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Zhao M, Cheng Y, Gao J, Zhou F. Single-cell mass cytometry in immunological skin diseases. Front Immunol 2024; 15:1401102. [PMID: 39081313 PMCID: PMC11286489 DOI: 10.3389/fimmu.2024.1401102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 07/01/2024] [Indexed: 08/02/2024] Open
Abstract
Immune-related skin diseases represent a collective of dermatological disorders intricately linked to dysfunctional immune system processes. These conditions are primarily characterized by an immoderate activation of the immune system or deviant immune responses, involving diverse immune components including immune cells, antibodies, and inflammatory mediators. However, the precise molecular dysregulation underlying numerous individual cases of these diseases and unique subsets respond under disease conditions remains elusive. Comprehending the mechanisms and determinants governing the homeostasis and functionality of diseases could offer potential therapeutic opportunities for intervention. Mass cytometry enables precise and high-throughput quantitative measurement of proteins within individual cells by utilizing antibodies labeled with rare heavy metal isotopes. Imaging mass cytometry employs mass spectrometry to obtain spatial information on cell-to-cell interactions within tissue sections, simultaneously utilizing more than 40 markers. The application of single-cell mass cytometry presents a unique opportunity to conduct highly multiplexed analysis at the single-cell level, thereby revolutionizing our understanding of cell population heterogeneity and hierarchy, cellular states, multiplexed signaling pathways, proteolysis products, and mRNA transcripts specifically in the context of many autoimmune diseases. This information holds the potential to offer novel approaches for the diagnosis, prognostic assessment, and monitoring responses to treatment, thereby enriching our strategies in managing the respective conditions. This review summarizes the present-day utilization of single-cell mass cytometry in studying immune-related skin diseases, highlighting its advantages and limitations. This technique will become increasingly prevalent in conducting extensive investigations into these disorders, ultimately yielding significant contributions to their accurate diagnosis and efficacious therapeutic interventions.
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Affiliation(s)
- Mingming Zhao
- Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, Hefei, Anhui, China
- Institute of Dermatology, Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Yuqi Cheng
- Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, Hefei, Anhui, China
- Institute of Dermatology, Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jinping Gao
- Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, Hefei, Anhui, China
- Institute of Dermatology, Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Fusheng Zhou
- Department of Dermatology, The First Affiliated Hospital, Anhui Medical University, Hefei, Anhui, China
- Institute of Dermatology, Anhui Medical University, Hefei, Anhui, China
- Key Laboratory of Dermatology (Anhui Medical University), Ministry of Education, Hefei, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
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Augustin RC, Cai WL, Luke JJ, Bao R. Facts and Hopes in Using Omics to Advance Combined Immunotherapy Strategies. Clin Cancer Res 2024; 30:1724-1732. [PMID: 38236069 PMCID: PMC11062841 DOI: 10.1158/1078-0432.ccr-22-2241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 09/28/2023] [Accepted: 12/22/2023] [Indexed: 01/19/2024]
Abstract
The field of oncology has been transformed by immune checkpoint inhibitors (ICI) and other immune-based agents; however, many patients do not receive a durable benefit. While biomarker assessments from pivotal ICI trials have uncovered certain mechanisms of resistance, results thus far have only scraped the surface. Mechanisms of resistance are as complex as the tumor microenvironment (TME) itself, and the development of effective therapeutic strategies will only be possible by building accurate models of the tumor-immune interface. With advancement of multi-omic technologies, high-resolution characterization of the TME is now possible. In addition to sequencing of bulk tumor, single-cell transcriptomic, proteomic, and epigenomic data as well as T-cell receptor profiling can now be simultaneously measured and compared between responders and nonresponders to ICI. Spatial sequencing and imaging platforms have further expanded the dimensionality of existing technologies. Rapid advancements in computation and data sharing strategies enable development of biologically interpretable machine learning models to integrate data from high-resolution, multi-omic platforms. These models catalyze the identification of resistance mechanisms and predictors of benefit in ICI-treated patients, providing scientific foundation for novel clinical trials. Moving forward, we propose a framework by which in silico screening, functional validation, and clinical trial biomarker assessment can be used for the advancement of combined immunotherapy strategies.
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Affiliation(s)
- Ryan C. Augustin
- UPMC Hillman Cancer Center, Pittsburgh, PA
- University of Pittsburgh, Department of Medicine, Pittsburgh, PA
- Mayo Clinic, Department of Medical Oncology, Rochester, MN
| | - Wesley L. Cai
- University of Pittsburgh, Department of Medicine, Pittsburgh, PA
| | - Jason J. Luke
- UPMC Hillman Cancer Center, Pittsburgh, PA
- University of Pittsburgh, Department of Medicine, Pittsburgh, PA
| | - Riyue Bao
- UPMC Hillman Cancer Center, Pittsburgh, PA
- University of Pittsburgh, Department of Medicine, Pittsburgh, PA
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DiIorio SE, Young B, Parker JB, Griffin MF, Longaker MT. Understanding Tendon Fibroblast Biology and Heterogeneity. Biomedicines 2024; 12:859. [PMID: 38672213 PMCID: PMC11048404 DOI: 10.3390/biomedicines12040859] [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: 03/07/2024] [Revised: 04/06/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
Tendon regeneration has emerged as an area of interest due to the challenging healing process of avascular tendon tissue. During tendon healing after injury, the formation of a fibrous scar can limit tendon strength and lead to subsequent complications. The specific biological mechanisms that cause fibrosis across different cellular subtypes within the tendon and across different tendons in the body continue to remain unknown. Herein, we review the current understanding of tendon healing, fibrosis mechanisms, and future directions for treatments. We summarize recent research on the role of fibroblasts throughout tendon healing and describe the functional and cellular heterogeneity of fibroblasts and tendons. The review notes gaps in tendon fibrosis research, with a focus on characterizing distinct fibroblast subpopulations in the tendon. We highlight new techniques in the field that can be used to enhance our understanding of complex tendon pathologies such as fibrosis. Finally, we explore bioengineering tools for tendon regeneration and discuss future areas for innovation. Exploring the heterogeneity of tendon fibroblasts on the cellular level can inform therapeutic strategies for addressing tendon fibrosis and ultimately reduce its clinical burden.
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Affiliation(s)
- Sarah E. DiIorio
- Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (S.E.D.); (B.Y.); (J.B.P.); (M.F.G.)
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Bill Young
- Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (S.E.D.); (B.Y.); (J.B.P.); (M.F.G.)
| | - Jennifer B. Parker
- Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (S.E.D.); (B.Y.); (J.B.P.); (M.F.G.)
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Michelle F. Griffin
- Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (S.E.D.); (B.Y.); (J.B.P.); (M.F.G.)
| | - Michael T. Longaker
- Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, CA 94305, USA; (S.E.D.); (B.Y.); (J.B.P.); (M.F.G.)
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
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Xia Y, Ma J, Yang X, Liu D, Zhu Y, Zhao Y, Fei X, Xu D, Dai J. Identifying the Spatial Architecture That Restricts the Proximity of CD8 + T Cells to Tumor Cells in Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 2024; 16:1434. [PMID: 38611111 PMCID: PMC11010991 DOI: 10.3390/cancers16071434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2024] [Revised: 04/03/2024] [Accepted: 04/05/2024] [Indexed: 04/14/2024] Open
Abstract
The anti-tumor function of CD8+ T cells is dependent on their proximity to tumor cells. Current studies have focused on the infiltration level of CD8+ T cells in the tumor microenvironment, while further spatial information, such as spatial localization and inter-cellular communication, have not been defined. In this study, co-detection by indexing (CODEX) was designed to characterize PDAC tissue regions with seven protein markers in order to identify the spatial architecture that regulates CD8+ T cells in human pancreatic ductal adenocarcinoma (PDAC). The cellular neighborhood algorithm was used to identify a total of six conserved and distinct cellular neighborhoods. Among these, one unique spatial architecture of CD8+ T and CD4+ T cell-enriched neighborhoods enriched the majority of CD8+ T cells, but heralded a poor prognosis. The proximity analysis revealed that the CD8+ T cells in this spatial architecture were significantly closer to themselves and the CD4+ T cells than to the tumor cells. Collectively, we identified a unique spatial architecture that restricted the proximity of CD8+ T cells to tumor cells in the tumor microenvironment, indicating a novel immune evasion mechanism of pancreatic ductal adenocarcinoma in a topologically regulated manner and providing new insights into the biology of PDAC.
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Affiliation(s)
- Yihan Xia
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Junrui Ma
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xiaobao Yang
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Danping Liu
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yujie Zhu
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yanan Zhao
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xuefeng Fei
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Dakang Xu
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jing Dai
- Department of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.X.); (J.M.); (X.Y.); (D.L.); (Y.Z.); (Y.Z.); (X.F.)
- College of Health Sciences and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Kumar G, Pandurengan RK, Parra ER, Kannan K, Haymaker C. Spatial modelling of the tumor microenvironment from multiplex immunofluorescence images: methods and applications. Front Immunol 2023; 14:1288802. [PMID: 38179056 PMCID: PMC10765501 DOI: 10.3389/fimmu.2023.1288802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/07/2023] [Indexed: 01/06/2024] Open
Abstract
Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing trials, a number of retrospective approaches can be adopted to understand differences in response, recurrence and progression by examining the patient's TME from tissue samples obtained at baseline and at various time points along the treatment. The multiplex immunofluorescence (mIF) technique provides insight on patient specific cell populations and their relative spatial distribution as qualitative measures of a favorable treatment outcome. Spatial analysis of these images provides an understanding of the intratumoral heterogeneity and clustering among cell populations in the TME. A number of mathematical models, which establish clustering as a measure of deviation from complete spatial randomness, can be applied to the mIF images represented as spatial point patterns. These mathematical models, developed for landscape ecology and geographic information studies, can be applied to the TME after careful consideration of the tumor type (cold vs. hot) and the tumor immune landscape. The spatial modelling of mIF images can show observable engagement of T cells expressing immune checkpoint molecules and this can then be correlated with single-cell RNA sequencing data.
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Affiliation(s)
| | | | | | - Kasthuri Kannan
- Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, United States
| | - Cara Haymaker
- Department of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, United States
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