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D'Souza, D.

Publications and source records attributed to D'Souza, D..

6 recordsLinked to original sources

Genetic drivers shape TREM2-dependent myeloid responses and glioblastoma progression

Glioblastoma (GBM) is characterized by a heterogeneous, myeloid-enriched, and highly immunosuppressive microenvironment. TREM2 regulates microglial and macrophage functions, but its role in GBM remains unclear. We investigated whether genetic drivers determine the effects of TREM2 using de novo and orthotopic transplantable murine models of Nf1-silenced/Ras-driven and PDGFB-driven GBM. To this end, we combined immune profiling, functional assays, secretome analysis, and single-cell RNA sequencing with bone marrow chimeras and conditional Trem2 deletion strategies. Trem2 deficiency prolonged survival and reduced tumor burden in Nf1-silenced/Ras-driven GBM, whereas it increased tumor burden without affecting survival in PDGFB-driven GBM. These different outcomes were accompanied by distinct changes in myeloid composition and soluble mediators. TREM2 was required for bone marrow-derived macrophage migration and microglial process extension towards Ras-derived, but not PDGFB-derived, tumor-conditioned medium. In contrast, both models showed impaired microglial efferocytosis. Single-cell RNA sequencing analysis of Nf1-silenced GBM showed that Trem2 loss shifted myeloid cells from disease-associated, pro-inflammatory states to a more homeostatic state. Bone marrow chimeras supported a tumor-promoting role for TREM2 in microglia, rather than infiltrating myeloid cells in Ras-driven GBM. In addition, conditional deletion of Trem2 before tumor implantation prolonged survival, whereas deletion after tumor establishment did not. These findings identify genetic context and timing of TREM2 activity as determinants of its effects on GBM progression, highlighting driver-dependent myeloid responses as considerations for developing TREM2-directed therapies in glioblastoma.

neuroscience↗

Dendritic cells type 1 control the formation, maintenance, and function of tertiary lymphoidstructures in cancer

Tertiary lymphoid structures (TLS) are organized immune cell aggregates that arise in chronic inflammatory conditions. In cancer, TLS are associated with better prognosis and enhanced response to immunotherapy, making these structures attractive therapeutic targets. However, the mechanisms regulating TLS formation and maintenance in cancer are incompletely understood. Using spatial transcriptomics and multiplex imaging across various human tumors, we found an enrichment of mature dendritic cells (DC) expressing high levels of CCR7 in TLS, prompting us to investigate the role of DC in the formation and maintenance of TLS in solid tumors. To address this, we developed a novel murine model of non-small cell lung cancer (NSCLC) that forms mature TLS, containing B cell follicles with germinal centers and T cell zones with T follicular helper cells (TFH) and TCF1+PD-1+ progenitor exhausted CD8+ T cells (Tpex). Here we show that, during the early stages of tumor development, TLS formation relies on IFN{gamma}-driven maturation of the conventional DC type 1 (cDC1) subset, their migration to tumor-draining lymph nodes (tdLN), and recruitment of activated T cells to the tumor site. As tumors progress, TLS maintenance becomes independent of T cell egress from tdLN, coinciding with a significant reduction of cDC1 migration to tdLN. Instead, mature cDC1 accumulate within intratumoral CCR7 ligand-enriched stromal hubs. Notably, timed depletion of cDC1 or disruption of their migration to these stromal hubs after TLS are formed alters TLS maintenance. Importantly, we found that cDC1-mediated antigen presentation to both CD4+ and CD8+ T cells and intact CD40 signaling, is critical for the maintenance of TLS, the preservation of the TFH cell pool, the formation of germinal center and the production of tumor-specific IgG antibodies. These findings underscore the key role of mature cDC1 in establishing and maintaining functional TLS within tumor lesions and highlight the potential for cDC1-targeting therapies as a promising strategy to enhance TLS function and improve anti-tumor immunity in patients with cancer.

immunology↗

Informing biologically relevant signal from spatial transcriptomic data

Visium is a spatial sequencing technology that utilizes messenger RNA (mRNA) to spatially map gene expression within tissues. Despite its potential, research utilizing deconvolution tools and exploring microenvironment dynamics remains challenging. We address this gap by benchmarking deconvolution tools across diverse biological contexts, identifying optimal methodologies. Subsequently, we introduce a novel pipeline integrating advanced deconvolution techniques and novel tools for reproducible tissue microenvironment analysis. Through this approach, we uncover intricate immune aggregate biology, highlighting the power of our methodology in unraveling complex biological phenomena.

bioinformatics↗

A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma

Multiple Myeloma (MM) remains incurable despite advances in treatment options. Although tumor subtypes and specific DNA abnormalities are linked to worse prognosis, the impact of immune dysfunction on disease emergence and/or treatment sensitivity remains unclear. We established a harmonized consortium to generate an Immune Atlas of MM aimed at informing disease etiology, risk stratification, and potential therapeutic strategies. We generated a transcriptome profile of 1,149,344 single cells from the bone marrow of 263 newly diagnosed patients enrolled in the CoMMpass study and characterized immune and hematopoietic cell populations. Associating cell abundances and gene expression with disease progression revealed the presence of a proinflammatory immune senescence-associated secretory phenotype in rapidly progressing patients. Furthermore, signaling analyses suggested active intercellular communication involving APRIL-BCMA, potentially promoting tumor growth and survival. Finally, we demonstrate that integrating immune cell levels with genetic information can significantly improve patient stratification.

genomics↗

Shift of lung macrophage composition is associated with COVID-19 disease severity and recovery

Though it has been 2 years since the start of the Coronavirus Disease 19 (COVID-19) pandemic, COVID-19 continues to be a worldwide health crisis. Despite the development of preventive vaccines, very little progress has been made to identify curative therapies to treat COVID-19 and other inflammatory diseases which remain a major unmet need in medicine. Our study sought to identify drivers of disease severity and death to develop tailored immunotherapy strategies to halt disease progression. Here we assembled the Mount Sinai COVID-19 Biobank which was comprised of ~600 hospitalized patients followed longitudinally during the peak of the pandemic. Moderate disease and survival were associated with a stronger antigen (Ag) presentation and effector T cell signature, while severe disease and death were associated with an altered Ag presentation signature, increased numbers of circulating inflammatory, immature myeloid cells, and extrafollicular activated B cells associated with autoantibody formation. Strikingly, we found that in severe COVID-19 patients, lung tissue resident alveolar macrophages (AM) were not only severely depleted, but also had an altered Ag presentation signature, and were replaced by inflammatory monocytes and monocyte-derived macrophages (MoM{Phi}). Notably, the size of the AM pool correlated with recovery or death, while AM loss and functionality were restored in patients that recovered. These data therefore suggest that local and systemic myeloid cell dysregulation is a driver of COVID-19 severity and that modulation of AM numbers and functionality in the lung may be a viable therapeutic strategy for the treatment of critical lung inflammatory illnesses.

immunology↗

Multimodal Single-Cell Characterization of the Human Granulocyte Lineage

High throughput single cell transcriptomics (scRNA-seq) has been successfully applied to characterize immune cell heterogeneity across a diverse range of settings; however, analysis of human granulocytes remains a significant challenge due to their low gene expression transcript detection. Consequently, granulocytes are typically either absent or highly under-represented and inaccurately enumerated in most human scRNA-seq datasets. Here, we apply multi-modal CITE-seq profiling to characterize granulocytes in human whole blood and bone marrow, and we show that these populations can be accurately detected and analyzed using the antibody-based modality, and that their frequencies and phenotype align well with antibody-based characterization of the same samples using CyTOF. These analyses also clearly highlight extremely low gene transcript detection across the entire granulocyte lineage including the earliest neutrophil progenitor populations when using the 10X Genomics platform. By contrast, when performing parallel analyses of the same samples using the BD Rhapsody platform, we recovered a much higher proportion of granulocyte gene transcripts, enabling true multi-modal characterization of human granulocyte heterogeneity.

immunology↗