Publications & Posters


Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma<span class='publication-meta'>Ji, <i>et al., Cell</i> Jul 2020</span>
Abstract: To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), Ji et al. combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging (MIBI, a multiplexed spatial proteomics platform) 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.

Ji, et al., Cell (2020) July 23


Multiplexed imaging of human tuberculosis granulomas uncovers immunoregulatory features conserved across tissue and blood<span class='publication-meta'>McCaffrey, <i>et al., BioRxiv</i> Jun 2020</span>
Abstract: Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis that is distinctly characterized by granuloma formation within infected tissues. Granulomas are dynamic and organized immune cell aggregates that limit dissemination, but can also hinder bacterial clearance. Consequently, outcome in TB is influenced by how granuloma structure and composition shift the balance between these two functions. To date, our understanding of what factors drive granuloma function in humans is limited. With this in mind, we used Multiplexed Ion Beam Imaging by Time-of-Flight (MIBI-TOF) to profile 37 proteins in tissues from thirteen patients with active TB disease from the U.S. and South Africa. With this dataset, we constructed a comprehensive tissue atlas where the lineage, functional state, and spatial distribution of 19 unique cell subsets were mapped onto eight phenotypically-distinct granuloma microenvironments. This work revealed an immunosuppressed microenvironment specific to TB granulomas with spatially coordinated co-expression of IDO1 and PD-L1 by myeloid cells and proliferating regulatory T cells. Interestingly, this microenvironment lacked markers consistent with Tcell activation, supporting a myeloid-mediated mechanism of immune suppression. We observed similar trends in gene expression of immunoregulatory proteins in a confirmatory transcriptomic analysis of peripheral blood collected from over 1500 individuals with latent or active TB infection and healthy controls across 29 cohorts spanning 14 countries. Notably, PD-L1 gene expression was found to correlate with TB progression and treatment response, supporting its potential use as a blood-based biomarker. Taken together, this study serves as a framework for leveraging independent cohorts and complementary methodologies to understand how local and systemic immune responses are linked in human health and disease.

PREPRINT – McCaffrey, et al., BioRxiv (2020) June 09


Multiplexed ion beam imaging (MIBI) for characterization of the tumor microenvironment across tumor types<span class='publication-meta'>Ptacek, <i>et al., Lab. Invest.</i> Mar 2020</span>

Abstract: An ability to characterize the cellular composition and spatial organization of the tumor microenvironment (TME) using multiplexed IHC has been limited by the techniques available. Here we show the applicability of multiplexed ion beam imaging (MIBI) for cell phenotype identification and analysis of spatial relationships across numerous tumor types. Formalin-fixed paraffin-embedded (FFPE) samples from tumor biopsies were simultaneously stained with a panel of 15 antibodies, each labeled with a specific metal isotope. Multi-step processing produced images of the TME that were further segmented into single cells. Frequencies of different cell subsets and the distributions of nearest neighbor distances between them were calculated using this data. A total of 50 tumor specimens from 15 tumor types were characterized for their immune profile and spatial organization. Most samples showed infiltrating cytotoxic T cells and macrophages present amongst tumor cells. Spatial analysis of the TME in two ovarian serous carcinoma images highlighted differences in the degree of mixing between tumor and immune cells across samples. Identification of admixed PD-L1+ macrophages and PD1+ T cells in an urothelial carcinoma sample allowed for the detailed observations of immune cell subset spatial arrangement. These results illustrate the high-parameter capability of MIBI at a sensitivity and resolution uniquely suited to understanding the complex tumor immune landscape including the spatial relationships of immune and tumor cells and expression of immunoregulatory proteins.

Ptacek, et al., Laboratory Investigation (2020) Mar 23: s41374-020-0417-4

doi: 10.1038/s41374-020-0417-4

Multiplexed single-cell metabolic profiles organize the spectrum of cytotoxic human T cells<span class='publication-meta'>Hartmann, <i>et al., BioRxiv</i> Jan 2020</span>
Abstract: Cellular metabolism regulates immune cell activation, differentiation and effector functions to the extent that its perturbation can augment immune responses. However, the analytical technologies available to study cellular metabolism lack single-cell resolution, obscuring metabolic heterogeneity and its connection to immune phenotype and function. To that end, we utilized high-dimensional, antibody-based technologies to simultaneously quantify the single-cell metabolic regulome in combination with phenotypic identity. Mass cytometry (CyTOF)-based application of this approach to early human T cell activation enabled the comprehensive reconstruction of the coordinated metabolic remodeling of naïve CD8+ T cells and aligned with conventional bulk assays for glycolysis and oxidative phosphorylation. Extending this analysis to a variety of tissue-resident immune cells revealed tissue-restricted metabolic states of human cytotoxic T cells, including metabolically repressed subsets that expressed CD39 and PD1 and that were enriched in colorectal carcinoma versus healthy adjacent tissue. Finally, combining this approach with multiplexed ion beam imaging by time-of-flight (MIBI-TOF) demonstrated the existence of spatially enriched metabolic neighborhoods, independent of cell identity and additionally revealed exclusion of metabolically repressed cytotoxic T cell states from the tumor-immune boundary in human colorectal carcinoma. Overall, we provide an approach that permits the robust approximation of metabolic states in individual cells along with multimodal analysis of cell identity and functional characteristics that can be applied to human clinical samples to study cellular metabolism how it may be perturbed to affect immunological outcomes.

Hartmann, et al., BioRxiv  17 Jan 2020: 10.1101/2020.01.17.909796

PREPRINT doi: 10.1101/2020.01.17.909796

MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure<span class='publication-meta'>Keren, <i>et al., Science Advances</i> Oct 2019</span>
Abstract: Understanding tissue structure and function requires tools that quantify the expression of multiple proteins while preserving spatial information. Here, we describe MIBI-TOF (multiplexed ion beam imaging by time of flight), an instrument that uses bright ion sources and orthogonal time-of-flight mass spectrometry to image metal-tagged antibodies at subcellular resolution in clinical tissue sections. We demonstrate quantitative, full periodic table coverage across a five-log dynamic range, imaging 36 labeled antibodies simultaneously with histochemical stains and endogenous elements. We image fields of view up to 800 μm × 800 μm at resolutions down to 260 nm with sensitivities approaching single-molecule detection. We leverage these properties to interrogate intrapatient heterogeneity in tumor organization in triple-negative breast cancer, revealing regional variability in tumor cell phenotypes in contrast to a structured immune response. Given its versatility and sample back-compatibility, MIBI-TOF is positioned to leverage existing annotated, archival tissue cohorts to explore emerging questions in cancer, immunology, and neurobiology.

Keren, et al., Science Advances  09 Oct 2019: 5(10), eaax5851

doi: 10.1126/sciadv.aax5851

A structured tumor-immune microenvironment in triple negative breast cancer revealed by multiplexed ion beam imaging<span class='publication-meta'>Keren, <em>et al, Cell</em> Sept 2018</span>
Abstract: 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 en-riched 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.

Keren et al. Cell, Volume 174, Issue 6, P1373-1387. E19. September 06, 2018

doi: 10.1016/j.cell.2018.08.039

Tissue imaging by mass spectrometry: a practical guide for the medicinal chemist<span class='publication-meta'>Johnson, <em>et al., ACS Medical Chemistry Letters</em> Jan 2019</span>
Abstract: Understanding the tissue distribution of therapeutic molecules is often critical for assessing their efficacy and toxicity. Unfortunately, standard methods for monitoring localized drug distribution are resource-intensive and are typically performed late in the discovery process. As a result, early development efforts often progress without detailed information on the effect that changes in structure and/or formulation have on drug localization. Recent innovations in mass spectrometry (MS) provide new options for mapping the spatial distribution of drug in tissue, and allow parallel detection of endogenous species. These advances are improving access to drug distribution data early in discovery, and provide insight into local biochemical changes that are directly related to drug activity. The literature on these topics is voluminous and the technology is advancing rapidly, offering a bewildering array of options for researchers who are new to the field. To guide medicinal chemists who wish to apply these methods in their research, this technology perspective provides our views on practical applications that are currently enabled by various MS imaging (MSI) approaches, along with recommendations for how best to implement these methods in pharmaceutical R&D.

Johnson et al. ACS Medical Chemistry Letters. January, 2019

Link to publication

Multiplexed ion beam imaging analysis for quantitation of protein expression in cancer tissue sections<span class='publication-meta'>Rost, <em>et al., Lab. Invest.</em> Aug 2017</span>
Abstract: Part of developing therapeutics is the need to identify patients who will respond to treatment. For HER2-targeted therapies, such as trastuzumab, the expression level of HER2 is used to identify patients likely to receive benefit from therapy. Currently, chromogenic immunohistochemistry on patient tumor tissue is one of the methodologies used to assess the expression level of HER2 to determine eligibility for trastuzumab. However, chromogenic staining is fraught with serious drawbacks that influence scoring, which is additionally flawed due to the subjective nature of human/pathologist bias. Thus, to advance drug development and precision medicine, there is a need to develop technologies that are more objective and quantitative through the collection and integration of larger data sets. In proof of concept experiments, we show multiplexed ion beam imaging (MIBI), a novel imaging technology, can quantitate HER2 expression on breast carcinoma tissue with known HER2 status and those values correlate with pathologist-determined IHC scores. The same type of quantitative analysis using the mean pixel value of five individual cells and total pixel count of the entire image was extended to a blinded study of breast carcinoma samples of unknown HER2 scores. Here, a strong correlation between quantitation of HER2 by MIBI analysis and pathologist-derived HER2 IHC score was identified. In addition, a comparison between MIBI analysis and immunofluorescence-based automated quantitative analysis (AQUA) technology, an industry-accepted quantitation system, showed strong correlation in the same blind study. Further comparison of the two systems determined MIBI was comparable to AQUA analysis when evaluated against pathologist-determined scores. Using HER2 as a model, these data show MIBI analysis can quantitate protein expression with greater sensitivity and objectivity compared to standard pathologist interpretation, demonstrating its potential as a technology capable of advancing cancer and patient diagnostics.

Rost et al., Lab Invest.  2017 Aug;97(8):992-1003

doi: 10.1038/labinvest.2017.50.

Multiplexed ion beam imaging of human breast tumors<span class='publication-meta'>Angelo, <em>et al., Nature Medicine</em> Apr 2014</span>
Abstract: Immunohistochemistry (IHC) is a tool for visualizing protein expression that is employed as part of the diagnostic workup for the majority of solid tissue malignancies. Existing IHC methods use antibodies tagged with fluorophores or enzyme reporters that generate colored pigments. Because these reporters exhibit spectral and spatial overlap when used simultaneously, multiplexed IHC is not routinely used in clinical settings. We have developed a method that uses secondary ion mass spectrometry to image antibodies
tagged with isotopically pure elemental metal reporters. Multiplexed ion beam imaging (MIBI) is capable of analyzing up to 100 targets simultaneously over a five-log dynamic range. Here, we used MIBI to analyze formalin-fixed,
paraffin-embedded human breast tumor tissue sections stained with ten labels simultaneously. The resulting data suggest that MIBI can provide new insights into disease pathogenesis that will be valuable for basic research,
drug discovery and clinical diagnostics.

Angelo et al. Nature Medicine 2014 Apr;20(4):436-42.

doi: 10.1038/nm.3488. Epub 2014 Mar 2.

Next-gen immunohistochemistry<span class='publication-meta'>Rimm, <em>et al., Nature Methods</em> 2014 </span>
Rimm.  Nature Methods 2014 11pages381–383 (2014)

doi: 10.1038/nmeth.2896


SITC 2019 – P61

Segmentation and Classification of Single Cells using Multiplexed Ion Beam Imaging (MIBI)

Cancer Immunotherapy
Keystone 2019

Multiplexed Ion Beam Imaging (MIBI) For Characterization of the Tumor
Microenvironment Across Tumor Types

SITC 2018 – P106

Multiplexed Ion Beam Imaging For Characterization of the Tumor Microenvironment Across Tumor Types

SITC Jason poster image

SITC 2018 – P20

A Structured Tumor Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Imaging

SITC Sean poster image

Pathology Visions 2018

Web Application for Management & Visualization of Highly Multiplexed Imaging Data

Digital pathology poster
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