Heterogeneity of B cell lymphopoiesis in patients with premalignant and active myeloma
Jana Jakubikova, Danka Cholujova, Gabor Beke, Teru Hideshima, Lubos Klucar, Merav Leiba, Krzysztof Jamroziak, Paul G. Richardson, Efstathios Kastritis, David M. Dorfman, Kenneth C. Anderson
Jana Jakubikova, Danka Cholujova, Gabor Beke, Teru Hideshima, Lubos Klucar, Merav Leiba, Krzysztof Jamroziak, Paul G. Richardson, Efstathios Kastritis, David M. Dorfman, Kenneth C. Anderson
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Resource and Technical Advance Hematology Oncology

Heterogeneity of B cell lymphopoiesis in patients with premalignant and active myeloma

Abstract

To better characterize the heterogeneity of multiple myeloma (MM), we profiled plasma cells (PCs) and their B cell lymphopoiesis in the BM samples from patients with monoclonal gammopathy of undetermined significance, smoldering MM, and active MM by mass cytometry (CyTOF) analysis. Characterization of intra- and interneoplastic heterogeneity of malignant plasmablasts and PCs revealed overexpression of the MM SET domain (MMSET), Notch-1, and CD47. Variations in upregulation of B cell signaling regulators (IFN regulatory factor 4 [IRF-4], CXCR4, B cell lymphoma 6 [Bcl-6], c-Myc, myeloid differentiation primary response protein 88 [MYD88], and spliced X box-binding protein 1 [sXBP-1]) and aberrant markers (CD319, CD269, CD200, CD117, CD56, and CD28) were associated with different clinical outcomes in clonal PC subsets. In addition, prognosis was related to heterogeneity in subclonal expression of stemness markers, including neuroepithelial stem cell protein (Nestin), SRY-box transcription factor 2 (Sox2), Krüppel-like factor 4 (KLF-4), and Nanog. Furthermore, we have defined significantly elevated levels of MMSET, MYD88, c-Myc, CD243, Notch-1, and CD47 from hematopoietic stem cells to PCs in myeloma B cell lymphopoiesis, noted even in premalignant conditions, with variably modulated expression of B cell development regulators, including IRF-4, Bcl-2, Bcl-6, and sXBP-1; aberrant PC markers (such as CD52, CD44, CD200, CD81, CD269, CD117, and CXCR4); and stemness-controlling regulators, including Nanog, KLF-4, octamer-binding transcription factor 3/4 (Oct3/4), Sox2, and retinoic acid receptor α2 (RARα2). This study provides the rationale for precise molecular profiling of patients with MM by CyTOF technology to define disease heterogeneity and prognosis.

Authors

Jana Jakubikova, Danka Cholujova, Gabor Beke, Teru Hideshima, Lubos Klucar, Merav Leiba, Krzysztof Jamroziak, Paul G. Richardson, Efstathios Kastritis, David M. Dorfman, Kenneth C. Anderson

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Figure 1

High-dimensional single-cell profiling of B cell lymphopoiesis in MM by CyTOF analysis.

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High-dimensional single-cell profiling of B cell lymphopoiesis in MM by ...
(A) Schema of experimental design used in this study. (B) SPADE analysis of B lymphoid cell subsets in representative BM sample of NDMM patient. Each node of the SPADE tree is colored for the median expression of CD38, with the size of each node correlated to amount of the cells. (C) Box plots of normalized median expression of B cell markers (CD34, CD10, CD19, IgM, IgD, CD20, CD22, CD27, IgG, IgA, CD38, and CD45) in MGUS (n = 16), SMM (n = 25), NDMM (n = 43), and RRMM (n = 104) versus HDs (n = 10). The maturation spectrum from hscs to Ig-switched memory B cells is defined by color code. Each box represents 0.25–0.75 percentile of median expression, with whiskers calculated by Tukey’s method. Multiple clusters in some B cell subsets are identified. Significant differences between MGUS, SMM, NDMM, and RRMM versus HDs are defined by Dunn’s multiple comparison test after the Kruskal-Wallis 1-way ANOVA by ranks, *P value < 0.05. (D) Box plots of normalized median expression of B cell markers (CD19, IgM, IgD, CD20, CD27, IgG, IgA, CD38, CD45, and CD138) in MGUS (n = 16), SMM (n = 25), NDMM (n = 43), and RRMM (n = 104) versus HDs (n = 10) in PB/PC clusters (PB/PC1–2) and PC clusters (PC1–7) defined by color code (bottom). Each box represents 0.25–0.75 percentile of median expression, with whiskers calculated by Tukey’s method. Significant differences identified between MGUS, SMM, NDMM, and RRMM versus HDs are defined by Dunn’s multiple comparison test after the Kruskal-Wallis 1-way ANOVA by ranks, *P value < 0.05.