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 4

Phenotypic and signaling changes in memory B cells of MM.

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Phenotypic and signaling changes in memory B cells of MM. (A) Notched bo...
(A) Notched boxes represent the 25th and 75th percentile values with Tukey whiskers of the ratio of statistically significant median expression for the indicated clustering markers calculated by the Mann-Whitney U test, P value < 0.05. (B) Violin plots show statistically significant normalized median expression of signaling markers on unswitched (UM1–4) and switched (SM1–3) clusters of memory B cells in MGUS (n = 16), SMM (n = 25), NDMM (n = 43), and RRMM (n = 104) versus HDs (n = 10), represented by color codes. Significant differences were defined by Dunn’s multiple comparison test after the Kruskal-Wallis 1-way ANOVA by ranks, *P value < 0.05. (C) Circle diagrams show schematic summary of statistically significant normalized median expression of signaling markers either downregulated (blue rectangle) or upregulated (red rectangle) within memory B cells from unswitched (UM1–4) to switched (SM1–3) memory B cells in MGUS, SMM, NDMM, and RRMM versus HDs by Dunn’s multiple comparison test after the Kruskal-Wallis 1-way ANOVA by ranks, with P value < 0.05. Venn diagrams show 15 intersections among MGUS, SMM, NDMM, and RRMM, and each intersection shows joint expression of statistically significant signaling markers either downregulated (–) or upregulated (+) within memory B cells from unswitched (UM1–4) to switched (SM1–3) memory B cells in MGUS, SMM, NDMM, and RRMM compared with HDs.