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Wang VG, Liu Z, Martinek J, Foroughi Pour A, Zhou J, Boruchov H, Ray K, Palucka K, Chuang JH. Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments. Commun Biol 2024; 7:1201. [PMID: 39341903 PMCID: PMC11438971 DOI: 10.1038/s42003-024-06902-2] [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: 03/11/2024] [Accepted: 09/16/2024] [Indexed: 10/01/2024] Open
Abstract
The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then verify CISA's applicability across data modalities with melanoma histocytometry whole slide images, revealing that T-cell:macrophage synapse formation correlates with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.
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Affiliation(s)
- Victor G Wang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
| | - Zichao Liu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
| | - Jan Martinek
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - Jie Zhou
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
| | - Hannah Boruchov
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Kelly Ray
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Karolina Palucka
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Jeffrey H Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA.
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2
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Williams HL, Frei AL, Koessler T, Berger MD, Dawson H, Michielin O, Zlobec I. The current landscape of spatial biomarkers for prediction of response to immune checkpoint inhibition. NPJ Precis Oncol 2024; 8:178. [PMID: 39138341 PMCID: PMC11322473 DOI: 10.1038/s41698-024-00671-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 08/05/2024] [Indexed: 08/15/2024] Open
Abstract
Enabling the examination of cell-cell relationships in tissue, spatially resolved omics technologies have revolutionised our perspectives on cancer biology. Clinically, the development of immune checkpoint inhibitors (ICI) has advanced cancer therapeutics. However, a major challenge of effective implementation is the identification of predictive biomarkers of response. In this review we examine the potential added predictive value of spatial biomarkers of response to ICI beyond current clinical benchmarks.
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Affiliation(s)
- Hannah L Williams
- Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
| | - Ana Leni Frei
- Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Thibaud Koessler
- Medical Oncology Department, Geneva University Hospitals, 4 rue Gabrielle-Perret-Gentil, 1205, Geneva, Switzerland
- Swiss Cancer Centre Léman, Lausanne, Geneva, Switzerland
- University of Geneva, Faculty of Medicine, Geneva, Switzerland
| | - Martin D Berger
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Heather Dawson
- Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland
| | - Olivier Michielin
- Medical Oncology Department, Geneva University Hospitals, 4 rue Gabrielle-Perret-Gentil, 1205, Geneva, Switzerland
- Swiss Cancer Centre Léman, Lausanne, Geneva, Switzerland
- University of Geneva, Faculty of Medicine, Geneva, Switzerland
| | - Inti Zlobec
- Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland
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3
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Magrill J, Moldoveanu D, Gu J, Lajoie M, Watson IR. Mapping the single cell spatial immune landscapes of the melanoma microenvironment. Clin Exp Metastasis 2024; 41:301-312. [PMID: 38217840 PMCID: PMC11374855 DOI: 10.1007/s10585-023-10252-4] [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: 07/15/2023] [Accepted: 11/27/2023] [Indexed: 01/15/2024]
Abstract
Melanoma is a highly immunogenic malignancy with an elevated mutational burden, diffuse lymphocytic infiltration, and one of the highest response rates to immune checkpoint inhibitors (ICIs). However, over half of all late-stage patients treated with ICIs will either not respond or develop progressive disease. Spatial imaging technologies are being increasingly used to study the melanoma tumor microenvironment (TME). The goal of such studies is to understand the complex interplay between the stroma, melanoma cells, and immune cell-types as well as their association with treatment response. Investigators seeking a better understanding of the role of cell location within the TME and the importance of spatial expression of biomarkers are increasingly turning to highly multiplexed imaging approaches to more accurately measure immune infiltration as well as to quantify receptor-ligand interactions (such as PD-1 and PD-L1) and cell-cell contacts. CyTOF-IMC (Cytometry by Time of Flight - Imaging Mass Cytometry) has enabled high-dimensional profiling of melanomas, allowing researchers to identify complex cellular subpopulations and immune cell interactions with unprecedented resolution. Other spatial imaging technologies, such as multiplexed immunofluorescence and spatial transcriptomics, have revealed distinct patterns of immune cell infiltration, highlighting the importance of spatial relationships, and their impact in modulating immunotherapy responses. Overall, spatial imaging technologies are just beginning to transform our understanding of melanoma biology, providing new avenues for biomarker discovery and therapeutic development. These technologies hold great promise for advancing personalized medicine to improve patient outcomes in melanoma and other solid malignancies.
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Affiliation(s)
- Jamie Magrill
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Dan Moldoveanu
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Jiayao Gu
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Mathieu Lajoie
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Ian R Watson
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.
- Department of Human Genetics, McGill University, Montréal, QC, Canada.
- Department of Biochemistry, McGill University, Montréal, QC, Canada.
- Research Institute of the McGill University Health Centre, Montréal, QC, Canada.
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4
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Rossi M, Radisky DC. Multiplex Digital Spatial Profiling in Breast Cancer Research: State-of-the-Art Technologies and Applications across the Translational Science Spectrum. Cancers (Basel) 2024; 16:1615. [PMID: 38730568 PMCID: PMC11083340 DOI: 10.3390/cancers16091615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/17/2024] [Accepted: 04/21/2024] [Indexed: 05/13/2024] Open
Abstract
While RNA sequencing and multi-omic approaches have significantly advanced cancer diagnosis and treatment, their limitation in preserving critical spatial information has been a notable drawback. This spatial context is essential for understanding cellular interactions and tissue dynamics. Multiplex digital spatial profiling (MDSP) technologies overcome this limitation by enabling the simultaneous analysis of transcriptome and proteome data within the intact spatial architecture of tissues. In breast cancer research, MDSP has emerged as a promising tool, revealing complex biological questions related to disease evolution, identifying biomarkers, and discovering drug targets. This review highlights the potential of MDSP to revolutionize clinical applications, ranging from risk assessment and diagnostics to prognostics, patient monitoring, and the customization of treatment strategies, including clinical trial guidance. We discuss the major MDSP techniques, their applications in breast cancer research, and their integration in clinical practice, addressing both their potential and current limitations. Emphasizing the strategic use of MDSP in risk stratification for women with benign breast disease, we also highlight its transformative potential in reshaping the landscape of breast cancer research and treatment.
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Affiliation(s)
| | - Derek C. Radisky
- Department of Cancer Biology, Mayo Clinic, Jacksonville, FL 32224, USA;
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5
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Agioti S, Zaravinos A. Immune Cytolytic Activity and Strategies for Therapeutic Treatment. Int J Mol Sci 2024; 25:3624. [PMID: 38612436 PMCID: PMC11011457 DOI: 10.3390/ijms25073624] [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] [Received: 01/31/2024] [Revised: 03/14/2024] [Accepted: 03/22/2024] [Indexed: 04/14/2024] Open
Abstract
Intratumoral immune cytolytic activity (CYT), calculated as the geometric mean of granzyme-A (GZMA) and perforin-1 (PRF1) expression, has emerged as a critical factor in cancer immunotherapy, with significant implications for patient prognosis and treatment outcomes. Immune checkpoint pathways, the composition of the tumor microenvironment (TME), antigen presentation, and metabolic pathways regulate CYT. Here, we describe the various methods with which we can assess CYT. The detection and analysis of tumor-infiltrating lymphocytes (TILs) using flow cytometry or immunohistochemistry provide important information about immune cell populations within the TME. Gene expression profiling and spatial analysis techniques, such as multiplex immunofluorescence and imaging mass cytometry allow the study of CYT in the context of the TME. We discuss the significant clinical implications that CYT has, as its increased levels are associated with positive clinical outcomes and a favorable prognosis. Moreover, CYT can be used as a prognostic biomarker and aid in patient stratification. Altering CYT through the different methods targeting it, offers promising paths for improving treatment responses. Overall, understanding and modulating CYT is critical for improving cancer immunotherapy. Research into CYT and the factors that influence it has the potential to transform cancer treatment and improve patient outcomes.
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Affiliation(s)
- Stephanie Agioti
- Cancer Genetics, Genomics and Systems Biology Laboratory, Basic and Translational Cancer Research Center (BTCRC), 1516 Nicosia, Cyprus;
| | - Apostolos Zaravinos
- Cancer Genetics, Genomics and Systems Biology Laboratory, Basic and Translational Cancer Research Center (BTCRC), 1516 Nicosia, Cyprus;
- Department of Life Sciences, School of Sciences, European University Cyprus, 1516 Nicosia, Cyprus
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6
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Aung TN, Bates KM, Rimm DL. High-Plex Assessment of Biomarkers in Tumors. Mod Pathol 2024; 37:100425. [PMID: 38219953 DOI: 10.1016/j.modpat.2024.100425] [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] [Received: 08/30/2023] [Revised: 01/02/2024] [Accepted: 01/08/2024] [Indexed: 01/16/2024]
Abstract
The assessment of biomarkers plays a critical role in the diagnosis and treatment of many cancers. Biomarkers not only provide diagnostic, prognostic, or predictive information but also can act as effective targets for new pharmaceutical therapies. As the utility of biomarkers increases, it becomes more important to utilize accurate and efficient methods for biomarker discovery and, ultimately, clinical assessment. High-plex imaging studies, defined here as assessment of 8 or more biomarkers on a single slide, have become the method of choice for biomarker discovery and assessment of biomarker spatial context. In this review, we discuss methods of measuring biomarkers in slide-mounted tissue samples, detail the various high-plex methods that allow for the simultaneous assessment of multiple biomarkers in situ, and describe the impact of high-plex biomarker assessment on the future of anatomic pathology.
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Affiliation(s)
- Thazin N Aung
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut
| | - Katherine M Bates
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut
| | - David L Rimm
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut; Department of Internal Medicine (Medical Oncology), Yale University School of Medicine, New Haven, Connecticut.
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7
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Hunter B, Nicorescu I, Foster E, McDonald D, Hulme G, Fuller A, Thomson A, Goldsborough T, Hilkens CMU, Majo J, Milross L, Fisher A, Bankhead P, Wills J, Rees P, Filby A, Merces G. OPTIMAL: An OPTimized Imaging Mass cytometry AnaLysis framework for benchmarking segmentation and data exploration. Cytometry A 2024; 105:36-53. [PMID: 37750225 PMCID: PMC10952805 DOI: 10.1002/cyto.a.24803] [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: 03/28/2023] [Revised: 09/13/2023] [Accepted: 09/18/2023] [Indexed: 09/27/2023]
Abstract
Analysis of imaging mass cytometry (IMC) data and other low-resolution multiplexed tissue imaging technologies is often confounded by poor single-cell segmentation and suboptimal approaches for data visualization and exploration. This can lead to inaccurate identification of cell phenotypes, states, or spatial relationships compared to reference data from single-cell suspension technologies. To this end we have developed the "OPTimized Imaging Mass cytometry AnaLysis (OPTIMAL)" framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualization/clustering, and spatial neighborhood analysis. Using a panel of 27 metal-tagged antibodies recognizing well-characterized phenotypic and functional markers to stain the same Formalin-Fixed Paraffin Embedded (FFPE) human tonsil sample tissue microarray over 12 temporally distinct batches we tested several cell segmentation models, a range of different arcsinh cofactor parameter transformation values, 5 different dimensionality reduction algorithms, and 2 clustering methods. Finally, we assessed the optimal approach for performing neighborhood analysis. We found that single-cell segmentation was improved by the use of an Ilastik-derived probability map but that issues with poor segmentation were only really evident after clustering and cell type/state identification and not always evident when using "classical" bivariate data display techniques. The optimal arcsinh cofactor for parameter transformation was 1 as it maximized the statistical separation between negative and positive signal distributions and a simple Z-score normalization step after arcsinh transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out-performing phenograph in terms of cell type identification. We also found that neighborhood analysis was influenced by the method used for finding neighboring cells with a "disc" pixel expansion outperforming a "bounding box" approach combined with the need for filtering objects based on size and image-edge location. Importantly, OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output and allows for single-cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.
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Affiliation(s)
- Bethany Hunter
- Flow Cytometry Core Facility, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Ioana Nicorescu
- Translational and Clinical Research Institute, Immunity and Inflammation Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Emma Foster
- Image Analysis Unit, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - David McDonald
- Flow Cytometry Core Facility, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Gillian Hulme
- Flow Cytometry Core Facility, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Andrew Fuller
- Flow Cytometry Core Facility, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Amanda Thomson
- Flow Cytometry Core Facility, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Translational and Clinical Research Institute, Immunity and Inflammation Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | | | - Catharien M. U. Hilkens
- Translational and Clinical Research Institute, Immunity and Inflammation Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Joaquim Majo
- Cellular Pathology, Newcastle upon Tyne Hospitals NHS Foundation TrustNewcastle upon TyneUK
| | - Luke Milross
- Transplantation and Regenerative Medicine, Newcastle University Translational and Clinical Research Institute, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Andrew Fisher
- Transplantation and Regenerative Medicine, Newcastle University Translational and Clinical Research Institute, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Peter Bankhead
- Centre for Genomic and Experimental Medicine, CRUK Scotland Centre, and Edinburgh PathologyUniversity of EdinburghEdinburghUK
| | - John Wills
- Department of Veterinary MedicineCambridge UniversityCambridgeUK
- Department of Biomedical EngineeringSwansea UniversitySwansea, WalesUK
| | - Paul Rees
- Department of Biomedical EngineeringSwansea UniversitySwansea, WalesUK
- Imaging PlatformBroad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - Andrew Filby
- Flow Cytometry Core Facility, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - George Merces
- Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
- Image Analysis Unit, Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
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8
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Martinez-Morilla S, Moutafi M, Fernandez AI, Jessel S, Divakar P, Wong PF, Garcia-Milian R, Schalper KA, Kluger HM, Rimm DL. Digital spatial profiling of melanoma shows CD95 expression in immune cells is associated with resistance to immunotherapy. Oncoimmunology 2023; 12:2260618. [PMID: 37781235 PMCID: PMC10540659 DOI: 10.1080/2162402x.2023.2260618] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 09/14/2023] [Indexed: 10/03/2023] Open
Abstract
Although immune checkpoint inhibitor (ICI) therapy has dramatically improved outcome for metastatic melanoma patients, many patients do not benefit. Since adverse events may be severe, biomarkers for resistance would be valuable, especially in the adjuvant setting. We performed high-plex digital spatial profiling (DSP) using the NanoString GeoMx® on 53 pre-treatment specimens from ICI-treated metastatic melanoma cases. We interrogated 77 targets simultaneously in four molecular compartments defined by S100B for tumor, CD68 for macrophages, CD45 for leukocytes, and nonimmune stromal cells defined as regions negative for all three compartment markers but positive for SYTO 13. For DSP validation, we confirmed the results obtained for some immune markers, such as CD8, CD4, CD20, CD68, CD45, and PD-L1, by quantitative immunofluorescence (QIF). In the univariable analysis, 38 variables were associated with outcome, 14 of which remained significant after multivariable adjustment. Among them, CD95 was further validated using multiplex immunofluorescence in the Discovery immunotherapy (ITX) Cohort and an independent validation cohort with similar characteristics, showing an association between high levels of CD95 and shorter progression-free survival. We found that CD95 in stroma was associated with resistance to ICI. With further validation, this biomarker could have value to select patients that will not benefit from immunotherapy.
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Affiliation(s)
| | - Myrto Moutafi
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | - Shlomit Jessel
- Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | | | - Pok Fai Wong
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Rolando Garcia-Milian
- Bioinformatics Support Program, Cushing/Whitney Medical Library, Yale School of Medicine, New Haven, CT, USA
| | - Kurt A. Schalper
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Harriet M. Kluger
- Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - David L. Rimm
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
- Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
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9
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Miller DM, Yadanapudi K, Rai V, Rai SN, Chen J, Frieboes HB, Masters A, McCallum A, Williams BJ. Untangling the web of glioblastoma treatment resistance using a multi-omic and multidisciplinary approach. Am J Med Sci 2023; 366:185-198. [PMID: 37330006 DOI: 10.1016/j.amjms.2023.06.010] [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: 12/15/2022] [Revised: 05/01/2023] [Accepted: 06/13/2023] [Indexed: 06/19/2023]
Abstract
Glioblastoma (GBM), the most common human brain tumor, has been notoriously resistant to treatment. As a result, the dismal overall survival of GBM patients has not changed over the past three decades. GBM has been stubbornly resistant to checkpoint inhibitor immunotherapies, which have been remarkably effective in the treatment of other tumors. It is clear that GBM resistance to therapy is multifactorial. Although therapeutic transport into brain tumors is inhibited by the blood brain barrier, there is evolving evidence that overcoming this barrier is not the predominant factor. GBMs generally have a low mutation burden, exist in an immunosuppressed environment and they are inherently resistant to immune stimulation, all of which contribute to treatment resistance. In this review, we evaluate the contribution of multi-omic approaches (genomic and metabolomic) along with analyzing immune cell populations and tumor biophysical characteristics to better understand and overcome GBM multifactorial resistance to treatment.
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Affiliation(s)
- Donald M Miller
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Medicine, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Kavitha Yadanapudi
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Medicine, School of Medicine, University of Louisville, Louisville, KY, USA
| | - Veeresh Rai
- Brown Cancer Center, University of Louisville, Louisville, KY, USA
| | - Shesh N Rai
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Biostatistics and Informatics Shared Resources, University of Cincinnati Cancer Center, Cincinnati, OH, USA; Cancer Data Science Center of University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Joseph Chen
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Bioengineering, Speed School of Engineering, University of Louisville, Louisville, KY, USA
| | - Hermann B Frieboes
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Bioengineering, Speed School of Engineering, University of Louisville, Louisville, KY, USA; Center for Preventative Medicine, University of Louisville, Louisville, KY, USA
| | - Adrianna Masters
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Radiation Oncology, University of Louisville, Louisville, KY, USA
| | - Abigail McCallum
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Neurosurgery, University of Louisville, Louisville, KY, USA
| | - Brian J Williams
- Brown Cancer Center, University of Louisville, Louisville, KY, USA; Department of Neurosurgery, University of Louisville, Louisville, KY, USA
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10
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Jin Z, Zhou Q, Cheng JN, Jia Q, Zhu B. Heterogeneity of the tumor immune microenvironment and clinical interventions. Front Med 2023; 17:617-648. [PMID: 37728825 DOI: 10.1007/s11684-023-1015-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 06/24/2023] [Indexed: 09/21/2023]
Abstract
The tumor immune microenvironment (TIME) is broadly composed of various immune cells, and its heterogeneity is characterized by both immune cells and stromal cells. During the course of tumor formation and progression and anti-tumor treatment, the composition of the TIME becomes heterogeneous. Such immunological heterogeneity is not only present between populations but also exists on temporal and spatial scales. Owing to the existence of TIME, clinical outcomes can differ when a similar treatment strategy is provided to patients. Therefore, a comprehensive assessment of TIME heterogeneity is essential for developing precise and effective therapies. Facilitated by advanced technologies, it is possible to understand the complexity and diversity of the TIME and its influence on therapy responses. In this review, we discuss the potential reasons for TIME heterogeneity and the current approaches used to explore it. We also summarize clinical intervention strategies based on associated mechanisms or targets to control immunological heterogeneity.
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Affiliation(s)
- Zheng Jin
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China
- Key Laboratory of Tumor Immunotherapy, Chongqing, 400037, China
- Research Institute, GloriousMed Clinical Laboratory (Shanghai) Co. Ltd., Shanghai, 201318, China
- Institute of Life Sciences, Chongqing Medical University, Chongqing, 400016, China
| | - Qin Zhou
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China
- Key Laboratory of Tumor Immunotherapy, Chongqing, 400037, China
- School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Jia-Nan Cheng
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China.
- Key Laboratory of Tumor Immunotherapy, Chongqing, 400037, China.
| | - Qingzhu Jia
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China.
- Key Laboratory of Tumor Immunotherapy, Chongqing, 400037, China.
| | - Bo Zhu
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing, 400037, China.
- Key Laboratory of Tumor Immunotherapy, Chongqing, 400037, China.
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11
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Andhari MD, Antoranz A, De Smet F, Bosisio FM. Recent advancements in tumour microenvironment landscaping for target selection and response prediction in immune checkpoint therapies achieved through spatial protein multiplexing analysis. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2023; 382:207-237. [PMID: 38225104 DOI: 10.1016/bs.ircmb.2023.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2024]
Abstract
Immune checkpoint therapies have significantly advanced cancer treatment. Nevertheless, the high costs and potential adverse effects associated with these therapies highlight the need for better predictive biomarkers to identify patients who are most likely to benefit from treatment. Unfortunately, the existing biomarkers are insufficient to identify such patients. New high-dimensional spatial technologies have emerged as a valuable tool for discovering novel biomarkers by analysing multiple protein markers at a single-cell resolution in tissue samples. These technologies provide a more comprehensive map of tissue composition, cell functionality, and interactions between different cell types in the tumour microenvironment. In this review, we provide an overview of how spatial protein-based multiplexing technologies have fuelled biomarker discovery and advanced the field of immunotherapy. In particular, we will focus on how these technologies contributed to (i) characterise the tumour microenvironment, (ii) understand the role of tumour heterogeneity, (iii) study the interplay of the immune microenvironment and tumour progression, (iv) discover biomarkers for immune checkpoint therapies (v) suggest novel therapeutic strategies.
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Affiliation(s)
- Madhavi Dipak Andhari
- Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium; The Laboratory for Precision Cancer Medicine, Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Asier Antoranz
- Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium; The Laboratory for Precision Cancer Medicine, Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Frederik De Smet
- Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium; The Laboratory for Precision Cancer Medicine, Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Francesca Maria Bosisio
- Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium.
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12
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Wang V, Liu Z, Martinek J, Zhou J, Boruchov H, Ray K, Palucka K, Chuang J. Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments. RESEARCH SQUARE 2023:rs.3.rs-2968528. [PMID: 37398220 PMCID: PMC10312981 DOI: 10.21203/rs.3.rs-2968528/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
The tumor microenvironment (TME) and the cellular interactions within it can be critical to tumor progression and treatment response. Although technologies to generate multiplex images of the TME are advancing, the many ways in which TME imaging data can be mined to elucidate cellular interactions are only beginning to be realized. Here, we present a novel approach for multipronged computational immune synapse analysis (CISA) that reveals T-cell synaptic interactions from multiplex images. CISA enables automated discovery and quantification of immune synapse interactions based on the localization of proteins on cell membranes. We first demonstrate the ability of CISA to detect T-cell:APC (antigen presenting cell) synaptic interactions in two independent human melanoma imaging mass cytometry (IMC) tissue microarray datasets. We then generate melanoma histocytometry whole slide images and verify that CISA can detect similar interactions across data modalities. Interestingly, CISA histoctyometry analysis also reveals that T-cell:macrophage synapse formation is associated with T-cell proliferation. We next show the generality of CISA by extending it to breast cancer IMC images, finding that CISA quantifications of T-cell:B-cell synapses are predictive of improved patient survival. Our work demonstrates the biological and clinical significance of spatially resolving cell-cell synaptic interactions in the TME and provides a robust method to do so across imaging modalities and cancer types.
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Affiliation(s)
| | - Zichao Liu
- 1The Jackson Laboratory for Genomic Medicine
| | | | - Jie Zhou
- The Jackson Laboratory for Genomic Medicine
| | | | - Kelly Ray
- The Jackson Laboratory for Genomic Medicine
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13
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Gavrielatou N, Vathiotis I, Aung TN, Shafi S, Burela S, Fernandez AI, Moutafi M, Burtness B, Economopoulou P, Anastasiou M, Foukas P, Psyrri A, Rimm DL. Digital Spatial Profiling Links Beta-2-microglobulin Expression with Immune Checkpoint Blockade Outcomes in Head and Neck Squamous Cell Carcinoma. CANCER RESEARCH COMMUNICATIONS 2023; 3:558-563. [PMID: 37057033 PMCID: PMC10088911 DOI: 10.1158/2767-9764.crc-22-0299] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 11/02/2022] [Accepted: 03/03/2023] [Indexed: 03/10/2023]
Abstract
Programmed cell death protein-1 (PD-1)-targeted immunotherapy is approved for recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) treatment. Although its efficacy correlates with PD-L1 expression, response is limited even among positive cases. We employed digital spatial profiling (DSP) to discover potential biomarkers of immunotherapy outcomes in HNSCC. Fifty prospectively collected, pretreatment biopsy samples from patients with anti-PD-1-treated R/M HNSCC, were assessed using DSP, for 71 proteins in four molecularly defined compartments (tumor, leukocyte, macrophage, and stroma). Markers were evaluated for associations with progression-free (PFS) and overall survival (OS). High beta-2 microglobulin (B2M), LAG-3, CD25, and 4-1BB in tumor; high B2M, CD45, CD4 in stroma, and low fibronectin in the macrophage compartment, correlated with prolonged PFS. Improved PFS and OS were observed for cases with high B2M by quantitative and mRNA. Findings were validated in an independent cohort for PFS (HR, 0.41; 95% confidence interval, 0.19-0.93; P = 0.034). B2M-high tumors showed enrichment with immune cell and immune checkpoint markers. Our study illustrates B2M expression is associated with improved survival for immune checkpoint inhibitor (ICI)-treated HNSCC. Significance In the current study, DSP revealed the positive association of B2M expression in the tumor compartment with immunotherapy outcomes in R/M HNSCC.
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Affiliation(s)
- Niki Gavrielatou
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | - Ioannis Vathiotis
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | - Thazin Nwe Aung
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | - Saba Shafi
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | - Sneha Burela
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | | | - Myrto Moutafi
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | - Barbara Burtness
- Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, New Haven, Connecticut
| | - Panagiota Economopoulou
- Department of Internal Medicine, Section of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - Maria Anastasiou
- Department of Internal Medicine, Section of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - Periklis Foukas
- Department of Internal Medicine, Section of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - Amanda Psyrri
- Department of Internal Medicine, Section of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - David L. Rimm
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
- Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, New Haven, Connecticut
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14
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Lee S, Vu HM, Lee JH, Lim H, Kim MS. Advances in Mass Spectrometry-Based Single Cell Analysis. BIOLOGY 2023; 12:395. [PMID: 36979087 PMCID: PMC10045136 DOI: 10.3390/biology12030395] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/27/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023]
Abstract
Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.
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Affiliation(s)
- Siheun Lee
- School of Undergraduate Studies, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
| | - Hung M. Vu
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
| | - Jung-Hyun Lee
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
| | - Heejin Lim
- Center for Scientific Instrumentation, Korea Basic Science Institute (KBSI), Cheongju 28119, Republic of Korea
| | - Min-Sik Kim
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
- New Biology Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
- Center for Cell Fate Reprogramming and Control, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic of Korea
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15
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Sheng W, Zhang C, Mohiuddin TM, Al-Rawe M, Zeppernick F, Falcone FH, Meinhold-Heerlein I, Hussain AF. Multiplex Immunofluorescence: A Powerful Tool in Cancer Immunotherapy. Int J Mol Sci 2023; 24:ijms24043086. [PMID: 36834500 PMCID: PMC9959383 DOI: 10.3390/ijms24043086] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/26/2023] [Accepted: 01/31/2023] [Indexed: 02/08/2023] Open
Abstract
Traditional immunohistochemistry (IHC) has already become an essential method of diagnosis and therapy in cancer management. However, this antibody-based technique is limited to detecting a single marker per tissue section. Since immunotherapy has revolutionized the antineoplastic therapy, developing new immunohistochemistry strategies to detect multiple markers simultaneously to better understand tumor environment and predict or assess response to immunotherapy is necessary and urgent. Multiplex immunohistochemistry (mIHC)/multiplex immunofluorescence (mIF), such as multiplex chromogenic IHC and multiplex fluorescent immunohistochemistry (mfIHC), is a new and emerging technology to label multiple biomarkers in a single pathological section. The mfIHC shows a higher performance in cancer immunotherapy. This review summarizes the technologies, which are applied for mfIHC, and discusses how they are employed for immunotherapy research.
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Affiliation(s)
- Wenjie Sheng
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
| | - Chaoyu Zhang
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
| | - T. M. Mohiuddin
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
| | - Marwah Al-Rawe
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
| | - Felix Zeppernick
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
| | - Franco H. Falcone
- Institute for Parasitology, Faculty of Veterinary Medicine, Justus Liebig University Giessen, 35392 Giessen, Germany
| | - Ivo Meinhold-Heerlein
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
| | - Ahmad Fawzi Hussain
- Department of Gynecology and Obstetrics, Medical Faculty, Justus-Liebig-University Giessen, Klinikstr. 33, 35392 Giessen, Germany
- Correspondence:
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16
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Glasson Y, Chépeaux LA, Dumé AS, Lafont V, Faget J, Bonnefoy N, Michaud HA. Single-cell high-dimensional imaging mass cytometry: one step beyond in oncology. Semin Immunopathol 2023; 45:17-28. [PMID: 36598557 PMCID: PMC9812013 DOI: 10.1007/s00281-022-00978-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 12/11/2022] [Indexed: 01/05/2023]
Abstract
Solid tumors have a dynamic ecosystem in which malignant and non-malignant (endothelial, stromal, and immune) cell types constantly interact. Importantly, the abundance, localization, and functional orientation of each cell component within the tumor microenvironment vary significantly over time and in response to treatment. Such intratumoral heterogeneity influences the tumor course and its sensitivity to treatments. Recently, high-dimensional imaging mass cytometry (IMC) has been developed to explore the tumor ecosystem at the single-cell level. In the last years, several studies demonstrated that IMC is a powerful tool to decipher the tumor complexity. In this review, we summarize the potential of this technology and how it may be useful for cancer research (from preclinical to clinical studies).
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Affiliation(s)
- Yaël Glasson
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | - Laure-Agnès Chépeaux
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | - Anne-Sophie Dumé
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | | | - Julien Faget
- IRCM, Univ Montpellier, ICM, Inserm Montpellier, France
| | - Nathalie Bonnefoy
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d’Imagerie de Masse, Inserm Montpellier, France
| | - Henri-Alexandre Michaud
- IRCM, Univ Montpellier, ICM, Plateforme de Cytométrie Et d'Imagerie de Masse, Inserm Montpellier, France.
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17
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Wlosik J, Fattori S, Rochigneux P, Goncalves A, Olive D, Chretien AS. Immune biology of NSCLC revealed by single-cell technologies: implications for the development of biomarkers in patients treated with immunotherapy. Semin Immunopathol 2023; 45:29-41. [PMID: 36414693 PMCID: PMC9974692 DOI: 10.1007/s00281-022-00973-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/31/2022] [Indexed: 11/23/2022]
Abstract
First-line immunotherapy in non-small-cell lung cancer largely improved patients' survival. PD-L1 testing is required before immune checkpoint inhibitor initiation. However, this biomarker fails to accurately predict patients' response. On the other hand, immunotherapy exposes patients to immune-related toxicity, the mechanisms of which are still unclear. Hence, there is an unmet need to develop clinically approved predictive biomarkers to better select patients who will benefit the most from immune checkpoint inhibitors and improve risk management. Single-cell technologies provide unprecedented insight into the tumor and its microenvironment, leading to the discovery of immune cells involved in immune checkpoint inhibitor response or toxicity. In this review, we will underscore the potential of the single-cell approach to identify candidate biomarkers improving non-small-cell lung cancer patients' care.
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Affiliation(s)
- J Wlosik
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University UM105, Inserm U1068, 13009, Marseille, France. .,Immunomonitoring Department, Institut Paoli-Calmettes, 13009, Marseille, France.
| | - S Fattori
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University UM105, Inserm U1068, 13009, Marseille, France.,Immunomonitoring Department, Institut Paoli-Calmettes, 13009, Marseille, France
| | - P Rochigneux
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University UM105, Inserm U1068, 13009, Marseille, France.,Immunomonitoring Department, Institut Paoli-Calmettes, 13009, Marseille, France.,Department of Medical Oncology, Inserm U1068, Aix-Marseille University UM105, CNRS UMR7258, Institute Paoli-Calmettes, 13009, Marseille, France
| | - A Goncalves
- Department of Medical Oncology, Inserm U1068, Aix-Marseille University UM105, CNRS UMR7258, Institute Paoli-Calmettes, 13009, Marseille, France.,Team Cell Polarity, Cell Signaling and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, Inserm U1068UM 105, 13009, Marseille, France
| | - D Olive
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University UM105, Inserm U1068, 13009, Marseille, France.,Immunomonitoring Department, Institut Paoli-Calmettes, 13009, Marseille, France
| | - A S Chretien
- Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University UM105, Inserm U1068, 13009, Marseille, France. .,Immunomonitoring Department, Institut Paoli-Calmettes, 13009, Marseille, France.
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18
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Wrobel J, Harris C, Vandekar S. Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data. Methods Mol Biol 2023; 2629:141-168. [PMID: 36929077 DOI: 10.1007/978-1-0716-2986-4_8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Advances in multiplexed single-cell immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) imaging technologies have enabled the analysis of cell-to-cell spatial relationships that promise to revolutionize our understanding of tissue-based diseases and autoimmune disorders. Multiplex images are collected as multichannel TIFF files; then denoised, segmented to identify cells and nuclei, normalized across slides with protein markers to correct for batch effects, and phenotyped; and then tissue composition and spatial context at the cellular level are analyzed. This chapter discusses methods and software infrastructure for image processing and statistical analysis of mIF/mIHC data.
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Affiliation(s)
- Julia Wrobel
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Coleman Harris
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
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19
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Liu Z, Xun J, Liu S, Wang B, Zhang A, Zhang L, Wang X, Zhang Q. Imaging mass cytometry: High-dimensional and single-cell perspectives on the microenvironment of solid tumours. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 175:140-146. [DOI: 10.1016/j.pbiomolbio.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/07/2022] [Accepted: 10/11/2022] [Indexed: 01/04/2023]
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20
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Wang XX, Wu LH, Dou QY, Ai L, Lu Y, Deng SZ, Liu QQ, Ji H, Zhang HM. Construction of m6A-based prognosis signature and prediction for immune and anti-angiogenic response. Front Mol Biosci 2022; 9:1034928. [PMID: 36339715 PMCID: PMC9634552 DOI: 10.3389/fmolb.2022.1034928] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/12/2022] [Indexed: 11/29/2022] Open
Abstract
Background: Increasing evidence illustrated that m6A regulator-mediated modification plays a crucial role in regulating tumor immune and angiogenesis microenvironment. And the combination of immune checkpoint inhibitor and anti-angiogenic therapy has been approved as new first-line therapy for advanced HCC. This study constructed a novel prognosis signature base on m6A-mediated modification and explored the related mechanism in predicting immune and anti-angiogenic responses. Methods: Gene expression profiles and clinical information were collected from TCGA and GEO. The ssGSEA, MCPCOUNT, and TIMER 2.0 algorithm was used to Estimation of immune cell infiltration. The IC50 of anti-angiogenic drugs in GDSC was calculated by the “pRRophetic” package. IMvigor210 cohort and Liu et al. cohort were used to validate the capability of immunotherapy response. Hepatocellular carcinoma single immune cells sequencing datasets GSE140228 were collected to present the expression landscapes of 5 hub genes in different sites and immune cell subpopulations of HCC patients. Results: Three m6A clusters with distinct immune and angiogenesis microenvironments were identified by consistent cluster analysis based on the expression of m6A regulators. We further constructed a 5-gene prognosis signature (termed as m6Asig-Score) which could predict both immune and anti-angiogenic responses. We illustrated that high m6Asig-Score is associated with poor prognosis, advanced TNM stage, and high TP53 mutation frequency. Besides, the m6Asig-Score was negatively associated with immune checkpoint inhibitors and anti-angiogenic drug response. We further found that two of the five m6Asig-Score inner genes, B2M and SMOX, were associated with immune cell infiltration, immune response, and the sensitivity to sorafenib, which were validated in two independent immunotherapy cohorts and the Genomics of Drug Sensitivity in Cancer (GDSC) database. Conclusion: We constructed a novel prognosis signature and identified B2M and SMOX for predicting immune and anti-angiogenic efficacy in HCC, which may guide the combined treatment strategies of immunotherapy and anti-angiogenic therapy in HCC.
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Affiliation(s)
- Xiang-Xu Wang
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Li-Hong Wu
- Xijing 986 Hospital Department, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Qiong-Yi Dou
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Liping Ai
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Yajie Lu
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Shi-Zhou Deng
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Qing-Qing Liu
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Hongchen Ji
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Hong-Mei Zhang
- Department of Clinical Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shaanxi, China
- *Correspondence: Hong-Mei Zhang,
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21
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Wang C, Wang Z, Yao T, Zhou J, Wang Z. The immune-related role of beta-2-microglobulin in melanoma. Front Oncol 2022; 12:944722. [PMID: 36046045 PMCID: PMC9421255 DOI: 10.3389/fonc.2022.944722] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 07/25/2022] [Indexed: 11/23/2022] Open
Abstract
Despite the remarkable success of immunotherapy in the treatment of melanoma, resistance to these agents still affects patient prognosis and response to therapies. Beta-2-microglobulin (β2M), an important subunit of major histocompatibility complex (MHC) class I, has important biological functions and roles in tumor immunity. In recent years, increasing studies have shown that B2M gene deficiency can inhibit MHC class I antigen presentation and lead to cancer immune evasion by affecting β2M expression. Based on this, B2M gene defect and T cell-based immunotherapy can interact to affect the efficacy of melanoma treatment. Taking into account the many recent advances in B2M-related melanoma immunity, here we discuss the immune function of the B2M gene in tumors, its common genetic alteration in melanoma, and its impact on and related improvements in melanoma immunotherapy. Our comprehensive review of β2M biology and its role in tumor immunotherapy contributes to understanding the potential of B2M gene as a promising melanoma therapeutic target.
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Affiliation(s)
- Chuqiao Wang
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ophthalmic Tumor, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zeqi Wang
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ophthalmic Tumor, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tengteng Yao
- Department of Ophthalmology, Shanghai Tenth People’s Hospital Affiliated to Tongji University, Shanghai, China
| | - Jibo Zhou
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ophthalmic Tumor, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Jibo Zhou, ; Zhaoyang Wang,
| | - Zhaoyang Wang
- Department of Ophthalmology, Shanghai Tenth People’s Hospital Affiliated to Tongji University, Shanghai, China
- *Correspondence: Jibo Zhou, ; Zhaoyang Wang,
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22
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Kuczkiewicz-Siemion O, Sokół K, Puton B, Borkowska A, Szumera-Ciećkiewicz A. The Role of Pathology-Based Methods in Qualitative and Quantitative Approaches to Cancer Immunotherapy. Cancers (Basel) 2022; 14:cancers14153833. [PMID: 35954496 PMCID: PMC9367614 DOI: 10.3390/cancers14153833] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/25/2022] [Accepted: 08/02/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Immunotherapy has become the filar of modern oncological treatment, and programmed death-ligand 1 expression is one of the primary immune markers assessed by pathologists. However, there are still some issues concerning the evaluation of the marker and limited information about the interaction between the tumour and associated immune cells. Recent studies have focused on cancer immunology to try to understand the complex tumour microenvironment, and multiplex imaging methods are more widely used for this purpose. The presented article aims to provide an overall review of a different multiplex in situ method using spectral imaging, supported by automated image-acquisition and software-assisted marker visualisation and interpretation. Multiplex imaging methods could improve the current understanding of complex tumour-microenvironment immunology and could probably help to better match patients to appropriate treatment regimens. Abstract Immune checkpoint inhibitors, including those concerning programmed cell death 1 (PD-1) and its ligand (PD-L1), have revolutionised the cancer therapy approach in the past decade. However, not all patients benefit from immunotherapy equally. The prediction of patient response to this type of therapy is mainly based on conventional immunohistochemistry, which is limited by intraobserver variability, semiquantitative assessment, or single-marker-per-slide evaluation. Multiplex imaging techniques and digital image analysis are powerful tools that could overcome some issues concerning tumour-microenvironment studies. This novel approach to biomarker assessment offers a better understanding of the complicated interactions between tumour cells and their environment. Multiplex labelling enables the detection of multiple markers simultaneously and the exploration of their spatial organisation. Evaluating a variety of immune cell phenotypes and differentiating their subpopulations is possible while preserving tissue histology in most cases. Multiplexing supported by digital pathology could allow pathologists to visualise and understand every cell in a single tissue slide and provide meaning in a complex tumour-microenvironment contexture. This review aims to provide an overview of the different multiplex imaging methods and their application in PD-L1 biomarker assessment. Moreover, we discuss digital imaging techniques, with a focus on slide scanners and software.
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Affiliation(s)
- Olga Kuczkiewicz-Siemion
- Department of Pathology, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
- Diagnostic Hematology Department, Institute of Hematology and Transfusion Medicine, 02-776 Warsaw, Poland
- Correspondence: (O.K.-S.); (A.S.-C.)
| | - Kamil Sokół
- Diagnostic Hematology Department, Institute of Hematology and Transfusion Medicine, 02-776 Warsaw, Poland
| | - Beata Puton
- Department of Pathology, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Aneta Borkowska
- Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
| | - Anna Szumera-Ciećkiewicz
- Department of Pathology, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 Warsaw, Poland
- Correspondence: (O.K.-S.); (A.S.-C.)
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23
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Cheng Y, Wang XM, Hu Q, Sun K, Zhao X, Zhang M, Wang G, Wang H, Xiong Y. Imaging Mass Cytometry Analysis of immune Checkpoint Inhibitor-Related Pneumonitis: A Case Report. Front Immunol 2022; 13:899971. [PMID: 35911750 PMCID: PMC9335486 DOI: 10.3389/fimmu.2022.899971] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Immune checkpoint inhibitor-related pneumonitis (CIP) is a rare but well-recognized immune-related adverse event (irAE), causes 35% of irAE related deaths. However, the mechanism of CIP remains unclear and no evidence-based treatment except for glucocorticoids is available. Herein, we report the case of a patient with metastatic bladder cancer who received tislelizumab and was diagnosed with CIP. The patient underwent transbronchial cryobiopsy. The patient was treated with glucocorticoid, but CIP recurred when the glucocorticoid tapering. The paraffine-embedded lung tissue was sectioned, stained with 31 heavy-metal tagged antibodies, and analyzed using imaging mass cytometry (IMC) technology. We identified multiple immune cell subsets in the lung tissue and observed the infiltration of memory T cells and the CD4+ DC subset. The data indicated the great potential of IMC technology in the identification and characterization of irAEs. Further investigation is warranted to identify the mechanism of action of CIP.
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Affiliation(s)
- Yuan Cheng
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
- *Correspondence: Yuan Cheng, ; Guangfa Wang,
| | - Xiao-Ming Wang
- School of Basic Medical Sciences, Wuhan University, Wuhan, China
| | - Qin Hu
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Kunyan Sun
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Xiang Zhao
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Meng Zhang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
| | - Guangfa Wang
- Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China
- *Correspondence: Yuan Cheng, ; Guangfa Wang,
| | - He Wang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Yan Xiong
- Department of Pathology, Peking University First Hospital, Beijing, China
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24
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Multiplex Tissue Imaging: Spatial Revelations in the Tumor Microenvironment. Cancers (Basel) 2022; 14:cancers14133170. [PMID: 35804939 PMCID: PMC9264815 DOI: 10.3390/cancers14133170] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 06/22/2022] [Accepted: 06/23/2022] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Cancer is the leading cause of death worldwide, and the overall aging of the population results in an increased risk of a cancer diagnosis during a person’s lifetime. Diagnosis and treatment at an early stage will typically increase the chances of survival. Tumors can develop therapy resistance, and it is difficult to predict how individual patients will respond to therapy. Most studies that aim to resolve this problem have focused on studying the composition and characteristics of dissociated tumors, while ignoring the role of cell localization and interactions within the tumor microenvironment. In the past decade, technological innovations have enabled multiplex imaging analyses of intact tumors to study localization and interaction parameters, which can be used as biomarkers, or can be correlated with treatment responses and clinical outcomes. Abstract The tumor microenvironment is a complex ecosystem containing various cell types, such as immune cells, fibroblasts, and endothelial cells, which interact with the tumor cells. In recent decades, the cancer research field has gained insight into the cellular subtypes that are involved in tumor microenvironment heterogeneity. Moreover, it has become evident that cellular interactions in the tumor microenvironment can either promote or inhibit tumor development, progression, and drug resistance, depending on the context. Multiplex spatial analysis methods have recently been developed; these have offered insight into how cellular crosstalk dynamics and heterogeneity affect cancer prognoses and responses to treatment. Multiplex (imaging) technologies and computational analysis methods allow for the spatial visualization and quantification of cell–cell interactions and properties. These technological advances allow for the discovery of cellular interactions within the tumor microenvironment and provide detailed single-cell information on properties that define cellular behavior. Such analyses give insights into the prognosis and mechanisms of therapy resistance, which is still an urgent problem in the treatment of multiple types of cancer. Here, we provide an overview of multiplex imaging technologies and concepts of downstream analysis methods to investigate cell–cell interactions, how these studies have advanced cancer research, and their potential clinical implications.
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25
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Moldoveanu D, Ramsay L, Lajoie M, Anderson-Trocme L, Lingrand M, Berry D, Perus LJM, Wei Y, Moraes C, Alkallas R, Rajkumar S, Zuo D, Dankner M, Xu EH, Bertos NR, Najafabadi HS, Gravel S, Costantino S, Richer MJ, Lund AW, Del Rincon SV, Spatz A, Miller WH, Jamal R, Lapointe R, Mes-Masson AM, Turcotte S, Petrecca K, Dumitra S, Meguerditchian AN, Richardson K, Tremblay F, Wang B, Chergui M, Guiot MC, Watters K, Stagg J, Quail DF, Mihalcioiu C, Meterissian S, Watson IR. Spatially mapping the immune landscape of melanoma using imaging mass cytometry. Sci Immunol 2022; 7:eabi5072. [PMID: 35363543 DOI: 10.1126/sciimmunol.abi5072] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Melanoma is an immunogenic cancer with a high response rate to immune checkpoint inhibitors (ICIs). It harbors a high mutation burden compared with other cancers and, as a result, has abundant tumor-infiltrating lymphocytes (TILs) within its microenvironment. However, understanding the complex interplay between the stroma, tumor cells, and distinct TIL subsets remains a substantial challenge in immune oncology. To properly study this interplay, quantifying spatial relationships of multiple cell types within the tumor microenvironment is crucial. To address this, we used cytometry time-of-flight (CyTOF) imaging mass cytometry (IMC) to simultaneously quantify the expression of 35 protein markers, characterizing the microenvironment of 5 benign nevi and 67 melanomas. We profiled more than 220,000 individual cells to identify melanoma, lymphocyte subsets, macrophage/monocyte, and stromal cell populations, allowing for in-depth spatial quantification of the melanoma microenvironment. We found that within pretreatment melanomas, the abundance of proliferating antigen-experienced cytotoxic T cells (CD8+CD45RO+Ki67+) and the proximity of antigen-experienced cytotoxic T cells to melanoma cells were associated with positive response to ICIs. Our study highlights the potential of multiplexed single-cell technology to quantify spatial cell-cell interactions within the tumor microenvironment to understand immune therapy responses.
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Affiliation(s)
- Dan Moldoveanu
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,McGill University Health Centre, Montréal, QC, Canada.,Department of Surgery, Division of General Surgery, McGill University, Montréal, QC, Canada
| | - LeeAnn Ramsay
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Mathieu Lajoie
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Luke Anderson-Trocme
- McGill University Genome Centre, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Marine Lingrand
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,Department of Biochemistry, McGill University, Montréal, QC, Canada
| | - Diana Berry
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,Department of Biochemistry, McGill University, Montréal, QC, Canada
| | - Lucas J M Perus
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Yuhong Wei
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Cleber Moraes
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Rached Alkallas
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,McGill University Genome Centre, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Shivshankari Rajkumar
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,Department of Biochemistry, McGill University, Montréal, QC, Canada
| | - Dongmei Zuo
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Matthew Dankner
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Eric Hongbo Xu
- Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - Nicholas R Bertos
- Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - Hamed S Najafabadi
- McGill University Genome Centre, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Simon Gravel
- McGill University Genome Centre, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada
| | | | - Martin J Richer
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Amanda W Lund
- Ronald O. Perelman Department of Dermatology and Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
| | - Sonia V Del Rincon
- Jewish General Hospital, McGill University, Montréal, QC, Canada.,Lady Davis Institute for Medical Research, Montréal, QC, Canada
| | - Alan Spatz
- McGill University Health Centre, Montréal, QC, Canada.,Lady Davis Institute for Medical Research, Montréal, QC, Canada.,McGill University, Montréal, QC, Canada
| | - Wilson H Miller
- Jewish General Hospital, McGill University, Montréal, QC, Canada.,Lady Davis Institute for Medical Research, Montréal, QC, Canada
| | - Rahima Jamal
- Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM) and Institut du Cancer de Montréal, Montréal, QC, Canada
| | - Réjean Lapointe
- Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM) and Institut du Cancer de Montréal, Montréal, QC, Canada.,Département de Médecine, Faculté de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Anne-Marie Mes-Masson
- Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM) and Institut du Cancer de Montréal, Montréal, QC, Canada.,Département de Médecine, Faculté de Médecine, Université de Montréal, Montréal, QC, Canada
| | - Simon Turcotte
- Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM) and Institut du Cancer de Montréal, Montréal, QC, Canada
| | - Kevin Petrecca
- Montreal Neurological Institute and Hospital, Montréal, QC, Canada
| | - Sinziana Dumitra
- McGill University Health Centre, Montréal, QC, Canada.,Department of Surgery, Division of General Surgery, McGill University, Montréal, QC, Canada.,Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - Ari-Nareg Meguerditchian
- McGill University Health Centre, Montréal, QC, Canada.,Department of Surgery, Division of General Surgery, McGill University, Montréal, QC, Canada.,Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | | | - Francine Tremblay
- McGill University Health Centre, Montréal, QC, Canada.,Department of Surgery, Division of General Surgery, McGill University, Montréal, QC, Canada
| | - Beatrice Wang
- McGill University Health Centre, Montréal, QC, Canada.,Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - May Chergui
- McGill University Health Centre, Montréal, QC, Canada
| | - Marie-Christine Guiot
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,McGill University Health Centre, Montréal, QC, Canada.,Montreal Neurological Institute and Hospital, Montréal, QC, Canada
| | - Kevin Watters
- McGill University Health Centre, Montréal, QC, Canada
| | - John Stagg
- Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM) and Institut du Cancer de Montréal, Montréal, QC, Canada
| | - Daniela F Quail
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,Department of Physiology, McGill University, Montréal, QC, Canada
| | - Catalin Mihalcioiu
- McGill University Health Centre, Montréal, QC, Canada.,Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - Sarkis Meterissian
- McGill University Health Centre, Montréal, QC, Canada.,Department of Surgery, Division of General Surgery, McGill University, Montréal, QC, Canada.,Research Institute of the McGill University Health Centre, Montréal, QC, Canada
| | - Ian R Watson
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.,Department of Biochemistry, McGill University, Montréal, QC, Canada.,Research Institute of the McGill University Health Centre, Montréal, QC, Canada
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26
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Guo X, Jessel S, Qu R, Kluger Y, Chen TM, Hollander L, Safirstein R, Nelson B, Cha C, Bosenberg M, Jilaveanu LB, Rimm D, Rothlin CV, Kluger HM, Desir GV. Inhibition of renalase drives tumour rejection by promoting T cell activation. Eur J Cancer 2022; 165:81-96. [PMID: 35219026 PMCID: PMC8940682 DOI: 10.1016/j.ejca.2022.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 12/30/2021] [Accepted: 01/10/2022] [Indexed: 12/25/2022]
Abstract
BACKGROUND Although programmed cell death protein 1 (PD-1) inhibitors have revolutionised treatment for advanced melanoma, not all patients respond. We previously showed that inhibition of the flavoprotein renalase (RNLS) in preclinical melanoma models decreases tumour growth. We hypothesised that RNLS inhibition promotes tumour rejection by effects on the tumour microenvironment (TME). METHODS We used two distinct murine melanoma models, studied in RNLS knockout (KO) or wild-type (WT) mice. WT mice were treated with the anti-RNLS antibody, m28, with or without anti-PD-1. 10X single-cell RNA-sequencing was used to identify transcriptional differences between treatment groups, and tumour cell content was interrogated by flow cytometry. Samples from patients treated with immunotherapy were examined for RNLS expression by quantitative immunofluorescence. RESULTS RNLS KO mice injected with wild-type melanoma cells reject their tumours, supporting the importance of RNLS in cells in the TME. This effect was blunted by anti-cluster of differentiation 3. However, MØ-specific RNLS ablation was insufficient to abrogate tumour formation. Anti-RNLS antibody treatment of melanoma-bearing mice resulted in enhanced T cell infiltration and activation and resulted in immune memory on rechallenging mice with injection of melanoma cells. At the single-cell level, treatment with anti-RNLS antibodies resulted in increased tumour density of MØ, neutrophils and lymphocytes and increased expression of IFNγ and granzyme B in natural killer cells and T cells. Intratumoural Forkhead Box P3 + CD4 cells were decreased. In two distinct murine melanoma models, we showed that melanoma-bearing mice treated with anti-RNLS antibodies plus anti-PD-1 had superior tumour shrinkage and survival than with either treatment alone. Importantly, in pretreatment samples from patients treated with PD-1 inhibitors, high RNLS expression was associated with decreased survival (log-rank P = 0.006), independent of other prognostic variables. CONCLUSIONS RNLS KO results in melanoma tumour regression in a T-cell-dependent fashion. Anti-RNLS antibodies enhance anti-PD-1 activity in two distinct aggressive murine melanoma models resistant to PD-1 inhibitors, supporting the development of anti-RNLS antibodies with PD-1 inhibitors as a novel approach for melanomas poorly responsive to anti-PD-1.
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Affiliation(s)
- Xiaojia Guo
- Department of Medicine Section of Nephrology, Yale University, New Haven, CT, USA
| | - Shlomit Jessel
- Department of Medicine Section of Medical Oncology, Yale University, New Haven, CT, USA
| | - Rihao Qu
- Department of Medicine Pathology, Yale University, New Haven, CT, USA
| | - Yuval Kluger
- Department of Medicine Pathology, Yale University, New Haven, CT, USA
| | - Tian-Min Chen
- Department of Medicine Section of Nephrology, Yale University, New Haven, CT, USA
| | - Lindsay Hollander
- Department of Medicine Section of Nephrology, Yale University, New Haven, CT, USA
| | - Robert Safirstein
- Department of Medicine Section of Nephrology, Yale University, New Haven, CT, USA; Department of Medicine VACHS, Yale University, New Haven, CT, USA
| | - Bryce Nelson
- Department of Medicine Pharmacology, Yale University, New Haven, CT, USA
| | - Charles Cha
- Department of Medicine Surgery, Yale University, New Haven, CT, USA
| | - Marcus Bosenberg
- Department of Medicine Section of Medical Oncology, Yale University, New Haven, CT, USA
| | - Lucia B Jilaveanu
- Department of Medicine Section of Medical Oncology, Yale University, New Haven, CT, USA
| | - David Rimm
- Department of Medicine Pathology, Yale University, New Haven, CT, USA
| | - Carla V Rothlin
- Department of Medicine Immunology, Yale University, New Haven, CT, USA
| | - Harriet M Kluger
- Department of Medicine Section of Medical Oncology, Yale University, New Haven, CT, USA
| | - Gary V Desir
- Department of Medicine Section of Nephrology, Yale University, New Haven, CT, USA; Department of Medicine VACHS, Yale University, New Haven, CT, USA; Department of Medicine Yale School of Medicine, Yale University, New Haven, CT, USA.
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27
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Le Rochais M, Hemon P, Pers JO, Uguen A. Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research. Front Immunol 2022; 13:859414. [PMID: 35432353 PMCID: PMC9009368 DOI: 10.3389/fimmu.2022.859414] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 03/10/2022] [Indexed: 12/21/2022] Open
Abstract
Imaging mass cytometry (IMC) enables the in situ analysis of in-depth-phenotyped cells in their native microenvironment within the preserved architecture of a single tissue section. To date, it permits the simultaneous analysis of up to 50 different protein- markers targeted by metal-conjugated antibodies. The application of IMC in the field of cancer research may notably help 1) to define biomarkers of prognostic and theragnostic significance for current and future treatments against well-established and novel therapeutic targets and 2) to improve our understanding of cancer progression and its resistance mechanisms to immune system and how to overcome them. In the present article, we not only provide a literature review on the use of the IMC in cancer-dedicated studies but we also present the IMC method and discuss its advantages and limitations among methods dedicated to deciphering the complexity of cancer tissue.
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Affiliation(s)
- Marion Le Rochais
- B Lymphocytes, Autoimmunity and Immunotherapies, UMR1227, Immunology Department, Augustin Morvan Hospital, Brest, France
- Pathology Department, Augustin Morvan Hospital, Brest, France
| | - Patrice Hemon
- B Lymphocytes, Autoimmunity and Immunotherapies, UMR1227, Immunology Department, Augustin Morvan Hospital, Brest, France
| | - Jacques-Olivier Pers
- B Lymphocytes, Autoimmunity and Immunotherapies, UMR1227, Immunology Department, Augustin Morvan Hospital, Brest, France
| | - Arnaud Uguen
- B Lymphocytes, Autoimmunity and Immunotherapies, UMR1227, Immunology Department, Augustin Morvan Hospital, Brest, France
- Pathology Department, Augustin Morvan Hospital, Brest, France
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28
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Cereceda K, Jorquera R, Villarroel-Espíndola F. Advances in mass cytometry and its applicability to digital pathology in clinical-translational cancer research. ADVANCES IN LABORATORY MEDICINE 2022; 3:5-29. [PMID: 37359436 PMCID: PMC10197474 DOI: 10.1515/almed-2021-0075] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 07/16/2021] [Indexed: 06/28/2023]
Abstract
The development and subsequent adaptation of mass cytometry for the histological analysis of tissue sections has allowed the simultaneous spatial characterization of multiple components. This is useful to find the correlation between the genotypic and phenotypic profile of tumor cells and their environment in clinical-translational studies. In this revision, we provide an overview of the most relevant hallmarks in the development, implementation and application of multiplexed imaging in the study of cancer and other conditions. A special focus is placed on studies based on imaging mass cytometry (IMC) and multiplexed ion beam imaging (MIBI). The purpose of this review is to help our readers become familiar with the verification techniques employed on this tool and outline the multiple applications reported in the literature. This review will also provide guidance on the use of IMC or MIBI in any field of biomedical research.
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Affiliation(s)
- Karina Cereceda
- Laboratorio de Medicina Traslacional, Instituto Oncológico Fundación Arturo López Pérez, Santiago, Chile
| | - Roddy Jorquera
- Laboratorio de Medicina Traslacional, Instituto Oncológico Fundación Arturo López Pérez, Santiago, Chile
| | - Franz Villarroel-Espíndola
- Laboratorio de Medicina Traslacional, Instituto Oncológico Fundación Arturo López Pérez, Santiago, Chile
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29
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Hickey JW, Neumann EK, Radtke AJ, Camarillo JM, Beuschel RT, Albanese A, McDonough E, Hatler J, Wiblin AE, Fisher J, Croteau J, Small EC, Sood A, Caprioli RM, Angelo RM, Nolan GP, Chung K, Hewitt SM, Germain RN, Spraggins JM, Lundberg E, Snyder MP, Kelleher NL, Saka SK. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging. Nat Methods 2022; 19:284-295. [PMID: 34811556 PMCID: PMC9264278 DOI: 10.1038/s41592-021-01316-y] [Citation(s) in RCA: 144] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 09/15/2021] [Indexed: 02/07/2023]
Abstract
Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.
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Affiliation(s)
- John W Hickey
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Elizabeth K Neumann
- Department of Biochemistry, Vanderbilt University, Nashville, TN, USA
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA
| | - Andrea J Radtke
- Lymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
| | - Jeannie M Camarillo
- Departments of Chemistry, Molecular Biosciences and the National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | - Rebecca T Beuschel
- Lymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Alexandre Albanese
- Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Boston Children's Hospital, Division of Hematology/Oncology, Boston, MA, USA
| | | | - Julia Hatler
- Antibody Development Department, Bio-Techne, Minneapolis, MN, USA
| | - Anne E Wiblin
- Department of Research and Development, Abcam, Cambridge, UK
| | - Jeremy Fisher
- Department of Research and Development, Cell Signaling Technology, Danvers, MA, USA
| | - Josh Croteau
- Department of Applications Science, BioLegend, San Diego, CA, USA
| | | | | | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, Nashville, TN, USA
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - R Michael Angelo
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Garry P Nolan
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kwanghun Chung
- Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Chemical Engineering, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, Republic of Korea
- Yonsei-IBS Institute, Yonsei University, Seoul, Republic of Korea
| | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ronald N Germain
- Lymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Jeffrey M Spraggins
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Neil L Kelleher
- Departments of Chemistry, Molecular Biosciences and the National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | - Sinem K Saka
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
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30
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Chen HY, Palendira U, Feng CG. Navigating the cellular landscape in tissue: Recent advances in defining the pathogenesis of human disease. Comput Struct Biotechnol J 2022; 20:5256-5263. [PMID: 36212528 PMCID: PMC9519395 DOI: 10.1016/j.csbj.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/04/2022] [Accepted: 09/04/2022] [Indexed: 11/19/2022] Open
Affiliation(s)
- Helen Y. Chen
- Immunology and Host Defence Group, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, NSW, Australia
- Centenary Institute, The University of Sydney, NSW, Australia
| | - Umaimainthan Palendira
- Immunology and Host Defence Group, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, NSW, Australia
- Centenary Institute, The University of Sydney, NSW, Australia
| | - Carl G. Feng
- Immunology and Host Defence Group, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, NSW, Australia
- Centenary Institute, The University of Sydney, NSW, Australia
- Corresponding author at: Level 5 (East) The Charles Perkins Centre (D17), The University of Sydney, NSW, 2006, Australia
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31
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Kakade VR, Weiss M, Cantley LG. Using Imaging Mass Cytometry to Define Cell Identities and Interactions in Human Tissues. Front Physiol 2021; 12:817181. [PMID: 35002783 PMCID: PMC8727440 DOI: 10.3389/fphys.2021.817181] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 11/25/2021] [Indexed: 12/30/2022] Open
Abstract
In the evolving landscape of highly multiplexed imaging techniques that can be applied to study complex cellular microenvironments, this review characterizes the use of imaging mass cytometry (IMC) to study the human kidney. We provide technical details for antibody validation, cell segmentation, and data analysis specifically tailored to human kidney samples, and elaborate on phenotyping of kidney cell types and novel insights that IMC can provide regarding pathophysiological processes in the injured or diseased kidney. This review will provide the reader with the necessary background to understand both the power and the limitations of IMC and thus support better perception of how IMC analysis can improve our understanding of human disease pathogenesis and can be integrated with other technologies such as single cell sequencing and proteomics to provide spatial context to cellular data.
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Affiliation(s)
| | | | - Lloyd G. Cantley
- Section of Nephrology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, United States
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Zhang J, Song J, Sheng J, Bai X, Liang T. Multiplex imaging reveals the architecture of the tumor immune microenvironment. Cancer Biol Med 2021; 18:j.issn.2095-3941.2021.0494. [PMID: 34709000 PMCID: PMC8610164 DOI: 10.20892/j.issn.2095-3941.2021.0494] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 09/23/2021] [Indexed: 11/21/2022] Open
Affiliation(s)
- Junlei Zhang
- Department of Hepatobiliary and Pancreatic Surgery; Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine; Zhejiang University Cancer Centre, Zhejiang University, Hangzhou 310002, China
| | - Jinyuan Song
- Department of Hepatobiliary and Pancreatic Surgery; Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine; Zhejiang University Cancer Centre, Zhejiang University, Hangzhou 310002, China
| | - Jianpeng Sheng
- Department of Hepatobiliary and Pancreatic Surgery; Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine; Zhejiang University Cancer Centre, Zhejiang University, Hangzhou 310002, China
| | - Xueli Bai
- Department of Hepatobiliary and Pancreatic Surgery; Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine; Zhejiang University Cancer Centre, Zhejiang University, Hangzhou 310002, China
| | - Tingbo Liang
- Department of Hepatobiliary and Pancreatic Surgery; Zhejiang Provincial Key Laboratory of Pancreatic Disease, the First Affiliated Hospital, Zhejiang University School of Medicine; Zhejiang University Cancer Centre, Zhejiang University, Hangzhou 310002, China
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Liotta LA, Pappalardo PA, Carpino A, Haymond A, Howard M, Espina V, Wulfkuhle J, Petricoin E. Laser Capture Proteomics: spatial tissue molecular profiling from the bench to personalized medicine. Expert Rev Proteomics 2021; 18:845-861. [PMID: 34607525 PMCID: PMC10720974 DOI: 10.1080/14789450.2021.1984886] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 09/21/2021] [Indexed: 10/20/2022]
Abstract
INTRODUCTION Laser Capture Microdissection (LCM) uses a laser to isolate, or capture, specific cells of interest in a complex heterogeneous tissue section, under direct microscopic visualization. Recently, there has been a surge of publications using LCM for tissue spatial molecular profiling relevant to a wide range of research topics. AREAS COVERED We summarize the many advances in tissue Laser Capture Proteomics (LCP) using mass spectrometry for discovery, and protein arrays for signal pathway network mapping. This review emphasizes: a) transition of LCM phosphoproteomics from the lab to the clinic for individualized cancer therapy, and b) the emerging frontier of LCM single cell molecular analysis combining proteomics with genomic, and transcriptomic analysis. The search strategy was based on the combination of MeSH terms with expert refinement. EXPERT OPINION LCM is complemented by a rich set of instruments, methodology protocols, and analytical A.I. (artificial intelligence) software for basic and translational research. Resolution is advancing to the tissue single cell level. A vision for the future evolution of LCM is presented. Emerging LCM technology is combining digital and AI guided remote imaging with automation, and telepathology, to a achieve multi-omic profiling that was not previously possible.
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Affiliation(s)
- Lance A. Liotta
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Philip A. Pappalardo
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Alan Carpino
- Fluidigm Corporation, South San Francisco, CA, USA
| | - Amanda Haymond
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Marissa Howard
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Virginia Espina
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Julie Wulfkuhle
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
| | - Emanuel Petricoin
- Center For Applied Proteomics and Molecular Medicine (CAPMM) School of Systems Biology, College of Sciences, George Mason University, Manassas, VA 20110, USA
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Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data. Cancers (Basel) 2021; 13:cancers13123031. [PMID: 34204319 PMCID: PMC8233801 DOI: 10.3390/cancers13123031] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/11/2021] [Accepted: 06/14/2021] [Indexed: 12/21/2022] Open
Abstract
Simple Summary Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME. Abstract Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or “zero-inflated” data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.
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Beta2-microglobulin(B2M) in cancer immunotherapies: Biological function, resistance and remedy. Cancer Lett 2021; 517:96-104. [PMID: 34129878 DOI: 10.1016/j.canlet.2021.06.008] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 05/31/2021] [Accepted: 06/09/2021] [Indexed: 12/30/2022]
Abstract
Cancer immunotherapies have made much headway during the past decades. Techniques including the immune checkpoint inhibition (ICI) and adoptive cell therapy (ACT) have harvested impressive efficacy and provided far-reaching tools for treating cancer patients. However, due to inadequate priming of the immune system, a certain subgroup of patients remains resistant to cancer immunotherapies during or after the treatment. β2-microglobulin (B2M) is an important subunit of major histocompatibility complex (MHC) class I which exerts substantive biological functions in tumorigenesis and immune control. Accumulating evidence has shown that alterations of B2M gene and B2M proteins contribute to poor reaction to cancer immunotherapies by dampening antigen presentation. Here, we discuss the basic biological functions of B2M, its distribution in a spectrum of cancers, and current understanding of its role in ICI, cancer vaccines and chimeric antigen receptor T cell (CAR-T) therapies. Furthermore, we summarize some promising therapeutic strategies to improve the efficacy inhibited by B2M defects.
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Liu J, Qu S, Zhang T, Gao Y, Shi H, Song K, Chen W, Yin W. Applications of Single-Cell Omics in Tumor Immunology. Front Immunol 2021; 12:697412. [PMID: 34177965 PMCID: PMC8221107 DOI: 10.3389/fimmu.2021.697412] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 05/17/2021] [Indexed: 12/20/2022] Open
Abstract
The tumor microenvironment (TME) is an ecosystem that contains various cell types, including cancer cells, immune cells, stromal cells, and many others. In the TME, cancer cells aggressively proliferate, evolve, transmigrate to the circulation system and other organs, and frequently communicate with adjacent immune cells to suppress local tumor immunity. It is essential to delineate this ecosystem's complex cellular compositions and their dynamic intercellular interactions to understand cancer biology and tumor immunology and to benefit tumor immunotherapy. But technically, this is extremely challenging due to the high complexities of the TME. The rapid developments of single-cell techniques provide us powerful means to systemically profile the multiple omics status of the TME at a single-cell resolution, shedding light on the pathogenic mechanisms of cancers and dysfunctions of tumor immunity in an unprecedently resolution. Furthermore, more advanced techniques have been developed to simultaneously characterize multi-omics and even spatial information at the single-cell level, helping us reveal the phenotypes and functionalities of disease-specific cell populations more comprehensively. Meanwhile, the connections between single-cell data and clinical characteristics are also intensively interrogated to achieve better clinical diagnosis and prognosis. In this review, we summarize recent progress in single-cell techniques, discuss their technical advantages, limitations, and applications, particularly in tumor biology and immunology, aiming to promote the research of cancer pathogenesis, clinically relevant cancer diagnosis, prognosis, and immunotherapy design with the help of single-cell techniques.
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Affiliation(s)
- Junwei Liu
- Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Saisi Qu
- Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Tongtong Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The Center for Integrated Oncology and Precision Medicine, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yufei Gao
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
| | - Hongyu Shi
- Department of Biological Testing, Zhejiang Puluoting Health Technology Co., Ltd., Hangzhou, China
| | - Kaichen Song
- Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Wei Chen
- Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- School of Mechanical Engineering, Zhejiang University, Hangzhou, China
| | - Weiwei Yin
- Department of Cardiology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Key Laboratory for Biomedical Engineering of the Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
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Elaldi R, Hemon P, Petti L, Cosson E, Desrues B, Sudaka A, Poissonnet G, Van Obberghen-Schilling E, Pers JO, Braud VM, Anjuère F, Meghraoui-Kheddar A. High Dimensional Imaging Mass Cytometry Panel to Visualize the Tumor Immune Microenvironment Contexture. Front Immunol 2021; 12:666233. [PMID: 33936105 PMCID: PMC8085494 DOI: 10.3389/fimmu.2021.666233] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 03/29/2021] [Indexed: 12/22/2022] Open
Abstract
The integrative analysis of tumor immune microenvironment (TiME) components, their interactions and their microanatomical distribution is mandatory to better understand tumor progression. Imaging Mass Cytometry (IMC) is a high dimensional tissue imaging system which allows the comprehensive and multiparametric in situ exploration of tumor microenvironments at a single cell level. We describe here the design of a 39-antibody IMC panel for the staining of formalin-fixed paraffin-embedded human tumor sections. We also provide an optimized staining procedure and details of the experimental workflow. This panel deciphers the nature of immune cells, their functions and their interactions with tumor cells and cancer-associated fibroblasts as well as with other TiME structural components known to be associated with tumor progression like nerve fibers and tumor extracellular matrix proteins. This panel represents a valuable innovative and powerful tool for fundamental and clinical studies that could be used for the identification of prognostic biomarkers and mechanisms of resistance to current immunotherapies.
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Affiliation(s)
- Roxane Elaldi
- Université Côte d'Azur, CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France.,Institut Universitaire de la Face et du Cou, Nice, France
| | - Patrice Hemon
- U1227, LBAI, University of Brest, INSERM, CHU de Brest, Brest, France
| | - Luciana Petti
- Université Côte d'Azur, CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France
| | - Estelle Cosson
- Université Côte d'Azur, CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France
| | | | - Anne Sudaka
- Centre Antoine Lacassagne, Anatomopathology Laboratory and Human Biobank, Nice, France
| | | | | | | | - Veronique M Braud
- Université Côte d'Azur, CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France
| | - Fabienne Anjuère
- Université Côte d'Azur, CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France
| | - Aïda Meghraoui-Kheddar
- Université Côte d'Azur, CNRS UMR7275, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France
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