Multiplexed ion beam imaging of human breast tumors
TL;DR: This work has developed a method that uses secondary ion mass spectrometry to image antibodies tagged with isotopically pure elemental metal reporters to provide new insights into disease pathogenesis that will be valuable for basic research, drug discovery and clinical diagnostics.
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.
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Broad Institute1, Howard Hughes Medical Institute2, Massachusetts Institute of Technology3, Wellcome Trust Sanger Institute4, University of Cambridge5, European Bioinformatics Institute6, Harvard University7, Weizmann Institute of Science8, University of Zurich9, Laboratory of Molecular Biology10, Utrecht University11, École Polytechnique Fédérale de Lausanne12, University of Pennsylvania13, German Cancer Research Center14, Heidelberg University15, Ludwig Maximilian University of Munich16, John Radcliffe Hospital17, Newcastle University18, Stanford University19, University of Oxford20, University of California, San Francisco21, Allen Institute for Brain Science22, Karolinska Institutet23, Royal Institute of Technology24, Icahn School of Medicine at Mount Sinai25, University of Cape Town26, University Medical Center Groningen27, Radboud University Nijmegen28, Kettering University29, University of Edinburgh30, Babraham Institute31, New York University32, Netherlands Cancer Institute33, Ragon Institute of MGH, MIT and Harvard34, University of Texas Health Science Center at Houston35, Technische Universität München36, Technical University of Denmark37, University of California, Berkeley38, King's College London39, California Institute of Technology40
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.
1,391 citations
Cites background or methods from "Multiplexed ion beam imaging of hum..."
...…2014; Lubeck et al., 2014; Shah et al., 2016; Ståhl et al., 2016); the distribution of scores of proteins at cellular or sub-cellular resolution (Angelo et al., 2014; Chen et al., 2015a; Giesen et al., 2014; Hama et al., 2011; Susaki et al., 2014; Yang et al., 2014); various aspects of…...
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..., 2014) and Mass Ion Bean Imaging (MIBI) (Angelo et al., 2014), involve staining a tissue specimen with antibodies, each labeled with a barcode of heavy metals, and rastering across the sample to measure the proteins in each ‘pixel’....
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..., 2016) or protein staining (Angelo et al., 2014; Giesen et al., 2014), it should be possible to spatially map multiple cell types at once based on expression signatures to see how they relate to each other and to connect them with cell types defined by morphology or function....
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...Some approaches for protein detection, such as Imaging Mass Cytometry (Giesen et al., 2014) and Mass Ion Bean Imaging (Angelo et al., 2014), involve staining a tissue specimen with antibodies, each labeled with a barcode of heavy metals, and rastering across the sample to measure the proteins in each ’pixel’....
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...Some approaches for protein detection, such as Imaging Mass Cytometry (Giesen et al., 2014) and Mass Ion Bean Imaging (Angelo et al., 2014), involve staining a tissue specimen with antibodies, each labeled with a barcode of heavy metals, and rastering across the sample to measure the proteins in…...
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TL;DR: The current state of mass cytometry is reviewed, providing an overview of the instrumentation, its present capabilities, and methods of data analysis, as well as thoughts on future developments and applications.
888 citations
Cites background from "Multiplexed ion beam imaging of hum..."
...Another approach, called 782 Cell 165, May 5, 2016 multiplexed ion beam imaging (MIBI), uses an ion beam to liberate metal ion reporters, which are quantified by mass spectrometry (Angelo et al., 2014)....
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...782 Cell 165, May 5, 2016 multiplexed ion beam imaging (MIBI), uses an ion beam to liberate metal ion reporters, which are quantified by mass spectrometry (Angelo et al., 2014)....
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Garvan Institute of Medical Research1, Peter MacCallum Cancer Centre2, Queen Mary University of London3, John Radcliffe Hospital4, Cedars-Sinai Medical Center5, University of Oxford6, Stanford University7, Harvard University8, Imperial College London9, University of Cambridge10, Johns Hopkins University11, University Hospital of Lausanne12, University of Pennsylvania13, University of Manchester14, French Institute of Health and Medical Research15, University of Edinburgh16, Walter and Eliza Hall Institute of Medical Research17, University of British Columbia18, University of Chicago19, Memorial Sloan Kettering Cancer Center20, University of Glasgow21, University College London22, University of Toronto23, Indiana University24, Translational Genomics Research Institute25
TL;DR: This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015 and aims to reduce incidence and improve outcomes for women with this disease.
Abstract: High-grade serous ovarian cancer (HGSOC) accounts for 70-80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.
801 citations
TL;DR: A review of the recent progress in cancer immunotherapy is outlined, particularly by focusing on landmark studies and the recent single-cell characterization of tumor-associated immune cells, and the phenotypic diversities of intratumoral immune cells and their connections with cancer Immunotherapy are summarized.
Abstract: Immunotherapy has revolutionized cancer treatment and rejuvenated the field of tumor immunology Several types of immunotherapy, including adoptive cell transfer (ACT) and immune checkpoint inhibitors (ICIs), have obtained durable clinical responses, but their efficacies vary, and only subsets of cancer patients can benefit from them Immune infiltrates in the tumor microenvironment (TME) have been shown to play a key role in tumor development and will affect the clinical outcomes of cancer patients Comprehensive profiling of tumor-infiltrating immune cells would shed light on the mechanisms of cancer–immune evasion, thus providing opportunities for the development of novel therapeutic strategies However, the highly heterogeneous and dynamic nature of the TME impedes the precise dissection of intratumoral immune cells With recent advances in single-cell technologies such as single-cell RNA sequencing (scRNA-seq) and mass cytometry, systematic interrogation of the TME is feasible and will provide insights into the functional diversities of tumor-infiltrating immune cells In this review, we outline the recent progress in cancer immunotherapy, particularly by focusing on landmark studies and the recent single-cell characterization of tumor-associated immune cells, and we summarize the phenotypic diversities of intratumoral immune cells and their connections with cancer immunotherapy We believe such a review could strengthen our understanding of the progress in cancer immunotherapy, facilitate the elucidation of immune cell modulation in tumor progression, and thus guide the development of novel immunotherapies for cancer treatment
737 citations
TL;DR: The intersection between deep learning and cellular image analysis is reviewed and an overview of both the mathematical mechanics and the programming frameworks of deep learning that are pertinent to life scientists are provided.
Abstract: Recent advances in computer vision and machine learning underpin a collection of algorithms with an impressive ability to decipher the content of images. These deep learning algorithms are being applied to biological images and are transforming the analysis and interpretation of imaging data. These advances are positioned to render difficult analyses routine and to enable researchers to carry out new, previously impossible experiments. Here we review the intersection between deep learning and cellular image analysis and provide an overview of both the mathematical mechanics and the programming frameworks of deep learning that are pertinent to life scientists. We survey the field's progress in four key applications: image classification, image segmentation, object tracking, and augmented microscopy. Last, we relay our labs' experience with three key aspects of implementing deep learning in the laboratory: annotating training data, selecting and training a range of neural network architectures, and deploying solutions. We also highlight existing datasets and implementations for each surveyed application.
714 citations
References
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TL;DR: The first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler is described, which can address a variety of biological questions quantitatively.
Abstract: Biologists can now prepare and image thousands of samples per day using automation, enabling chemical screens and functional genomics (for example, using RNA interference). Here we describe the first free, open-source system designed for flexible, high-throughput cell image analysis, CellProfiler. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).
4,578 citations
TL;DR: Single-cell “mass cytometry” analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.
Abstract: Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell "mass cytometry" to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.
2,147 citations
TL;DR: It is found that cell cycle activity during normal ageing and after injury led to polyploidy and multinucleation, but also to new diploid, mononucleate cardiomyocytes.
Abstract: Although recent studies have revealed that heart cells are generated in adult mammals, the frequency of generation and the source of new heart cells are not yet known. Some studies suggest a high rate of stem cell activity with differentiation of progenitors to cardiomyocytes. Other studies suggest that new cardiomyocytes are born at a very low rate, and that they may be derived from the division of pre-existing cardiomyocytes. Here we show, by combining two different pulse-chase approaches--genetic fate-mapping with stable isotope labelling, and multi-isotope imaging mass spectrometry--that the genesis of cardiomyocytes occurs at a low rate by the division of pre-existing cardiomyocytes during normal ageing, a process that increases adjacent to areas of myocardial injury. We found that cell cycle activity during normal ageing and after injury led to polyploidy and multinucleation, but also to new diploid, mononucleate cardiomyocytes. These data reveal pre-existing cardiomyocytes as the dominant source of cardiomyocyte replacement in normal mammalian myocardial homeostasis as well as after myocardial injury.
1,146 citations
TL;DR: A novel instrument for real time analysis of individual biological cells or other microparticles is described and real-time simultaneous detection of multiple isotopes from individual 1.8 microm polystyrene beads labeled with lanthanides is shown.
Abstract: A novel instrument for real time analysis of individual biological cells or other microparticles is described. The instrument is based on inductively coupled plasma time-of-flight mass spectrometry and comprises a three-aperture plasma−vacuum interface, a dc quadrupole turning optics for decoupling ions from neutral components, an rf quadrupole ion guide discriminating against low-mass dominant plasma ions, a point-to-parallel focusing dc quadrupole doublet, an orthogonal acceleration reflectron analyzer, a discrete dynode fast ion detector, and an 8-bit 1 GHz digitizer. A high spectrum generation frequency of 76.8 kHz provides capability for collecting multiple spectra from each particle-induced transient ion cloud, typically of 200−300 μs duration. It is shown that the transients can be resolved and characterized individually at a peak frequency of 1100 particles per second. Design considerations and optimization data are presented. The figures of merit of the instrument are measured under standard indu...
1,072 citations
TL;DR: CellProfiler 2.0 is described, which has been engineered to meet the needs of its growing user base, with new algorithms and features to facilitate high-throughput work.
Abstract: Summary: There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins can now be run within a CellProfiler pipeline.
Availability and Implementation: CellProfiler 2.0 is free and open source, available at http://www.cellprofiler.org under the GPL v. 2 license. It is available as a packaged application for Macintosh OS X and Microsoft Windows and can be compiled for Linux.
Contact: anne@broadinstitute.org
Supplementary information:Supplementary data are available at Bioinformatics online.
968 citations