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Frank D, Patnana PK, Vorwerk J, Mao L, Gopal LM, Jung N, Hennig T, Ruhnke L, Frenz JM, Kuppusamy M, Autry R, Wei L, Sun K, Mohammed Ahmed HM, Künstner A, Busch H, Müller H, Hutter S, Hoermann G, Liu L, Xie X, Al-Matary Y, Nimmagadda SC, Cano FC, Heuser M, Thol F, Göhring G, Steinemann D, Thomale J, Leitner T, Fischer A, Rad R, Röllig C, Altmann H, Kunadt D, Berdel WE, Hüve J, Neumann F, Klingauf J, Calderon V, Opalka B, Dührsen U, Rosenbauer F, Dugas M, Varghese J, Reinhardt HC, von Bubnoff N, Möröy T, Lenz G, Batcha AMN, Giorgi M, Selvam M, Wang E, McWeeney SK, Tyner JW, Stölzel F, Mann M, Jayavelu AK, Khandanpour C. Germ line variant GFI1-36N affects DNA repair and sensitizes AML cells to DNA damage and repair therapy. Blood 2023; 142:2175-2191. [PMID: 37756525 PMCID: PMC10733838 DOI: 10.1182/blood.2022015752] [Citation(s) in RCA: 0] [Impact Index Per Article: 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: 02/07/2022] [Revised: 07/06/2023] [Accepted: 07/24/2023] [Indexed: 09/29/2023] Open
Abstract
ABSTRACT Growth factor independence 1 (GFI1) is a DNA-binding transcription factor and a key regulator of hematopoiesis. GFI1-36N is a germ line variant, causing a change of serine (S) to asparagine (N) at position 36. We previously reported that the GFI1-36N allele has a prevalence of 10% to 15% among patients with acute myeloid leukemia (AML) and 5% to 7% among healthy Caucasians and promotes the development of this disease. Using a multiomics approach, we show here that GFI1-36N expression is associated with increased frequencies of chromosomal aberrations, mutational burden, and mutational signatures in both murine and human AML and impedes homologous recombination (HR)-directed DNA repair in leukemic cells. GFI1-36N exhibits impaired binding to N-Myc downstream-regulated gene 1 (Ndrg1) regulatory elements, causing decreased NDRG1 levels, which leads to a reduction of O6-methylguanine-DNA-methyltransferase (MGMT) expression levels, as illustrated by both transcriptome and proteome analyses. Targeting MGMT via temozolomide, a DNA alkylating drug, and HR via olaparib, a poly-ADP ribose polymerase 1 inhibitor, caused synthetic lethality in human and murine AML samples expressing GFI1-36N, whereas the effects were insignificant in nonmalignant GFI1-36S or GFI1-36N cells. In addition, mice that received transplantation with GFI1-36N leukemic cells treated with a combination of temozolomide and olaparib had significantly longer AML-free survival than mice that received transplantation with GFI1-36S leukemic cells. This suggests that reduced MGMT expression leaves GFI1-36N leukemic cells particularly vulnerable to DNA damage initiating chemotherapeutics. Our data provide critical insights into novel options to treat patients with AML carrying the GFI1-36N variant.
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Affiliation(s)
- Daria Frank
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
| | - Pradeep Kumar Patnana
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
- Department of Hematology and Oncology, University Hospital of Schleswig-Holstein, University Cancer Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Jan Vorwerk
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
| | - Lianghao Mao
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
| | - Lavanya Mokada Gopal
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
| | - Noelle Jung
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
| | - Thorben Hennig
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
| | - Leo Ruhnke
- Department of Internal Medicine I, University Hospital Dresden, Technical University Dresden, Dresden, Germany
| | - Joris Maximillian Frenz
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
| | - Maithreyan Kuppusamy
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
| | - Robert Autry
- Hopp Children’s Cancer Center, Heidelberg, Germany
| | - Lanying Wei
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Institute of Medical Informatics, University of Münster, Münster, Germany
| | - Kaiyan Sun
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
| | - Helal Mohammed Mohammed Ahmed
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology and Oncology, University Hospital of Schleswig-Holstein, University Cancer Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Axel Künstner
- Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Hauke Busch
- Medical Systems Biology Group, Lübeck Institute of Experimental Dermatology, University of Lübeck, Lübeck, Germany
- Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany
| | | | | | | | - Longlong Liu
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology, First Affiliated Hospital, Guangzhou Medical University, Guangzhou, China
| | - Xiaoqing Xie
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology-Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yahya Al-Matary
- Department of Dermatology, University Hospital Essen, Essen, Germany
| | - Subbaiah Chary Nimmagadda
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology and Oncology, University Hospital of Schleswig-Holstein, University Cancer Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Fiorella Charles Cano
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Michael Heuser
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Felicitas Thol
- Department of Hematology, Hemostasis, Oncology and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany
| | - Gudrun Göhring
- Department of Human Genetics, Hannover Medical School, Hannover, Germany
| | - Doris Steinemann
- Department of Human Genetics, Hannover Medical School, Hannover, Germany
| | - Jürgen Thomale
- Institute of Cell Biology, University Hospital Essen, Essen, Germany
| | - Theo Leitner
- Department of Hematology and Oncology, University Hospital of Schleswig-Holstein, University Cancer Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Anja Fischer
- Institute of Molecular Oncology and Functional Genomics, School of Medicine, Technische Universität München, Munich, Germany
- Center for Translational Cancer Research, School of Medicine, Technische Universität München, Munich, Germany
| | - Roland Rad
- Institute of Molecular Oncology and Functional Genomics, School of Medicine, Technische Universität München, Munich, Germany
- Center for Translational Cancer Research, School of Medicine, Technische Universität München, Munich, Germany
- Department of Medicine II, Klinikum Rechts der Isar, School of Medicine, Technische Universität München, Munich, Germany
| | | | | | | | - Wolfgang E. Berdel
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
| | - Jana Hüve
- Fluorescence Microscopy Facility Münster, Institute of Medical Physics and Biophysics, University of Münster, Münster, Germany
| | - Felix Neumann
- Fluorescence Microscopy Facility Münster, Institute of Medical Physics and Biophysics, University of Münster, Münster, Germany
- Refined Laser Systems GmbH, Münster, Germany
| | - Jürgen Klingauf
- Fluorescence Microscopy Facility Münster, Institute of Medical Physics and Biophysics, University of Münster, Münster, Germany
- Institute of Medical Physics and Biophysics, University of Münster, Münster, Germany
| | - Virginie Calderon
- Bioinformatic Core Facility, Institut de Recherches Cliniques de Montréal, Montréal, QC, Canada
| | - Bertram Opalka
- Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
| | - Ulrich Dührsen
- Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
| | - Frank Rosenbauer
- Institute of Molecular Tumor Biology, Faculty of Medicine, University of Münster, Münster, Germany
| | - Martin Dugas
- Institute of Medical Informatics, University Hospital Heidelberg, Heidelberg, Germany
| | - Julian Varghese
- Institute of Medical Informatics, University of Münster, Münster, Germany
| | - Hans Christian Reinhardt
- Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
| | - Nikolas von Bubnoff
- Department of Hematology and Oncology, University Hospital of Schleswig-Holstein, University Cancer Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Tarik Möröy
- Institut de Recherches Cliniques de Montréal, Montreal, QC, Canada
- Division of Experimental Medicine, McGill University, Montreal, QC, Canada
- Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, Montreal, QC, Canada
| | - Georg Lenz
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
| | - Aarif M. N. Batcha
- Institute of Medical Data Processing, Biometrics and Epidemiology, Faculty of Medicine, Ludwig Maximilians University Munich, Munich, Germany
- Data Integration for Future Medicine, Ludwig Maximilian University Munich, Munich, Germany
| | - Marianna Giorgi
- Roswell Park Comprehensive Cancer Center, Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY
| | - Murugan Selvam
- Roswell Park Comprehensive Cancer Center, Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY
| | - Eunice Wang
- Roswell Park Comprehensive Cancer Center, Jacobs School of Medicine and Biomedical Sciences, Buffalo, NY
| | - Shannon K. McWeeney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR
- Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR
| | - Jeffrey W. Tyner
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR
- Department of Cell, Developmental and Cancer Biology, Oregon Health & Science University, Portland, OR
| | - Friedrich Stölzel
- Department of Internal Medicine I, University Hospital Dresden, Technical University Dresden, Dresden, Germany
- Department of Medicine II, Division for Stem Cell Transplantation and Cellular Immunotherapy, University Cancer Center Schleswig-Holstein, University Hospital Schleswig-Holstein Kiel, Christian Albrecht University Kiel, Kiel, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Munich, Germany
| | - Ashok Kumar Jayavelu
- Proteomics and Cancer Cell Signaling Group, Clinical Cooperation Unit Pediatric Leukemia, German Cancer Research Center and Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Heidelberg, Germany
- Hopp Children’s Cancer Center, Heidelberg, Germany
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Munich, Germany
- Molecular Medicine Partnership Unit, European Molecular Biology Laboratory and Medical Faculty, University of Heidelberg, Heidelberg, Germany
| | - Cyrus Khandanpour
- Department of Medicine A, Hematology, Oncology and Pneumology, University Hospital Münster, Münster, Germany
- Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
- Department of Hematology and Oncology, University Hospital of Schleswig-Holstein, University Cancer Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
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2
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Batcha AMN, Buckup N, Bamopoulos SA, Jurinovic V, Rothenberg-Thurley M, Gittinger H, Ksienzyk B, Dufour A, Schneider S, Kontro M, Saad J, Heckmann CA, Sauerland C, Görlich D, Berdel WE, Wörmann BJ, Krug U, Braess J, Mansmann U, Hiddemann W, Spiekermann K, Metzeler KH, Herold T. Germline SNPs previously implicated as prognostic biomarkers do not associate with outcomes in intensively treated AML. Blood Adv 2023; 7:1040-1044. [PMID: 36149944 PMCID: PMC10036512 DOI: 10.1182/bloodadvances.2022007988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/30/2022] [Accepted: 09/09/2022] [Indexed: 11/20/2022] Open
Affiliation(s)
- Aarif M N Batcha
- Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
- Data Integration for Future Medicine (DIFUTURE), LMU Munich, Munich, Germany
| | - Nele Buckup
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
| | - Stefanos A Bamopoulos
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
- Department of Hematology, Oncology and Tumor Immunology (Campus Benjamin Franklin), Charité University Medicine Berlin, Berlin, Germany
| | - Vindi Jurinovic
- Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
| | - Maja Rothenberg-Thurley
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
| | - Hanna Gittinger
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
| | - Bianka Ksienzyk
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
| | - Annika Dufour
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
| | - Stephanie Schneider
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
- Institute of Human Genetics, University Hospital, LMU Munich, Munich, Germany
| | - Mika Kontro
- Department of Haematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Foundation for the Finnish Cancer Institute, Helsinki, Finland
| | - Joseph Saad
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Caroline A Heckmann
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Cristina Sauerland
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
| | - Wolfgang E Berdel
- Department of Medicine A, Hematology and Oncology, University of Münster, Münster, Germany
| | | | - Utz Krug
- Department of Medicine III, Hospital Leverkusen, Leverkusen, Germany
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany
| | - Ulrich Mansmann
- Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
- Data Integration for Future Medicine (DIFUTURE), LMU Munich, Munich, Germany
- German Cancer Consortium, Heidelberg, Germany
- German Cancer Research Center, Heidelberg, Germany
| | - Wolfgang Hiddemann
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium, Heidelberg, Germany
- German Cancer Research Center, Heidelberg, Germany
| | - Karsten Spiekermann
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium, Heidelberg, Germany
- German Cancer Research Center, Heidelberg, Germany
| | - Klaus H Metzeler
- Department of Hematology and Cellular Therapy, University Hospital Leipzig, Leipzig, Germany
| | - Tobias Herold
- Department of Medicine III, Laboratory for Leukemia Diagnostics, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium, Heidelberg, Germany
- German Cancer Research Center, Heidelberg, Germany
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3
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Uhl B, Haring F, Slotta-Huspenina J, Luft J, Schneewind V, Hildinger J, Wu Z, Steiger K, Smiljanov B, Batcha AMN, Keppler OT, Hellmuth JC, Lahmer T, Stock K, Weiss BG, Canis M, Stark K, Bromberger T, Moser M, Schulz C, Weichert W, Zuchtriegel G, Reichel CA. Vitronectin promotes immunothrombotic dysregulation in the venular microvasculature. Front Immunol 2023; 14:1078005. [PMID: 36845099 PMCID: PMC9945350 DOI: 10.3389/fimmu.2023.1078005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 01/05/2023] [Indexed: 02/10/2023] Open
Abstract
Microvascular immunothrombotic dysregulation is a critical process in the pathogenesis of severe systemic inflammatory diseases. The mechanisms controlling immunothrombosis in inflamed microvessels, however, remain poorly understood. Here, we report that under systemic inflammatory conditions the matricellular glycoproteinvitronectin (VN) establishes an intravascular scaffold, supporting interactions of aggregating platelets with immune cells and the venular endothelium. Blockade of the VN receptor glycoprotein (GP)IIb/IIIa interfered with this multicellular interplay and effectively prevented microvascular clot formation. In line with these experimental data, particularly VN was found to be enriched in the pulmonary microvasculature of patients with non-infectious (pancreatitis-associated) or infectious (coronavirus disease 2019 (COVID-19)-associated) severe systemic inflammatory responses. Targeting the VN-GPIIb/IIIa axis hence appears as a promising, already feasible strategy to counteract microvascular immunothrombotic dysregulation in systemic inflammatory pathologies.
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Affiliation(s)
- Bernd Uhl
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany,*Correspondence: Bernd Uhl,
| | - Florian Haring
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | | | - Joshua Luft
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Vera Schneewind
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Jonas Hildinger
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Zhengquan Wu
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Katja Steiger
- Department of Pathology, Technical University of Munich, Munich, Germany
| | - Bojan Smiljanov
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Aarif M. N. Batcha
- Institute of Medical Data Processing, Biometrics, and Epidemiology (IBE), University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany,Data Integration for Future Medicine (DiFuture), University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Oliver T. Keppler
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany,German Centre for Infection Research (DZIF), Partner Site München, Munich, Germany
| | - Johannes C. Hellmuth
- Department of Medicine III, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Munich, Germany,COVID-19 Registry of the LMU Munich (CORKUM), University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Tobias Lahmer
- Department of Internal Medicine II, Technical University of Munich, Munich, Germany
| | - Konrad Stock
- Department of Nephrology, Technical University of Munich, Munich, Germany
| | - Bernhard G. Weiss
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany
| | - Martin Canis
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany
| | - Konstantin Stark
- Department of Cardiology, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Thomas Bromberger
- Institute of Experimental Hematology, Technical University of Munich, Munich, Germany
| | - Markus Moser
- Institute of Experimental Hematology, Technical University of Munich, Munich, Germany
| | - Christian Schulz
- Department of Cardiology, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Wilko Weichert
- Department of Pathology, Technical University of Munich, Munich, Germany
| | - Gabriele Zuchtriegel
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
| | - Christoph A. Reichel
- Department of Otorhinolaryngology, University Hospital, Ludwig-Maximilians-Universität München (LMU), Munich, Germany,Walter Brendel Centre of Experimental Medicine, University Hospital, Ludwig-Maximilians-Universität München (LMU) Munich, Munich, Germany
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4
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Manz KM, Batcha AMN, Mansmann U. [Regional and Temporal Trends in SARS-CoV-2-Associated Mortality in Bavaria: An Age-Stratified Analysis Over 5 Quarters for Persons Aged 50 and Older]. Gesundheitswesen 2022; 84:e2-e10. [PMID: 35168287 DOI: 10.1055/a-1714-8184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the influence of regional factors such as incidence rate, hospitalizations, socio-economic status and nursing homes on the regional and temporal heterogeneity of SARS-CoV-2-associated mortality in Bavaria. METHODOLOGY Official Bavarian SARS-CoV-2 reporting data were considered for three age groups (50-64, 65-74,>74 years) between March 2020 and April 2021. Maps of regional standardized mortality rates were spatially smoothed using a Bayesian hierarchical model. RESULTS The picture of regional mortality was heterogeneous with an increasing gradient toward the northeast. Adjustment for standardized incidence rates, hospitalizations of infected persons, and availability of care homes for the elderly levelled the heterogeneity. CONCLUSION The north-east gradient in Bavarian SARS-CoV-2-specific mortality rates is clearly explained by the comparable gradient in regional incidence rates. Other regional factors show a less clear influence.
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Affiliation(s)
- Kirsi Marjaana Manz
- Institut für Medizinische Informationsverarbeitung Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, München, Germany
| | - Aarif M N Batcha
- Institut für Medizinische Informationsverarbeitung Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, München, Germany.,Data Integration for Future Medicine (DiFuture, www.difuture.de), Ludwig-Maximilians-Universität München, München, Germany
| | - Ulrich Mansmann
- Institut für Medizinische Informationsverarbeitung Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, München, Germany.,Pettenkofer School of Public Health, Ludwig Maximilians University Munich, Munchen, Germany
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5
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Kerbs P, Vosberg S, Krebs S, Graf A, Blum H, Swoboda A, Batcha AMN, Mansmann U, Metzler D, Heckman CA, Herold T, Greif PA. Fusion gene detection by RNA-sequencing complements diagnostics of acute myeloid leukemia and identifies recurring NRIP1-MIR99AHG rearrangements. Haematologica 2022; 107:100-111. [PMID: 34134471 PMCID: PMC8719081 DOI: 10.3324/haematol.2021.278436] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 05/03/2021] [Indexed: 12/04/2022] Open
Abstract
Identification of fusion genes in clinical routine is mostly based on cytogenetics and targeted molecular genetics, such as metaphase karyotyping, fluorescence in situ hybridization and reverse-transcriptase polymerase chain reaction. However, sequencing technologies are becoming more important in clinical routine as processing time and costs per sample decrease. To evaluate the performance of fusion gene detection by RNAsequencing compared to standard diagnostic techniques, we analyzed 806 RNA-sequencing samples from patients with acute myeloid leukemia using two state-of-the-art software tools, namely Arriba and FusionCatcher. RNA-sequencing detected 90% of fusion events that were reported by routine with high evidence, while samples in which RNA-sequencing failed to detect fusion genes had overall lower and inhomogeneous sequence coverage. Based on properties of known and unknown fusion events, we developed a workflow with integrated filtering strategies for the identification of robust fusion gene candidates by RNA-sequencing. Thereby, we detected known recurrent fusion events in 26 cases that were not reported by routine and found discrepancies in evidence for known fusion events between routine and RNA-sequencing in three cases. Moreover, we identified 157 fusion genes as novel robust candidates and comparison to entries from ChimerDB or Mitelman Database showed novel recurrence of fusion genes in 14 cases. Finally, we detected the novel recurrent fusion gene NRIP1- MIR99AHG resulting from inv(21)(q11.2;q21.1) in nine patients (1.1%) and LTN1-MX1 resulting from inv(21)(q21.3;q22.3) in two patients (0.25%). We demonstrated that NRIP1-MIR99AHG results in overexpression of the 3' region of MIR99AHG and the disruption of the tricistronic miRNA cluster miR-99a/let-7c/miR-125b-2. Interestingly, upregulation of MIR99AHG and deregulation of the miRNA cluster, residing in the MIR99AHG locus, are known mechanisms of leukemogenesis in acute megakaryoblastic leukemia. Our findings demonstrate that RNA-sequencing has a strong potential to improve the systematic detection of fusion genes in clinical applications and provides a valuable tool for fusion discovery.
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Affiliation(s)
- Paul Kerbs
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sebastian Vosberg
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, LMU Munich, Munich, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, LMU Munich, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, LMU Munich, Munich, Germany
| | - Anja Swoboda
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Aarif M N Batcha
- Department of Medical Data Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
| | - Ulrich Mansmann
- Department of Medical Data Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany
| | - Dirk Metzler
- Division of Evolutionary Biology, Faculty of Biology, LMU Munich, Planegg-Martinsried, Germany
| | - Caroline A Heckman
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Tobias Herold
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp A Greif
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), partner site Munich; and; German Cancer Research Center (DKFZ), Heidelberg, Germany.
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6
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Papaioannou D, Ozer HG, Nicolet D, Urs AP, Herold T, Mrózek K, Batcha AMN, Metzeler KH, Yilmaz AS, Volinia S, Bill M, Kohlschmidt J, Pietrzak M, Walker CJ, Carroll AJ, Braess J, Powell BL, Eisfeld AK, Uy GL, Wang ES, Kolitz JE, Stone RM, Hiddemann W, Byrd JC, Bloomfield CD, Garzon R. Clinical and molecular relevance of genetic variants in the non-coding transcriptome of patients with cytogenetically normal acute myeloid leukemia. Haematologica 2021; 107:1034-1044. [PMID: 34261293 DOI: 10.3324/haematol.2021.266643] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Indexed: 11/09/2022] Open
Abstract
Expression levels of long non-coding RNAs (lncRNAs) have been shown to associate with clinical outcome of patients with cytogenetically normal acute myeloid leukemia (CN-AML). However, the frequency and clinical significance of genetic variants in the nucleotide sequences of lncRNAs in AML patients is unknown. Herein, we analyzed total RNA sequencing data of 377 younger adults (aged.
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Affiliation(s)
- Dimitrios Papaioannou
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; Laura and Isaac Perlmutter Cancer Center, New York University School of Medicine, NYU Langone Health, New York
| | - Hatice G Ozer
- The Ohio State University, Department of Biomedical Informatics, Columbus
| | - Deedra Nicolet
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; The Ohio State University Comprehensive Cancer Center, Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH; Alliance Statistics and Data Center, The Ohio State University, Comprehensive Cancer Center, Columbus
| | - Amog P Urs
- The Ohio State University, Comprehensive Cancer Center, Columbus
| | - Tobias Herold
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany; Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Center for Environmental Health (HMGU), Munich
| | - Krzysztof Mrózek
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; The Ohio State University Comprehensive Cancer Center, Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus
| | - Aarif M N Batcha
- Institute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany; Medical Data Integration Center (MeDIC), University Hospital, LMU Munich
| | - Klaus H Metzeler
- Department of Hematology, Cell Therapy and Hemostaseology, University Hospital Leipzig, Leipzig
| | - Ayse S Yilmaz
- The Ohio State University, Department of Biomedical Informatics, Columbus
| | - Stefano Volinia
- Department of Morphology, Surgery and Experimental Medicine, University of Ferrara, Ferrara
| | - Marius Bill
- The Ohio State University, Comprehensive Cancer Center, Columbus
| | - Jessica Kohlschmidt
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; The Ohio State University Comprehensive Cancer Center, Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH; Alliance Statistics and Data Center, The Ohio State University, Comprehensive Cancer Center, Columbus
| | - Maciej Pietrzak
- The Ohio State University, Department of Biomedical Informatics, Columbus
| | - Christopher J Walker
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; The Ohio State University Comprehensive Cancer Center, Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus
| | - Andrew J Carroll
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg
| | - Bayard L Powell
- The Comprehensive Cancer Center of Wake Forest University, Winston-Salem, NC
| | - Ann-Kathrin Eisfeld
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; The Ohio State University Comprehensive Cancer Center, Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus
| | - Geoffrey L Uy
- Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO
| | | | - Jonathan E Kolitz
- Monter Cancer Center, Hofstra Northwell School of Medicine, Lake Success
| | - Richard M Stone
- Dana-Farber Cancer Institute, Harvard University, Boston, MA
| | - Wolfgang Hiddemann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany; German Cancer Research Center (DKFZ), Heidelberg
| | - John C Byrd
- The Ohio State University, Comprehensive Cancer Center, Columbus, OH; The Ohio State University Comprehensive Cancer Center, Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus
| | | | - Ramiro Garzon
- The Ohio State University, Comprehensive Cancer Center, Columbus.
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7
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Anande G, Deshpande NP, Mareschal S, Batcha AMN, Hampton HR, Herold T, Lehmann S, Wilkins MR, Wong JWH, Unnikrishnan A, Pimanda JE. RNA Splicing Alterations Induce a Cellular Stress Response Associated with Poor Prognosis in Acute Myeloid Leukemia. Clin Cancer Res 2020; 26:3597-3607. [PMID: 32122925 DOI: 10.1158/1078-0432.ccr-20-0184] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 02/13/2020] [Accepted: 02/26/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE RNA splicing is a fundamental biological process that generates protein diversity from a finite set of genes. Recurrent somatic mutations of splicing factor genes are common in some hematologic cancers but are relatively uncommon in acute myeloid leukemia (AML, < 20% of patients). We examined whether RNA splicing differences exist in AML, even in the absence of splicing factor mutations. EXPERIMENTAL DESIGN We developed a bioinformatics pipeline to study alternative RNA splicing in RNA-sequencing data from large cohorts of patients with AML. RESULTS We have identified recurrent differential alternative splicing between patients with poor and good prognosis. These splicing events occurred even in patients without any discernible splicing factor mutations. Alternative splicing recurrently occurred in genes with specific molecular functions, primarily related to protein translation. Developing tools to predict the functional impact of alternative splicing on the translated protein, we discovered that approximately 45% of the splicing events directly affected highly conserved protein domains. Several splicing factors were themselves misspliced and the splicing of their target transcripts were altered. Studying differential gene expression in the same patients, we identified that alternative splicing of protein translation genes in ELNAdv patients resulted in the induction of an integrated stress response and upregulation of inflammation-related genes. Finally, using machine learning techniques, we identified a splicing signature of four genes which refine the accuracy of existing risk prognosis schemes and validated it in a completely independent cohort. CONCLUSIONS Our discoveries therefore identify aberrant alternative splicing as a molecular feature of adverse AML with clinical relevance.See related commentary by Bowman, p. 3503.
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Affiliation(s)
- Govardhan Anande
- Adult Cancer Program, Lowy Cancer Research Centre & Prince of Wales Clinical School, University of New South Wales Sydney, New South Wales, Australia
| | - Nandan P Deshpande
- School of Biotechnology and Biomolecular Sciences, University of New South Wales Sydney, New South Wales, Australia
| | - Sylvain Mareschal
- Hematology Centre, Karolinska University Hospital and Department of Medicine, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Aarif M N Batcha
- Institute of Medical Data Processing, Biometrics and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.,Data Integration for Future Medicine, LMU Munich, Munich, Germany
| | - Henry R Hampton
- Adult Cancer Program, Lowy Cancer Research Centre & Prince of Wales Clinical School, University of New South Wales Sydney, New South Wales, Australia
| | - Tobias Herold
- Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Soren Lehmann
- Hematology Centre, Karolinska University Hospital and Department of Medicine, Karolinska Institutet, Huddinge, Stockholm, Sweden.,Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Marc R Wilkins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales Sydney, New South Wales, Australia
| | - Jason W H Wong
- Adult Cancer Program, Lowy Cancer Research Centre & Prince of Wales Clinical School, University of New South Wales Sydney, New South Wales, Australia.,School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Ashwin Unnikrishnan
- Adult Cancer Program, Lowy Cancer Research Centre & Prince of Wales Clinical School, University of New South Wales Sydney, New South Wales, Australia.
| | - John E Pimanda
- Adult Cancer Program, Lowy Cancer Research Centre & Prince of Wales Clinical School, University of New South Wales Sydney, New South Wales, Australia. .,Department of Pathology, School of Medical Sciences, University of New South Wales Sydney, New South Wales, Australia.,Department of Haematology, Prince of Wales Hospital, Sydney, New South Wales, Australia
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8
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Batcha AMN, Bamopoulos SA, Kerbs P, Kumar A, Jurinovic V, Rothenberg-Thurley M, Ksienzyk B, Philippou-Massier J, Krebs S, Blum H, Schneider S, Konstandin N, Bohlander SK, Heckman C, Kontro M, Hiddemann W, Spiekermann K, Braess J, Metzeler KH, Greif PA, Mansmann U, Herold T. Allelic Imbalance of Recurrently Mutated Genes in Acute Myeloid Leukaemia. Sci Rep 2019; 9:11796. [PMID: 31409822 PMCID: PMC6692371 DOI: 10.1038/s41598-019-48167-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 07/29/2019] [Indexed: 12/24/2022] Open
Abstract
The patho-mechanism of somatic driver mutations in cancer usually involves transcription, but the proportion of mutations and wild-type alleles transcribed from DNA to RNA is largely unknown. We systematically compared the variant allele frequencies of recurrently mutated genes in DNA and RNA sequencing data of 246 acute myeloid leukaemia (AML) patients. We observed that 95% of all detected variants were transcribed while the rest were not detectable in RNA sequencing with a minimum read-depth cut-off (10x). Our analysis focusing on 11 genes harbouring recurring mutations demonstrated allelic imbalance (AI) in most patients. GATA2, RUNX1, TET2, SRSF2, IDH2, PTPN11, WT1, NPM1 and CEBPA showed significant AIs. While the effect size was small in general, GATA2 exhibited the largest allelic imbalance. By pooling heterogeneous data from three independent AML cohorts with paired DNA and RNA sequencing (N = 253), we could validate the preferential transcription of GATA2-mutated alleles. Differential expression analysis of the genes with significant AI showed no significant differential gene and isoform expression for the mutated genes, between mutated and wild-type patients. In conclusion, our analyses identified AI in nine out of eleven recurrently mutated genes. AI might be a common phenomenon in AML which potentially contributes to leukaemogenesis.
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Affiliation(s)
- Aarif M N Batcha
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany. .,Data Integration for Future Medicine (DiFuture, www.difuture.de), LMU Munich, Munich, Germany.
| | - Stefanos A Bamopoulos
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Paul Kerbs
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Ashwini Kumar
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Vindi Jurinovic
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.,Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Maja Rothenberg-Thurley
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Bianka Ksienzyk
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Julia Philippou-Massier
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Munich, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, University of Munich, Munich, Germany
| | - Stephanie Schneider
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,Institute of Human Genetics, University Hospital, LMU Munich, Munich, Germany
| | - Nikola Konstandin
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Stefan K Bohlander
- Leukaemia and Blood Cancer Research Unit, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand
| | - Caroline Heckman
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Mika Kontro
- Department of Haematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
| | - Wolfgang Hiddemann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Karsten Spiekermann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany
| | - Klaus H Metzeler
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp A Greif
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ulrich Mansmann
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.,Data Integration for Future Medicine (DiFuture, www.difuture.de), LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tobias Herold
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany. .,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany. .,German Cancer Research Center (DKFZ), Heidelberg, Germany. .,Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), Munich, Germany.
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9
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Vaikari VP, Du Y, Wu S, Zhang T, Metzeler K, Batcha AMN, Herold T, Hiddemann W, Akhtari M, Alachkar H. Clinical and preclinical characterization of CD99 isoforms in acute myeloid leukemia. Haematologica 2019; 105:999-1012. [PMID: 31371417 PMCID: PMC7109747 DOI: 10.3324/haematol.2018.207001] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 07/25/2019] [Indexed: 12/19/2022] Open
Abstract
In an effort to identify target genes in acute myeloid leukemia (AML), we compared gene expression profiles between normal and AML cells from various publicly available datasets. We identified CD99, a gene that is up-regulated in AML patients. In 186 patients from The Cancer Genome Atlas AML dataset, CD99 was over-expressed in patients with FLT3-ITD and was down-regulated in patients with TP53 mutations. CD99 is a trans-membrane protein expressed on leukocytes and plays a role in cell adhesion, trans-endothelial migration, and T-cell differentiation. The CD99 gene encodes two isoforms with distinct expression and functional profiles in both normal and malignant tissues. Here we report that, although the CD99 long isoform initially induces an increase in cell proliferation, it also induces higher levels of reactive oxygen species, DNA damage, apoptosis and a subsequent decrease in cell viability. In several leukemia murine models, the CD99 long isoform delayed disease progression and resulted in lower leukemia engraftment in the bone marrow. Furthermore, the CD99 monoclonal antibody reduced cell viability, colony formation, and cell migration, and induced cell differentiation and apoptosis in leukemia cell lines and primary blasts. Mechanistically, CD99 long isoform resulted in transient induction followed by a dramatic decrease in both ERK and SRC phosphorylation. Altogether, our study provides new insights into the role of CD99 isoforms in AML that could potentially be relevant for the preclinical development of CD99 targeted therapy.
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Affiliation(s)
- Vijaya Pooja Vaikari
- Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Yang Du
- Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Sharon Wu
- Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Tian Zhang
- Medical Biology Program, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Klaus Metzeler
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Aarif M N Batcha
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany.,Data Integration for Future Medicine (DiFuture, www.difuture.de), LMU Munich, Germany
| | - Tobias Herold
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany.,Research Unit Apoptosis in Hematopoietic Stem Cells, Helmholtz Zentrum München, German Center for Environmental Health (HMGU), Munich Germany
| | - Wolfgang Hiddemann
- Laboratory for Leukemia Diagnostics, Department of Medicine III, University Hospital, LMU Munich, Munich, Germany
| | - Mojtaba Akhtari
- USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles Southern California, Los Angeles, CA, USA
| | - Houda Alachkar
- Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA .,USC Norris Comprehensive Cancer Center, University of Southern California, Los Angeles Southern California, Los Angeles, CA, USA
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10
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Herold T, Jurinovic V, Batcha AMN, Bamopoulos SA, Rothenberg-Thurley M, Ksienzyk B, Hartmann L, Greif PA, Phillippou-Massier J, Krebs S, Blum H, Amler S, Schneider S, Konstandin N, Sauerland MC, Görlich D, Berdel WE, Wörmann BJ, Tischer J, Subklewe M, Bohlander SK, Braess J, Hiddemann W, Metzeler KH, Mansmann U, Spiekermann K. A 29-gene and cytogenetic score for the prediction of resistance to induction treatment in acute myeloid leukemia. Haematologica 2017; 103:456-465. [PMID: 29242298 PMCID: PMC5830382 DOI: 10.3324/haematol.2017.178442] [Citation(s) in RCA: 72] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Accepted: 12/07/2017] [Indexed: 01/15/2023] Open
Abstract
Primary therapy resistance is a major problem in acute myeloid leukemia treatment. We set out to develop a powerful and robust predictor for therapy resistance for intensively treated adult patients. We used two large gene expression data sets (n=856) to develop a predictor of therapy resistance, which was validated in an independent cohort analyzed by RNA sequencing (n=250). In addition to gene expression markers, standard clinical and laboratory variables as well as the mutation status of 68 genes were considered during construction of the model. The final predictor (PS29MRC) consisted of 29 gene expression markers and a cytogenetic risk classification. A continuous predictor is calculated as a weighted linear sum of the individual variables. In addition, a cut off was defined to divide patients into a high-risk and a low-risk group for resistant disease. PS29MRC was highly significant in the validation set, both as a continuous score (OR=2.39, P=8.63·10−9, AUC=0.76) and as a dichotomous classifier (OR=8.03, P=4.29·10−9); accuracy was 77%. In multivariable models, only TP53 mutation, age and PS29MRC (continuous: OR=1.75, P=0.0011; dichotomous: OR=4.44, P=0.00021) were left as significant variables. PS29MRC dominated all models when compared with currently used predictors, and also predicted overall survival independently of established markers. When integrated into the European LeukemiaNet (ELN) 2017 genetic risk stratification, four groups (median survival of 8, 18, 41 months, and not reached) could be defined (P=4.01·10−10). PS29MRC will make it possible to design trials which stratify induction treatment according to the probability of response, and refines the ELN 2017 classification.
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Affiliation(s)
- Tobias Herold
- Department of Internal Medicine III, University of Munich, Germany .,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Vindi Jurinovic
- Institute for Medical Informatics, Biometry and Epidemiology, University of Munich, Germany
| | - Aarif M N Batcha
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute for Medical Informatics, Biometry and Epidemiology, University of Munich, Germany
| | | | | | - Bianka Ksienzyk
- Department of Internal Medicine III, University of Munich, Germany
| | - Luise Hartmann
- Department of Internal Medicine III, University of Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp A Greif
- Department of Internal Medicine III, University of Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Stefan Krebs
- Institute of Biostatistics and Clinical Research, University of Münster, Germany
| | - Helmut Blum
- Institute of Biostatistics and Clinical Research, University of Münster, Germany
| | - Susanne Amler
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | | | - Dennis Görlich
- Institute of Biostatistics and Clinical Research, University of Munich, Germany
| | - Wolfgang E Berdel
- Department of Medicine, Hematology and Oncology, University of Münster, Germany
| | | | - Johanna Tischer
- Department of Internal Medicine III, University of Munich, Germany
| | - Marion Subklewe
- Department of Internal Medicine III, University of Munich, Germany
| | - Stefan K Bohlander
- Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand
| | - Jan Braess
- Department of Oncology and Hematology, Hospital Barmherzige Brüder, Regensburg, Germany
| | - Wolfgang Hiddemann
- Department of Internal Medicine III, University of Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Klaus H Metzeler
- Department of Internal Medicine III, University of Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ulrich Mansmann
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute for Medical Informatics, Biometry and Epidemiology, University of Munich, Germany
| | - Karsten Spiekermann
- Department of Internal Medicine III, University of Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany.,German Cancer Research Center (DKFZ), Heidelberg, Germany
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