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Hofmann J, Kokkaliaris KD. Bone marrow niches for hematopoietic stem cells: life span dynamics and adaptation to acute stress. Blood 2024; 144:21-34. [PMID: 38579285 DOI: 10.1182/blood.2023023788] [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: 01/18/2024] [Revised: 03/28/2024] [Accepted: 03/28/2024] [Indexed: 04/07/2024] Open
Abstract
ABSTRACT Hematopoietic stem cells (HSCs) are instrumental for organismal survival because they are responsible for lifelong production of mature blood lineages in homeostasis and response to external stress. To fulfill their function, HSCs rely on reciprocal interactions with specialized tissue microenvironments, termed HSC niches. From embryonic development to advanced aging, HSCs transition through several hematopoietic organs in which they are supported by distinct extrinsic cues. Here, we describe recent discoveries on how HSC niches collectively adapt to ensure robust hematopoietic function during biological aging and after exposure to acute stress. We also discuss the latest strategies leveraging niche-derived signals to revert aging-associated phenotypes and enhance hematopoietic recovery after myeloablation.
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Affiliation(s)
- Johanna Hofmann
- Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany
- Department 15, Biosciences, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | - Konstantinos D Kokkaliaris
- Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, Quantitative Spatial Cancer Biology Laboratory, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, Frankfurt am Main, Germany
- University Cancer Center, Frankfurt am Main, Germany
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Sarachakov A, Varlamova A, Svekolkin V, Polyakova M, Valencia I, Unkenholz C, Pannellini T, Galkin I, Ovcharov P, Tabakov D, Postovalova E, Shin N, Sethi I, Bagaev A, Itkin T, Crane G, Kluk M, Geyer J, Inghirami G, Patel S. Spatial mapping of human hematopoiesis at single-cell resolution reveals aging-associated topographic remodeling. Blood 2023; 142:2282-2295. [PMID: 37774374 DOI: 10.1182/blood.2023021280] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/01/2023] Open
Abstract
ABSTRACT The spatial anatomy of hematopoiesis in the bone marrow (BM) has been extensively studied in mice and other preclinical models, but technical challenges have precluded a commensurate exploration in humans. Institutional pathology archives contain thousands of paraffinized BM core biopsy tissue specimens, providing a rich resource for studying the intact human BM topography in a variety of physiologic states. Thus, we developed an end-to-end pipeline involving multiparameter whole tissue staining, in situ imaging at single-cell resolution, and artificial intelligence-based digital whole slide image analysis and then applied it to a cohort of disease-free samples to survey alterations in the hematopoietic topography associated with aging. Our data indicate heterogeneity in marrow adipose tissue (MAT) content within each age group and an inverse correlation between MAT content and proportions of early myeloid and erythroid precursors, irrespective of age. We identify consistent endosteal and perivascular positioning of hematopoietic stem and progenitor cells (HSPCs) with medullary localization of more differentiated elements and, importantly, uncover new evidence of aging-associated changes in cellular and vascular morphologies, microarchitectural alterations suggestive of foci with increased lymphocytes, and diminution of a potentially active megakaryocytic niche. Overall, our findings suggest that there is topographic remodeling of human hematopoiesis associated with aging. More generally, we demonstrate the potential to deeply unravel the spatial biology of normal and pathologic human BM states using intact archival tissue specimens.
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Affiliation(s)
| | | | | | | | - Itzel Valencia
- Multiparametric In Situ Imaging Laboratory, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY
| | - Caitlin Unkenholz
- Multiparametric In Situ Imaging Laboratory, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY
| | - Tania Pannellini
- Multiparametric In Situ Imaging Laboratory, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY
| | | | | | | | | | | | | | | | - Tomer Itkin
- Division of Regenerative Medicine, Department of Medicine, Hartman Institute for Therapeutic Organ Regeneration, Ansary Stem Cell Institute, Weill Cornell Medicine, New York, NY
| | - Genevieve Crane
- Department of Laboratory Medicine, Cleveland Clinic, Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland, OH
| | - Michael Kluk
- Division of Hematopathology, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, NY
| | - Julia Geyer
- Division of Hematopathology, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, NY
| | - Giorgio Inghirami
- Division of Hematopathology, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, NY
| | - Sanjay Patel
- Multiparametric In Situ Imaging Laboratory, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY
- Division of Hematopathology, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, NY
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Ryou H, Lomas O, Theissen H, Thomas E, Rittscher J, Royston D. Quantitative interpretation of bone marrow biopsies in MPN-What's the point in a molecular age? Br J Haematol 2023; 203:523-535. [PMID: 37858962 PMCID: PMC10952168 DOI: 10.1111/bjh.19154] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 09/20/2023] [Accepted: 09/30/2023] [Indexed: 10/21/2023]
Abstract
The diagnosis of myeloproliferative neoplasms (MPN) requires the integration of clinical, morphological, genetic and immunophenotypic findings. Recently, there has been a transformation in our understanding of the cellular and molecular mechanisms underlying disease initiation and progression in MPN. This has been accompanied by the widespread application of high-resolution quantitative molecular techniques. By contrast, microscopic interpretation of bone marrow biopsies by haematologists/haematopathologists remains subjective and qualitative. However, advances in tissue image analysis and artificial intelligence (AI) promise to transform haematopathology. Pioneering studies in bone marrow image analysis offer to refine our understanding of the boundaries between reactive samples and MPN subtypes and better capture the morphological correlates of high-risk disease. They also demonstrate potential to improve the evaluation of current and novel therapeutics for MPN and other blood cancers. With increased therapeutic targeting of diverse molecular, cellular and extra-cellular components of the marrow, these approaches can address the unmet need for improved objective and quantitative measures of disease modification in the context of clinical trials. This review focuses on the state-of-the-art in image analysis/AI of bone marrow tissue, with an emphasis on its potential to complement and inform future clinical studies and research in MPN.
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Affiliation(s)
- Hosuk Ryou
- Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
| | - Oliver Lomas
- Department of HaematologyOxford University Hospitals NHS Foundation TrustOxfordUK
| | - Helen Theissen
- Department of Engineering Science, Institute of Biomedical Engineering (IBME)University of OxfordOxfordUK
| | - Emily Thomas
- Department of Engineering Science, Institute of Biomedical Engineering (IBME)University of OxfordOxfordUK
| | - Jens Rittscher
- Department of Engineering Science, Institute of Biomedical Engineering (IBME)University of OxfordOxfordUK
- Ground Truth LabsOxfordUK
- Oxford NIHR Biomedical Research CentreOxford University Hospitals NHS Foundation TrustOxfordUK
- Ludwig Institute for Cancer ResearchUniversity of OxfordOxfordUK
| | - Daniel Royston
- Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
- Department of PathologyOxford University Hospitals NHS Foundation TrustOxfordUK
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van Eekelen L, Litjens G, Hebeda KM. Artificial Intelligence in Bone Marrow Histological Diagnostics: Potential Applications and Challenges. Pathobiology 2023; 91:8-17. [PMID: 36791682 PMCID: PMC10937040 DOI: 10.1159/000529701] [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: 12/30/2022] [Accepted: 02/13/2023] [Indexed: 02/17/2023] Open
Abstract
The expanding digitalization of routine diagnostic histological slides holds a potential to apply artificial intelligence (AI) to pathology, including bone marrow (BM) histology. In this perspective, we describe potential tasks in diagnostics that can be supported, investigations that can be guided, and questions that can be answered by the future application of AI on whole-slide images of BM biopsies. These range from characterization of cell lineages and quantification of cells and stromal structures to disease prediction. First glimpses show an exciting potential to detect subtle phenotypic changes with AI that are due to specific genotypes. The discussion is illustrated by examples of current AI research using BM biopsy slides. In addition, we briefly discuss current challenges for implementation of AI-supported diagnostics.
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Affiliation(s)
- Leander van Eekelen
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
- Computational Pathology Group, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Geert Litjens
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
- Computational Pathology Group, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Konnie M. Hebeda
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
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