1
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Kudo T, Meireles AM, Moncada R, Chen Y, Wu P, Gould J, Hu X, Kornfeld O, Jesudason R, Foo C, Höckendorf B, Corrada Bravo H, Town JP, Wei R, Rios A, Chandrasekar V, Heinlein M, Chuong AS, Cai S, Lu CS, Coelho P, Mis M, Celen C, Kljavin N, Jiang J, Richmond D, Thakore P, Benito-Gutiérrez E, Geiger-Schuller K, Hleap JS, Kayagaki N, de Sousa E Melo F, McGinnis L, Li B, Singh A, Garraway L, Rozenblatt-Rosen O, Regev A, Lubeck E. Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView. Nat Biotechnol 2024:10.1038/s41587-024-02391-0. [PMID: 39375449 DOI: 10.1038/s41587-024-02391-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 08/20/2024] [Indexed: 10/09/2024]
Abstract
Optical pooled screening (OPS) is a scalable method for linking image-based phenotypes with cellular perturbations. However, it has thus far been restricted to relatively low-plex phenotypic readouts in cancer cell lines in culture due to limitations associated with in situ sequencing of perturbation barcodes. Here, we develop PerturbView, an OPS technology that leverages in vitro transcription to amplify barcodes before in situ sequencing, enabling screens with highly multiplexed phenotypic readouts across diverse systems, including primary cells and tissues. We demonstrate PerturbView in induced pluripotent stem cell-derived neurons, primary immune cells and tumor tissue sections from animal models. In a screen of immune signaling pathways in primary bone marrow-derived macrophages, PerturbView uncovered both known and novel regulators of NF-κB signaling. Furthermore, we combine PerturbView with spatial transcriptomics in tissue sections from a mouse xenograft model, paving the way to in situ screens with rich optical and transcriptomic phenotypes. PerturbView broadens the scope of OPS to a wide range of models and applications.
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Affiliation(s)
- Takamasa Kudo
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Ana M Meireles
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Reuben Moncada
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Yushu Chen
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Ping Wu
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Joshua Gould
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Xiaoyu Hu
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Opher Kornfeld
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Rajiv Jesudason
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Conrad Foo
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Burkhard Höckendorf
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Hector Corrada Bravo
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Jason P Town
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Runmin Wei
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Antonio Rios
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | | | - Melanie Heinlein
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Amy S Chuong
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Shuangyi Cai
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Cherry Sakura Lu
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
- Faculty of Environment and Information Studies, Keio University, Tokyo, Japan
| | - Paula Coelho
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Monika Mis
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Cemre Celen
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Noelyn Kljavin
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Jian Jiang
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - David Richmond
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Pratiksha Thakore
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Elia Benito-Gutiérrez
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | | | - Jose Sergio Hleap
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
- Bioinformatics Department, ProCogia, Toronto, Ontario, Canada
| | - Nobuhiko Kayagaki
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | | | - Lisa McGinnis
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Bo Li
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Avtar Singh
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Levi Garraway
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Orit Rozenblatt-Rosen
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA
| | - Aviv Regev
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA.
| | - Eric Lubeck
- Genentech Research and Early Development, Genentech, Inc., South San Francisco, CA, USA.
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2
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Wang Z, Santa-Maria CA, Popel AS, Sulam J. Bi-level Graph Learning Unveils Prognosis-Relevant Tumor Microenvironment Patterns in Breast Multiplexed Digital Pathology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590118. [PMID: 38712207 PMCID: PMC11071347 DOI: 10.1101/2024.04.22.590118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
The tumor microenvironment is widely recognized for its central role in driving cancer progression and influencing prognostic outcomes. There have been increasing efforts dedicated to characterizing this complex and heterogeneous environment, including developing potential prognostic tools by leveraging modern deep learning methods. However, the identification of generalizable data-driven biomarkers has been limited, in part due to the inability to interpret the complex, black-box predictions made by these models. In this study, we introduce a data-driven yet interpretable approach for identifying patterns of cell organizations in the tumor microenvironment that are associated with patient prognoses. Our methodology relies on the construction of a bi-level graph model: (i) a cellular graph, which models the intricate tumor microenvironment, and (ii) a population graph that captures inter-patient similarities, given their respective cellular graphs, by means of a soft Weisfeiler-Lehman subtree kernel. This systematic integration of information across different scales enables us to identify patient subgroups exhibiting unique prognoses while unveiling tumor microenvironment patterns that characterize them. We demonstrate our approach in a cohort of breast cancer patients and show that the identified tumor microenvironment patterns result in a risk stratification system that provides new complementary information with respect to standard stratification systems. Our results, which are validated in two independent cohorts, allow for new insights into the prognostic implications of the breast tumor microenvironment. This methodology could be applied to other cancer types more generally, providing insights into the cellular patterns of organization associated with different outcomes.
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3
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Zhu E, Xie Q, Huang X, Zhang Z. Application of spatial omics in gastric cancer. Pathol Res Pract 2024; 262:155503. [PMID: 39128411 DOI: 10.1016/j.prp.2024.155503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 07/25/2024] [Accepted: 07/27/2024] [Indexed: 08/13/2024]
Abstract
Gastric cancer (GC), a globally prevalent and lethal malignancy, continues to be a key research focus. However, due to its considerable heterogeneity and complex pathogenesis, the treatment and diagnosis of gastric cancer still face significant challenges. With the rapid development of spatial omics technology, which provides insights into the spatial information within tumor tissues, it has emerged as a significant tool in gastric cancer research. This technology affords new insights into the pathology and molecular biology of gastric cancer for scientists. This review discusses recent advances in spatial omics technology for gastric cancer research, highlighting its applications in the tumor microenvironment (TME), tumor heterogeneity, tumor genesis and development mechanisms, and the identification of potential biomarkers and therapeutic targets. Moreover, this article highlights spatial omics' potential in precision medicine and summarizes existing challenges and future directions. It anticipates spatial omics' continuing impact on gastric cancer research, aiming to improve diagnostic and therapeutic approaches for patients. With this review, we aim to offer a comprehensive overview to scientists and clinicians in gastric cancer research, motivating further exploration and utilization of spatial omics technology. Our goal is to improve patient outcomes, including survival rates and quality of life.
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Affiliation(s)
- Erran Zhu
- Department of Clinical Medicine, Grade 20, Hengyang Medical College, University of South China, Hengyang, Hunan, 421001, China
| | - Qi Xie
- Department of Clinical Medicine, Grade 20, Hengyang Medical College, University of South China, Hengyang, Hunan, 421001, China
| | - Xinqi Huang
- Excellent Class, Clinical Medicine, Grade 20, Hengyang Medical College, University of South China, Hengyang, Hunan, 421001, China
| | - Zhiwei Zhang
- Cancer Research Institute of Hengyang Medical College, University of South China; Key Laboratory of Cancer Cellular and Molecular Pathology of Hunan; Department of Pathology, Department of Pathology of Hengyang Medical College, University of South China; The First Affiliated Hospital of University of South China, China.
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4
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Calvanese AL, Cecconi V, Stäheli S, Schnepf D, Nater M, Pereira P, Gschwend J, Heikenwälder M, Schneider C, Ludewig B, Silina K, van den Broek M. Sustained innate interferon is an essential inducer of tertiary lymphoid structures. Eur J Immunol 2024; 54:e2451207. [PMID: 38980268 DOI: 10.1002/eji.202451207] [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: 04/19/2024] [Revised: 06/25/2024] [Accepted: 06/26/2024] [Indexed: 07/10/2024]
Abstract
Tertiary lymphoid structures (TLS) resemble follicles of secondary lymphoid organs and develop in nonlymphoid tissues during inflammation and cancer. Which cell types and signals drive the development of TLS is largely unknown. To investigate early events of TLS development in the lungs, we repeatedly instilled p(I:C) plus ovalbumin (Ova) intranasally. This induced TLS ranging from lymphocytic aggregates to organized and functional structures containing germinal centers. We found that TLS development is independent of FAP+ fibroblasts, alveolar macrophages, or CCL19 but crucially depends on type I interferon (IFN-I). Mechanistically, IFN-I initiates two synergistic pathways that culminate in the development of TLS. On the one hand, IFN-I induces lymphotoxin (LT)α in lymphoid cells, which stimulate stromal cells to produce the B-cell-attracting chemokine CXCL13 through LTβR-signaling. On the other hand, IFN-I is sensed by stromal cells that produce the T-cell-attracting chemokines CXCL9, CXCL10 as well as CCL19 and CCL21 independently of LTβR. Consequently, B-cell aggregates develop within a week, whereas follicular dendritic cells and germinal centers appear after 3 weeks. Thus, sustained production of IFN-I together with an antigen is essential for the induction of functional TLS in the lungs.
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Affiliation(s)
| | - Virginia Cecconi
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
| | - Severin Stäheli
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
| | - Daniel Schnepf
- Institute of Virology, Medical Center University of Freiburg, Freiburg im Breisgau, Germany
| | - Marc Nater
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
| | - Paulo Pereira
- Institute of Experimental Immunology, University of Zurich, Zurich, Switzerland
| | - Julia Gschwend
- Institute of Physiology, University of Zurich, Zurich, Switzerland
| | - Mathias Heikenwälder
- Division of Chronic Inflammation and Cancer, German Cancer Research Center Heidelberg (DKFZ), Heidelberg, Germany
- M3 Research Institute, Eberhard Karls University Tübingen, Tübingen, Germany
| | | | - Burkhard Ludewig
- Institute of Immunobiology, Medical Research Center, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Karina Silina
- Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biosciences, ETH Zurich, Zurich, Switzerland
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5
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Wang J, Alhaskawi A, Dong Y, Tian T, Abdalbary SA, Lu H. Advances in spatial multi-omics in tumors. TUMORI JOURNAL 2024; 110:327-339. [PMID: 39185632 DOI: 10.1177/03008916241271458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Single-cell techniques have convincingly demonstrated that tumor tissue usually contains multiple genetically defined cell subclones with different gene mutation sets as well as various transcriptional profiles, but the spatial heterogeneity of the microenvironment and the macrobiological characteristics of the tumor ecosystem have not been described. For the past few years, spatial multi-omics technologies have revealed the cellular interactions, microenvironment, and even systemic tumor-host interactions in the tumor ecosystem at the spatial level, which can not only improve classical therapies such as surgery, radiotherapy, and chemotherapy but also promote the development of emerging targeted therapies in immunotherapy. Here, we review some emerging spatial omics techniques in cancer research and therapeutic applications and propose prospects for their future development.
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Affiliation(s)
- Junyan Wang
- The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Ahmad Alhaskawi
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yanzhao Dong
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Tu Tian
- Department of Plastic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Sahar Ahmed Abdalbary
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
- Department of Orthopedic Physical Therapy, Faculty of Physical Therapy, Nahda University in Beni Suef, Beni Suef, Egypt
| | - Hui Lu
- The First Affiliated Hospital, Zhejiang University, Hangzhou, China
- Department of Orthopedics, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
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6
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Faupel-Badger J, Kohaar I, Bahl M, Chan AT, Campbell JD, Ding L, De Marzo AM, Maitra A, Merrick DT, Hawk ET, Wistuba II, Ghobrial IM, Lippman SM, Lu KH, Lawler M, Kay NE, Tlsty TD, Rebbeck TR, Srivastava S. Defining precancer: a grand challenge for the cancer community. Nat Rev Cancer 2024:10.1038/s41568-024-00744-0. [PMID: 39354069 DOI: 10.1038/s41568-024-00744-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/16/2024] [Indexed: 10/03/2024]
Abstract
The term 'precancer' typically refers to an early stage of neoplastic development that is distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting in abnormal cells that are at least partially self-sustaining and function outside of normal cellular cues that constrain cell proliferation and survival. Although such cells are often histologically distinct from both the corresponding normal and invasive cancer cells of the same tissue origin, defining precancer remains a challenge for both the research and clinical communities. Once sufficient molecular and phenotypic changes have occurred in the precancer, the tissue is identified as a 'cancer' by a histopathologist. While even diagnosing cancer can at times be challenging, the determination of invasive cancer is generally less ambiguous and suggests a high likelihood of and potential for metastatic disease. The 'hallmarks of cancer' set out the fundamental organizing principles of malignant transformation but exactly how many of these hallmarks and in what configuration they define precancer has not been clearly and consistently determined. In this Expert Recommendation, we provide a starting point for a conceptual framework for defining precancer, which is based on molecular, pathological, clinical and epidemiological criteria, with the goal of advancing our understanding of the initial changes that occur and opportunities to intervene at the earliest possible time point.
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Affiliation(s)
| | - Indu Kohaar
- Division of Cancer Prevention, National Cancer Institute, NIH, Rockville, MD, USA
| | - Manisha Bahl
- Division of Breast Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew T Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Joshua D Campbell
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Li Ding
- Department of Medicine and Genetics, McDonnell Genome Institute, and Siteman Cancer Center, Washington University in St Louis, Saint Louis, MO, USA
| | - Angelo M De Marzo
- Department of Pathology, Urology and Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anirban Maitra
- Department of Translational Molecular Pathology, Sheikh Ahmed Center for Pancreatic Cancer Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Daniel T Merrick
- Division of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ernest T Hawk
- Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Irene M Ghobrial
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Scott M Lippman
- Department of Medicine, University of California, La Jolla, San Diego, CA, USA
| | - Karen H Lu
- Department of Gynecological Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Mark Lawler
- Patrick G Johnson Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Neil E Kay
- Division of Hematology, Mayo Clinic, Rochester, MN, USA
| | - Thea D Tlsty
- Department of Medicine and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Timothy R Rebbeck
- Dana-Farber Cancer Institute and Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Sudhir Srivastava
- Division of Cancer Prevention, National Cancer Institute, NIH, Rockville, MD, USA.
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7
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Monasterio G, Morales RA, Bejarano DA, Abalo XM, Fransson J, Larsson L, Schlitzer A, Lundeberg J, Das S, Villablanca EJ. A versatile tissue-rolling technique for spatial-omics analyses of the entire murine gastrointestinal tract. Nat Protoc 2024; 19:3085-3137. [PMID: 38906985 DOI: 10.1038/s41596-024-01001-2] [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: 04/05/2023] [Accepted: 02/19/2024] [Indexed: 06/23/2024]
Abstract
Tissues are dynamic and complex biological systems composed of specialized cell types that interact with each other for proper biological function. To comprehensively characterize and understand the cell circuitry underlying biological processes within tissues, it is crucial to preserve their spatial information. Here we report a simple mounting technique to maximize the area of the tissue to be analyzed, encompassing the whole length of the murine gastrointestinal (GI) tract, from mouth to rectum. Using this method, analysis of the whole murine GI tract can be performed in a single slide not only by means of histological staining, immunohistochemistry and in situ hybridization but also by multiplexed antibody staining and spatial transcriptomic approaches. We demonstrate the utility of our method in generating a comprehensive gene and protein expression profile of the whole GI tract by combining the versatile tissue-rolling technique with a cutting-edge transcriptomics method (Visium) and two cutting-edge proteomics methods (ChipCytometry and CODEX-PhenoCycler) in a systematic and easy-to-follow step-by-step procedure. The entire process, including tissue rolling, processing and sectioning, can be achieved within 2-3 d for all three methods. For Visium spatial transcriptomics, an additional 2 d are needed, whereas for spatial proteomics assays (ChipCytometry and CODEX-PhenoCycler), another 3-4 d might be considered. The whole process can be accomplished by researchers with skills in performing murine surgery, and standard histological and molecular biology methods.
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Affiliation(s)
- Gustavo Monasterio
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and University Hospital, Stockholm, Sweden
- Center of Molecular Medicine, Stockholm, Sweden
| | - Rodrigo A Morales
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and University Hospital, Stockholm, Sweden
- Center of Molecular Medicine, Stockholm, Sweden
| | - David A Bejarano
- Quantitative Systems Biology, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany
| | - Xesús M Abalo
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Jennifer Fransson
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and University Hospital, Stockholm, Sweden
- Center of Molecular Medicine, Stockholm, Sweden
| | - Ludvig Larsson
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Andreas Schlitzer
- Quantitative Systems Biology, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Srustidhar Das
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and University Hospital, Stockholm, Sweden.
- Center of Molecular Medicine, Stockholm, Sweden.
| | - Eduardo J Villablanca
- Division of Immunology and Allergy, Department of Medicine Solna, Karolinska Institute and University Hospital, Stockholm, Sweden.
- Center of Molecular Medicine, Stockholm, Sweden.
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8
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Lacinski RA, Dziadowicz SA, Melemai VK, Fitzpatrick B, Pisquiy JJ, Heim T, Lohse I, Schoedel KE, Llosa NJ, Weiss KR, Lindsey BA. Spatial multiplexed immunofluorescence analysis reveals coordinated cellular networks associated with overall survival in metastatic osteosarcoma. Bone Res 2024; 12:55. [PMID: 39333065 PMCID: PMC11436896 DOI: 10.1038/s41413-024-00359-z] [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: 02/05/2024] [Revised: 06/16/2024] [Accepted: 07/18/2024] [Indexed: 09/29/2024] Open
Abstract
Patients diagnosed with advanced osteosarcoma, often in the form of lung metastases, have abysmal five-year overall survival rates. The complexity of the osteosarcoma immune tumor microenvironment has been implicated in clinical trial failures of various immunotherapies. The purpose of this exploratory study was to spatially characterize the immune tumor microenvironment of metastatic osteosarcoma lung specimens. Knowledge of the coordinating cellular networks within these tissues could then lead to improved outcomes when utilizing immunotherapy for treatment of this disease. Importantly, various cell types, interactions, and cellular neighborhoods were associated with five-year survival status. Of note, increases in cellular interactions between T lymphocytes, positive for programmed cell death protein 1, and myeloid-derived suppressor cells were observed in the 5-year deceased cohort. Additionally, cellular neighborhood analysis identified an Immune-Cold Parenchyma cellular neighborhood, also associated with worse 5-year survival. Finally, the Osteosarcoma Spatial Score, which approximates effector immune activity in the immune tumor microenvironment through the spatial proximity of immune and tumor cells, was increased within 5-year survivors, suggesting improved effector signaling in this patient cohort. Ultimately, these data represent a robust spatial multiplexed immunofluorescence analysis of the metastatic osteosarcoma immune tumor microenvironment. Various communication networks, and their association with survival, were described. In the future, identification of these networks may suggest the use of specific, combinatory immunotherapeutic strategies for improved anti-tumor immune responses and outcomes in osteosarcoma.
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Affiliation(s)
- Ryan A Lacinski
- Department of Orthopaedics, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
- Cancer Institute, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
| | - Sebastian A Dziadowicz
- Department of Microbiology, Immunology and Cell Biology, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
- Bioinformatics Core, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
| | - Vincent K Melemai
- Department of Orthopaedics, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
| | - Brody Fitzpatrick
- Department of Orthopaedics, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
| | - John J Pisquiy
- Department of Orthopaedics, West Virginia University School of Medicine, Morgantown, WV, 26506, USA
| | - Tanya Heim
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, 15213, USA
| | - Ines Lohse
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, 15213, USA
| | - Karen E Schoedel
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, 15213, USA
| | - Nicolas J Llosa
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Kurt R Weiss
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, 15213, USA
| | - Brock A Lindsey
- Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
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9
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Keller MS, Gold I, McCallum C, Manz T, Kharchenko PV, Gehlenborg N. Vitessce: integrative visualization of multimodal and spatially resolved single-cell data. Nat Methods 2024:10.1038/s41592-024-02436-x. [PMID: 39333268 DOI: 10.1038/s41592-024-02436-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 08/16/2024] [Indexed: 09/29/2024]
Abstract
Multiomics technologies with single-cell and spatial resolution make it possible to measure thousands of features across millions of cells. However, visual analysis of high-dimensional transcriptomic, proteomic, genome-mapped and imaging data types simultaneously remains a challenge. Here we describe Vitessce, an interactive web-based visualization framework for exploration of multimodal and spatially resolved single-cell data. We demonstrate integrative visualization of millions of data points, including cell-type annotations, gene expression quantities, spatially resolved transcripts and cell segmentations, across multiple coordinated views. The open-source software is available at http://vitessce.io .
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Affiliation(s)
- Mark S Keller
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Ilan Gold
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Chuck McCallum
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Trevor Manz
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Altos Labs, San Diego, CA, USA
| | - Nils Gehlenborg
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
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10
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Bai Z, Zhang D, Gao Y, Tao B, Zhang D, Bao S, Enninful A, Wang Y, Li H, Su G, Tian X, Zhang N, Xiao Y, Liu Y, Gerstein M, Li M, Xing Y, Lu J, Xu ML, Fan R. Spatially exploring RNA biology in archival formalin-fixed paraffin-embedded tissues. Cell 2024:S0092-8674(24)01019-5. [PMID: 39353436 DOI: 10.1016/j.cell.2024.09.001] [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: 02/02/2024] [Revised: 07/29/2024] [Accepted: 09/03/2024] [Indexed: 10/04/2024]
Abstract
The capability to spatially explore RNA biology in formalin-fixed paraffin-embedded (FFPE) tissues holds transformative potential for histopathology research. Here, we present pathology-compatible deterministic barcoding in tissue (Patho-DBiT) by combining in situ polyadenylation and computational innovation for spatial whole transcriptome sequencing, tailored to probe the diverse RNA species in clinically archived FFPE samples. It permits spatial co-profiling of gene expression and RNA processing, unveiling region-specific splicing isoforms, and high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for 5 years. Furthermore, genome-wide single-nucleotide RNA variants can be captured to distinguish malignant subclones from non-malignant cells in human lymphomas. Patho-DBiT also maps microRNA regulatory networks and RNA splicing dynamics, decoding their roles in spatial tumorigenesis. Single-cell level Patho-DBiT dissects the spatiotemporal cellular dynamics driving tumor clonal architecture and progression. Patho-DBiT stands poised as a valuable platform to unravel rich RNA biology in FFPE tissues to aid in clinical pathology evaluation.
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Affiliation(s)
- Zhiliang Bai
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.
| | - Dingyao Zhang
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Yan Gao
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Bo Tao
- Department of Pathology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Daiwei Zhang
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shuozhen Bao
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Archibald Enninful
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Yadong Wang
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Haikuo Li
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Graham Su
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Xiaolong Tian
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Ningning Zhang
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Yang Xiao
- Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
| | - Yang Liu
- Department of Pathology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Mingyao Li
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Yi Xing
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Jun Lu
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA; Yale Stem Cell Center and Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06520, USA.
| | - Mina L Xu
- Department of Pathology, Yale University School of Medicine, New Haven, CT 06520, USA.
| | - Rong Fan
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Department of Pathology, Yale University School of Medicine, New Haven, CT 06520, USA; Yale Stem Cell Center and Yale Cancer Center, Yale University School of Medicine, New Haven, CT 06520, USA; Human and Translational Immunology, Yale University School of Medicine, New Haven, CT 06520, USA.
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11
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Donovan ML, Jhaveri N, Ma N, Cheikh BB, DeRosa J, Mihani R, Berrell N, Suen JY, Monkman J, Fraser JF, Kulasinghe A. Protocol for high-plex, whole-slide imaging of human formalin-fixed paraffin-embedded tissue using PhenoCycler-Fusion. STAR Protoc 2024; 5:103226. [PMID: 39031553 PMCID: PMC11314888 DOI: 10.1016/j.xpro.2024.103226] [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: 03/12/2024] [Revised: 05/03/2024] [Accepted: 07/05/2024] [Indexed: 07/22/2024] Open
Abstract
Single-cell spatial analysis of proteins is rapidly becoming increasingly important in revealing biological insights. Here, we present a protocol for automated high-plex multi-slide immunofluorescence staining and imaging of human head and neck cancer formalin-fixed paraffin-embedded (FFPE) sections using PhenoCycler-Fusion 2.0 technology. We describe steps for preparing human head and neck cancer FFPE tissues, staining with a panel of immunophenotyping markers, and Flow Cell assembly. We then detail procedures for setting up for a PhenoCycler-Fusion run, post-run Flow Cell removal, and downstream analyses. For complete details on the use and execution of this protocol, please refer to Jhaveri et al.1.
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Affiliation(s)
- Meg L Donovan
- Queensland Spatial Biology Centre, Wesley Research Institute, Level 8 East Wing, The Wesley Hospital, Auchenflower, QLD 4066, Australia; Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Niyati Jhaveri
- Akoya Biosciences, The Spatial Biology Company, Marlborough, MA, USA
| | - Ning Ma
- Akoya Biosciences, The Spatial Biology Company, Marlborough, MA, USA
| | - Bassem Ben Cheikh
- Akoya Biosciences, The Spatial Biology Company, Marlborough, MA, USA
| | - James DeRosa
- Akoya Biosciences, The Spatial Biology Company, Marlborough, MA, USA
| | - Ritu Mihani
- Akoya Biosciences, The Spatial Biology Company, Marlborough, MA, USA
| | - Naomi Berrell
- Queensland Spatial Biology Centre, Wesley Research Institute, Level 8 East Wing, The Wesley Hospital, Auchenflower, QLD 4066, Australia; Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - Jacky Y Suen
- Critical Care Research Group, The Prince Charles Hospital, Brisbane, QLD 4032, Australia; Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
| | - James Monkman
- Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia
| | - John F Fraser
- Queensland Spatial Biology Centre, Wesley Research Institute, Level 8 East Wing, The Wesley Hospital, Auchenflower, QLD 4066, Australia; Critical Care Research Group, The Prince Charles Hospital, Brisbane, QLD 4032, Australia; Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Arutha Kulasinghe
- Queensland Spatial Biology Centre, Wesley Research Institute, Level 8 East Wing, The Wesley Hospital, Auchenflower, QLD 4066, Australia; Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4102, Australia.
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12
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Gong D, Arbesfeld-Qiu JM, Perrault E, Bae JW, Hwang WL. Spatial oncology: Translating contextual biology to the clinic. Cancer Cell 2024:S1535-6108(24)00349-0. [PMID: 39366372 DOI: 10.1016/j.ccell.2024.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 08/01/2024] [Accepted: 09/06/2024] [Indexed: 10/06/2024]
Abstract
Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.
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Affiliation(s)
- Dennis Gong
- Center for Systems Biology, Department of Radiation Oncology, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jeanna M Arbesfeld-Qiu
- Center for Systems Biology, Department of Radiation Oncology, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard University, Graduate School of Arts and Sciences, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Ella Perrault
- Center for Systems Biology, Department of Radiation Oncology, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard University, Graduate School of Arts and Sciences, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Jung Woo Bae
- Center for Systems Biology, Department of Radiation Oncology, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - William L Hwang
- Center for Systems Biology, Department of Radiation Oncology, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard University, Graduate School of Arts and Sciences, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA.
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13
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Wu M, Tao H, Xu T, Zheng X, Wen C, Wang G, Peng Y, Dai Y. Spatial proteomics: unveiling the multidimensional landscape of protein localization in human diseases. Proteome Sci 2024; 22:7. [PMID: 39304896 DOI: 10.1186/s12953-024-00231-2] [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: 04/29/2024] [Accepted: 09/01/2024] [Indexed: 09/22/2024] Open
Abstract
Spatial proteomics is a multidimensional technique that studies the spatial distribution and function of proteins within cells or tissues across both spatial and temporal dimensions. This field multidimensionally reveals the complex structure of the human proteome, including the characteristics of protein spatial distribution, dynamic protein translocation, and protein interaction networks. Recently, as a crucial method for studying protein spatial localization, spatial proteomics has been applied in the clinical investigation of various diseases. This review summarizes the fundamental concepts and characteristics of tissue-level spatial proteomics, its research progress in common human diseases such as cancer, neurological disorders, cardiovascular diseases, autoimmune diseases, and anticipates its future development trends. The aim is to highlight the significant impact of spatial proteomics on understanding disease pathogenesis, advancing diagnostic methods, and developing potential therapeutic targets in clinical research.
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Affiliation(s)
- Mengyao Wu
- School of Medicine, Anhui University of Science & Technology, Huainan, China
| | - Huihui Tao
- School of Medicine, Anhui University of Science & Technology, Huainan, China.
- Key Laboratory of Industrial Dust Deep Reduction and Occupational Health and Safety of Anhui Higher Education Institutes, Huainan, China.
- Anhui Province Engineering Laboratory of Occupational Health and Safety, Huainan, China.
| | - Tiantian Xu
- School of Medicine, Anhui University of Science & Technology, Huainan, China
| | - Xuejia Zheng
- The First Hospital of Anhui University of Science and Technology, Huainan, China
| | - Chunmei Wen
- School of Medicine, Anhui University of Science & Technology, Huainan, China
| | - Guoying Wang
- School of Medicine, Anhui University of Science & Technology, Huainan, China
| | - Yali Peng
- School of Medicine, Anhui University of Science & Technology, Huainan, China
| | - Yong Dai
- School of Medicine, Anhui University of Science & Technology, Huainan, China
- The First Hospital of Anhui University of Science and Technology, Huainan, China
- Joint Research Center for Occupational Medicine and Health of IHM, Anhui University of Science and Technology, Huainan, China
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14
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Lemaitre L, Adeniji N, Suresh A, Reguram R, Zhang J, Park J, Reddy A, Trevino AE, Mayer AT, Deutzmann A, Hansen AS, Tong L, Arjunan V, Kambham N, Visser BC, Dua MM, Bonham CA, Kothary N, D'Angio HB, Preska R, Rosen Y, Zou J, Charu V, Felsher DW, Dhanasekaran R. Spatial analysis reveals targetable macrophage-mediated mechanisms of immune evasion in hepatocellular carcinoma minimal residual disease. NATURE CANCER 2024:10.1038/s43018-024-00828-8. [PMID: 39304772 DOI: 10.1038/s43018-024-00828-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 08/14/2024] [Indexed: 09/22/2024]
Abstract
Hepatocellular carcinoma (HCC) frequently recurs from minimal residual disease (MRD), which persists after therapy. Here, we identified mechanisms of persistence of residual tumor cells using post-chemoembolization human HCC (n = 108 patients, 1.07 million cells) and a transgenic mouse model of MRD. Through single-cell high-plex cytometric imaging, we identified a spatial neighborhood within which PD-L1 + M2-like macrophages interact with stem-like tumor cells, correlating with CD8+ T cell exhaustion and poor survival. Further, through spatial transcriptomics of residual HCC, we showed that macrophage-derived TGFβ1 mediates the persistence of stem-like tumor cells. Last, we demonstrate that combined blockade of Pdl1 and Tgfβ excluded immunosuppressive macrophages, recruited activated CD8+ T cells and eliminated residual stem-like tumor cells in two mouse models: a transgenic model of MRD and a syngeneic orthotopic model of doxorubicin-resistant HCC. Thus, our spatial analyses reveal that PD-L1+ macrophages sustain MRD by activating the TGFβ pathway in stem-like cancer cells and targeting this interaction may prevent HCC recurrence from MRD.
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Affiliation(s)
- Lea Lemaitre
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Nia Adeniji
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Akanksha Suresh
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Reshma Reguram
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Josephine Zhang
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Jangho Park
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Amit Reddy
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | | | | | - Anja Deutzmann
- Division of Oncology, Departments of Medicine and Pathology, Stanford University, Stanford, CA, USA
| | - Aida S Hansen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Ling Tong
- Division of Oncology, Departments of Medicine and Pathology, Stanford University, Stanford, CA, USA
| | - Vinodhini Arjunan
- Division of Gastroenterology and Hepatology, Stanford University, Stanford, CA, USA
| | - Neeraja Kambham
- Department of Pathology, Stanford University, Stanford, CA, USA
| | | | - Monica M Dua
- Department of Surgery, Stanford University, Stanford, CA, USA
| | - C Andrew Bonham
- Department of Surgery, Stanford University, Stanford, CA, USA
| | - Nishita Kothary
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | | | - Yanay Rosen
- Department of Biomedical Data Science and Computer Science, Stanford University, Stanford, CA, USA
| | - James Zou
- Department of Biomedical Data Science and Computer Science, Stanford University, Stanford, CA, USA
| | - Vivek Charu
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Dean W Felsher
- Division of Oncology, Departments of Medicine and Pathology, Stanford University, Stanford, CA, USA.
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15
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Xiong X, Wang X, Liu CC, Shao ZM, Yu KD. Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era. Biomark Res 2024; 12:107. [PMID: 39294728 PMCID: PMC11411917 DOI: 10.1186/s40364-024-00654-1] [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: 06/28/2024] [Accepted: 09/10/2024] [Indexed: 09/21/2024] Open
Abstract
As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.
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Affiliation(s)
- Xin Xiong
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Xin Wang
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Cui-Cui Liu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Zhi-Ming Shao
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Ke-Da Yu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
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16
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Sun H, Yu S, Casals AM, Bäckström A, Lu Y, Lindskog C, Lundberg E, Murphy RF. Flexible and robust cell type annotation for highly multiplexed tissue images. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.12.612510. [PMID: 39345395 PMCID: PMC11429614 DOI: 10.1101/2024.09.12.612510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Identifying cell types in highly multiplexed images is essential for understanding tissue spatial organization. Current cell type annotation methods often rely on extensive reference images and manual adjustments. In this work, we present a tool, Robust Image-Based Cell Annotator (RIBCA), that enables accurate, automated, unbiased, and fine-grained cell type annotation for images with a wide range of antibody panels, without requiring additional model training or human intervention. Our tool has successfully annotated over 1 million cells, revealing the spatial organization of various cell types across more than 40 different human tissues. It is open-source and features a modular design, allowing for easy extension to additional cell types.
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17
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Ono-Minagi H, Nohno T, Takabatake K, Tanaka T, Katsuyama T, Miyawaki K, Wada J, Ibaragi S, Iida S, Yoshino T, Nagatsuka H, Sakai T, Ohuchi H. Histological differences related to autophagy in the minor salivary gland between primary and secondary types of Sjögren's syndrome. BMC Oral Health 2024; 24:1099. [PMID: 39285388 PMCID: PMC11406829 DOI: 10.1186/s12903-024-04869-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Accepted: 09/05/2024] [Indexed: 09/19/2024] Open
Abstract
Some forms of Sjögren's syndrome (SS) follow a clinical course accompanied by systemic symptoms caused by lymphocyte infiltration and proliferation in the liver, kidneys, and other organs. To better understand the clinical outcomes of SS, here we used minor salivary gland tissues from patients and examine their molecular, biological, and pathological characteristics. A retrospective study was performed, combining clinical data and formalin-fixed paraffin-embedded (FFPE) samples from female patients over 60 years of age who underwent biopsies at Okayama University Hospital. We employed direct digital RNA counting with nCounter® and multiplex immunofluorescence analysis with a PhenoCycler™ on the labial gland biopsies. We compared FFPE samples from SS patients who presented with other connective tissue diseases (secondary SS) with those from stable SS patients with symptoms restricted to the exocrine glands (primary SS). Secondary SS tissues showed enhanced epithelial damage and lymphocytic infiltration accompanied by elevated expression of autophagy marker genes in the immune cells of the labial glands. The close intercellular distance between helper T cells and B cells positive for autophagy-associated molecules suggests accelerated autophagy in these lymphocytes and potential B cell activation by helper T cells. These findings indicate that examination of FFPE samples from labial gland biopsies can be an effective tool for evaluating molecular histological differences between secondary and primary SS through multiplexed analysis of gene expression and tissue imaging.
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Affiliation(s)
- Hitomi Ono-Minagi
- Department of Cytology and Histology, Dentistry and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan.
- Division of Hospital Dentistry, Central Clinical Department, Okayama University Hospital, Okayama, Japan.
- Research Fellow of Japan Society for the Promotion of Science, Tokyo, Japan.
- Adeno-Associated Virus Biology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, United States of America.
| | - Tsutomu Nohno
- Department of Cytology and Histology, Okayama University Medical School, Okayama, Japan
| | - Kiyofumi Takabatake
- Department of Oral Pathology and Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Takehiro Tanaka
- Department of Pathology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Takayuki Katsuyama
- Department of Nephrology, Rheumatology, Endocrinology and Metabolism, Okayama University Hospital, Okayama, Japan
| | - Kohta Miyawaki
- Division of Precision Medicine, Kyushu University School of Medicine, Fukuoka, Japan
| | - Jun Wada
- Department of Nephrology, Rheumatology, Endocrinology and Metabolism, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Soichiro Ibaragi
- Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Seiji Iida
- Department of Oral and Maxillofacial Reconstructive Surgery, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Tadashi Yoshino
- Department of Pathology, Dentistry and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan
| | - Hitoshi Nagatsuka
- Department of Oral Pathology and Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Takayoshi Sakai
- Department of Rehabilitation for Orofacial Disorders, Osaka University Graduate School of Dentistry, Osaka, Japan
| | - Hideyo Ohuchi
- Department of Cytology and Histology, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan.
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18
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Liang W, Zhu Z, Xu D, Wang P, Guo F, Xiao H, Hou C, Xue J, Zhi X, Ran R. The burgeoning spatial multi-omics in human gastrointestinal cancers. PeerJ 2024; 12:e17860. [PMID: 39285924 PMCID: PMC11404479 DOI: 10.7717/peerj.17860] [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: 03/27/2024] [Accepted: 07/14/2024] [Indexed: 09/19/2024] Open
Abstract
The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.
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Affiliation(s)
- Weizheng Liang
- Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
| | - Zhenpeng Zhu
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Dandan Xu
- Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
| | - Peng Wang
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Fei Guo
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
| | - Haoshan Xiao
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Chenyang Hou
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
- Hebei North University, Zhangjiakou, Hebei Province, China
| | - Jun Xue
- Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China
| | - Xuejun Zhi
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
| | - Rensen Ran
- Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China
- Department of Chemical Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
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19
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Eremina OE, Vazquez C, Larson KN, Mouchawar A, Fernando A, Zavaleta C. The evolution of immune profiling: will there be a role for nanoparticles? NANOSCALE HORIZONS 2024. [PMID: 39254004 DOI: 10.1039/d4nh00279b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Immune profiling provides insights into the functioning of the immune system, including the distribution, abundance, and activity of immune cells. This understanding is essential for deciphering how the immune system responds to pathogens, vaccines, tumors, and other stimuli. Analyzing diverse immune cell types facilitates the development of personalized medicine approaches by characterizing individual variations in immune responses. With detailed immune profiles, clinicians can tailor treatment strategies to the specific immune status and needs of each patient, maximizing therapeutic efficacy while minimizing adverse effects. In this review, we discuss the evolution of immune profiling, from interrogating bulk cell samples in solution to evaluating the spatially-rich molecular profiles across intact preserved tissue sections. We also review various multiplexed imaging platforms recently developed, based on immunofluorescence and imaging mass spectrometry, and their impact on the field of immune profiling. Identifying and localizing various immune cell types across a patient's sample has already provided important insights into understanding disease progression, the development of novel targeted therapies, and predicting treatment response. We also offer a new perspective by highlighting the unprecedented potential of nanoparticles (NPs) that can open new horizons in immune profiling. NPs are known to provide enhanced detection sensitivity, targeting specificity, biocompatibility, stability, multimodal imaging features, and multiplexing capabilities. Therefore, we summarize the recent developments and advantages of NPs, which can contribute to advancing our understanding of immune function to facilitate precision medicine. Overall, NPs have the potential to offer a versatile and robust approach to profile the immune system with improved efficiency and multiplexed imaging power.
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Affiliation(s)
- Olga E Eremina
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
- Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, California 90089, USA
| | - Celine Vazquez
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
- Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, California 90089, USA
| | - Kimberly N Larson
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
- Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, California 90089, USA
| | - Anthony Mouchawar
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
- Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, California 90089, USA
| | - Augusta Fernando
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
- Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, California 90089, USA
| | - Cristina Zavaleta
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California 90089, USA.
- Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, California 90089, USA
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20
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Smith D, Eichinger A, Rech A, Wang J, Esteva E, Seyedian A, Yang X, Zhang M, Martinez D, Tan K, Luo M, Park C, Reizis B, Pillai V. Spatial and Single Cell Mapping of Castleman Disease Reveals Key Stromal Cell Types and Cytokine Pathways. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.09.609717. [PMID: 39314418 PMCID: PMC11419132 DOI: 10.1101/2024.09.09.609717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Castleman disease (CD) is inflammatory lymphoproliferative disorder of unclear etiology. To determine the cellular and molecular basis of CD, we analyzed the spatial proteome of 4,485,009 single cells, transcriptome of 50,117 single nuclei, immune repertoire of 8187 single nuclei, and pathogenic mutations in Unicentric CD, idiopathic Multicentric CD, HHV8-associated MCD, and reactive lymph nodes. CD was characterized by increased non-lymphoid and stromal cells that formed unique microenvironments where they interacted with lymphoid cells. Interaction of activated follicular dendritic cell (FDC) cytoplasmic meshworks with mantle zone B cells was associated with B cell activation and differentiation. VEGF, IL-6, MAPK, and extracellular matrix pathways were elevated in stromal cells of CD. CXCL13+ FDCs, PDGFRA+ T-zone reticular cells (TRC), and ACTA2-positive perivascular reticular cells (PRC) were identified as the predominant source of increased VEGF expression and IL-6 signaling in CD. VEGF expression by FDCs was associated with peri-follicular neovascularization. FDC, TRC and PRC of CD activated JAK-STAT, TGFβ, and MAPK pathways via ligand-receptor interactions involving collagen, integrins, complement components, and VEGF receptors. T, B and plasma cells were polyclonal but showed class-switched and somatically hypermutated IgG1+ plasma cells consistent with stromal cell-driven germinal center activation. In conclusion, our findings show that stromal cell activation and associated B-cell activation and differentiation, neovascularization and stromal remodeling underlie CD and suggest new targets for treatment.
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Affiliation(s)
- David Smith
- Center for Single Cell Biology, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA
| | - Anna Eichinger
- Department of Pathology, New York University Grossman School of Medicine, New York City, NY
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Andrew Rech
- Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia and the University of Pennsylvania, PA
| | - Julia Wang
- Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia and the University of Pennsylvania, PA
| | - Eduardo Esteva
- Department of Pathology, New York University Grossman School of Medicine, New York City, NY
| | - Arta Seyedian
- Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Xiaoxu Yang
- Center for Single Cell Biology, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA
| | - Mei Zhang
- Center for Single Cell Biology, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA
| | - Dan Martinez
- Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia and the University of Pennsylvania, PA
| | - Kai Tan
- Center for Single Cell Biology, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA
- Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA
| | - Minjie Luo
- Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia and the University of Pennsylvania, PA
| | - Christopher Park
- Department of Pathology, New York University Grossman School of Medicine, New York City, NY
| | - Boris Reizis
- Department of Pathology, New York University Grossman School of Medicine, New York City, NY
| | - Vinodh Pillai
- Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia and the University of Pennsylvania, PA
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21
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Zhou Z, Jiang Y, Sun Z, Zhang T, Feng W, Li G, Li R, Xing L. Virtual multiplexed immunofluorescence staining from non-antibody-stained fluorescence imaging for gastric cancer prognosis. EBioMedicine 2024; 107:105287. [PMID: 39154539 PMCID: PMC11378090 DOI: 10.1016/j.ebiom.2024.105287] [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: 01/29/2024] [Revised: 07/11/2024] [Accepted: 08/01/2024] [Indexed: 08/20/2024] Open
Abstract
BACKGROUND Multiplexed immunofluorescence (mIF) staining, such as CODEX and MIBI, holds significant clinical value for various fields, such as disease diagnosis, biological research, and drug development. However, these techniques are often hindered by high time and cost requirements. METHODS Here we present a Multimodal-Attention-based virtual mIF Staining (MAS) system that utilises a deep learning model to extract potential antibody-related features from dual-modal non-antibody-stained fluorescence imaging, specifically autofluorescence (AF) and DAPI imaging. The MAS system simultaneously generates predictions of mIF with multiple survival-associated biomarkers in gastric cancer using self- and multi-attention learning mechanisms. FINDINGS Experimental results with 180 pathological slides from 94 patients with gastric cancer demonstrate the efficiency and consistent performance of the MAS system in both cancer and noncancer gastric tissues. Furthermore, we showcase the prognostic accuracy of the virtual mIF images of seven gastric cancer related biomarkers, including CD3, CD20, FOXP3, PD1, CD8, CD163, and PD-L1, which is comparable to those obtained from the standard mIF staining. INTERPRETATION The MAS system rapidly generates reliable multiplexed staining, greatly reducing the cost of mIF and improving clinical workflow. FUNDING Stanford 2022 HAI Seed Grant; National Institutes of Health 1R01CA256890.
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Affiliation(s)
- Zixia Zhou
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
| | - Yuming Jiang
- Department of Radiation Oncology, Wake Forest University School of Medicine, Winston Salem, NC, 27109, USA.
| | - Zepang Sun
- Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical University, 510515, Guangzhou, China
| | - Taojun Zhang
- Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical University, 510515, Guangzhou, China
| | - Wanying Feng
- Department of Pathology, School of Basic Medical Sciences, Southern Medical University, 510515, Guangzhou, China
| | - Guoxin Li
- Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, Southern Medical University, 510515, Guangzhou, China
| | - Ruijiang Li
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
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22
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Chen J, Larsson L, Swarbrick A, Lundeberg J. Spatial landscapes of cancers: insights and opportunities. Nat Rev Clin Oncol 2024; 21:660-674. [PMID: 39043872 DOI: 10.1038/s41571-024-00926-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2024] [Indexed: 07/25/2024]
Abstract
Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.
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Affiliation(s)
- Julia Chen
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia
- Department of Medical Oncology, St George Hospital, Sydney, New South Wales, Australia
| | - Ludvig Larsson
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden.
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23
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Demangel C, Surace L. Host-pathogen interactions from a metabolic perspective: methods of investigation. Microbes Infect 2024; 26:105267. [PMID: 38007087 DOI: 10.1016/j.micinf.2023.105267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 10/21/2023] [Accepted: 11/21/2023] [Indexed: 11/27/2023]
Abstract
Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.
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Affiliation(s)
- Caroline Demangel
- Institut Pasteur, Université Paris Cité, Inserm U1224, Immunobiology and Therapy Unit, Paris, France
| | - Laura Surace
- Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital Bonn, University of Bonn, Bonn, Germany.
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24
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Wang Y, Liu X, Zeng Y, Saka S, Xie W, Goldaracena I, Kohman R, Yin P, Church G. Multiplexed in situ protein imaging using DNA-barcoded antibodies with extended hybridization chain reactions. Nucleic Acids Res 2024; 52:e71. [PMID: 38966983 PMCID: PMC11347153 DOI: 10.1093/nar/gkae592] [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: 07/25/2023] [Revised: 05/23/2024] [Accepted: 06/25/2024] [Indexed: 07/06/2024] Open
Abstract
Antibodies have long served as vital tools in biological and clinical laboratories for the specific detection of proteins. Conventional methods employ fluorophore or horseradish peroxidase-conjugated antibodies to detect signals. More recently, DNA-conjugated antibodies have emerged as a promising technology, capitalizing on the programmability and amplification capabilities of DNA to enable highly multiplexed and ultrasensitive protein detection. However, the nonspecific binding of DNA-conjugated antibodies has impeded the widespread adoption of this approach. Here, we present a novel DNA-conjugated antibody staining protocol that addresses these challenges and demonstrates superior performance in suppressing nonspecific signals compared to previously published protocols. We further extend the utility of DNA-conjugated antibodies for signal-amplified in situ protein imaging through the hybridization chain reaction (HCR) and design a novel HCR DNA pair to expand the HCR hairpin pool from the previously published 5 pairs to 13, allowing for flexible hairpin selection and higher multiplexing. Finally, we demonstrate highly multiplexed in situ protein imaging using these techniques in both cultured cells and tissue sections.
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Affiliation(s)
- Yu Wang
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of System Biology, Harvard Medical School, Boston, MA 02115, USA
- Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
| | - Xiaoyu Liu
- Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
| | - Yitian Zeng
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Sinem K Saka
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of System Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Wenxin Xie
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Isabel Goldaracena
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of System Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Richie E Kohman
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Peng Yin
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of System Biology, Harvard Medical School, Boston, MA 02115, USA
| | - George M Church
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
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25
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Huang J, Yuan C, Jiang J, Chen J, Badve SS, Gokmen-Polar Y, Segura RL, Yan X, Lazar A, Gao J, Epstein M, Wang L, Hu J. MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.24.609528. [PMID: 39253421 PMCID: PMC11383057 DOI: 10.1101/2024.08.24.609528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Multi-modal spatial omics data are invaluable for exploring complex cellular behaviors in diseases from both morphological and molecular perspectives. Current analytical methods primarily focus on clustering and classification, and do not adequately examine the relationship between cell morphology and molecular dynamics. Here, we present MorphLink, a framework designed to systematically identify disease-related morphological-molecular interplays. MorphLink has been evaluated across a wide array of datasets, showcasing its effectiveness in extracting and linking interpretable morphological features with various molecular measurements in multi-modal spatial omics analyses. These linkages provide a transparent depiction of cellular behaviors that drive transcriptomic heterogeneity and immune diversity across different regions within diseased tissues, such as cancer. Additionally, MorphLink is scalable and robust against cross-sample batch effects, making it an efficient method for integrative spatial omics data analysis across samples, cohorts, and modalities, and enhancing the interpretation of results for large-scale studies.
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26
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Border S, Ferreira RM, Lucarelli N, Manthey D, Kumar S, Paul A, Mimar S, Naglah A, Cheng YH, Barisoni L, Ray J, Strekalova Y, Rosenberg AZ, Tomaszewski JE, Hodgin JB, El-Achkar TM, Jain S, Eadon MT, Sarder P. FUSION: A web-based application for in-depth exploration of multi-omics data with brightfield histology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.09.602778. [PMID: 39026885 PMCID: PMC11257503 DOI: 10.1101/2024.07.09.602778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Spatial -OMICS technologies facilitate the interrogation of molecular profiles in the context of the underlying histopathology and tissue microenvironment. Paired analysis of histopathology and molecular data can provide pathologists with otherwise unobtainable insights into biological mechanisms. To connect the disparate molecular and histopathologic features into a single workspace, we developed FUSION (Functional Unit State IdentificatiON in WSIs [Whole Slide Images]), a web-based tool that provides users with a broad array of visualization and analytical tools including deep learning-based algorithms for in-depth interrogation of spatial -OMICS datasets and their associated high-resolution histology images. FUSION enables end-to-end analysis of functional tissue units (FTUs), automatically aggregating underlying molecular data to provide a histopathology-based medium for analyzing healthy and altered cell states and driving new discoveries using "pathomic" features. We demonstrate FUSION using 10x Visium spatial transcriptomics (ST) data from both formalin-fixed paraffin embedded (FFPE) and frozen prepared datasets consisting of healthy and diseased tissue. Through several use-cases, we demonstrate how users can identify spatial linkages between quantitative pathomics, qualitative image characteristics, and spatial --omics.
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Affiliation(s)
- Samuel Border
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
| | | | - Nicholas Lucarelli
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
| | | | - Suhas Kumar
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
| | - Anindya Paul
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
| | - Sayat Mimar
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
| | - Ahmed Naglah
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
| | - Ying-Hua Cheng
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Laura Barisoni
- Department of Pathology, Division of AI and Computational Pathology, Duke University, Durham, NC
- Department of Medicine, Division of Nephrology, Duke University, Durham, NC
| | - Jessica Ray
- Department of Health Outcomes & Biomedical Informatics, University of Florida, Gainesville, FL
| | - Yulia Strekalova
- College of Public Health and Health Professions, University of Florida, Gainesville, FL
| | - Avi Z Rosenberg
- Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD
| | - John E Tomaszewski
- Department of Pathology & Anatomical Sciences, Jacobs School of Medicine & Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY
| | | | - Tarek M El-Achkar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
- Indianapolis VA Medical Center, Indianapolis, IN
| | - Sanjay Jain
- Department of Medicine, Division of Nephrology, Washington University School of Medicine, St. Louis, MO
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Pinaki Sarder
- Department of Medicine - Section of Quantitative Health, University of Florida, Gainesville, FL
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27
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Hwang W, Raymond T, McPartland T, Jeong S, Evans CL. Fluorescence Lifetime Multiplexing (FLEX) for simultaneous high dimensional spatial biology in 3D. Commun Biol 2024; 7:1012. [PMID: 39154126 PMCID: PMC11330493 DOI: 10.1038/s42003-024-06702-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 08/08/2024] [Indexed: 08/19/2024] Open
Abstract
Immunohistochemistry is a crucial method for detecting specific proteins within tissue samples, yet constrained to one biomarker per tissue section. Multiplexed immunofluorescence, while allowing simultaneous visualization of multiple proteins, faces limitations in the number of simultaneous fluorescent labels due to spectral overlap. Although cyclic immunofluorescence techniques have successfully broadened antibody staining capacities in a single tissue sample, they are plagued by time-consuming and labor-intensive procedures, sample degradation risks, and inability to scale beyond thin sections. In this study, we introduce the use of 3D confocal Fluorescence Lifetime Imaging Microscopy as a high-throughput, multiplexed immunofluorescence platform that can differentiate 11 or more biomarkers in 3D tissue volumes. Leveraging both spectral and lifetime information, this approach allows for practical spatial biology in thin sections that can readily scale to larger volumes of tissue. We believe that this highly multiplexed and versatile biomarker imaging platform will significantly expedite cancer research and enable new translational approaches in the future.
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Affiliation(s)
- Wonsang Hwang
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Tucker Raymond
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Tyler McPartland
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Conor L Evans
- Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA.
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28
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Gunawardana J, Law SC, Sabdia MB, Fennell É, Hennessy A, Leahy CI, Murray PG, Bednarska K, Brosda S, Trotman J, Berkahn L, Zaharia A, Birch S, Burgess M, Talaulikar D, Lee JN, Jude E, Hawkes EA, Jain S, Nath K, Snell C, Swain F, Tobin JWD, Keane C, Shanavas M, Blyth E, Steidl C, Savage K, Farinha P, Boyle M, Meissner B, Green MR, Vega F, Gandhi MK. Intra-tumoral and peripheral blood TIGIT and PD-1 as immune biomarkers in nodular lymphocyte predominant Hodgkin lymphoma. Am J Hematol 2024. [PMID: 39152767 DOI: 10.1002/ajh.27459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 07/12/2024] [Accepted: 07/28/2024] [Indexed: 08/19/2024]
Abstract
In classical Hodgkin lymphoma (cHL), responsiveness to immune-checkpoint blockade (ICB) is associated with specific tumor microenvironment (TME) and peripheral blood features. The role of ICB in nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) is not established. To gain insights into its potential in NLPHL, we compared TME and peripheral blood signatures between HLs using an integrative multiomic analysis. A discovery/validation approach in 121 NLPHL and 114 cHL patients highlighted >2-fold enrichment in programmed cell death-1 (PD-1) and T-cell Ig and ITIM domain (TIGIT) gene expression for NLPHL versus cHL. Multiplex imaging showed marked increase in intra-tumoral protein expression of PD-1+ (and/or TIGIT+) CD4+ T-cells and PD-1+CD8+ T-cells in NLPHL compared to cHL. This included T-cells that rosetted with lymphocyte predominant (LP) and Hodgkin Reed-Sternberg (HRS) cells. In NLPHL, intra-tumoral PD-1+CD4+ T-cells frequently expressed TCF-1, a marker of heightened T-cell response to ICB. The peripheral blood signatures between HLs were also distinct, with higher levels of PD-1+TIGIT+ in TH1, TH2, and regulatory CD4+ T-cells in NLPHL versus cHL. Circulating PD-1+CD4+ had high levels of TCF-1. Notably, in both lymphomas, highly expanded populations of clonal TIGIT+PD-1+CD4+ and TIGIT+PD-1+CD8+ T-cells in the blood were also present in the TME, indicating that immune-checkpoint expressing T-cells circulated between intra-tumoral and blood compartments. In in vitro assays, ICB was capable of reducing rosette formation around LP and HRS cells, suggesting that disruption of rosetting may be a mechanism of action of ICB in HL. Overall, results indicate that further evaluation of ICB is warranted in NLPHL.
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Affiliation(s)
- Jay Gunawardana
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Soi C Law
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Muhammed B Sabdia
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Éanna Fennell
- School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute and Bernal Institute, University of Limerick, Limerick, Ireland
| | - Aoife Hennessy
- School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute and Bernal Institute, University of Limerick, Limerick, Ireland
| | - Ciara I Leahy
- School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute and Bernal Institute, University of Limerick, Limerick, Ireland
| | - Paul G Murray
- School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute and Bernal Institute, University of Limerick, Limerick, Ireland
- Royal College of Surgeons Ireland, Adliya, Bahrain
| | - Karolina Bednarska
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Sandra Brosda
- Frazer Institute, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Judith Trotman
- Concord Repatriation General Hospital, University of Sydney, Sydney, New South Wales, Australia
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
| | - Leanne Berkahn
- Department of Haematology, Auckland City Hospital, Auckland, New Zealand
| | - Andreea Zaharia
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Simone Birch
- Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Melinda Burgess
- School of Medicine, Limerick Digital Cancer Research Centre, Health Research Institute and Bernal Institute, University of Limerick, Limerick, Ireland
- Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Dipti Talaulikar
- Haematology Translational Research Unit, ACT Pathology, Canberra Health Services, Canberra, Australian Capital Territory, Australia
- College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Justina N Lee
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Emily Jude
- Austin Health, Heidelberg, Victoria, Australia
| | - Eliza A Hawkes
- Olivia Newton John Cancer Research and Wellness Centre, Austin Health, Melbourne, Victoria, Australia
- Transfusion Research Unit, School of Public Health and Preventative Medicine, Monash University, Melbourne, Victoria, Australia
| | - Sanjiv Jain
- Anatomical Pathology Department, The Canberra Hospital, Canberra, Australian Capital Territory, Australia
| | - Karthik Nath
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Cameron Snell
- Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Mater Pathology, Brisbane, Queensland, Australia
| | - Fiona Swain
- Royal College of Surgeons Ireland, Adliya, Bahrain
- Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Joshua W D Tobin
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Colm Keane
- Frazer Institute, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Princess Alexandra Hospital, Brisbane, Queensland, Australia
| | - Mohamed Shanavas
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Emily Blyth
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Camperdown, New South Wales, Australia
- Department of Haematology, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
| | - Christian Steidl
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Kerry Savage
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Pedro Farinha
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Merrill Boyle
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | - Barbara Meissner
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
| | | | - Francisco Vega
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Maher K Gandhi
- Blood Cancer Research Group, Mater Research, Translational Research Institute, University of Queensland, Brisbane, Queensland, Australia
- Princess Alexandra Hospital, Brisbane, Queensland, Australia
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29
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Sarkar S, Zheng X, Clair GC, Kwon YM, You Y, Swensen AC, Webb-Robertson BJM, Nakayasu ES, Qian WJ, Metz TO. Exploring new frontiers in type 1 diabetes through advanced mass-spectrometry-based molecular measurements. Trends Mol Med 2024:S1471-4914(24)00195-3. [PMID: 39152082 DOI: 10.1016/j.molmed.2024.07.009] [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: 05/23/2024] [Revised: 07/17/2024] [Accepted: 07/22/2024] [Indexed: 08/19/2024]
Abstract
Type 1 diabetes (T1D) is a devastating autoimmune disease for which advanced mass spectrometry (MS) methods are increasingly used to identify new biomarkers and better understand underlying mechanisms. For example, integration of MS analysis and machine learning has identified multimolecular biomarker panels. In mechanistic studies, MS has contributed to the discovery of neoepitopes, and pathways involved in disease development and identifying therapeutic targets. However, challenges remain in understanding the role of tissue microenvironments, spatial heterogeneity, and environmental factors in disease pathogenesis. Recent advancements in MS, such as ultra-fast ion-mobility separations, and single-cell and spatial omics, can play a central role in addressing these challenges. Here, we review recent advancements in MS-based molecular measurements and their role in understanding T1D.
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Affiliation(s)
- Soumyadeep Sarkar
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Xueyun Zheng
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Geremy C Clair
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Yu Mi Kwon
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Youngki You
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Adam C Swensen
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | | | - Ernesto S Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
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30
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Börner K, Blood PD, Silverstein JC, Ruffalo M, Satija R, Teichmann SA, Pryhuber G, Misra RS, Purkerson J, Fan J, Hickey JW, Molla G, Xu C, Zhang Y, Weber G, Jain Y, Qaurooni D, Kong Y, Bueckle A, Herr BW. Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.27.587041. [PMID: 38826261 PMCID: PMC11142047 DOI: 10.1101/2024.03.27.587041] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The Human BioMolecular Atlas Program (HuBMAP) aims to construct a reference 3D structural, cellular, and molecular atlas of the healthy adult human body. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) serves experimental datasets and supports data processing, search, filtering, and visualization. The Human Reference Atlas (HRA) Portal (https://humanatlas.io) provides open access to atlas data, code, procedures, and instructional materials. Experts from more than 20 consortia are collaborating to construct the HRA's Common Coordinate Framework (CCF), knowledge graphs, and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes, and biomarkers) and to use the HRA to understand changes that occur at each of these levels with aging, disease, and other perturbations. The 6th release of the HRA v2.0 covers 36 organs with 4,499 unique anatomical structures, 1,195 cell types, and 2,089 biomarkers (e.g., genes, proteins, lipids) linked to ontologies and 2D/3D reference objects. New experimental data can be mapped into the HRA using (1) three cell type annotation tools (e.g., Azimuth) or (2) validated antibody panels (OMAPs), or (3) by registering tissue data spatially. This paper describes the HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interface (APIs), flexible hybrid cloud infrastructure, and previews atlas usage applications.
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Affiliation(s)
- Katy Börner
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
- CIFAR MacMillan Multiscale Human program, CIFAR, Toronto, ON, Canada
| | - Philip D. Blood
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Jonathan C. Silverstein
- Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Matthew Ruffalo
- Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | | | - Sarah A. Teichmann
- CIFAR MacMillan Multiscale Human program, CIFAR, Toronto, ON, Canada
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Ravi S. Misra
- University of Rochester Medical Center, Rochester, NY, USA
| | | | - Jean Fan
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, USA
| | - John W. Hickey
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; New York Genome Center, New York, NY, USA
| | | | - Chuan Xu
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yun Zhang
- J. Craig Venter Institute, La Jolla, CA, USA
| | - Griffin Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Yashvardhan Jain
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
| | - Danial Qaurooni
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
| | - Yongxin Kong
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
| | | | - Andreas Bueckle
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
| | - Bruce W. Herr
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA
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31
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Su J, Song Y, Zhu Z, Huang X, Fan J, Qiao J, Mao F. Cell-cell communication: new insights and clinical implications. Signal Transduct Target Ther 2024; 9:196. [PMID: 39107318 PMCID: PMC11382761 DOI: 10.1038/s41392-024-01888-z] [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: 12/29/2023] [Revised: 05/09/2024] [Accepted: 06/02/2024] [Indexed: 09/11/2024] Open
Abstract
Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.
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Affiliation(s)
- Jimeng Su
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center, Peking University Third Hospital, Beijing, China
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
| | - Ying Song
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center, Peking University Third Hospital, Beijing, China
| | - Zhipeng Zhu
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center, Peking University Third Hospital, Beijing, China
| | - Xinyue Huang
- Biomedical Research Institute, Shenzhen Peking University-the Hong Kong University of Science and Technology Medical Center, Shenzhen, China
| | - Jibiao Fan
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
| | - Jie Qiao
- State Key Laboratory of Female Fertility Promotion, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.
- National Clinical Research Center for Obstetrics and Gynecology (Peking University Third Hospital), Beijing, China.
- Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education, Beijing, China.
- Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing, China.
| | - Fengbiao Mao
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China.
- Cancer Center, Peking University Third Hospital, Beijing, China.
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32
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Matusiak M, Hickey JW, van IJzendoorn DG, Lu G, Kidziński L, Zhu S, Colburg DR, Luca B, Phillips DJ, Brubaker SW, Charville GW, Shen J, Loh KM, Okwan-Duodu DK, Nolan GP, Newman AM, West RB, van de Rijn M. Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon Cancer. Cancer Discov 2024; 14:1418-1439. [PMID: 38552005 PMCID: PMC11294822 DOI: 10.1158/2159-8290.cd-23-1300] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 02/23/2024] [Accepted: 03/26/2024] [Indexed: 08/03/2024]
Abstract
Tumor-associated macrophages are transcriptionally heterogeneous, but the spatial distribution and cell interactions that shape macrophage tissue roles remain poorly characterized. Here, we spatially resolve five distinct human macrophage populations in normal and malignant human breast and colon tissue and reveal their cellular associations. This spatial map reveals that distinct macrophage populations reside in spatially segregated micro-environmental niches with conserved cellular compositions that are repeated across healthy and diseased tissue. We show that IL4I1+ macrophages phagocytose dying cells in areas with high cell turnover and predict good outcome in colon cancer. In contrast, SPP1+ macrophages are enriched in hypoxic and necrotic tumor regions and portend worse outcome in colon cancer. A subset of FOLR2+ macrophages is embedded in plasma cell niches. NLRP3+ macrophages co-localize with neutrophils and activate an inflammasome in tumors. Our findings indicate that a limited number of unique human macrophage niches function as fundamental building blocks in tissue. Significance: This work broadens our understanding of the distinct roles different macrophage populations may exert on cancer growth and reveals potential predictive markers and macrophage population-specific therapy targets.
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Affiliation(s)
| | - John W. Hickey
- Department of Pathology, Stanford University, Stanford, California.
| | | | - Guolan Lu
- Department of Pathology, Stanford University, Stanford, California.
| | - Lukasz Kidziński
- Department of Bioengineering, Stanford University, Stanford, California.
| | - Shirley Zhu
- Department of Pathology, Stanford University, Stanford, California.
| | | | - Bogdan Luca
- Department of Medicine, Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California.
- Department of Biomedical Data Science, Stanford University, Stanford, California.
| | | | - Sky W. Brubaker
- Department of Microbiology and Immunology, Stanford University, Stanford, California.
| | | | - Jeanne Shen
- Department of Pathology, Stanford University, Stanford, California.
| | - Kyle M. Loh
- Department of Developmental Biology, Stanford University, Stanford, California.
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California.
| | | | - Garry P. Nolan
- Department of Pathology, Stanford University, Stanford, California.
| | - Aaron M. Newman
- Department of Biomedical Data Science, Stanford University, Stanford, California.
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California.
- Stanford Cancer Institute, Stanford University, Stanford, California.
| | - Robert B. West
- Department of Pathology, Stanford University, Stanford, California.
| | - Matt van de Rijn
- Department of Pathology, Stanford University, Stanford, California.
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33
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Dezem FS, Arjumand W, DuBose H, Morosini NS, Plummer J. Spatially Resolved Single-Cell Omics: Methods, Challenges, and Future Perspectives. Annu Rev Biomed Data Sci 2024; 7:131-153. [PMID: 38768396 DOI: 10.1146/annurev-biodatasci-102523-103640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Overlaying omics data onto spatial biological dimensions has been a promising technology to provide high-resolution insights into the interactome and cellular heterogeneity relative to the organization of the molecular microenvironment of tissue samples in normal and disease states. Spatial omics can be categorized into three major modalities: (a) next-generation sequencing-based assays, (b) imaging-based spatially resolved transcriptomics approaches including in situ hybridization/in situ sequencing, and (c) imaging-based spatial proteomics. These modalities allow assessment of transcripts and proteins at a cellular level, generating large and computationally challenging datasets. The lack of standardized computational pipelines to analyze and integrate these nonuniform structured data has made it necessary to apply artificial intelligence and machine learning strategies to best visualize and translate their complexity. In this review, we summarize the currently available techniques and computational strategies, highlight their advantages and limitations, and discuss their future prospects in the scientific field.
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Affiliation(s)
- Felipe Segato Dezem
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Center for Spatial Omics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA;
| | - Wani Arjumand
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Center for Spatial Omics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA;
| | - Hannah DuBose
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Center for Spatial Omics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA;
| | - Natalia Silva Morosini
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Center for Spatial Omics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA;
| | - Jasmine Plummer
- Department of Cellular and Molecular Biology and Comprehensive Cancer Center, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
- Center for Spatial Omics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA;
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34
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Deen AJ, Thorsson J, O’Roberts EM, Panshikar P, Ullman T, Krantz D, Oses C, Stadler C. Making Multiplexed Imaging Flexible: Combining Essential Markers With Established Antibody Panels. J Histochem Cytochem 2024; 72:517-544. [PMID: 39215640 PMCID: PMC11421402 DOI: 10.1369/00221554241274856] [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: 03/19/2024] [Accepted: 07/22/2024] [Indexed: 09/04/2024] Open
Abstract
Multiplexed immunofluorescence (IF) can be achieved using different commercially available platforms, often making use of conjugated antibodies detected in iterative cycles. A growing portfolio of pre-conjugated antibodies is offered by the providers, as well as the possibility for in-house conjugation. For many conjugation methods and kits, there are limitations in which antibodies can be used, and conjugation results are sometimes irreproducible. The conjugation process can limit or slow down the progress of studies requiring conjugation of essential markers needed for a given project. Here, we demonstrate a protocol combining manual indirect immunofluorescence (IF) of primary antibodies, followed by antibody elution and staining with multiplexed panels of commercially pre-conjugated antibodies on the PhenoCycler platform. We present detailed protocols for applying the workflow on fresh frozen and formalin fixed paraffin embedded tissue sections. We also provide a ready to use workflow for coregistration of the images and demonstrate this for two examples.
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Affiliation(s)
- Ashik Jawahar Deen
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Johan Thorsson
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
| | - Eleanor M. O’Roberts
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
| | - Pranauti Panshikar
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
| | - Tony Ullman
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
| | - David Krantz
- Department of Oncology-Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden
| | - Carolina Oses
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
| | - Charlotte Stadler
- Department of Protein Science, Royal Institute of Technology, Stockholm, Sweden
- Science for Life Laboratory, Solna, Sweden
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35
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Maliga Z, Kim DY, Bui ATN, Lin JR, Dewan AK, Jadeja S, Murphy GF, Nirmal AJ, Lian CG, Sorger PK, LeBoeuf NR. Immune Profiling of Dermatologic Adverse Events from Checkpoint Blockade Using Tissue Cyclic Immunofluorescence: A Pilot Study. J Invest Dermatol 2024; 144:1887-1890.e5. [PMID: 38360200 PMCID: PMC11447745 DOI: 10.1016/j.jid.2024.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 01/04/2024] [Accepted: 01/07/2024] [Indexed: 02/17/2024]
Affiliation(s)
- Zoltan Maliga
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - Daniel Y Kim
- Harvard-MIT Health Sciences and Technology Program, Harvard Medical School, Boston, Massachusetts, USA
| | - Ai-Tram N Bui
- Department of Dermatology, The Center for Cutaneous Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Jia-Ren Lin
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - Anna K Dewan
- Department of Dermatology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Saagar Jadeja
- Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - George F Murphy
- Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Ajit J Nirmal
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - Christine G Lian
- Program in Dermatopathology, Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Peter K Sorger
- Laboratory of Systems Pharmacology, Harvard Medical School, Boston, Massachusetts, USA
| | - Nicole R LeBoeuf
- Department of Dermatology, The Center for Cutaneous Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, Massachusetts, USA.
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36
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Kirchgaessner R, Watson C, Creason A, Keutler K, Goecks J. Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.05.570058. [PMID: 38106203 PMCID: PMC10723289 DOI: 10.1101/2023.12.05.570058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Multiplex tissue imaging are a collection of increasingly popular single-cell spatial proteomics and transcriptomics assays for characterizing biological tissues both compositionally and spatially. However, several technical issues limit the utility of multiplex tissue imaging, including the limited number of molecules (proteins and RNAs) that can be assayed, tissue loss, and protein probe failure. In this work, we demonstrate how machine learning methods can address these limitations by imputing protein abundance at the single-cell level using multiplex tissue imaging datasets from a breast cancer cohort. We first compared machine learning methods' strengths and weaknesses for imputing single-cell protein abundance. Machine learning methods used in this work include regularized linear regression, gradient-boosted regression trees, and deep learning autoencoders. We also incorporated cellular spatial information to improve imputation performance. Using machine learning, single-cell protein expression can be imputed with mean absolute error ranging between 0.05-0.3 on a [0,1] scale. Finally, we used imputed data to predict whether single cells were more likely to come from pre-treatment or post-treatment biopsies. Our results demonstrate (1) the feasibility of imputing single-cell abundance levels for many proteins using machine learning; (2) how including cellular spatial information can substantially enhance imputation results; and (3) the use of single-cell protein abundance levels in a use case to demonstrate biological relevance.
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37
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Gustafson KT, Sayar Z, Modestino A, Le HH, Gower A, Civitci F, Esener SC, Heller MJ, Eksi SE. Oligo cyc-DEP: On-chip cyclic immunofluorescence profiling of cell-derived nanoparticles. Electrophoresis 2024. [PMID: 39049673 DOI: 10.1002/elps.202400088] [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: 04/29/2024] [Revised: 06/29/2024] [Accepted: 07/10/2024] [Indexed: 07/27/2024]
Abstract
We present a follow-on technique for the cyclic-immunofluorescence profiling of suspension particles isolated using dielectrophoresis. The original lab-on-chip technique ("cyc-DEP" [cyclic immunofluorescent imaging on dielectrophoretic chip]) was designed for the multiplex surveillance of circulating biomarkers. Nanoparticles were collected from low-volume liquid biopsies using microfluidic dielectrophoretic chip technology. Subsequent rounds of cyclic immunofluorescent labeling and quenching were imaged and quantified with a custom algorithm to detect multiple proteins. While cyc-DEP improved assay multiplicity, long runtimes threatened its clinical adoption. Here, we modify the original cyc-DEP platform to reduce assay runtimes. Nanoparticles were formulated from human prostate adenocarcinoma cells and collected using dielectrophoresis. Three proteins were labeled on-chip with a mixture of short oligonucleotide-conjugated antibodies. The sample was then incubated with complementary fluorophore-conjugated oligonucleotides, which were dehybridized using an ethylene carbonate buffer after each round of imaging. Oligonucleotide removal exhibited an average quenching efficiency of 98 ± 3% (n = 12 quenching events), matching the original cyc-DEP platform. The presented "oligo cyc-DEP" platform achieved clinically relevant sample-to-answer times, reducing the duration for three rounds of cyclic immunolabeling from approximately 20 to 6.5 h-a 67% decrease attributed to rapid fluorophore removal and the consolidated co-incubation of antibodies.
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Affiliation(s)
- Kyle T Gustafson
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Zeynep Sayar
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Augusta Modestino
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Hillary H Le
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Austin Gower
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Fehmi Civitci
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Sadik C Esener
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Michael J Heller
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Sebnem Ece Eksi
- Cancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Division of Oncological Sciences, Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
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38
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Chen HC, Ma Y, Cheng J, Chen YC. Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes. CANCER HETEROGENEITY AND PLASTICITY 2024; 1:0004. [PMID: 39156821 PMCID: PMC11328949 DOI: 10.47248/chp2401010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/20/2024]
Abstract
Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.
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Affiliation(s)
- Hsiao-Chun Chen
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
| | - Yushu Ma
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
| | - Jinxiong Cheng
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA 15260, USA
| | - Yu-Chih Chen
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA 15260, USA
- CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
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39
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Schmidt L, Saynisch M, Hoegsbjerg C, Schmidt A, Mackey A, Lackmann JW, Müller S, Koch M, Brachvogel B, Kjaer M, Antczak P, Krüger M. Spatial proteomics of skeletal muscle using thin cryosections reveals metabolic adaptation at the muscle-tendon transition zone. Cell Rep 2024; 43:114374. [PMID: 38900641 DOI: 10.1016/j.celrep.2024.114374] [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: 12/07/2023] [Revised: 04/05/2024] [Accepted: 05/31/2024] [Indexed: 06/22/2024] Open
Abstract
Morphological studies of skeletal muscle tissue provide insights into the architecture of muscle fibers, the surrounding cells, and the extracellular matrix (ECM). However, a spatial proteomics analysis of the skeletal muscle including the muscle-tendon transition zone is lacking. Here, we prepare cryotome muscle sections of the mouse soleus muscle and measure each slice using short liquid chromatography-mass spectrometry (LC-MS) gradients. We generate 3,000 high-resolution protein profiles that serve as the basis for a network analysis to reveal the complex architecture of the muscle-tendon junction. Among the protein profiles that increase from muscle to tendon, we find proteins related to neuronal activity, fatty acid biosynthesis, and the renin-angiotensin system (RAS). Blocking the RAS in cultured mouse tenocytes using losartan reduces the ECM synthesis. Overall, our analysis of thin cryotome sections provides a spatial proteome of skeletal muscle and reveals that the RAS acts as an additional regulator of the matrix within muscle-tendon junctions.
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Affiliation(s)
- Luisa Schmidt
- Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany
| | - Michael Saynisch
- Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany
| | - Christian Hoegsbjerg
- Institute of Sports Medicine Copenhagen, Department of Orthopaedic Surgery, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark; Part of IOC Research Center Copenhagen and Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Abigail Mackey
- Institute of Sports Medicine Copenhagen, Department of Orthopaedic Surgery, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark; Part of IOC Research Center Copenhagen and Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jan-Wilm Lackmann
- Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany
| | - Stefan Müller
- Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany
| | - Manuel Koch
- Institute for Dental Research and Oral Musculoskeletal Biology, Center for Biochemistry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Bent Brachvogel
- Department of Pediatrics and Adolescent Medicine, Experimental Neonatology, Medical Faculty, University of Cologne, Cologne, Germany; Center for Biochemistry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Michael Kjaer
- Institute of Sports Medicine Copenhagen, Department of Orthopaedic Surgery, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark; Part of IOC Research Center Copenhagen and Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Philipp Antczak
- Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany; Center for Molecular Medicine (CMMC), University of Cologne, 50931 Cologne, Germany.
| | - Marcus Krüger
- Institute for Genetics, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, Germany; Center for Molecular Medicine (CMMC), University of Cologne, 50931 Cologne, Germany.
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40
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Quek C, Pratapa A, Bai X, Al-Eryani G, Pires da Silva I, Mayer A, Bartonicek N, Harvey K, Maher NG, Conway JW, Kasalo RJ, Ben Cheikh B, Braubach O, Palendira U, Saw RPM, Stretch JR, Shannon KF, Menzies AM, Scolyer RA, Long GV, Swarbrick A, Wilmott JS. Single-cell spatial multiomics reveals tumor microenvironment vulnerabilities in cancer resistance to immunotherapy. Cell Rep 2024; 43:114392. [PMID: 38944836 DOI: 10.1016/j.celrep.2024.114392] [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: 10/13/2023] [Revised: 03/31/2024] [Accepted: 06/07/2024] [Indexed: 07/02/2024] Open
Abstract
Heterogeneous resistance to immunotherapy remains a major challenge in cancer treatment, often leading to disease progression and death. Using CITE-seq and matched 40-plex PhenoCycler tissue imaging, we performed longitudinal multimodal single-cell analysis of tumors from metastatic melanoma patients with innate resistance, acquired resistance, or response to immunotherapy. We established the multimodal integration toolkit to align transcriptomic features, cellular epitopes, and spatial information to provide deeper insights into the tumors. With longitudinal analysis, we identified an "immune-striving" tumor microenvironment marked by peri-tumor lymphoid aggregates and low infiltration of T cells in the tumor and the emergence of MITF+SPARCL1+ and CENPF+ melanoma subclones after therapy. The enrichment of B cell-associated signatures in the molecular composition of lymphoid aggregates was associated with better survival. These findings provide further insights into the establishment of microenvironmental cell interactions and molecular composition of spatial structures that could inform therapeutic intervention.
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Affiliation(s)
- Camelia Quek
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
| | | | - Xinyu Bai
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Ghamdan Al-Eryani
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; School of Clinical Medicine, St Vincent's Clinical Campus, UNSW Medicine & Health, UNSW Sydney, NSW, Australia
| | - Inês Pires da Silva
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Crown Princess Mary Cancer Centre, Westmead and Blacktown Hospitals, Sydney, Australia
| | - Aaron Mayer
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA; Enable Medicine, Stanford, CA, USA
| | - Nenad Bartonicek
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; School of Clinical Medicine, St Vincent's Clinical Campus, UNSW Medicine & Health, UNSW Sydney, NSW, Australia
| | - Kate Harvey
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Nigel G Maher
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Jordan W Conway
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Rebecca J Kasalo
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | | | | | - Umaimainthan Palendira
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Centenary Institute, The University of Sydney, Sydney, NSW, Australia
| | - Robyn P M Saw
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Jonathan R Stretch
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Kerwin F Shannon
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, NSW, Australia; Sydney Head & Neck Cancer Institute, Chris O'Brien Lifehouse Cancer Centre, Sydney, NSW, Australia
| | - Alexander M Menzies
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Department of Medical Oncology, Royal North Shore and Mater Hospitals, Sydney, NSW, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital & NSW Health Pathology, Sydney, NSW, Australia
| | - Georgina V Long
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia; Department of Medical Oncology, Royal North Shore and Mater Hospitals, Sydney, NSW, Australia
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia; School of Clinical Medicine, St Vincent's Clinical Campus, UNSW Medicine & Health, UNSW Sydney, NSW, Australia
| | - James S Wilmott
- Melanoma Institute Australia, The University of Sydney, Sydney, NSW, Australia; Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
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41
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McCarthy M, Lu X, Ogunleye O, Latham DR, Abravanel M, Pritko D, Huggins JR, Haskell CV, Patel ND, Pittman ZA, Sanabria H, Birtwistle MR. Increasing Signal Intensity of Fluorescent Oligo-Labeled Antibodies to Enable Combination Multiplexing. Bioconjug Chem 2024; 35:1053-1063. [PMID: 38889324 PMCID: PMC11262307 DOI: 10.1021/acs.bioconjchem.4c00246] [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: 05/30/2024] [Revised: 06/03/2024] [Accepted: 06/05/2024] [Indexed: 06/20/2024]
Abstract
Full-spectrum flow cytometry has increased antibody-based multiplexing, yet further increases remain potentially impactful. We recently proposed how fluorescence multiplexing using spectral imaging and combinatorics (MuSIC) could do so using tandem dyes and an oligo-based antibody labeling method. In this work, we found that such labeled antibodies had significantly lower signal intensities than conventionally labeled antibodies in human cell experiments. To improve signal intensity, we tested moving the fluorophores from the original external (ext.) 5' or 3' end-labeled orientation to internal (int.) fluorophore modifications. Cell-free spectrophotometer measurements showed a ∼6-fold signal intensity increase of the new int. configuration compared to the previous ext. configuration. Time-resolved fluorescence and fluorescence correlation spectroscopy showed that the ∼3-fold brightness difference is due to static quenching most likely by the oligo or solution in the ext. configuration. Spectral flow cytometry experiments using peripheral blood mononuclear cells show int. MuSIC probe-labeled antibodies (i) retained increased signal intensity while having no significant difference in the estimated % of CD8+ lymphocytes and (ii) labeled with Atto488, Atto647, and Atto488/647 combinations can be demultiplexed in triple-stained samples. The antibody labeling approach is general and can be broadly applied to many biological and diagnostic applications where spectral detection is available.
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Affiliation(s)
- Madeline
E. McCarthy
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Xiaoming Lu
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Oluwaferanmi Ogunleye
- Department
of Chemistry, Clemson University, Clemson, South Carolina 29634-0002, United
States
| | - Danielle R. Latham
- Department
of Physics and Astronomy, Clemson University, Clemson, South Carolina 29634-0002, United
States
| | - Megan Abravanel
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Daniel Pritko
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Jonah R. Huggins
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Charlotte V. Haskell
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Nishi D. Patel
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Zachariah A. Pittman
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
| | - Hugo Sanabria
- Department
of Chemistry, Clemson University, Clemson, South Carolina 29634-0002, United
States
| | - Marc R. Birtwistle
- Department
of Chemical and Biomolecular Engineering, Clemson University, Clemson, South Carolina 29634-0002, United States
- Department
of Bioengineering, Clemson University, Clemson, South Carolina 29634-0002, United
States
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42
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Rocca G, Galli M, Celant A, Stucchi G, Marongiu L, Cozzi S, Innocenti M, Granucci F. Multiplexed imaging to reveal tissue dendritic cell spatial localisation and function. FEBS Lett 2024. [PMID: 38969618 DOI: 10.1002/1873-3468.14962] [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: 04/22/2024] [Revised: 05/20/2024] [Accepted: 05/28/2024] [Indexed: 07/07/2024]
Abstract
Dendritic cells (DCs) play a pivotal role in immune surveillance, acting as sentinels that coordinate immune responses within tissues. Although differences in the identity and functional states of DC subpopulations have been identified through multiparametric flow cytometry and single-cell RNA sequencing, these methods do not provide information about the spatial context in which the cells are located. This knowledge is crucial for understanding tissue organisation and cellular cross-talk. Recent developments in multiplex imaging techniques can now offer insights into this complex spatial and functional landscape. This review provides a concise overview of these imaging methodologies, emphasising their application in identifying DCs to delineate their tissue-specific functions and aiding newcomers in navigating this field.
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Affiliation(s)
- Giuseppe Rocca
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Marco Galli
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Anna Celant
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Giulia Stucchi
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Laura Marongiu
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Stefano Cozzi
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Metello Innocenti
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
| | - Francesca Granucci
- Department of Biotechnology and Biosciences, University of Milano Bicocca, Milan, Italy
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43
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Arceneaux JS, Brockman AA, Khurana R, Chalkley MBL, Geben LC, Krbanjevic A, Vestal M, Zafar M, Weatherspoon S, Mobley BC, Ess KC, Ihrie RA. Multiparameter quantitative analyses of diagnostic cells in brain tissues from tuberous sclerosis complex. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2024. [PMID: 38953209 DOI: 10.1002/cyto.b.22194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 06/05/2024] [Accepted: 06/11/2024] [Indexed: 07/03/2024]
Abstract
The advent of high-dimensional imaging offers new opportunities to molecularly characterize diagnostic cells in disorders that have previously relied on histopathological definitions. One example case is found in tuberous sclerosis complex (TSC), a developmental disorder characterized by systemic growth of benign tumors. Within resected brain tissues from patients with TSC, detection of abnormally enlarged balloon cells (BCs) is pathognomonic for this disorder. Though BCs can be identified by an expert neuropathologist, little is known about the specificity and broad applicability of protein markers for these cells, complicating classification of proposed BCs identified in experimental models of this disorder. Here, we report the development of a customized machine learning pipeline (BAlloon IDENtifier; BAIDEN) that was trained to prospectively identify BCs in tissue sections using a histological stain compatible with high-dimensional cytometry. This approach was coupled to a custom 36-antibody panel and imaging mass cytometry (IMC) to explore the expression of multiple previously proposed BC marker proteins and develop a descriptor of BC features conserved across multiple tissue samples from patients with TSC. Here, we present a modular workflow encompassing BAIDEN, a custom antibody panel, a control sample microarray, and analysis pipelines-both open-source and in-house-and apply this workflow to understand the abundance, structure, and signaling activity of BCs as an example case of how high-dimensional imaging can be applied within human tissues.
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Affiliation(s)
- Jerome S Arceneaux
- Department of Biochemistry, Cancer Biology, Neuroscience, and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Asa A Brockman
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Rohit Khurana
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Mary-Bronwen L Chalkley
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - Laura C Geben
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee, USA
| | - Aleksandar Krbanjevic
- Department of Pathology, Microbiology, & Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Matthew Vestal
- Duke University Children's Hospital and Health Center, Durham, North Carolina, USA
| | - Muhammad Zafar
- Duke University Children's Hospital and Health Center, Durham, North Carolina, USA
| | - Sarah Weatherspoon
- Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, Tennessee, USA
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Bret C Mobley
- Department of Pathology, Microbiology, & Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kevin C Ess
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Section of Child Neurology, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA
| | - Rebecca A Ihrie
- Department of Cell & Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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44
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Wang C, Qiu J, Liu M, Wang Y, Yu Y, Liu H, Zhang Y, Han L. Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2401263. [PMID: 38767182 PMCID: PMC11267386 DOI: 10.1002/advs.202401263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/26/2024] [Indexed: 05/22/2024]
Abstract
Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.
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Affiliation(s)
- Chao Wang
- Institute of Marine Science and TechnologyShandong UniversityQingdao266237China
| | - Jiaoyan Qiu
- Institute of Marine Science and TechnologyShandong UniversityQingdao266237China
| | - Mengqi Liu
- Institute of Marine Science and TechnologyShandong UniversityQingdao266237China
| | - Yihe Wang
- Institute of Marine Science and TechnologyShandong UniversityQingdao266237China
| | - Yang Yu
- Department of PeriodontologySchool and Hospital of StomatologyCheeloo College of MedicineShandong UniversityJinan250100China
| | - Hong Liu
- State Key Laboratory of Crystal MaterialsShandong UniversityJinan250100China
| | - Yu Zhang
- Institute of Marine Science and TechnologyShandong UniversityQingdao266237China
| | - Lin Han
- Institute of Marine Science and TechnologyShandong UniversityQingdao266237China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence ApplicationJinan250100China
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45
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Brewer M, Migas LG, Clouthier KA, Allen JL, Anderson DM, Pingry E, Farrow M, Quardokus EM, Spraggins JM, Van de Plas R, de Caestecker MP. Validation of an organ mapping antibody panel for cyclical immunofluorescence microscopy on normal human kidneys. Am J Physiol Renal Physiol 2024; 327:F91-F102. [PMID: 38721662 PMCID: PMC11390132 DOI: 10.1152/ajprenal.00426.2023] [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: 01/02/2024] [Revised: 03/11/2024] [Accepted: 03/26/2024] [Indexed: 06/21/2024] Open
Abstract
The lack of standardization in antibody validation remains a major contributor to irreproducibility of human research. To address this, we have applied a standardized approach to validate a panel of antibodies to identify 18 major cell types and 5 extracellular matrix compartments in the human kidney by immunofluorescence (IF) microscopy. We have used these to generate an organ mapping antibody panel for two-dimensional (2-D) and three-dimensional (3-D) cyclical IF (CyCIF) to provide a more detailed method for evaluating tissue segmentation and volumes using a larger panel of markers than would normally be possible using standard fluorescence microscopy. CyCIF also makes it possible to perform multiplexed IF microscopy of whole slide images, which is a distinct advantage over other multiplexed imaging technologies that are applicable to limited fields of view. This enables a broader view of cell distributions across larger anatomical regions, allowing a better chance to capture localized regions of dysfunction in diseased tissues. These methods are broadly accessible to any laboratory with a fluorescence microscope, enabling spatial cellular phenotyping in normal and disease states. We also provide a detailed solution for image alignment between CyCIF cycles that can be used by investigators to perform these studies without programming experience using open-sourced software. This ability to perform multiplexed imaging without specialized instrumentation or computational skills opens the door to integration with more highly dimensional molecular imaging modalities such as spatial transcriptomics and imaging mass spectrometry, enabling the discovery of molecular markers of specific cell types, and how these are altered in disease.NEW & NOTEWORTHY We describe here validation criteria used to define on organ mapping panel of antibodies that can be used to define 18 cell types and five extracellular matrix compartments using cyclical immunofluorescence (CyCIF) microscopy. As CyCIF does not require specialized instrumentation, and image registration required to assemble CyCIF images can be performed by any laboratory without specialized computational skills, this technology is accessible to any laboratory with access to a fluorescence microscope and digital scanner.
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Affiliation(s)
- Maya Brewer
- Division of Nephrology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Lukasz G Migas
- Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
| | - Kelly A Clouthier
- Division of Nephrology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Jamie L Allen
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
| | - David M Anderson
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
| | - Ellie Pingry
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
| | - Melissa Farrow
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
| | - Ellen M Quardokus
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, Indiana, United States
| | - Jeffrey M Spraggins
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Chemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Raf Van de Plas
- Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
- Mass Spectrometry Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
| | - Mark P de Caestecker
- Division of Nephrology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
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46
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Strongin Z, Raymond Marchand L, Deleage C, Pampena MB, Cardenas MA, Beusch CM, Hoang TN, Urban EA, Gourves M, Nguyen K, Tharp GK, Lapp S, Rahmberg AR, Harper J, Del Rio Estrada PM, Gonzalez-Navarro M, Torres-Ruiz F, Luna-Villalobos YA, Avila-Rios S, Reyes-Teran G, Sekaly R, Silvestri G, Kulpa DA, Saez-Cirion A, Brenchley JM, Bosinger SE, Gordon DE, Betts MR, Kissick HT, Paiardini M. Distinct SIV-specific CD8 + T cells in the lymph node exhibit simultaneous effector and stem-like profiles and are associated with limited SIV persistence. Nat Immunol 2024; 25:1245-1256. [PMID: 38886592 DOI: 10.1038/s41590-024-01875-0] [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: 06/16/2023] [Accepted: 05/14/2024] [Indexed: 06/20/2024]
Abstract
Human immunodeficiency virus (HIV) cure efforts are increasingly focused on harnessing CD8+ T cell functions, which requires a deeper understanding of CD8+ T cells promoting HIV control. Here we identifiy an antigen-responsive TOXhiTCF1+CD39+CD8+ T cell population with high expression of inhibitory receptors and low expression of canonical cytolytic molecules. Transcriptional analysis of simian immunodeficiency virus (SIV)-specific CD8+ T cells and proteomic analysis of purified CD8+ T cell subsets identified TOXhiTCF1+CD39+CD8+ T cells as intermediate effectors that retained stem-like features with a lineage relationship with terminal effector T cells. TOXhiTCF1+CD39+CD8+ T cells were found at higher frequency than TCF1-CD39+CD8+ T cells in follicular microenvironments and were preferentially located in proximity of SIV-RNA+ cells. Their frequency was associated with reduced plasma viremia and lower SIV reservoir size. Highly similar TOXhiTCF1+CD39+CD8+ T cells were detected in lymph nodes from antiretroviral therapy-naive and antiretroviral therapy-suppressed people living with HIV, suggesting this population of CD8+ T cells contributes to limiting SIV and HIV persistence.
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Affiliation(s)
- Zachary Strongin
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Laurence Raymond Marchand
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Claire Deleage
- AIDS and Cancer Virus Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, USA
| | - M Betina Pampena
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for AIDS Research and Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Christian Michel Beusch
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Timothy N Hoang
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Elizabeth A Urban
- AIDS and Cancer Virus Program, Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, USA
| | - Mael Gourves
- Institut Pasteur, Université Paris Cité, Viral Reservoirs and Immune Control Unit, Paris, France
- Institut Pasteur, Université Paris Cité, HIV Inflammation and Persistence Unit, Paris, France
| | - Kevin Nguyen
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Gregory K Tharp
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Stacey Lapp
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Andrew R Rahmberg
- Barrier Immunity Section, Laboratory of Viral Diseases, NIAIDNIH, Bethesda, MD, USA
| | - Justin Harper
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Perla M Del Rio Estrada
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Mauricio Gonzalez-Navarro
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Fernanda Torres-Ruiz
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Yara Andrea Luna-Villalobos
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Santiago Avila-Rios
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico
| | - Gustavo Reyes-Teran
- Comision Coordinadora de los Institutos Nacionales de Salud y Hospitales de Alta Especialidad, Mexico City, Mexico
| | - Rafick Sekaly
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Emory Vaccine Center, Emory University, Atlanta, GA, USA
- Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Guido Silvestri
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Emory Vaccine Center, Emory University, Atlanta, GA, USA
| | - Deanna A Kulpa
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Asier Saez-Cirion
- Institut Pasteur, Université Paris Cité, Viral Reservoirs and Immune Control Unit, Paris, France
- Institut Pasteur, Université Paris Cité, HIV Inflammation and Persistence Unit, Paris, France
| | - Jason M Brenchley
- Barrier Immunity Section, Laboratory of Viral Diseases, NIAIDNIH, Bethesda, MD, USA
| | - Steven E Bosinger
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Emory Vaccine Center, Emory University, Atlanta, GA, USA
| | - David Ezra Gordon
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Michael R Betts
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for AIDS Research and Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Haydn T Kissick
- Department of Urology, Emory University School of Medicine, Atlanta, GA, USA
- Emory Vaccine Center, Emory University, Atlanta, GA, USA
- Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Mirko Paiardini
- Division of Microbiology and Immunology, Emory National Primate Research Center, Emory University, Atlanta, GA, USA.
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
- Emory Vaccine Center, Emory University, Atlanta, GA, USA.
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47
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Huynh KLA, Tyc KM, Matuck BF, Easter QT, Pratapa A, Kumar NV, Pérez P, Kulchar RJ, Pranzatelli TJ, de Souza D, Weaver TM, Qu X, Soares Junior LAV, Dolhnokoff M, Kleiner DE, Hewitt SM, Ferraz da Silva LF, Rocha VG, Warner BM, Byrd KM, Liu J. Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT. RESEARCH SQUARE 2024:rs.3.rs-4536158. [PMID: 38978567 PMCID: PMC11230516 DOI: 10.21203/rs.3.rs-4536158/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data. TACIT uses unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integrating TACIT-identified cell types with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discovered under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.
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Affiliation(s)
- Khoa L. A. Huynh
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
| | - Katarzyna M. Tyc
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
- Massey Cancer Center, Richmond VA, USA
| | - Bruno F. Matuck
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA
| | - Quinn T. Easter
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA
| | - Aditya Pratapa
- Department of Cell Biology, Duke University, Durham, NC, USA
| | - Nikhil V. Kumar
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA
| | - Paola Pérez
- Salivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Rachel J. Kulchar
- Salivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Thomas J.F. Pranzatelli
- Adeno-Associated Virus Biology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Deiziane de Souza
- Department of Pathology, Medicine School of University of Sao Paulo, SP, BR
| | - Theresa M. Weaver
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA
| | - Xufeng Qu
- Massey Cancer Center, Richmond VA, USA
| | | | - Marisa Dolhnokoff
- Department of Pathology, Medicine School of University of Sao Paulo, SP, BR
| | - David E. Kleiner
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stephen M. Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Vanderson Geraldo Rocha
- Department of Hematology, Transfusion and Cell Therapy Service, University of Sao Paulo, Sao Paulo, Brazil
| | - Blake M. Warner
- Salivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Kevin M. Byrd
- Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA
- Salivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
- Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jinze Liu
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
- Massey Cancer Center, Richmond VA, USA
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48
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Hirai T, Kondo A, Shimizu T, Fukuda H, Tokita D, Takagi T, Mayer AT, Ishida H. Unveiling Spatial Immune Cell Profile in Kidney Allograft Rejections Using 36-plex Immunofluorescence Imaging. Transplantation 2024:00007890-990000000-00800. [PMID: 38913785 DOI: 10.1097/tp.0000000000005107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
BACKGROUND Kidney allograft rejections are orchestrated by a variety of immune cells. Because of the complex histopathologic features, accurate pathological diagnosis poses challenges even for expert pathologists. The objective of this study was to unveil novel spatial indices associated with transplant rejection by using a spatial bioinformatic approach using 36-plex immunofluorescence image data. METHODS The image obtained from 11 T cell-mediated rejection (TCMR) and 12 antibody-mediated rejection (AMR) samples were segmented into 753 737 single cells using DeepCell's Mesmer algorithm. These cells were categorized into 13 distinct cell types through unsupervised clustering based on their biomarker expression profiles. Cell neighborhood analysis allowed us to stratify kidney tissue into 8 distinct neighborhood components consisting of unique cell type enrichment profiles. RESULTS In contrast to TCMR samples, AMR samples exhibited a higher frequency of neighborhood components that were characterized by an enrichment of CD31+ endothelial cells. Although the overall frequency of CD68+ macrophages in AMR samples was not significantly high, CD68+ macrophages within endothelial cell-rich lesions exhibited a significantly higher frequency in AMR samples than TCMR samples. Furthermore, the frequency of interactions between CD31+ cells and CD68+ cells was significantly increased in AMR samples, implying the pivotal role of macrophages in AMR pathogenesis. Importantly, patients demonstrating a high frequency of CD31:CD68 interactions experienced significantly poorer outcomes in terms of chronic AMR progression. CONCLUSIONS Collectively, these data indicate the potential of spatial bioinformatic as a valuable tool for aiding in pathological diagnosis and for uncovering new insights into the mechanisms underlying transplant rejection.
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Affiliation(s)
- Toshihito Hirai
- Department of Urology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
| | | | - Tomokazu Shimizu
- Division of Organ Transplant Management, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
| | - Hironori Fukuda
- Department of Urology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
| | - Daisuke Tokita
- Department of Urology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
- Center for Clinical Sciences, National Center for Global Health and Medicine, Shinjuku, Tokyo, Japan
| | - Toshio Takagi
- Department of Urology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
| | | | - Hideki Ishida
- Division of Organ Transplant Management, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
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49
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Mao D, Tang X, Zhang R, Chen T, Liu C, Gou H, Sun P, Mao Y, Deng J, Li W, Sun F, Zhu X. DNA-Programmed Four-Bit Quaternary Fluorescence Encoding (FLUCO) Enables 51-Colored Bioimaging Analysis. J Am Chem Soc 2024. [PMID: 38859621 DOI: 10.1021/jacs.4c00811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024]
Abstract
Color encoding plays a crucial role in painting, digital photography, and spectral analysis. Achieving accurate, target-responsive color encoding at the molecular level has the potential to revolutionize scientific research and technological innovation, but significant challenges persist. Here, we propose a multibit DNA self-assembly system based on computer-aided design (CAD) technology, enabling accurate, target-responsive, amplified color encoding at the molecular level, termed fluorescence encoding (FLUCO). As a model, we establish a quaternary FLUCO system using four-bit DNA self-assembly, which can accurately encode 51 colors, presenting immense potential in applications such as spatial proteomic imaging and multitarget analysis. Notably, FLUCO enables the simultaneous imaging of multiple targets exceeding the limitations of channels using conventional imaging equipment, and marks the integration of computer science for molecular encoding and decoding. Overall, our work paves the way for target-responsive, controllable molecular encoding, facilitating spatial omics analysis, exfoliated cell analysis, and high-throughput liquid biopsy.
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Affiliation(s)
- Dongsheng Mao
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
| | - Xiaochen Tang
- Department of Clinical Laboratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, P. R. China
| | - Runchi Zhang
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
- Center for Molecular Recognition and Biosensing, School of Life Sciences, Shanghai University, Shanghai 200444, P. R. China
| | - Tianshu Chen
- Department of Clinical Laboratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, P. R. China
| | - Chenbin Liu
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
| | - Hongquan Gou
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
| | - Pei Sun
- Center for Molecular Recognition and Biosensing, School of Life Sciences, Shanghai University, Shanghai 200444, P. R. China
| | - Yichun Mao
- Center for Molecular Recognition and Biosensing, School of Life Sciences, Shanghai University, Shanghai 200444, P. R. China
| | - Jie Deng
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
| | - Wenxing Li
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
| | - Fenyong Sun
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
| | - Xiaoli Zhu
- Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P. R. China
- Center for Molecular Recognition and Biosensing, School of Life Sciences, Shanghai University, Shanghai 200444, P. R. China
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50
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Kim SH, Chun C, Yoon TY. Profiling of BCLxL Protein Complexes in Non-Small Cell Lung Cancer Cells via Multiplexed Single-Molecule Pull-Down and Co-Immunoprecipitation. Anal Chem 2024; 96:8932-8941. [PMID: 38728439 DOI: 10.1021/acs.analchem.3c05801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
We introduce multiplexed single-molecule pull-down and co-immunoprecipitation, named m-SMPC, an analysis tool for profiling multiple protein complexes within a single reaction chamber using single-molecule fluorescence imaging. We employed site-selective conjugation of biotin and fluorescent dye directly onto the monoclonal antibodies, which completed an independent sandwich immunoassay without the issue of host cross-reactivity. We applied this technique to profile endogenous B-cell lymphoma extra-large (BCLxL) complexes in non-small cell lung cancer (NSCLC) cells. Up to three distinct BCLxL complexes were successfully detected simultaneously within a single reaction chamber without fluorescence signal crosstalk. Notably, the NSCLC cell line EBC-1 exhibited high BCLxL-BAX and BCLxL-BAK levels, which closely paralleled a strong response to the BCLxL inhibitor A-1331852. This streamlined method offers the potential for quantitative biomarkers derived from protein complex profiling, paving the way for their application in protein complex-targeted therapies.
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Affiliation(s)
- Shi Ho Kim
- Department of Biomarker Discovery, PROTEINA Co., Ltd, Seoul 08826, South Korea
| | - Changju Chun
- School of Biological Sciences, Seoul National University, Seoul 08826, South Korea
- Institute for Molecular Biology and Genetics, Seoul National University, Seoul 08826, South Korea
| | - Tae-Young Yoon
- Department of Biomarker Discovery, PROTEINA Co., Ltd, Seoul 08826, South Korea
- School of Biological Sciences, Seoul National University, Seoul 08826, South Korea
- Institute for Molecular Biology and Genetics, Seoul National University, Seoul 08826, South Korea
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