1
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Waldvogel SM, Posey JE, Goodell MA. Human embryonic genetic mosaicism and its effects on development and disease. Nat Rev Genet 2024; 25:698-714. [PMID: 38605218 PMCID: PMC11408116 DOI: 10.1038/s41576-024-00715-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] [Accepted: 02/22/2024] [Indexed: 04/13/2024]
Abstract
Nearly every mammalian cell division is accompanied by a mutational event that becomes fixed in a daughter cell. When carried forward to additional cell progeny, a clone of variant cells can emerge. As a result, mammals are complex mosaics of clones that are genetically distinct from one another. Recent high-throughput sequencing studies have revealed that mosaicism is common, clone sizes often increase with age and specific variants can affect tissue function and disease development. Variants that are acquired during early embryogenesis are shared by multiple cell types and can affect numerous tissues. Within tissues, variant clones compete, which can result in their expansion or elimination. Embryonic mosaicism has clinical implications for genetic disease severity and transmission but is likely an under-recognized phenomenon. To better understand its implications for mosaic individuals, it is essential to leverage research tools that can elucidate the mechanisms by which expanded embryonic variants influence development and disease.
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Affiliation(s)
- Sarah M Waldvogel
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, USA
- Graduate Program in Cancer and Cell Biology, Baylor College of Medicine, Houston, TX, USA
| | - Jennifer E Posey
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Margaret A Goodell
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA.
- Graduate Program in Cancer and Cell Biology, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
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2
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Faiz M, Kalev-Zylinska ML, Dunstan-Harrison C, Singleton DC, Hay MP, Ledgerwood EC. Megakaryocyte maturation involves activation of the adaptive unfolded protein response. Genes Cells 2024; 29:889-901. [PMID: 39138929 DOI: 10.1111/gtc.13151] [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: 02/12/2024] [Revised: 07/21/2024] [Accepted: 07/26/2024] [Indexed: 08/15/2024]
Abstract
Endoplasmic reticulum stress triggers the unfolded protein response (UPR) to promote cell survival or apoptosis. Transient endoplasmic reticulum stress activation has been reported to trigger megakaryocyte production, and UPR activation has been reported as a feature of megakaryocytic cancers. However, the role of UPR signaling in megakaryocyte biology is not fully understood. We studied the involvement of UPR in human megakaryocytic differentiation using PMA (phorbol 12-myristate 13-acetate)-induced maturation of megakaryoblastic cell lines and thrombopoietin-induced differentiation of human peripheral blood-derived progenitors. Our results demonstrate that an adaptive UPR is a feature of megakaryocytic differentiation and that this response is not associated with ER stress-induced apoptosis. Differentiation did not alter the response to the canonical endoplasmic reticulum stressors DTT or thapsigargin. However, thapsigargin, but not DTT, inhibited differentiation, consistent with the involvement of Ca2+ signaling in megakaryocyte differentiation.
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Affiliation(s)
- Mifra Faiz
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Maggie L Kalev-Zylinska
- Blood and Cancer Biology Laboratory, Department of Molecular Medicine & Pathology, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Caitlin Dunstan-Harrison
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
| | - Dean C Singleton
- Auckland Cancer Society Research Centre, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Michael P Hay
- Auckland Cancer Society Research Centre, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
| | - Elizabeth C Ledgerwood
- Department of Biochemistry, School of Biomedical Sciences, University of Otago, Dunedin, New Zealand
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3
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Laplane L, Maley CC. The evolutionary theory of cancer: challenges and potential solutions. Nat Rev Cancer 2024; 24:718-733. [PMID: 39256635 DOI: 10.1038/s41568-024-00734-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/24/2024] [Indexed: 09/12/2024]
Abstract
The clonal evolution model of cancer was developed in the 1950s-1970s and became central to cancer biology in the twenty-first century, largely through studies of cancer genetics. Although it has proven its worth, its structure has been challenged by observations of phenotypic plasticity, non-genetic forms of inheritance, non-genetic determinants of clone fitness and non-tree-like transmission of genes. There is even confusion about the definition of a clone, which we aim to resolve. The performance and value of the clonal evolution model depends on the empirical extent to which evolutionary processes are involved in cancer, and on its theoretical ability to account for those evolutionary processes. Here, we identify limits in the theoretical performance of the clonal evolution model and provide solutions to overcome those limits. Although we do not claim that clonal evolution can explain everything about cancer, we show how many of the complexities that have been identified in the dynamics of cancer can be integrated into the model to improve our current understanding of cancer.
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Affiliation(s)
- Lucie Laplane
- UMR 8590 Institut d'Histoire et Philosophie des Sciences et des Techniques, CNRS, University Paris I Pantheon-Sorbonne, Paris, France
- UMR 1287 Hematopoietic Tissue Aging, Gustave Roussy Cancer Campus, Villejuif, France
| | - Carlo C Maley
- Arizona Cancer Evolution Center, Arizona State University, Tempe, AZ, USA.
- School of Life Sciences, Arizona State University, Tempe, AZ, USA.
- Biodesign Center for Biocomputing, Security and Society, Arizona State University, Tempe, AZ, USA.
- Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA.
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4
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Jin X, Zhang R, Fu Y, Zhu Q, Hong L, Wu A, Wang H. Unveiling aging dynamics in the hematopoietic system insights from single-cell technologies. Brief Funct Genomics 2024; 23:639-650. [PMID: 38688725 DOI: 10.1093/bfgp/elae019] [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: 02/10/2024] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 05/02/2024] Open
Abstract
As the demographic structure shifts towards an aging society, strategies aimed at slowing down or reversing the aging process become increasingly essential. Aging is a major predisposing factor for many chronic diseases in humans. The hematopoietic system, comprising blood cells and their associated bone marrow microenvironment, intricately participates in hematopoiesis, coagulation, immune regulation and other physiological phenomena. The aging process triggers various alterations within the hematopoietic system, serving as a spectrum of risk factors for hematopoietic disorders, including clonal hematopoiesis, immune senescence, myeloproliferative neoplasms and leukemia. The emerging single-cell technologies provide novel insights into age-related changes in the hematopoietic system. In this review, we summarize recent studies dissecting hematopoietic system aging using single-cell technologies. We discuss cellular changes occurring during aging in the hematopoietic system at the levels of the genomics, transcriptomics, epigenomics, proteomics, metabolomics and spatial multi-omics. Finally, we contemplate the future prospects of single-cell technologies, emphasizing the impact they may bring to the field of hematopoietic system aging research.
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Affiliation(s)
- Xinrong Jin
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Ruohan Zhang
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Yunqi Fu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Qiunan Zhu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Liquan Hong
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Aiwei Wu
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
| | - Hu Wang
- Zhejiang Key Laboratory of Medical Epigenetics, School of Basic Medical Sciences, The Third People's Hospital of Deqing, Deqing Hospital of Hangzhou Normal University, Hangzhou Normal University, Hangzhou 311121, China
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5
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Shivarov V, Tsvetkova G, Micheva I, Hadjiev E, Petrova J, Ivanova A, Madjarova G, Ivanova M. Differential modulation of mutant CALR and JAK2 V617F-driven oncogenesis by HLA genotype in myeloproliferative neoplasms. Front Immunol 2024; 15:1427810. [PMID: 39351227 PMCID: PMC11439724 DOI: 10.3389/fimmu.2024.1427810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 08/26/2024] [Indexed: 10/04/2024] Open
Abstract
It has been demonstrated previously that human leukocyte antigen class I (HLA-I) and class II (HLA-II) alleles may modulate JAK2 V617F and CALR mutation (CALRmut)-associated oncogenesis in myeloproliferative neoplasms (MPNs). However, the role of immunogenetic factors in MPNs remains underexplored. We aimed to investigate the potential involvement of HLA genes in CALRmut+ MPNs. High-resolution genotyping of HLA-I and -II loci was conducted in 42 CALRmut+ and 158 JAK2 V617F+ MPN patients and 1,083 healthy controls. A global analysis of the diversity of HLA-I genotypes revealed no significant differences between CALRmut+ patients and controls. However, one HLA-I allele (C*06:02) showed an inverse correlation with presence of CALR mutation. A meta-analysis across independent cohorts and healthy individuals from the 1000 Genomes Project confirmed an inverse correlation between the presentation capabilities of the HLA-I loci for JAK2 V617F and CALRmut-derived peptides in both patients and healthy individuals. scRNA-Seq analysis revealed low expression of TAP1 and CIITA genes in CALRmut+ hematopoietic stem and progenitor cells. In conclusion, the HLA-I genotype differentially restricts JAK2 V617F and CALRmut-driven oncogenesis potentially explaining the mutual exclusivity of the two mutations and differences in their presentation latency. These findings have practical implications for the development of neoantigen-based vaccines in MPNs.
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Affiliation(s)
- Velizar Shivarov
- Department of Experimental Research, Medical University Pleven, Pleven, Bulgaria
| | - Gergana Tsvetkova
- Department of Clinical Hematology, Alexandrovska University Hospital, Medical University Sofia, Sofia, Bulgaria
| | - Ilina Micheva
- Department of Clinical Hematology, Saint Marina University Hospital, Medical University Varna, Varna, Bulgaria
| | - Evgueniy Hadjiev
- Department of Clinical Hematology, Alexandrovska University Hospital, Medical University Sofia, Sofia, Bulgaria
| | - Jasmina Petrova
- Department of Physical Chemistry, Faculty of Chemistry and Pharmacy, Sofia University “St. Kl. Ohridski”, Sofia, Bulgaria
| | - Anela Ivanova
- Department of Physical Chemistry, Faculty of Chemistry and Pharmacy, Sofia University “St. Kl. Ohridski”, Sofia, Bulgaria
| | - Galia Madjarova
- Department of Physical Chemistry, Faculty of Chemistry and Pharmacy, Sofia University “St. Kl. Ohridski”, Sofia, Bulgaria
| | - Milena Ivanova
- Department of Clinical Immunology, Alexandrovska University Hospital, Medical University Sofia, Sofia, Bulgaria
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6
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Pessoa Rodrigues C, Collins JM, Yang S, Martinez C, Kim JW, Lama C, Nam AS, Alt C, Lin C, Zon LI. Transcripts of repetitive DNA elements signal to block phagocytosis of hematopoietic stem cells. Science 2024; 385:eadn1629. [PMID: 39264994 DOI: 10.1126/science.adn1629] [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: 11/26/2023] [Revised: 04/09/2024] [Accepted: 07/04/2024] [Indexed: 09/14/2024]
Abstract
Macrophages maintain hematopoietic stem cell (HSC) quality by assessing cell surface Calreticulin (Calr), an "eat-me" signal induced by reactive oxygen species (ROS). Using zebrafish genetics, we identified Beta-2-microglobulin (B2m) as a crucial "don't eat-me" signal on blood stem cells. A chemical screen revealed inducers of surface Calr that promoted HSC proliferation without triggering ROS or macrophage clearance. Whole-genome CRISPR-Cas9 screening showed that Toll-like receptor 3 (Tlr3) signaling regulated b2m expression. Targeting b2m or tlr3 reduced the HSC clonality. Elevated B2m levels correlated with high expression of repetitive element (RE) transcripts. Overall, our data suggest that RE-associated double-stranded RNA could interact with TLR3 to stimulate surface expression of B2m on hematopoietic stem and progenitor cells. These findings suggest that the balance of Calr and B2m regulates macrophage-HSC interactions and defines hematopoietic clonality.
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Affiliation(s)
- Cecilia Pessoa Rodrigues
- Howard Hughes Medical Institute, Boston Children's Hospital Boston, MA, USA
- Harvard Stem Cell Institute, Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Joseph M Collins
- Howard Hughes Medical Institute, Boston Children's Hospital Boston, MA, USA
- Harvard Stem Cell Institute, Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Song Yang
- Howard Hughes Medical Institute, Boston Children's Hospital Boston, MA, USA
| | - Catherine Martinez
- Harvard Stem Cell Institute, Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Ji Wook Kim
- Howard Hughes Medical Institute, Boston Children's Hospital Boston, MA, USA
- Harvard Stem Cell Institute, Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
| | - Chhiring Lama
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Anna S Nam
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Clemens Alt
- Wellman Center for Photomedicine, Mass General Research Institute, Boston, MA, USA
| | - Charles Lin
- Wellman Center for Photomedicine, Mass General Research Institute, Boston, MA, USA
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Leonard I Zon
- Howard Hughes Medical Institute, Boston Children's Hospital Boston, MA, USA
- Harvard Stem Cell Institute, Stem Cell and Regenerative Biology Department, Harvard University, Cambridge, MA, USA
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7
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Tirosh I, Suva ML. Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors. Cancer Cell 2024; 42:1497-1506. [PMID: 39214095 DOI: 10.1016/j.ccell.2024.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 07/22/2024] [Accepted: 08/06/2024] [Indexed: 09/04/2024]
Abstract
Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.
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Affiliation(s)
- Itay Tirosh
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 761001, Israel.
| | - Mario L Suva
- Department of Pathology and Krantz Family Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
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8
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Safina K, van Galen P. New frameworks for hematopoiesis derived from single-cell genomics. Blood 2024; 144:1039-1047. [PMID: 38985829 DOI: 10.1182/blood.2024024006] [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: 04/25/2024] [Revised: 06/21/2024] [Accepted: 06/22/2024] [Indexed: 07/12/2024] Open
Abstract
ABSTRACT Recent advancements in single-cell genomics have enriched our understanding of hematopoiesis, providing intricate details about hematopoietic stem cell biology, differentiation, and lineage commitment. Technological advancements have highlighted extensive heterogeneity of cell populations and continuity of differentiation routes. Nevertheless, intermediate "attractor" states signify structure in stem and progenitor populations that link state transition dynamics to fate potential. We discuss how innovative model systems quantify lineage bias and how stress accelerates differentiation, thereby reducing fate plasticity compared with native hematopoiesis. We conclude by offering our perspective on the current model of hematopoiesis and discuss how a more precise understanding can translate to strategies that extend healthy hematopoiesis and prevent disease.
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Affiliation(s)
- Ksenia Safina
- Division of Hematology, Brigham and Women's Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
- Ludwig Center at Harvard, Boston, MA
| | - Peter van Galen
- Division of Hematology, Brigham and Women's Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
- Ludwig Center at Harvard, Boston, MA
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9
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Marot-Lassauzaie V, Beneyto-Calabuig S, Obermayer B, Velten L, Beule D, Haghverdi L. Identifying cancer cells from calling single-nucleotide variants in scRNA-seq data. BIOINFORMATICS (OXFORD, ENGLAND) 2024; 40:btae512. [PMID: 39163479 PMCID: PMC11379463 DOI: 10.1093/bioinformatics/btae512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 06/14/2024] [Accepted: 08/15/2024] [Indexed: 08/22/2024]
Abstract
MOTIVATION Single-cell RNA sequencing (scRNA-seq) data are widely used to study cancer cell states and their heterogeneity. However, the tumour microenvironment is usually a mixture of healthy and cancerous cells and it can be difficult to fully separate these two populations based on transcriptomics alone. If available, somatic single-nucleotide variants (SNVs) observed in the scRNA-seq data could be used to identify the cancer population and match that information with the single cells' expression profile. However, calling somatic SNVs in scRNA-seq data is a challenging task, as most variants seen in the short-read data are not somatic, but can instead be germline variants, RNA edits or transcription, sequencing, or processing errors. In addition, only variants present in actively transcribed regions for each individual cell will be seen in the data. RESULTS To address these challenges, we develop CCLONE (Cancer Cell Labelling On Noisy Expression), an interpretable tool adapted to handle the uncertainty and sparsity of SNVs called from scRNA-seq data. CCLONE jointly identifies cancer clonal populations, and their associated variants. We apply CCLONE on two acute myeloid leukaemia datasets and one lung adenocarcinoma dataset and show that CCLONE captures both genetic clones and somatic events for multiple patients. These results show how CCLONE can be used to gather insight into the course of the disease and the origin of cancer cells in scRNA-seq data. AVAILABILITY AND IMPLEMENTATION Source code is available at github.com/HaghverdiLab/CCLONE.
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Affiliation(s)
- Valérie Marot-Lassauzaie
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Hannoversche Str. 28, 10115 Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Sergi Beneyto-Calabuig
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Benedikt Obermayer
- Core Unit Bioinformatics, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Lars Velten
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Dieter Beule
- Core Unit Bioinformatics, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Robert-Rössle-Str. 10, 13125 Berlin, Germany
| | - Laleh Haghverdi
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Hannoversche Str. 28, 10115 Berlin, Germany
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10
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Hockemeyer K, Sakellaropoulos T, Chen X, Ivashkiv O, Sirenko M, Zhou H, Gambi G, Battistello E, Avrampou K, Sun Z, Guillamot M, Chiriboga L, Jour G, Dolgalev I, Corrigan K, Bhatt K, Osman I, Tsirigos A, Kourtis N, Aifantis I. The stress response regulator HSF1 modulates natural killer cell anti-tumour immunity. Nat Cell Biol 2024:10.1038/s41556-024-01490-z. [PMID: 39223375 DOI: 10.1038/s41556-024-01490-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 07/18/2024] [Indexed: 09/04/2024]
Abstract
Diverse cellular insults converge on activation of the heat shock factor 1 (HSF1), which regulates the proteotoxic stress response to maintain protein homoeostasis. HSF1 regulates numerous gene programmes beyond the proteotoxic stress response in a cell-type- and context-specific manner to promote malignancy. However, the role(s) of HSF1 in immune populations of the tumour microenvironment remain elusive. Here, we leverage an in vivo model of HSF1 activation and single-cell transcriptomic tumour profiling to show that augmented HSF1 activity in natural killer (NK) cells impairs cytotoxicity, cytokine production and subsequent anti-tumour immunity. Mechanistically, HSF1 directly binds and regulates the expression of key mediators of NK cell effector function. This work demonstrates that HSF1 regulates the immune response under the stress conditions of the tumour microenvironment. These findings have important implications for enhancing the efficacy of adoptive NK cell therapies and for designing combinatorial strategies including modulators of NK cell-mediated tumour killing.
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Affiliation(s)
- Kathryn Hockemeyer
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Theodore Sakellaropoulos
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
- Applied Bioinformatics Laboratories, NYU Langone Medical Center, New York, NY, USA
| | - Xufeng Chen
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Olha Ivashkiv
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Maria Sirenko
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Hua Zhou
- Applied Bioinformatics Laboratories, NYU Langone Medical Center, New York, NY, USA
| | - Giovanni Gambi
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Elena Battistello
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Kleopatra Avrampou
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Zhengxi Sun
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Maria Guillamot
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Luis Chiriboga
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
| | - George Jour
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA
| | - Igor Dolgalev
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
- Applied Bioinformatics Laboratories, NYU Langone Medical Center, New York, NY, USA
| | - Kate Corrigan
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Kamala Bhatt
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
| | - Iman Osman
- Ronald O. Perelman Department of Dermatology, NYU Grossman School of Medicine, New York, NY, USA
- Department of Urology, NYU Grossman School of Medicine, New York, NY, USA
- Interdisciplinary Melanoma Cooperative Group, NYU Langone Medical Center, New York, NY, USA
- Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA
| | - Aristotelis Tsirigos
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA
- Applied Bioinformatics Laboratories, NYU Langone Medical Center, New York, NY, USA
- Department of Medicine, NYU Grossman School of Medicine, New York, NY, USA
| | - Nikos Kourtis
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA.
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA.
- Regeneron Pharmaceuticals, Tarrytown, NY, USA.
| | - Iannis Aifantis
- Department of Pathology, NYU Grossman School of Medicine, New York, NY, USA.
- Laura & Isaac Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA.
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11
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Aertgeerts M, Meyers S, Demeyer S, Segers H, Cools J. Unlocking the Complexity: Exploration of Acute Lymphoblastic Leukemia at the Single Cell Level. Mol Diagn Ther 2024:10.1007/s40291-024-00739-5. [PMID: 39190087 DOI: 10.1007/s40291-024-00739-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/08/2024] [Indexed: 08/28/2024]
Abstract
Acute lymphoblastic leukemia (ALL) is the most common cancer in children. ALL originates from precursor lymphocytes that acquire multiple genomic changes over time, including chromosomal rearrangements and point mutations. While a large variety of genomic defects was identified and characterized in ALL over the past 30 years, it was only in recent years that the clonal heterogeneity was recognized. Thanks to the latest advancements in single-cell sequencing techniques, which have evolved from the analysis of a few hundred cells to the analysis of thousands of cells simultaneously, the study of tumor heterogeneity now becomes possible. Different modalities can be explored at the single-cell level: DNA, RNA, epigenetic modifications, and intracellular and cell surface proteins. In this review, we describe these techniques and highlight their advantages and limitations in the study of ALL biology. Moreover, multiomics technologies and the incorporation of the spatial dimension can provide insight into intercellular communication. We describe how the different single-cell sequencing technologies help to unravel the molecular complexity of ALL, shedding light on its development, its heterogeneity, its interaction with the leukemia microenvironment and possible relapse mechanisms.
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Affiliation(s)
- Margo Aertgeerts
- Department of Oncology, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven-UZ Leuven, Leuven, Belgium
| | - Sarah Meyers
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven-UZ Leuven, Leuven, Belgium
| | - Sofie Demeyer
- Department of Human Genetics, KU Leuven, Leuven, Belgium
- Center for Cancer Biology, VIB, Leuven, Belgium
- Leuvens Kanker Instituut (LKI), KU Leuven-UZ Leuven, Leuven, Belgium
| | - Heidi Segers
- Department of Oncology, KU Leuven, Leuven, Belgium.
- Leuvens Kanker Instituut (LKI), KU Leuven-UZ Leuven, Leuven, Belgium.
- Department of Pediatric Hematology and Oncology, UZ Leuven, Leuven, Belgium.
| | - Jan Cools
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Center for Cancer Biology, VIB, Leuven, Belgium.
- Leuvens Kanker Instituut (LKI), KU Leuven-UZ Leuven, Leuven, Belgium.
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12
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Poort VM, Hagelaar R, van Roosmalen MJ, Trabut L, Buijs-Gladdines JGCAM, van Wijk B, Meijerink J, van Boxtel R. Transient Differentiation-State Plasticity Occurs during Acute Lymphoblastic Leukemia Initiation. Cancer Res 2024; 84:2720-2733. [PMID: 38885294 PMCID: PMC11325147 DOI: 10.1158/0008-5472.can-24-1090] [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: 04/01/2024] [Revised: 04/20/2024] [Accepted: 06/10/2024] [Indexed: 06/20/2024]
Abstract
Leukemia is characterized by oncogenic lesions that result in a block of differentiation, whereas phenotypic plasticity is retained. A better understanding of how these two phenomena arise during leukemogenesis in humans could help inform diagnosis and treatment strategies. Here, we leveraged the well-defined differentiation states during T-cell development to pinpoint the initiation of T-cell acute lymphoblastic leukemia (T-ALL), an aggressive form of childhood leukemia, and study the emergence of phenotypic plasticity. Single-cell whole genome sequencing of leukemic blasts was combined with multiparameter flow cytometry to couple cell identity and clonal lineages. Irrespective of genetic events, leukemia-initiating cells altered their phenotypes by differentiation and dedifferentiation. The construction of the phylogenies of individual leukemias using somatic mutations revealed that phenotypic diversity is reflected by the clonal structure of cancer. The analysis also indicated that the acquired phenotypes are heritable and stable. Together, these results demonstrate a transient period of plasticity during leukemia initiation, where phenotypic switches seem unidirectional. Significance: A method merging multicolor flow cytometry with single-cell whole genome sequencing to couple cell identity with clonal lineages uncovers differentiation-state plasticity in leukemia, reconciling blocked differentiation with phenotypic plasticity in cancer.
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Affiliation(s)
- Vera M Poort
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Rico Hagelaar
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Markus J van Roosmalen
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Laurianne Trabut
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | | | - Bram van Wijk
- Department of Pediatric Cardiothoracic Surgery, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jules Meijerink
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
| | - Ruben van Boxtel
- Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
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13
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Ghosh G, Shannon AE, Searle BC. Data acquisition approaches for single cell proteomics. Proteomics 2024:e2400022. [PMID: 39088833 DOI: 10.1002/pmic.202400022] [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: 05/18/2024] [Revised: 07/09/2024] [Accepted: 07/10/2024] [Indexed: 08/03/2024]
Abstract
Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.
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Affiliation(s)
- Gautam Ghosh
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio, USA
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA
| | - Ariana E Shannon
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA
- Department of Biomedical Informatics, The Ohio State University Medical Center, Columbus, Ohio, USA
| | - Brian C Searle
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio, USA
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA
- Department of Biomedical Informatics, The Ohio State University Medical Center, Columbus, Ohio, USA
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14
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Heimlich JB, Bhat P, Parker AC, Jenkins MT, Vlasschaert C, Ulloa J, Van Amburg JC, Potts CR, Olson S, Silver AJ, Ahmad A, Sharber B, Brown D, Hu N, van Galen P, Savona MR, Bick AG, Ferrell PB. Multiomic profiling of human clonal hematopoiesis reveals genotype and cell-specific inflammatory pathway activation. Blood Adv 2024; 8:3665-3678. [PMID: 38507736 DOI: 10.1182/bloodadvances.2023011445] [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: 08/14/2023] [Revised: 02/08/2024] [Accepted: 02/08/2024] [Indexed: 03/22/2024] Open
Abstract
ABSTRACT Clonal hematopoiesis (CH) is an age-associated phenomenon that increases the risk of hematologic malignancy and cardiovascular disease. CH is thought to enhance disease risk through inflammation in the peripheral blood.1 Here, we profile peripheral blood gene expression in 66 968 single cells from a cohort of 17 patients with CH and 7 controls. Using a novel mitochondrial DNA barcoding approach, we were able to identify and separately compare mutant Tet methylcytosine dioxygenase 2 (TET2) and DNA methyltransferase 3A (DNMT3A) cells with nonmutant counterparts. We discovered the vast majority of mutated cells were in the myeloid compartment. Additionally, patients harboring DNMT3A and TET2 CH mutations possessed a proinflammatory profile in CD14+ monocytes through previously unrecognized pathways such as galectin and macrophage inhibitory factor. We also found that T cells from patients with CH, although mostly unmutated, had decreased expression of GTPase of the immunity associated protein genes, which are critical to T-cell development, suggesting that CH impairs T-cell function.
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Affiliation(s)
- J Brett Heimlich
- Division of Cardiovascular Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Pawan Bhat
- Vanderbilt University School of Medicine, Nashville, TN
| | | | | | | | - Jessica Ulloa
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Joseph C Van Amburg
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Chad R Potts
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Sydney Olson
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | | | - Ayesha Ahmad
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Brian Sharber
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Donovan Brown
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Ningning Hu
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Peter van Galen
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Boston, MA
- Ludwig Center at Harvard, Harvard Medical School, Boston, MA
| | - Michael R Savona
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
- Vanderbilt-Ingram Cancer Center, Program in Cancer Biology, and Center for Immunobiology, Nashville, TN
- Center for Immunobiology, Vanderbilt University School of Medicine, Nashville, TN
| | - Alexander G Bick
- Division of Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - P Brent Ferrell
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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15
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Kim GD, Shin SI, Jung SW, An H, Choi SY, Eun M, Jun CD, Lee S, Park J. Cell Type- and Age-Specific Expression of lncRNAs across Kidney Cell Types. J Am Soc Nephrol 2024; 35:870-885. [PMID: 38621182 PMCID: PMC11230714 DOI: 10.1681/asn.0000000000000354] [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: 12/06/2023] [Accepted: 04/08/2024] [Indexed: 04/17/2024] Open
Abstract
Key Points
We constructed a single-cell long noncoding RNA atlas of various tissues, including normal and aged kidneys.We identified age- and cell type–specific expression changes of long noncoding RNAs in kidney cells.
Background
Accumulated evidence demonstrates that long noncoding RNAs (lncRNAs) regulate cell differentiation and homeostasis, influencing kidney aging and disease. Despite their versatility, the function of lncRNA remains poorly understood because of the lack of a reference map of lncRNA transcriptome in various cell types.
Methods
In this study, we used a targeted single-cell RNA sequencing method to enrich and characterize lncRNAs in individual cells. We applied this method to various mouse tissues, including normal and aged kidneys.
Results
Through tissue-specific clustering analysis, we identified cell type–specific lncRNAs that showed a high correlation with known cell-type marker genes. Furthermore, we constructed gene regulatory networks to explore the functional roles of differentially expressed lncRNAs in each cell type. In the kidney, we observed dynamic expression changes of lncRNAs during aging, with specific changes in glomerular cells. These cell type– and age-specific expression patterns of lncRNAs suggest that lncRNAs may have a potential role in regulating cellular processes, such as immune response and energy metabolism, during kidney aging.
Conclusions
Our study sheds light on the comprehensive landscape of lncRNA expression and function and provides a valuable resource for future analysis of lncRNAs (https://gist-fgl.github.io/sc-lncrna-atlas/).
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Affiliation(s)
- Gyeong Dae Kim
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - So-I Shin
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Su Woong Jung
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
- Division of Nephrology, Department of Internal Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Hyunsu An
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Sin Young Choi
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Minho Eun
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Chang-Duk Jun
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Sangho Lee
- Division of Nephrology, Department of Internal Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Jihwan Park
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
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16
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Frenkel M, Raman S. Discovering mechanisms of human genetic variation and controlling cell states at scale. Trends Genet 2024; 40:587-600. [PMID: 38658256 DOI: 10.1016/j.tig.2024.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 03/29/2024] [Accepted: 03/29/2024] [Indexed: 04/26/2024]
Abstract
Population-scale sequencing efforts have catalogued substantial genetic variation in humans such that variant discovery dramatically outpaces interpretation. We discuss how single-cell sequencing is poised to reveal genetic mechanisms at a rate that may soon approach that of variant discovery. The functional genomics toolkit is sufficiently modular to systematically profile almost any type of variation within increasingly diverse contexts and with molecularly comprehensive and unbiased readouts. As a result, we can construct deep phenotypic atlases of variant effects that span the entire regulatory cascade. The same conceptual approach to interpreting genetic variation should be applied to engineering therapeutic cell states. In this way, variant mechanism discovery and cell state engineering will become reciprocating and iterative processes towards genomic medicine.
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Affiliation(s)
- Max Frenkel
- Cellular and Molecular Biology Graduate Program, University of Wisconsin, Madison, WI, USA; Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Biochemistry, University of Wisconsin, Madison, WI, USA.
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA; Department of Bacteriology, University of Wisconsin, Madison, WI, USA; Department of Chemical and Biological Engineering, University of Wisconsin, Madison, WI, USA.
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17
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Ganesan S, Cortés-López M, Swett AD, Dai X, Hickey S, Chamely P, Hawkins AG, Juul S, Landau DA, Gaiti F. GoT-Splice protocol for multi-omics profiling of gene expression, cell-surface proteins, mutational status, and RNA splicing in human cells. STAR Protoc 2024; 5:102966. [PMID: 38512867 PMCID: PMC10966806 DOI: 10.1016/j.xpro.2024.102966] [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: 11/27/2023] [Revised: 01/25/2024] [Accepted: 03/04/2024] [Indexed: 03/23/2024] Open
Abstract
Studying RNA splicing factor mutations is challenging due to difficulties in distinguishing wild-type and mutant cells within complex human tissues and inaccuracies associated with reconstructing splicing signals from short-read sequencing data. Here, we present Genotyping of Transcriptomes (GoT)-Splice, a protocol that overcomes these limitations by combining GoT with enhanced long-read single-cell transcriptome and cell-surface proteomics profiling. We describe steps for long-read library preparation and analysis, followed by cDNA re-amplification, enrichment of mutation of interest, sample indexing, and GoT library preparation. For complete details on the use and execution of this protocol, please refer to Cortés-López et al.1.
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Affiliation(s)
- Saravanan Ganesan
- New York Genome Center, New York, NY 10013, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA.
| | - Mariela Cortés-López
- New York Genome Center, New York, NY 10013, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA
| | - Ariel D Swett
- New York Genome Center, New York, NY 10013, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA
| | - Xiaoguang Dai
- Oxford Nanopore Technologies Inc., New York, NY 10013, USA
| | - Scott Hickey
- Oxford Nanopore Technologies Inc., Alameda, CA 94501-1170, USA
| | - Paulina Chamely
- New York Genome Center, New York, NY 10013, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA
| | - Allegra G Hawkins
- Childhood Cancer Data Lab, Alex's Lemonade Stand Foundation for Childhood Cancer, Wynnewood, PA 19096, USA
| | - Sissel Juul
- Oxford Nanopore Technologies Inc., New York, NY 10013, USA
| | - Dan A Landau
- New York Genome Center, New York, NY 10013, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA; Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA.
| | - Federico Gaiti
- University Health Network, Princess Margaret Cancer Centre, Toronto, ON M5G 0A3, Canada; University of Toronto, Medical Biophysics, Toronto, ON M5G 1L7, Canada.
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18
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Li J, Wang Z, Tong L, Wang Q, Rajamani KT, Muñoz-Castañeda R, Mu S, Qi T, Zhang Y, Ngiam ZC, Ohte N, Hanashima C, Wu Z, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development. Cell 2024; 187:3236-3248.e21. [PMID: 38772369 PMCID: PMC11193654 DOI: 10.1016/j.cell.2024.04.050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 11/30/2023] [Accepted: 04/30/2024] [Indexed: 05/23/2024]
Abstract
Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Sean K Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Grace S Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Jiwen Li
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Keerthi T Rajamani
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Rodrigo Muñoz-Castañeda
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Shang Mu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Tianbo Qi
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yunxiao Zhang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zi Chao Ngiam
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Naoto Ohte
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Carina Hanashima
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Zhuhao Wu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Joshua Z Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA.
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19
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Rathgeber AC, Ludwig LS, Penter L. Single-cell genomics-based immune and disease monitoring in blood malignancies. Clin Hematol Int 2024; 6:62-84. [PMID: 38884110 PMCID: PMC11180218 DOI: 10.46989/001c.117961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 12/25/2023] [Indexed: 06/18/2024] Open
Abstract
Achieving long-term disease control using therapeutic immunomodulation is a long-standing concept with a strong tradition in blood malignancies. Besides allogeneic hematopoietic stem cell transplantation that continues to provide potentially curative treatment for otherwise challenging diagnoses, recent years have seen impressive progress in immunotherapies for leukemias and lymphomas with immune checkpoint blockade, bispecific monoclonal antibodies, and CAR T cell therapies. Despite their success, non-response, relapse, and immune toxicities remain frequent, thus prioritizing the elucidation of the underlying mechanisms and identifying predictive biomarkers. The increasing availability of single-cell genomic tools now provides a system's immunology view to resolve the molecular and cellular mechanisms of immunotherapies at unprecedented resolution. Here, we review recent studies that leverage these technological advancements for tracking immune responses, the emergence of immune resistance, and toxicities. As single-cell immune monitoring tools evolve and become more accessible, we expect their wide adoption for routine clinical applications to catalyze more precise therapeutic steering of personal immune responses.
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Affiliation(s)
- Anja C. Rathgeber
- Berlin Institute for Medical Systems BiologyMax Delbrück Center for Molecular Medicine
- Department of Hematology, Oncology, and TumorimmunologyCharité - Universitätsmedizin Berlin
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin
| | - Leif S. Ludwig
- Berlin Institute for Medical Systems BiologyMax Delbrück Center for Molecular Medicine
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin
| | - Livius Penter
- Department of Hematology, Oncology, and TumorimmunologyCharité - Universitätsmedizin Berlin
- BIH Biomedical Innovation AcademyBerlin Institute of Health at Charité - Universitätsmedizin Berlin
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20
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Winter PS, Ramseier ML, Navia AW, Saksena S, Strouf H, Senhaji N, DenAdel A, Mirza M, An HH, Bilal L, Dennis P, Leahy CS, Shigemori K, Galves-Reyes J, Zhang Y, Powers F, Mulugeta N, Gupta AJ, Calistri N, Van Scoyk A, Jones K, Liu H, Stevenson KE, Ren S, Luskin MR, Couturier CP, Amini AP, Raghavan S, Kimmerling RJ, Stevens MM, Crawford L, Weinstock DM, Manalis SR, Shalek AK, Murakami MA. Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597767. [PMID: 38915726 PMCID: PMC11195125 DOI: 10.1101/2024.06.06.597767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.
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Affiliation(s)
- Peter S. Winter
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Michelle L. Ramseier
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Andrew W. Navia
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Sachit Saksena
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Computational and Systems Biology Program, MIT, Cambridge, MA, USA
| | - Haley Strouf
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Nezha Senhaji
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Alan DenAdel
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- Department of Biostatistics, Brown University, Providence, RI, USA
| | - Mahnoor Mirza
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Hyun Hwan An
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Laura Bilal
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Peter Dennis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Catharine S. Leahy
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kay Shigemori
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jennyfer Galves-Reyes
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Ye Zhang
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
| | - Foster Powers
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Nolawit Mulugeta
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | | | - Nicholas Calistri
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Alex Van Scoyk
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kristen Jones
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Huiyun Liu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Siyang Ren
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA USA
| | - Marlise R. Luskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Charles P. Couturier
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | | | - Srivatsan Raghavan
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | - Mark M. Stevens
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
| | - Lorin Crawford
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
- Department of Biostatistics, Brown University, Providence, RI, USA
- Microsoft Research, Cambridge, MA, USA
| | - David M. Weinstock
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Current Address: Merck and Co., Rahway, NJ, USA
| | - Scott R. Manalis
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
| | - Alex K. Shalek
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA
- Institute for Medical Engineering & Science, MIT, Cambridge, MA, USA
- Department of Chemistry, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Mark A. Murakami
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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21
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Zhang Z, Huang J, Zhang Z, Shen H, Tang X, Wu D, Bao X, Xu G, Chen S. Application of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia. Biomark Res 2024; 12:60. [PMID: 38858750 PMCID: PMC11165883 DOI: 10.1186/s40364-024-00600-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 05/17/2024] [Indexed: 06/12/2024] Open
Abstract
Acute myeloid leukemia (AML) is the most frequent leukemia in adults with a high mortality rate. Current diagnostic criteria and selections of therapeutic strategies are generally based on gene mutations and cytogenetic abnormalities. Chemotherapy, targeted therapies, and hematopoietic stem cell transplantation (HSCT) are the major therapeutic strategies for AML. Two dilemmas in the clinical management of AML are related to its poor prognosis. One is the inaccurate risk stratification at diagnosis, leading to incorrect treatment selections. The other is the frequent resistance to chemotherapy and/or targeted therapies. Genomic features have been the focus of AML studies. However, the DNA-level aberrations do not always predict the expression levels of genes and proteins and the latter is more closely linked to disease phenotypes. With the development of high-throughput sequencing and mass spectrometry technologies, studying downstream effectors including RNA, proteins, and metabolites becomes possible. Transcriptomics can reveal gene expression and regulatory networks, proteomics can discover protein expression and signaling pathways intimately associated with the disease, and metabolomics can reflect precise changes in metabolites during disease progression. Moreover, omics profiling at the single-cell level enables studying cellular components and hierarchies of the AML microenvironment. The abundance of data from different omics layers enables the better risk stratification of AML by identifying prognosis-related biomarkers, and has the prospective application in identifying drug targets, therefore potentially discovering solutions to the two dilemmas. In this review, we summarize the existing AML studies using omics methods, both separately and combined, covering research fields of disease diagnosis, risk stratification, prognosis prediction, chemotherapy, as well as targeted therapy. Finally, we discuss the directions and challenges in the application of multi-omics in precision medicine of AML. Our review may inspire both omics researchers and clinical physicians to study AML from a different angle.
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Affiliation(s)
- Zhiyu Zhang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Key Laboratory of Drug Research for Prevention and Treatment of Hyperlipidemic Diseases, Soochow University, Suzhou, 215123, Jiangsu, China
- Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases, College of Pharmaceutical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China
- MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, 215123, Jiangsu Province, China
| | - Jiayi Huang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Zhibo Zhang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hongjie Shen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiaowen Tang
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Depei Wu
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiebing Bao
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China.
| | - Guoqiang Xu
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and College of Pharmaceutical Sciences, Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Key Laboratory of Drug Research for Prevention and Treatment of Hyperlipidemic Diseases, Soochow University, Suzhou, 215123, Jiangsu, China.
- Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases, College of Pharmaceutical Sciences, Soochow University, Suzhou, 215123, Jiangsu, China.
- MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, 215123, Jiangsu Province, China.
| | - Suning Chen
- National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, the First Affiliated Hospital of Soochow University, Suzhou, China.
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22
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Yuan DJ, Zinno J, Botella T, Dhingra D, Wang S, Hawkins A, Swett A, Sotelo J, Raviram R, Hughes C, Potenski C, Yokoyama A, Kakiuchi N, Ogawa S, Landau DA. Genotype-to-phenotype mapping of somatic clonal mosaicism via single-cell co-capture of DNA mutations and mRNA transcripts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595241. [PMID: 38826366 PMCID: PMC11142212 DOI: 10.1101/2024.05.22.595241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Somatic mosaicism is a hallmark of malignancy that is also pervasively observed in human physiological aging, with clonal expansions of cells harboring mutations in recurrently mutated driver genes. Bulk sequencing of tissue microdissection captures mutation frequencies, but cannot distinguish which mutations co-occur in the same clones to reconstruct clonal architectures, nor phenotypically profile clonal populations to delineate how driver mutations impact cellular behavior. To address these challenges, we developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure and observed a clonal landscape dominated by a large number of clones with a single driver event, but only rare clones with two driver mutations. NOTCH1 mutants dominate the clonal landscape and are linked to stunted epithelial differentiation, while TP53 mutants and double-driver mutants promote clonal expansion through both differentiation biases and increased cell cycling. Thus, joint single-cell highly multiplexed capture of somatic mutations and mRNA transcripts enables high resolution reconstruction of clonal architecture and associated phenotypes in solid tissue somatic mosaicism.
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Affiliation(s)
- Dennis J Yuan
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - John Zinno
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Theo Botella
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | | | | | - Allegra Hawkins
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Ariel Swett
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Jesus Sotelo
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Ramya Raviram
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Clayton Hughes
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Catherine Potenski
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
| | - Akira Yokoyama
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- Department of Medical Oncology, Kyoto University, Kyoto, Japan
| | - Nobuyuki Kakiuchi
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- The Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan
| | - Seishi Ogawa
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
| | - Dan A Landau
- New York Genome Center, New York, NY
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY
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23
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Schiroli G, Kartha V, Duarte FM, Kristiansen TA, Mayerhofer C, Shrestha R, Earl A, Hu Y, Tay T, Rhee C, Buenrostro JD, Scadden DT. Cell of origin epigenetic priming determines susceptibility to Tet2 mutation. Nat Commun 2024; 15:4325. [PMID: 38773071 PMCID: PMC11109152 DOI: 10.1038/s41467-024-48508-6] [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: 06/17/2023] [Accepted: 04/30/2024] [Indexed: 05/23/2024] Open
Abstract
Hematopoietic stem cell (HSC) mutations can result in clonal hematopoiesis (CH) with heterogeneous clinical outcomes. Here, we investigate how the cell state preceding Tet2 mutation impacts the pre-malignant phenotype. Using an inducible system for clonal analysis of myeloid progenitors, we find that the epigenetic features of clones at similar differentiation status are highly heterogeneous and functionally respond differently to Tet2 mutation. Cell differentiation stage also influences Tet2 mutation response indicating that the cell of origin's epigenome modulates clone-specific behaviors in CH. Molecular features associated with higher risk outcomes include Sox4 that sensitizes cells to Tet2 inactivation, inducing dedifferentiation, altered metabolism and increasing the in vivo clonal output of mutant cells, as confirmed in primary GMP and HSC models. Our findings validate the hypothesis that epigenetic features can predispose specific clones for dominance, explaining why identical genetic mutations can result in different phenotypes.
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Affiliation(s)
- Giulia Schiroli
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Vinay Kartha
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Fabiana M Duarte
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Trine A Kristiansen
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Christina Mayerhofer
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Rojesh Shrestha
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Andrew Earl
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Yan Hu
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Tristan Tay
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Catherine Rhee
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA
| | - Jason D Buenrostro
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA.
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA.
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
| | - David T Scadden
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, 02138, USA.
- Harvard Stem Cell Institute, Cambridge, MA, 02138, USA.
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24
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Cooper S, Obolenski S, Waters AJ, Bassett AR, Coelho MA. Analyzing the functional effects of DNA variants with gene editing. CELL REPORTS METHODS 2024; 4:100776. [PMID: 38744287 PMCID: PMC11133854 DOI: 10.1016/j.crmeth.2024.100776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/01/2024] [Accepted: 04/22/2024] [Indexed: 05/16/2024]
Abstract
Continual advancements in genomics have led to an ever-widening disparity between the rate of discovery of genetic variants and our current understanding of their functions and potential roles in disease. Systematic methods for phenotyping DNA variants are required to effectively translate genomics data into improved outcomes for patients with genetic diseases. To make the biggest impact, these approaches must be scalable and accurate, faithfully reflect disease biology, and define complex disease mechanisms. We compare current methods to analyze the function of variants in their endogenous DNA context using genome editing strategies, such as saturation genome editing, base editing and prime editing. We discuss how these technologies can be linked to high-content readouts to gain deep mechanistic insights into variant effects. Finally, we highlight key challenges that need to be addressed to bridge the genotype to phenotype gap, and ultimately improve the diagnosis and treatment of genetic diseases.
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Affiliation(s)
- Sarah Cooper
- Cellular and Gene Editing Research, Wellcome Sanger Institute, Hinxton, UK
| | - Sofia Obolenski
- Experimental Cancer Genetics, Wellcome Sanger Institute, Hinxton, UK; Department of Dermatology, Leiden University Medical Center, Leiden, the Netherlands
| | - Andrew J Waters
- Experimental Cancer Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Andrew R Bassett
- Cellular and Gene Editing Research, Wellcome Sanger Institute, Hinxton, UK.
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25
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Muyas F, Sauer CM, Valle-Inclán JE, Li R, Rahbari R, Mitchell TJ, Hormoz S, Cortés-Ciriano I. De novo detection of somatic mutations in high-throughput single-cell profiling data sets. Nat Biotechnol 2024; 42:758-767. [PMID: 37414936 PMCID: PMC11098751 DOI: 10.1038/s41587-023-01863-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 06/07/2023] [Indexed: 07/08/2023]
Abstract
Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism and cell plasticity. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq (assay for transposase-accessible chromatin sequence) data sets directly without requiring matched bulk or single-cell DNA sequencing data. SComatic distinguishes somatic mutations from polymorphisms, RNA-editing events and artefacts using filters and statistical tests parameterized on non-neoplastic samples. Using >2.6 million single cells from 688 single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells accurately, even in differentiated cells from polyclonal tissues that are not amenable to mutation detection using existing methods. Validated against matched genome sequencing and scRNA-seq data, SComatic achieves F1 scores between 0.6 and 0.7 across diverse data sets, in comparison to 0.2-0.4 for the second-best performing method. In summary, SComatic permits de novo mutational signature analysis, and the study of clonal heterogeneity and mutational burdens at single-cell resolution.
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Affiliation(s)
- Francesc Muyas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Carolin M Sauer
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Jose Espejo Valle-Inclán
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK
| | - Ruoyan Li
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Raheleh Rahbari
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Thomas J Mitchell
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust and NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Department of Surgery, University of Cambridge, Cambridge, UK
| | - Sahand Hormoz
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Isidro Cortés-Ciriano
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, UK.
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26
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Izzo F, Myers RM, Ganesan S, Mekerishvili L, Kottapalli S, Prieto T, Eton EO, Botella T, Dunbar AJ, Bowman RL, Sotelo J, Potenski C, Mimitou EP, Stahl M, El Ghaity-Beckley S, Arandela J, Raviram R, Choi DC, Hoffman R, Chaligné R, Abdel-Wahab O, Smibert P, Ghobrial IM, Scandura JM, Marcellino B, Levine RL, Landau DA. Mapping genotypes to chromatin accessibility profiles in single cells. Nature 2024; 629:1149-1157. [PMID: 38720070 PMCID: PMC11139586 DOI: 10.1038/s41586-024-07388-y] [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: 05/22/2022] [Accepted: 04/04/2024] [Indexed: 05/19/2024]
Abstract
In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1-3. Therefore, somatic mutations are likely to alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. Here, to chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed genotyping of targeted loci with single-cell chromatin accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from patients with myeloproliferative neoplasms with JAK2V617F-mutated haematopoiesis. Differential accessibility analysis between wild-type and JAK2V617F-mutant progenitors revealed both cell-intrinsic and cell-state-specific shifts within mutant haematopoietic precursors, including cell-intrinsic pro-inflammatory signatures in haematopoietic stem cells, and a distinct profibrotic inflammatory chromatin landscape in megakaryocytic progenitors. Integration of mitochondrial genome profiling and cell-surface protein expression measurement allowed expansion of genotyping onto DOGMA-seq through imputation, enabling single-cell capture of genotypes, chromatin accessibility, RNA expression and cell-surface protein expression. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner, influencing inflammation states and differentiation trajectories. We envision that GoT-ChA will empower broad future investigations of the critical link between somatic mutations and epigenetic alterations across clonal populations in malignant and non-malignant contexts.
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Affiliation(s)
- Franco Izzo
- New York Genome Center, New York, NY, USA.
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Robert M Myers
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Saravanan Ganesan
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Levan Mekerishvili
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics and Systems Biology Graduate Program, Weill Cornell Medicine, New York, NY, USA
| | - Sanjay Kottapalli
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Tamara Prieto
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Elliot O Eton
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Theo Botella
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Andrew J Dunbar
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert L Bowman
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jesus Sotelo
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Catherine Potenski
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Eleni P Mimitou
- New York Genome Center, New York, NY, USA
- Immunai, New York, NY, USA
| | - Maximilian Stahl
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medical Oncology, Division of Leukemia, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sebastian El Ghaity-Beckley
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - JoAnn Arandela
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ramya Raviram
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Daniel C Choi
- Laboratory of Molecular Hematopoiesis, Hematology and Oncology, Weill Cornell Medicine, New York, NY, USA
- Richard T. Silver MD Myeloproliferative Neoplasm Center, Weill Cornell Medicine, New York, NY, USA
- Regenerative Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Ronald Hoffman
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ronan Chaligné
- New York Genome Center, New York, NY, USA
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- SAIL: Single-cell Analytics Innovation Lab, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Omar Abdel-Wahab
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Peter Smibert
- New York Genome Center, New York, NY, USA
- 10x Genomics, Pleasanton, CA, USA
| | - Irene M Ghobrial
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Joseph M Scandura
- Laboratory of Molecular Hematopoiesis, Hematology and Oncology, Weill Cornell Medicine, New York, NY, USA
- Richard T. Silver MD Myeloproliferative Neoplasm Center, Weill Cornell Medicine, New York, NY, USA
- Regenerative Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Bridget Marcellino
- Division of Hematology/Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ross L Levine
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Dan A Landau
- New York Genome Center, New York, NY, USA.
- Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
- Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
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27
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Sud A, Parry EM, Wu CJ. The molecular map of CLL and Richter's syndrome. Semin Hematol 2024; 61:73-82. [PMID: 38368146 DOI: 10.1053/j.seminhematol.2024.01.009] [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: 10/31/2023] [Revised: 01/16/2024] [Accepted: 01/20/2024] [Indexed: 02/19/2024]
Abstract
Clonal expansion of B-cells, from the early stages of monoclonal B-cell lymphocytosis through to chronic lymphocytic leukemia (CLL), and then in some cases to Richter's syndrome (RS) provides a comprehensive model of cancer evolution, notable for the marked morphological transformation and distinct clinical phenotypes. High-throughput sequencing of large cohorts of patients and single-cell studies have generated a molecular map of CLL and more recently, of RS, yielding fundamental insights into these diseases and of clonal evolution. A selection of CLL driver genes have been functionally interrogated to yield novel insights into the biology of CLL. Such findings have the potential to impact patient care through risk stratification, treatment selection and drug discovery. However, this molecular map remains incomplete, with extant questions concerning the origin of the B-cell clone, the role of the TME, inter- and intra-compartmental heterogeneity and of therapeutic resistance mechanisms. Through the application of multi-modal single-cell technologies across tissues, disease states and clinical contexts, these questions can now be addressed with the answers holding great promise of generating translatable knowledge to improve patient care.
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Affiliation(s)
- Amit Sud
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
| | - Erin M Parry
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA.
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Medicine, Brigham and Women's Hospital, Boston, MA
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28
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Weng C, Yu F, Yang D, Poeschla M, Liggett LA, Jones MG, Qiu X, Wahlster L, Caulier A, Hussmann JA, Schnell A, Yost KE, Koblan LW, Martin-Rufino JD, Min J, Hammond A, Ssozi D, Bueno R, Mallidi H, Kreso A, Escabi J, Rideout WM, Jacks T, Hormoz S, van Galen P, Weissman JS, Sankaran VG. Deciphering cell states and genealogies of human haematopoiesis. Nature 2024; 627:389-398. [PMID: 38253266 PMCID: PMC10937407 DOI: 10.1038/s41586-024-07066-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: 12/01/2022] [Accepted: 01/12/2024] [Indexed: 01/24/2024]
Abstract
The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs)1. Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems2-5, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging. Here we introduce an improved, single-cell lineage-tracing system based on deep detection of naturally occurring mitochondrial DNA mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs and map the physiological state and output of clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as both differences in total HSC output and biases towards the production of different mature cell types. We also find that the diversity of HSC clones decreases markedly with age, leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides a clonally resolved and cell-state-aware atlas of human haematopoiesis at single-cell resolution, showing an unappreciated functional diversity of human HSC clones and, more broadly, paving the way for refined studies of clonal dynamics across a range of tissues in human health and disease.
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Affiliation(s)
- Chen Weng
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Fulong Yu
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, P.R. China
| | - Dian Yang
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Molecular Pharmacology and Therapeutics, Department of Systems Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Michael Poeschla
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - L Alexander Liggett
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew G Jones
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Xiaojie Qiu
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Genetics and Computer Science, BASE Research Initiative, Betty Irene Moore Children's Heart Center, Stanford University, Stanford, CA, USA
| | - Lara Wahlster
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alexis Caulier
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jeffrey A Hussmann
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alexandra Schnell
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kathryn E Yost
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Luke W Koblan
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jorge D Martin-Rufino
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joseph Min
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alessandro Hammond
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Daniel Ssozi
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Raphael Bueno
- Division of Thoracic and Cardiac Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Hari Mallidi
- Division of Thoracic and Cardiac Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Antonia Kreso
- Division of Cardiac Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Javier Escabi
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - William M Rideout
- Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA
| | - Tyler Jacks
- Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA
| | - Sahand Hormoz
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Peter van Galen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Hematology, Brigham and Women's Hospital, Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Ludwig Center at Harvard, Harvard Medical School, Boston, MA, USA
| | - Jonathan S Weissman
- Whitehead Institute for Biomedical Research, Cambridge, MA, USA.
- Department of Biology and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Koch Institute For Integrative Cancer Research at MIT, MIT, Cambridge, MA, USA.
| | - Vijay G Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Harvard Stem Cell Institute, Cambridge, MA, USA.
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29
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Lin A, Torres CM, Hobbs EC, Bardhan J, Aley SB, Spencer CT, Taylor KL, Chiang T. Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures. Health Secur 2024; 22:130-139. [PMID: 38483337 PMCID: PMC11044874 DOI: 10.1089/hs.2023.0076] [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] [Indexed: 03/26/2024] Open
Affiliation(s)
- Andy Lin
- Andy Lin, PhD, is a Linus Pauling Distinguished Postdoctoral Fellow; in the National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA
| | - Cameron M. Torres
- Cameron M. Torres is a Graduate Research Assistant and Wieland Fellow, Department of Biological Sciences; at the University of Texas at El Paso, El Paso, TX
| | - Errett C. Hobbs
- Errett C. Hobbs, PhD, is a Data Scientist; in the National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA
| | - Jaydeep Bardhan
- Jaydeep Bardhan, PhD, is a Research Line Manager, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA
| | - Stephen B. Aley
- Stephen B. Aley, PhD, is a Professor, Biological Sciences, and an Associate Vice President for Research, Sponsored Projects; at the University of Texas at El Paso, El Paso, TX
| | - Charles T. Spencer
- Charles T. Spencer, PhD, is an Associate Professor, Biological Sciences, and Edward and Barbara Brown Egbert Endowed Chair of the Department of Biological Sciences; at the University of Texas at El Paso, El Paso, TX
| | - Karen L. Taylor
- Karen L. Taylor, MS, is a Research Line Manager; in the National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA
| | - Tony Chiang
- Tony Chiang, PhD, is a Data Scientist; in the National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA
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30
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Lin A, Torres C, Hobbs EC, Bardhan J, Aley S, Spencer CT, Taylor KL, Chiang T. Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures. ARXIV 2024:arXiv:2310.13898v3. [PMID: 37961741 PMCID: PMC10635321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.
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Affiliation(s)
- Andy Lin
- National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA 98109, USA
| | - Cameron Torres
- Department of Biological Sciences, University of Texas at El Paso, El Paso, Texas 79968 USA
| | - Errett C Hobbs
- National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA 98109, USA
| | - Jaydeep Bardhan
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Seattle, WA 98109, USA
| | - Stephen Aley
- Department of Biological Sciences, University of Texas at El Paso, El Paso, Texas 79968 USA
| | - Charles T Spencer
- Department of Biological Sciences, University of Texas at El Paso, El Paso, Texas 79968 USA
| | - Karen L Taylor
- National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA 98109, USA
| | - Tony Chiang
- National Security Directorate, Pacific Northwest National Laboratory, Seattle, WA 98109, USA
- Department of Biological Sciences, University of Texas at El Paso, El Paso, Texas 79968 USA
- Department of Mathematics, University of Washington, Seattle 98102 USA
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31
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Nan L, Zhang H, Weitz DA, Shum HC. Development and future of droplet microfluidics. LAB ON A CHIP 2024; 24:1135-1153. [PMID: 38165829 DOI: 10.1039/d3lc00729d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
Over the past two decades, advances in droplet-based microfluidics have facilitated new approaches to process and analyze samples with unprecedented levels of precision and throughput. A wide variety of applications has been inspired across multiple disciplines ranging from materials science to biology. Understanding the dynamics of droplets enables optimization of microfluidic operations and design of new techniques tailored to emerging demands. In this review, we discuss the underlying physics behind high-throughput generation and manipulation of droplets. We also summarize the applications in droplet-derived materials and droplet-based lab-on-a-chip biotechnology. In addition, we offer perspectives on future directions to realize wider use of droplet microfluidics in industrial production and biomedical analyses.
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Affiliation(s)
- Lang Nan
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong, China
| | - Huidan Zhang
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - David A Weitz
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, 02138, USA
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong, China
| | - Ho Cheung Shum
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
- Advanced Biomedical Instrumentation Centre, Hong Kong Science Park, Shatin, New Territories, Hong Kong, China
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32
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Verma T, Papadantonakis N, Peker Barclift D, Zhang L. Molecular Genetic Profile of Myelofibrosis: Implications in the Diagnosis, Prognosis, and Treatment Advancements. Cancers (Basel) 2024; 16:514. [PMID: 38339265 PMCID: PMC10854658 DOI: 10.3390/cancers16030514] [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: 12/30/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 02/12/2024] Open
Abstract
Myelofibrosis (MF) is an essential element of primary myelofibrosis, whereas secondary MF may develop in the advanced stages of other myeloid neoplasms, especially polycythemia vera and essential thrombocythemia. Over the last two decades, advances in molecular diagnostic techniques, particularly the integration of next-generation sequencing in clinical laboratories, have revolutionized the diagnosis, classification, and clinical decision making of myelofibrosis. Driver mutations involving JAK2, CALR, and MPL induce hyperactivity in the JAK-STAT signaling pathway, which plays a central role in cell survival and proliferation. Approximately 80% of myelofibrosis cases harbor additional mutations, frequently in the genes responsible for epigenetic regulation and RNA splicing. Detecting these mutations is crucial for diagnosing myeloproliferative neoplasms (MPNs), especially in cases where no mutations are present in the three driver genes (triple-negative MPNs). While fibrosis in the bone marrow results from the disturbance of inflammatory cytokines, it is fundamentally associated with mutation-driven hematopoiesis. The mutation profile and order of acquiring diverse mutations influence the MPN phenotype. Mutation profiling reveals clonal diversity in MF, offering insights into the clonal evolution of neoplastic progression. Prognostic prediction plays a pivotal role in guiding the treatment of myelofibrosis. Mutation profiles and cytogenetic abnormalities have been integrated into advanced prognostic scoring systems and personalized risk stratification for MF. Presently, JAK inhibitors are part of the standard of care for MF, with newer generations developed for enhanced efficacy and reduced adverse effects. However, only a minority of patients have achieved a significant molecular-level response. Clinical trials exploring innovative approaches, such as combining hypomethylation agents that target epigenetic regulators, drugs proven effective in myelodysplastic syndrome, or immune and inflammatory modulators with JAK inhibitors, have demonstrated promising results. These combinations may be more effective in patients with high-risk mutations and complex mutation profiles. Expanding mutation profiling studies with more sensitive and specific molecular methods, as well as sequencing a broader spectrum of genes in clinical patients, may reveal molecular mechanisms in cases currently lacking detectable driver mutations, provide a better understanding of the association between genetic alterations and clinical phenotypes, and offer valuable information to advance personalized treatment protocols to improve long-term survival and eradicate mutant clones with the hope of curing MF.
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Affiliation(s)
- Tanvi Verma
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Nikolaos Papadantonakis
- Department of Hematology and Medical Oncology, Winship Cancer Institute of Emory University, Atlanta, GA 30322, USA
| | - Deniz Peker Barclift
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Linsheng Zhang
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
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33
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Cooper SE, Coelho MA, Strauss ME, Gontarczyk AM, Wu Q, Garnett MJ, Marioni JC, Bassett AR. scSNV-seq: high-throughput phenotyping of single nucleotide variants by coupled single-cell genotyping and transcriptomics. Genome Biol 2024; 25:20. [PMID: 38225637 PMCID: PMC10789043 DOI: 10.1186/s13059-024-03169-y] [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: 06/13/2023] [Accepted: 01/09/2024] [Indexed: 01/17/2024] Open
Abstract
CRISPR screens with single-cell transcriptomic readouts are a valuable tool to understand the effect of genetic perturbations including single nucleotide variants (SNVs) associated with diseases. Interpretation of these data is currently limited as genotypes cannot be accurately inferred from guide RNA identity alone. scSNV-seq overcomes this limitation by coupling single-cell genotyping and transcriptomics of the same cells enabling accurate and high-throughput screening of SNVs. Analysis of variants across the JAK1 gene with scSNV-seq demonstrates the importance of determining the precise genetic perturbation and accurately classifies clinically observed missense variants into three functional categories: benign, loss of function, and separation of function.
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Affiliation(s)
- Sarah E Cooper
- Cellular and Gene Editing Research, Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Matthew A Coelho
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Magdalena E Strauss
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
| | - Aleksander M Gontarczyk
- Cellular and Gene Editing Research, Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Qianxin Wu
- Cellular and Gene Editing Research, Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Mathew J Garnett
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - John C Marioni
- EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- Cellular Genetics, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE, UK
- Present Address: Genentech, South San Francisco, CA, USA
| | - Andrew R Bassett
- Cellular and Gene Editing Research, Wellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK.
- Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
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34
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Ciriello G, Magnani L, Aitken SJ, Akkari L, Behjati S, Hanahan D, Landau DA, Lopez-Bigas N, Lupiáñez DG, Marine JC, Martin-Villalba A, Natoli G, Obenauf AC, Oricchio E, Scaffidi P, Sottoriva A, Swarbrick A, Tonon G, Vanharanta S, Zuber J. Cancer Evolution: A Multifaceted Affair. Cancer Discov 2024; 14:36-48. [PMID: 38047596 PMCID: PMC10784746 DOI: 10.1158/2159-8290.cd-23-0530] [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: 05/04/2023] [Revised: 08/29/2023] [Accepted: 10/23/2023] [Indexed: 12/05/2023]
Abstract
Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery. SIGNIFICANCE Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.
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Affiliation(s)
- Giovanni Ciriello
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Luca Magnani
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
- Breast Epigenetic Plasticity and Evolution Laboratory, Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Sarah J. Aitken
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, United Kingdom
- Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Leila Akkari
- Division of Tumor Biology and Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sam Behjati
- Wellcome Sanger Institute, Hinxton, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Douglas Hanahan
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, Lausanne, Switzerland
| | - Dan A. Landau
- New York Genome Center, New York, New York
- Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, New York
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Darío G. Lupiáñez
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Jean-Christophe Marine
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KULeuven, Leuven, Belgium
| | - Ana Martin-Villalba
- Department of Molecular Neurobiology, German Cancer Research Center (DFKZ), Heidelberg, Germany
| | - Gioacchino Natoli
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
| | - Anna C. Obenauf
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
| | - Elisa Oricchio
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
| | - Paola Scaffidi
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
- Cancer Epigenetic Laboratory, The Francis Crick Institute, London, United Kingdom
| | - Andrea Sottoriva
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
| | - Giovanni Tonon
- Vita-Salute San Raffaele University, Milan, Italy
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sakari Vanharanta
- Translational Cancer Medicine Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johannes Zuber
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
- Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria
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35
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Penter L, Borji M, Nagler A, Lyu H, Lu WS, Cieri N, Maurer K, Oliveira G, Al'Khafaji AM, Garimella KV, Li S, Neuberg DS, Ritz J, Soiffer RJ, Garcia JS, Livak KJ, Wu CJ. Integrative genotyping of cancer and immune phenotypes by long-read sequencing. Nat Commun 2024; 15:32. [PMID: 38167262 PMCID: PMC10762175 DOI: 10.1038/s41467-023-44137-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural 'barcodes', we define the optimal targets for nanoranger, namely those loci close to the 5' end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.
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Grants
- P01 CA229092 NCI NIH HHS
- P50 CA101942 NCI NIH HHS
- UM1 CA186709 NCI NIH HHS
- U24 CA224316 NCI NIH HHS
- P01 CA066996 NCI NIH HHS
- U24 CA224331 NCI NIH HHS
- U24 CA224285 NCI NIH HHS
- R50 CA251956 NCI NIH HHS
- U24 CA224309 NCI NIH HHS
- U24 CA224319 NCI NIH HHS
- K08 CA245209 NCI NIH HHS
- This work was supported by National Institutes of Health, National Cancer Institute grant P01CA229092 (CJW), UM1CA186709 (Principal Investigator: Geoffrey Shapiro), National Cancer Institute Cancer Therapy Evaluation Program, Bristol-Myers Squibb, and LLS Therapy Accelerator Program. L.P. was supported by a research fellowship from the German Research Foundation (DFG, PE 3127/1-1) and is a Scholar of the American Society of Hematology, participant in the BIH Charité Digital Clinician Scientist Program funded by the DFG, the Charité – Universitätsmedizin Berlin, and the Berlin Institute of Health at Charité (BIH) and is supported by the Max-Eder program of the German Cancer Aid. A.A. is supported by the Broad Institute IGNITE award. K.M. is suppored by the ASCO YIA award. G.O. was supported by the Claudia Adams Barr Program for Innovative Cancer Research and by DF/HCC Kidney Cancer SPORE P50 CA101942. S.L. is supported by the National Institutes of Health, National Cancer Institute Research Specialist Award (R50CA251956). JSG is supported by the Conquer Cancer Foundation Career Development Award, Leukemia and Lymphoma Society Translational Research Program Award, and NIH K08CA245209. NCI CTEP provided study drug (Ipilimumab) support. This work was further supported by the CIMAC-CIDC Network. Scientific and financial support for the CIMAC-CIDC Network is provided through National Institutes of Health, National Cancer Institute Cooperative Agreements U24CA224319 (to the Icahn School of Medicine at Mount Sinai CIMAC), U24CA224331 (to the Dana-Farber Cancer Institute CIMAC), U24CA224285 (to the MD Anderson Cancer Center CIMAC), U24CA224309 (to the Stanford University CIMAC), and U24CA224316 (to the CIDC at Dana-Farber Cancer Institute). The CIMAC-CIDC website is found at https://cimac-network.org/.
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Affiliation(s)
- Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program, Charitéplatz 1, 10117, Berlin, Germany
| | - Mehdi Borji
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Adi Nagler
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Haoxiang Lyu
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Wesley S Lu
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Nicoletta Cieri
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Katie Maurer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Giacomo Oliveira
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Aziz M Al'Khafaji
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Kiran V Garimella
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Shuqiang Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Donna S Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jerome Ritz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Robert J Soiffer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Jacqueline S Garcia
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kenneth J Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
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36
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Zhang T, Jia H, Song T, Lv L, Gulhan DC, Wang H, Guo W, Xi R, Guo H, Shen N. De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data. Genome Med 2023; 15:115. [PMID: 38111063 PMCID: PMC10726641 DOI: 10.1186/s13073-023-01269-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/04/2023] [Indexed: 12/20/2023] Open
Abstract
Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is challenging but highly valuable. We propose RESA - Recurrently Expressed SNV Analysis, a computational framework to identify expressed somatic mutations from scRNA-seq data. RESA achieves an average precision of 0.77 on three in silico spike-in datasets. In extensive benchmarking against existing methods using 19 datasets, RESA consistently outperforms them. Furthermore, we applied RESA to analyze intratumor mutational heterogeneity in a melanoma drug resistance dataset. By enabling high precision detection of expressed somatic mutations, RESA substantially enhances the reliability of mutational analysis in scRNA-seq. RESA is available at https://github.com/ShenLab-Genomics/RESA .
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Affiliation(s)
- Tianyun Zhang
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Hanying Jia
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- Kidney Disease Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 311121, China
| | - Tairan Song
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Lin Lv
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Doga C Gulhan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Haishuai Wang
- College of Computer Science, Zhejiang University, Hangzhou, 311121, Zhejiang, China
| | - Wei Guo
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Jiaxing, 314400, China
| | - Ruibin Xi
- School of Mathematical Sciences and Center for Statistical Science, Peking University, 5 Yiheyuan Road, Beijing, 100871, China
| | - Hongshan Guo
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
| | - Ning Shen
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China.
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37
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Turkalj S, Jakobsen NA, Groom A, Radtke FA, Vyas P. A protocol for simultaneous high-sensitivity genotyping and chromatin accessibility profiling in single cells. STAR Protoc 2023; 4:102641. [PMID: 37897733 PMCID: PMC10641301 DOI: 10.1016/j.xpro.2023.102641] [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: 08/11/2023] [Revised: 09/19/2023] [Accepted: 09/22/2023] [Indexed: 10/30/2023] Open
Abstract
Single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) resolves the heterogeneity of epigenetic states across cells but does not typically capture exonic mutations, which limits our knowledge of how somatic mutations alter chromatin landscapes. Here, we present a plate-based approach coupling high-sensitivity genotyping of genomic loci with high-content scATAC-seq libraries from the same single cells. We first describe steps for optimization of genotyping primers, followed by detailed guidance on the preparation of both scATAC-seq and single-cell genotyping libraries, fully automated on high-throughput liquid handling platforms. For complete details on the use and execution of this protocol, please refer to Turkalj, Jakobsen et al.1.
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Affiliation(s)
- Sven Turkalj
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
| | - Niels Asger Jakobsen
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Angus Groom
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Felix A Radtke
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Paresh Vyas
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK; Oxford Centre for Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
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38
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Isobe T, Kucinski I, Barile M, Wang X, Hannah R, Bastos HP, Chabra S, Vijayabaskar MS, Sturgess KHM, Williams MJ, Giotopoulos G, Marando L, Li J, Rak J, Gozdecka M, Prins D, Shepherd MS, Watcham S, Green AR, Kent DG, Vassiliou GS, Huntly BJP, Wilson NK, Göttgens B. Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes. CELL GENOMICS 2023; 3:100426. [PMID: 38116120 PMCID: PMC10726426 DOI: 10.1016/j.xgen.2023.100426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 07/13/2023] [Accepted: 09/29/2023] [Indexed: 12/21/2023]
Abstract
Acute myeloid leukemia (AML) and myeloid neoplasms develop through acquisition of somatic mutations that confer mutation-specific fitness advantages to hematopoietic stem and progenitor cells. However, our understanding of mutational effects remains limited to the resolution attainable within immunophenotypically and clinically accessible bulk cell populations. To decipher heterogeneous cellular fitness to preleukemic mutational perturbations, we performed single-cell RNA sequencing of eight different mouse models with driver mutations of myeloid malignancies, generating 269,048 single-cell profiles. Our analysis infers mutation-driven perturbations in cell abundance, cellular lineage fate, cellular metabolism, and gene expression at the continuous resolution, pinpointing cell populations with transcriptional alterations associated with differentiation bias. We further develop an 11-gene scoring system (Stem11) on the basis of preleukemic transcriptional signatures that predicts AML patient outcomes. Our results demonstrate that a single-cell-resolution deep characterization of preleukemic biology has the potential to enhance our understanding of AML heterogeneity and inform more effective risk stratification strategies.
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Affiliation(s)
- Tomoya Isobe
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Iwo Kucinski
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Melania Barile
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Xiaonan Wang
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Rebecca Hannah
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Hugo P Bastos
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Shirom Chabra
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - M S Vijayabaskar
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Katherine H M Sturgess
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Matthew J Williams
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - George Giotopoulos
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Ludovica Marando
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Juan Li
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Justyna Rak
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK; Hematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Malgorzata Gozdecka
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK; Hematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Daniel Prins
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Mairi S Shepherd
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Sam Watcham
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Anthony R Green
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - David G Kent
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK; York Biomedical Research Institute, Department of Biology, University of York, York, UK
| | - George S Vassiliou
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK; Hematological Cancer Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Brian J P Huntly
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK
| | - Nicola K Wilson
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK.
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Hematology, University of Cambridge, Cambridge, UK.
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39
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Mahmud M, Vasireddy S, Gowin K, Amaraneni A. Myeloproliferative Neoplasms: Contemporary Review and Molecular Landscape. Int J Mol Sci 2023; 24:17383. [PMID: 38139212 PMCID: PMC10744078 DOI: 10.3390/ijms242417383] [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: 09/15/2023] [Revised: 11/29/2023] [Accepted: 12/02/2023] [Indexed: 12/24/2023] Open
Abstract
Myelofibrosis (MF), Myeloproliferative neoplasms (MPNs), and MDS/MPN overlap syndromes have a broad range of clinical presentations and molecular abnormalities, making their diagnosis and classification complex. This paper reviews molecular aberration, epigenetic modifications, chromosomal anomalies, and their interactions with cellular and other immune mechanisms in the manifestations of these disease spectra, clinical features, classification, and treatment modalities. The advent of new-generation sequencing has broadened the understanding of the genetic factors involved. However, while great strides have been made in the pharmacological treatment of these diseases, treatment of advanced disease remains hematopoietic stem cell transplant.
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Affiliation(s)
- Muftah Mahmud
- Department of Medicine, Midwestern University Internal Medicine Residency Consortium, Cottonwood, AZ 86326, USA
| | - Swati Vasireddy
- Department of Medicine, University of Arizona Health Sciences, Tucson, AZ 85701, USA
| | - Krisstina Gowin
- Division of Hematology and Oncology, Department of Medicine, University of Arizona Cancer Center, Tucson, AZ 85701, USA
| | - Akshay Amaraneni
- Division of Hematology and Oncology, Department of Medicine, University of Arizona Cancer Center, Tucson, AZ 85701, USA
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40
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Patruno L, Milite S, Bergamin R, Calonaci N, D’Onofrio A, Anselmi F, Antoniotti M, Graudenzi A, Caravagna G. A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing. PLoS Comput Biol 2023; 19:e1011557. [PMID: 37917660 PMCID: PMC10645363 DOI: 10.1371/journal.pcbi.1011557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/14/2023] [Accepted: 09/30/2023] [Indexed: 11/04/2023] Open
Abstract
Single-cell RNA and ATAC sequencing technologies enable the examination of gene expression and chromatin accessibility in individual cells, providing insights into cellular phenotypes. In cancer research, it is important to consistently analyze these states within an evolutionary context on genetic clones. Here we present CONGAS+, a Bayesian model to map single-cell RNA and ATAC profiles onto the latent space of copy number clones. CONGAS+ clusters cells into tumour subclones with similar ploidy, rendering straightforward to compare their expression and chromatin profiles. The framework, implemented on GPU and tested on real and simulated data, scales to analyse seamlessly thousands of cells, demonstrating better performance than single-molecule models, and supporting new multi-omics assays. In prostate cancer, lymphoma and basal cell carcinoma, CONGAS+ successfully identifies complex subclonal architectures while providing a coherent mapping between ATAC and RNA, facilitating the study of genotype-phenotype maps and their connection to genomic instability.
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Affiliation(s)
- Lucrezia Patruno
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, Italy
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Salvatore Milite
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
- Centre for Computational Biology, Human Technopole, Milan, Italy
| | - Riccardo Bergamin
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Nicola Calonaci
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Alberto D’Onofrio
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Fabio Anselmi
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
| | - Marco Antoniotti
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, Italy
- B4—Bicocca Bioinformatics Biostatistics and Bioimaging Centre, Università degli Studi di Milano-Bicocca, Milan, Italy
| | - Alex Graudenzi
- Department of Informatics, Systems and Communication, Università degli Studi di Milano-Bicocca, Milan, Italy
- B4—Bicocca Bioinformatics Biostatistics and Bioimaging Centre, Università degli Studi di Milano-Bicocca, Milan, Italy
| | - Giulio Caravagna
- Department of Mathematics and Geosciences, Università degli Studi di Trieste, Trieste, Italy
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41
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Van Horebeek L, David M, Dedoncker N, Mallants K, Bijnens B, Goris A, Dubois B. A targeted sequencing extension for transcript genotyping in single-cell transcriptomics. Life Sci Alliance 2023; 6:e202301971. [PMID: 37696578 PMCID: PMC10494938 DOI: 10.26508/lsa.202301971] [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: 02/05/2023] [Revised: 08/17/2023] [Accepted: 08/29/2023] [Indexed: 09/13/2023] Open
Abstract
As no existing methods within the single-cell RNA sequencing repertoire combine genotyping of specific genomic loci with high throughput, we evaluated a straightforward, targeted sequencing approach as an extension to high-throughput droplet-based single-cell RNA sequencing. Overlaying standard gene expression data with transcript level genotype information provides a strategy to study the impact of genetic variants. Here, we describe this targeted sequencing extension, explain how to process the data and evaluate how technical parameters such as amount of input cDNA, number of amplification rounds, and sequencing depth influence the number of transcripts detected. Finally, we demonstrate how targeted sequencing can be used in two contexts: (1) simultaneous investigation of the presence of a somatic variant and its potential impact on the transcriptome of affected cells and (2) evaluation of allele-specific expression of a germline variant in ad hoc cell subsets. Through these and other comparable applications, our targeted sequencing extension has the potential to improve our understanding of functional effects caused by genetic variation.
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Affiliation(s)
- Lies Van Horebeek
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Margaux David
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Nina Dedoncker
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Klara Mallants
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Baukje Bijnens
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - An Goris
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Bénédicte Dubois
- https://ror.org/05f950310 Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium
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42
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Wildschut MHE, Mena J, Dördelmann C, van Oostrum M, Hale BD, Settelmeier J, Festl Y, Lysenko V, Schürch PM, Ring A, Severin Y, Bader MS, Pedrioli PGA, Goetze S, van Drogen A, Balabanov S, Skoda RC, Lopes M, Wollscheid B, Theocharides APA, Snijder B. Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis. Nat Commun 2023; 14:6414. [PMID: 37828014 PMCID: PMC10570306 DOI: 10.1038/s41467-023-42101-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 09/25/2023] [Indexed: 10/14/2023] Open
Abstract
Myelofibrosis is a hematopoietic stem cell disorder belonging to the myeloproliferative neoplasms. Myelofibrosis patients frequently carry driver mutations in either JAK2 or Calreticulin (CALR) and have limited therapeutic options. Here, we integrate ex vivo drug response and proteotype analyses across myelofibrosis patient cohorts to discover targetable vulnerabilities and associated therapeutic strategies. Drug sensitivities of mutated and progenitor cells were measured in patient blood using high-content imaging and single-cell deep learning-based analyses. Integration with matched molecular profiling revealed three targetable vulnerabilities. First, CALR mutations drive BET and HDAC inhibitor sensitivity, particularly in the absence of high Ras pathway protein levels. Second, an MCM complex-high proliferative signature corresponds to advanced disease and sensitivity to drugs targeting pro-survival signaling and DNA replication. Third, homozygous CALR mutations result in high endoplasmic reticulum (ER) stress, responding to ER stressors and unfolded protein response inhibition. Overall, our integrated analyses provide a molecularly motivated roadmap for individualized myelofibrosis patient treatment.
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Affiliation(s)
- Mattheus H E Wildschut
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Department of Medical Oncology and Hematology, Division of Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Julien Mena
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Cyril Dördelmann
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
| | - Marc van Oostrum
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Benjamin D Hale
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Jens Settelmeier
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Yasmin Festl
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Veronika Lysenko
- Department of Medical Oncology and Hematology, Division of Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Patrick M Schürch
- Department of Medical Oncology and Hematology, Division of Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Alexander Ring
- Department of Medical Oncology and Hematology, Division of Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Yannik Severin
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Michael S Bader
- Department of Biomedicine, Experimental Hematology, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Patrick G A Pedrioli
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- ETH PHRT Swiss Multi-Omics Center (SMOC), Zurich, Switzerland
| | - Sandra Goetze
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- ETH PHRT Swiss Multi-Omics Center (SMOC), Zurich, Switzerland
| | - Audrey van Drogen
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- ETH PHRT Swiss Multi-Omics Center (SMOC), Zurich, Switzerland
| | - Stefan Balabanov
- Department of Medical Oncology and Hematology, Division of Hematology, University Hospital Zurich, Zurich, Switzerland
| | - Radek C Skoda
- Department of Biomedicine, Experimental Hematology, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Massimo Lopes
- Institute of Molecular Cancer Research, University of Zurich, Zurich, Switzerland
| | - Bernd Wollscheid
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
| | - Alexandre P A Theocharides
- Department of Medical Oncology and Hematology, Division of Hematology, University Hospital Zurich, Zurich, Switzerland.
| | - Berend Snijder
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
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43
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Wang Z, Tong L, Wang Q, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell type-specific transcriptional networks in cortical development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558077. [PMID: 37790302 PMCID: PMC10542124 DOI: 10.1101/2023.09.18.558077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Systematic analysis of gene function across diverse cell types in vivo is hindered by two challenges: obtaining sufficient cells from live tissues and accurately identifying each cell's perturbation in high-throughput single-cell assays. Leveraging AAV's versatile cell type tropism and high labeling capacity, we expanded the resolution and scale of in vivo CRISPR screens: allowing phenotypic analysis at single-cell resolution across a multitude of cell types in the embryonic brain, adult brain, and peripheral nervous system. We undertook extensive tests of 86 AAV serotypes, combined with a transposon system, to substantially amplify labeling and accelerate in vivo gene delivery from weeks to days. Using this platform, we performed an in utero genetic screen as proof-of-principle and identified pleiotropic regulatory networks of Foxg1 in cortical development, including Layer 6 corticothalamic neurons where it tightly controls distinct networks essential for cell fate specification. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% (mediated by lentivirus), and achieve analysis of over 30,000 cells in one experiment, thus enabling massively parallel in vivo Perturb-seq. Compatible with various perturbation techniques (CRISPRa/i) and phenotypic measurements (single-cell or spatial multi-omics), our platform presents a flexible, modular approach to interrogate gene function across diverse cell types in vivo, connecting gene variants to their causal functions.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Sean K. Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Grace S. Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Joshua Z. Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
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44
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Cortés-López M, Chamely P, Hawkins AG, Stanley RF, Swett AD, Ganesan S, Mouhieddine TH, Dai X, Kluegel L, Chen C, Batta K, Furer N, Vedula RS, Beaulaurier J, Drong AW, Hickey S, Dusaj N, Mullokandov G, Stasiw AM, Su J, Chaligné R, Juul S, Harrington E, Knowles DA, Potenski CJ, Wiseman DH, Tanay A, Shlush L, Lindsley RC, Ghobrial IM, Taylor J, Abdel-Wahab O, Gaiti F, Landau DA. Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths. Cell Stem Cell 2023; 30:1262-1281.e8. [PMID: 37582363 PMCID: PMC10528176 DOI: 10.1016/j.stem.2023.07.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 05/28/2023] [Accepted: 07/18/2023] [Indexed: 08/17/2023]
Abstract
RNA splicing factors are recurrently mutated in clonal blood disorders, but the impact of dysregulated splicing in hematopoiesis remains unclear. To overcome technical limitations, we integrated genotyping of transcriptomes (GoT) with long-read single-cell transcriptomics and proteogenomics for single-cell profiling of transcriptomes, surface proteins, somatic mutations, and RNA splicing (GoT-Splice). We applied GoT-Splice to hematopoietic progenitors from myelodysplastic syndrome (MDS) patients with mutations in the core splicing factor SF3B1. SF3B1mut cells were enriched in the megakaryocytic-erythroid lineage, with expansion of SF3B1mut erythroid progenitor cells. We uncovered distinct cryptic 3' splice site usage in different progenitor populations and stage-specific aberrant splicing during erythroid differentiation. Profiling SF3B1-mutated clonal hematopoiesis samples revealed that erythroid bias and cell-type-specific cryptic 3' splice site usage in SF3B1mut cells precede overt MDS. Collectively, GoT-Splice defines the cell-type-specific impact of somatic mutations on RNA splicing, from early clonal outgrowths to overt neoplasia, directly in human samples.
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Affiliation(s)
- Mariela Cortés-López
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Paulina Chamely
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Allegra G Hawkins
- Childhood Cancer Data Lab, Alex's Lemonade Stand Foundation, Philadelphia, PA, USA
| | - Robert F Stanley
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ariel D Swett
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Saravanan Ganesan
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Tarek H Mouhieddine
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Xiaoguang Dai
- Oxford Nanopore Technologies Inc., New York, NY, USA
| | - Lloyd Kluegel
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Celine Chen
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kiran Batta
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
| | - Nili Furer
- Weizmann Institute of Science, Department of Molecular Cell Biology, Rehovot, Israel
| | - Rahul S Vedula
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | | | - Scott Hickey
- Oxford Nanopore Technologies Inc., San Francisco, CA, USA
| | - Neville Dusaj
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Gavriel Mullokandov
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Adam M Stasiw
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Jiayu Su
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA
| | - Ronan Chaligné
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sissel Juul
- Oxford Nanopore Technologies Inc., New York, NY, USA
| | | | - David A Knowles
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA; Department of Computer Science, Columbia University, New York, NY, USA
| | - Catherine J Potenski
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Daniel H Wiseman
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
| | - Amos Tanay
- Weizmann Institute of Science, Department of Computer Science and Applied Mathematics, Rehovot, Israel
| | - Liran Shlush
- Weizmann Institute of Science, Department of Molecular Cell Biology, Rehovot, Israel
| | - Robert C Lindsley
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Irene M Ghobrial
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Justin Taylor
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Omar Abdel-Wahab
- Molecular Pharmacology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Federico Gaiti
- University Health Network, Princess Margaret Cancer Centre, Toronto, ON, Canada; University of Toronto, Medical Biophysics, Toronto, ON, Canada.
| | - Dan A Landau
- New York Genome Center, New York, NY, USA; Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
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45
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Benabid A, Schneider RK. Inflammation drives pressure on TP53 mutant clones in myeloproliferative neoplasms. Nat Genet 2023; 55:1432-1434. [PMID: 37666990 DOI: 10.1038/s41588-023-01479-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Affiliation(s)
- Adam Benabid
- Oncode Institute, Erasmus MC, Rotterdam, The Netherlands
- Department of Cell and Tumor Biology; Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Rebekka K Schneider
- Oncode Institute, Erasmus MC, Rotterdam, The Netherlands.
- Department of Cell and Tumor Biology; Medical Faculty, RWTH Aachen University, Aachen, Germany.
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46
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Takahashi K, Tanaka T. Clonal evolution and hierarchy in myeloid malignancies. Trends Cancer 2023; 9:707-715. [PMID: 37302922 PMCID: PMC10766088 DOI: 10.1016/j.trecan.2023.05.004] [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: 03/02/2023] [Revised: 05/15/2023] [Accepted: 05/18/2023] [Indexed: 06/13/2023]
Abstract
Myeloid malignancies, a group of hematopoietic disorders that includes acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs), are caused by the accumulation of genetic and epigenetic changes in hematopoietic stem and progenitor cells (HSPCs) over time. Despite the relatively low number of genomic drivers compared with other forms of cancer, the process by which these changes shape the genomic architecture of myeloid malignancies remains elusive. Recent advancements in clonal hematopoiesis research and the use of cutting-edge single cell technologies have shed new light on the developmental process of myeloid malignancies. In this review, we delve into the intricacies of clonal evolution in myeloid malignancies and its implications for the development of new diagnostic and therapeutic approaches.
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Affiliation(s)
- Koichi Takahashi
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Tomoyuki Tanaka
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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47
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Li X, Wang Y, Deng S, Zhu G, Wang C, Johnson NA, Zhang Z, Tirado CR, Xu Y, Metang LA, Gonzalez J, Mukherji A, Ye J, Yang Y, Peng W, Tang Y, Hofstad M, Xie Z, Yoon H, Chen L, Liu X, Chen S, Zhu H, Strand D, Liang H, Raj G, He HH, Mendell JT, Li B, Wang T, Mu P. Loss of SYNCRIP unleashes APOBEC-driven mutagenesis, tumor heterogeneity, and AR-targeted therapy resistance in prostate cancer. Cancer Cell 2023; 41:1427-1449.e12. [PMID: 37478850 PMCID: PMC10530398 DOI: 10.1016/j.ccell.2023.06.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 05/24/2023] [Accepted: 06/29/2023] [Indexed: 07/23/2023]
Abstract
Tumor mutational burden and heterogeneity has been suggested to fuel resistance to many targeted therapies. The cytosine deaminase APOBEC proteins have been implicated in the mutational signatures of more than 70% of human cancers. However, the mechanism underlying how cancer cells hijack the APOBEC mediated mutagenesis machinery to promote tumor heterogeneity, and thereby foster therapy resistance remains unclear. We identify SYNCRIP as an endogenous molecular brake which suppresses APOBEC-driven mutagenesis in prostate cancer (PCa). Overactivated APOBEC3B, in SYNCRIP-deficient PCa cells, is a key mutator, representing the molecular source of driver mutations in some frequently mutated genes in PCa, including FOXA1, EP300. Functional screening identifies eight crucial drivers for androgen receptor (AR)-targeted therapy resistance in PCa that are mutated by APOBEC3B: BRD7, CBX8, EP300, FOXA1, HDAC5, HSF4, STAT3, and AR. These results uncover a cell-intrinsic mechanism that unleashes APOBEC-driven mutagenesis, which plays a significant role in conferring AR-targeted therapy resistance in PCa.
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Affiliation(s)
- Xiaoling Li
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Yunguan Wang
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, USA; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Su Deng
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Guanghui Zhu
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada
| | - Choushi Wang
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Nickolas A Johnson
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Zeda Zhang
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Yaru Xu
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lauren A Metang
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Julisa Gonzalez
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Atreyi Mukherji
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Jianfeng Ye
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA
| | - Yuqiu Yang
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, USA
| | - Wei Peng
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Yitao Tang
- Department of Bioinformatics and Computational Biology, MD Anderson Cancer Center, Houston, TX, USA
| | - Mia Hofstad
- Department of Urology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Zhiqun Xie
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, USA
| | - Heewon Yoon
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Liping Chen
- Department of Urology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Xihui Liu
- Department of Urology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Sujun Chen
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada
| | - Hong Zhu
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Douglas Strand
- Department of Urology, UT Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Han Liang
- Department of Bioinformatics and Computational Biology, MD Anderson Cancer Center, Houston, TX, USA; Department of Systems Biology, MD Anderson Cancer Center, Houston, TX, USA
| | - Ganesh Raj
- Department of Urology, UT Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Housheng Hansen He
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada
| | - Joshua T Mendell
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Bo Li
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA
| | - Tao Wang
- Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ping Mu
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA; Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA; Hamon Center for Regenerative Science and Medicine, UT Southwestern Medical Center, Dallas, TX, USA.
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48
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Avagyan S, Zon LI. Clonal hematopoiesis and inflammation - the perpetual cycle. Trends Cell Biol 2023; 33:695-707. [PMID: 36593155 PMCID: PMC10310890 DOI: 10.1016/j.tcb.2022.12.001] [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: 10/03/2022] [Revised: 12/04/2022] [Accepted: 12/08/2022] [Indexed: 01/01/2023]
Abstract
Acquired genetic or cytogenetic alterations in a blood stem cell that confer clonal fitness promote its relative expansion leading to clonal hematopoiesis (CH). Despite a largely intact hematopoietic output, CH is associated with a heightened risk of progression to hematologic malignancies and with non-hematologic health manifestations, including cardiovascular disease and overall mortality. We focus on the evidence for the role of inflammation in establishing, maintaining and reciprocally being affected by CH. We describe the known pro-inflammatory signals associated with CH and preclinical studies that elucidated the cellular mechanisms involved. We review the evolving literature on early-onset CH in germline predisposition conditions and the possible role of immune dysregulation in this context.
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Affiliation(s)
- Serine Avagyan
- Dana-Farber/Boston Children's Hospital Cancer and Blood Disorders Center, Boston, MA, USA.
| | - Leonard I Zon
- Boston Children's Hospital, Boston, MA 02215, USA; Howard Hughes Medical Institute, USA
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49
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Bouzid H, Belk JA, Jan M, Qi Y, Sarnowski C, Wirth S, Ma L, Chrostek MR, Ahmad H, Nachun D, Yao W, Beiser A, Bick AG, Bis JC, Fornage M, Longstreth WT, Lopez OL, Natarajan P, Psaty BM, Satizabal CL, Weinstock J, Larson EB, Crane PK, Keene CD, Seshadri S, Satpathy AT, Montine TJ, Jaiswal S. Clonal hematopoiesis is associated with protection from Alzheimer's disease. Nat Med 2023; 29:1662-1670. [PMID: 37322115 PMCID: PMC10353941 DOI: 10.1038/s41591-023-02397-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 05/12/2023] [Indexed: 06/17/2023]
Abstract
Clonal hematopoiesis of indeterminate potential (CHIP) is a premalignant expansion of mutated hematopoietic stem cells. As CHIP-associated mutations are known to alter the development and function of myeloid cells, we hypothesized that CHIP may also be associated with the risk of Alzheimer's disease (AD), a disease in which brain-resident myeloid cells are thought to have a major role. To perform association tests between CHIP and AD dementia, we analyzed blood DNA sequencing data from 1,362 individuals with AD and 4,368 individuals without AD. Individuals with CHIP had a lower risk of AD dementia (meta-analysis odds ratio (OR) = 0.64, P = 3.8 × 10-5), and Mendelian randomization analyses supported a potential causal association. We observed that the same mutations found in blood were also detected in microglia-enriched fraction of the brain in seven of eight CHIP carriers. Single-nucleus chromatin accessibility profiling of brain-derived nuclei in six CHIP carriers revealed that the mutated cells comprised a large proportion of the microglial pool in the samples examined. While additional studies are required to validate the mechanistic findings, these results suggest that CHIP may have a role in attenuating the risk of AD.
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Affiliation(s)
- Hind Bouzid
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Julia A Belk
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Max Jan
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Yanyan Qi
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Chloé Sarnowski
- Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA
| | - Sara Wirth
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lisa Ma
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Matthew R Chrostek
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Herra Ahmad
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Cardiology, Charité Universitätsmedizin, Berlin, Germany
| | - Daniel Nachun
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Winnie Yao
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexa Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Alexander G Bick
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - William T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Pradeep Natarajan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Joshua Weinstock
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Eric B Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Paul K Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA
| | - Ansuman T Satpathy
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Siddhartha Jaiswal
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- The Phil & Penny Knight Initiative for Brain Resilience at the Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
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Kim JJ, Steinson ER, Lau MS, de Rooij DG, Page DC, Kingston RE. Cell type-specific role of CBX2 and its disordered region in spermatogenesis. Genes Dev 2023; 37:640-660. [PMID: 37553262 PMCID: PMC10499018 DOI: 10.1101/gad.350393.122] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 07/28/2023] [Indexed: 08/10/2023]
Abstract
Polycomb group (PcG) proteins maintain the repressed state of lineage-inappropriate genes and are therefore essential for embryonic development and adult tissue homeostasis. One critical function of PcG complexes is modulating chromatin structure. Canonical Polycomb repressive complex 1 (cPRC1), particularly its component CBX2, can compact chromatin and phase-separate in vitro. These activities are hypothesized to be critical for forming a repressed physical environment in cells. While much has been learned by studying these PcG activities in cell culture models, it is largely unexplored how cPRC1 regulates adult stem cells and their subsequent differentiation in living animals. Here, we show in vivo evidence of a critical nonenzymatic repressive function of cPRC1 component CBX2 in the male germline. CBX2 is up-regulated as spermatogonial stem cells differentiate and is required to repress genes that were active in stem cells. CBX2 forms condensates (similar to previously described Polycomb bodies) that colocalize with target genes bound by CBX2 in differentiating spermatogonia. Single-cell analyses of mosaic Cbx2 mutant testes show that CBX2 is specifically required to produce differentiating A1 spermatogonia. Furthermore, the region of CBX2 responsible for compaction and phase separation is needed for the long-term maintenance of male germ cells in the animal. These results emphasize that the regulation of chromatin structure by CBX2 at a specific stage of spermatogenesis is critical, which distinguishes this from a mechanism that is reliant on histone modification.
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Affiliation(s)
- Jongmin J Kim
- Department of Molecular Biology, MGH Research Institute, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Emma R Steinson
- Department of Molecular Biology, MGH Research Institute, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Mei Sheng Lau
- Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology, and Research (A*STAR), Proteos, Singapore 138673, Republic of Singapore
| | - Dirk G de Rooij
- Reproductive Biology Group, Division of Developmental Biology, Department of Biology, Faculty of Science, Utrecht University, Utrecht 3584 CH, the Netherlands
| | - David C Page
- Whitehead Institute, Cambridge, Massachusetts 02142, USA
- Howard Hughes Medical Institute, Whitehead Institute, Cambridge, Massachusetts 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Robert E Kingston
- Department of Molecular Biology, MGH Research Institute, Massachusetts General Hospital, Boston, Massachusetts 02114, USA;
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
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