1
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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2
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Biran A, Yin S, Kretzmer H, Ten Hacken E, Parvin S, Lucas F, Uduman M, Gutierrez C, Dangle N, Billington L, Regis FF, Rassenti LZ, Mohammad A, Hoffmann GB, Stevenson K, Zheng M, Witten E, Fernandes SM, Tausch E, Sun C, Stilgenbauer S, Brown JR, Kipps TJ, Aster JC, Gnirke A, Neuberg DS, Letai A, Wang L, Carrasco RD, Meissner A, Wu CJ. Activation of Notch and Myc Signaling via B-cell-Restricted Depletion of Dnmt3a Generates a Consistent Murine Model of Chronic Lymphocytic Leukemia. Cancer Res 2021; 81:6117-6130. [PMID: 34686499 PMCID: PMC8678341 DOI: 10.1158/0008-5472.can-21-1273] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 08/18/2021] [Accepted: 10/19/2021] [Indexed: 11/16/2022]
Abstract
Chronic lymphocytic leukemia (CLL) is characterized by disordered DNA methylation, suggesting these epigenetic changes might play a critical role in disease onset and progression. The methyltransferase DNMT3A is a key regulator of DNA methylation. Although DNMT3A somatic mutations in CLL are rare, we found that low DNMT3A expression is associated with more aggressive disease. A conditional knockout mouse model showed that homozygous depletion of Dnmt3a from B cells results in the development of CLL with 100% penetrance at a median age of onset of 5.3 months, and heterozygous Dnmt3a depletion yields a disease penetrance of 89% with a median onset at 18.5 months, confirming its role as a haploinsufficient tumor suppressor. B1a cells were confirmed as the cell of origin of disease in this model, and Dnmt3a depletion resulted in focal hypomethylation and activation of Notch and Myc signaling. Amplification of chromosome 15 containing the Myc gene was detected in all CLL mice tested, and infiltration of high-Myc-expressing CLL cells in the spleen was observed. Notably, hyperactivation of Notch and Myc signaling was exclusively observed in the Dnmt3a CLL mice, but not in three other CLL mouse models tested (Sf3b1-Atm, Ikzf3, and MDR), and Dnmt3a-depleted CLL were sensitive to pharmacologic inhibition of Notch signaling in vitro and in vivo. Consistent with these findings, human CLL samples with lower DNMT3A expression were more sensitive to Notch inhibition than those with higher DNMT3A expression. Altogether, these results suggest that Dnmt3a depletion induces CLL that is highly dependent on activation of Notch and Myc signaling. SIGNIFICANCE: Loss of DNMT3A expression is a driving event in CLL and is associated with aggressive disease, activation of Notch and Myc signaling, and enhanced sensitivity to Notch inhibition.
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MESH Headings
- Animals
- Anti-Bacterial Agents/pharmacology
- Apoptosis
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Cell Proliferation
- DNA Methyltransferase 3A/genetics
- DNA Methyltransferase 3A/metabolism
- DNA Methyltransferase 3A/physiology
- Daptomycin/pharmacology
- Disease Models, Animal
- Drug Resistance, Neoplasm
- Female
- Gene Expression Regulation, Neoplastic
- Humans
- Leukemia, Lymphocytic, Chronic, B-Cell/drug therapy
- Leukemia, Lymphocytic, Chronic, B-Cell/metabolism
- Leukemia, Lymphocytic, Chronic, B-Cell/pathology
- Male
- Mice
- Mice, Inbred NOD
- Mice, Knockout
- Mice, SCID
- Prognosis
- Proto-Oncogene Proteins c-myc/genetics
- Proto-Oncogene Proteins c-myc/metabolism
- RNA-Seq
- Receptors, Notch/antagonists & inhibitors
- Receptors, Notch/genetics
- Receptors, Notch/metabolism
- Survival Rate
- Tumor Cells, Cultured
- Xenograft Model Antitumor Assays
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Affiliation(s)
- Anat Biran
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Shanye Yin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Helene Kretzmer
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Elisa Ten Hacken
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Salma Parvin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Fabienne Lucas
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Mohamed Uduman
- Center for Immuno-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Catherine Gutierrez
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Nathan Dangle
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Leah Billington
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Fara Faye Regis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Laura Z Rassenti
- Moores Cancer Center, University of California San Diego Health, La Jolla, California
| | - Arman Mohammad
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Data Science, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | | | - Kristen Stevenson
- Department of Data Science, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Mei Zheng
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Elizabeth Witten
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Stacey M Fernandes
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Eugen Tausch
- Department of Internal Medicine III, Ulm University, Ulm, Germany
| | - Clare Sun
- Hematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | | | - Jennifer R Brown
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Thomas J Kipps
- Moores Cancer Center, University of California San Diego Health, La Jolla, California
| | - John C Aster
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Andreas Gnirke
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Donna S Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Anthony Letai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Lili Wang
- Department of Systems Biology, Beckman Research Institute, City of Hope National Comprehensive Cancer Center, Monrovia, California
| | - Ruben D Carrasco
- Harvard Medical School, Boston, Massachusetts
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Alexander Meissner
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, 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
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3
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Lazarian G, Yin S, Ten Hacken E, Sewastianik T, Uduman M, Font-Tello A, Gohil SH, Li S, Kim E, Joyal H, Billington L, Witten E, Zheng M, Huang T, Severgnini M, Lefebvre V, Rassenti LZ, Gutierrez C, Georgopoulos K, Ott CJ, Wang L, Kipps TJ, Burger JA, Livak KJ, Neuberg DS, Baran-Marszak F, Cymbalista F, Carrasco RD, Wu CJ. A hotspot mutation in transcription factor IKZF3 drives B cell neoplasia via transcriptional dysregulation. Cancer Cell 2021; 39:380-393.e8. [PMID: 33689703 PMCID: PMC8034546 DOI: 10.1016/j.ccell.2021.02.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 09/25/2020] [Accepted: 02/04/2021] [Indexed: 12/20/2022]
Abstract
Hotspot mutation of IKZF3 (IKZF3-L162R) has been identified as a putative driver of chronic lymphocytic leukemia (CLL), but its function remains unknown. Here, we demonstrate its driving role in CLL through a B cell-restricted conditional knockin mouse model. Mutant Ikzf3 alters DNA binding specificity and target selection, leading to hyperactivation of B cell receptor (BCR) signaling, overexpression of nuclear factor κB (NF-κB) target genes, and development of CLL-like disease in elderly mice with a penetrance of ~40%. Human CLL carrying either IKZF3 mutation or high IKZF3 expression was associated with overexpression of BCR/NF-κB pathway members and reduced sensitivity to BCR signaling inhibition by ibrutinib. Our results thus highlight IKZF3 oncogenic function in CLL via transcriptional dysregulation and demonstrate that this pro-survival function can be achieved by either somatic mutation or overexpression of this CLL driver. This emphasizes the need for combinatorial approaches to overcome IKZF3-mediated BCR inhibitor resistance.
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Affiliation(s)
- Gregory Lazarian
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; INSERM, U978, Université Paris 13, Bobigny, France; Laboratoire d'Hématologie, APHP Hôpital Avicenne, Bobigny, France
| | - Shanye Yin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Elisa Ten Hacken
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Tomasz Sewastianik
- Harvard Medical School, Boston, MA, USA; Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Experimental Hematology, Institute of Hematology and Transfusion Medicine, Warsaw, Poland
| | - Mohamed Uduman
- Center for Immuno-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Alba Font-Tello
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Satyen H Gohil
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Academic Haematology, University College London, London, UK
| | - Shuqiang Li
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Ekaterina Kim
- Department of Leukemia, the University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Heather Joyal
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Leah Billington
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Elizabeth Witten
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Mei Zheng
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Teddy Huang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mariano Severgnini
- Center for Immuno-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Valerie Lefebvre
- Laboratoire d'Hématologie, APHP Hôpital Avicenne, Bobigny, France
| | | | - Catherine Gutierrez
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Katia Georgopoulos
- Cutaneous Biology Research Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Christopher J Ott
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lili Wang
- Department of Systems Biology, Beckman Research Institute, City of Hope National Comprehensive Cancer Center, Monrovia, CA, USA
| | - Thomas J Kipps
- Division of Hematology-Oncology, Department of Medicine, Moores Cancer Center, University of California, San Diego, USA
| | - Jan A Burger
- Department of Leukemia, the University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kenneth J Livak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Donna S Neuberg
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Fanny Baran-Marszak
- INSERM, U978, Université Paris 13, Bobigny, France; Laboratoire d'Hématologie, APHP Hôpital Avicenne, Bobigny, France
| | - Florence Cymbalista
- INSERM, U978, Université Paris 13, Bobigny, France; Laboratoire d'Hématologie, APHP Hôpital Avicenne, Bobigny, France
| | - Ruben D Carrasco
- Harvard Medical School, Boston, MA, USA; Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
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4
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Abstract
Denervated extensor digitorum longus (EDL) muscles in rats rapidly lose mass and contractile force. After two months of denervation, mass and maximum tetanic force have fallen to 31% and 2% of the values of contralateral control muscles. Our purpose was to determine if grafting a long-term denervated muscle into an innervated site provides an effective means of restoring its structure and function. EDL muscles that had been denervated for periods of 2-12 months were freely grafted into innervated sites of EDL muscles in 4-month inbred host animals. Contralateral normally innervated EDL muscles from the same donors were implanted into the opposite legs of the same hosts. Two months after grafting, the muscles were removed and measurements were made in vitro of isometric contractile properties. The grafts were then prepared for morphological analysts. In all cases, the maximum forces generated by innervated grafts of denervated muscles were greater than those generated by denervated muscles. However, when compared with grafts of control muscles in the contralateral limb, grafts of previously denervated muscles showed a steady decline in structural and functional recovery corresponding to the time of previous denervation. The decline was especially pronounced for muscles denervated between 2 and 7 months prior to grafting. Grafts of 7-month denervated muscles were restored to only 17% of the maximum tetanic force of contralateral control grafts compared with 83% for grafts of 2-month denervated muscles. The longer a muscle had been denervated prior to grafting, the higher proportion of thin atrophic muscle fibers it contained. We conclude that grafting into an innervated site improves the mass and maximum force of a muscle over the denervated state, but the longer the period of prior denervation the poorer the recovery of the grafted muscles.
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Affiliation(s)
- B M Carlson
- Department of Anatomy and Cell Biology, 4643 Medical Science II Building, University of Michigan, Ann Arbor, Michigan 48109, USA Department of Biology and Physiology, University of Michigan, Ann Arbor, Michigan 48109, USA Institute of Gerontology, University of Michigan, Ann Arbor, Michigan 48109, USA
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5
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Abstract
The dystrophin protein complex (DPC), composed of at least 10 proteins that associate with dystrophin, is critical for the maintenance of normal muscle fiber structure and physiology. In this study, we used immunohistochemistry and confocal microscopy to examine the relative abundance and distribution of several of these proteins in muscle biopsies taken from patients with various muscular dystrophies. The optical sectioning capability of confocal microscopy allowed us to comprehensively analyze the semiquantitative expression of components of the DPC. Alpha-sarcoglycan-deficient patients displayed a marked reduction in membrane immunostaining of the sarcoglycan complex. Gamma-sarcoglycan-deficient patients showed variable decreased immunostaining of the sarcoglycan complex proteins. When beta-sarcoglycan was expressed appropriately at the sarcolemma of gamma-sarcoglycan-deficient patients, intracellular labeling of beta-sarcoglycan was also present. Beta-sarcoglycan-deficient patients showed poor localization of extracellular matrix proteins in addition to a complete absence of the sarcoglycans. Merosin-deficient patients showed relatively normal immunostaining levels of all other members of the DPC. Finally, dystrophin-deficient patients showed little or no change in the expression of extracellular matrix proteins; however, some sarcoglycans were significantly decreased. These data allowed us to suggest unique fundamental interactions between the members of the DPC.
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Affiliation(s)
- R Draviam
- Department of Cell Biology and Physiology, University of Pittsburgh School of Medicine, S225 Biomedical Science Tower, Pittsburgh, Pennsylvania 15261, USA
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6
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Abstract
The discovery of dystrophin and its definition as the causative molecule in Duchenne Muscular Dystrophy has led to a renewed interest in the molecular structure of the muscle fiber plasma membrane and its association with the extracellular basal lamina. The original identification of dystrophin gave credence to the possibility that the plasma membrane of the muscle fiber may be highly organized and involved in maintaining appropriate homeostasis in this actively contracting cellular system. In this review, we examine the currently known members of the muscle fiber plasma membrane cytoskeleton and the interactions that occur between the different members of this complex using histological, electron microscopic, and confocal methods. From our studies and others cited in this review, it is clear that the dystrophin cytoskeletal complex is not completely understood and component molecules continue to be discovered. Perhaps equally importantly, currently defined molecules (such as alpha-actinin or neuronal nitric oxide synthase) are being recognized as being specifically associated with the complex. What is striking from all of the studies, to date, is that while we are able to identify members of the dystrophin cytoskeletal complex and while we are able to associate mutations of individual molecules with disease(s), we are still unable to truly define the roles of each of the molecules in maintaining the normal physiology of the muscle fiber.
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Affiliation(s)
- S C Watkins
- Department of Cell Biology and Physiology, University of Pittsburgh, School of Medicine, Pittsburgh, Pennsylvania 15261, USA.
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7
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Affiliation(s)
- L Billington
- Department of Biology, University of Michigan, Ann Arbor, USA
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8
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Abstract
Disruption of the nerve supply results in the rapid loss of mass and contractile force in skeletal muscles. These losses are reversible to a high degree in short-term denervated muscles with grafting and nerve implantation. However, return is much poorer in long-term denervated muscles. This study examined the basis for the differences in the recovery of non-denervated and 7-month denervated rat extensor digitorum longus (EDL) muscles after grafting and nerve implantation. We found that the level of recovery is related to the ability of muscle fibers to degenerate and regenerate after grafting. Fibers within long-term denervated muscles do not degenerate and regenerate as well as those within muscles which are not denervated prior to grafting. The functional recovery of the denervated muscles is significantly improved when their fibers are induced to degenerate with the myotoxic anesthetic, Marcaine, Degeneration of these fibers is followed by massive regeneration. The finding that denervated muscles are capable of being restored to a significant level by inducing regeneration may be useful in the clinical treatment of denervated muscles.
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Affiliation(s)
- L Billington
- University of Pittsburgh, Department of Neurology, PA 15261, USA. billing + @pitt.edu
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