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Identification of heterogeneous networks and plasma-monocytes crosstalks in multiple myeloma stratified by R-ISS system through single-cell sequencing

ABSTRACT: Purpose: to identify new potential pathways and therapeutic targets to kill plasma cells and affect their microenvironment in stage R-ISS III MM patients. Methods: We performed single-cell RNA sequencing of bone marrow samples obtained from nine MM patients and from two normal controls including pseudotime analysis, SCENIC analysis,cell–cell communication networks,large-scale chromosomal CNV analysis.The new markers that we reported originally were verified by qPCR, flow cytometry and immunofluorescence staining. Results: We identified two R-ISS-related modules, namely, “protein metabolism” (module 2) and “cell proliferation” (module 1). The gene expression pattern in pseudotime suggested that the gene activation in module 2 provides a substantial basis for the malignant proliferation of plasma cells during MM progression. We found that STAT1 may activate LETM1 to promote MM progression via the C-type lectin receptor signaling pathway. And PDIA6 was putatively activated by the UQCRB regulon to participate in oxidative phosphorylation. Moreover, a subcluster of monocytes exclusively found in stage III and specifically expressed CCL3L1, CCL3, and CXCL2 was modulated by ATF3. CCL3/CCL5/CCL3L1–CCR1, CCL4–SLC7A1, CD47–SIPRA, SEMA4A–PLXND1, and LILRB4–LAIR1 were identified as the active ligand–receptor pairs in plasma–monocyte communications in stage III. Conclusions: we systematically analyzed the molecular events and the regulated networks in the progression of the R-ISS stages, and the results suggested a promising landscape for the treatment of MM.

ORGANISM(S): Homo sapiens

PROVIDER: GSE176131 | GEO | 2022/11/30

REPOSITORIES: GEO

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Project description:Tumor immune microenvironmental alterations occur early in multiple myeloma (MM) development. In this study, we aim to systematically characterize the tumor immune microenvironment (TME) and the tumor-immune interactions from precursor stages, i.e., monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM), to newly diagnosed MM, comparing these to healthy donors. CIBERSORT analysis revealed proportions of 27 cell types, including 10 innate immune cells (monocytes, M0/M1/M2 macrophages, resting/activated dendritic cells, resting/activated mast cells, eosinophils, and neutrophils), 7 T cell subsets (CD8+ T cells, naive CD4+ T cells, resting/activated memory CD4+ T cells, follicular helper T cells, regulatory T cells, and gamma delta T cells), resting/activated NK cells, naive B cells, memory B cells, plasma cells, myeloma plasma cells, memory plasma cells, osteoblasts, osteoclasts and adipocytes. We removed plasma cells (PC) from the 100% total cell proportions to avoid bias resulting from different tumor burdens. We found that the proportions of neutrophils, mast cells, and monocytes account for the majority of innate immune cells and were decreased in NDMM and its precursor stages when compared with NBM. We noticed a significant abundance of M2 macrophages in NDMM, but not in the precursor stages. The proportion of CD8+ T cells was increased at the SMM and MM stages, and the proportion of activated memory CD4+ T cells continued to decrease from NBM to MGUS, SMM, and MM. We performed correlation analysis of immune cell proportions with the time of progression of MGUS and SMM patients. We observed neutrophil proportions were negatively correlated with the time to progression in SMM patients, indicating more neutrophils predict inferior outcomes for SMM patients. However, in NDMM patients, we observed that the neutrophil percentage was decreased in patients with high-risk status based on the 70-gene Prognostic Risk Score (GEP-70) or at stage III of International Staging System (ISS), and patients with high proportions of neutrophils had a significantly superior overall survival (OS) and event-free survival (EFS). For T cell populations, we observed that the proportions of CD8+ T cells were negatively correlated with the time of progression in SMM patients and the γδ T cells were positively correlated. We observed the proportions of γδ T cells were also positively correlated with the time of progression in MGUS patients. Consistent with the time-to-progression data, high-risk SMM patients showed higher proportions of CD8+ T cells and lower proportions of naïve CD4+ T cells and γδ T cells.

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Identification of heterogeneous networks and plasma-monocytes crosstalks in multiple myeloma stratified by R-ISS system through single-cell sequencing

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