logo logo
Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging. Goltsev Yury,Samusik Nikolay,Kennedy-Darling Julia,Bhate Salil,Hale Matthew,Vazquez Gustavo,Black Sarah,Nolan Garry P Cell A highly multiplexed cytometric imaging approach, termed co-detection by indexing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an in situ polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell-interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed spatial cytometry demonstrated here allows for quantitative systemic characterization of tissue architecture in normal and clinically aberrant samples. 10.1016/j.cell.2018.07.010
Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients. NPJ digital medicine Cellular subpopulations within the colorectal tumor microenvironment (TME) include CD3 and CD8 lymphocytes, CD68 and CD163 macrophages, and tumor buds (TBs), all of which have known prognostic significance in stage II colorectal cancer. However, the prognostic relevance of their spatial interactions remains unknown. Here, by applying automated image analysis and machine learning approaches, we evaluate the prognostic significance of these cellular subpopulations and their spatial interactions. Resultant data, from a training cohort retrospectively collated from Edinburgh, UK hospitals ( = 113), were used to create a combinatorial prognostic model, which identified a subpopulation of patients who exhibit 100% survival over a 5-year follow-up period. The combinatorial model integrated lymphocytic infiltration, the number of lymphocytes within 50-μm proximity to TBs, and the CD68/CD163 macrophage ratio. This finding was confirmed on an independent validation cohort, which included patients treated in Japan and Scotland ( = 117). This work shows that by analyzing multiple cellular subpopulations from the complex TME, it is possible to identify patients for whom surgical resection alone may be curative. 10.1038/s41746-020-0275-x
Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics. Allam Mayar,Cai Shuangyi,Coskun Ahmet F NPJ precision oncology Cancers exhibit functional and structural diversity in distinct patients. In this mass, normal and malignant cells create tumor microenvironment that is heterogeneous among patients. A residue from primary tumors leaks into the bloodstream as cell clusters and single cells, providing clues about disease progression and therapeutic response. The complexity of these hierarchical microenvironments needs to be elucidated. Although tumors comprise ample cell types, the standard clinical technique is still the histology that is limited to a single marker. Multiplexed imaging technologies open new directions in pathology. Spatially resolved proteomic, genomic, and metabolic profiles of human cancers are now possible at the single-cell level. This perspective discusses spatial bioimaging methods to decipher the cascade of microenvironments in solid and liquid biopsies. A unique synthesis of top-down and bottom-up analysis methods is presented. Spatial multi-omics profiles can be tailored to precision oncology through artificial intelligence. Data-driven patient profiling enables personalized medicine and beyond. 10.1038/s41698-020-0114-1
Biomarkers Associated with Beneficial PD-1 Checkpoint Blockade in Non-Small Cell Lung Cancer (NSCLC) Identified Using High-Plex Digital Spatial Profiling. Zugazagoitia Jon,Gupta Swati,Liu Yuting,Fuhrman Kit,Gettinger Scott,Herbst Roy S,Schalper Kurt A,Rimm David L Clinical cancer research : an official journal of the American Association for Cancer Research PURPOSE:Only a minority of patients with advanced non-small cell lung cancer (NSCLC) truly benefits from single-agent PD-1 checkpoint blockade, and more robust predictive biomarkers are needed. EXPERIMENTAL DESIGN:We assessed tumor samples from 67 immunotherapy-treated NSCLC cases represented in a tissue microarray, 53 of whom had pretreatment samples and received monotherapy. Using GeoMx Digital Spatial Profiling System (NanoString Technologies), we quantified 39 immune parameters simultaneously in four tissue compartments defined by fluorescence colocalization [tumor (panCK), leucocytes (CD45), macrophages (CD68), and nonimmune stroma]. RESULTS:A total of 156 protein variables were generated per case. In the univariate unadjusted analysis, we found 18 markers associated with outcome in spatial context, five of which remained significant after multiplicity adjustment. In the multivariate analysis, high levels of CD56 and CD4 measured in the CD45 compartment were the only markers that were predictive for all clinical outcomes, including progression-free survival (PFS, HR: 0.24, = 0.006; and HR: 0.31, = 0.011, respectively), and overall survival (OS, HR: 0.26, = 0.014; and HR: 0.23, = 0.007, respectively). Then, using an orthogonal method based on multiplex immunofluorescence and cell counting (inForm), we validated that high CD56 immune cell counts in the stroma were associated with PFS and OS in the same cohort. CONCLUSIONS:This pilot scale discovery study shows the potential of the digital spatial profiling technology in the identification of spatially informed biomarkers of response to PD-1 checkpoint blockade in NSCLC. We identified a number of relevant candidate immune predictors in spatial context that deserve validation in larger independent cohorts. 10.1158/1078-0432.CCR-20-0175
A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging. Keren Leeat,Bosse Marc,Marquez Diana,Angoshtari Roshan,Jain Samir,Varma Sushama,Yang Soo-Ryum,Kurian Allison,Van Valen David,West Robert,Bendall Sean C,Angelo Michael Cell The immune system is critical in modulating cancer progression, but knowledge of immune composition, phenotype, and interactions with tumor is limited. We used multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to simultaneously quantify in situ expression of 36 proteins covering identity, function, and immune regulation at sub-cellular resolution in 41 triple-negative breast cancer patients. Multi-step processing, including deep-learning-based segmentation, revealed variability in the composition of tumor-immune populations across individuals, reconciled by overall immune infiltration and enriched co-occurrence of immune subpopulations and checkpoint expression. Spatial enrichment analysis showed immune mixed and compartmentalized tumors, coinciding with expression of PD1, PD-L1, and IDO in a cell-type- and location-specific manner. Ordered immune structures along the tumor-immune border were associated with compartmentalization and linked to survival. These data demonstrate organization in the tumor-immune microenvironment that is structured in cellular composition, spatial arrangement, and regulatory-protein expression and provide a framework to apply multiplexed imaging to immune oncology. 10.1016/j.cell.2018.08.039
The single-cell pathology landscape of breast cancer. Nature Single-cell analyses have revealed extensive heterogeneity between and within human tumours, but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data available for 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis. 10.1038/s41586-019-1876-x
A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry. Cell metabolism Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing β cells. A comprehensive picture of the changes during T1D development is lacking due to limited sample availability, inability to sample longitudinally, and the paucity of technologies enabling comprehensive tissue profiling. Here, we analyzed 1,581 islets from 12 human donors, including eight with T1D, using imaging mass cytometry (IMC). IMC enabled simultaneous measurement of 35 biomarkers with single-cell and spatial resolution. We performed pseudotime analysis of islets through T1D progression from snapshot data to reconstruct the evolution of β cell loss and insulitis. Our analyses revealed that β cell destruction is preceded by a β cell marker loss and by recruitment of cytotoxic and helper T cells. The approaches described herein demonstrate the value of IMC for improving our understanding of T1D pathogenesis, and our data lay the foundation for hypothesis generation and follow-on experiments. 10.1016/j.cmet.2018.11.014
Multiplexed In Situ Imaging Mass Cytometry Analysis of the Human Endocrine Pancreas and Immune System in Type 1 Diabetes. Cell metabolism The interaction between the immune system and endocrine cells in the pancreas is crucial for the initiation and progression of type 1 diabetes (T1D). Imaging mass cytometry (IMC) enables multiplexed assessment of the abundance and localization of more than 30 proteins on the same tissue section at 1-μm resolution. Herein, we have developed a panel of 33 antibodies that allows for the quantification of key cell types including pancreatic exocrine cells, islet cells, immune cells, and stromal components. We employed this panel to analyze 12 pancreata obtained from donors with clinically diagnosed T1D and 6 pancreata from non-diabetic controls. In the pancreata from donors with T1D, we simultaneously visualized significant alterations in islet architecture, endocrine cell composition, and immune cell presentation. Indeed, we demonstrate the utility of IMC to investigate complex events on the cellular level that will provide new insights on the pathophysiology of T1D. 10.1016/j.cmet.2019.01.003
Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry. Schulz Daniel,Zanotelli Vito Riccardo Tomaso,Fischer Jana Raja,Schapiro Denis,Engler Stefanie,Lun Xiao-Kang,Jackson Hartland Warren,Bodenmiller Bernd Cell systems To build comprehensive models of cellular states and interactions in normal and diseased tissue, genetic and proteomic information must be extracted with single-cell and spatial resolution. Here, we extended imaging mass cytometry to enable multiplexed detection of mRNA and proteins in tissues. Three mRNA target species were detected by RNAscope-based metal in situ hybridization with simultaneous antibody detection of 16 proteins. Analysis of 70 breast cancer samples showed that HER2 and CK19 mRNA and protein levels are moderately correlated on the single-cell level, but that only HER2, and not CK19, has strong mRNA-to-protein correlation on the cell population level. The chemoattractant CXCL10 was expressed in stromal cell clusters, and the frequency of CXCL10-expressing cells correlated with T cell presence. Our flexible and expandable method will allow an increase in the information content retrieved from patient samples for biomedical purposes, enable detailed studies of tumor biology, and serve as a tool to bridge comprehensive genomic and proteomic tissue analysis. 10.1016/j.cels.2017.12.001
A 40-Marker Panel for High Dimensional Characterization of Cancer Immune Microenvironments by Imaging Mass Cytometry. Ijsselsteijn Marieke E,van der Breggen Ruud,Farina Sarasqueta Arantza,Koning Frits,de Miranda Noel F C C Frontiers in immunology Multiplex immunophenotyping technologies are indispensable for a deeper understanding of biological systems. Until recently, high-dimensional cellular analyses implied the loss of tissue context as they were mostly performed in single-cell suspensions. The advent of imaging mass cytometry introduced the possibility to simultaneously detect a multitude of cellular markers in tissue sections. This technique can be applied to various tissue sources including snap-frozen and formalin-fixed, paraffin-embedded (FFPE) tissues. However, a number of methodological challenges must be overcome when developing large antibody panels in order to preserve signal intensity and specificity of antigen detection. We report the development of a 40-marker panel for imaging mass cytometry on FFPE tissues with a particular focus on the study of cancer immune microenvironments. It comprises a variety of immune cell markers including lineage and activation markers as well as surrogates of cancer cell states and tissue-specific markers (e.g., stroma, epithelium, vessels) for cellular contextualization within the tissue. Importantly, we developed an optimized workflow for maximum antibody performance by separating antibodies into two distinct incubation steps, at different temperatures and incubation times, shown to significantly improve immunodetection. Furthermore, we provide insight into the antibody validation process and discuss why some antibodies and/or cellular markers are not compatible with the technique. This work is aimed at supporting the implementation of imaging mass cytometry in other laboratories by describing methodological procedures in detail. Furthermore, the panel described here is an excellent immune monitoring tool that can be readily applied in the context of cancer research. 10.3389/fimmu.2019.02534
Immune monitoring using mass cytometry and related high-dimensional imaging approaches. Hartmann Felix J,Bendall Sean C Nature reviews. Rheumatology The cellular complexity and functional diversity of the human immune system necessitate the use of high-dimensional single-cell tools to uncover its role in multifaceted diseases such as rheumatic diseases, as well as other autoimmune and inflammatory disorders. Proteomic technologies that use elemental (heavy metal) reporter ions, such as mass cytometry (also known as CyTOF) and analogous high-dimensional imaging approaches (including multiplexed ion beam imaging (MIBI) and imaging mass cytometry (IMC)), have been developed from their low-dimensional counterparts, flow cytometry and immunohistochemistry, to meet this need. A growing number of studies have been published that use these technologies to identify functional biomarkers and therapeutic targets in rheumatic diseases, but the full potential of their application to rheumatic disease research has yet to be fulfilled. This Review introduces the underlying technologies for high-dimensional immune monitoring and discusses aspects necessary for their successful implementation, including study design principles, analytical tools and future developments for the field of rheumatology. 10.1038/s41584-019-0338-z
Decoding human fetal liver haematopoiesis. Nature Definitive haematopoiesis in the fetal liver supports self-renewal and differentiation of haematopoietic stem cells and multipotent progenitors (HSC/MPPs) but remains poorly defined in humans. Here, using single-cell transcriptome profiling of approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells, we identify the repertoire of human blood and immune cells during development. We infer differentiation trajectories from HSC/MPPs and evaluate the influence of the tissue microenvironment on blood and immune cell development. We reveal physiological erythropoiesis in fetal skin and the presence of mast cells, natural killer and innate lymphoid cell precursors in the yolk sac. We demonstrate a shift in the haemopoietic composition of fetal liver during gestation away from being predominantly erythroid, accompanied by a parallel change in differentiation potential of HSC/MPPs, which we functionally validate. Our integrated map of fetal liver haematopoiesis provides a blueprint for the study of paediatric blood and immune disorders, and a reference for harnessing the therapeutic potential of HSC/MPPs. 10.1038/s41586-019-1652-y
Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma. Cell To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer. 10.1016/j.cell.2020.05.039
Mass Cytometry Imaging for the Study of Human Diseases-Applications and Data Analysis Strategies. Frontiers in immunology High parameter imaging is an important tool in the life sciences for both discovery and healthcare applications. Imaging Mass Cytometry (IMC) and Multiplexed Ion Beam Imaging (MIBI) are two relatively recent technologies which enable clinical samples to be simultaneously analyzed for up to 40 parameters at subcellular resolution. Importantly, these "Mass Cytometry Imaging" (MCI) modalities are being rapidly adopted for studies of the immune system in both health and disease. In this review we discuss, first, the various applications of MCI to date. Second, due to the inherent challenge of analyzing high parameter spatial data, we discuss the various approaches that have been employed for the processing and analysis of data from MCI experiments. 10.3389/fimmu.2019.02657