Single-cell sequencing identifies characteristics of disease and bone marrow in concurrent multiple myeloma and myelodysplastic syndrome

To the Editor: Multiple myeloma (MM) is a malignant plasma cell tumor that predominantly expands within the bone marrow and produces excessive amounts of monoclonal proteins (M-protein).[1] Myelodysplastic syndromes (MDS) is a group of malignant clonal diseases originating from hematopoietic stem cells (HSCs), with an increased risk of progression to acute myeloid leukemia.[2] The pathogenesis and evolution of MM and MDS are all highly dependent on the bone marrow microenvironment (BME). However, the cellular and molecular features of both the disease and the BME in patients with concurrent MM and MDS have not yet been reported. In the present study, we explored the molecular heterogeneity and pathological association between MDS and MM by applying single-cell RNA sequencing (scRNA-seq) to the bone marrow cells of four patients with concurrent MM and MDS (MM-MDS) [Supplementary Methods and Supplementary Table 1, https://links.lww.com/CM9/C897]. Maintaining rigorous quality control, we identified, via known marker genes, 20 major cell types within the BM, including plasma cells (PCs), HSCs, myeloid cells, lymphoid cells, and stromal cells [Figure 1A and B]. Cell fraction analysis showed that PCs generally represented the most diverse cluster among patients with MM and MM-MDS [Figure 1C]. Based on the differential proportions of CD138+ PCs and mature myeloid cells, we categorized patients with MM and MM-MDS into high-risk and low-risk groups for subsequent analysis. The differentiation trajectory of HSC revealed a remarkable commonality within the low-risk MDS and low-risk MM-MDS groups, both of which exhibited significantly higher proportions of pro-monocyte (proMONO) and neutrophil-like monocyte (Neu-like MO) cells than their high-risk counterparts. Concurrently, the proportions of plasma cells in the low-risk MDS and low-risk MM-MDS groups were significantly lower than those in the high-risk groups [Figure 1D–F]. Collectively, these findings indicate a notable similarity in both severity and pathogenesis between MM and MDS.Figure 1: Single cell profiling of bone marrow from MM patients with or without MDS and healthy donors. (A and B) UMAP embedding of single-cell RNA sequencing samples across 3 groups consisting of 85,200 high quality single-cells portioned into 20 cell types (A) and sample ID (B). (C) Comparison of the average ratio of the detected BM cells. (D) Pseudotime analysis of HSC differentiation. (E) UMAP of BM cells from 5 groups. (F) Trajectory analysis of HSC. BM: Bone marrow; CD: Cluster of differentiation; cDC: Conventional dendritic cell; GMP: Granulocyte–monocyte progenitors; HD: Healthy donor; HSC: Hematopoietic stem cells; MDS: Myelodysplastic syndromes; MKP: Megakaryocyte; MM: Multiple myeloma; Neu-like MONO: Neutrophil-like monocyte; NK: Natural killer; pro-B: progenitor B; pDC: Plasma dendritic cell; proMONO: pro-monocyte; UMAP: Uniform manifold approximation and projection.We concentrated on analyzing PCs (CD138+) to examine their characteristics in patients with MM and MM-MDS. A comparative analysis of plasma cell fractions across all of the patients revealed significant activation in patients with MM relative to those with MM-MDS. Further, an elevated concentration of PCs was observed in MM-MDS samples 2 and 4 compared with samples 1 and 3, suggesting notable heterogeneity within the MM-MDS group [Supplementary Figure 1A, https://links.lww.com/CM9/C897]. Furthermore, PCs in MM-MDS samples 2 and 4 exhibited significantly higher copy number variation (CNV) scores than MM-MDS samples 1 and 3 [Supplementary Figure 1B, https://links.lww.com/CM9/C897]. Based on the treatment efficacy observed in MM and the aforementioned intra-group differences identified in MM-MDS, we divided the MM and MM-MDS patient samples into two categories—low-risk (MM-MDS 1 and 3) and high-risk (MM-MDS 2 and 4). Transcriptome analysis showed that each type of sample had its own gene expression characteristics [Supplementary Figure 1C, https://links.lww.com/CM9/C897]. Pathway enrichment analysis of high-risk MM-MDS samples revealed strong associations with cell growth and cancer gene sets, indicating that the degree of malignancy of PCs in the high-risk group was greater than that in the low-risk MM-MDS group (P <0.001) [Supplementary Figure 1D and E, https://links.lww.com/CM9/C897]. Gene ontology (GO) enrichment analysis revealed that, in both high- and low-risk groups, pathways related to protein processing in the endoplasmic reticulum and oxidative phosphorylation were upregulated in MM-MDS compared to MM [Supplementary Figure 1F–I, https://links.lww.com/CM9/C897]. Comparative analysis of differentially expressed genes (DEGs) between patients in the high- and low-risk MM-MDS groups showed that DEGs were enriched in pathways related to protein processing within the endoplasmic reticulum, as well as mitogen-activated protein kinase (MAPK) and nuclear factor kappa B (NF-κB) signaling pathways, which are closely associated with the pathogenesis of MM [Supplementary Figure 2A, https://links.lww.com/CM9/C897]. In both HDs and patients with MM-MDS, the number of interactions between the plasma cells and BM cells was comparable. However, plasma cells in patients with MM indicated the highest level of active communication with BM cells, particularly HSCs and monocytes [Supplementary Figure 2B, https://links.lww.com/CM9/C897]. These differences were largely attributable to the TNF receptor superfamily member 13B (TNFRSF13B)–TNFRSF13C and interleukin 16 (IL16)–CD4 signaling pathways in HSCs, myeloid cells, and stromal cells. The signaling patterns received by PCs in both patients with MM and MM-MDS were comparable, particularly in relation to TNFRSF13B-TNFRSF17 in granulocyte–monocyte progenitors (GMP) and resistin (RETN)–cyclase-associated actin cytoskeleton regulatory protein 1 (CAP1) in GMP and pro-monocytes. In addition, TNFSF13B was upregulated in patients with MM—especially in those with rapid disease progression—and was associated with tumor growth and poor outcomes in the multiple myeloma research foundation (MMRF) CoMMpass dataset.[3] Overall, PCs in patients with MM and MM-MDS received, on average, more signals from HSCs and myeloid cells than those in HDs, who primarily demonstrated intracellular communication through macrophage migration inhibitory factor (MIF)–CD74–C-X-C receptor 4 (CXCR4)/CD44 with HSCs and GMP [Supplementary Figure 2C, https://links.lww.com/CM9/C897]. Consistent with these findings, the MM group exhibited significant enrichment in MIF signaling, as well as B And T lymphocyte associated (BTLA) and IL16, compared with the other groups [Supplementary Figure 2D, https://links.lww.com/CM9/C897]. These results indicate that the interactions between plasma and BM cells lead to the creation of a microenvironment that promotes the survival of malignant cells. Analysis of cell type proportions revealed that patients with MM-MDS exhibited a high frequency of the GMP lineage—referred to as the GMP pattern—and erythroblasts, as well as megakaryocyte (MKP), which is comparable to the common myeloid progenitors (CMP) pattern. ScRNA-seq data obtained from the BM biopsies of five patients with MDS were combined into an integrated dataset downloaded from Cai’s study.[4] Cell proportion analysis indicated that patient samples from the low-risk MM-MDS group exhibited a higher proportion of the Neu-like Mo. This trend was also observed in the low-risk MDS group [Supplementary Figure 3A and B, https://links.lww.com/CM9/C897]. To define the biological properties of GMP patterns and differentiation states, we conducted a focused analysis of transcriptional factors. In the high-risk group, overactivation of STAT1, combined with elevated expression of interferon regulatory factor 7 (IRF7) and the myeloid factor CCAAT enhancer binding protein beta (CEBPB), together promoted HSC differentiation into myeloid cells [Supplementary Figure 3C, https://links.lww.com/CM9/C897]. In GMP cells, the expression level of CEBPE was elevated in both the low-risk MDS and low-risk MM-MDS groups [Supplementary Figure 3D, https://links.lww.com/CM9/C897]. In brief, these findings suggest that low-risk MM-MDS promotes Neu-like Mo differentiation through CEBPE activation in the BME. Analysis of cellular proportions revealed that patients with MM-MDS had a higher percentage of B cells and neutrophils. To examine changes in B cells, we clustered and performed further analyses on this specific subset [Supplementary Figure 4A, https://links.lww.com/CM9/C897]. It was found that DEGs related to B cell development and homeostasis, such as YBX3 and OGT—along with genes from the ATP and HSPA families—exhibited high enrichment. Moreover, pathway analysis of these DEGs in B cells from patients with MM-MDS revealed significant enrichment in ATP formation, regulation of leukocyte activation, and cellular responses to cytokine stimulation [Supplementary Figure 4B and C, https://links.lww.com/CM9/C897],[5] while neutrophils from the MM and normal groups clustered closer than those from patients with MM-MDS, which were more independent [Supplementary Figure 4D, https://links.lww.com/CM9/C897]. Neutrophils from patients with MM-MDS tended to express genes regulating chemotactic and activation-regulating factors, such as S100A8/9, FCGR3B, and LYN [Supplementary Figure 4E, https://links.lww.com/CM9/C897], reflecting enrichment in pathways related to neutrophil degranulation, positive regulation of immune responses, and leukocyte migration [Supplementary Figure 4F, https://links.lww.com/CM9/C897]. Furthermore, CD8+ T cells in the high-risk MDS group displayed increased exhaustion and cytotoxicity (P <0.001) [Supplementary Figure 4G and H, https://links.lww.com/CM9/C897]. Collectively, these results indicate that patients with MM-MDS experience an inflammatory state characterized by elevated proportions of B cells, neutrophils, and activated T cells. In summary, our data demonstrate that MM-MDS is biologically distinct from classical MM and is characterized by significant transcriptional heterogeneity among plasma cells, a unique dependence on the TNFRSF13B/C pathway, modifications in unfolded protein response (UPR)/protein folding and proteostasis mechanisms, and an inflammatory BME that plays a crucial role in the progression of both conditions. Furthermore, the differentiation trajectories revealed that the Neu-like Mo population was exclusively present in patients at low risk of developing MM-MDS, indicating the potential for Neu-like Mo as a predictive biomarker. Nevertheless, our study has two major limitations. First, resolving clonal origin typically requires integrated clonal evolution analyses to track shared versus independent mutations and distinguish therapy-related from de novo disease. Second, due to the small cohort size, our findings require validation in larger patient groups. Therefore, to identify conserved molecular signatures, establish robust clinical correlates, future research should focus on larger sample sizes for sequencing. Acknowledgments We thank Prof. Zhigang Cai from Tianjin Medical University School of Basic Medical Science for providing the scRNA-seq data of MSD patients. Data-sharing statement The data underlying this article will be shared on reasonable request to the corresponding author. The scRNA-seq data of concurrent MM and MDS samples can be publicly found at the Gene Expression Omnibus database under accession number GSE278230. The code used for the downstream data analyses is freely available at the GitHub (https://github.com/wang212963/MM-MDS). Funding This work was supported by grants from the National Natural Science Foundation of China (Nos. 82400243, 82370209, 82570254, 82300229, and 82500275), the Collaborative Academic Innovation Project of Shandong Cancer Hospital (No. FC009), and the Taishan Scholars Expert Program of Shandong Province (No. tstp20230632). Conflicts of interest None.