Characterization of Waldenström Macroglobulinemia/Lymphoplasmacytic Lymphoma Using Single Cell Transcriptomic Analysis

Background: Single cell (sc) RNA and B-cell receptor (BCR) sequencing can be used to characterize and enhance our understanding of intra-tumoral heterogeneity and gene expression profiles versus bulk approaches. Moreover, neoplastic cells can be compared to the patient's own comparable normal cell counterparts, facilitating identification of dysregulated genes and pathways. We applied these techniques to lymphoplasmacytic lymphoma (LPL)/Waldenström macroglobulinemia (WM) patient samples to better understand the cellular make-up and gene expression profiles of tumor cells. Methods: Paired scRNA-seq and scBCR-seq were performed on fresh bone marrow (BM) aspirate samples from patients with symptomatic (N=26) and smoldering (N=3) WM, as well as a peripheral blood (PBMC) sample from 1 patient with smoldering LPL. All samples were subjected to CD138+ and CD19+ selection. cDNA libraries were prepared from these enriched samples, followed by simultaneous 5' gene expression (scRNA-seq) and scBCR-seq. Single-cell data were processed as previously described (Dang et al., Cancer Cell, 2023). The mutation status of MYD88, CXCR4, TP53, DNMT3A, TET2, and ASXL1 for each patient was determined by clinical molecular diagnostics. Results: We profiled 247,916 high-quality cells including 111,848 B-cells (21,382 progenitor/precursor/immature B-cells and 90,466 mature B-cells) and 136,068 plasma cells (PCs). We also obtained scBCR-seq data on 223,062 cells, of which 198,403 had paired scRNA-seq data. Clonotype was defined as monoclonal (frequency ≥5), polyclonal (frequency <5), and undetected. Unsupervised clustering analysis revealed 10 neoplastic clusters in B cells, including 4 precursor, 2 naïve, 3 memory and 1 atypical B-cell cluster. Additionally, 3 neoplastic clusters were identified in PCs. More than half of the naïve/germinal center (GC) B, unswitched memory B, IgE memory B, and PCs were monoclonal, while immature B, naïve B, S100A10+ memory B, and atypical B-cells were polyclonal. Monoclonal cells within a single patient displayed multiple phenotypes despite sharing the same clonotype. MYD88-mutated patients (N=25) had higher proportions of naïve and unswitched memory B-cells, but lower proportions of precursor B, switched memory B, and CXCR4+ PCs compared to MYD88 wild-type patients (N=4). MYD88mutCXCR4mut patients (N=10) had more PCs, but fewer naïve/GC B-cells than MYD88mutCXCR4wt patients (N=15). Smoldering WM patients (N=3) had higher proportions of proliferating pro/pre-B, naïve B, and unswitched memory B-cells than symptomatic WM patients (N=25). Patients with prior covalent BTK inhibitor treatment (N=12) had more plasmablasts but fewer naïve/GC B-cells compared to those without prior treatment (N=17). Differential gene expression analysis between monoclonal and polyclonal B-cells showed high expression of JCHAIN, BCL2, XBP1, ZNF804A, CDKN1A, and HSPA5, among others, in monoclonal B-cells. Pathway analysis revealed up-regulated apoptotic signaling, B-cell activation, response to endoplasmic reticulum stress, and glucose starvation, with down-regulated B-cell-mediated immunity and actin filament-based processes in monoclonal B-cells. Comparing monoclonal and polyclonal PCs, we observed elevated expression of JCHAIN, IGHM, CD79A, CXCR4, ZNF804A, among others, and a variety of ribosome genes, et al., with downregulated activity in B-cell activation, phagocytosis, humoral immune response, and complement activation in monoclonal PCs. Conclusions: These data highlight the intra-tumoral heterogeneity among WM patients and suggest that differences in gene expression between monoclonal and polyclonal cells may help inform new therapeutic strategies and sequences for pre-clinical and clinical investigation.

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Journal
Blood
Published
2024-11-05
DOI
https://doi.org/10.1182/blood-2024-208915
Primary Topic
Chronic Lymphocytic Leukemia Research
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article
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article

Characterization of Waldenström Macroglobulinemia/Lymphoplasmacytic Lymphoma Using Single Cell Transcriptomic Analysis

Melody Becnel, Mahmoud Gaballa, Lorenzo Gensini, Robert Zygmunt Orlowski et al.
Blood
Chronic Lymphocytic Leukemia Research
article

Characterization of Waldenström Macroglobulinemia/Lymphoplasmacytic Lymphoma Using Single Cell Transcriptomic Analysis

Melody Becnel, Mahmoud Gaballa, Lorenzo Gensini, Robert Zygmunt Orlowski, Hans Chulhee Lee, Sherif Seif, Linghua Wang, Lauren Lewis, Krina K. Patel, Hima Bansal, Minghao Dang, B Gabriel, Oren Pasvolsky, Maria Jose Acevedo-Calado, Sheeba K. Thomas, J Christine Ye, Donna M. Weber
article en

Abstract

Background: Single cell (sc) RNA and B-cell receptor (BCR) sequencing can be used to characterize and enhance our understanding of intra-tumoral heterogeneity and gene expression profiles versus bulk approaches. Moreover, neoplastic cells can be compared to the patient's own comparable normal cell counterparts, facilitating identification of dysregulated genes and pathways. We applied these techniques to lymphoplasmacytic lymphoma (LPL)/Waldenström macroglobulinemia (WM) patient samples to better understand the cellular make-up and gene expression profiles of tumor cells. Methods: Paired scRNA-seq and scBCR-seq were performed on fresh bone marrow (BM) aspirate samples from patients with symptomatic (N=26) and smoldering (N=3) WM, as well as a peripheral blood (PBMC) sample from 1 patient with smoldering LPL. All samples were subjected to CD138+ and CD19+ selection. cDNA libraries were prepared from these enriched samples, followed by simultaneous 5' gene expression (scRNA-seq) and scBCR-seq. Single-cell data were processed as previously described (Dang et al., Cancer Cell, 2023). The mutation status of MYD88, CXCR4, TP53, DNMT3A, TET2, and ASXL1 for each patient was determined by clinical molecular diagnostics. Results: We profiled 247,916 high-quality cells including 111,848 B-cells (21,382 progenitor/precursor/immature B-cells and 90,466 mature B-cells) and 136,068 plasma cells (PCs). We also obtained scBCR-seq data on 223,062 cells, of which 198,403 had paired scRNA-seq data. Clonotype was defined as monoclonal (frequency ≥5), polyclonal (frequency <5), and undetected. Unsupervised clustering analysis revealed 10 neoplastic clusters in B cells, including 4 precursor, 2 naïve, 3 memory and 1 atypical B-cell cluster. Additionally, 3 neoplastic clusters were identified in PCs. More than half of the naïve/germinal center (GC) B, unswitched memory B, IgE memory B, and PCs were monoclonal, while immature B, naïve B, S100A10+ memory B, and atypical B-cells were polyclonal. Monoclonal cells within a single patient displayed multiple phenotypes despite sharing the same clonotype. MYD88-mutated patients (N=25) had higher proportions of naïve and unswitched memory B-cells, but lower proportions of precursor B, switched memory B, and CXCR4+ PCs compared to MYD88 wild-type patients (N=4). MYD88mutCXCR4mut patients (N=10) had more PCs, but fewer naïve/GC B-cells than MYD88mutCXCR4wt patients (N=15). Smoldering WM patients (N=3) had higher proportions of proliferating pro/pre-B, naïve B, and unswitched memory B-cells than symptomatic WM patients (N=25). Patients with prior covalent BTK inhibitor treatment (N=12) had more plasmablasts but fewer naïve/GC B-cells compared to those without prior treatment (N=17). Differential gene expression analysis between monoclonal and polyclonal B-cells showed high expression of JCHAIN, BCL2, XBP1, ZNF804A, CDKN1A, and HSPA5, among others, in monoclonal B-cells. Pathway analysis revealed up-regulated apoptotic signaling, B-cell activation, response to endoplasmic reticulum stress, and glucose starvation, with down-regulated B-cell-mediated immunity and actin filament-based processes in monoclonal B-cells. Comparing monoclonal and polyclonal PCs, we observed elevated expression of JCHAIN, IGHM, CD79A, CXCR4, ZNF804A, among others, and a variety of ribosome genes, et al., with downregulated activity in B-cell activation, phagocytosis, humoral immune response, and complement activation in monoclonal PCs. Conclusions: These data highlight the intra-tumoral heterogeneity among WM patients and suggest that differences in gene expression between monoclonal and polyclonal cells may help inform new therapeutic strategies and sequences for pre-clinical and clinical investigation.

BloodVol. 144(Supplement 1)
The University of Texas MD Anderson Cancer Center (US)
Openalex Percentile: Top 60%
Chronic Lymphocytic Leukemia Research
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