A multiomic analysis of Waldenström macroglobulinemia defines distinct disease subtypes

We carried out a single-cell (sc) multiomic analysis on a series of MYD88 mutated Waldenström macroglobulinemia (WM) cases and identified two distinct subtypes of disease, memory B-cell-like (MBC-like) and plasma cell-like (PC-like), based on their expression of key lineage defining genes. Biologically, the subtypes are characterized by their variable capacity to differentiate fully towards a plasma cell (PC) and exhibit unique transcriptomic, chromatin accessibility, and genomic profiles. The MBC-like subtype is unable to differentiate beyond the memory B-cell (MBC) stage, upregulates key MBC genes, and is characterized by upregulated BCR and AKT/mTOR signaling. In contrast, the PC-like subtype can partially differentiate towards a PC, upregulates key PC genes, has enhanced NF-kB signaling, and has an upregulated unfolded protein response. Pseudotime trajectory analysis of combined scRNA-sequencing and scATAC-sequencing supports the variable differentiation capacity of each subtype and implicate key transcription factors SPI1, SPIB, BCL11A, and XBP1 in these features. The existence and generalizability of the two disease subtypes were validated further using hierarchical clustering of bulk RNA-seq data from a secondary set of cases. The biological significance of the subtypes was further established using whole genome sequencing, where it was shown that CXCR4, NIK, and ARID1A mutations occur predominantly in the MBC-like subtype and 6q deletions in the PC-like subtype. We conclude that the variable differentiation blockade seen in WM manifests itself clinically as two disease subtypes with distinct epigenetic, mutational, transcriptional, and clinical features with potential implications for WM treatment strategies. B-cells from 13 MYD88 mutated Waldenstrom macroglobulinemia (WM) patients were flow sorted from bone marrow (BM) using CD3-/CD19+. Sorted cells were pooled and libraries prepared for single-cell RNA-seq and single-cell ATAC-seq using 10x Genomics protocol and sequenced on an Illumina NovaSeq 6000.