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Zhang W, Sen A, Pena JK, Reitsma A, Alexander OC, Tajima T, Martinez OM, Krams SM. Application of Mass Cytometry Platforms to Solid Organ Transplantation. Transplantation 2024:00007890-990000000-00687. [PMID: 38467594 DOI: 10.1097/tp.0000000000004925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Transplantation serves as the cornerstone of treatment for patients with end-stage organ disease. The prevalence of complications, such as allograft rejection, infection, and malignancies, underscores the need to dissect the complex interactions of the immune system at the single-cell level. In this review, we discuss studies using mass cytometry or cytometry by time-of-flight, a cutting-edge technology enabling the characterization of immune populations and cell-to-cell interactions in granular detail. We review the application of mass cytometry in human and experimental animal studies in the context of transplantation, uncovering invaluable contributions of the tool to understanding rejection and other transplant-related complications. We discuss recent innovations that have the potential to streamline and standardize mass cytometry workflows for application to multisite clinical trials. Additionally, we introduce imaging mass cytometry, a technique that couples the power of mass cytometry with spatial context, thereby mapping cellular interactions within tissue microenvironments. The synergistic integration of mass cytometry and imaging mass cytometry data with other omics data sets and high-dimensional data platforms to further define immune dynamics is discussed. In conclusion, mass cytometry technologies, when integrated with other tools and data, shed light on the intricate landscape of the immune response in transplantation. This approach holds significant potential for enhancing patient outcomes by advancing our understanding and facilitating the development of new diagnostics and therapeutics.
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Affiliation(s)
- Wenming Zhang
- Department of Surgery, Stanford University, Stanford, CA
| | - Ayantika Sen
- Department of Surgery, Stanford University, Stanford, CA
| | | | - Andrea Reitsma
- Department of Surgery, Stanford University, Stanford, CA
| | - Oliver C Alexander
- Department of Surgery, Stanford University, Stanford, CA
- Meharry Medical College, School of Medicine, Nashville, TN
| | - Tetsuya Tajima
- Department of Surgery, Stanford University, Stanford, CA
| | | | - Sheri M Krams
- Department of Surgery, Stanford University, Stanford, CA
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2
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Rybakowska P, Alarcón-Riquelme ME, Marañón C. Approaching Mass Cytometry Translational Studies by Experimental and Data Curation Settings. Methods Mol Biol 2024; 2779:369-394. [PMID: 38526795 DOI: 10.1007/978-1-0716-3738-8_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Clinical studies are conducted to better understand the pathological mechanism of diseases and to find biomarkers associated with disease activity, drug response, or outcome prediction. Mass cytometry (MC) is a high-throughput single-cell technology that measures hundreds of cells per second with more than 40 markers per cell. Thus, it is a suitable tool for immune monitoring and biomarker discovery studies. Working in translational and clinical settings requires a careful experimental design to minimize, monitor, and correct the variations introduced during sample collection, preparation, acquisition, and analysis. In this review, we will focus on these important aspects of MC-related experiments and data curation in the context of translational clinical research projects.
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Affiliation(s)
- Paulina Rybakowska
- Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain
| | - Marta E Alarcón-Riquelme
- Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain
- Institute for Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Concepción Marañón
- Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain.
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3
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Berson E, Gajera CR, Phongpreecha T, Perna A, Bukhari SA, Becker M, Chang AL, De Francesco D, Espinosa C, Ravindra NG, Postupna N, Latimer CS, Shively CA, Register TC, Craft S, Montine KS, Fox EJ, Keene CD, Bendall SC, Aghaeepour N, Montine TJ. Cross-species comparative analysis of single presynapses. Sci Rep 2023; 13:13849. [PMID: 37620363 PMCID: PMC10449792 DOI: 10.1038/s41598-023-40683-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/16/2023] [Indexed: 08/26/2023] Open
Abstract
Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 presynaptic proteins revealed near-complete separation between primates and mice involving synaptic pruning, cellular energy, lipid metabolism, and neurotransmission. In addition, our analysis revealed a strong overlap between the presynaptic composition of human and macaque in the cerebral cortex and neostriatum. Our unique approach illuminates species- and region-specific variation in presynapse molecular composition.
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Affiliation(s)
- Eloïse Berson
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Chandresh R Gajera
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
| | - Thanaphong Phongpreecha
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Amalia Perna
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
| | - Syed A Bukhari
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
| | - Martin Becker
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Alan L Chang
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Davide De Francesco
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Camilo Espinosa
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Neal G Ravindra
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Nadia Postupna
- Department of Laboratory Medicine & Pathology, University of Washington, Seattle, WA, USA
| | - Caitlin S Latimer
- Department of Laboratory Medicine & Pathology, University of Washington, Seattle, WA, USA
| | - Carol A Shively
- Department of Pathology/Comparative Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Thomas C Register
- Department of Pathology/Comparative Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Suzanne Craft
- Department of Internal Medicine-Geriatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Kathleen S Montine
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
| | - Edward J Fox
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA
| | - C Dirk Keene
- Department of Laboratory Medicine & Pathology, University of Washington, Seattle, WA, USA
| | - Sean C Bendall
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA
- Department of Pediatrics, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Thomas J Montine
- Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA.
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4
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Guldberg SM, Okholm TLH, McCarthy EE, Spitzer MH. Computational Methods for Single-Cell Proteomics. Annu Rev Biomed Data Sci 2023; 6:47-71. [PMID: 37040735 PMCID: PMC10621466 DOI: 10.1146/annurev-biodatasci-020422-050255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.
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Affiliation(s)
- Sophia M Guldberg
- Department of Otolaryngology-Head and Neck Surgery and Department of Microbiology and Immunology, University of California, San Francisco, California, USA;
- Biomedical Sciences Graduate Program, University of California, San Francisco, California, USA
- Gladstone-UCSF Institute for Genomic Immunology, San Francisco, California, USA
| | - Trine Line Hauge Okholm
- Department of Otolaryngology-Head and Neck Surgery and Department of Microbiology and Immunology, University of California, San Francisco, California, USA;
- Gladstone-UCSF Institute for Genomic Immunology, San Francisco, California, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, USA
| | - Elizabeth E McCarthy
- Department of Otolaryngology-Head and Neck Surgery and Department of Microbiology and Immunology, University of California, San Francisco, California, USA;
- Biomedical Sciences Graduate Program, University of California, San Francisco, California, USA
- Institute for Human Genetics; Division of Rheumatology, Department of Medicine; Medical Scientist Training Program; and Biological and Medical Informatics Graduate Program, University of California, San Francisco, California, USA
| | - Matthew H Spitzer
- Department of Otolaryngology-Head and Neck Surgery and Department of Microbiology and Immunology, University of California, San Francisco, California, USA;
- Gladstone-UCSF Institute for Genomic Immunology, San Francisco, California, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, California, USA
- Chan Zuckerberg Biohub, San Francisco, California, USA
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5
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Single-cell technologies uncover intra-tumor heterogeneity in childhood cancers. Semin Immunopathol 2023; 45:61-69. [PMID: 36625902 DOI: 10.1007/s00281-022-00981-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 12/11/2022] [Indexed: 01/11/2023]
Abstract
Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution. This facilitates unraveling the heterogeneity of childhood cancers to identify cell subtypes that are prone to treatment resistance. The rapid accumulation of single-cell data from different modalities necessitates the development of novel computational approaches for processing, visualizing, and analyzing single-cell data. Here, we review single-cell approaches utilized or under development in the context of childhood cancers. We review computational methods for analyzing single-cell data and discuss best practices for their application. Finally, we review the impact of several studies of childhood tumors analyzed with these approaches and future directions to implement single-cell studies into translational cancer research in pediatric oncology.
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6
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Ben Amara A, Rouviere MS, Fattori S, Wlosik J, Gregori E, Boucherit N, Bernard PL, Nunès JA, Vey N, Luche H, Gorvel L, Olive D, Chretien AS. High-throughput mass cytometry staining for deep phenotyping of human natural killer cells. STAR Protoc 2022; 3:101768. [PMID: 36269638 PMCID: PMC9589031 DOI: 10.1016/j.xpro.2022.101768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/29/2022] [Accepted: 09/15/2022] [Indexed: 11/06/2022] Open
Abstract
This protocol details the step-by-step procedure for in-depth immune phenotyping of peripheral blood natural killer (NK) cells from clinical samples by mass cytometry. The protocol consists of three main steps: PBMC incubation with a mix of metal-conjugated antibodies for extracellular phenotyping followed by fixation, permeabilization and incubation with a mix of metal-conjugated antibodies for staining of intracellular proteins, and sample acquisition on a mass cytometer. High-dimensional analysis enables the visualization of NK cell subsets and their phenotypical characteristics. For complete details on the use and execution of this protocol, please refer to Chretien et al. (2021).
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Affiliation(s)
- Amira Ben Amara
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Marie-Sarah Rouviere
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Stéphane Fattori
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Julia Wlosik
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Emilie Gregori
- Centre d'Immunophénomique–Luminy (Ciphe), Inserm US012, CNRS UMS3367, Aix-Marseille University, 13009 Marseille, France
| | - Nicolas Boucherit
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Pierre-Louis Bernard
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Jacques A. Nunès
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France
| | - Norbert Vey
- Hematology Department, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM 105, 13009 Marseille, France
| | - Herve Luche
- Centre d'Immunophénomique–Luminy (Ciphe), Inserm US012, CNRS UMS3367, Aix-Marseille University, 13009 Marseille, France
| | - Laurent Gorvel
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France,Corresponding author
| | - Daniel Olive
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France,Corresponding author
| | - Anne-Sophie Chretien
- Immunomonitoring Department, Institut Paoli-Calmettes, 13009 Marseille, France,Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM105, 13009 Marseille, France,Corresponding author
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