scholarly journals Single Cell Spatial Analysis Reveals the Topology of Immunomodulatory Purinergic Signaling in Glioblastoma

2022 ◽  
Author(s):  
Shannon Coy ◽  
Shu Wang ◽  
Sylwia A Stopka ◽  
Jia-Ren Lin ◽  
Rumana Rashid ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Organization ◽  
Purinergic Signaling ◽  
Tissue Imaging ◽  
Spatial Proximity ◽  
Spatially Resolved ◽  
Lineage Differentiation ◽  
Regulatory Enzymes ◽  
Immunosuppressive Microenvironment ◽  
Cd73 Expression

Glioblastoma develops an immunosuppressive microenvironment that fosters tumorigenesis and resistance to current therapeutic strategies. Here we use multiplexed tissue imaging and single-cell RNA-sequencing to characterize the composition, spatial organization, and clinical significance of extracellular purinergic signaling in glioblastoma. We show that glioblastoma exhibit strong expression of CD39 and CD73 ectoenzymes, correlating with increased adenosine levels. Microglia are the predominant source of CD39, while CD73 is principally expressed by tumor cells, particularly in tumors with amplification of EGFR and astrocyte-like differentiation. Spatially-resolved single-cell analyses demonstrate strong spatial correlation between tumor CD73 and microglial CD39, and that their spatial proximity is associated with poor clinical outcomes. Together, this data reveals that tumor CD73 expression correlates with tumor genotype, lineage differentiation, and functional states, and that core purine regulatory enzymes expressed by neoplastic and tumor-associated myeloid cells interact to promote a distinctive adenosine-rich signaling niche and immunosuppressive microenvironment potentially amenable to therapeutic targeting.

scholarly journals TAMI-45. PHENOGENOMIC CHARACTERIZATION OF IMMUNOMODULATORY PURINERGIC SIGNALING IN GLIOBLASTOMA

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii222-ii223
Author(s):  
Shannon Coy ◽  
Rumana Rashid ◽  
Sylwia Stopka ◽  
Jia-Ren Lin ◽  
Philipp Euskirchen ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Single Cell ◽  
Purinergic Signaling ◽  
Progression Free Survival ◽  
Tissue Imaging ◽  
Phenotypic Properties ◽  
Spatially Resolved ◽  
Therapeutic Benefits ◽  
Adenosine Concentration ◽  
Cd73 Expression

Abstract INTRODUCTION Purinergic signaling plays critical roles in the regulation of tumor growth and anti-tumor immunity via autocrine/paracrine binding of metabolites to receptors on neoplastic and non-neoplastic populations. Extracellular purine concentrations are mediated by the ectonucleotidase enzymes CD39 and CD73, which catabolize ATP to adenosine. Within tumors such as glioblastoma, neoplastic, immune, and stromal cells expressing these enzymes may co-localize to generate immunosuppressive adenosine-rich environments. However, the composition, architecture, and phenotypic properties of these tumor ecosystems and their relationship to tumor genotype are poorly characterized. METHODS We quantified CD73 expression by immunohistochemistry in a cohort of CNS tumors [meningiomas(n=222), gliomas(n=244), ependymomas(n=44), medulloblastomas(n=24), and craniopharyngiomas(n=38)]. We used publicly-available single-cell RNA-seq data and 36-marker multiplexed tissue imaging (t-CyCIF) of 139 clinically and genomically annotated glioblastoma resections to characterize CD39 and CD73-expressing populations, define the immune architecture and tumor cell-states at single cell resolution, and identify markers of clinical outcome. We used mass spectrometry imaging (MALDI-MSI) to generate spatially-resolved quantification of purine metabolite levels in glioblastoma resections (n=10). RESULTS CD73 exhibited strong expression in a subset of gliomas and meningiomas but was typically not expressed in ependymomas or medulloblastomas. CD73 expression correlated with poor progression-free-survival in IDH-wildtype glioblastoma (p=0.04). scRNA-seq and t-CyCIF in glioblastoma showed CD73 expression in tumor cells, and CD39 expression in macrophages and endothelial cells. MALDI-MSI showed significantly greater adenosine concentrations (3.5-fold;p=0.04) in glioblastomas with high CD73 expression. scRNA-seq showed direct correlations between stem-like mRNA expression, proliferation, and CD73 expression in DIPG. CD73 expression significantly correlated with EGFR amplification, interferon signaling, and PD-L1 expression in glioblastoma. CONCLUSIONS Phenogenomic analysis of purinergic immunomodulatory signaling revealed significant interplay between CD73 activity and genotype, adenosine concentration, differentiation-state, clinical outcome, and possible interaction between CD39-positive macrophages and CD73-positive neoplastic cells. Anti-CD73 therapy may provide therapeutic benefits in glioblastoma by blunting immunosuppressive and oncogenic adenosine signaling.

scholarly journals Combined single-cell and spatial transcriptomics reveals the molecular, cellular and spatial bone marrow niche organization

2019 ◽  
Author(s):  
Chiara Baccin ◽  
Jude Al-Sabah ◽  
Lars Velten ◽  
Patrick M. Helbling ◽  
Florian Grünschläger ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Single Cell ◽  
Spatial Organization ◽  
Cell Types ◽  
Bone Marrow Niche ◽  
Cellular Composition ◽  
Spatially Resolved ◽  
Resident Cell ◽  
Cell Gene Expression ◽  
Novel Strategy

SUMMARYThe bone marrow (BM) constitutes the primary site for life-long blood production and skeletal regeneration. However, its cellular composition and the spatial organization into distinct ‘niches’ remains controversial. Here, we combine single-cell and spatially resolved transcriptomics to systematically map the molecular and cellular composition of the endosteal, sinusoidal, and arteriolar BM niches. This allowed us to transcriptionally profile all major BM resident cell types, determine their localization, and clarify the cellular and spatial sources of key growth factors and cytokines. Our data demonstrate that previously unrecognized Cxcl12-abundant reticular (CAR) cell subsets (i.e. Adipo- and Osteo-CAR cells) differentially localize to sinusoidal or arteriolar surfaces, locally act as ‘professional cytokine secreting cells’, and thereby establish distinct peri-vascular micro-niches. Importantly, we also demonstrate that the 3-dimensional organization of the BM can be accurately inferred from single-cell gene expression data using the newly developed RNA-Magnet algorithm. Together, our study reveals the cellular and spatial organization of BM niches, and offers a novel strategy to dissect the complex organization of whole organs in a systematic manner.One Sentence SummaryIntegration of single-cell and spatial transcriptomics reveals the molecular, cellular and spatial organization of bone marrow niches

scholarly journals Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mayar Allam ◽  
Thomas Hu ◽  
Shuangyi Cai ◽  
Krishnan Laxminarayanan ◽  
Robert B. Hughley ◽  
...  
Keyword(s):  
Single Cell ◽  
Biological Tissues ◽  
Chronic Tonsillitis ◽  
Tissue Imaging ◽  
Imaging Data ◽  
Mass Cytometry ◽  
Tissue Sections ◽  
Spatially Resolved ◽  
Cell Granularity ◽  
Health And Disease

AbstractDeep molecular profiling of biological tissues is an indicator of health and disease. We used imaging mass cytometry (IMC) to acquire spatially resolved 20-plex protein data in tissue sections from normal and chronic tonsillitis cases. We present SpatialViz, a suite of algorithms to explore spatial relationships in multiplexed tissue images by visualizing and quantifying single-cell granularity and anatomical complexity in diverse multiplexed tissue imaging data. Single-cell and spatial maps confirmed that CD68+ cells were correlated with the enhanced Granzyme B expression and CD3+ cells exhibited enrichment of CD4+ phenotype in chronic tonsillitis. SpatialViz revealed morphological distributions of cellular organizations in distinct anatomical areas, spatially resolved single-cell associations across anatomical categories, and distance maps between the markers. Spatial topographic maps showed the unique organization of different tissue layers. The spatial reference framework generated network-based comparisons of multiplex data from healthy and diseased tonsils. SpatialViz is broadly applicable to multiplexed tissue biology.

scholarly journals XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment

2021 ◽  
Vol 7 (17) ◽  
pp. eabg4755
Author(s):  
Youjin Lee ◽  
Derek Bogdanoff ◽  
Yutong Wang ◽  
George C. Hartoularos ◽  
Jonathan M. Woo ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Spatial Organization ◽  
Cell Types ◽  
Mouse Tumor ◽  
Spatially Resolved ◽  
Distinct Cell ◽  
Single Cell Rna Sequencing ◽  
A Cell ◽  
Anatomical Space

Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.

scholarly journals Annotation of Spatially Resolved Single-cell Data with STELLAR

2021 ◽  
Author(s):  
Maria Brbic ◽  
Kaidi Cao ◽  
John W Hickey ◽  
Yuqi Tan ◽  
Michael Snyder ◽  
...  
Keyword(s):  
Deep Learning ◽  
Single Cell ◽  
Computational Methods ◽  
Spatial Organization ◽  
Cell Types ◽  
Learning Method ◽  
Spatially Resolved ◽  
Reference Set ◽  
Time Savings ◽  
Cell Data

Spatial protein and RNA imaging technologies have been gaining rapid attention but current computational methods for annotating cells are based on techniques established for dissociated single-cell technologies and thus do not take spatial organization into account. Here we present STELLAR, a geometric deep learning method that utilizes spatial and molecular cell information to automatically assign cell types from an annotated reference set as well as discover new cell types and cell states. STELLAR transfers annotations across different dissection regions, tissues, and donors and detects higher-order tissue structures with dramatic time savings.

scholarly journals Spatiotemporal single-cell RNA sequencing of developing chicken hearts identifies interplay between cellular differentiation and morphogenesis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Madhav Mantri ◽  
Gaetano J. Scuderi ◽  
Roozbeh Abedini-Nassab ◽  
Michael F. Z. Wang ◽  
David McKellar ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Differentiation ◽  
Spatial Organization ◽  
Spatial Information ◽  
Cellular Interactions ◽  
Chicken Heart ◽  
Spatially Resolved ◽  
Expression Of Genes ◽  
Single Cell Rna Sequencing

AbstractSingle-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about tissue morphology and cellular interactions. Here, we combine single-cell and spatial transcriptomics with algorithms for data integration to study the development of the chicken heart from the early to late four-chambered heart stage. We create a census of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions in cardiac lineages defines transcriptional differences between epithelial and mesenchymal cells within the epicardial lineage. Using spatially resolved expression analysis, we identify anatomically restricted expression programs, including expression of genes implicated in congenital heart disease. Last, we discover a persistent enrichment of the small, secreted peptide, thymosin beta-4, throughout coronary vascular development. Overall, our study identifies an intricate interplay between cellular differentiation and morphogenesis.

scholarly journals 920 A single-cell spatially resolved MERFISH map of the colorectal tumor immune microenvironment

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A965-A965
Author(s):  
Colles Price ◽  
Jonathan Chen ◽  
Karin Pelka ◽  
Sherry Chao ◽  
Jiang He ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Spatial Organization ◽  
Single Cells ◽  
Cell Types ◽  
List Type ◽  
Cellular Composition ◽  
Cell Type ◽  
Spatially Resolved

BackgroundUnderstanding the tumor microenvironment (TIME) requires more than just a catalog of cell types and gene programs. It is critical to see the spatial organization of the cells are and where they form multicellular interaction networks. Here we present a single-cell spatially resolved transcriptomic analysis of human mismatch repair deficient (MMRd) and proficient (MMRp) colorectal cancer (CRC) specimens. High tumor mutational burden MMRd tumors are known to have an immune response characterized by higher cytolytic T cell infiltrates compared to MMRp tumors, making them an ideal system for spatial single-cell profiling and understanding how the immune-driven programs differ between these tumors.MethodsMERFISH is a massively multiplexed single molecule imaging technology which can simultaneously capture and measure the quantity and distribution of hundreds to thousands of RNA species within single cells across a tissue.1 We designed a MERFISH library of over 450 genes including genes important to proliferation, apoptosis, immune signaling, immune cell type pathways and other critical pathways in CRC. Patient samples were obtained commercially or through Massachusetts General Hospital. Samples were hybridized with the designed MERFISH library and stained with a cell boundary marker to delineate cells across the tissue. We performed unsupervised clustering to identify cell types and we explored calculated spatial statistics to characterize how the cell type distribution varied between MMRd and MMRp tumors. We identified the cellular composition of each tumor, including immune and stromal cells, and the spatial distribution of these cell types.ResultsUsing MERFISH, we were able to readily identify all cell types and states previously discovered by single-cell RNA sequencing2 in intact patient specimens, thus providing an accurate map of the cellular composition and spatial organization of these cells in the tumor microenvironment. Of note, previously predicted multicellular interaction networks2 appeared as spatially organized structures in the tissue and were distinct in MMRd versus MMRp tumor specimens. Our data provide a richness of concrete hypotheses about which cells are working together and how these cells function cooperatively, which will be critical in advancing immunotherapy in these immunologically distinct types of colorectal cancer.ConclusionsHere we present a single-cell resolved spatial map of the cell types and states in the tumor microenvironment of MMRd and MMRp cancer. This will aid the development of future immunotherapies for CRC patients.ReferencesChen KH, Boettiger AN, Moffitt JR, Wang S, Zhuang X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 2015;348:AAA 6090.Pelka K, Hofree M, Chen J, Sarkizova S, Pirl JD, Jorgji V, et al. Multicellular immune hubs and their organization in MMRd and MMRp colorectal cancer. BioRxiv 2021;426796.Ethics ApprovalAll samples not commercially purchased were collected in accordance with IRB protocol DF/HCC IRB 02-240.

scholarly journals Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region

Science ◽  
2018 ◽  
Vol 362 (6416) ◽  
pp. eaau5324 ◽  
Author(s):  
Jeffrey R. Moffitt ◽  
Dhananjay Bambah-Mukku ◽  
Stephen W. Eichhorn ◽  
Eric Vaughn ◽  
Karthik Shekhar ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Organization ◽  
Social Behaviors ◽  
Cell Types ◽  
Mapping Method ◽  
Preoptic Region ◽  
Neuronal Populations ◽  
Spatially Resolved ◽  
Mechanistic Investigation ◽  
And Function

The hypothalamus controls essential social behaviors and homeostatic functions. However, the cellular architecture of hypothalamic nuclei—including the molecular identity, spatial organization, and function of distinct cell types—is poorly understood. Here, we developed an imaging-based in situ cell-type identification and mapping method and combined it with single-cell RNA-sequencing to create a molecularly annotated and spatially resolved cell atlas of the mouse hypothalamic preoptic region. We profiled ~1 million cells, identified ~70 neuronal populations characterized by distinct neuromodulatory signatures and spatial organizations, and defined specific neuronal populations activated during social behaviors in male and female mice, providing a high-resolution framework for mechanistic investigation of behavior circuits. The approach described opens a new avenue for the construction of cell atlases in diverse tissues and organisms.

scholarly journals Spatiotemporal single-cell RNA sequencing of developing hearts reveals interplay between cellular differentiation and morphogenesis

2020 ◽  
Author(s):  
Madhav Mantri ◽  
Gaetano J. Scuderi ◽  
Roozbeh Abedini Nassab ◽  
Michael F.Z. Wang ◽  
David McKellar ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Differentiation ◽  
Spatial Organization ◽  
Spatial Information ◽  
Cardiac Development ◽  
Cellular Interactions ◽  
Chicken Heart ◽  
Spatially Resolved ◽  
Single Cell Rna Sequencing

ABSTRACTSingle-cell RNA sequencing is a powerful tool to study developmental biology but does not preserve spatial information about cellular interactions and tissue morphology. Here, we combined single-cell and spatial transcriptomics with new algorithms for data integration to study the early development of the chicken heart. We collected data from four key ventricular development stages, ranging from the early chamber formation stage to the late four-chambered stage. We created an atlas of the diverse cellular lineages in developing hearts, their spatial organization, and their interactions during development. Spatial mapping of differentiation transitions revealed the intricate interplay between cellular differentiation and morphogenesis in cardiac cellular lineages. Using spatially resolved expression analysis, we identified anatomically restricted gene expression programs. Last, we discovered a stage-dependent role for the small secreted peptide, thymosin beta-4, in the coordination of multi-lineage cellular populations. Overall, our study identifies key stage-specific regulatory programs that govern cardiac development.

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