Defining the genetic and immune landscape of precursor myeloma progression with single-cell sequencing
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ABSTRACT:
PROVIDER: PRJNA554883 | ENA |
REPOSITORIES: ENA
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Project description:Precursor states of Multiple Myeloma (MM) and its native tumor microenvironment need in-depth molecular characterization to better stratify and treat patients at risk. Using single-cell RNA sequencing of bone marrow cells from precursor stages, MGUS and smoldering myeloma (SMM), to full-blown MM alongside healthy donors, we demonstrate early immune changes during patient progression. We find NK cell abundance is frequently increased in early stages, and associated with altered chemokine receptor expression. As early as SMM, we show loss of GrK+ memory cytotoxic T-cells, and show their critical role in MM immunosurveillance in mouse models. Finally, we report MHC class II dysregulation in CD14+ monocytes, which results in T cell suppression in vitro. These results provide a comprehensive map of immune changes at play over the evolution of pre-malignant MM, which will help develop strategies for immune-based patient stratification.
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Project description:Multiple myeloma is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, multiple myeloma remains incurable and better risk stratification as well as new therapies are therefore highly needed. The proteome of multiple myeloma has not been systematically assessed before and holds the potential to uncover additional insight into disease biology and improved prognostic models. Here, we provide a comprehensive multi-omics analysis including deep tandem mass tag (TMT)-based quantitative global (phospho)proteomics, RNA sequencing and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive multiple myeloma patients treated in clinical trials, plasma cell leukemia, and the premalignancy monoclonal gammopathy of undetermined significance (MGUS), as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells is highly deregulated as compared to healthy plasma cells and is both defined by chromosomal alterations and extensive post-transcriptional regulation. A protein signature was identified that is associated with aggressive disease and more predictive for outcome than cytogenetic-based risk assessment in newly diagnosed multiple myeloma. Integration with functional genetics and single-cell sequencing revealed generally and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include novel potential targets for (immuno)therapies. These findings provide new insights in the biology of multiple myeloma and will be a unique resource for investigating new therapeutic approaches.
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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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Project description:Multiple myeloma is a plasma cell malignancy almost always preceded by precursor conditions, but low tumor burden of these early stages has hindered the study of their molecular programs through bulk sequencing technologies. Here, we generated and analyzed single cell RNA-sequencing of plasma cells from 26 patients at varying disease stages and 9 healthy donors. In silico dissection and comparison of normal and transformed plasma cells from the same bone marrow biopsy enabled discovery of novel, patient-specific transcriptional changes. Using Bayesian Non-Negative Matrix Factorization, we discovered 15 gene expression signatures which represent transcriptional modules relevant to myeloma biology, and identified a signature that is uniformly lost in neoplastic cells across disease stages. Finally, we demonstrated that tumors contain heterogeneous subpopulations expressing distinct transcriptional patterns. Our findings characterize transcriptomic alterations present at the earliest stages of myeloma, paving the way for exploration of personalized treatment approaches prior to malignant disease.
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