible Regulatory T-Cells in Multiple Myeloma Is Contact-Dependent and Antigen-Presenting Cell-Independent , 2012, PloS one.

[22]  Antonio Lanzavecchia,et al.  Functionally distinct subsets of human FOXP3+ Treg cells that phenotypically mirror effector Th cells. , 2012, Blood.

[23]  Charles P. Lin,et al.  In vivo imaging of Treg cells providing immune privilege to the haematopoietic stem-cell niche , 2011, Nature.

[24]  Sean C. Bendall,et al.  Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum , 2011, Science.

[25]  K. Matsushima,et al.  Chemokine receptor CXCR3 facilitates CD8+ T cell differentiation into short-lived effector cells leading to memory degeneration , 2011, The Journal of experimental medicine.

[26]  Wenda Gao,et al.  Expression of CD39 by Human Peripheral Blood CD4+CD25+ T Cells Denotes a Regulatory Memory Phenotype , 2010, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

[27]  D. Hafler,et al.  FOXP3+ regulatory T cells in the human immune system , 2010, Nature Reviews Immunology.

[28]  J. Kutok,et al.  Elevated IL-17 produced by TH17 cells promotes myeloma cell growth and inhibits immune function in multiple myeloma. , 2010, Blood.

[29]  N. Tubridy,et al.  CD39+Foxp3+ Regulatory T Cells Suppress Pathogenic Th17 Cells and Are Impaired in Multiple Sclerosis1 , 2009, The Journal of Immunology.

[30]  T. Nomura,et al.  Functional delineation and differentiation dynamics of human CD4+ T cells expressing the FoxP3 transcription factor. , 2009, Immunity.

[31]  M. Kleinewietfeld,et al.  CD49d provides access to "untouched" human Foxp3+ Treg free of contaminating effector cells. , 2009, Blood.

[32]  M. Roncarolo,et al.  CD4+ T‐regulatory cells: toward therapy for human diseases , 2008, Immunological reviews.

[33]  T. Ley,et al.  Granzyme B and perforin are important for regulatory T cell-mediated suppression of tumor clearance. , 2007, Immunity.

[34]  S. Jameson,et al.  CD8(+) T cell differentiation: choosing a path through T-bet. , 2007, Immunity.

[35]  P. Rossini,et al.  Expression of ectonucleotidase CD39 by Foxp3+ Treg cells: hydrolysis of extracellular ATP and immune suppression. , 2007, Blood.

[36]  T. Whiteside,et al.  A Unique Subset of CD4+CD25highFoxp3+ T Cells Secreting Interleukin-10 and Transforming Growth Factor-β1 Mediates Suppression in the Tumor Microenvironment , 2007, Clinical Cancer Research.

[37]  M. Pérez‐Andrés,et al.  Characterization of bone marrow T cells in monoclonal gammopathy of undetermined significance, multiple myeloma, and plasma cell leukemia demonstrates increased infiltration by cytotoxic/Th1 T cells demonstrating a squed TCR‐Vβ repertoire , 2006, Cancer.

[38]  M. Kleinewietfeld,et al.  CCR6 expression defines regulatory effector/memory-like cells within the CD25(+)CD4+ T-cell subset. , 2005, Blood.

[39]  Iris Xie,et al.  New developments and challenges , 2015 .

[40]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .