Abstract Elimination of suppressive T cells may enable and enhance cancer immunotherapy. Here, we demonstrate that the cell membrane protein SLAMF7 was highly expressed on immunosuppressive CD8 + CD28 - CD57 + Tregs in multiple myeloma (MM). SLAMF7 expression associated with T cell exhaustion surface markers and exhaustion-related transcription factor signatures. T cells from patients with a high frequency of SLAMF7 + CD8 + T cells exhibited decreased immunoreactivity towards the MART-1 aa26–35*A27L antigen. A monoclonal anti-SLAMF7 antibody (elotuzumab) specifically depleted SLAMF7 + CD8 + T cells in vitro and in vivo via macrophage-mediated antibody-dependent cellular phagocytosis (ADCP). Anti-SLAMF7 treatment of MM patients depleted suppressive T cells in peripheral blood. These data highlight SLAMF7 as a marker for suppressive CD8 + Treg and suggest that anti-SLAMF7 antibodies can be used to boost anti-tumoral immune responses in cancer patients.
In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression.
Introduction: Non-Hodgkin lymphoma (NHL) NHL arise in lymph nodes whose normal architecture is variably altered by different NHL subtypes. While follicular lymphoma maintains a germinal center-like growth program, diffuse large B cell lymphomas (DLBCL) is characterized by a diffuse growth pattern. To uncover driving forces of these distinct growth patterns we studied lymph node derived immune cell subsets and stroma cells (SC) which are known to function as tissue organizers through chemokine gradients that enable the compartmentalization of specific immune cell subsets into functionally specialized microdomains (Figure 1). Methods: Here, we utilized a combined single-cell and spatially-resolved mapping approach of lymph node derived stroma cells, lymphoma infiltrating T-cells and malignant B-cells to dissect the pathophysiological mechanisms underlying the gradual loss of tissue organization in indolent and diffusely growing aggressive lymphomas. We validated altered chemokine gradients in large lymphoma patient cohorts and in-vitro SC co-culture lymphocyte co-culture models. Results: First, we characterized and quantified how lymph node resident cells organize into spatially distinct cellular neighborhoods and how these functional units are disturbed and disrupted in diffusely growing lymphomas using ultra-high-plex immunofluorescence (CODEX). To determine the molecular programs underlying loss of tissue organization, we employed holistic single-cell transcriptomic mapping of the lymph node ecosystem, covering major lymph node resident cell types, including rare mesenchymal and endothelial populations. Combined with transcriptomic and outcome data from patient cohorts, this approach revealed that highly specialized mesenchymal cells, which create chemokine gradients in normal lymph nodes, downregulate chemokines responsible for the maintenance of tissue organization and enter a dysfunctional state characterized by inflammatory and fibrotic phenotypes. In silico modelling of intercellular attractions based on receptor ligand expression levels recapitulated lymphoma specific cellular neighborhoods and revealed that DLBCL specific chemokine signatures were sufficient to explain the loss of lymph node organization in DLBCL. In addition to the loss of mesenchymal-derived chemokine gradients, inflammatory immune cells create ectopic sources of chemokines in diffusely growing lymphomas, further disturbing the highly orchestrated chemokine gradients. Ongoing Trial Keywords: Bioinformatics, Computational and Systems Biology, Genomics, Epigenomics, and Other -Omics, Microenvironment No conflicts of interests pertinent to the abstract.
Abstract Infections are a key source of stress to the hematopoietic system. While infections consume short-lived innate immune cells, their recovery depends on quiescent hematopoietic stem cells (HSCs) with long-term self-renewal capacity. Both chronic inflammatory stress and bacterial infections compromise competitive HSC capacity and cause bone marrow (BM) failure. However, our understanding of how HSCs act during acute and contained infections remains incomplete. Here, we used advanced chimeric and genetic mouse models in combination with pharmacological interventions to dissect the complex nature of the acute systemic response of HSCs to lipopolysaccharide (LPS), a well-established model for inducing inflammatory stress. Acute LPS challenge transiently induced proliferation of quiescent HSCs in vivo. This response was not only mediated via direct LPS-TLR4 conjugation on HSCs but also involved indirect TLR4 signaling in CD115+ monocytic cells, inducing a complex proinflammatory cytokine cascade in BM. Downstream of LPS-TLR4 signaling, the combined action of proinflammatory cytokines such as interferon (IFN)α, IFNγ, tumor necrosis factor-α, interleukin (IL)-1α, IL-1β, and many others is required to mediate full HSC activation in vivo. Together, our study reveals detailed mechanistic insights into the interplay of proinflammatory cytokine-induced molecular pathways and cell types that jointly orchestrate the complex process of emergency hematopoiesis and HSC activation upon LPS exposure in vivo.
Background: Multiple myeloma is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, it remains incurable and better risk stratification as well as new therapies are therefore highly needed. While genomic alterations and gene expression profiles have been extensively studied that led to new insights into disease biology and improved prognostic models, the proteome of multiple myeloma has not been systematically assessed. Aims: To provide a comprehensive multi-omics analysis of plasma cell malignancies. Methods: Samples from 138 patients with plasma cell malignancies including 114 cases of newly diagnosed multiple myeloma treated within trials of the German Study Group Multiple Myeloma (DSMM) with available clinical data, were analyzed by deep tandem mass tags (TMT)-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing. Results: TMT-based proteomics of multiple myeloma samples identified a total of 8,336 proteins and 25,131 phosphopeptides in at least half of the samples. Among the highly expressed proteins were established markers of multiple myeloma including the transcription factor IRF4, and cell-surface proteins CD38 and CD138. Primary genetic events had profound effects on the expression levels of proteins in cis and trans. Most significant proteins and phosphopeptides in the mutually exclusive genetic subtypes of multiple myeloma include the translocation partners CCND1 in cases with t(11;14) with subsequent increase of CDK4 and RB1 phosphorylation and NSD2 in cases with t(4;14), as well as proteins upregulated specifically in hyperdiploid myeloma, such as USP4 (Chr 3p) and PKM (Chr 15q). However, protein levels and activity could not necessarily be inferred by genetic alterations or RNA expression which may affect targeted therapy approaches in multiple myeloma. For example, FGFR3, the second translocation partner in t(4;14) cases, could only be detected in 63% of cases with t(4;14) and vice versa also non-t(4;14) cases had above average FGFR3 expression. FGFR3 protein expression was highly associated with FGFR3 signaling and in myeloma cell lines FGFR3 expression predicted sensitivity to FGFR3 inhibition. MCL1, which is encoded on chr 1q and currently being investigated as a therapeutic target in multiple myeloma in clinical trials, was elevated in only 70% of cases with 1q gain but also in 34% of patients without a detected 1q alteration. Cases with t(11;14) had extensive deregulation of proteins involved in the apoptotic pathway and B-cell markers which may be linked to the particular sensitivity to BCL2 inhibition of this subgroup. Comparison with the proteome of plasma cells and hematopoietic progenitor cells isolated from healthy donors and integration with CRISPR/Cas9 screens revealed new potential disease drivers and therapeutic targets of multiple myeloma. In addition, we found surface proteins with selective expression on multiple myeloma cells as compared to healthy bone marrow cells which could be confirmed by single-cell RNA sequencing. Correlation of protein and phosphopeptide levels with outcome revealed a protein high-risk signature consisting of eight proteins that is highly predictive for progression-free and overall survival in intensively treated patients and independent of cytogenetic-based risk stratification. This high-risk signature was furthermore enriched in plasma-cell leukemia, the most aggressive plasma cell malignancy. Summary/Conclusion: Our findings provide new insights in the biology of multiple myeloma and highlight the broad implications of proteomics studies in hematologic malignancies.Keywords: Proteomics, Myeloma, Multiple myeloma
