Analyzing proteome topology and function by automated multidimensional fluorescence microscopy

Extracellular vesicles: A bright star of nanomedicine

Extracellular vesicles (EVs) have unique structural, compositional, and morphological characteristics as well as predominant physiochemical stability and biocompatibility properties. They play a crucial role in pathophysiological regulation, and also have broad prospects for clinical application in the diagnosis, prognosis, and therapy of disease, and tissue regeneration and repair. Herein, the biosynthesis and physiological functions and current methods for separation and identification of EVs are summarized. Specifically, engineered EVs may be used to enhance targeted therapy in cancer and repair damaged tissues, and they may be developed as an individualized imaging diagnostic reagent, among other potential applications. We will focus on reviewing recent studies on engineered EVs in which alterations enhanced their therapeutic capability or diagnostic imaging potential via physical, chemical, and biological modification approaches. This review will clarify the superior biological functions and powerful therapeutic potential of EVs, particularly with regard to new designs based on EVs and their utilization in a new generation of nanomedicine diagnosis and treatment platforms.

New technology on the horizon: Fast analytical screening technique FNA (FAST-FNA) enables rapid, multiplex biomarker analysis in head and neck cancers

PD-L1 profiling was recently approved by the US Food and Drug Administration as a companion diagnostic for anti-PD1 treatment in patients with head and neck cancer, ushering in a new era for precision medicine. However, the routine development and implementation of such testing is still limited by current clinical workflows and the lack of better and more comprehensive alternatives. In this review, the authors discuss the real-world challenges of clinically based biomarker testing and highlight the advantages of developing fine-needle aspiration (FNA)-based biomarker testing that would enable frequent and serial tumor sampling. A conceptual and technological innovation is introduced, fast analytical screening technique (FAST)-FNA (FAST chemistry-enabled FNA), which is being developed to inform immunotherapy treatment options in patients with head and neck cancer and to assist with the development of the next generation of predictive biomarkers.

SYLARAS: A Platform for the Statistical Analysis and Visual Display of Systemic Immunoprofiling Data and Its Application to Glioblastoma

Accurately profiling systemic immune responses to cancer initiation and progression is necessary for understanding tumor surveillance and, ultimately, improving therapy. Here, we describe the SYLARAS software tool (systemic lymphoid architecture response assessment) and a dataset collected with SYLARAS that describes the frequencies of immune cells in primary and secondary lymphoid organs and in the tumor microenvironment of mice engrafted with a standard syngeneic glioblastoma (GBM) model. The data resource involves profiles of 5 lymphoid tissues in 48 mice and shows that GBM causes wide-spread changes in the local and systemic immune architecture. We use SYLARAS to identify a subset of CD45R/B220⁺ CD8⁺ T cells that is depleted from circulation but accumulates in the tumor mass and confirm this finding using multiplexed immunofluorescence microscopy. SYLARAS is freely available for download at (https://github.com/gjbaker/sylaras). A record of this paper’s transparent peer review process is included in the Supplemental Information.

Localized tumors such as glioblastoma alter the composition of the immune system in peripheral organs including the spleen, lymph nodes, bone marrow, and thymus. SYLARAS enables efficient, systematic analysis of immune system architecture across many organs and samples to reveal subtle, recurrent changes on a background of between-sample biological variability.

Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We re-engineered co-detection by indexing (CODEX) for paraffin-embedded tissue microarrays, enabling simultaneous profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating how complex biological processes, such as antitumoral immunity, occur through concerted actions of cells and spatial domains.

Fibrosis and Immune Cell Infiltration Are Separate Events Regulated by Cell-Specific Receptor Notch3 Expression

BACKGROUND

Kidney injuries that result in chronic inflammation initiate crosstalk between stressed resident cells and infiltrating immune cells. In animal models, whole-body receptor Notch3 deficiency protects from leukocyte infiltration and organ fibrosis. However, the relative contribution of Notch3 expression in tissue versus infiltrating immune cells is unknown.

METHODS

Chimeric mice deficient for Notch3 in hematopoietic cells and/or resident tissue cells were generated, and kidney fibrosis and inflammation after unilateral ureteral obstruction (UUO) were analyzed. Adoptive transfer of labeled bone marrow-derived cells validated the results in a murine Leishmania ear infection model. In vitro adhesion assays, integrin activation, and extracellular matrix production were analyzed.

RESULTS

Fibrosis follows UUO, but inflammatory cell infiltration mostly depends upon Notch3 expression in hematopoietic cells, which coincides with an enhanced proinflammatory milieu (e.g., CCL2 and CCL5 upregulation). Notch3 expression on CD45⁺ leukocytes plays a prominent role in efficient cell transmigration. Functionally, leukocyte adhesion and integrin activation are abrogated in the absence of receptor Notch3. Chimeric animal models also reveal that tubulointerstitial fibrosis develops, even in the absence of prominent leukocyte infiltrates after ureteral obstruction. Deleting Notch3 receptors on resident cells blunts kidney fibrosis, ablates NF-κB signaling, and lessens matrix deposition.

CONCLUSIONS

Cell-specific receptor Notch3 signaling independently orchestrates leukocyte infiltration and organ fibrosis. Interference with Notch3 signaling may present a novel therapeutic approach in inflammatory as well as fibrotic diseases.

An annotated fluorescence image dataset for training nuclear segmentation methods

Fully-automated nuclear image segmentation is the prerequisite to ensure statistically significant, quantitative analyses of tissue preparations,applied in digital pathology or quantitative microscopy. The design of segmentation methods that work independently of the tissue type or preparation is complex, due to variations in nuclear morphology, staining intensity, cell density and nuclei aggregations. Machine learning-based segmentation methods can overcome these challenges, however high quality expert-annotated images are required for training. Currently, the limited number of annotated fluorescence image datasets publicly available do not cover a broad range of tissues and preparations. We present a comprehensive, annotated dataset including tightly aggregated nuclei of multiple tissues for the training of machine learning-based nuclear segmentation algorithms. The proposed dataset covers sample preparation methods frequently used in quantitative immunofluorescence microscopy. We demonstrate the heterogeneity of the dataset with respect to multiple parameters such as magnification, modality, signal-to-noise ratio and diagnosis. Based on a suggested split into training and test sets and additional single-nuclei expert annotations, machine learning-based image segmentation methods can be trained and evaluated.

Single-cell proteomic analysis

The ability to comprehensively profile proteins in every individual cell of complex biological systems is crucial to advance our understanding of normal physiology and disease pathogenesis. Conventional bulk cell experiments mask the cell heterogeneity in the population, while the single-cell imaging methods suffer from the limited multiplexing capacities. Recent advances in microchip-, mass spectrometry-, and reiterative staining-based technologies have enabled comprehensive protein profiling in single cells. These approaches will bring new insights into a variety of biological and biomedical fields, such as signaling network regulation, cell heterogeneity, tissue architecture, disease diagnosis, and treatment monitoring. In this article, we will review the recent advances in the development of single-cell proteomic technologies, describe their advantages, discuss the current limitations and challenges, and propose potential solutions. We will also highlight the wide applications of these technologies in biology and medicine. This article is categorized under: Cancer > Molecular and Cellular Physiology.

Spatial domain analysis predicts risk of colorectal cancer recurrence and infers associated tumor microenvironment networks

An unmet clinical need in solid tumor cancers is the ability to harness the intrinsic spatial information in primary tumors that can be exploited to optimize prognostics, diagnostics and therapeutic strategies for precision medicine. Here, we develop a transformational spatial analytics computational and systems biology platform (SpAn) that predicts clinical outcomes and captures emergent spatial biology that can potentially inform therapeutic strategies. We apply SpAn to primary tumor tissue samples from a cohort of 432 chemo-naïve colorectal cancer (CRC) patients iteratively labeled with a highly multiplexed (hyperplexed) panel of 55 fluorescently tagged antibodies. We show that SpAn predicts the 5-year risk of CRC recurrence with a mean AUROC of 88.5% (SE of 0.1%), significantly better than current state-of-the-art methods. Additionally, SpAn infers the emergent network biology of tumor microenvironment spatial domains revealing a spatially-mediated role of CRC consensus molecular subtype features with the potential to inform precision medicine.

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

Deep Profiling of Cellular Heterogeneity by Emerging Single-Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single-cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well-established methods for single-cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining-based techniques for single-cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single-cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single-cell proteomic technologies in cell biology and medical research are discussed.

Life-Saving Microscopy Method for Amyotrophic Lateral Sclerosis Patients

The submission describes in the form of a communication recent experiences with a promising new therapeutic approach for amyotrophic lateral sclerosis (ALS). This approach is based on imaging cycler microscopy that led to the discovery of ALS specific cells in the blood, which invade the pyramidal system (lateral corticospinal tract) of ALS patients, where they compress motor axons. The depletion of these cells leads to remission of clinical symptoms and demonstrates the important role of these cells in ALS. The therapy will be offered to ALS patients in licensed and certified centers (in progress). © 2020 International Society for Advancement of Cytometry.

Digital Spindle: A New Way to Explore Mitotic Functions by Whole Cell Data Collection and a Computational Approach

From cells to organisms, every living system is three-dimensional (3D), but the performance of fluorescence microscopy has been largely limited when attempting to obtain an overview of systems' dynamic processes in three dimensions. Recently, advanced light-sheet illumination technologies, allowing drastic improvement in spatial discrimination, volumetric imaging times, and phototoxicity/photobleaching, have been making live imaging to collect precise and reliable 3D information increasingly feasible. In particular, lattice light-sheet microscopy (LLSM), using an ultrathin light-sheet, enables whole-cell 3D live imaging of cellular processes, including mitosis, at unprecedented spatiotemporal resolution for extended periods of time. This technology produces immense and complex data, including a significant amount of information, raising new challenges for big image data analysis and new possibilities for data utilization. Once the data are digitally archived in a computer, the data can be reused for various purposes by anyone at any time. Such an information science approach has the potential to revolutionize the use of bioimage data, and provides an alternative method for cell biology research in a data-driven manner. In this article, we introduce examples of analyzing digital mitotic spindles and discuss future perspectives in cell biology.

Profiling Cell Signaling Networks at Single-cell Resolution

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

Ultra-fast cycling for multiplexed cellular fluorescence imaging

Rapid analysis of single and scant cell populations is essential in modern diagnostics, yet existing methods are often limited and slow. Here we describe an ultra-fast, highly efficient cycling method for the analysis of single cells based on unique linkers for tetrazine (Tz) / trans-cyclooctene (TCO) mediated quenching. Surprisingly, the quenching reaction rates were more than 3 orders of magnitude faster (t1/2 < 1 sec) than predicted. This allowed multi-cycle staining and immune cell profiling within an hour, leveraging the accelerated kinetics to open new diagnostic possibilities for rapid cellular analyses.

Ultra-fast Cycling for Multiplexed Cellular Fluorescence Imaging

Rapid analysis of single and scant cell populations is essential in modern diagnostics, yet existing methods are often limited and slow. Herein, we describe an ultra-fast, highly efficient cycling method for the analysis of single cells based on unique linkers for tetrazine (Tz)/trans-cyclooctene (TCO)-mediated quenching. Surprisingly, the quenching reaction rates were more than 3 orders of magnitude faster (t1/2 <1 s) than predicted. This allowed multi-cycle staining and immune cell profiling within an hour, leveraging the accelerated kinetics to open new diagnostic possibilities for rapid cellular analyses.

Advances in quantitative immunohistochemistry and their contribution to breast cancer

Introduction: Automated image analysis provides an objective, quantitative, and reproducible method of measurement of biomarkers. Image quantification is particularly well suited for the analysis of tissue microarrays which has played a major pivotal role in the rapid assessment of molecular biomarkers. Data acquired from grinding up bulk tissue samples miss spatial information regarding cellular localization; therefore, methods that allow for spatial cell phenotyping at high resolution have proven to be valuable in many biomarker discovery assays. Here, we focus our attention on breast cancer as an example of a tumor type that has benefited from quantitative biomarker studies using tissue microarray format.Areas covered: The history of immunofluorescence and immunohistochemistry and the current status of these techniques, including multiplexing technologies (spectral and non-spectral) and image analysis software will be addressed. Finally, we will turn our attention to studies that have provided proof-of-principle evidence that have been impacted from the use of these techniques.Expert opinion: Assessment of prognostic and predictive biomarkers on tissue sections and TMA using Quantitative immunohistochemistry is an important advancement in the investigation of biologic markers. The challenges in standardization of quantitative technologies for accurate assessment are required for adoption into routine clinical practice.

IL-7 derived from lymph node fibroblastic reticular cells is dispensable for naive T cell homeostasis but crucial for central memory T cell survival

The survival of peripheral T cells is dependent on their access to peripheral LNs (pLNs) and stimulation by IL-7. In pLNs fibroblastic reticular cells (FRCs) and lymphatic endothelial cells (LECs) produce IL-7 suggesting their contribution to the IL-7-dependent survival of T cells. However, IL-7 production is detectable in multiple organs and is not restricted to pLNs. This raises the question whether pLN-derived IL-7 is required for the maintenance of peripheral T cell homeostasis. Here, we show that numbers of naive T cells (T_N ) remain unaffected in pLNs and spleen of mice lacking Il7 gene activity in pLN FRCs, LECs, or both. In contrast, frequencies of central memory T cells (T_CM ) are reduced in FRC-specific IL-7 KO mice. Thus, steady state IL-7 production by pLN FRCs is critical for the maintenance of T_CM , but not T_N , indicating that both T cell subsets colonize different ecological niches in vivo.

RESTORE: Robust intEnSiTy nORmalization mEthod for multiplexed imaging

Recent advances in multiplexed imaging technologies promise to improve the understanding of the functional states of individual cells and the interactions between the cells in tissues. This often requires compilation of results from multiple samples. However, quantitative integration of information between samples is complicated by variations in staining intensity and background fluorescence that obscure biological variations. Failure to remove these unwanted artifacts will complicate downstream analysis and diminish the value of multiplexed imaging for clinical applications. Here, to compensate for unwanted variations, we automatically identify negative control cells for each marker within the same tissue and use their expression levels to infer background signal level. The intensity profile is normalized by the inferred level of the negative control cells to remove between-sample variation. Using a tissue microarray data and a pair of longitudinal biopsy samples, we demonstrated that the proposed approach can remove unwanted variations effectively and shows robust performance.

Chang et al. develop an analytical method called RESTORE to control for variations due to technical artifacts in multiplexed imaging. They test their method on a CycIF stained tissue microarray dataset and biopsies processed at different times. Their method can improve the applicability of imaging techniques in diagnostics and inference using unbiased clustering methods.

Convergence of pathway analysis and pattern recognition predicts sensitization to latest generation TRAIL therapeutics by IAP antagonism

Second generation TRAIL-based therapeutics, combined with sensitising co-treatments, have recently entered clinical trials. However, reliable response predictors for optimal patient selection are not yet available. Here, we demonstrate that a novel and translationally relevant hexavalent TRAIL receptor agonist, IZI1551, in combination with Birinapant, a clinically tested IAP antagonist, efficiently induces cell death in various melanoma models, and that responsiveness can be predicted by combining pathway analysis, data-driven modelling and pattern recognition. Across a panel of 16 melanoma cell lines, responsiveness to IZI1551/Birinapant was heterogeneous, with complete resistance and pronounced synergies observed. Expression patterns of TRAIL pathway regulators allowed us to develop a combinatorial marker that predicts potent cell killing with high accuracy. IZI1551/Birinapant responsiveness could be predicted not only for cell lines, but also for 3D tumour cell spheroids and for cells directly isolated from patient melanoma metastases (80–100% prediction accuracies). Mathematical parameter reduction identified 11 proteins crucial to ensure prediction accuracy, with x-linked inhibitor of apoptosis protein (XIAP) and procaspase-3 scoring highest, and Bcl-2 family members strongly represented. Applied to expression data of a cohort of n = 365 metastatic melanoma patients in a proof of concept in silico trial, the predictor suggested that IZI1551/Birinapant responsiveness could be expected for up to 30% of patient tumours. Overall, response frequencies in melanoma models were very encouraging, and the capability to predict melanoma sensitivity to combinations of latest generation TRAIL-based therapeutics and IAP antagonists can address the need for patient selection strategies in clinical trials based on these novel drugs.

Single-cell analysis targeting the proteome

The existence of cellular heterogeneity and its central relevance to biological phenomena provides a strong rationale for a need for analytical methods that enable analysis at the single-cell level. Analysis of the genome and transcriptome is possible at the single-cell level, but the comprehensive interrogation of the proteome with this level of resolution remains challenging. Single-cell protein analysis tools are advancing rapidly, however, and providing insights into collections of proteins with great relevance to cell and disease biology. Here, we review single-cell protein analysis technologies and assess their advantages and limitations. The emerging technologies presented have the potential to reveal new insights into tumour heterogeneity and therapeutic resistance, elucidate mechanisms of immune response and immunotherapy, and accelerate drug discovery.

Using toponomics to characterize phenotypic diversity in alveolar macrophages from male mice treated with exogenous SP-A1

Background

We used the Toponome Imaging System (TIS) to identify “patterns of marker expression”, referred to here as combinatorial molecular phenotypes (CMPs) in alveolar macrophages (AM) in response to the innate immune molecule, SP-A1.

Methods

We compared 114 AM from male SP-A deficient mice. One group (n = 3) was treated with exogenous human surfactant protein A1 (hSP-A1) and the other with vehicle (n = 3). AM obtained by bronchoalveolar lavage were plated onto slides and analyzed using TIS to study the AM toponome, the spatial network of proteins within intact cells. With TIS, each slide is sequentially immunostained with multiple FITC-conjugated antibodies. Images are analyzed pixel-by-pixel identifying all of the proteins within each pixel, which are then designated as CMPs. CMPs represent organized protein clusters postulated to contribute to specific functions.

Results

1) We compared identical CMPs in KO and SP-A1 cells and found them to differ significantly (p = 0.0007). Similarities between pairs of markers in the two populations also differed significantly (p < 0.0001). 2) Focusing on the 20 most abundant CMPs for each cell, we developed a method to generate CMP “signatures” that characterized various groups of cells. Phenotypes were defined as cells exhibiting similar signatures of CMPs. i) AM were extremely diverse and each group contained cells with multiple phenotypes. ii) Among the 114 AM analyzed, no two cells were identical. iii) However, CMP signatures could distinguish among cell subpopulations within and between groups. iv) Some cell populations were enriched with SP-A1 treatment, some were more common without SP-A1, and some seemed not to be influenced by the presence of SP-A1. v) We also found that AM were more diverse in mice treated with SP-A1 compared to those treated with vehicle.

Conclusions

AM diversity is far more extensive than originally thought. The increased diversity of SP-A1-treated mice points to the possibility that SP-A1 enhances or activates several pathways in the AM to better prepare it for its innate immune functions and other functions shown previously to be affected by SP-A treatment. Future studies may identify key protein(s) responsible for CMP integrity and consequently for a given function, and target it for therapeutic purposes.

Multiplex Immunofluorescence Assays

Multiplexed imaging platforms to simultaneously detect multiple epitopes in the same tissue section emerged in the last years as very powerful tools to study tumor immune contexture. These revolutionary technologies are providing a deep methodology for tumor evaluation in formalin-fixed and paraffin-embedded (FFPE) to improve the understanding of tumor microenvironment, new targets for treatment, prognostic and predictive biomarkers, and translational studies. Multiplexed imaging platforms allow for the identification of several antigens simultaneously from a single tissue section, core needle biopsies, and tissue microarrays. In recent years, multiplexed imaging has improved the abilities to characterize the different types of cell populations in malignant and non-malignant tissues, and their spatial distribution in relationship to clinical outcomes. Multiplexed technologies associated with digital image analysis software offer a high-quality throughput assay to study cancer specimens at multiple time points before, during and after treatment. The aim of this chapter is to provide a review of multiplexed imaging covering its fundamentals, advantages, disadvantages, and material and methods for staining applied to FFPE tumor tissues and focusing on the use of multiplex immunofluorescence with tyramine signal amplification staining for immune profiling and translational research.

New Technologies to Image Tumors

The premise of this book is the importance of the tumor microenvironment (TME). Until recently, most research on and clinical attention to cancer biology, diagnosis, and prognosis were focused on the malignant (or premalignant) cellular compartment that could be readily appreciated using standard morphology-based imaging.

Highly multiplexed immunofluorescence images and single-cell data of immune markers in tonsil and lung cancer

In this data descriptor, we document a dataset of multiplexed immunofluorescence images and derived single-cell measurements of immune lineage and other markers in formaldehyde-fixed and paraffin-embedded (FFPE) human tonsil and lung cancer tissue. We used tissue cyclic immunofluorescence (t-CyCIF) to generate fluorescence images which we artifact corrected using the BaSiC tool, stitched and registered using the ASHLAR algorithm, and segmented using ilastik software and MATLAB. We extracted single-cell features from these images using HistoCAT software. The resulting dataset can be visualized using image browsers and analyzed using high-dimensional, single-cell methods. This dataset is a valuable resource for biological discovery of the immune system in normal and diseased states as well as for the development of multiplexed image analysis and viewing tools.

Multiplexed and high-throughput neuronal fluorescence imaging with diffusible probes

Synapses contain hundreds of distinct proteins whose heterogeneous expression levels are determinants of synaptic plasticity and signal transmission relevant to a range of diseases. Here, we use diffusible nucleic acid imaging probes to profile neuronal synapses using multiplexed confocal and super-resolution microscopy. Confocal imaging is performed using high-affinity locked nucleic acid imaging probes that stably yet reversibly bind to oligonucleotides conjugated to antibodies and peptides. Super-resolution PAINT imaging of the same targets is performed using low-affinity DNA imaging probes to resolve nanometer-scale synaptic protein organization across nine distinct protein targets. Our approach enables the quantitative analysis of thousands of synapses in neuronal culture to identify putative synaptic sub-types and co-localization patterns from one dozen proteins. Application to characterize synaptic reorganization following neuronal activity blockade reveals coordinated upregulation of the post-synaptic proteins PSD-95, SHANK3 and Homer-1b/c, as well as increased correlation between synaptic markers in the active and synaptic vesicle zones.

Qualifying antibodies for image-based immune profiling and multiplexed tissue imaging

Multiplexed tissue imaging enables precise, spatially resolved enumeration and characterization of cell types and states in human resection specimens. A growing number of methods applicable to formalin-fixed, paraffin-embedded (FFPE) tissue sections have been described, the majority of which rely on antibodies for antigen detection and mapping. This protocol provides step-by-step procedures for confirming the selectivity and specificity of antibodies used in fluorescence-based tissue imaging and for the construction and validation of antibody panels. Although the protocol is implemented using tissue-based cyclic immunofluorescence (t-CyCIF) as an imaging platform, these antibody-testing methods are broadly applicable. We demonstrate assembly of a 16-antibody panel for enumerating and localizing T cells and B cells, macrophages, and cells expressing immune checkpoint regulators. The protocol is accessible to individuals with experience in microscopy and immunofluorescence; some experience in computation is required for data analysis. A typical 30-antibody dataset for 20 FFPE slides can be generated within 2 weeks.

Next-generation computational tools for interrogating cancer immunity

The remarkable success of cancer therapies with immune checkpoint blockers is revolutionizing oncology and has sparked intensive basic and translational research into the mechanisms of cancer-immune cell interactions. In parallel, numerous novel cutting-edge technologies for comprehensive molecular and cellular characterization of cancer immunity have been developed, including single-cell sequencing, mass cytometry and multiplexed spatial cellular phenotyping. In order to process, analyse and visualize multidimensional data sets generated by these technologies, computational methods and software tools are required. Here, we review computational tools for interrogating cancer immunity, discuss advantages and limitations of the various methods and provide guidelines to assist in method selection.

Integrating Imaging and Omics: Computational Methods and Challenges

Fluorescence microscopy imaging has long been complementary to DNA sequencing- and mass spectrometry–based omics in biomedical research, but these approaches are now converging. On the one hand, omics methods are moving from in vitro methods that average across large cell populations to in situ molecular characterization tools with single-cell sensitivity. On the other hand, fluorescence microscopy imaging has moved from a morphological description of tissues and cells to quantitative molecular profiling with single-molecule resolution. Recent technological developments underpinned by computational methods have started to blur the lines between imaging and omics and have made their direct correlation and seamless integration an exciting possibility. As this trend continues rapidly, it will allow us to create comprehensive molecular profiles of living systems with spatial and temporal context and subcellular resolution. Key to achieving this ambitious goal will be novel computational methods and successfully dealing with the challenges of data integration and sharing as well as cloud-enabled big data analysis.

Exploring single cells in space and time during tissue development, homeostasis and regeneration

Complex 3D tissues arise during development following tightly organized events in space and time. In particular, gene regulatory networks and local interactions between single cells lead to emergent properties at the tissue and organism levels. To understand the design principles of tissue organization, we need to characterize individual cells at given times, but we also need to consider the collective behavior of multiple cells across different spatial and temporal scales. In recent years, powerful single cell methods have been developed to characterize cells in tissues and to address the challenging questions of how different tissues are formed throughout development, maintained in homeostasis, and repaired after injury and disease. These approaches have led to a massive increase in data pertaining to both mRNA and protein abundances in single cells. As we review here, these new technologies, in combination with in toto live imaging, now allow us to bridge spatial and temporal information quantitatively at the single cell level and generate a mechanistic understanding of tissue development.

ColiCoords: A Python package for the analysis of bacterial fluorescence microscopy data

Single-molecule fluorescence microscopy studies of bacteria provide unique insights into the mechanisms of cellular processes and protein machineries in ways that are unrivalled by any other technique. With the cost of microscopes dropping and the availability of fully automated microscopes, the volume of microscopy data produced has increased tremendously. These developments have moved the bottleneck of throughput from image acquisition and sample preparation to data analysis. Furthermore, requirements for analysis procedures have become more stringent given the demand of various journals to make data and analysis procedures available. To address these issues we have developed a new data analysis package for analysis of fluorescence microscopy data from rod-like cells. Our software ColiCoords structures microscopy data at the single-cell level and implements a coordinate system describing each cell. This allows for the transformation of Cartesian coordinates from transmission light and fluorescence images and single-molecule localization microscopy (SMLM) data to cellular coordinates. Using this transformation, many cells can be combined to increase the statistical power of fluorescence microscopy datasets of any kind. ColiCoords is open source, implemented in the programming language Python, and is extensively documented. This allows for modifications for specific needs or to inspect and publish data analysis procedures. By providing a format that allows for easy sharing of code and associated data, we intend to promote open and reproducible research. The source code and documentation can be found via the project's GitHub page.

Multiplex Label Free Characterization of Cancer Cell Lines Using Surface Plasmon Resonance Imaging

Rapid multiplex cell surface marker analysis can expedite investigations in which large number of antigens need to be analyzed. Simultaneous analysis of multiple surface antigens at the same level of sensitivity is however limited in the current golden standard analysis method, flow cytometry. In this paper we introduce a surface plasmon resonance imaging (SPRi)-based technique for 44-plex parameter analysis using a single sample, in less than 20 min. We analyzed the expression on cells from five different cancer cell lines by SPRi on a 44-plex antibody array including 4 negative controls and compared the output with flow cytometry. The combined correlation of the markers that showed expression by flow cytometry was 0.76. The results demonstrate as a proof of principle that SPRi can be applied for rapid semi-quantitative multiplex cell surface marker analysis.

Precision immunoprofiling by image analysis and artificial intelligence

Clinical success of immunotherapy is driving the need for new prognostic and predictive assays to inform patient selection and stratification. This requirement can be met by a combination of computational pathology and artificial intelligence. Here, we critically assess computational approaches supporting the development of a standardized methodology in the assessment of immune-oncology biomarkers, such as PD-L1 and immune cell infiltrates. We examine immunoprofiling through spatial analysis of tumor-immune cell interactions and multiplexing technologies as a predictor of patient response to cancer treatment. Further, we discuss how integrated bioinformatics can enable the amalgamation of complex morphological phenotypes with the multiomics datasets that drive precision medicine. We provide an outline to machine learning (ML) and artificial intelligence tools and illustrate fields of application in immune-oncology, such as pattern-recognition in large and complex datasets and deep learning approaches for survival analysis. Synergies of surgical pathology and computational analyses are expected to improve patient stratification in immuno-oncology. We propose that future clinical demands will be best met by (1) dedicated research at the interface of pathology and bioinformatics, supported by professional societies, and (2) the integration of data sciences and digital image analysis in the professional education of pathologists.

Innate extracellular vesicles from melanoma patients suppress β-catenin in tumor cells by miRNA-34a

Upon tumor development, new extracellular vesicles appear in circulation. Our knowledge of their relative abundance, function, and overall impact on cancer development is still preliminary. Here, we demonstrate that plasma extracellular vesicles (pEVs) of non-tumor origin are persistently increased in untreated and post-excision melanoma patients, exhibiting strong suppressive effects on the proliferation of tumor cells. Plasma vesicle numbers, miRNAs, and protein levels were elevated two- to tenfold and detected many years after tumor resection. The vesicles revealed individual and clinical stage-specific miRNA profiles as well as active ADAM10. However, whereas pEV from patients preventing tumor relapse down-regulated β-catenin and blocked tumor cell proliferation in an miR-34a-dependent manner, pEV from metastatic patients lost this ability and stimulated β-catenin-mediated transcription. Cancer-induced pEV may constitute an innate immune mechanism suppressing tumor cell activity including that of residual cancer cells present after primary surgery.

A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry

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.

State-of-the-Art of Profiling Immune Contexture in the Era of Multiplexed Staining and Digital Analysis to Study Paraffin Tumor Tissues

Multiplexed platforms for multiple epitope detection have emerged in the last years as very powerful tools to study tumor tissues. These revolutionary technologies provide important visual techniques for tumor examination in formalin-fixed paraffin-embedded specimens to improve the understanding of the tumor microenvironment, promote new treatment discoveries, aid in cancer prevention, as well as allowing translational studies to be carried out. The aim of this review is to highlight the more recent methodologies that use multiplexed staining to study simultaneous protein identification in formalin-fixed paraffin-embedded tumor tissues for immune profiling, clinical research, and potential translational analysis. New multiplexed methodologies, which permit the identification of several proteins at the same time in one single tissue section, have been developed in recent years with the ability to study different cell populations, cells by cells, and their spatial distribution in different tumor specimens including whole sections, core needle biopsies, and tissue microarrays. Multiplexed technologies associated with image analysis software can be performed with a high-quality throughput assay to study cancer specimens and are important tools for new discoveries. The different multiplexed technologies described in this review have shown their utility in the study of cancer tissues and their advantages for translational research studies and application in cancer prevention and treatments.

Extracellular vesicles from mature dendritic cells (DC) differentiate monocytes into immature DC

Mature dendritic cells (DC) secrete substantial amounts of vesicles that are primarily ingested by monocytes, leading to differentiation processes in these target cells towards monocyte-derived DC.

During inflammation, murine and human monocytes can develop into dendritic cells (DC), but this process is not entirely understood. Here, we demonstrate that extracellular vesicles (EV) secreted by mature human DC (maDC) differentiate peripheral monocytes into immature DC, expressing a unique marker pattern, including 6-sulfo LacNAc (slan), Zbtb46, CD64, and CD14. While EV from both maDC and immature DC differentiated monocytes similar to GM-CSF/IL-4 stimulation, only maDC-EV produced precursors, which upon maturation stimulus developed into T-cell–activating and IL-12p70–secreting maDC. Mechanistically, maDC-EV induced cell signaling through GM-CSF, which was abundant in EV as were IL-4 and other cytokines and chemokines. When injected into the mouse skin, murine maDC-EV attracted immune cells including monocytes that developed activation markers typical for inflammatory cells. Skin-injected EV also reached lymph nodes, causing a similar immune cell infiltration. We conclude that DC-derived EV likely serve to perpetuate an immune reaction and may contribute to chronic inflammation.

Single-cell barcode analysis provides a rapid readout of cellular signaling pathways in clinical specimens

Serial tissue sampling has become essential in guiding modern targeted and personalized cancer treatments. An alternative to image guided core biopsies are fine needle aspirates (FNA) that yield cells rather than tissues but are much better tolerated and have lower complication rates. The efficient pathway analysis of such cells in the clinic has been difficult, time consuming and costly. Here we develop an antibody-DNA barcoding approach where harvested cells can be rapidly re-stained through the use of custom designed oligonucleotide-fluorophore conjugates. We show that this approach can be used to interrogate drug-relevant pathways in scant clinical samples. Using the PI3K/PTEN/CDK4/6 pathways in breast cancer as an example, we demonstrate how analysis can be performed in tandem with trial enrollment and can evaluate downstream signaling following therapeutic inhibition. This approach should allow more widespread use of scant single cell material in clinical samples.

Adoptive T Cell Therapy: New Avenues Leading to Safe Targets and Powerful Allies

Adoptive transfer of TCR-engineered T cells is a potent therapy, able to induce clinical responses in different human malignancies. Nevertheless, treatment toxicities may occur and, in particular for solid tumors, responses may be variable and often not durable. To address these challenges, it is imperative to carefully select target antigens and to immunologically interrogate the corresponding tumors when designing optimal T cell therapies. Here, we review recent advances, covering both omics- and laboratory tools that can enable the selection of optimal T cell epitopes and TCRs as well as the identification of dominant immune evasive mechanisms within tumor tissues. Furthermore, we discuss how these techniques may aid in a rational design of effective combinatorial adoptive T cell therapies.

Cold shock Y-box binding protein-1 acetylation status in monocytes is associated with systemic inflammation and vascular damage

BACKGROUND AND AIMS

In dialysis patients, vascular morbidities are highly prevalent and linked to leukocyte extravasation, especially of polarized monocytes. Experimental data demonstrate that phenotypic changes in monocytes require Y-box binding protein-1 (YB-1) upregulation.

METHODS

We determined YB-1 expression in circulating and vessel-invading monocytes from healthy controls and dialysis patients to correlate results with intima plaque formation and systemic inflammation.

RESULTS

Compared to healthy subjects, dialysis patients have fewer classical and more intermediate and non-classical monocytes. Post-translationally modified YB-1 (lysine 301/304 acetylation) is detected at high levels in the nucleus of adherent and invading CD14⁺CD68⁺ monocytes from umbilical cord and atherosclerosis-prone vessels. The content of non-acetylated YB-1 is significantly decreased (p < 0.001), whereas acetylated YB-1 is correspondingly increased (p < 0.001) throughout all monocyte subpopulations, such that the overall content remains unchanged.

CONCLUSIONS

In dialysis patients the YB-1 acetylation status is higher with prevailing diabetes and intima plaque formation. Pro-inflammatory mediators TNFα, IL-6, uPAR, CCL2, M-CSF, progranulin, ANP, and midkine, as well as anti-inflammatory IL-10 are significantly increased in dialysis patients, emphasizing a systemic inflammatory milieu. Strong positive correlations of monocytic YB-1 content are seen with ANP, IP-10, IL-6, and IL-10 serum levels. This is the first study demonstrating an association of cold shock protein YB-1 expression with inflammation in hemodialysis patients.

Multiplexed protein maps link subcellular organization to cellular states

Obtaining highly multiplexed protein measurements across multiple length scales has enormous potential for biomedicine. Here, we measured, by iterative indirect immunofluorescence imaging (4i), 40-plex protein readouts from biological samples at high-throughput from the millimeter to the nanometer scale. This approach simultaneously captures properties apparent at the population, cellular, and subcellular levels, including microenvironment, cell shape, and cell cycle state. It also captures the detailed morphology of organelles, cytoskeletal structures, nuclear subcompartments, and the fate of signaling receptors in thousands of single cells in situ. We used computer vision and systems biology approaches to achieve unsupervised comprehensive quantification of protein subcompartmentalization within various multicellular, cellular, and pharmacological contexts. Thus, highly multiplexed subcellular protein maps can be used to identify functionally relevant single-cell states.

Ancillary studies in cytology: Secondary or necessary?

Ancillary studies are rapidly becoming an integral and necessary aspect of cytologic analysis. In addition to morphologic features, cytologic specimens contain an enormous amount of information content within their molecules that should be tapped to add value to these samples. Fortunately, a large number of existing and emerging technologies exist to provide access to this information. Adoption of these technologies will require continued attention to fundamental aspects of specimen procurement, handling, and processing to ensure testing accuracy. Successful implementation of ancillary studies will depend on rigorous validation of assays and the development of evidence-based guidelines for their use in patients. Cytopathologists must embrace the role of ancillary test stewardship to ensure the future clinical use of cytologic specimens.

Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging

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.

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Autoimmunity analyzed by multiplexed DNA-tagged antibody staining (CODEX)

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CODEX data reveal pairwise interactions and niches changing with disease

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First tier of neighbors significantly impacts marker expression in the index cells

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Changes in splenic morphology correlate with shifts in cell frequencies

Toward mapping the human body at a cellular resolution

The adult human body is composed of nearly 37 trillion cells, each with potentially unique molecular characteristics. This Perspective describes some of the challenges and opportunities faced in mapping the molecular characteristics of these cells in specific regions of the body and highlights areas for international collaboration toward the broader goal of comprehensively mapping the human body with cellular resolution.

Histological coherent Raman imaging: a prognostic review

Histopathology plays a central role in diagnosis of many diseases including solid cancers. Efforts are underway to transform this subjective art to an objective and quantitative science. Coherent Raman imaging (CRI), a label-free imaging modality with sub-cellular spatial resolution and molecule-specific contrast possesses characteristics which could support the qualitative-to-quantitative transition of histopathology. In this work we briefly survey major themes related to modernization of histopathology, review applications of CRI to histopathology and, finally, discuss potential roles for CRI in the transformation of histopathology that is already underway.

JAK2-V617F promotes venous thrombosis through β1/β2 integrin activation

JAK2-V617F-positive chronic myeloproliferative neoplasia (CMN) commonly displays dysfunction of integrins and adhesion molecules expressed on platelets, erythrocytes, and leukocytes. However, the mechanism by which the 2 major leukocyte integrin chains, β1 and β2, may contribute to CMN pathophysiology remained unclear. β1 (α4β1; VLA-4) and β2 (αLβ2; LFA-1) integrins are essential regulators for attachment of leukocytes to endothelial cells. We here showed enhanced adhesion of granulocytes from mice with JAK2-V617F knockin (JAK2+/VF mice) to vascular cell adhesion molecule 1- (VCAM1-) and intercellular adhesion molecule 1-coated (ICAM1-coated) surfaces. Soluble VCAM1 and ICAM1 ligand binding assays revealed increased affinity of β1 and β2 integrins for their respective ligands. For β1 integrins, this correlated with a structural change from the low- to the high-affinity conformation induced by JAK2-V617F. JAK2-V617F triggered constitutive activation of the integrin inside-out signaling molecule Rap1, resulting in translocation toward the cell membrane. Employing a venous thrombosis model, we demonstrated that neutralizing anti-VLA-4 and anti-β2 integrin antibodies suppress pathologic thrombosis as observed in JAK2+/VF mice. In addition, aberrant homing of JAK2+/VF leukocytes to the spleen was inhibited by neutralizing anti-β2 antibodies and by pharmacologic inhibition of Rap1. Thus, our findings identified cross-talk between JAK2-V617F and integrin activation promoting pathologic thrombosis and abnormal trafficking of leukocytes to the spleen.

Easy Employment and Crosstalk-Free Detection of Seven Fluorophores in a Widefield Fluorescence Microscope

Immunofluorescence staining has become an essential tool in pathology and biomedical sciences to identify rare cells, cell–cell interactions, and submicroscopic cellular components. Many experimental settings, however, suffer from the fact that traditional widefield fluorescence microscopy is usually restricted to imaging three or four fluorophores only. Due to a lack of morphological information and a high detection limit, even flow cytometry—which is capable of staining 20 or more fluorophores at the same time—is limited in its applicability, especially in areas such as rare cell detection. Other advanced imaging approaches, such as confocal laser scanning microscopy and imaging flow cytometry, may be addressing these shortcomings, but in turn require sophisticated downstream data processing and high capital outlay. Here, we describe a new method and filter set-up to routinely employ up to seven fluorophores on a traditional widefield fluorescence microscope equipped with a standard high-pressure mercury light source. Quantification of crosstalk between channels and actual seven-color imaging of cancer cells spiked into leukocytes demonstrate that there is no need for digital compensation correction algorithms. Our set-up thus permits a detailed analysis of rare cell populations, co-localization of antigens, and cell morphology in a standard research or routine laboratory setting.