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., Nat. Biotechnol.  31 Aug 2020: s41587-020-0651-8
doi: 10.1038/s41587-020-0651-8

Abstract: Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

Hwang, et al., BioRxiv  25 Aug 2020: 10.1101/2020.08.25.267336
PREPRINT doi: 10.1101/2020.08.25.267336

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

doi: https://doi.org/10.1101/2020.06.08.140426

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

doi: https://doi.org/10.1101/2020.06.08.140426

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

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

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

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.

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.

Rimm.  Nature Methods 2014 11, pages381–383 (2014)

doi: 10.1038/nmeth.2896