1
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Zhou Y, Li H, Tse E, Sun H. Metal-detection based techniques and their applications in metallobiology. Chem Sci 2024; 15:10264-10280. [PMID: 38994399 PMCID: PMC11234822 DOI: 10.1039/d4sc00108g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Accepted: 06/05/2024] [Indexed: 07/13/2024] Open
Abstract
Metals are essential for human health and play a crucial role in numerous biological processes and pathways. Gaining a deeper insight into these biological events will facilitate novel strategies for disease prevention, early detection, and personalized treatment. In recent years, there has been significant progress in the development of metal-detection based techniques from single cell metallome and proteome profiling to multiplex imaging, which greatly enhance our comprehension of the intricate roles played by metals in complex biological systems. This perspective summarizes the recent progress in advanced metal-detection based techniques and highlights successful applications in elucidating the roles of metals in biology and medicine. Technologies including machine learning that couple with single-cell analysis such as mass cytometry and their application in metallobiology, cancer biology and immunology are also emphasized. Finally, we provide insights into future prospects and challenges involved in metal-detection based techniques, with the aim of inspiring further methodological advancements and applications that are accessible to chemists, biologists, and clinicians.
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Affiliation(s)
- Ying Zhou
- Department of Chemistry, CAS-HKU Joint Laboratory of Metallomics for Health and Environment, The University of Hong Kong Pokfulam Road Hong Kong SAR P. R. China
| | - Hongyan Li
- Department of Chemistry, CAS-HKU Joint Laboratory of Metallomics for Health and Environment, The University of Hong Kong Pokfulam Road Hong Kong SAR P. R. China
| | - Eric Tse
- Department of Medicine, LKS Faculty of Medicine, The University of Hong Kong Pokfulam Road Hong Kong SAR P. R. China
| | - Hongzhe Sun
- Department of Chemistry, CAS-HKU Joint Laboratory of Metallomics for Health and Environment, The University of Hong Kong Pokfulam Road Hong Kong SAR P. R. China
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2
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Shen R, Huang Y, Kong D, Ma W, Liu J, Zhang H, Cheng S, Feng L. Spatial distribution pattern of immune cells is associated with patient prognosis in colorectal cancer. J Transl Med 2024; 22:606. [PMID: 38951801 PMCID: PMC11218284 DOI: 10.1186/s12967-024-05418-x] [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: 03/10/2024] [Accepted: 06/19/2024] [Indexed: 07/03/2024] Open
Abstract
BACKGROUND The spatial context of tumor-infiltrating immune cells (TIICs) is important in predicting colorectal cancer (CRC) patients' clinical outcomes. However, the prognostic value of the TIIC spatial distribution is unknown. Thus, we aimed to investigate the association between TIICs in situ and patient prognosis in a large CRC sample. METHODS We implemented multiplex immunohistochemistry staining technology in 190 CRC samples to quantify 14 TIIC subgroups in situ. To delineate the spatial relationship of TIICs to tumor cells, tissue slides were segmented into tumor cell and microenvironment compartments based on image recognition technology, and the distance between immune and tumor cells was calculated by implementing the computational pipeline phenoptr. RESULTS MPO+ neutrophils and CD68+IDO1+ tumor-associated macrophages (TAMs) were enriched in the epithelial compartment, and myeloid lineage cells were located nearest to tumor cells. Except for CD68+CD163+ TAMs, other cells were all positively associated with favorable prognosis. The prognostic predictive power of TIICs was highly related to their distance to tumor cells. Unsupervised clustering analysis divided colorectal cancer into three subtypes with distinct prognostic outcomes, and correlation analysis revealed the synergy among B cells, CD68+IDO1+TAMs, and T lineage cells in producing an effective immune response. CONCLUSIONS Our study suggests that the integration of spatial localization with TIIC abundance is important for comprehensive prognostic assessment.
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Affiliation(s)
- Rongfang Shen
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China
| | - Ying Huang
- Department of Head and Neck Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Deyang Kong
- Department of Colorectal Surgery, State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China
| | - Wenhui Ma
- Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jie Liu
- Department of Head and Neck Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Haizeng Zhang
- Department of Colorectal Surgery, State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
| | - Shujun Cheng
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
| | - Lin Feng
- State Key Laboratory of Molecular Oncology, Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuannanli, Chaoyang District, Beijing, 100021, China.
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3
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Guo Y, Luo L, Zhu J, Li C. Advance in Multi-omics Research Strategies on Cholesterol Metabolism in Psoriasis. Inflammation 2024; 47:839-852. [PMID: 38244176 DOI: 10.1007/s10753-023-01961-9] [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: 09/24/2023] [Revised: 11/29/2023] [Accepted: 12/25/2023] [Indexed: 01/22/2024]
Abstract
The skin is a complex and dynamic organ where homeostasis is maintained through the intricate interplay between the immune system and metabolism, particularly cholesterol metabolism. Various factors such as cytokines, inflammatory mediators, cholesterol metabolites, and metabolic enzymes play crucial roles in facilitating these interactions. Dysregulation of this delicate balance contributes to the pathogenic pathways of inflammatory skin conditions, notably psoriasis. In this article, we provide an overview of omics biomarkers associated with psoriasis in relation to cholesterol metabolism. We explore multi-omics approaches that reveal the communication between immunometabolism and psoriatic inflammation. Additionally, we summarize the use of multi-omics strategies to uncover the complexities of multifactorial and heterogeneous inflammatory diseases. Finally, we highlight potential future perspectives related to targeted drug therapies and research areas that can advance precise medicine. This review aims to serve as a valuable resource for those investigating the role of cholesterol metabolism in psoriasis.
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Affiliation(s)
- Youming Guo
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China
- Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs, Nanjing, Jiangsu, China
| | - Lingling Luo
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China
| | - Jing Zhu
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China
| | - Chengrang Li
- Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, Jiangsu, China.
- Jiangsu Key Laboratory of Molecular Biology for Skin Diseases and STIs, Nanjing, Jiangsu, China.
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4
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Peters-Clarke TM, Coon JJ, Riley NM. Instrumentation at the Leading Edge of Proteomics. Anal Chem 2024; 96:7976-8010. [PMID: 38738990 DOI: 10.1021/acs.analchem.3c04497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Nicholas M Riley
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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5
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Desai N, Chavda V, Singh TRR, Thorat ND, Vora LK. Cancer Nanovaccines: Nanomaterials and Clinical Perspectives. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2401631. [PMID: 38693099 DOI: 10.1002/smll.202401631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/30/2024] [Indexed: 05/03/2024]
Abstract
Cancer nanovaccines represent a promising frontier in cancer immunotherapy, utilizing nanotechnology to augment traditional vaccine efficacy. This review comprehensively examines the current state-of-the-art in cancer nanovaccine development, elucidating innovative strategies and technologies employed in their design. It explores both preclinical and clinical advancements, emphasizing key studies demonstrating their potential to elicit robust anti-tumor immune responses. The study encompasses various facets, including integrating biomaterial-based nanocarriers for antigen delivery, adjuvant selection, and the impact of nanoscale properties on vaccine performance. Detailed insights into the complex interplay between the tumor microenvironment and nanovaccine responses are provided, highlighting challenges and opportunities in optimizing therapeutic outcomes. Additionally, the study presents a thorough analysis of ongoing clinical trials, presenting a snapshot of the current clinical landscape. By curating the latest scientific findings and clinical developments, this study aims to serve as a comprehensive resource for researchers and clinicians engaged in advancing cancer immunotherapy. Integrating nanotechnology into vaccine design holds immense promise for revolutionizing cancer treatment paradigms, and this review provides a timely update on the evolving landscape of cancer nanovaccines.
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Affiliation(s)
- Nimeet Desai
- Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Kandi, Telangana, 502285, India
| | - Vivek Chavda
- Department of Pharmaceutics and Pharmaceutical Technology, L M College of Pharmacy, Ahmedabad, 380009, India
| | | | - Nanasaheb D Thorat
- Limerick Digital Cancer Research Centre (LDCRC), University of Limerick, Castletroy, Limerick, V94T9PX, Ireland
- Department of Physics, Bernal Institute, Castletroy, Limerick, V94T9PX, Ireland
- Nuffield Department of Women's & Reproductive Health, Medical Science Division, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Lalitkumar K Vora
- School of Pharmacy, Queen's University Belfast, 97 Lisburn Road, Belfast, BT9 7BL, UK
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6
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Kidane FA, Müller L, Rocha-Hasler M, Tu A, Stanek V, Campion N, Bartosik T, Zghaebi M, Stoshikj S, Gompelmann D, Spittler A, Idzko M, Eckl-Dorna J, Schneider S. Deep immune profiling of chronic rhinosinusitis in allergic and non-allergic cohorts using mass cytometry. Clin Immunol 2024; 262:110174. [PMID: 38462155 DOI: 10.1016/j.clim.2024.110174] [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: 01/19/2024] [Revised: 02/19/2024] [Accepted: 02/20/2024] [Indexed: 03/12/2024]
Abstract
Chronic rhinosinusitis (CRS) is a persistent nasal and paranasal sinus mucosa inflammation comprising two phenotypes, namely CRS with nasal polyps (CRSwNP) and without (CRSsNP). CRSwNP can be associated with asthma and hypersensitivity to non-steroidal anti-inflammatory drug (NSAID) in a syndrome known as NSAID-exacerbated respiratory disease (N-ERD). Furthermore, CRS frequently intertwines with respiratory allergies. This study investigated levels of 33 different nasal and serum cytokines and phenotypic characteristics of peripheral blood mononuclear cells (PBMCs) within cohorts of CRS patients (n = 24), additionally examining the influence of comorbid respiratory allergies by mass cytometry. N-ERD patients showed heightened type 2 nasal cytokine levels. Mass cytometry revealed increased activated naive B cell levels in CRSwNP and N-ERD, while resting naive B cells were higher in CRSsNP. Th2a cell levels were significantly elevated in allergic subjects, but not in CRS groups. In conclusion, there are distinct immunological features in PBMCs of CRS phenotypes and allergy.
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Affiliation(s)
- Fana Alem Kidane
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Lena Müller
- Core Facilities, Medical University of Vienna, Vienna, Austria
| | | | - Aldine Tu
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Victoria Stanek
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Nicholas Campion
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Tina Bartosik
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Mohammed Zghaebi
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
| | - Slagjana Stoshikj
- Division of Pulmonology, Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria
| | - Daniela Gompelmann
- Division of Pulmonology, Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria
| | - Andreas Spittler
- Core Facilities, Medical University of Vienna, Vienna, Austria; Department of Surgery, Research Lab, Medical University of Vienna, Vienna, Austria
| | - Marco Idzko
- Division of Pulmonology, Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria
| | - Julia Eckl-Dorna
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria.
| | - Sven Schneider
- Department of Otorhinolaryngology, Medical University of Vienna, Vienna, Austria
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7
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Peng H, Moore C, Zhang Y, Saha D, Jiang S, Timmerman R. An AI-based approach for modeling the synergy between radiotherapy and immunotherapy. Sci Rep 2024; 14:8250. [PMID: 38589494 PMCID: PMC11001871 DOI: 10.1038/s41598-024-58684-6] [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: 08/04/2023] [Accepted: 04/02/2024] [Indexed: 04/10/2024] Open
Abstract
Personalized, ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) is designed to administer tumoricidal doses in a pulsed mode with extended intervals, spanning weeks or months. This approach leverages longer intervals to adapt the treatment plan based on tumor changes and enhance immune-modulated effects. In this investigation, we seek to elucidate the potential synergy between combined PULSAR and PD-L1 blockade immunotherapy using experimental data from a Lewis Lung Carcinoma (LLC) syngeneic murine cancer model. Employing a long short-term memory (LSTM) recurrent neural network (RNN) model, we simulated the treatment response by treating irradiation and anti-PD-L1 as external stimuli occurring in a temporal sequence. Our findings demonstrate that: (1) The model can simulate tumor growth by integrating various parameters such as timing and dose, and (2) The model provides mechanistic interpretations of a "causal relationship" in combined treatment, offering a completely novel perspective. The model can be utilized for in-silico modeling, facilitating exploration of innovative treatment combinations to optimize therapeutic outcomes. Advanced modeling techniques, coupled with additional efforts in biomarker identification, may deepen our understanding of the biological mechanisms underlying the combined treatment.
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Affiliation(s)
- Hao Peng
- Departments of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- Medical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Casey Moore
- Departments of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yuanyuan Zhang
- Departments of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Debabrata Saha
- Departments of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Steve Jiang
- Departments of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Medical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Robert Timmerman
- Departments of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA
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8
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Zhang W, Sen A, Pena JK, Reitsma A, Alexander OC, Tajima T, Martinez OM, Krams SM. Application of Mass Cytometry Platforms to Solid Organ Transplantation. Transplantation 2024:00007890-990000000-00687. [PMID: 38467594 DOI: 10.1097/tp.0000000000004925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Transplantation serves as the cornerstone of treatment for patients with end-stage organ disease. The prevalence of complications, such as allograft rejection, infection, and malignancies, underscores the need to dissect the complex interactions of the immune system at the single-cell level. In this review, we discuss studies using mass cytometry or cytometry by time-of-flight, a cutting-edge technology enabling the characterization of immune populations and cell-to-cell interactions in granular detail. We review the application of mass cytometry in human and experimental animal studies in the context of transplantation, uncovering invaluable contributions of the tool to understanding rejection and other transplant-related complications. We discuss recent innovations that have the potential to streamline and standardize mass cytometry workflows for application to multisite clinical trials. Additionally, we introduce imaging mass cytometry, a technique that couples the power of mass cytometry with spatial context, thereby mapping cellular interactions within tissue microenvironments. The synergistic integration of mass cytometry and imaging mass cytometry data with other omics data sets and high-dimensional data platforms to further define immune dynamics is discussed. In conclusion, mass cytometry technologies, when integrated with other tools and data, shed light on the intricate landscape of the immune response in transplantation. This approach holds significant potential for enhancing patient outcomes by advancing our understanding and facilitating the development of new diagnostics and therapeutics.
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Affiliation(s)
- Wenming Zhang
- Department of Surgery, Stanford University, Stanford, CA
| | - Ayantika Sen
- Department of Surgery, Stanford University, Stanford, CA
| | | | - Andrea Reitsma
- Department of Surgery, Stanford University, Stanford, CA
| | - Oliver C Alexander
- Department of Surgery, Stanford University, Stanford, CA
- Meharry Medical College, School of Medicine, Nashville, TN
| | - Tetsuya Tajima
- Department of Surgery, Stanford University, Stanford, CA
| | | | - Sheri M Krams
- Department of Surgery, Stanford University, Stanford, CA
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9
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Reichardt CM, Muñoz-Becerra M, Rius Rigau A, Rückert M, Fietkau R, Schett G, Gaipl US, Frey B, Muñoz LE. Neutrophils seeking new neighbors: radiotherapy affects the cellular framework and the spatial organization in a murine breast cancer model. Cancer Immunol Immunother 2024; 73:67. [PMID: 38430241 PMCID: PMC10908631 DOI: 10.1007/s00262-024-03653-1] [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: 11/02/2023] [Accepted: 02/06/2024] [Indexed: 03/03/2024]
Abstract
Neutrophils are known to contribute in many aspects of tumor progression and metastasis. The presence of neutrophils or neutrophil-derived mediators in the tumor microenvironment has been associated with poor prognosis in several types of solid tumors. However, the effects of classical cancer treatments such as radiation therapy on neutrophils are poorly understood. Furthermore, the cellular composition and distribution of immune cells in the tumor is of increasing interest in cancer research and new imaging technologies allow to perform more complex spatial analyses within tumor tissues. Therefore, we aim to offer novel insight into intra-tumoral formation of cellular neighborhoods and communities in murine breast cancer. To address this question, we performed image mass cytometry on tumors of the TS/A breast cancer tumor model, performed spatial neighborhood analyses of the tumor microenvironment and quantified neutrophil-extracellular trap degradation products in serum of the mice. We show that irradiation with 2 × 8 Gy significantly alters the cellular composition and spatial organization in the tumor, especially regarding neutrophils and other cells of the myeloid lineage. Locally applied radiotherapy further affects neutrophils in a systemic manner by decreasing the serum neutrophil extracellular trap concentrations which correlates positively with survival. In addition, the intercellular cohesion is maintained due to radiotherapy as shown by E-Cadherin expression. Radiotherapy, therefore, might affect the epithelial-mesenchymal plasticity in tumors and thus prevent metastasis. Our findings underscore the growing importance of the spatial organization of the tumor microenvironment, particularly with respect to radiotherapy, and provide insight into potential mechanisms by which radiotherapy affects epithelial-mesenchymal plasticity and tumor metastasis.
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Affiliation(s)
- C M Reichardt
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - M Muñoz-Becerra
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - A Rius Rigau
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - M Rückert
- Translational Radiobiology, Department of Radiation Oncology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - R Fietkau
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
- Department of Radiation Oncology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - G Schett
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
| | - U S Gaipl
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
- Translational Radiobiology, Department of Radiation Oncology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Department of Radiation Oncology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - B Frey
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
- Translational Radiobiology, Department of Radiation Oncology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Department of Radiation Oncology, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - L E Muñoz
- Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.
- Deutsches Zentrum Für Immuntherapie (DZI), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany.
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10
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Lin H, Buerki-Thurnherr T, Kaur J, Wick P, Pelin M, Tubaro A, Carniel FC, Tretiach M, Flahaut E, Iglesias D, Vázquez E, Cellot G, Ballerini L, Castagnola V, Benfenati F, Armirotti A, Sallustrau A, Taran F, Keck M, Bussy C, Vranic S, Kostarelos K, Connolly M, Navas JM, Mouchet F, Gauthier L, Baker J, Suarez-Merino B, Kanerva T, Prato M, Fadeel B, Bianco A. Environmental and Health Impacts of Graphene and Other Two-Dimensional Materials: A Graphene Flagship Perspective. ACS NANO 2024; 18:6038-6094. [PMID: 38350010 PMCID: PMC10906101 DOI: 10.1021/acsnano.3c09699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/15/2024]
Abstract
Two-dimensional (2D) materials have attracted tremendous interest ever since the isolation of atomically thin sheets of graphene in 2004 due to the specific and versatile properties of these materials. However, the increasing production and use of 2D materials necessitate a thorough evaluation of the potential impact on human health and the environment. Furthermore, harmonized test protocols are needed with which to assess the safety of 2D materials. The Graphene Flagship project (2013-2023), funded by the European Commission, addressed the identification of the possible hazard of graphene-based materials as well as emerging 2D materials including transition metal dichalcogenides, hexagonal boron nitride, and others. Additionally, so-called green chemistry approaches were explored to achieve the goal of a safe and sustainable production and use of this fascinating family of nanomaterials. The present review provides a compact survey of the findings and the lessons learned in the Graphene Flagship.
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Affiliation(s)
- Hazel Lin
- CNRS,
UPR3572, Immunology, Immunopathology and Therapeutic Chemistry, ISIS, University of Strasbourg, 67000 Strasbourg, France
| | - Tina Buerki-Thurnherr
- Empa,
Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Particles-Biology Interactions, 9014 St. Gallen, Switzerland
| | - Jasreen Kaur
- Nanosafety
& Nanomedicine Laboratory, Institute
of Environmental Medicine, Karolinska Institutet, 177 77 Stockholm, Sweden
| | - Peter Wick
- Empa,
Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Particles-Biology Interactions, 9014 St. Gallen, Switzerland
| | - Marco Pelin
- Department
of Life Sciences, University of Trieste, 34127 Trieste, Italy
| | - Aurelia Tubaro
- Department
of Life Sciences, University of Trieste, 34127 Trieste, Italy
| | | | - Mauro Tretiach
- Department
of Life Sciences, University of Trieste, 34127 Trieste, Italy
| | - Emmanuel Flahaut
- CIRIMAT,
Université de Toulouse, CNRS, INPT,
UPS, 31062 Toulouse CEDEX 9, France
| | - Daniel Iglesias
- Facultad
de Ciencias y Tecnologías Químicas, Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain
- Instituto
Regional de Investigación Científica Aplicada (IRICA), Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain
| | - Ester Vázquez
- Facultad
de Ciencias y Tecnologías Químicas, Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain
- Instituto
Regional de Investigación Científica Aplicada (IRICA), Universidad de Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain
| | - Giada Cellot
- International
School for Advanced Studies (SISSA), 34136 Trieste, Italy
| | - Laura Ballerini
- International
School for Advanced Studies (SISSA), 34136 Trieste, Italy
| | - Valentina Castagnola
- Center
for
Synaptic Neuroscience and Technology, Istituto
Italiano di Tecnologia, 16132 Genova, Italy
- IRCCS
Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Fabio Benfenati
- Center
for
Synaptic Neuroscience and Technology, Istituto
Italiano di Tecnologia, 16132 Genova, Italy
- IRCCS
Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Andrea Armirotti
- Analytical
Chemistry Facility, Istituto Italiano di
Tecnologia, 16163 Genoa, Italy
| | - Antoine Sallustrau
- Département
Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SIMoS, Gif-sur-Yvette 91191, France
| | - Frédéric Taran
- Département
Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SIMoS, Gif-sur-Yvette 91191, France
| | - Mathilde Keck
- Département
Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, SIMoS, Gif-sur-Yvette 91191, France
| | - Cyrill Bussy
- Nanomedicine
Lab, Faculty of Biology, Medicine and Health, University of Manchester,
Manchester Academic Health Science Centre, National Graphene Institute, Manchester M13 9PT, United
Kingdom
| | - Sandra Vranic
- Nanomedicine
Lab, Faculty of Biology, Medicine and Health, University of Manchester,
Manchester Academic Health Science Centre, National Graphene Institute, Manchester M13 9PT, United
Kingdom
| | - Kostas Kostarelos
- Nanomedicine
Lab, Faculty of Biology, Medicine and Health, University of Manchester,
Manchester Academic Health Science Centre, National Graphene Institute, Manchester M13 9PT, United
Kingdom
| | - Mona Connolly
- Instituto Nacional de Investigación y Tecnología
Agraria
y Alimentaria (INIA), CSIC, Carretera de la Coruña Km 7,5, E-28040 Madrid, Spain
| | - José Maria Navas
- Instituto Nacional de Investigación y Tecnología
Agraria
y Alimentaria (INIA), CSIC, Carretera de la Coruña Km 7,5, E-28040 Madrid, Spain
| | - Florence Mouchet
- Laboratoire
Ecologie Fonctionnelle et Environnement, Université de Toulouse, CNRS, INPT, UPS, 31000 Toulouse, France
| | - Laury Gauthier
- Laboratoire
Ecologie Fonctionnelle et Environnement, Université de Toulouse, CNRS, INPT, UPS, 31000 Toulouse, France
| | - James Baker
- TEMAS Solutions GmbH, 5212 Hausen, Switzerland
| | | | - Tomi Kanerva
- Finnish Institute of Occupational Health, 00250 Helsinki, Finland
| | - Maurizio Prato
- Center
for Cooperative Research in Biomaterials (CIC biomaGUNE), Basque Research and Technology Alliance (BRTA), 20014 Donostia-San
Sebastián, Spain
- Ikerbasque, Basque Foundation for Science, 48013 Bilbao, Spain
- Department
of Chemical and Pharmaceutical Sciences, University of Trieste, 34127 Trieste, Italy
| | - Bengt Fadeel
- Nanosafety
& Nanomedicine Laboratory, Institute
of Environmental Medicine, Karolinska Institutet, 177 77 Stockholm, Sweden
| | - Alberto Bianco
- CNRS,
UPR3572, Immunology, Immunopathology and Therapeutic Chemistry, ISIS, University of Strasbourg, 67000 Strasbourg, France
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11
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Chen Y, Chen X, Zhang B, Zhang Y, Li S, Liu Z, Gao Y, Zhao Y, Yan L, Li Y, Tian T, Lin Y. DNA framework signal amplification platform-based high-throughput systemic immune monitoring. Signal Transduct Target Ther 2024; 9:28. [PMID: 38320992 PMCID: PMC10847453 DOI: 10.1038/s41392-024-01736-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 11/14/2023] [Accepted: 01/01/2024] [Indexed: 02/08/2024] Open
Abstract
Systemic immune monitoring is a crucial clinical tool for disease early diagnosis, prognosis and treatment planning by quantitative analysis of immune cells. However, conventional immune monitoring using flow cytometry faces huge challenges in large-scale sample testing, especially in mass health screenings, because of time-consuming, technical-sensitive and high-cost features. However, the lack of high-performance detection platforms hinders the development of high-throughput immune monitoring technology. To address this bottleneck, we constructed a generally applicable DNA framework signal amplification platform (DSAP) based on post-systematic evolution of ligands by exponential enrichment and DNA tetrahedral framework-structured probe design to achieve high-sensitive detection for diverse immune cells, including CD4+, CD8+ T-lymphocytes, and monocytes (down to 1/100 μl). Based on this advanced detection platform, we present a novel high-throughput immune-cell phenotyping system, DSAP, achieving 30-min one-step immune-cell phenotyping without cell washing and subset analysis and showing comparable accuracy with flow cytometry while significantly reducing detection time and cost. As a proof-of-concept, DSAP demonstrates excellent diagnostic accuracy in immunodeficiency staging for 107 HIV patients (AUC > 0.97) within 30 min, which can be applied in HIV infection monitoring and screening. Therefore, we initially introduced promising DSAP to achieve high-throughput immune monitoring and open robust routes for point-of-care device development.
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Affiliation(s)
- Ye Chen
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Xingyu Chen
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Bowen Zhang
- Department of Prosthodontics, Tianjin Stomatological Hospital, School of Medicine, Nankai University, Tianjin, 300041, PR China
| | - Yuxin Zhang
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Songhang Li
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Zhiqiang Liu
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Yang Gao
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Yuxuan Zhao
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Lin Yan
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, PR China
| | - Yi Li
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, PR China.
| | - Taoran Tian
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China.
| | - Yunfeng Lin
- State Key Laboratory of Oral Diseases, National Center for Stomatology, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, PR China.
- Sichuan Provincial Engineering Research Center of Oral Biomaterials, Chengdu, 610041, Sichuan, China.
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12
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Qian Y, Yin Y, Zheng X, Liu Z, Wang X. Metabolic regulation of tumor-associated macrophage heterogeneity: insights into the tumor microenvironment and immunotherapeutic opportunities. Biomark Res 2024; 12:1. [PMID: 38185636 PMCID: PMC10773124 DOI: 10.1186/s40364-023-00549-7] [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: 10/01/2023] [Accepted: 12/12/2023] [Indexed: 01/09/2024] Open
Abstract
Tumor-associated macrophages (TAMs) are a heterogeneous population that play diverse functions in tumors. Their identity is determined not only by intrinsic factors, such as origins and transcription factors, but also by external signals from the tumor microenvironment (TME), such as inflammatory signals and metabolic reprogramming. Metabolic reprogramming has rendered TAM to exhibit a spectrum of activities ranging from pro-tumorigenic to anti-tumorigenic, closely associated with tumor progression and clinical prognosis. This review implicates the diversity of TAM phenotypes and functions, how this heterogeneity has been re-evaluated with the advent of single-cell technologies, and the impact of TME metabolic reprogramming on TAMs. We also review current therapies targeting TAM metabolism and offer new insights for TAM-dependent anti-tumor immunotherapy by focusing on the critical role of different metabolic programs in TAMs.
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Affiliation(s)
- Yujing Qian
- Department of Obstetrics and Gynecology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China
| | - Yujia Yin
- Department of Obstetrics and Gynecology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China
| | - Xiaocui Zheng
- Department of Obstetrics and Gynecology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China
| | - Zhaoyuan Liu
- Department of Immunology and Microbiology, Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Xipeng Wang
- Department of Obstetrics and Gynecology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
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13
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South SM, Marlin MC, Mehta-D'souza P, Stephens T, Conner T, Burt KG, Guthridge JM, Scanzello CR, Griffin TM. Imaging mass cytometry reveals tissue-specific cellular immune phenotypes in the mouse knee following ACL injury. OSTEOARTHRITIS AND CARTILAGE OPEN 2023; 5:100416. [PMID: 38107076 PMCID: PMC10724482 DOI: 10.1016/j.ocarto.2023.100416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023] Open
Abstract
Objective To develop an imaging mass cytometry method for identifying complex cell phenotypes, inter-cellular interactions, and population changes in the synovium and infrapatellar fat pad (IFP) of the mouse knee following a non-invasive compression injury. Design Fifteen male C57BL/6 mice were fed a high-fat diet for 8 weeks prior to random assignment to sham, 0.88 mm, or 1.7 mm knee compression displacement at 24 weeks of age. 2-weeks after loading, limbs were prepared for histologic and imaging mass cytometry analysis, focusing on myeloid immune cell populations in the synovium and IFP. Results 1.7 mm compression caused anterior cruciate ligament (ACL) rupture, development of post-traumatic osteoarthritis, and a 2- to 3-fold increase in cellularity of synovium and IFP tissues compared to sham or 0.88 mm compression. Imaging mass cytometry identified 11 myeloid cell subpopulations in synovium and 7 in IFP, of which approximately half were elevated 2 weeks after ACL injury in association with the vasculature. Notably, two monocyte/macrophage subpopulations and an MHC IIhi population were elevated 2-weeks post-injury in the synovium but not IFP. Vascular and immune cell interactions were particularly diverse in the synovium, incorporating 8 unique combinations of 5 myeloid cell populations, including a monocyte/macrophage population, an MHC IIhi population, and 3 different undefined F4/80+ myeloid populations. Conclusions Developing an imaging mass cytometry method for the mouse enabled us to identify a diverse array of synovial and IFP vascular-associated myeloid cell subpopulations. These subpopulations were differentially elevated in synovial and IFP tissues 2-weeks post injury, providing new details on tissue-specific immune regulation.
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Affiliation(s)
- Sanique M. South
- Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
- Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, Eugene, OR, 97403, USA
| | - M. Caleb Marlin
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
| | - Padmaja Mehta-D'souza
- Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
| | - Tayte Stephens
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
| | - Taylor Conner
- Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
| | - Kevin G. Burt
- Translational Musculoskeletal Research Center & Department of Medicine, Corporal Michael J. Crescenz Department of Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
- Division of Rheumatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Joel M. Guthridge
- Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
| | - Carla R. Scanzello
- Translational Musculoskeletal Research Center & Department of Medicine, Corporal Michael J. Crescenz Department of Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
- Division of Rheumatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Timothy M. Griffin
- Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, 73104, USA
- Oklahoma City VA Health Care System, Oklahoma City, OK, 73104, USA
- Oklahoma Center for Geroscience and the Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
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14
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Tang L, Huang ZP, Mei H, Hu Y. Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer. Mil Med Res 2023; 10:52. [PMID: 37941075 PMCID: PMC10631149 DOI: 10.1186/s40779-023-00486-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/10/2023] [Indexed: 11/10/2023] Open
Abstract
Advances in chimeric antigen receptor (CAR)-T cell therapy have significantly improved clinical outcomes of patients with relapsed or refractory hematologic malignancies. However, progress is still hindered as clinical benefit is only available for a fraction of patients. A lack of understanding of CAR-T cell behaviors in vivo at the single-cell level impedes their more extensive application in clinical practice. Mounting evidence suggests that single-cell sequencing techniques can help perfect the receptor design, guide gene-based T cell modification, and optimize the CAR-T manufacturing conditions, and all of them are essential for long-term immunosurveillance and more favorable clinical outcomes. The information generated by employing these methods also potentially informs our understanding of the numerous complex factors that dictate therapeutic efficacy and toxicities. In this review, we discuss the reasons why CAR-T immunotherapy fails in clinical practice and what this field has learned since the milestone of single-cell sequencing technologies. We further outline recent advances in the application of single-cell analyses in CAR-T immunotherapy. Specifically, we provide an overview of single-cell studies focusing on target antigens, CAR-transgene integration, and preclinical research and clinical applications, and then discuss how it will affect the future of CAR-T cell therapy.
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Affiliation(s)
- Lu Tang
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China
| | - Zhong-Pei Huang
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China
| | - Heng Mei
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China.
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China.
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Yu Hu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Medical Center of Cell Therapy for Neoplastic Disease, Wuhan, 430022, China.
- Key Laboratory of Biological Targeted Therapy, The Ministry of Education, Wuhan, 430022, China.
- Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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15
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Li Y, Wang B, Ahmad Khan Z, He J, Cheung E, Su W, Wang A, Jiang H, Jiang L, Ding X. Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry. Anal Chem 2023; 95:14998-15007. [PMID: 37767956 DOI: 10.1021/acs.analchem.3c02706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.
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Affiliation(s)
- Yiyang Li
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Boqian Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Zara Ahmad Khan
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Jie He
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Edwin Cheung
- Cancer Centre, University of Macau, Taipa 999078, Macau SAR
- Centre for Precision Medicine Research and Training, University of Macau, Taipa 999078, Macau SAR
- MoE Frontiers Science Center for Precision Oncology, University of Macau, Taipa 999078, Macau SAR
- Faculty of Health Sciences, University of Macau, Taipa 999078, Macau SAR
| | - Wenqiong Su
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Aiting Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Hui Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, China
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16
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Hegarty C, Neto N, Cahill P, Floudas A. Computational approaches in rheumatic diseases - Deciphering complex spatio-temporal cell interactions. Comput Struct Biotechnol J 2023; 21:4009-4020. [PMID: 37649712 PMCID: PMC10462794 DOI: 10.1016/j.csbj.2023.08.005] [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: 04/04/2023] [Revised: 08/04/2023] [Accepted: 08/04/2023] [Indexed: 09/01/2023] Open
Abstract
Inflammatory arthritis, including rheumatoid (RA), and psoriatic (PsA) arthritis, are clinically and immunologically heterogeneous diseases with no identified cure. Chronic inflammation of the synovial tissue ushers loss of function of the joint that severely impacts the patient's quality of life, eventually leading to disability and life-threatening comorbidities. The pathogenesis of synovial inflammation is the consequence of compounded immune and stromal cell interactions influenced by genetic and environmental factors. Deciphering the complexity of the synovial cellular landscape has accelerated primarily due to the utilisation of bulk and single cell RNA sequencing. Particularly the capacity to generate cell-cell interaction networks could reveal evidence of previously unappreciated processes leading to disease. However, there is currently a lack of universal nomenclature as a result of varied experimental and technological approaches that discombobulates the study of synovial inflammation. While spatial transcriptomic analysis that combines anatomical information with transcriptomic data of synovial tissue biopsies promises to provide more insights into disease pathogenesis, in vitro functional assays with single-cell resolution will be required to validate current bioinformatic applications. In order to provide a comprehensive approach and translate experimental data to clinical practice, a combination of clinical and molecular data with machine learning has the potential to enhance patient stratification and identify individuals at risk of arthritis that would benefit from early therapeutic intervention. This review aims to provide a comprehensive understanding of the effect of computational approaches in deciphering synovial inflammation pathogenesis and discuss the impact that further experimental and novel computational tools may have on therapeutic target identification and drug development.
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Affiliation(s)
- Ciara Hegarty
- Translational Immunology lab, School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Nuno Neto
- Trinity Centre for Biomedical Engineering, Trinity College Dublin, Ireland
| | - Paul Cahill
- Vascular Biology lab, School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Achilleas Floudas
- Translational Immunology lab, School of Biotechnology, Dublin City University, Dublin, Ireland
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17
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Lin Y, Cao Y, Willie E, Patrick E, Yang JYH. Atlas-scale single-cell multi-sample multi-condition data integration using scMerge2. Nat Commun 2023; 14:4272. [PMID: 37460600 DOI: 10.1038/s41467-023-39923-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 07/04/2023] [Indexed: 07/20/2023] Open
Abstract
The recent emergence of multi-sample multi-condition single-cell multi-cohort studies allows researchers to investigate different cell states. The effective integration of multiple large-cohort studies promises biological insights into cells under different conditions that individual studies cannot provide. Here, we present scMerge2, a scalable algorithm that allows data integration of atlas-scale multi-sample multi-condition single-cell studies. We have generalized scMerge2 to enable the merging of millions of cells from single-cell studies generated by various single-cell technologies. Using a large COVID-19 data collection with over five million cells from 1000+ individuals, we demonstrate that scMerge2 enables multi-sample multi-condition scRNA-seq data integration from multiple cohorts and reveals signatures derived from cell-type expression that are more accurate in discriminating disease progression. Further, we demonstrate that scMerge2 can remove dataset variability in CyTOF, imaging mass cytometry and CITE-seq experiments, demonstrating its applicability to a broad spectrum of single-cell profiling technologies.
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Affiliation(s)
- Yingxin Lin
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
| | - Yue Cao
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
| | - Elijah Willie
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
| | - Ellis Patrick
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China
- The Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Jean Y H Yang
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, NSW, Australia.
- Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.
- School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia.
- Laboratory of Data Discovery for Health Limited (D24H), Science Park, Hong Kong SAR, China.
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18
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Ji F, Hur M, Hur S, Wang S, Sarkar P, Shao S, Aispuro D, Cong X, Hu Y, Li Z, Xue M. Multiplex Protein Imaging through PACIFIC: Photoactive Immunofluorescence with Iterative Cleavage. ACS BIO & MED CHEM AU 2023; 3:283-294. [PMID: 37363079 PMCID: PMC10288499 DOI: 10.1021/acsbiomedchemau.3c00018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 06/28/2023]
Abstract
Multiplex protein imaging technologies enable deep phenotyping and provide rich spatial information about biological samples. Existing methods have shown great success but also harbored trade-offs between various pros and cons, underscoring the persisting necessity to expand the imaging toolkits. Here we present PACIFIC: photoactive immunofluorescence with iterative cleavage, a new modality of multiplex protein imaging methods. PACIFIC achieves iterative multiplexing by implementing photocleavable fluorophores for antibody labeling with one-step spin-column purification. PACIFIC requires no specialized instrument, no DNA encoding, or chemical treatments. We demonstrate that PACIFIC can resolve cellular heterogeneity in both formalin-fixed paraffin-embedded (FFPE) samples and fixed cells. To further highlight how PACIFIC assists discovery, we integrate PACIFIC with live-cell tracking and identify phosphor-p70S6K as a critical driver that governs U87 cell mobility. Considering the cost, flexibility, and compatibility, we foresee that PACIFIC can confer deep phenotyping capabilities to anyone with access to traditional immunofluorescence platforms.
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Affiliation(s)
- Fei Ji
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
| | - Moises Hur
- Martin
Luther King Jr High School, Riverside, California 92508, United States
| | - Sungwon Hur
- Martin
Luther King Jr High School, Riverside, California 92508, United States
| | - Siwen Wang
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
- Environmental
Toxicology Graduate Program, University
of California, Riverside, Riverside, California 92521, United States
| | - Priyanka Sarkar
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
| | - Shiqun Shao
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
- College
of Chemical and Biological Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, P.R. China
| | - Desiree Aispuro
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
- Environmental
Toxicology Graduate Program, University
of California, Riverside, Riverside, California 92521, United States
| | - Xu Cong
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
| | - Yanhao Hu
- Diamond
Bar High School, Diamond
Bar, California 91765, United States
| | - Zhonghan Li
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
| | - Min Xue
- Department
of Chemistry, University of California,
Riverside, Riverside, California 92521, United States
- Environmental
Toxicology Graduate Program, University
of California, Riverside, Riverside, California 92521, United States
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19
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Sawyer AJ, Patrick E, Edwards J, Wilmott JS, Fielder T, Yang Q, Barber DL, Ernst JD, Britton WJ, Palendira U, Chen X, Feng CG. Spatial mapping reveals granuloma diversity and histopathological superstructure in human tuberculosis. J Exp Med 2023; 220:e20221392. [PMID: 36920308 PMCID: PMC10035589 DOI: 10.1084/jem.20221392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/07/2023] [Accepted: 02/28/2023] [Indexed: 03/16/2023] Open
Abstract
The hallmark of tuberculosis (TB) is the formation of immune cell-enriched aggregates called granulomas. While granulomas are pathologically diverse, their tissue-wide heterogeneity has not been spatially resolved at the single-cell level in human tissues. By spatially mapping individual immune cells in every lesion across entire tissue sections, we report that in addition to necrotizing granulomas, the human TB lung contains abundant non-necrotizing leukocyte aggregates surrounding areas of necrotizing tissue. These cellular lesions were more diverse in composition than necrotizing lesions and could be stratified into four general classes based on cellular composition and spatial distribution of B cells and macrophages. The cellular composition of non-necrotizing structures also correlates with their proximity to necrotizing lesions, indicating these are foci of distinct immune reactions adjacent to necrotizing granulomas. Together, we show that during TB, diseased lung tissue develops a histopathological superstructure comprising at least four different types of non-necrotizing cellular aggregates organized as satellites of necrotizing granulomas.
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Affiliation(s)
- Andrew J. Sawyer
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Centenary Institute, The University of Sydney, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, Australia
| | - Ellis Patrick
- School of Mathematics and Statistics, Faculty of Science, The University of Sydney, Sydney, Australia
- Centre for Cancer Research, Westmead Institute for Medical Research, The University of Sydney, Westmead, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Sydney, Australia
| | - Jarem Edwards
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - James S. Wilmott
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, Australia
- Melanoma Institute Australia, The University of Sydney, Sydney, Australia
| | - Timothy Fielder
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, Australia
| | - Qianting Yang
- Guangdong Key Lab for Diagnosis and Treatment of Emerging Infectious Diseases, Shenzhen, Third People’s Hospital, Shenzhen, Shenzhen, China
| | - Daniel L. Barber
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Joel D. Ernst
- Division of Experimental Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Warwick J. Britton
- Centenary Institute, The University of Sydney, Sydney, Australia
- Department of Clinical Immunology, Royal Prince Alfred Hospital, Camperdown, Australia
| | - Umaimainthan Palendira
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Centenary Institute, The University of Sydney, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, Australia
| | - Xinchun Chen
- Guangdong Key Laboratory of Regional Immunity and Diseases, Department of Pathogen Biology, Shenzhen UniversitySchool of Medicine, Shenzhen, China
| | - Carl G. Feng
- School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
- Centenary Institute, The University of Sydney, Sydney, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, Australia
- Institute for Infectious Diseases, The University of Sydney, Sydney, Australia
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20
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Wang X, Ren L, Diao Z, He Y, Zhang J, Liu M, Li Y, Sun L, Chen R, Ji Y, Xu J, Ma B. Robust Spontaneous Raman Flow Cytometry for Single-Cell Metabolic Phenome Profiling via pDEP-DLD-RFC. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2207497. [PMID: 36871147 DOI: 10.1002/advs.202207497] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 02/08/2023] [Indexed: 06/04/2023]
Abstract
A full-spectrum spontaneous single-cell Raman spectrum (fs-SCRS) captures the metabolic phenome for a given cellular state of the cell in a label-free, landscape-like manner. Herein a positive dielectrophoresis induced deterministic lateral displacement-based Raman flow cytometry (pDEP-DLD-RFC) is established. This robust flow cytometry platform utilizes a periodical positive dielectrophoresis induced deterministic lateral displacement (pDEP-DLD) force that is exerted to focus and trap fast-moving single cells in a wide channel, which enables efficient fs-SCRS acquisition and extended stable running time. It automatically produces deeply sampled, heterogeneity-resolved, and highly reproducible ramanomes for isogenic cell populations of yeast, microalgae, bacteria, and human cancers, which support biosynthetic process dissection, antimicrobial susceptibility profiling, and cell-type classification. Moreover, when coupled with intra-ramanome correlation analysis, it reveals state- and cell-type-specific metabolic heterogeneity and metabolite-conversion networks. The throughput of ≈30-2700 events min-1 for profiling both nonresonance and resonance marker bands in a fs-SCRS, plus the >5 h stable running time, represent the highest performance among reported spontaneous Raman flow cytometry (RFC) systems. Therefore, pDEP-DLD-RFC is a valuable new tool for label-free, noninvasive, and high-throughput profiling of single-cell metabolic phenomes.
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Affiliation(s)
- Xixian Wang
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lihui Ren
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
- College of Information Science & Engineering, Ocean University of China, Qingdao, 266100, China
| | - Zhidian Diao
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuehui He
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jiaping Zhang
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Min Liu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuandong Li
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lijun Sun
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Rongze Chen
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuetong Ji
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
- Qingdao Single-Cell Biotech. Co., Ltd, Qingdao, 266100, China
| | - Jian Xu
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo Ma
- Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Key Laboratory of Energy Genetics, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, China
- Shandong Energy Institute, Qingdao, 266101, China
- Qingdao New Energy Shandong Laboratory, Qingdao, 266101, China
- College of Life Science, University of Chinese Academy of Sciences, Beijing, 100049, China
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21
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Zhang Y, Sun H, Lian X, Tang J, Zhu F. ANPELA: Significantly Enhanced Quantification Tool for Cytometry-Based Single-Cell Proteomics. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2207061. [PMID: 36950745 DOI: 10.1002/advs.202207061] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/13/2023] [Indexed: 05/27/2023]
Abstract
ANPELA is widely used for quantifying traditional bulk proteomic data. Recently, there is a clear shift from bulk proteomics to the single-cell ones (SCP), for which powerful cytometry techniques demonstrate the fantastic capacity of capturing cellular heterogeneity that is completely overlooked by traditional bulk profiling. However, the in-depth and high-quality quantification of SCP data is still challenging and severely affected by the large numbers of quantification workflows and extreme performance dependence on the studied datasets. In other words, the proper selection of well-performing workflow(s) for any studied dataset is elusory, and it is urgently needed to have a significantly enhanced and accelerated tool to address this issue. However, no such tool is developed yet. Herein, ANPELA is therefore updated to its 2.0 version (https://idrblab.org/anpela/), which is unique in providing the most comprehensive set of quantification alternatives (>1000 workflows) among all existing tools, enabling systematic performance evaluation from multiple perspectives based on machine learning, and identifying the optimal workflow(s) using overall performance ranking together with the parallel computation. Extensive validation on different benchmark datasets and representative application scenarios suggest the great application potential of ANPELA in current SCP research for gaining more accurate and reliable biological insights.
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Affiliation(s)
- Ying Zhang
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Huaicheng Sun
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xichen Lian
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Jing Tang
- Department of Bioinformatics, Chongqing Medical University, Chongqing, 400016, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310058, China
- Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Hangzhou, 330110, China
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22
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Mogilenko DA, Sergushichev A, Artyomov MN. Systems Immunology Approaches to Metabolism. Annu Rev Immunol 2023; 41:317-342. [PMID: 37126419 DOI: 10.1146/annurev-immunol-101220-031513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Over the last decade, immunometabolism has emerged as a novel interdisciplinary field of research and yielded significant fundamental insights into the regulation of immune responses. Multiple classical approaches to interrogate immunometabolism, including bulk metabolic profiling and analysis of metabolic regulator expression, paved the way to appreciating the physiological complexity of immunometabolic regulation in vivo. Studying immunometabolism at the systems level raised the need to transition towards the next-generation technology for metabolic profiling and analysis. Spatially resolved metabolic imaging and computational algorithms for multi-modal data integration are new approaches to connecting metabolism and immunity. In this review, we discuss recent studies that highlight the complex physiological interplay between immune responses and metabolism and give an overview of technological developments that bear the promise of capturing this complexity most directly and comprehensively.
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Affiliation(s)
- Denis A Mogilenko
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA; ,
- Current affiliation: Department of Medicine, Department of Pathology, Microbiology, and Immunology, and Vanderbilt Center for Immunobiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA;
| | - Alexey Sergushichev
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA; ,
- Computer Technologies Laboratory, ITMO University, Saint Petersburg, Russia
| | - Maxim N Artyomov
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA; ,
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23
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Aleynick N, Li Y, Xie Y, Zhang M, Posner A, Roshal L, Pe'er D, Vanguri RS, Hollmann TJ. Cross-platform dataset of multiplex fluorescent cellular object image annotations. Sci Data 2023; 10:193. [PMID: 37029126 PMCID: PMC10082189 DOI: 10.1038/s41597-023-02108-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 03/27/2023] [Indexed: 04/09/2023] Open
Abstract
Defining cellular and subcellular structures in images, referred to as cell segmentation, is an outstanding obstacle to scalable single-cell analysis of multiplex imaging data. While advances in machine learning-based segmentation have led to potentially robust solutions, such algorithms typically rely on large amounts of example annotations, known as training data. Datasets consisting of annotations which are thoroughly assessed for quality are rarely released to the public. As a result, there is a lack of widely available, annotated data suitable for benchmarking and algorithm development. To address this unmet need, we release 105,774 primarily oncological cellular annotations concentrating on tumor and immune cells using over 40 antibody markers spanning three fluorescent imaging platforms, over a dozen tissue types and across various cellular morphologies. We use readily available annotation techniques to provide a modifiable community data set with the goal of advancing cellular segmentation for the greater imaging community.
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Affiliation(s)
- Nathaniel Aleynick
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yanyun Li
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yubin Xie
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Mianlei Zhang
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Posner
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Lev Roshal
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dana Pe'er
- Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Howard Hughes Medical Institute, New York, NY, USA
| | - Rami S Vanguri
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Travis J Hollmann
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Bristol Meyers Squibb, Princeton, NJ, USA.
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24
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Fu J, Zhu F, Xu CJ, Li Y. Metabolomics meets systems immunology. EMBO Rep 2023; 24:e55747. [PMID: 36916532 PMCID: PMC10074123 DOI: 10.15252/embr.202255747] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/24/2022] [Accepted: 02/24/2023] [Indexed: 03/16/2023] Open
Abstract
Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.
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Affiliation(s)
- Jianbo Fu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
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25
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Laigle L, Chadli L, Moingeon P. Biomarker-driven development of new therapies for autoimmune diseases: current status and future promises. Expert Rev Clin Immunol 2023; 19:305-314. [PMID: 36680799 DOI: 10.1080/1744666x.2023.2172404] [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] [Indexed: 01/22/2023]
Abstract
INTRODUCTION Auto-immune diseases are complex and heterogeneous. Various types of biomarkers can be used to support precision medicine approaches to autoimmune diseases, ensuring that the right patient receives the most appropriate therapy to improve treatment outcomes. AREAS COVERED We review the recent progress made in modeling several autoimmune diseases such as Systemic Lupus Erythematosus, primary Sjogren Syndrome, and Rheumatoid Arthritis following extensive molecular profiling of large cohorts of patients. From this knowledge, BMKs are being identified which support diagnostic as well as patient stratification and prediction of response to treatment. The identification of biomarkers should be initiated early in drug development and properly validated during subsequent clinical trials. To ensure the robustness and reproducibility of biomarkers, the PERMIT Consortium recently established recommendations highlighting the importance of relevant study design, sample size, and appropriate validation of analytical methods. EXPERT OPINION The integration by AI-powered analytics of massive data provided by multi-omics technologies, high-resolution medical imaging and sensors borne by patients will eventually allow the identification of clinically relevant BMKs, likely in the form of combinatorial predictive algorithms, to support future drug development for autoimmune diseases.
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Affiliation(s)
| | - Loubna Chadli
- Servier Médical, Research and Development, Suresnes, France
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26
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Rong D, Wang Y, Liu L, Cao H, Huang T, Liu H, Hao X, Sun G, Sun G, Zheng Z, Kang J, Xia Y, Chen Z, Tang W, Wang X. GLIS1 intervention enhances anti-PD1 therapy for hepatocellular carcinoma by targeting SGK1-STAT3-PD1 pathway. J Immunother Cancer 2023; 11:jitc-2022-005126. [PMID: 36787938 PMCID: PMC9930610 DOI: 10.1136/jitc-2022-005126] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2023] [Indexed: 02/16/2023] Open
Abstract
BACKGROUND GLI-similar 1 (GLIS1) is one of of Krüppel-like zinc finger proteins, which are either stimulators or inhibitors of genetic transcription. Nevertheless, its effects on T cell were elusive. METHODS In this study, we intend to explore the effects of GLIS1 on modulating the anticancer potency of CD8+ T cells in hepatocellular carcinoma (HCC). The expression of GLIS1 in CD8 peripheral blood mononuclear cell and CD8 tumor-infiltrating lymphocytes of HCC tissues was validated by quantificational real-time-PCR and flow cytometry. The anticancer potency of CD8+ T cells with GLIS1 knock down was confirmed in C57BL/6 mouse model and HCC patient-derived xenograft mice model. GLIS1-/- C57BL/6 mice was applied to explore the effects GLIS1 on tumor immune microenvironment. Chromatin immunoprecipitation and RNA transcriptome sequencing analysis were both performed in GLIS1-knock down of CD8+ T cells. RESULTS GLIS1 was upregulated in exhausted CD8+ T cells in HCC. GLIS1 downregulation in CD8+ T cells repressed cancer development, elevated the infiltrate ability of CD8+ T cells, mitigated CD8+ T cell exhaustion and ameliorated the anti-PD1 reaction of CD8+ T cells in HCC. The causal link beneath this included transcriptional regulation of SGK1-STAT3-PD1 pathway by GLIS1, thereby maintaining the abundant PD1 expression on the surface of CD8+ T cells. CONCLUSION Our study revealed that GLIS1 promoted CD8+ T cell exhaustion in HCC through transcriptional regulating SGK1-STAT3-PD1 pathway. Downregulating the expression of GLIS1 in CD8+ T cells exerted an effect with anti-PD1 treatment synergistically, revealing a prospective method for HCC immune therapy.
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Affiliation(s)
- Dawei Rong
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Yuliang Wang
- School of Basic Medicine, Nanjing Medical University, Nanjing, China
| | - Li Liu
- Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hengsong Cao
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Tian Huang
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Hanyuan Liu
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Xiaopei Hao
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Guangshun Sun
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Guoqiang Sun
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Zhiying Zheng
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Junwei Kang
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Yongxiang Xia
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Ziyi Chen
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Weiwei Tang
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
| | - Xuehao Wang
- Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Liver Transplantation, Chinese Academy of Medical Sciences, NHC Key Laboratory of Living Donor Liver Transplantation, Nanjing, China
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27
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Arnett LP, Rana R, Chung WWY, Li X, Abtahi M, Majonis D, Bassan J, Nitz M, Winnik MA. Reagents for Mass Cytometry. Chem Rev 2023; 123:1166-1205. [PMID: 36696538 DOI: 10.1021/acs.chemrev.2c00350] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Mass cytometry (cytometry by time-of-flight detection [CyTOF]) is a bioanalytical technique that enables the identification and quantification of diverse features of cellular systems with single-cell resolution. In suspension mass cytometry, cells are stained with stable heavy-atom isotope-tagged reagents, and then the cells are nebulized into an inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) instrument. In imaging mass cytometry, a pulsed laser is used to ablate ca. 1 μm2 spots of a tissue section. The plume is then transferred to the CyTOF, generating an image of biomarker expression. Similar measurements are possible with multiplexed ion bean imaging (MIBI). The unit mass resolution of the ICP-TOF-MS detector allows for multiparametric analysis of (in principle) up to 130 different parameters. Currently available reagents, however, allow simultaneous measurement of up to 50 biomarkers. As new reagents are developed, the scope of information that can be obtained by mass cytometry continues to increase, particularly due to the development of new small molecule reagents which enable monitoring of active biochemistry at the cellular level. This review summarizes the history and current state of mass cytometry reagent development and elaborates on areas where there is a need for new reagents. Additionally, this review provides guidelines on how new reagents should be tested and how the data should be presented to make them most meaningful to the mass cytometry user community.
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Affiliation(s)
- Loryn P Arnett
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Rahul Rana
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Wilson Wai-Yip Chung
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Xiaochong Li
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Mahtab Abtahi
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Daniel Majonis
- Standard BioTools Canada Inc. (formerly Fluidigm Canada Inc.), 1380 Rodick Road, Suite 400, Markham, OntarioL3R 4G5, Canada
| | - Jay Bassan
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Mark Nitz
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada
| | - Mitchell A Winnik
- Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, OntarioM5S 3H6, Canada.,Department of Chemical Engineering and Applied Chemistry, 200 College Street, Toronto, OntarioM5S 3E5, Canada
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28
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Nishiyama R, Hiramatsu K, Kawamura S, Dodo K, Furuya K, de Pablo JG, Takizawa S, Min W, Sodeoka M, Goda K. Color-scalable flow cytometry with Raman tags. PNAS NEXUS 2023; 2:pgad001. [PMID: 36845353 PMCID: PMC9950787 DOI: 10.1093/pnasnexus/pgad001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 01/13/2023] [Indexed: 01/15/2023]
Abstract
Flow cytometry is an indispensable tool in biology and medicine for counting and analyzing cells in large heterogeneous populations. It identifies multiple characteristics of every single cell, typically via fluorescent probes that specifically bind to target molecules on the cell surface or within the cell. However, flow cytometry has a critical limitation: the color barrier. The number of chemical traits that can be simultaneously resolved is typically limited to several due to the spectral overlap between fluorescence signals from different fluorescent probes. Here, we present color-scalable flow cytometry based on coherent Raman flow cytometry with Raman tags to break the color barrier. This is made possible by combining a broadband Fourier-transform coherent anti-Stokes Raman scattering (FT-CARS) flow cytometer, resonance-enhanced cyanine-based Raman tags, and Raman-active dots (Rdots). Specifically, we synthesized 20 cyanine-based Raman tags whose Raman spectra are linearly independent in the fingerprint region (400 to 1,600 cm-1). For highly sensitive detection, we produced Rdots composed of 12 different Raman tags in polymer nanoparticles whose detection limit was as low as 12 nM for a short FT-CARS signal integration time of 420 µs. We performed multiplex flow cytometry of MCF-7 breast cancer cells stained by 12 different Rdots with a high classification accuracy of 98%. Moreover, we demonstrated a large-scale time-course analysis of endocytosis via the multiplex Raman flow cytometer. Our method can theoretically achieve flow cytometry of live cells with >140 colors based on a single excitation laser and a single detector without increasing instrument size, cost, or complexity.
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Affiliation(s)
- Ryo Nishiyama
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan
| | | | - Shintaro Kawamura
- Synthetic Organic Chemistry Laboratory, RIKEN Cluster for Pioneering Research, Saitama 351-0198, Japan,RIKEN Center for Sustainable Resource Science, Saitama 351-0198, Japan
| | - Kosuke Dodo
- Synthetic Organic Chemistry Laboratory, RIKEN Cluster for Pioneering Research, Saitama 351-0198, Japan,RIKEN Center for Sustainable Resource Science, Saitama 351-0198, Japan
| | - Kei Furuya
- Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan
| | | | | | - Wei Min
- Department of Chemistry, Columbia University, New York , NY 10027, USA
| | - Mikiko Sodeoka
- Synthetic Organic Chemistry Laboratory, RIKEN Cluster for Pioneering Research, Saitama 351-0198, Japan,RIKEN Center for Sustainable Resource Science, Saitama 351-0198, Japan
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29
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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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30
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Robert M, Chépeaux LA, Glasson Y, Dumé AS, Sannier A, Papo T, Bonnefoy N, Michaud HA, Sacré K. Comprehensive analysis of cell lineages involved in giant cell arteritis pathogenesis using highly multiplexed imaging mass cytometry. Clin Exp Rheumatol 2023; 22:103216. [PMID: 36280094 DOI: 10.1016/j.autrev.2022.103216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 12/27/2022]
Affiliation(s)
- Marie Robert
- Service de Médecine Interne, Hôpital Bichat, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France
| | - Laure-Agnès Chépeaux
- Plateforme de Cytométrie et d'Imagerie de Masse de Montpellier, IRCM, INSERM, Univ Montpellier, ICM, Montpellier, France
| | - Yael Glasson
- Plateforme de Cytométrie et d'Imagerie de Masse de Montpellier, IRCM, INSERM, Univ Montpellier, ICM, Montpellier, France
| | - Anne-Sophie Dumé
- Plateforme de Cytométrie et d'Imagerie de Masse de Montpellier, IRCM, INSERM, Univ Montpellier, ICM, Montpellier, France
| | - Aurélie Sannier
- Service d'Anatomopathologie, Hôpital Bichat, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France
| | - Thomas Papo
- Service de Médecine Interne, Hôpital Bichat, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France
| | - Nathalie Bonnefoy
- Plateforme de Cytométrie et d'Imagerie de Masse de Montpellier, IRCM, INSERM, Univ Montpellier, ICM, Montpellier, France
| | - Henri-Alexandre Michaud
- Plateforme de Cytométrie et d'Imagerie de Masse de Montpellier, IRCM, INSERM, Univ Montpellier, ICM, Montpellier, France.
| | - Karim Sacré
- Service de Médecine Interne, Hôpital Bichat, Assistance Publique - Hôpitaux de Paris (AP-HP), Paris, France; Plateforme de Cytométrie et d'Imagerie de Masse de Montpellier, IRCM, INSERM, Univ Montpellier, ICM, Montpellier, France; Université Paris Cité, Centre de Recherche sur l'Inflammation, INSERM UMR1149, CNRS ERL8252, Faculté de Médecine site Bichat, Laboratoire d'Excellence Inflamex, Paris, France.
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31
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Monitoring of the Forgotten Immune System during Critical Illness-A Narrative Review. Medicina (B Aires) 2022; 59:medicina59010061. [PMID: 36676685 PMCID: PMC9866378 DOI: 10.3390/medicina59010061] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Revised: 12/24/2022] [Accepted: 12/25/2022] [Indexed: 12/29/2022] Open
Abstract
Immune organ failure is frequent in critical illness independent of its cause and has been acknowledged for a long time. Most patients admitted to the ICU, whether featuring infection, trauma, or other tissue injury, have high levels of alarmins expression in tissues or systemically which then activate innate and adaptive responses. Although necessary, this response is frequently maladaptive and leads to organ dysfunction. In addition, the counter-response aiming to restore homeostasis and repair injury can also be detrimental and contribute to persistent chronic illness. Despite intensive research on this topic in the last 40 years, the immune system is not routinely monitored in critical care units. In this narrative review we will first discuss the inflammatory response after acute illness and the players of maladaptive response, focusing on neutrophils, monocytes, and T cells. We will then go through commonly used biomarkers, like C-reactive protein, procalcitonin and pancreatic stone protein (PSP) and what they monitor. Next, we will discuss the strengths and limitations of flow cytometry and related techniques as an essential tool for more in-depth immune monitoring and end with a presentation of the most promising cell associated markers, namely HLA-DR expression on monocytes, neutrophil expression of CD64 and PD-1 expression on T cells. In sum, immune monitoring critically ill patients is a forgotten and missing piece in the monitoring capacity of intensive care units. New technology, including bed-side equipment and in deep cell phenotyping using emerging multiplexing techniques will likely allow the definition of endotypes and a more personalized care in the future.
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32
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Aglas‐Leitner F, Juillard P, Juillard A, Byrne SN, Hawke S, Grau GE, Marsh‐Wakefield F. Circulating CCR6 +ILC proportions are lower in multiple sclerosis patients. Clin Transl Immunology 2022; 11:e1426. [PMID: 36578284 PMCID: PMC9782758 DOI: 10.1002/cti2.1426] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 09/17/2022] [Accepted: 10/15/2022] [Indexed: 12/24/2022] Open
Abstract
Objectives The role of innate lymphoid cells (ILC), particularly helper ILC, in the pathogenesis of multiple sclerosis (MS) is not well understood. Here, we present a comprehensive analysis of peripheral ILC subsets in MS patients prior and after alemtuzumab administration using mass cytometry. Methods Circulating ILC were analysed by mass cytometry in MS patients before and after alemtuzumab. These were compared with non-MS controls. MS-related shifts among ILC immunophenotypes were further elucidated by fast interpolation-based t-SNE (Flt-SNE) dimensionality reduction. Results Neither natural killer (NK) cells nor helper ILC (ILC1, ILC2 and ILC3) levels were altered following alemtuzumab treatment. However, CD56bright NK cell expansions were observed in relapsing patients. MS patients prior to alemtuzumab further displayed proportional shifts from ILC1 to ILC2, with MS-associated decreases in CCR6+ helper ILC proportions. Conclusion CD56bright NK cells during relapse indicate an immediate response to disease reactivation, while CCR6-related shifts among helper ILC suggest altered ILC migration to the CNS during MS.
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Affiliation(s)
- Florentina Aglas‐Leitner
- Vascular Immunology Unit, School of Medical Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia,Medical University of ViennaViennaAustria
| | - Pierre Juillard
- Vascular Immunology Unit, School of Medical Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
| | - Anette Juillard
- Vascular Immunology Unit, School of Medical Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
| | - Scott N Byrne
- Centre for Immunology and Allergy ResearchThe Westmead Institute for Medical ResearchSydneyNSWAustralia,Faculty of Medicine and Health, School of Medical SciencesThe University of SydneySydneyNSWAustralia
| | - Simon Hawke
- Vascular Immunology Unit, School of Medical Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia,Central West Neurology and NeurosurgeryOrangeNSWAustralia
| | - Georges E Grau
- Vascular Immunology Unit, School of Medical Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
| | - Felix Marsh‐Wakefield
- Vascular Immunology Unit, School of Medical Sciences, Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia,Liver Injury & Cancer ProgramCentenary InstituteSydneyNSWAustralia,Human Cancer & Viral Immunology LaboratoryThe University of SydneySydneyNSWAustralia
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33
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Tao Y, Li X, Zhang Y, He L, Lu Q, Wang Y, Pan L, Wang Z, Feng C, Xie Y, Lai Z, Li T, Tang Z, Wang Q, Wang X. TP53-related signature for predicting prognosis and tumor microenvironment characteristics in bladder cancer: A multi-omics study. Front Genet 2022; 13:1057302. [PMID: 36568387 PMCID: PMC9780475 DOI: 10.3389/fgene.2022.1057302] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 11/21/2022] [Indexed: 12/13/2022] Open
Abstract
Background: The tumor suppressor gene TP53 is frequently mutated or inactivated in bladder cancer (BLCA), which is implicated in the pathogenesis of tumor. However, the cellular mechanisms of TP53 mutations are complicated, yet well-defined, but their clinical prognostic value in the management of BLCA remains controversial. This study aimed to explore the role of TP53 mutation in regulating the tumor microenvironment (TME), elucidate the effects of TP53 activity on BLCA prognosis and immunotherapy response. Methods: A TP53-related signature based on TP53-induced and TP53-repressed genes was used to construct a TP53 activity-related score and classifier. The abundance of different immune cell types was determined using CIBERSORT to estimate immune cell infiltration. Moreover, the heterogeneity of the tumor immune microenvironment between the high and low TP53 score groups was further evaluated using single-cell mass cytometry (CyTOF) and imaging mass cytometry (IMC). Moreover, pathway enrichment analysis was performed to explore the differential biological functions between tumor epithelial cells with high and low TP53 activity scores. Finally, the receptor-ligand interactions between immune cells and tumor epithelial cells harboring distinct TP53 activity were analyzed by single-cell RNA-sequencing. Results: The TP53 activity-related gene signature differentiated well between TP53 functional retention and inactivation in BLCA. BLCA patients with low TP53 scores had worse survival prognosis, more TP53 mutations, higher grade, and stronger lymph node metastasis than those with high TP53 scores. Additionally, CyTOF and IMC analyses revealed that BLCA patients with low TP53 scores exhibited a potent immunosuppressive TME. Consistently, single-cell sequencing results showed that tumor epithelial cells with low TP53 scores were significantly associated with high cell proliferation and stemness abilities and strongly interacted with immunosuppressive receptor-ligand pairs. Conclusion: BLCA patients with low TP53 scores have a worse prognosis and a more immunosuppressive TME. This TP53 activity-related signature can serve as a potential prognostic signature for predicting the immune response, which may facilitate the development of new strategies for immunotherapy in BLCA.
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Affiliation(s)
- Yuting Tao
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China,Key Laboratory of Biological Molecular Medicine Research, Education Department of Guangxi Zhuang Autonomous Region, Guangxi Medical University, Nanning, China,Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Xia Li
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China,Key Laboratory of Biological Molecular Medicine Research, Education Department of Guangxi Zhuang Autonomous Region, Guangxi Medical University, Nanning, China,Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Yushan Zhang
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China,Key Laboratory of Biological Molecular Medicine Research, Education Department of Guangxi Zhuang Autonomous Region, Guangxi Medical University, Nanning, China,Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Liangyu He
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China,Departments of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Qinchen Lu
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China,Key Laboratory of Biological Molecular Medicine Research, Education Department of Guangxi Zhuang Autonomous Region, Guangxi Medical University, Nanning, China,Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Yaobang Wang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Lixin Pan
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China,Key Laboratory of Biological Molecular Medicine Research, Education Department of Guangxi Zhuang Autonomous Region, Guangxi Medical University, Nanning, China,Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Zhenxing Wang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Chao Feng
- Department of Biochemistry and Molecular Biology, School of Basic Medicine, Guangxi Medical University, Nanning, China,Key Laboratory of Biological Molecular Medicine Research, Education Department of Guangxi Zhuang Autonomous Region, Guangxi Medical University, Nanning, China,Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Yuanliang Xie
- Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China,Departments of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China,Department of Urology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China
| | - Zhiyong Lai
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
| | - Tianyu Li
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China,Departments of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Zhong Tang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China,School of Information and Management, Guangxi Medical University, Nanning, China
| | - Qiuyan Wang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China,*Correspondence: Qiuyan Wang, ; Xi Wang,
| | - Xi Wang
- Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China,Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China,*Correspondence: Qiuyan Wang, ; Xi Wang,
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Zeng L, Yang K, Zhang T, Zhu X, Hao W, Chen H, Ge J. Research progress of single-cell transcriptome sequencing in autoimmune diseases and autoinflammatory disease: A review. J Autoimmun 2022; 133:102919. [PMID: 36242821 DOI: 10.1016/j.jaut.2022.102919] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 12/07/2022]
Abstract
Autoimmunity refers to the phenomenon that the body's immune system produces antibodies or sensitized lymphocytes to its own tissues to cause an immune response. Immune disorders caused by autoimmunity can mediate autoimmune diseases. Autoimmune diseases have complicated pathogenesis due to the many types of cells involved, and the mechanism is still unclear. The emergence of single-cell research technology can solve the problem that ordinary transcriptome technology cannot be accurate to cell type. It provides unbiased results through independent analysis of cells in tissues and provides more mRNA information for identifying cell subpopulations, which provides a novel approach to study disruption of immune tolerance and disturbance of pro-inflammatory pathways on a cellular basis. It may fundamentally change the understanding of molecular pathways in the pathogenesis of autoimmune diseases and develop targeted drugs. Single-cell transcriptome sequencing (scRNA-seq) has been widely applied in autoimmune diseases, which provides a powerful tool for demonstrating the cellular heterogeneity of tissues involved in various immune inflammations, identifying pathogenic cell populations, and revealing the mechanism of disease occurrence and development. This review describes the principles of scRNA-seq, introduces common sequencing platforms and practical procedures, and focuses on the progress of scRNA-seq in 41 autoimmune diseases, which include 9 systemic autoimmune diseases and autoinflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, etc.) and 32 organ-specific autoimmune diseases (5 Skin diseases, 3 Nervous system diseases, 4 Eye diseases, 2 Respiratory system diseases, 2 Circulatory system diseases, 6 Liver, Gallbladder and Pancreas diseases, 2 Gastrointestinal system diseases, 3 Muscle, Bones and joint diseases, 3 Urinary system diseases, 2 Reproductive system diseases). This review also prospects the molecular mechanism targets of autoimmune diseases from the multi-molecular level and multi-dimensional analysis combined with single-cell multi-omics sequencing technology (such as scRNA-seq, Single cell ATAC-seq and single cell immune group library sequencing), which provides a reference for further exploring the pathogenesis and marker screening of autoimmune diseases and autoimmune inflammatory diseases in the future.
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Affiliation(s)
- Liuting Zeng
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Kailin Yang
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China.
| | - Tianqing Zhang
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China
| | - Xiaofei Zhu
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China.
| | - Wensa Hao
- Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hua Chen
- Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases, State Key Laboratory of Complex Severe and Rare Diseases, Beijing, China.
| | - Jinwen Ge
- Key Laboratory of Hunan Province for Integrated Traditional Chinese and Western Medicine on Prevention and Treatment of Cardio-Cerebral Diseases, Hunan University of Chinese Medicine, Changsha, China; Hunan Academy of Chinese Medicine, Changsha, China.
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35
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Hsieh WC, Budiarto BR, Wang YF, Lin CY, Gwo MC, So DK, Tzeng YS, Chen SY. Spatial multi-omics analyses of the tumor immune microenvironment. J Biomed Sci 2022; 29:96. [DOI: 10.1186/s12929-022-00879-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 11/02/2022] [Indexed: 11/16/2022] Open
Abstract
AbstractIn the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell–cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial ‘omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.
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Vijayaragavan K, Cannon BJ, Tebaykin D, Bossé M, Baranski A, Oliveria JP, Bukhari SA, Mrdjen D, Corces MR, McCaffrey EF, Greenwald NF, Sigal Y, Marquez D, Khair Z, Bruce T, Goldston M, Bharadwaj A, Montine KS, Angelo RM, Montine TJ, Bendall SC. Single-cell spatial proteomic imaging for human neuropathology. Acta Neuropathol Commun 2022; 10:158. [PMID: 36333818 PMCID: PMC9636771 DOI: 10.1186/s40478-022-01465-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022] Open
Abstract
Neurodegenerative disorders are characterized by phenotypic changes and hallmark proteopathies. Quantifying these in archival human brain tissues remains indispensable for validating animal models and understanding disease mechanisms. We present a framework for nanometer-scale, spatial proteomics with multiplex ion beam imaging (MIBI) for capturing neuropathological features. MIBI facilitated simultaneous, quantitative imaging of 36 proteins on archival human hippocampus from individuals spanning cognitively normal to dementia. Customized analysis strategies identified cell types and proteopathies in the hippocampus across stages of Alzheimer's disease (AD) neuropathologic change. We show microglia-pathologic tau interactions in hippocampal CA1 subfield in AD dementia. Data driven, sample independent creation of spatial proteomic regions identified persistent neurons in pathologic tau neighborhoods expressing mitochondrial protein MFN2, regardless of cognitive status, suggesting a survival advantage. Our study revealed unique insights from multiplexed imaging and data-driven approaches for neuropathologic analysis and serves broadly as a methodology for spatial proteomic analysis of archival human neuropathology. TEASER: Multiplex Ion beam Imaging enables deep spatial phenotyping of human neuropathology-associated cellular and disease features.
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Affiliation(s)
| | - Bryan J Cannon
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Dmitry Tebaykin
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Marc Bossé
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Alex Baranski
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - J P Oliveria
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Syed A Bukhari
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Dunja Mrdjen
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Erin F McCaffrey
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Noah F Greenwald
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Diana Marquez
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Zumana Khair
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Trevor Bruce
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Mako Goldston
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Anusha Bharadwaj
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Kathleen S Montine
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - R Michael Angelo
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Thomas J Montine
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Sean C Bendall
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA.
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Zhao J, Liu Y, Wang M, Ma J, Yang P, Wang S, Wu Q, Gao J, Chen M, Qu G, Wang J, Jiang G. Insights into highly multiplexed tissue images: A primer for Mass Cytometry Imaging data analysis. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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38
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Kramvis A, Chang KM, Dandri M, Farci P, Glebe D, Hu J, Janssen HLA, Lau DTY, Penicaud C, Pollicino T, Testoni B, Van Bömmel F, Andrisani O, Beumont-Mauviel M, Block TM, Chan HLY, Cloherty GA, Delaney WE, Geretti AM, Gehring A, Jackson K, Lenz O, Maini MK, Miller V, Protzer U, Yang JC, Yuen MF, Zoulim F, Revill PA. A roadmap for serum biomarkers for hepatitis B virus: current status and future outlook. Nat Rev Gastroenterol Hepatol 2022; 19:727-745. [PMID: 35859026 PMCID: PMC9298709 DOI: 10.1038/s41575-022-00649-z] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/16/2022] [Indexed: 12/13/2022]
Abstract
Globally, 296 million people are infected with hepatitis B virus (HBV), and approximately one million people die annually from HBV-related causes, including liver cancer. Although there is a preventative vaccine and antiviral therapies suppressing HBV replication, there is no cure. Intensive efforts are under way to develop curative HBV therapies. Currently, only a few biomarkers are available for monitoring or predicting HBV disease progression and treatment response. As new therapies become available, new biomarkers to monitor viral and host responses are urgently needed. In October 2020, the International Coalition to Eliminate Hepatitis B Virus (ICE-HBV) held a virtual and interactive workshop on HBV biomarkers endorsed by the International HBV Meeting. Various stakeholders from academia, clinical practice and the pharmaceutical industry, with complementary expertise, presented and participated in panel discussions. The clinical utility of both classic and emerging viral and immunological serum biomarkers with respect to the course of infection, disease progression, and response to current and emerging treatments was appraised. The latest advances were discussed, and knowledge gaps in understanding and interpretation of HBV biomarkers were identified. This Roadmap summarizes the strengths, weaknesses, opportunities and challenges of HBV biomarkers.
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Affiliation(s)
- Anna Kramvis
- Hepatitis Virus Diversity Research Unit, Department of Internal Medicine, School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa.
| | - Kyong-Mi Chang
- The Corporal Michael J. Crescenz Veterans Affairs Medical Center and University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Maura Dandri
- Department of Internal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- German Centre for Infection Research (DZIF), Hamburg-Lübeck-Borstel-Riems partner site, Hamburg, Germany
| | - Patrizia Farci
- Hepatic Pathogenesis Section, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Dieter Glebe
- National Reference Center for Hepatitis B Viruses and Hepatitis D Viruses, Institute of Medical Virology, Justus Liebig University Giessen, Giessen, Germany
- German Center for Infection Research (DZIF), Partner Site Giessen-Marburg-Langen, Giessen, Germany
| | - Jianming Hu
- Department of Microbiology and Immunology, The Pennsylvania State University College of Medicine, Philadelphia, PA, USA
| | - Harry L A Janssen
- Toronto Centre for Liver Disease, University of Toronto, Toronto, Canada
| | - Daryl T Y Lau
- Division of Gastroenterology and Hepatology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Capucine Penicaud
- Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Teresa Pollicino
- Laboratory of Molecular Hepatology, Department of Human Pathology, University Hospital "G. Martino" of Messina, Messina, Italy
| | - Barbara Testoni
- INSERM U1052, CNRS UMR-5286, Cancer Research Center of Lyon (CRCL), Lyon, France
- University of Lyon, Université Claude-Bernard (UCBL), Lyon, France
| | - Florian Van Bömmel
- Department of Hepatology, Leipzig University Medical Center, Leipzig, Germany
| | - Ourania Andrisani
- Basic Medical Sciences, Purdue University, West Lafayette, Indiana, USA
| | | | | | - Henry L Y Chan
- Chinese University of Hong Kong, Shatin, Hong Kong
- Union Hospital, Shatin, Hong Kong
| | | | | | - Anna Maria Geretti
- Roche Pharma Research & Early Development, Basel, Switzerland
- Department of Infectious Diseases, Fondazione PTV, Faculty of Medicine, University of Rome Tor Vergata, Rome, Italy
- Department of Infectious Diseases, School of Immunology & Microbial Sciences, King's College London, London, UK
| | - Adam Gehring
- Toronto Centre for Liver Disease, University Health Network, Toronto, Canada
| | - Kathy Jackson
- Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | | | - Mala K Maini
- Division of Infection & Immunity, Institute of Immunity & Transplantation, University College London, London, UK
| | - Veronica Miller
- Forum for Collaborative Research, University of California Berkeley School of Public Health, Washington DC Campus, Washington, DC, USA
| | - Ulrike Protzer
- Institute of Virology, School of Medicine, Technical University of Munich, Helmholtz Zentrum München, Munich, Germany
| | | | - Man-Fung Yuen
- Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong, China
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong, China
| | - Fabien Zoulim
- INSERM Unit 1052 - Cancer Research Center of Lyon, Hospices Civils de Lyon, Lyon University, Lyon, France
| | - Peter A Revill
- Victorian Infectious Diseases Reference Laboratory, Royal Melbourne Hospital at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
- Department of Microbiology and Immunology, University of Melbourne, Parkville, Victoria, Australia.
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Fusco L, Gazzi A, Shuck CE, Orecchioni M, Alberti D, D'Almeida SM, Rinchai D, Ahmed E, Elhanani O, Rauner M, Zavan B, Grivel JC, Keren L, Pasqual G, Bedognetti D, Ley K, Gogotsi Y, Delogu LG. Immune Profiling and Multiplexed Label-Free Detection of 2D MXenes by Mass Cytometry and High-Dimensional Imaging. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2205154. [PMID: 36207284 PMCID: PMC10915970 DOI: 10.1002/adma.202205154] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/22/2022] [Indexed: 06/16/2023]
Abstract
There is a critical unmet need to detect and image 2D materials within single cells and tissues while surveying a high degree of information from single cells. Here, a versatile multiplexed label-free single-cell detection strategy is proposed based on single-cell mass cytometry by time-of-flight (CyTOF) and ion-beam imaging by time-of-flight (MIBI-TOF). This strategy, "Label-free sINgle-cell tracKing of 2D matErials by mass cytometry and MIBI-TOF Design" (LINKED), enables nanomaterial detection and simultaneous measurement of multiple cell and tissue features. As a proof of concept, a set of 2D materials, transition metal carbides, nitrides, and carbonitrides (MXenes), is selected to ensure mass detection within the cytometry range while avoiding overlap with more than 70 currently available tags, each able to survey multiple biological parameters. First, their detection and quantification in 15 primary human immune cell subpopulations are demonstrated. Together with the detection, mass cytometry is used to capture several biological aspects of MXenes, such as their biocompatibility and cytokine production after their uptake. Through enzymatic labeling, MXenes' mediation of cell-cell interactions is simultaneously evaluated. In vivo biodistribution experiments using a mixture of MXenes in mice confirm the versatility of the detection strategy and reveal MXene accumulation in the liver, blood, spleen, lungs, and relative immune cell subtypes. Finally, MIBI-TOF is applied to detect MXenes in different organs revealing their spatial distribution. The label-free detection of 2D materials by mass cytometry at the single-cell level, on multiple cell subpopulations and in multiple organs simultaneously, will enable exciting new opportunities in biomedicine.
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Affiliation(s)
- Laura Fusco
- ImmuneNano Laboratory, Department of Biomedical Sciences, University of Padua, Padua, 35129, Italy
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA, 19104, USA
- Human Immunology Division, Translational Medicine Department, Sidra Medicine, Doha, 26999, Qatar
| | - Arianna Gazzi
- ImmuneNano Laboratory, Department of Biomedical Sciences, University of Padua, Padua, 35129, Italy
- Department of Chemical and Pharmaceutical Sciences, University of Trieste, Trieste, 34127, Italy
| | - Christopher E Shuck
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA, 19104, USA
| | | | - Dafne Alberti
- Laboratory of Synthetic Immunology, Oncology and Immunology Section, Department of Surgery Oncology and Gastroenterology, University of Padua, Padua, 35124, Italy
| | - Sènan Mickael D'Almeida
- Flow Cytometry Core Facility, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, 1015, Switzerland
| | - Darawan Rinchai
- Human Immunology Division, Translational Medicine Department, Sidra Medicine, Doha, 26999, Qatar
| | - Eiman Ahmed
- Human Immunology Division, Translational Medicine Department, Sidra Medicine, Doha, 26999, Qatar
| | - Ofer Elhanani
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Martina Rauner
- Department of Medicine III, Center for Healthy Aging, Technical University Dresden, 01307, Dresden, Germany
| | - Barbara Zavan
- Department of Medical Sciences, University of Ferrara, Ferrara, 44121, Italy
- Maria Cecilia Hospital, GVM Care & Research, Ravenna, 48033, Italy
| | | | - Leeat Keren
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, 7610001, Israel
| | - Giulia Pasqual
- Laboratory of Synthetic Immunology, Oncology and Immunology Section, Department of Surgery Oncology and Gastroenterology, University of Padua, Padua, 35124, Italy
| | - Davide Bedognetti
- Human Immunology Division, Translational Medicine Department, Sidra Medicine, Doha, 26999, Qatar
- Department of Internal Medicine and Medical Specialties, University of Genoa, Genoa, 16132, Italy
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, 34110, Qatar
| | - Klaus Ley
- La Jolla Institute for Immunology, San Diego, CA, 92037, USA
- Immunology Center of Georgia (IMMCG), Augusta University, Augusta, GA, 30912, USA
| | - Yury Gogotsi
- A. J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA, 19104, USA
| | - Lucia Gemma Delogu
- ImmuneNano Laboratory, Department of Biomedical Sciences, University of Padua, Padua, 35129, Italy
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Ko J, Wilkovitsch M, Oh J, Kohler RH, Bolli E, Pittet MJ, Vinegoni C, Sykes DB, Mikula H, Weissleder R, Carlson JCT. Spatiotemporal multiplexed immunofluorescence imaging of living cells and tissues with bioorthogonal cycling of fluorescent probes. Nat Biotechnol 2022; 40:1654-1662. [PMID: 35654978 PMCID: PMC9669087 DOI: 10.1038/s41587-022-01339-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 04/28/2022] [Indexed: 02/07/2023]
Abstract
Cells in complex organisms undergo frequent functional changes, but few methods allow comprehensive longitudinal profiling of living cells. Here we introduce scission-accelerated fluorophore exchange (SAFE), a method for multiplexed temporospatial imaging of living cells with immunofluorescence. SAFE uses a rapid bioorthogonal click chemistry to remove immunofluorescent signals from the surface of labeled cells, cycling the nanomolar-concentration reagents in seconds and enabling multiple rounds of staining of the same samples. It is non-toxic and functional in both dispersed cells and intact living tissues. We demonstrate multiparameter (n ≥ 14), non-disruptive imaging of murine peripheral blood mononuclear and bone marrow cells to profile cellular differentiation. We also show longitudinal multiplexed imaging of bone marrow progenitor cells as they develop into neutrophils over 6 days and real-time multiplexed cycling of living mouse hepatic tissues. We anticipate that SAFE will find broad utility for investigating physiologic dynamics in living systems.
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Affiliation(s)
- Jina Ko
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Juhyun Oh
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Rainer H Kohler
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Evangelia Bolli
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
| | - Mikael J Pittet
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
- Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland
- Ludwig Institute for Cancer Research, Lausanne Branch, Zurich, Switzerland
- AGORA Cancer Center, Lausanne, Switzerland
| | - Claudio Vinegoni
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | - David B Sykes
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hannes Mikula
- Institute of Applied Synthetic Chemistry, TU Wien, Vienna, Austria
| | - Ralph Weissleder
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
| | - Jonathan C T Carlson
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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41
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van der Pan K, Kassem S, Khatri I, de Ru AH, Janssen GMC, Tjokrodirijo RTN, al Makindji F, Stavrakaki E, de Jager AL, Naber BAE, de Laat IF, Louis A, van den Bossche WBL, Vogelezang LB, Balvers RK, Lamfers MLM, van Veelen PA, Orfao A, van Dongen JJM, Teodosio C, Díez P. Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting. Front Med (Lausanne) 2022; 9:997305. [PMID: 36237552 PMCID: PMC9553008 DOI: 10.3389/fmed.2022.997305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 08/31/2022] [Indexed: 11/13/2022] Open
Abstract
Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.
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Affiliation(s)
- Kyra van der Pan
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Sara Kassem
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Indu Khatri
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Leiden Computational Biology Center, LUMC, Leiden, Netherlands
| | - Arnoud H. de Ru
- Center for Proteomics and Metabolomics, LUMC, Leiden, Netherlands
| | | | | | - Fadi al Makindji
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | | | - Anniek L. de Jager
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Brigitta A. E. Naber
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Inge F. de Laat
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Alesha Louis
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | | | | | | | | | | | - Alberto Orfao
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Jacques J. M. van Dongen
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- *Correspondence: Jacques J. M. van Dongen
| | - Cristina Teodosio
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Paula Díez
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
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Yu H, Tai Q, Yang C, Weng L, Gao M, Zhang X. Counting Protein Number in a Single Cell by a Picoliter Liquid Operating Technology. Anal Chem 2022; 94:11925-11933. [PMID: 35980697 DOI: 10.1021/acs.analchem.2c02701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Ultra-low-copy number proteins play a crucial role in exploring cellular heterogeneity and the insight of protein biomarkers in a single cell. However, counting ultra-low-copy number target proteins in a single cell remains a grand challenge. Herein, we developed a so-called single-cell picoliter liquid operating technology for counting target proteins in a single cell. An ingenious volume-controllable sampling technique was employed to capture a single cell for subsequent analysis. Remarkably, 50 pL of sample volume was employed for sample preparation, single-cell capture, in-droplet lysis, and target protein immobilization on a functionalized coverslip in a monolayer. Then, target protein antibodies coupled with quantum dots were added and incubated to label those immobilized proteins. After clean-up, a single-view image under 100× objective was taken, and the 80 × 80 μm2 view image was then applied to count the precise copy number of the target proteins in the single cell. Furthermore, good linearity and repeatability were achieved for ultra-low-copy number proteins, ranging from 1 to 1500. Finally, the expression level of human epidermal growth factor receptor 2 in single cells from both MCF-7 and MDA-MB-231 cell lines was also analyzed. In a word, this work stimulated the development of capillary-based single-cell analysis and updated the connotation of counting ultra-low-copy number proteins.
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Affiliation(s)
- Hailong Yu
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Qunfei Tai
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Chenjie Yang
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Lingxiao Weng
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Mingxia Gao
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Xiangmin Zhang
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
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43
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Kumánovics A, Sadighi Akha AA. Flow cytometry for B-cell subset analysis in immunodeficiencies. J Immunol Methods 2022; 509:113327. [DOI: 10.1016/j.jim.2022.113327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 06/07/2022] [Accepted: 08/01/2022] [Indexed: 11/28/2022]
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44
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Anwar IJ, Luo X. Research Highlights. Transplantation 2022; 106:1298-1299. [PMID: 37779318 DOI: 10.1097/tp.0000000000004225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
| | - Xunrong Luo
- Department of Medicine, Division of Nephrology, Duke University, Durham, NC
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45
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Feldman TP, Egan ES. Uncovering a Cryptic Site of Malaria Pathogenesis: Models to Study Interactions Between Plasmodium and the Bone Marrow. Front Cell Infect Microbiol 2022; 12:917267. [PMID: 35719356 PMCID: PMC9201243 DOI: 10.3389/fcimb.2022.917267] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 05/03/2022] [Indexed: 12/21/2022] Open
Abstract
The bone marrow is a critical site of host-pathogen interactions in malaria infection. The discovery of Plasmodium asexual and transmission stages in the bone marrow has renewed interest in the tissue as a niche for cellular development of both host and parasite. Despite its importance, bone marrow in malaria infection remains largely unexplored due to the challenge of modeling the complex hematopoietic environment in vitro. Advancements in modeling human erythropoiesis ex-vivo from primary human hematopoietic stem and progenitor cells provide a foothold to study the host-parasite interactions occurring in this understudied site of malaria pathogenesis. This review focuses on current in vitro methods to recapitulate and assess bone marrow erythropoiesis and their potential applications in the malaria field. We summarize recent studies that leveraged ex-vivo erythropoiesis to shed light on gametocyte development in nucleated erythroid stem cells and begin to characterize host cell responses to Plasmodium infection in the hematopoietic niche. Such models hold potential to elucidate mechanisms of disordered erythropoiesis, an underlying contributor to malaria anemia, as well as understand the biological determinants of parasite sexual conversion. This review compares the advantages and limitations of the ex-vivo erythropoiesis approach with those of in vivo human and animal studies of the hematopoietic niche in malaria infection. We highlight the need for studies that apply single cell analyses to this complex system and incorporate physical and cellular components of the bone marrow that may influence erythropoiesis and parasite development.
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Affiliation(s)
- Tamar P. Feldman
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, United States
| | - Elizabeth S. Egan
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, United States
- *Correspondence: Elizabeth S. Egan,
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Badve SS, Gökmen-Polar Y. Protein Profiling of Breast Cancer for Treatment Decision-Making. Am Soc Clin Oncol Educ Book 2022; 42:1-9. [PMID: 35580295 DOI: 10.1200/edbk_351207] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The increasing use of neoadjuvant therapy has resulted in therapeutic decisions being made on the basis of diagnostic needle core biopsy. For many patients, this method might yield the only fragment of tumor available for biomarker analysis, necessitating judicious use. Many multiplex protein analytic methods have been developed that employ fluorescence or other tags to overcome the limitations of immunohistochemistry while still retaining the spatial annotation. Interpretation of the data can be difficult because of the limitations of the human eye. Computational deconvolution of the signals may be necessary for some of these methods to enable identification of cell-specific localization and coexpression of biomarkers. Herein, we present the different methods that are coming of age and their application in cancer research, with a focus on breast cancer. We also discuss the limitations, which include high costs and long turnaround times. The methods are also based on the premise that preanalytical factors will have identical impact on all proteins analyzed. There is a need to establish standards to normalize the data and enable cross-sample comparisons. In spite of these limitations, the multiplex technologies are extremely valuable discovery tools and can provide novel insights into the biology of cancer and mechanisms of drug resistance.
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Affiliation(s)
- Sunil S Badve
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA
| | - Yesim Gökmen-Polar
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA
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47
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Verberk SG, de Goede KE, Gorki FS, van Dierendonck XA, Argüello RJ, Van den Bossche J. An integrated toolbox to profile macrophage immunometabolism. CELL REPORTS METHODS 2022; 2:100192. [PMID: 35497494 PMCID: PMC9046227 DOI: 10.1016/j.crmeth.2022.100192] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 12/23/2021] [Accepted: 03/07/2022] [Indexed: 10/25/2022]
Abstract
Macrophages are dynamic immune cells that can adopt several activation states. Fundamental to these functional activation states is the regulation of cellular metabolic processes. Especially in mice, metabolic alterations underlying pro-inflammatory or homeostatic phenotypes have been assessed using various techniques. However, researchers new to the field may encounter ambiguity in choosing which combination of techniques is best suited to profile immunometabolism. To address this need, we have developed a toolbox to assess cellular metabolism in a semi-high-throughput 96-well-plate-based format. Application of the toolbox to activated mouse and human macrophages enables fast metabolic pre-screening and robust measurement of extracellular fluxes, mitochondrial mass and membrane potential, and glucose and lipid uptake. Moreover, we propose an application of SCENITH technology for ex vivo metabolic profiling. We validate established activation-induced metabolic rewiring in mouse macrophages and report new insights into human macrophage metabolism. By thoroughly discussing each technique, we hope to guide readers with practical workflows for investigating immunometabolism.
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Affiliation(s)
- Sanne G.S. Verberk
- Department of Molecular Cell Biology and Immunology, Amsterdam Cardiovascular Sciences, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Institute for Infection and Immunity, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Kyra E. de Goede
- Department of Molecular Cell Biology and Immunology, Amsterdam Cardiovascular Sciences, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Institute for Infection and Immunity, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Friederike S. Gorki
- Department of Molecular Cell Biology and Immunology, Amsterdam Cardiovascular Sciences, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Institute for Infection and Immunity, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Institute of Innate Immunity, University Hospital Bonn, University of Bonn, 53127 Bonn, Germany
| | - Xanthe A.M.H. van Dierendonck
- Department of Molecular Cell Biology and Immunology, Amsterdam Cardiovascular Sciences, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Institute for Infection and Immunity, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rafael J. Argüello
- Aix Marseille Univ, CNRS, INSERM, CIML, Centre d’Immunologie de Marseille-Luminy, Marseille, France
| | - Jan Van den Bossche
- Department of Molecular Cell Biology and Immunology, Amsterdam Cardiovascular Sciences, Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam Institute for Infection and Immunity, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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48
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Huang Y, Si X, Shao M, Teng X, Xiao G, Huang H. Rewiring mitochondrial metabolism to counteract exhaustion of CAR-T cells. J Hematol Oncol 2022; 15:38. [PMID: 35346311 PMCID: PMC8960222 DOI: 10.1186/s13045-022-01255-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 03/11/2022] [Indexed: 12/16/2022] Open
Abstract
Short persistence and early exhaustion of T cells are major limits to the efficacy and broad application of immunotherapy. Exhausted T and chimeric antigen receptor (CAR)-T cells upregulate expression of genes associated with terminated T cell differentiation, aerobic glycolysis and apoptosis. Among cell exhaustion characteristics, impaired mitochondrial function and dynamics are considered hallmarks. Here, we review the mitochondrial characteristics of exhausted T cells and particularly discuss different aspects of mitochondrial metabolism and plasticity. Furthermore, we propose a novel strategy of rewiring mitochondrial metabolism to emancipate T cells from exhaustion and of targeting mitochondrial plasticity to boost CAR-T cell therapy efficacy.
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Affiliation(s)
- Yue Huang
- Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, No. 79 Qingchun Road, Hangzhou, China.,Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, China.,Institute of Hematology, Zhejiang University, Hangzhou, China.,Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, China
| | - Xiaohui Si
- Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, No. 79 Qingchun Road, Hangzhou, China.,Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, China.,Institute of Hematology, Zhejiang University, Hangzhou, China.,Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, China
| | - Mi Shao
- Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, No. 79 Qingchun Road, Hangzhou, China.,Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, China.,Institute of Hematology, Zhejiang University, Hangzhou, China.,Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, China
| | - Xinyi Teng
- Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, No. 79 Qingchun Road, Hangzhou, China.,Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, China.,Institute of Hematology, Zhejiang University, Hangzhou, China.,Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, China
| | - Gang Xiao
- Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, China. .,Institute of Hematology, Zhejiang University, Hangzhou, China. .,Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, China. .,Institute of Immunology, Zhejiang University, Hangzhou, China.
| | - He Huang
- Bone Marrow Transplantation Center, The First Affiliated Hospital, School of Medicine, Zhejiang University, No. 79 Qingchun Road, Hangzhou, China. .,Liangzhu Laboratory, Zhejiang University Medical Center, 1369 West Wenyi Road, Hangzhou, China. .,Institute of Hematology, Zhejiang University, Hangzhou, China. .,Zhejiang Province Engineering Laboratory for Stem Cell and Immunity Therapy, Hangzhou, China.
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Wculek SK, Dunphy G, Heras-Murillo I, Mastrangelo A, Sancho D. Metabolism of tissue macrophages in homeostasis and pathology. Cell Mol Immunol 2022; 19:384-408. [PMID: 34876704 PMCID: PMC8891297 DOI: 10.1038/s41423-021-00791-9] [Citation(s) in RCA: 129] [Impact Index Per Article: 64.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 09/25/2021] [Indexed: 02/06/2023] Open
Abstract
Cellular metabolism orchestrates the intricate use of tissue fuels for catabolism and anabolism to generate cellular energy and structural components. The emerging field of immunometabolism highlights the importance of cellular metabolism for the maintenance and activities of immune cells. Macrophages are embryo- or adult bone marrow-derived leukocytes that are key for healthy tissue homeostasis but can also contribute to pathologies such as metabolic syndrome, atherosclerosis, fibrosis or cancer. Macrophage metabolism has largely been studied in vitro. However, different organs contain diverse macrophage populations that specialize in distinct and often tissue-specific functions. This context specificity creates diverging metabolic challenges for tissue macrophage populations to fulfill their homeostatic roles in their particular microenvironment and conditions their response in pathological conditions. Here, we outline current knowledge on the metabolic requirements and adaptations of macrophages located in tissues during homeostasis and selected diseases.
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Affiliation(s)
- Stefanie K Wculek
- Immunobiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, Madrid, 28029, Spain.
| | - Gillian Dunphy
- Immunobiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, Madrid, 28029, Spain
| | - Ignacio Heras-Murillo
- Immunobiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, Madrid, 28029, Spain
| | - Annalaura Mastrangelo
- Immunobiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, Madrid, 28029, Spain
| | - David Sancho
- Immunobiology Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, Madrid, 28029, Spain.
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50
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Purohit V, Wagner A, Yosef N, Kuchroo VK. Systems-based approaches to study immunometabolism. Cell Mol Immunol 2022; 19:409-420. [PMID: 35121805 PMCID: PMC8891302 DOI: 10.1038/s41423-021-00783-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 09/17/2021] [Indexed: 02/06/2023] Open
Abstract
Technical advances at the interface of biology and computation, such as single-cell RNA-sequencing (scRNA-seq), reveal new layers of complexity in cellular systems. An emerging area of investigation using the systems biology approach is the study of the metabolism of immune cells. The diverse spectra of immune cell phenotypes, sparsity of immune cell numbers in vivo, limitations in the number of metabolites identified, dynamic nature of cellular metabolism and metabolic fluxes, tissue specificity, and high dependence on the local milieu make investigations in immunometabolism challenging, especially at the single-cell level. In this review, we define the systemic nature of immunometabolism, summarize cell- and system-based approaches, and introduce mathematical modeling approaches for systems interrogation of metabolic changes in immune cells. We close the review by discussing the applications and shortcomings of metabolic modeling techniques. With systems-oriented studies of metabolism expected to become a mainstay of immunological research, an understanding of current approaches toward systems immunometabolism will help investigators make the best use of current resources and push the boundaries of the discipline.
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Affiliation(s)
- Vinee Purohit
- Evergrande Center for Immunologic Diseases and Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA
| | - Allon Wagner
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, 94720, USA
- Center for Computational Biology, University of California, Berkeley, CA, 94720, USA
| | - Nir Yosef
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, 94720, USA
- Center for Computational Biology, University of California, Berkeley, CA, 94720, USA
| | - Vijay K Kuchroo
- Evergrande Center for Immunologic Diseases and Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, 02141, USA.
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