1
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Chen SS. Mouse models of CLL: In vivo modeling of disease initiation, progression, and transformation to Richter transformation. Semin Hematol 2024:S0037-1963(24)00056-8. [PMID: 38755077 DOI: 10.1053/j.seminhematol.2024.03.003] [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: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 05/18/2024]
Abstract
Chronic lymphocytic leukemia (CLL) is a highly complex disease characterized by the proliferation of CD5+ B cells in lymphoid tissues. Current modern treatments have brought significant clinical benefits to CLL patients. However, there are still unmet needs. Patients relapse on Bruton's tyrosine kinase inhibitors and BCL2 inhibitors and often develop more aggressive diseases including Richter transformation (RT), an incurable complication of up to ∼10% patients. This evidence underscores the need for improved immunotherapies, combination treatment strategies, and predictive biomarkers. A mouse model that can recapitulate human CLL disease and certain components of the tumor immune microenvironment represents a promising preclinical tool for such purposes. In this review, we provide an overview of CRISPR-engineered and xenograft mouse models utilizing either cell lines, or primary CLL cells suitable for studies of key events driving the disease onset, progression and transformation of CLL. We also review how CRISPR/Cas9 established mouse models carrying loss-of-function lesions allow one to study key mutations driving disease progression. Finally, we discuss how next generation humanized mice might improve to generation of faithful xenograft mouse models of human CLL.
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Affiliation(s)
- Shih-Shih Chen
- Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Manhasset, New York.
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2
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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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3
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Cortes-Figueiredo F, Asseyer S, Chien C, Zimmermann HG, Ruprecht K, Schmitz-Hübsch T, Bellmann-Strobl J, Paul F, Morais VA. CD4 + T cell mitochondrial genotype in Multiple Sclerosis: a cross-sectional and longitudinal analysis. Sci Rep 2024; 14:7507. [PMID: 38553515 PMCID: PMC10980703 DOI: 10.1038/s41598-024-57592-z] [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: 03/29/2023] [Accepted: 03/20/2024] [Indexed: 04/02/2024] Open
Abstract
Multiple Sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system (CNS), with a largely unknown etiology, where mitochondrial dysfunction likely contributes to neuroaxonal loss and brain atrophy. Mirroring the CNS, peripheral immune cells from patients with MS, particularly CD4+ T cells, show inappropriate mitochondrial phenotypes and/or oxidative phosphorylation (OxPhos) insufficiency, with a still unknown contribution of mitochondrial DNA (mtDNA). We hypothesized that mitochondrial genotype in CD4+ T cells might influence MS disease activity and progression. Thus, we performed a retrospective cross-sectional and longitudinal study on patients with a recent diagnosis of either Clinically Isolated Syndrome (CIS) or Relapsing-Remitting MS (RRMS) at two timepoints: 6 months (VIS1) and 36 months (VIS2) after disease onset. Our primary outcomes were the differences in mtDNA extracted from CD4+ T cells between: (I) patients with CIS/RRMS (PwMS) at VIS1 and age- and sex-matched healthy controls (HC), in the cross-sectional analysis, and (II) different diagnostic evolutions in PwMS from VIS1 to VIS2, in the longitudinal analysis. We successfully performed mtDNA whole genome sequencing (mean coverage: 2055.77 reads/base pair) in 183 samples (61 triplets). Nonetheless, mitochondrial genotype was not associated with a diagnosis of CIS/RRMS, nor with longitudinal diagnostic evolution.
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Affiliation(s)
- Filipe Cortes-Figueiredo
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Susanna Asseyer
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Claudia Chien
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Hanna G Zimmermann
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| | - Klemens Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Tanja Schmitz-Hübsch
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Judith Bellmann-Strobl
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Friedemann Paul
- Experimental and Clinical Research Center, a Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité - Universitätsmedizin Berlin, Berlin, Germany.
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
| | - Vanessa A Morais
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal.
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4
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Xue Y, Su Z, Lin X, Ho MK, Yu KHO. Single-cell lineage tracing with endogenous markers. Biophys Rev 2024; 16:125-139. [PMID: 38495438 PMCID: PMC10937880 DOI: 10.1007/s12551-024-01179-5] [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: 11/30/2023] [Accepted: 01/18/2024] [Indexed: 03/19/2024] Open
Abstract
Resolving lineage relationships between cells in an organism provides key insights into the fate of individual cells and drives a fundamental understanding of the process of development and disease. A recent rapid increase in experimental and computational advances for detecting naturally occurring somatic nuclear and mitochondrial mutation at single-cell resolution has expanded lineage tracing from model organisms to humans. This review discusses the advantages and challenges of experimental and computational techniques for cell lineage tracing using somatic mutation as endogenous DNA barcodes to decipher the relationships between cells during development and tumour evolution. We outlook the advantages of spatial clonal evolution analysis and single-cell lineage tracing using endogenous genetic markers.
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Affiliation(s)
- Yan Xue
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Units 1201-1206, 1223 & 1225, 12/F, Building 19W, 19 Science Park West Avenue, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China
| | - Zezhuo Su
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Units 1201-1206, 1223 & 1225, 12/F, Building 19W, 19 Science Park West Avenue, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China
- Department of Orthopaedics and Traumatology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Xinyi Lin
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Mun Kay Ho
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Ken H. O. Yu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Units 1201-1206, 1223 & 1225, 12/F, Building 19W, 19 Science Park West Avenue, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China
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5
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Liu J, Jiang P, Lu Z, Yu Z, Qian P. Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance. Exp Hematol Oncol 2024; 13:12. [PMID: 38291542 PMCID: PMC10826069 DOI: 10.1186/s40164-024-00479-6] [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: 11/02/2023] [Accepted: 01/16/2024] [Indexed: 02/01/2024] Open
Abstract
Leukemias are refractory hematological malignancies, characterized by marked intrinsic heterogeneity which poses significant obstacles to effective treatment. However, traditional bulk sequencing techniques have not been able to effectively unravel the heterogeneity among individual tumor cells. With the emergence of single-cell sequencing technology, it has bestowed upon us an unprecedented resolution to comprehend the mechanisms underlying leukemogenesis and drug resistance across various levels, including the genome, epigenome, transcriptome and proteome. Here, we provide an overview of the currently prevalent single-cell sequencing technologies and a detailed summary of single-cell studies conducted on leukemia, with a specific focus on four key aspects: (1) leukemia's clonal architecture, (2) frameworks to determine leukemia subtypes, (3) tumor microenvironment (TME) and (4) the drug-resistant mechanisms of leukemia. This review provides a comprehensive summary of current single-cell studies on leukemia and highlights the markers and mechanisms that show promising clinical implications for the diagnosis and treatment of leukemia.
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Affiliation(s)
- Jianche Liu
- Center for Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China
- International Campus, Zhejiang University-University of Edinburgh Institute (ZJU-UoE Institute), Zhejiang University School of Medicine, Zhejiang University, 718 East Haizhou Road, Haining, 314400, China
| | - Penglei Jiang
- Center for Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China
- Institute of Hematology, Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Zhejiang University, Hangzhou, 310058, China
| | - Zezhen Lu
- Center for Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China
- International Campus, Zhejiang University-University of Edinburgh Institute (ZJU-UoE Institute), Zhejiang University School of Medicine, Zhejiang University, 718 East Haizhou Road, Haining, 314400, China
| | - Zebin Yu
- Center for Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China
- Institute of Hematology, Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Zhejiang University, Hangzhou, 310058, China
| | - Pengxu Qian
- Center for Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310058, China.
- Liangzhu Laboratory, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China.
- Institute of Hematology, Zhejiang Engineering Laboratory for Stem Cell and Immunotherapy, Zhejiang University, Hangzhou, 310058, China.
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6
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Duran-Ferrer M, Martín-Subero JI. Epigenomic Characterization of Lymphoid Neoplasms. ANNUAL REVIEW OF PATHOLOGY 2024; 19:371-396. [PMID: 37832942 DOI: 10.1146/annurev-pathmechdis-051122-100856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Lymphoid neoplasms represent a heterogeneous group of disease entities and subtypes with markedly different molecular and clinical features. Beyond genetic alterations, lymphoid tumors also show widespread epigenomic changes. These severely affect the levels and distribution of DNA methylation, histone modifications, chromatin accessibility, and three-dimensional genome interactions. DNA methylation stands out as a tracer of cell identity and memory, as B cell neoplasms show epigenetic imprints of their cellular origin and proliferative history, which can be quantified by an epigenetic mitotic clock. Chromatin-associated marks are informative to uncover altered regulatory regions and transcription factor networks contributing to the development of distinct lymphoid tumors. Tumor-intrinsic epigenetic and genetic aberrations cooperate and interact with microenvironmental cells to shape the transcriptome at different phases of lymphoma evolution, and intraclonal heterogeneity can now be characterized by single-cell profiling. Finally, epigenetics offers multiple clinical applications, including powerful diagnostic and prognostic biomarkers as well as therapeutic targets.
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Affiliation(s)
- Martí Duran-Ferrer
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain;
| | - José Ignacio Martín-Subero
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain;
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Departamento de Fundamentos Clínicos, Universitat de Barcelona, Barcelona, Spain
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7
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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
- 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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8
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Huuhtanen J, Adnan-Awad S, Theodoropoulos J, Forstén S, Warfvinge R, Dufva O, Bouhlal J, Dhapola P, Duàn H, Laajala E, Kasanen T, Klievink J, Ilander M, Jaatinen T, Olsson-Strömberg U, Hjorth-Hansen H, Burchert A, Karlsson G, Kreutzman A, Lähdesmäki H, Mustjoki S. Single-cell analysis of immune recognition in chronic myeloid leukemia patients following tyrosine kinase inhibitor discontinuation. Leukemia 2024; 38:109-125. [PMID: 37919606 PMCID: PMC10776410 DOI: 10.1038/s41375-023-02074-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 09/19/2023] [Accepted: 10/17/2023] [Indexed: 11/04/2023]
Abstract
Immunological control of residual leukemia cells is thought to occur in patients with chronic myeloid leukemia (CML) that maintain treatment-free remission (TFR) following tyrosine kinase inhibitor (TKI) discontinuation. To study this, we analyzed 55 single-cell RNA and T cell receptor (TCR) sequenced samples (scRNA+TCRαβ-seq) from patients with CML (n = 13, N = 25), other cancers (n = 28), and healthy (n = 7). The high number and active phenotype of natural killer (NK) cells in CML separated them from healthy and other cancers. Most NK cells in CML belonged to the active CD56dim cluster with high expression of GZMA/B, PRF1, CCL3/4, and IFNG, with interactions with leukemic cells via inhibitory LGALS9-TIM3 and PVR-TIGIT interactions. Accordingly, upregulation of LGALS9 was observed in CML target cells and TIM3 in NK cells when co-cultured together. Additionally, we created a classifier to identify TCRs targeting leukemia-associated antigen PR1 and quantified anti-PR1 T cells in 90 CML and 786 healthy TCRβ-sequenced samples. Anti-PR1 T cells were more prevalent in CML, enriched in bone marrow samples, and enriched in the mature, cytotoxic CD8 + TEMRA cluster, especially in a patient maintaining TFR. Our results highlight the role of NK cells and anti-PR1 T cells in anti-leukemic immune responses in CML.
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Affiliation(s)
- Jani Huuhtanen
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland.
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland.
- Department of Computer Science, Aalto University, Espoo, Finland.
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland.
| | - Shady Adnan-Awad
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
- Foundation for the Finnish Cancer Institute, Helsinki, Finland
| | - Jason Theodoropoulos
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Sofia Forstén
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Rebecca Warfvinge
- Division of Molecular Hematology, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Olli Dufva
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Jonas Bouhlal
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Parashar Dhapola
- Division of Molecular Hematology, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Hanna Duàn
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Essi Laajala
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Tiina Kasanen
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Jay Klievink
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland
| | - Mette Ilander
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
| | - Taina Jaatinen
- Histocompatibility Testing Laboratory, Finnish Red Cross Blood Service, Helsinki, Finland
| | - Ulla Olsson-Strömberg
- Department of Medical Sciences, Uppsala University and Hematology Section, Uppsala University Hospital, Uppsala, Sweden
| | - Henrik Hjorth-Hansen
- Department of Hematology, St. Olavs Hospital, Trondheim, Norway
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Andreas Burchert
- Department of Hematology, Oncology and Immunology, Philipps University Marburg, and University Medical Center Giessen and Marburg, Marburg, Germany
| | - Göran Karlsson
- Division of Molecular Hematology, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Anna Kreutzman
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
| | - Harri Lähdesmäki
- Department of Computer Science, Aalto University, Espoo, Finland
| | - Satu Mustjoki
- Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki, Helsinki, Finland.
- Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland.
- iCAN Digital Precision Cancer Medicine Flagship, Helsinki, Finland.
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9
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Poos AM, Prokoph N, Przybilla MJ, Mallm JP, Steiger S, Seufert I, John L, Tirier SM, Bauer K, Baumann A, Rohleder J, Munawar U, Rasche L, Kortüm KM, Giesen N, Reichert P, Huhn S, Müller-Tidow C, Goldschmidt H, Stegle O, Raab MS, Rippe K, Weinhold N. Resolving therapy resistance mechanisms in multiple myeloma by multiomics subclone analysis. Blood 2023; 142:1633-1646. [PMID: 37390336 PMCID: PMC10733835 DOI: 10.1182/blood.2023019758] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/12/2023] [Indexed: 07/02/2023] Open
Abstract
Intratumor heterogeneity as a clinical challenge becomes most evident after several treatment lines, when multidrug-resistant subclones accumulate. To address this challenge, the characterization of resistance mechanisms at the subclonal level is key to identify common vulnerabilities. In this study, we integrate whole-genome sequencing, single-cell (sc) transcriptomics (scRNA sequencing), and chromatin accessibility (scATAC sequencing) together with mitochondrial DNA mutations to define subclonal architecture and evolution for longitudinal samples from 15 patients with relapsed or refractory multiple myeloma. We assess transcriptomic and epigenomic changes to resolve the multifactorial nature of therapy resistance and relate it to the parallel occurrence of different mechanisms: (1) preexisting epigenetic profiles of subclones associated with survival advantages, (2) converging phenotypic adaptation of genetically distinct subclones, and (3) subclone-specific interactions of myeloma and bone marrow microenvironment cells. Our study showcases how an integrative multiomics analysis can be applied to track and characterize distinct multidrug-resistant subclones over time for the identification of molecular targets against them.
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Affiliation(s)
- Alexandra M. Poos
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Nina Prokoph
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Moritz J. Przybilla
- Division Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
| | - Jan-Philipp Mallm
- Single Cell Open Lab, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Simon Steiger
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Isabelle Seufert
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Lukas John
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Stephan M. Tirier
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Katharina Bauer
- Single Cell Open Lab, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Anja Baumann
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Jennifer Rohleder
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Umair Munawar
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
| | - Leo Rasche
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
- Mildred Scheel Early Career Center, University Hospital of Würzburg, Würzburg, Germany
| | - K. Martin Kortüm
- Department of Internal Medicine 2, University Hospital of Würzburg, Würzburg, Germany
| | - Nicola Giesen
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Philipp Reichert
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Stefanie Huhn
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Carsten Müller-Tidow
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- National Center for Tumor Diseases, Heidelberg, Germany
| | - Hartmut Goldschmidt
- Department of Internal Medicine V, GMMG-Study Group at University Hospital Heidelberg, Heidelberg, Germany
| | - Oliver Stegle
- Division Computational Genomics and Systems Genetics, German Cancer Research Center, Heidelberg, Germany
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Marc S. Raab
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Molecular Hematology/Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Karsten Rippe
- Division of Chromatin Networks, German Cancer Research Center and BioQuant, Heidelberg, Germany
| | - Niels Weinhold
- Department of Internal Medicine V, University Hospital Heidelberg, Heidelberg, Germany
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10
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Parry EM, Lemvigh CK, Deng S, Dangle N, Ruthen N, Knisbacher BA, Broséus J, Hergalant S, Guièze R, Li S, Zhang W, Johnson C, Long JM, Yin S, Werner L, Anandappa A, Purroy N, Gohil S, Oliveira G, Bachireddy P, Shukla SA, Huang T, Khoury JD, Thakral B, Dickinson M, Tam C, Livak KJ, Getz G, Neuberg D, Feugier P, Kharchenko P, Wierda W, Olsen LR, Jain N, Wu CJ. ZNF683 marks a CD8 + T cell population associated with anti-tumor immunity following anti-PD-1 therapy for Richter syndrome. Cancer Cell 2023; 41:1803-1816.e8. [PMID: 37738974 PMCID: PMC10618915 DOI: 10.1016/j.ccell.2023.08.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 05/30/2023] [Accepted: 08/30/2023] [Indexed: 09/24/2023]
Abstract
Unlike many other hematologic malignancies, Richter syndrome (RS), an aggressive B cell lymphoma originating from indolent chronic lymphocytic leukemia, is responsive to PD-1 blockade. To discover the determinants of response, we analyze single-cell transcriptome data generated from 17 bone marrow samples longitudinally collected from 6 patients with RS. Response is associated with intermediate exhausted CD8 effector/effector memory T cells marked by high expression of the transcription factor ZNF683, determined to be evolving from stem-like memory cells and divergent from terminally exhausted cells. This signature overlaps with that of tumor-infiltrating populations from anti-PD-1 responsive solid tumors. ZNF683 is found to directly target key T cell genes (TCF7, LMO2, CD69) and impact pathways of T cell cytotoxicity and activation. Analysis of pre-treatment peripheral blood from 10 independent patients with RS treated with anti-PD-1, as well as patients with solid tumors treated with anti-PD-1, supports an association of ZNF683high T cells with response.
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Affiliation(s)
- Erin M Parry
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Camilla K Lemvigh
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Stephanie Deng
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Nathan Dangle
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Neil Ruthen
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | | | - Julien Broséus
- Inserm UMRS1256 Nutrition-Génétique et Exposition Aux Risques Environnementaux (N-GERE), Université de Lorraine, 54000 Nancy, France; Université de Lorraine, CHRU-Nancy, Service d'hématologie Biologique, Pôle Laboratoires, 54000 Nancy, France
| | - Sébastien Hergalant
- Inserm UMRS1256 Nutrition-Génétique et Exposition Aux Risques Environnementaux (N-GERE), Université de Lorraine, 54000 Nancy, France
| | - Romain Guièze
- CHU Clermont-Ferrand, 63000 Clermont-Ferrand, France; EA 7453 (CHELTER), Université Clermont Auvergne, 63001 Clermont-Ferrand, France
| | - Shuqiang Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Wandi Zhang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Connor Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jaclyn M Long
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA; Evergrande Center for Immunologic Diseases, Harvard Medical School and Brigham and Women's Hospital, Boston, MA 02115, USA; Division of Gastroenterology, Hepatology, and Nutrition, Boston Children's Hospital, Boston, MA 02115, USA
| | - Shanye Yin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Lillian Werner
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Annabelle Anandappa
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Noelia Purroy
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Satyen Gohil
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Giacomo Oliveira
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Pavan Bachireddy
- Department of Hematopoietic Biology and Malignancy, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Sachet A Shukla
- Department of Hematopoietic Biology and Malignancy, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Teddy Huang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Joseph D Khoury
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Beenu Thakral
- Department of Hematopathology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Michael Dickinson
- Peter MacCallum Cancer Centre, Royal Melbourne Hospital, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, VIC, Australia
| | - Constantine Tam
- Alfred Health, Melbourne, VIC, Australia; Monash University, Melbourne, VIC, Australia
| | - Kenneth J Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Donna Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Pierre Feugier
- Inserm UMRS1256 Nutrition-Génétique et Exposition Aux Risques Environnementaux (N-GERE), Université de Lorraine, 54000 Nancy, France; Université de Lorraine, CHRU Nancy, service d'hématologie clinique, Nancy, France
| | - Peter Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02215, USA
| | - William Wierda
- Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Lars Rønn Olsen
- Department of Health Technology, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Nitin Jain
- Department of Leukemia, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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11
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Parry EM, ten Hacken E, Wu CJ. Richter syndrome: novel insights into the biology of transformation. Blood 2023; 142:11-22. [PMID: 36758208 PMCID: PMC10356575 DOI: 10.1182/blood.2022016502] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023] Open
Abstract
Although the genetic landscape of chronic lymphocytic leukemia (CLL) has been broadly profiled by large-scale sequencing studies performed over the past decade, the molecular basis of the transformation of CLL into aggressive lymphoma, or Richter syndrome (RS), has remained incompletely characterized. Recent advances in computational methods of clonal deconvolution, as well as extensive sample collection efforts in this rapidly progressive malignancy, have now enabled comprehensive analysis of paired CLL and RS samples and have led to multiple new studies investigating the genetic, transcriptomic, and epigenetic origins of RS. In parallel, new genetically engineered and xenograft mouse models have provided the opportunity for gleaning fresh biological and mechanistic insights into RS development and stepwise evolution from antecedent CLL. Altogether, these studies have defined RS driver lesions and CLL risk lesions and identified pathways dysregulated in transformation. Moreover, unique molecular subtypes of RS have been revealed, including a disease marked by profound genomic instability with chromothripsis/chromoplexy and whole genome duplication. Novel profiling approaches, including single-cell DNA and transcriptome sequencing of RS biopsy specimens and cell-free DNA profiling of patient plasma, demonstrate promise for the timely identification of RS clones and may translate to noninvasive identification and early diagnosis of RS. This review summarizes the recent scientific advances in RS and supports the integrated study of human genomics with mouse modeling to provide an advanced understanding of the biological underpinnings of transformation. These recent studies have major implications for much-needed novel therapeutic strategies for this still largely incurable malignancy.
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Affiliation(s)
- 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
| | - Elisa ten Hacken
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
- Harvard Medical School, Boston, 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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12
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Lareau CA, Liu V, Muus C, Praktiknjo SD, Nitsch L, Kautz P, Sandor K, Yin Y, Gutierrez JC, Pelka K, Satpathy AT, Regev A, Sankaran VG, Ludwig LS. Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility. Nat Protoc 2023; 18:1416-1440. [PMID: 36792778 PMCID: PMC10317201 DOI: 10.1038/s41596-022-00795-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 11/11/2022] [Indexed: 02/17/2023]
Abstract
Natural sequence variation within mitochondrial DNA (mtDNA) contributes to human phenotypes and may serve as natural genetic markers in human cells for clonal and lineage tracing. We recently developed a single-cell multi-omic approach, called 'mitochondrial single-cell assay for transposase-accessible chromatin with sequencing' (mtscATAC-seq), enabling concomitant high-throughput mtDNA genotyping and accessible chromatin profiling. Specifically, our technique allows the mitochondrial genome-wide inference of mtDNA variant heteroplasmy along with information on cell state and accessible chromatin variation in individual cells. Leveraging somatic mtDNA mutations, our method further enables inference of clonal relationships among native ex vivo-derived human cells not amenable to genetic engineering-based clonal tracing approaches. Here, we provide a step-by-step protocol for the use of mtscATAC-seq, including various cell-processing and flow cytometry workflows, by using primary hematopoietic cells, subsequent single-cell genomic library preparation and sequencing that collectively take ~3-4 days to complete. We discuss experimental and computational data quality control metrics and considerations for the extension to other mammalian tissues. Overall, mtscATAC-seq provides a broadly applicable platform to map clonal relationships between cells in human tissues, investigate fundamental aspects of mitochondrial genetics and enable additional modes of multi-omic discovery.
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Affiliation(s)
- Caleb A Lareau
- Department of Pathology, Stanford University, Stanford, CA, USA.
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA.
| | - Vincent Liu
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Christoph Muus
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Samantha D Praktiknjo
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
| | - Lena Nitsch
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Pauline Kautz
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany
- Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - Katalin Sandor
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Yajie Yin
- Department of Pathology, Stanford University, Stanford, CA, USA
| | | | - Karin Pelka
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Ansuman T Satpathy
- Department of Pathology, Stanford University, Stanford, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Aviv Regev
- Genentech, South San Francisco, CA, USA.
| | - Vijay G Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Hematology/Oncology, Boston Children's Hospital and Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
| | - Leif S Ludwig
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
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13
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Oder B, Chatzidimitriou A, Langerak AW, Rosenquist R, Österholm C. Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia. Front Oncol 2023; 13:1143811. [PMID: 37091144 PMCID: PMC10117666 DOI: 10.3389/fonc.2023.1143811] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 03/22/2023] [Indexed: 04/08/2023] Open
Abstract
Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.
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Affiliation(s)
- Blaž Oder
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Anastasia Chatzidimitriou
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Anton W. Langerak
- Department of Immunology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Richard Rosenquist
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Cecilia Österholm
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Cecilia Österholm,
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14
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Penter L, ten Hacken E, Southard J, Lareau CA, Ludwig LS, Li S, Neuberg DS, Livak KJ, Wu CJ. Mitochondrial DNA Mutations as Natural Barcodes for Lineage Tracing of Murine Tumor Models. Cancer Res 2023; 83:667-672. [PMID: 36469010 PMCID: PMC9988704 DOI: 10.1158/0008-5472.can-22-0275] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 05/13/2022] [Accepted: 06/07/2022] [Indexed: 12/13/2022]
Abstract
Murine models are indispensable tools for functional genomic studies and preclinical testing of novel therapeutic approaches. Mitochondrial single-cell assay for transposase-accessible chromatin using sequencing (mtscATAC-seq) enables the dissection of cellular heterogeneity and clonal dynamics by capturing chromatin accessibility, copy-number variations (CNV), and mitochondrial DNA (mtDNA) mutations, yet its applicability to murine studies remains unexplored. By leveraging mtscATAC-seq in novel chronic lymphocytic leukemia and Richter syndrome mouse models, we report the detection of mtDNA mutations, particularly in highly proliferative murine cells, alongside CNV and chromatin state changes indicative of clonal evolution upon secondary transplant. This study thus demonstrates the feasibility and utility of multi-modal single-cell and natural barcoding approaches to characterize murine cancer models. SIGNIFICANCE mtDNA mutations can serve as natural barcodes to enable lineage tracing in murine cancer models, which can be used to provide new insights into disease biology and to identify therapeutic vulnerabilities.
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Affiliation(s)
- Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, 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
| | - Elisa ten Hacken
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Jackson Southard
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Caleb A. Lareau
- Department of Pathology, Stanford University, Stanford, California, USA
| | - Leif S. Ludwig
- 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, Charitéplatz 1, 10117 Berlin, Germany
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115 Berlin, Germany
| | - Shuqiang Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA
| | - Donna S. Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Kenneth J. Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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15
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ten Hacken E, Sewastianik T, Yin S, Hoffmann GB, Gruber M, Clement K, Penter L, Redd RA, Ruthen N, Hergalant S, Sholokhova A, Fell G, Parry EM, Broséus J, Guieze R, Lucas F, Hernández-Sánchez M, Baranowski K, Southard J, Joyal H, Billington L, Regis FFD, Witten E, Uduman M, Knisbacher BA, Li S, Lyu H, Vaisitti T, Deaglio S, Inghirami G, Feugier P, Stilgenbauer S, Tausch E, Davids MS, Getz G, Livak KJ, Bozic I, Neuberg DS, Carrasco RD, Wu CJ. In Vivo Modeling of CLL Transformation to Richter Syndrome Reveals Convergent Evolutionary Paths and Therapeutic Vulnerabilities. Blood Cancer Discov 2023; 4:150-169. [PMID: 36468984 PMCID: PMC9975769 DOI: 10.1158/2643-3230.bcd-22-0082] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 09/16/2022] [Accepted: 12/02/2022] [Indexed: 12/12/2022] Open
Abstract
Transformation to aggressive disease histologies generates formidable clinical challenges across cancers, but biological insights remain few. We modeled the genetic heterogeneity of chronic lymphocytic leukemia (CLL) through multiplexed in vivo CRISPR-Cas9 B-cell editing of recurrent CLL loss-of-function drivers in mice and recapitulated the process of transformation from indolent CLL into large cell lymphoma [i.e., Richter syndrome (RS)]. Evolutionary trajectories of 64 mice carrying diverse combinatorial gene assortments revealed coselection of mutations in Trp53, Mga, and Chd2 and the dual impact of clonal Mga/Chd2 mutations on E2F/MYC and interferon signaling dysregulation. Comparative human and murine RS analyses demonstrated tonic PI3K signaling as a key feature of transformed disease, with constitutive activation of the AKT and S6 kinases, downmodulation of the PTEN phosphatase, and convergent activation of MYC/PI3K transcriptional programs underlying enhanced sensitivity to MYC/mTOR/PI3K inhibition. This robust experimental system presents a unique framework to study lymphoid biology and therapy. SIGNIFICANCE Mouse models reflective of the genetic complexity and heterogeneity of human tumors remain few, including those able to recapitulate transformation to aggressive disease histologies. Herein, we model CLL transformation into RS through multiplexed in vivo gene editing, providing key insight into the pathophysiology and therapeutic vulnerabilities of transformed disease. This article is highlighted in the In This Issue feature, p. 101.
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Affiliation(s)
- Elisa ten Hacken
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Tomasz Sewastianik
- Harvard Medical School, Boston, Massachusetts
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Experimental Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Shanye Yin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | | | - Michaela Gruber
- CEMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Kendell Clement
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Molecular Pathology Unit, Center for Cancer Research and Center for Computational and Integrative Biology, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Pathology, Harvard Medical School, Boston, Massachusetts
| | - Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- 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
| | - Robert A. Redd
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Neil Ruthen
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sébastien Hergalant
- Inserm UMRS1256 Nutrition-Génétique et Exposition aux Risques Environnementaux (N-GERE), Université de Lorraine, Nancy, France
| | - Alanna Sholokhova
- Department of Applied Mathematics, University of Washington, Seattle, Washington
| | - Geoffrey Fell
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Erin M. Parry
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Julien Broséus
- Inserm UMRS1256 Nutrition-Génétique et Exposition aux Risques Environnementaux (N-GERE), Université de Lorraine, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service d'Hématologie Biologique, Pôle Laboratoires, Nancy, France
| | | | - Fabienne Lucas
- Harvard Medical School, Boston, Massachusetts
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - María Hernández-Sánchez
- Department of Biochemistry and Molecular Biology, Pharmacy School, Universidad Complutense de Madrid, Madrid, Spain
| | - Kaitlyn Baranowski
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Jackson Southard
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Heather Joyal
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Leah Billington
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Fara Faye D. Regis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Elizabeth Witten
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Mohamed Uduman
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Binyamin A. Knisbacher
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Cancer Research Center, Sheba Medical Center, Tel Hashomer, Israel
| | - Shuqiang Li
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Haoxiang Lyu
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Tiziana Vaisitti
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Silvia Deaglio
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Giorgio Inghirami
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Pierre Feugier
- Inserm UMRS1256 Nutrition-Génétique et Exposition aux Risques Environnementaux (N-GERE), Université de Lorraine, Nancy, France
- Université de Lorraine, CHRU-Nancy, Service d'Hématologie Biologique, Pôle Laboratoires, Nancy, France
| | - Stephan Stilgenbauer
- Department III of Internal Medicine III, Division of CLL, Ulm University, Ulm, Germany
| | - Eugen Tausch
- Department III of Internal Medicine III, Division of CLL, Ulm University, Ulm, Germany
| | - Matthew S. Davids
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Kenneth J. Livak
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ivana Bozic
- Department of Applied Mathematics, University of Washington, Seattle, Washington
| | - Donna S. Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ruben D. Carrasco
- Harvard Medical School, Boston, Massachusetts
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
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16
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Ludwig LS, Lareau CA. Concomitant Sequencing of Accessible Chromatin and Mitochondrial Genomes in Single Cells Using mtscATAC-Seq. Methods Mol Biol 2023; 2611:269-282. [PMID: 36807073 DOI: 10.1007/978-1-0716-2899-7_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Mitochondria are unique organelles of eukaryotic cells that carry their own multicopy number and circular genome. In most mammals, including humans and mice, the size of the chromosome is ~16,000 base pairs and unlike nuclear DNA, mitochondrial DNA (mtDNA) is not densely compacted. This results in mtDNA to be highly accessible for enzymes such as the Tn5 transposase, commonly used for accessible chromatin profiling of nuclear chromatinized DNA. Here, we describe a method for the concomitant sequencing of mtDNA and accessible chromatin in thousands of individual cells via the mitochondrial single-cell assay for transposase accessible chromatin by sequencing (mtscATAC-seq). Our approach extends the utility of existing scATAC-seq products and protocols as we (Nam et al, Nat Rev Genet 22:3-18, 2021) fix cells using formaldehyde to retain mitochondria and its mtDNA within its originating cell, (Buenrostro et al, Nat Methods 10:1213-1218, 2013) modify lysis conditions to permeabilize cells and mitochondria, and (Corces et al, Nat Methods 14:959-962, 2017) optimize bioinformatic processing protocols to collectively increase mitochondrial genome coverage for downstream analysis. Here, we discuss the essentials for the experimental and computational methodologies to generate and analyze thousands of multiomic profiles of single cells over the course of a few days, enabling the profiling of accessible chromatin and mtDNA genotypes to reconstruct clonal relationships and studies of mitochondrial genetics and disease.
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Affiliation(s)
- Leif S Ludwig
- Berlin Institute of Health at Charité Universitätsmedizin Berlin, Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Caleb A Lareau
- Departments of Genetics and Pathology, Stanford University, Stanford, CA, USA.
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17
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Kulis M, Martin-Subero JI. Integrative epigenomics in chronic lymphocytic leukaemia: Biological insights and clinical applications. Br J Haematol 2023; 200:280-290. [PMID: 36121003 DOI: 10.1111/bjh.18465] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/10/2022] [Accepted: 09/05/2022] [Indexed: 01/21/2023]
Abstract
Chronic lymphocytic leukaemia (CLL) is not only characterised by driver genetic alterations but by extensive epigenetic changes. Over the last decade, epigenomic studies have described the DNA methylome, chromatin accessibility, histone modifications and the three-dimensional (3D) genome architecture of CLL. Beyond its regulatory role, the DNA methylome contains imprints of the cellular origin and proliferative history of CLL cells. These two aspects are strong independent prognostic factors. Integrative analyses of chromatin marks have uncovered novel regulatory elements and altered transcription factor networks as non-genetic means mediating gene deregulation in CLL. Additionally, CLL cells display a disease-specific pattern of 3D genome interactions. From the technological perspective, we are currently witnessing a transition from bulk omics to single-cell analyses. This review aims at summarising the major findings from the epigenomics field as well as providing a prospect of the present and future of single-cell analyses in CLL.
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Affiliation(s)
- Marta Kulis
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jose Ignacio Martin-Subero
- Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.,Departamento de Fundamentos Clínicos, Universitat de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
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18
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Introduction to a review series on single-cell genomics: getting ready for clinical impact in leukemia and myeloid neoplasms. Blood 2023; 141:323-325. [PMID: 36103728 DOI: 10.1182/blood.2022017361] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 09/06/2022] [Accepted: 09/06/2022] [Indexed: 02/01/2023] Open
Abstract
Edited by Associate Editor Berthold Göttgens, this Review Series focuses on how the use of single-cell genomic and multiomic analyses are broadening our understanding of the complexity of leukemias and myeloid neoplasms. For acute myeloid leukemia, acute lymphoblastic leukemia, chronic lymphocytic leukemia, and myeloproliferative neoplasm, leading experts bring us up to date with recent data and speculate how these rapidly developing technologies may inform the directions of clinical care.
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19
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Nagler A, Wu CJ. The end of the beginning: application of single-cell sequencing to chronic lymphocytic leukemia. Blood 2023; 141:369-379. [PMID: 36095842 PMCID: PMC9936302 DOI: 10.1182/blood.2021014669] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/12/2022] [Accepted: 07/23/2022] [Indexed: 01/31/2023] Open
Abstract
Single-cell analysis has emerged over the past decade as a transformative technology informative for the systematic analysis of complex cell populations such as in cancers and the tumor immune microenvironment. The methodologic and analytical advancements in this realm have evolved rapidly, scaling from but a few cells at its outset to the current capabilities of processing and analyzing hundreds of thousands of individual cells at a time. The types of profiling attainable at individual cell resolution now range from genetic and transcriptomic characterization and extend to epigenomic and spatial analysis. Additionally, the increasing ability to achieve multiomic integration of these data layers now yields ever richer insights into diverse molecular disease subtypes and the patterns of cellular circuitry on a per-cancer basis. Over the years, chronic lymphocytic leukemia (CLL) consistently has been at the forefront of genomic investigation, given the ready accessibility of pure leukemia cells and immune cells from circulating blood of patients with this disease. Herein, we review the recent forays into the application of single-cell analysis to CLL, which are already revealing a new understanding of the natural progression of CLL, the impact of novel therapies, and the interactions with coevolving nonmalignant immune cell populations. As we emerge from the end of the beginning of this technologic revolution, CLL stands poised to reap the benefits of single-cell analysis from the standpoints of uncovering fresh fundamental biological knowledge and of providing a path to devising regimens of personalized diagnosis, treatment, and monitoring.
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Affiliation(s)
- Adi Nagler
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA
- Harvard Medical School, Boston, MA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA
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20
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Kim M, Mahmood M, Reznik E, Gammage PA. Mitochondrial DNA is a major source of driver mutations in cancer. Trends Cancer 2022; 8:1046-1059. [PMID: 36041967 PMCID: PMC9671861 DOI: 10.1016/j.trecan.2022.08.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/29/2022] [Accepted: 08/02/2022] [Indexed: 12/24/2022]
Abstract
Mitochondrial DNA (mtDNA) mutations are among the most common genetic events in all tumors and directly impact metabolic homeostasis. Despite the central role mitochondria play in energy metabolism and cellular physiology, the role of mutations in the mitochondrial genomes of tumors has been contentious. Until recently, genomic and functional studies of mtDNA variants were impeded by a lack of adequate tumor mtDNA sequencing data and available methods for mitochondrial genome engineering. These barriers and a conceptual fog surrounding the functional impact of mtDNA mutations in tumors have begun to lift, revealing a path to understanding the role of this essential metabolic genome in cancer initiation and progression. Here we discuss the history, recent developments, and challenges that remain for mitochondrial oncogenetics as the impact of a major new class of cancer-associated mutations is unveiled.
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Affiliation(s)
- Minsoo Kim
- Computational Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Ed Reznik
- Computational Oncology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Urology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Payam A Gammage
- CRUK Beatson Institute, Glasgow, UK; Institute of Cancer Sciences, University of Glasgow, Glasgow, UK.
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21
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Nadeu F, Royo R, Massoni-Badosa R, Playa-Albinyana H, Garcia-Torre B, Duran-Ferrer M, Dawson KJ, Kulis M, Diaz-Navarro A, Villamor N, Melero JL, Chapaprieta V, Dueso-Barroso A, Delgado J, Moia R, Ruiz-Gil S, Marchese D, Giró A, Verdaguer-Dot N, Romo M, Clot G, Rozman M, Frigola G, Rivas-Delgado A, Baumann T, Alcoceba M, González M, Climent F, Abrisqueta P, Castellví J, Bosch F, Aymerich M, Enjuanes A, Ruiz-Gaspà S, López-Guillermo A, Jares P, Beà S, Capella-Gutierrez S, Gelpí JL, López-Bigas N, Torrents D, Campbell PJ, Gut I, Rossi D, Gaidano G, Puente XS, Garcia-Roves PM, Colomer D, Heyn H, Maura F, Martín-Subero JI, Campo E. Detection of early seeding of Richter transformation in chronic lymphocytic leukemia. Nat Med 2022; 28:1662-1671. [PMID: 35953718 PMCID: PMC9388377 DOI: 10.1038/s41591-022-01927-8] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 07/01/2022] [Indexed: 02/06/2023]
Abstract
Richter transformation (RT) is a paradigmatic evolution of chronic lymphocytic leukemia (CLL) into a very aggressive large B cell lymphoma conferring a dismal prognosis. The mechanisms driving RT remain largely unknown. We characterized the whole genome, epigenome and transcriptome, combined with single-cell DNA/RNA-sequencing analyses and functional experiments, of 19 cases of CLL developing RT. Studying 54 longitudinal samples covering up to 19 years of disease course, we uncovered minute subclones carrying genomic, immunogenetic and transcriptomic features of RT cells already at CLL diagnosis, which were dormant for up to 19 years before transformation. We also identified new driver alterations, discovered a new mutational signature (SBS-RT), recognized an oxidative phosphorylation (OXPHOS)high–B cell receptor (BCR)low-signaling transcriptional axis in RT and showed that OXPHOS inhibition reduces the proliferation of RT cells. These findings demonstrate the early seeding of subclones driving advanced stages of cancer evolution and uncover potential therapeutic targets for RT. Single-cell genomic and transcriptomic analyses of longitudinal samples of patients with Richter syndrome reveal the presence and dynamics of clones driving transformation from chronic lymphocytic leukemia years before clinical manifestation
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Affiliation(s)
- Ferran Nadeu
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.
| | - Romina Royo
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Ramon Massoni-Badosa
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Heribert Playa-Albinyana
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Beatriz Garcia-Torre
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Martí Duran-Ferrer
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | | | - Marta Kulis
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Ander Diaz-Navarro
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología, Universidad de Oviedo, Oviedo, Spain
| | - Neus Villamor
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain
| | | | - Vicente Chapaprieta
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Julio Delgado
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain.,Universitat de Barcelona, Barcelona, Spain
| | - Riccardo Moia
- Division of Hematology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy
| | - Sara Ruiz-Gil
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Domenica Marchese
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
| | - Ariadna Giró
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Núria Verdaguer-Dot
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Mónica Romo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Guillem Clot
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Maria Rozman
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain
| | | | - Alfredo Rivas-Delgado
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain
| | - Tycho Baumann
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain.,Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Miguel Alcoceba
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Biología Molecular e Histocompatibilidad, IBSAL-Hospital Universitario, Centro de Investigación del Cáncer-IBMCC (USAL-CSIC), Salamanca, Spain
| | - Marcos González
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Biología Molecular e Histocompatibilidad, IBSAL-Hospital Universitario, Centro de Investigación del Cáncer-IBMCC (USAL-CSIC), Salamanca, Spain
| | - Fina Climent
- Hospital Universitari de Bellvitge-Institut d'Investigació Biomédica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - Pau Abrisqueta
- Department of Hematology, Vall d'Hebron Institute of Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Josep Castellví
- Department of Hematology, Vall d'Hebron Institute of Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Francesc Bosch
- Department of Hematology, Vall d'Hebron Institute of Oncology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Marta Aymerich
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain
| | - Anna Enjuanes
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Sílvia Ruiz-Gaspà
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Armando López-Guillermo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain.,Universitat de Barcelona, Barcelona, Spain
| | - Pedro Jares
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain.,Universitat de Barcelona, Barcelona, Spain
| | - Sílvia Beà
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain.,Universitat de Barcelona, Barcelona, Spain
| | | | - Josep Ll Gelpí
- Barcelona Supercomputing Center (BSC), Barcelona, Spain.,Universitat de Barcelona, Barcelona, Spain
| | - Núria López-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - David Torrents
- Barcelona Supercomputing Center (BSC), Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | | | - Ivo Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Davide Rossi
- Oncology Institute of Southern Switzerland, Bellinzona, Switzerland
| | - Gianluca Gaidano
- Division of Hematology, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy
| | - Xose S Puente
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología, Universidad de Oviedo, Oviedo, Spain
| | - Pablo M Garcia-Roves
- Universitat de Barcelona, Barcelona, Spain.,Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - Dolors Colomer
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Hospital Clínic of Barcelona, Barcelona, Spain.,Universitat de Barcelona, Barcelona, Spain
| | - Holger Heyn
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Francesco Maura
- Myeloma Service, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL, USA
| | - José I Martín-Subero
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain.,Universitat de Barcelona, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Elías Campo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain. .,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain. .,Hospital Clínic of Barcelona, Barcelona, Spain. .,Universitat de Barcelona, Barcelona, Spain.
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22
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Casado-Pelaez M, Bueno-Costa A, Esteller M. Single cell cancer epigenetics. Trends Cancer 2022; 8:820-838. [PMID: 35821003 DOI: 10.1016/j.trecan.2022.06.005] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 05/02/2022] [Accepted: 06/08/2022] [Indexed: 10/17/2022]
Abstract
Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations.
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Affiliation(s)
- Marta Casado-Pelaez
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Catalonia, Spain
| | - Alberto Bueno-Costa
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Catalonia, Spain
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Catalonia, Spain; Centro de Investigacion Biomedica en Red Cancer (CIBERONC), 28029 Madrid, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain; Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Catalonia, Spain.
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23
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Penter L, Gohil SH, Wu CJ. Natural Barcodes for Longitudinal Single Cell Tracking of Leukemic and Immune Cell Dynamics. Front Immunol 2022; 12:788891. [PMID: 35046946 PMCID: PMC8761982 DOI: 10.3389/fimmu.2021.788891] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 12/08/2021] [Indexed: 11/26/2022] Open
Abstract
Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences to serve as personal natural barcodes and review technical implementations in single-cell analysis workflows. Applications of these methodologies include the study of acquired therapeutic resistance and the dissection of donor- and host cellular interactions in the context of allogeneic hematopoietic stem cell transplantation.
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Affiliation(s)
- Livius Penter
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, United States
- Harvard Medical School, Boston, MA, United States
- 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
| | - Satyen H. Gohil
- Department of Academic Haematology, University College London Cancer Institute, London, United Kingdom
- Department of Haematology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, United States
- Harvard Medical School, Boston, MA, United States
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
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24
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Kwok M, Wu CJ. Clonal Evolution of High-Risk Chronic Lymphocytic Leukemia: A Contemporary Perspective. Front Oncol 2021; 11:790004. [PMID: 34976831 PMCID: PMC8716560 DOI: 10.3389/fonc.2021.790004] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 11/24/2021] [Indexed: 12/13/2022] Open
Abstract
Clonal evolution represents the natural process through which cancer cells continuously search for phenotypic advantages that enable them to develop and expand within microenvironmental constraints. In chronic lymphocytic leukemia (CLL), clonal evolution underpins leukemic progression and therapeutic resistance, with differences in clonal evolutionary dynamics accounting for its characteristically diverse clinical course. The past few years have witnessed profound changes in our understanding of CLL clonal evolution, facilitated by a maturing definition of high-risk CLL and an increasing sophistication of next-generation sequencing technology. In this review, we offer a modern perspective on clonal evolution of high-risk CLL, highlighting recent discoveries, paradigm shifts and unresolved questions. We appraise recent advances in our understanding of the molecular basis of CLL clonal evolution, focusing on the genetic and non-genetic sources of intratumoral heterogeneity, as well as tumor-immune dynamics. We review the technological innovations, particularly in single-cell technology, which have fostered these advances and represent essential tools for future discoveries. In addition, we discuss clonal evolution within several contexts of particular relevance to contemporary clinical practice, including the settings of therapeutic resistance to CLL targeted therapy and immunotherapy, as well as Richter transformation of CLL to high-grade lymphoma.
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Affiliation(s)
- Marwan Kwok
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
- Centre for Clinical Haematology, Queen Elizabeth Hospital Birmingham, Birmingham, United Kingdom
| | - Catherine J. Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Broad Institute of MIT and Harvard, Cambridge, MA, United States
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
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25
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Harnessing Mitochondrial Mutations to ATAC Clonal Evolution in CLL. Cancer Discov 2021; 11:2965-2967. [DOI: 10.1158/2159-8290.cd-21-1225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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26
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Alpár D, Egyed B, Bödör C, Kovács GT. Single-Cell Sequencing: Biological Insight and Potential Clinical Implications in Pediatric Leukemia. Cancers (Basel) 2021; 13:5658. [PMID: 34830811 PMCID: PMC8616124 DOI: 10.3390/cancers13225658] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 11/05/2021] [Accepted: 11/09/2021] [Indexed: 01/15/2023] Open
Abstract
Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15-20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40-85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.
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Affiliation(s)
- Donát Alpár
- HCEMM-SE Molecular Oncohematology Research Group, 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, H-1085 Budapest, Hungary; (D.A.); (B.E.); (C.B.)
| | - Bálint Egyed
- HCEMM-SE Molecular Oncohematology Research Group, 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, H-1085 Budapest, Hungary; (D.A.); (B.E.); (C.B.)
- 2nd Department of Pediatrics, Semmelweis University, H-1094 Budapest, Hungary
| | - Csaba Bödör
- HCEMM-SE Molecular Oncohematology Research Group, 1st Department of Pathology and Experimental Cancer Research, Semmelweis University, H-1085 Budapest, Hungary; (D.A.); (B.E.); (C.B.)
| | - Gábor T. Kovács
- 2nd Department of Pediatrics, Semmelweis University, H-1094 Budapest, Hungary
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