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Xydia M, Rahbari R, Ruggiero E, Macaulay I, Tarabichi M, Lohmayer R, Wilkening S, Michels T, Brown D, Vanuytven S, Mastitskaya S, Laidlaw S, Grabe N, Pritsch M, Fronza R, Hexel K, Schmitt S, Müller-Steinhardt M, Halama N, Domschke C, Schmidt M, von Kalle C, Schütz F, Voet T, Beckhove P. Common clonal origin of conventional T cells and induced regulatory T cells in breast cancer patients. Nat Commun 2021; 12:1119. [PMID: 33602930 PMCID: PMC7893042 DOI: 10.1038/s41467-021-21297-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 12/11/2020] [Indexed: 02/06/2023] Open
Abstract
Regulatory CD4+ T cells (Treg) prevent tumor clearance by conventional T cells (Tconv) comprising a major obstacle of cancer immune-surveillance. Hitherto, the mechanisms of Treg repertoire formation in human cancers remain largely unclear. Here, we analyze Treg clonal origin in breast cancer patients using T-Cell Receptor and single-cell transcriptome sequencing. While Treg in peripheral blood and breast tumors are clonally distinct, Tconv clones, including tumor-antigen reactive effectors (Teff), are detected in both compartments. Tumor-infiltrating CD4+ cells accumulate into distinct transcriptome clusters, including early activated Tconv, uncommitted Teff, Th1 Teff, suppressive Treg and pro-tumorigenic Treg. Trajectory analysis suggests early activated Tconv differentiation either into Th1 Teff or into suppressive and pro-tumorigenic Treg. Importantly, Tconv, activated Tconv and Treg share highly-expanded clones contributing up to 65% of intratumoral Treg. Here we show that Treg in human breast cancer may considerably stem from antigen-experienced Tconv converting into secondary induced Treg through intratumoral activation.
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Affiliation(s)
- Maria Xydia
- RCI Regensburg Centre for Interventional Immunology, University and Department of Hematology/Oncology, University Medical Centre of Regensburg, Regensburg, Germany.
- Translational Immunology Department, German Cancer Research Centre, Heidelberg, Germany.
| | - Raheleh Rahbari
- The Cancer, Ageing and Somatic Mutation Program, Wellcome Sanger Institute, Hinxton, UK
| | - Eliana Ruggiero
- Translational Oncology Department, National Centre for Tumor Diseases and German Cancer Research Centre, Heidelberg, Germany
| | - Iain Macaulay
- The Cancer, Ageing and Somatic Mutation Program, Wellcome Sanger Institute, Hinxton, UK
- Technical Development, Earlham Institute, Norwich, UK
| | - Maxime Tarabichi
- The Cancer, Ageing and Somatic Mutation Program, Wellcome Sanger Institute, Hinxton, UK
- The Francis Crick Institute, London, UK
| | - Robert Lohmayer
- RCI Regensburg Centre for Interventional Immunology, University and Department of Hematology/Oncology, University Medical Centre of Regensburg, Regensburg, Germany
- Institute for Theoretical Physics, University of Regensburg, Regensburg, Germany
| | - Stefan Wilkening
- Translational Oncology Department, National Centre for Tumor Diseases and German Cancer Research Centre, Heidelberg, Germany
| | - Tillmann Michels
- RCI Regensburg Centre for Interventional Immunology, University and Department of Hematology/Oncology, University Medical Centre of Regensburg, Regensburg, Germany
| | - Daniel Brown
- Department of Human Genetics, University of Leuven, KU Leuven, Leuven, Belgium
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | - Sebastiaan Vanuytven
- The Francis Crick Institute, London, UK
- Department of Human Genetics, University of Leuven, KU Leuven, Leuven, Belgium
| | - Svetlana Mastitskaya
- Medical Oncology Department, National Centre for Tumor Diseases, Heidelberg, Germany
- Centre for Cardiovascular and Metabolic Neuroscience, Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Sean Laidlaw
- The Cancer, Ageing and Somatic Mutation Program, Wellcome Sanger Institute, Hinxton, UK
| | - Niels Grabe
- Medical Oncology Department, National Centre for Tumor Diseases, Heidelberg, Germany
- Hamamatsu Tissue Imaging and Analysis Centre, BIOQUANT, University of Heidelberg, Heidelberg, Germany
| | - Maria Pritsch
- Translational Immunology Department, German Cancer Research Centre, Heidelberg, Germany
| | - Raffaele Fronza
- Translational Oncology Department, National Centre for Tumor Diseases and German Cancer Research Centre, Heidelberg, Germany
| | - Klaus Hexel
- Flow Cytometry Core Facility, German Cancer Research Centre, Heidelberg, Germany
| | - Steffen Schmitt
- Flow Cytometry Core Facility, German Cancer Research Centre, Heidelberg, Germany
| | - Michael Müller-Steinhardt
- German Red Cross (DRK Blood Donation Service in Baden-Württemberg-Hessen) and Institute for Transfusion Medicine and Immunology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Niels Halama
- Medical Oncology Department, National Centre for Tumor Diseases, Heidelberg, Germany
- Hamamatsu Tissue Imaging and Analysis Centre, BIOQUANT, University of Heidelberg, Heidelberg, Germany
| | - Christoph Domschke
- Department of Gynecology and Obstetrics, University Hospital of Heidelberg, Heidelberg, Germany
| | - Manfred Schmidt
- Translational Oncology Department, National Centre for Tumor Diseases and German Cancer Research Centre, Heidelberg, Germany
| | - Christof von Kalle
- Translational Oncology Department, National Centre for Tumor Diseases and German Cancer Research Centre, Heidelberg, Germany
- Clinical Study Centre, Charité/BIH, Berlin, Germany
| | - Florian Schütz
- Department of Gynecology and Obstetrics, University Hospital of Heidelberg, Heidelberg, Germany
| | - Thierry Voet
- The Cancer, Ageing and Somatic Mutation Program, Wellcome Sanger Institute, Hinxton, UK
- Department of Human Genetics, University of Leuven, KU Leuven, Leuven, Belgium
| | - Philipp Beckhove
- RCI Regensburg Centre for Interventional Immunology, University and Department of Hematology/Oncology, University Medical Centre of Regensburg, Regensburg, Germany.
- Translational Immunology Department, German Cancer Research Centre, Heidelberg, Germany.
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Wilkening S, Schmitt FJ, Lenz O, Zebger I, Horch M, Friedrich T. Discriminating changes in intracellular NADH/NAD + levels due to anoxicity and H 2 supply in R. eutropha cells using the Frex fluorescence sensor. Biochim Biophys Acta Bioenerg 2019; 1860:148062. [PMID: 31419395 DOI: 10.1016/j.bbabio.2019.148062] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 07/23/2019] [Accepted: 08/10/2019] [Indexed: 12/19/2022]
Abstract
The hydrogen-oxidizing "Knallgas" bacterium Ralstonia eutropha can thrive in aerobic and anaerobic environments and readily switches between heterotrophic and autotrophic metabolism, making it an attractive host for biotechnological applications including the sustainable H2-driven production of hydrocarbons. The soluble hydrogenase (SH), one out of four different [NiFe]-hydrogenases in R. eutropha, mediates H2 oxidation even in the presence of O2, thus providing an ideal model system for biological hydrogen production and utilization. The SH reversibly couples H2 oxidation with the reduction of NAD+ to NADH, thereby enabling the sustainable regeneration of this biotechnologically important nicotinamide cofactor. Thus, understanding the interaction of the SH with the cellular NADH/NAD+ pool is of high interest. Here, we applied the fluorescent biosensor Frex to measure changes in cytoplasmic [NADH] in R. eutropha cells under different gas supply conditions. The results show that Frex is well-suited to distinguish SH-mediated changes in the cytoplasmic redox status from effects of general anaerobiosis of the respiratory chain. Upon H2 supply, the Frex reporter reveals a robust fluorescence response and allows for monitoring rapid changes in cellular [NADH]. Compared to the Peredox fluorescence reporter, Frex displays a diminished NADH affinity, which prevents the saturation of the sensor under typical bacterial [NADH] levels. Thus, Frex is a valuable reporter for on-line monitoring of the [NADH]/[NAD+] redox state in living cells of R. eutropha and other proteobacteria. Based on these results, strategies for a rational optimization of fluorescent NADH sensors are discussed.
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Affiliation(s)
- S Wilkening
- Technische Universität Berlin, Institut für Chemie PC 14, Straße des 17. Juni 135, 10623 Berlin, Germany
| | - F-J Schmitt
- Technische Universität Berlin, Institut für Chemie PC 14, Straße des 17. Juni 135, 10623 Berlin, Germany
| | - O Lenz
- Technische Universität Berlin, Institut für Chemie PC 14, Straße des 17. Juni 135, 10623 Berlin, Germany
| | - I Zebger
- Technische Universität Berlin, Institut für Chemie PC 14, Straße des 17. Juni 135, 10623 Berlin, Germany
| | - M Horch
- Technische Universität Berlin, Institut für Chemie PC 14, Straße des 17. Juni 135, 10623 Berlin, Germany; Department of Chemistry and York Biomedical Research Institute, University of York, YO10 5DD, United Kingdom
| | - T Friedrich
- Technische Universität Berlin, Institut für Chemie PC 14, Straße des 17. Juni 135, 10623 Berlin, Germany.
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Afzal S, Wilkening S, von Kalle C, Schmidt M, Fronza R. GENE-IS: Time-Efficient and Accurate Analysis of Viral Integration Events in Large-Scale Gene Therapy Data. Mol Ther Nucleic Acids 2016; 6:133-139. [PMID: 28325279 PMCID: PMC5363413 DOI: 10.1016/j.omtn.2016.12.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 11/24/2016] [Accepted: 12/01/2016] [Indexed: 12/22/2022]
Abstract
Integration site profiling and clonality analysis of viral vector distribution in gene therapy is a key factor to monitor the fate of gene-corrected cells, assess the risk of malignant transformation, and establish vector biosafety. We developed the Genome Integration Site Analysis Pipeline (GENE-IS) for highly time-efficient and accurate detection of next-generation sequencing (NGS)-based viral vector integration sites (ISs) in gene therapy data. It is the first available tool with dual analysis mode that allows IS analysis both in data generated by PCR-based methods, such as linear amplification method PCR (LAM-PCR), and by rapidly evolving targeted sequencing (e.g., Agilent SureSelect) technologies. GENE-IS makes use of trimming strategies, customized reference genome, and soft-clipped information with sequential filtering steps to provide annotated IS with clonality information. It is a scalable, robust, precise, and reliable tool for large-scale pre-clinical and clinical data analysis that provides users complete flexibility and control over analysis with a broad range of configurable parameters. GENE-IS is available at https://github.com/G100DKFZ/gene-is.
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Affiliation(s)
- Saira Afzal
- Department of Translational Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Stefan Wilkening
- Department of Translational Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Christof von Kalle
- Department of Translational Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Manfred Schmidt
- Department of Translational Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Raffaele Fronza
- Department of Translational Oncology, National Center for Tumor Diseases (NCT) and German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
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Wilkening S, Afzal S, Senís E, Fronza R, von Kalle C, Grimm D, Schmidt M. 470. New Insights into rAAV Integration Mechanisms by Targeted Enrichment Sequencing. Mol Ther 2016. [DOI: 10.1016/s1525-0016(16)33279-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Gil-Farina I, Käppel C, Wilkening S, Lopez-Franco E, Astrid Paneda M, Prieto J, Spronck L, von Kalle C, Petry H, Gonzalez-Aseguinolaza G, Schmidt M. 664. Improving AAV Gene Therapy Safety Analysis: Multiplex LAM-PCR Provide New Insights Into AAV Vector Integration. Mol Ther 2015. [DOI: 10.1016/s1525-0016(16)34273-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Afzal S, Fronza R, Wilkening S, Bartholomä C, von Kalle C, Schmidt M. 339. GENIS: A Bioinformatics Tool for Reliable and Automated Genome Insertion Site Analysis. Mol Ther 2015. [DOI: 10.1016/s1525-0016(16)33948-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Senís E, Mosteiro L, Wilkening S, Schmidt M, Serrano M, Grimm D. 300. AAV Vector-Mediated In Vivo Reprogramming of Various Cell Types in Adult Mice. Mol Ther 2015. [DOI: 10.1016/s1525-0016(16)33909-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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8
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Wilkening S, Afzal S, Fronza R, von Kalle C, Schmidt M. 127. Detection of Vector Integration Sites by Targeted Sequencing. Mol Ther 2015. [DOI: 10.1016/s1525-0016(16)33732-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Abstract
Mechanisms conferring robustness against regulatory variants have been controversial. Previous studies suggested widespread buffering of RNA misexpression on protein levels during translation. We do not find evidence that translational buffering is common. Instead, we find extensive buffering at the level of RNA expression, exerted through negative feedback regulation acting in trans, which reduces the effect of regulatory variants on gene expression. Our approach is based on a novel experimental design in which allelic differential expression in a yeast hybrid strain is compared to allelic differential expression in a pool of its spores. Allelic differential expression in the hybrid is due to cis-regulatory differences only. Instead, in the pool of spores allelic differential expression is not only due to cis-regulatory differences but also due to local trans effects that include negative feedback. We found that buffering through such local trans regulation is widespread, typically compensating for about 15% of cis-regulatory effects on individual genes. Negative feedback is stronger not only for essential genes, indicating its functional relevance, but also for genes with low to middle levels of expression, for which tight regulation matters most. We suggest that negative feedback is one mechanism of Waddington's canalization, facilitating the accumulation of genetic variants that might give selective advantage in different environments.
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Affiliation(s)
- Daniel M Bader
- Computational Genomics, Gene Center, Ludwig Maximilians University, Munich, Germany
| | - Stefan Wilkening
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Gen Lin
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Manu M Tekkedil
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
| | - Kim Dietrich
- Computational Genomics, Gene Center, Ludwig Maximilians University, Munich, Germany
| | - Lars M Steinmetz
- European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany Stanford Genome Technology Center, Palo Alto, CA, USA Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Julien Gagneur
- Computational Genomics, Gene Center, Ludwig Maximilians University, Munich, Germany
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10
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Peterlongo P, Chang-Claude J, Moysich KB, Rudolph A, Schmutzler RK, Simard J, Soucy P, Eeles RA, Easton DF, Hamann U, Wilkening S, Chen B, Rookus MA, Schmidt MK, van der Baan FH, Spurdle AB, Walker LC, Lose F, Maia AT, Montagna M, Matricardi L, Lubinski J, Jakubowska A, Gómez Garcia EB, Olopade OI, Nussbaum RL, Nathanson KL, Domchek SM, Rebbeck TR, Arun BK, Karlan BY, Orsulic S, Lester J, Chung WK, Miron A, Southey MC, Goldgar DE, Buys SS, Janavicius R, Dorfling CM, van Rensburg EJ, Ding YC, Neuhausen SL, Hansen TVO, Gerdes AM, Ejlertsen B, Jønson L, Osorio A, Martínez-Bouzas C, Benitez J, Conway EE, Blazer KR, Weitzel JN, Manoukian S, Peissel B, Zaffaroni D, Scuvera G, Barile M, Ficarazzi F, Mariette F, Fortuzzi S, Viel A, Giannini G, Papi L, Martayan A, Tibiletti MG, Radice P, Vratimos A, Fostira F, Garber JE, Donaldson A, Brewer C, Foo C, Evans DGR, Frost D, Eccles D, Brady A, Cook J, Tischkowitz M, Adlard J, Barwell J, Walker L, Izatt L, Side LE, Kennedy MJ, Rogers MT, Porteous ME, Morrison PJ, Platte R, Davidson R, Hodgson SV, Ellis S, Cole T, Godwin AK, Claes K, Van Maerken T, Meindl A, Gehrig A, Sutter C, Engel C, Niederacher D, Steinemann D, Plendl H, Kast K, Rhiem K, Ditsch N, Arnold N, Varon-Mateeva R, Wappenschmidt B, Wang-Gohrke S, Bressac-de Paillerets B, Buecher B, Delnatte C, Houdayer C, Stoppa-Lyonnet D, Damiola F, Coupier I, Barjhoux L, Venat-Bouvet L, Golmard L, Boutry-Kryza N, Sinilnikova OM, Caron O, Pujol P, Mazoyer S, Belotti M, Piedmonte M, Friedlander ML, Rodriguez GC, Copeland LJ, de la Hoya M, Segura PP, Nevanlinna H, Aittomäki K, van Os TAM, Meijers-Heijboer HEJ, van der Hout AH, Vreeswijk MPG, Hoogerbrugge N, Ausems MGEM, van Doorn HC, Collée JM, Olah E, Diez O, Blanco I, Lazaro C, Brunet J, Feliubadalo L, Cybulski C, Gronwald J, Durda K, Jaworska-Bieniek K, Sukiennicki G, Arason A, Chiquette J, Teixeira MR, Olswold C, Couch FJ, Lindor NM, Wang X, Szabo CI, Offit K, Corines M, Jacobs L, Robson ME, Zhang L, Joseph V, Berger A, Singer CF, Rappaport C, Kaulich DG, Pfeiler G, Tea MKM, Phelan CM, Greene MH, Mai PL, Rennert G, Mulligan AM, Glendon G, Tchatchou S, Andrulis IL, Toland AE, Bojesen A, Pedersen IS, Thomassen M, Jensen UB, Laitman Y, Rantala J, von Wachenfeldt A, Ehrencrona H, Askmalm MS, Borg Å, Kuchenbaecker KB, McGuffog L, Barrowdale D, Healey S, Lee A, Pharoah PDP, Chenevix-Trench G, Antoniou AC, Friedman E. Candidate genetic modifiers for breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev 2015; 24:308-16. [PMID: 25336561 PMCID: PMC4294951 DOI: 10.1158/1055-9965.epi-14-0532] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND BRCA1 and BRCA2 mutation carriers are at substantially increased risk for developing breast and ovarian cancer. The incomplete penetrance coupled with the variable age at diagnosis in carriers of the same mutation suggests the existence of genetic and nongenetic modifying factors. In this study, we evaluated the putative role of variants in many candidate modifier genes. METHODS Genotyping data from 15,252 BRCA1 and 8,211 BRCA2 mutation carriers, for known variants (n = 3,248) located within or around 445 candidate genes, were available through the iCOGS custom-designed array. Breast and ovarian cancer association analysis was performed within a retrospective cohort approach. RESULTS The observed P values of association ranged between 0.005 and 1.000. None of the variants was significantly associated with breast or ovarian cancer risk in either BRCA1 or BRCA2 mutation carriers, after multiple testing adjustments. CONCLUSION There is little evidence that any of the evaluated candidate variants act as modifiers of breast and/or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers. IMPACT Genome-wide association studies have been more successful at identifying genetic modifiers of BRCA1/2 penetrance than candidate gene studies.
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Affiliation(s)
- Paolo Peterlongo
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy. Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy.
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Kirsten B Moysich
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, New York
| | - Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rita K Schmutzler
- Center for Hereditary Breast and Ovarian Cancer, Medical Faculty, University Hospital Cologne, Germany. Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Germany. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Germany, on behalf of the German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC)
| | - Jacques Simard
- Centre Hospitalier Universitaire de Québec Research Center and Laval University, Quebec City, Canada
| | - Penny Soucy
- Centre Hospitalier Universitaire de Québec Research Center and Laval University, Quebec City, Canada
| | - Rosalind A Eeles
- Oncogenetics Team, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Surrey, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefan Wilkening
- Genomic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bowang Chen
- Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matti A Rookus
- Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Marjanka K Schmidt
- Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | | | - Amanda B Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer, Brisbane, Australia
| | - Logan C Walker
- Department of Pathology, University of Otago, Christchurch, New Zealand
| | - Felicity Lose
- Department of Genetics and Computational Biology, QIMR Berghofer, Brisbane, Australia
| | - Ana-Teresa Maia
- Department of Biomedical Sciences and Medicine, Gambelas Campus, University of Algarve, Portugal
| | - Marco Montagna
- Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto IOV - IRCCS, Padua, Italy
| | - Laura Matricardi
- Immunology and Molecular Oncology Unit, Istituto Oncologico Veneto IOV - IRCCS, Padua, Italy
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | | | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics, Department of Medicine and Human Genetics, University of Chicago Medical Center, Chicago, Illinois
| | - Robert L Nussbaum
- Department of Medicine and Institute for Human Genetics, University of California, San Francisco, San Francisco, California
| | - Katherine L Nathanson
- Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadephia, Pennsylvania
| | - Susan M Domchek
- Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadephia, Pennsylvania
| | - Timothy R Rebbeck
- Department of Epidemiology and Biostatistics, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadephia, Pennsylvania
| | - Banu K Arun
- University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Beth Y Karlan
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Sandra Orsulic
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jenny Lester
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, New York
| | - Alex Miron
- Department of Genetics and Genomics at Case Western Reserve Medical School, Cleveland, Ohio
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, Australia
| | - David E Goldgar
- Department of Dermatology, University of Utah School of Medicine, Salt Lake City, Utah
| | - Saundra S Buys
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
| | - Ramunas Janavicius
- Vilnius University Hospital Santariskiu Clinics, Hematology, Oncology, and Transfusion Medicine Center, Dept. of Molecular and Regenerative Medicine; State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
| | | | | | - Yuan Chun Ding
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Thomas V O Hansen
- Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Anne-Marie Gerdes
- Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Bent Ejlertsen
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Lars Jønson
- Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Ana Osorio
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain. Human Genetics Group, Spanish National Cancer Centre (CNIO), Madrid, Spain
| | - Cristina Martínez-Bouzas
- Molecular Genetics Laboratory, Department of Biochemistry, Cruces Hospital Barakaldo, 48903-Barakaldo-Bizkaia, Spain
| | - Javier Benitez
- Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain. Human Genetics Group and Genotyping Unit, Spanish National Cancer Centre (CNIO), Madrid, Spain
| | - Edye E Conway
- Saint Alphonsus Regional Medical Center, care of City of Hope Clinical Cancer Genetics Community Research Network, Duarte, California
| | | | - Jeffrey N Weitzel
- Clinical Cancer Genetics, City of Hope, Duarte, California (for the City of Hope Clinical Cancer Genetics Community Research Network)
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
| | - Bernard Peissel
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
| | - Daniela Zaffaroni
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
| | - Giulietta Scuvera
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
| | - Monica Barile
- Division of Cancer Prevention and Genetics, Istituto Europeo di Oncologia, Milan, Italy
| | - Filomena Ficarazzi
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy. Cogentech Cancer Genetic Test Laboratory, Milan, Italy
| | - Frederique Mariette
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy. Cogentech Cancer Genetic Test Laboratory, Milan, Italy
| | - Stefano Fortuzzi
- IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy. Cogentech Cancer Genetic Test Laboratory, Milan, Italy
| | - Alessandra Viel
- Division of Experimental Oncology 1, CRO Aviano National Cancer Institute, Aviano (PN), Italy
| | | | - Laura Papi
- Unit of Medical Genetics, Department of Biomedical, Experimental, and Clinical Sciences, University of Florence, Florence, Italy
| | - Aline Martayan
- Unit of Genetic Counseling, Medical Oncology Department, Istituto Nazionale Tumori Regina Elena, Rome, Italy
| | - Maria Grazia Tibiletti
- UO Anatomia Patologica Ospedale di Circolo e Fondazione Macchi, Polo Universitario Varese, Italy
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy
| | - Athanassios Vratimos
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research "Demokritos", Aghia Paraskevi Attikis, Athens, Greece
| | - Florentia Fostira
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research "Demokritos", Aghia Paraskevi Attikis, Athens, Greece
| | | | - Alan Donaldson
- Clinical Genetics Department, St. Michael's Hospital, Bristol, United Kingdom
| | - Carole Brewer
- Department of Clinical Genetics, Royal Devon & Exeter Hospital, Exeter, United Kingdom
| | - Claire Foo
- Cheshire & Merseyside Clinical Genetics Service, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom
| | - D Gareth R Evans
- Genetic Medicine, Manchester Academic Health Sciences Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
| | - Debra Frost
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Diana Eccles
- University of Southampton, Faculty of Medicine, Southampton University Hospitals NHS Trust, Southampton, United Kingdom
| | - Angela Brady
- North West Thames Regional Genetics Service, Kennedy-Galton Centre, Harrow, United Kingdom
| | - Jackie Cook
- Sheffield Clinical Genetics Service, Sheffield Children's Hospital, Sheffield, United Kingdom
| | - Marc Tischkowitz
- Department of Clinical Genetics, East Anglian Regional Genetics Service, Addenbrookes Hospital, Cambridge, United Kingdom
| | - Julian Adlard
- Yorkshire Regional Genetics Service, Leeds, United Kingdom
| | - Julian Barwell
- Leicestershire Clinical Genetics Service, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom
| | - Lisa Walker
- Oxford Regional Genetics Service, Churchill Hospital, Oxford, United Kingdom
| | - Louise Izatt
- Clinical Genetics, Guy's and St. Thomas' NHS Foundation Trust, London, United Kingdom
| | - Lucy E Side
- North East Thames Regional Genetics Service, Great Ormond Street Hospital for Children NHS Trust, London, United Kingdom
| | - M John Kennedy
- Academic Unit of Clinical and Molecular Oncology, Trinity College Dublin, Ireland. St. James's Hospital, Dublin, Ireland
| | - Mark T Rogers
- All Wales Medical Genetics Services, University Hospital of Wales, Cardiff, United Kingdom
| | - Mary E Porteous
- South East of Scotland Regional Genetics Service, Western General Hospital, Edinburgh, United Kingdom
| | - Patrick J Morrison
- Centre for Cancer Research and Cell Biology, Queens University of Belfast, Department of Medical Genetics, Belfast HSC Trust, Belfast, United Kingdom
| | - Radka Platte
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Rosemarie Davidson
- West of Scotland Regional Genetics Service, Southern General Hospital, Glasgow, United Kingdom
| | - Shirley V Hodgson
- Medical Genetics Unit, St. George's, University of London, London, United Kingdom
| | - Steve Ellis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Trevor Cole
- West Midlands Regional Genetics Service, Birmingham Women's Hospital Healthcare NHS Trust, Edgbaston, Birmingham, United Kingdom
| | - Andrew K Godwin
- Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, Missouri
| | - Kathleen Claes
- Center for Medical Genetics, Ghent University, Ghent, Belgium
| | - Tom Van Maerken
- Center for Medical Genetics, Ghent University, Ghent, Belgium
| | - Alfons Meindl
- Department of Gynaecology and Obstetrics, Division of Tumor Genetics, Klinikum rechts der Isar, Technical University Munich, Germany
| | - Andrea Gehrig
- Institute of Human Genetics, University Würzburg, Wurzburg, Germany
| | | | - Christoph Engel
- Institute for Medical Informatics, Statistics, and Epidemiology, University of Leipzig, Leipzig, Germany
| | | | | | - Hansjoerg Plendl
- Institute of Human Genetics, University Hospital of Schleswig-Holstein/University Kiel, Kiel, Germany
| | - Karin Kast
- Department of Gynecology and Obstetrics, University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany
| | - Kerstin Rhiem
- Center for Hereditary Breast and Ovarian Cancer, Medical Faculty, University Hospital Cologne, Germany. Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Germany. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Germany
| | - Nina Ditsch
- Department of Gynaecology and Obstetrics, University Munich, Munich, Germany
| | - Norbert Arnold
- Department of Gynecology and Obstetrics, University Hospital of Schleswig-Holstein/University Kiel, Kiel, Germany
| | | | - Barbara Wappenschmidt
- Center for Hereditary Breast and Ovarian Cancer, Medical Faculty, University Hospital Cologne, Germany. Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Germany. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Germany
| | - Shan Wang-Gohrke
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Germany
| | - Brigitte Bressac-de Paillerets
- INSERM U946, Fondation Jean Dausset, Paris, France. Service de Génétique, Institut de Cancérologie Gustave Roussy, Villejuif, France
| | - Bruno Buecher
- Institut Curie, Department of Tumour Biology, Paris, France
| | | | - Claude Houdayer
- Institut Curie, Department of Tumour Biology, Paris, France. Université Paris Descartes, Sorbonne Paris Cité, France
| | - Dominique Stoppa-Lyonnet
- Institut Curie, Department of Tumour Biology, Paris, France. Université Paris Descartes, Sorbonne Paris Cité, France. Institut Curie, INSERM U830, Paris, France
| | - Francesca Damiola
- INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en Cancérologie de Lyon, Lyon, France
| | - Isabelle Coupier
- Unité d'Oncogénétique, CHU Arnaud de Villeneuve, Montpellier, France. Unité d'Oncogénétique, CRLCC Val d'Aurelle, Montpellier, France
| | - Laure Barjhoux
- Unité d'Oncogénétique, CRLCC Val d'Aurelle, Montpellier, France
| | - Laurence Venat-Bouvet
- Department of Medical Oncology, Centre Hospitalier Universitaire Dupuytren, Limoges, France
| | - Lisa Golmard
- Institut Curie, Department of Tumour Biology, Paris, France
| | - Nadia Boutry-Kryza
- Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon - Centre Léon Bérard, Lyon, France
| | - Olga M Sinilnikova
- INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en Cancérologie de Lyon, Lyon, France. Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils de Lyon - Centre Léon Bérard, Lyon, France. IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy
| | - Olivier Caron
- Consultation de Génétique, Département de Médecine, Institut de Cancérologie Gustave Roussy, Villejuif, France
| | - Pascal Pujol
- Unité d'Oncogénétique, CHU Arnaud de Villeneuve, Montpellier, France. INSERM 896, CRCM Val d'Aurelle, Montpellier, France
| | - Sylvie Mazoyer
- INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en Cancérologie de Lyon, Lyon, France
| | - Muriel Belotti
- Institut Curie, Department of Tumour Biology, Paris, France
| | - Marion Piedmonte
- Gynecologic Oncology Group Statistical and Data Center, Roswell Park Cancer Institute, Buffalo, New York
| | - Michael L Friedlander
- Australia New Zealand Gynaecological Oncology Group (ANZGOG), Coordinating Centre, Camperdown, Australia
| | - Gustavo C Rodriguez
- Division of Gynecologic Oncology, NorthShore University HealthSystem, Evanston, Illinois
| | - Larry J Copeland
- Ohio State University, Department of Obstetrics and Gynecology, Hilliard, Ohio
| | - Miguel de la Hoya
- Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, Madrid, Spain
| | - Pedro Perez Segura
- Department of Oncology, Hospital Clinico San Carlos, IdISSC, Madrid, Spain
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Central Hospital, Helsinki, Finland. University of Helsinki, Helsinki, Finland
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Central Hospital, Helsinki, Finland
| | - Theo A M van Os
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, the Netherlands
| | | | - Annemarie H van der Hout
- Department of Genetics, University Medical Center, Groningen University, Groningen, the Netherlands
| | - Maaike P G Vreeswijk
- Department of Human Genetics, Leiden University Medical Center (LUMC), Leiden, the Netherlands
| | - Nicoline Hoogerbrugge
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Margreet G E M Ausems
- Department of Medical Genetics, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Helena C van Doorn
- Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Erasmus University MC Cancer Institute, Rotterdam, the Netherlands
| | - J Margriet Collée
- Department of Clinical Genetics, Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Edith Olah
- Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary
| | - Orland Diez
- Oncogenetics Group, University Hospital Vall d'Hebron, Barcelona, Spain. Universitat Autònoma de Barcelona, Barcelona, Spain. Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain. Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
| | - Ignacio Blanco
- Genetic Counseling Unit, Hereditary Cancer Program, IDIBELL-Catalan Institute of Oncology, Barcelona, Spain
| | - Conxi Lazaro
- Molecular Diagnostic Unit, Hereditary Cancer Program, IDIBELL-Catalan Institute of Oncology, Barcelona, Spain
| | - Joan Brunet
- Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI-Catalan Institute of Oncology, Girona, Spain
| | | | - Cezary Cybulski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jacek Gronwald
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Katarzyna Durda
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | | | - Grzegorz Sukiennicki
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Adalgeir Arason
- BMC, Faculty of Medicine, University of Iceland, Reykjavik, Iceland. Department of Pathology, Landspitali University Hospital, Reykjavik, Iceland
| | - Jocelyne Chiquette
- Unité de Recherche en Santé des Populations, Centre des Maladies du Sein Deschênes-Fabia, Centre de Recherche FRSQ du Centre Hospitalier Affilié Universitaire de Québec, Québec, Canada
| | - Manuel R Teixeira
- Biomedical Sciences Institute (ICBAS), Porto University, Porto, Portugal. Department of Genetics, Portuguese Oncology Institute, Porto, Portugal
| | - Curtis Olswold
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnessotta
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, and Health Sciences Research, Mayo Clinic, Rochester, Minnessotta
| | | | - Xianshu Wang
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnessotta
| | - Csilla I Szabo
- National Human Genome Research Institute, NIH, Bethesda, Maryland
| | - Kenneth Offit
- Clinical Genetics Research Laboratory, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Marina Corines
- Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Lauren Jacobs
- Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Mark E Robson
- Clinical Genetics Research Laboratory, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Liying Zhang
- Diagnostic Molecular Genetics Laboratory, Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Vijai Joseph
- Clinical Genetics Research Laboratory, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Andreas Berger
- Department of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Christian F Singer
- Department of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Christine Rappaport
- Department of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | | | - Georg Pfeiler
- Department of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Muy-Kheng M Tea
- Department of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Catherine M Phelan
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, Florida
| | - Mark H Greene
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, Maryland
| | - Phuong L Mai
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Rockville, Maryland
| | - Gad Rennert
- Clalit National Cancer Control Center, Haifa, Israel
| | - Anna Marie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada. Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada
| | - Gord Glendon
- Ontario Cancer Genetics Network: Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Sandrine Tchatchou
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. Departments of Molecular Genetics and Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada
| | - Amanda Ewart Toland
- Division of Human Cancer Genetics, Departments of Internal Medicine and Molecular Virology, Immunology, and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Anders Bojesen
- Department of Clinical Genetics, Vejle Hospital, Vejle, Denmark
| | - Inge Sokilde Pedersen
- Section of Molecular Diagnostics, Department of Biochemistry, Aalborg University Hospital, Aalborg, Denmark
| | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark
| | - Uffe Birk Jensen
- Department of Clinical Genetics, Aarhus University Hospital, Aarhus, Denmark
| | | | - Johanna Rantala
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Hans Ehrencrona
- Department of Clinical Genetics, Lund University Hospital, Lund, Sweden. Department of Immunology, Genetics, and Pathology, Uppsala University, Uppsala, Sweden
| | - Marie Stenmark Askmalm
- Division of Clinical Genetics, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Åke Borg
- Department of Oncology, Lund University, Lund, Sweden
| | - Karoline B Kuchenbaecker
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Lesley McGuffog
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Daniel Barrowdale
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Sue Healey
- Department of Genetics and Computational Biology, QIMR Berghofer, Brisbane, Australia
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Paul D P Pharoah
- Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | | | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Gupta I, Clauder-Münster S, Klaus B, Järvelin AI, Aiyar RS, Benes V, Wilkening S, Huber W, Pelechano V, Steinmetz LM. Alternative polyadenylation diversifies post-transcriptional regulation by selective RNA-protein interactions. Mol Syst Biol 2014; 10:719. [PMID: 24569168 PMCID: PMC4023391 DOI: 10.1002/msb.135068] [Citation(s) in RCA: 75] [Impact Index Per Article: 7.5] [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] [Indexed: 12/25/2022] Open
Abstract
Recent research has uncovered extensive variability in the boundaries of transcript isoforms, yet the functional consequences of this variation remain largely unexplored. Here, we systematically discriminate between the molecular phenotypes of overlapping coding and non‐coding transcriptional events from each genic locus using a novel genome‐wide, nucleotide‐resolution technique to quantify the half‐lives of 3′ transcript isoforms in yeast. Our results reveal widespread differences in stability among isoforms for hundreds of genes in a single condition, and that variation of even a single nucleotide in the 3′ untranslated region (UTR) can affect transcript stability. While previous instances of negative associations between 3′ UTR length and transcript stability have been reported, here, we find that shorter isoforms are not necessarily more stable. We demonstrate the role of RNA‐protein interactions in conditioning isoform‐specific stability, showing that PUF3 binds and destabilizes specific polyadenylation isoforms. Our findings indicate that although the functional elements of a gene are encoded in DNA sequence, the selective incorporation of these elements into RNA through transcript boundary variation allows a single gene to have diverse functional consequences.
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Affiliation(s)
- Ishaan Gupta
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
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12
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Schlüter N, Kassens A, Stinshoff H, Knauer K, Wilkening S, Wrenzycki C. 114 PROGESTERONE CONCENTRATIONS DURING IVM AFFECT BOVINE OOCYTE QUALITY AT THE MOLECULAR LEVEL. Reprod Fertil Dev 2014. [DOI: 10.1071/rdv26n1ab114] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Progesterone (P4) is important for the developmental competence of cumulus–oocyte complexes (COC) used for in vitro maturation (IVM). In a recent study, we were able to show that circulating P4 concentrations had an effect on the molecular quality of COC recovered during repeated ovum pickup sessions, which might affect further development. (Schlüter et al. 2013 Reprod. Fertil. Dev. 25, 250). The aim of the present study was to determine the influence of different P4 concentrations during IVM on the molecular quality of bovine COC. The COC were collected from slaughterhouse ovaries and cultured as described recently (Stinshoff et al. 2011 Theriogenology 76, 1433–1441). The IVM medium was supplemented with 0, 50, 150, 300, and 450 ng mL–1 P4. Ethanol served as vehicle control. After IVF with a bull of proven fertility, the presumptive zygotes were cultured in SOF under 5% oxygen (Stinshoff et al. 2011). Cleavage and developmental rates were determined at Day 3 and Day 7/8 (Day 0: IVF). Additionally, maturation rates were assessed. For mRNA analysis, immature and matured denuded COC (n = 5) were individually frozen at –80°C to analyse the relative transcript abundance using RT-qPCR. The transcripts studied play important roles during oocyte development [growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15), glucose transporter 1 (SCL2A1), hypoxia inducible factor 2α (HIF2α), nuclear progesterone receptor (PGR), progestin and adipoQ receptor 5 (PAQR5), progesterone receptor membrane component 1 and 2 (PGRMC1, PGRMC2)]. Data were tested using ANOVA followed by multiple pairwise comparisons using Tukey's test. A P-value of <0.05 was considered significant. The percentage of oocytes that reached the MII stage was similar in oocytes from all treatment groups (82.2–88.1%). Despite similar cleavage rates across all groups, the developmental rates did show significant differences. More embryos developed to the blastocyst stage stemming from oocytes cultured without any supplement or cultured only with alcohol compared to oocytes stemming from the group cultured with less than 50 ng mL–1 P4 (25.4 ± 5.7 and 27.9 ± 7.2 v. 15.8 ± 2.6). The relative abundance of SCL2A1, BMP15, and PGRMC1transcripts in single oocytes did not show differences related to the supplementation of the IVM medium, whereas GDF9, HIF2α, and PAQR5 mRNA was reduced in oocytes of all groups compared with immature ones. The PGR and PGRMC2 transcripts were increased in matured oocytes of the control group and the vehicle control group (PGRMC2). In summary, supplementation of the IVM medium with different P4 concentrations had an effect on the molecular quality of oocytes after IVM, which might affect further development.
The financial support of the FBF (Förderverein Biotechnologieforschung) e.V. is gratefully acknowledged.
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13
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Wilkening S, Tekkedil MM, Lin G, Fritsch ES, Wei W, Gagneur J, Lazinski DW, Camilli A, Steinmetz LM. Genotyping 1000 yeast strains by next-generation sequencing. BMC Genomics 2013; 14:90. [PMID: 23394869 PMCID: PMC3575377 DOI: 10.1186/1471-2164-14-90] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [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: 12/07/2012] [Accepted: 02/06/2013] [Indexed: 11/17/2022] Open
Abstract
Background The throughput of next-generation sequencing machines has increased dramatically over the last few years; yet the cost and time for library preparation have not changed proportionally, thus representing the main bottleneck for sequencing large numbers of samples. Here we present an economical, high-throughput library preparation method for the Illumina platform, comprising a 96-well based method for DNA isolation for yeast cells, a low-cost DNA shearing alternative, and adapter ligation using heat inactivation of enzymes instead of bead cleanups. Results Up to 384 whole-genome libraries can be prepared from yeast cells in one week using this method, for less than 15 euros per sample. We demonstrate the robustness of this protocol by sequencing over 1000 yeast genomes at ~30x coverage. The sequence information from 768 yeast segregants derived from two divergent S. cerevisiae strains was used to generate a meiotic recombination map at unprecedented resolution. Comparisons to other datasets indicate a high conservation of recombination at a chromosome-wide scale, but differences at the local scale. Additionally, we detected a high degree of aneuploidy (3.6%) by examining the sequencing coverage in these segregants. Differences in allele frequency allowed us to attribute instances of aneuploidy to gains of chromosomes during meiosis or mitosis, both of which showed a strong tendency to missegregate specific chromosomes. Conclusions Here we present a high throughput workflow to sequence genomes of large number of yeast strains at a low price. We have used this workflow to obtain recombination and aneuploidy data from hundreds of segregants, which can serve as a foundation for future studies of linkage, recombination, and chromosomal aberrations in yeast and higher eukaryotes.
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Affiliation(s)
- Stefan Wilkening
- Genome Biology Unit, European Molecular Biology Laboratory, Meyerhofstr. 1, 69117, Heidelberg, Germany
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14
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Beuing K, Stinshoff H, Wilkening S, Wrenzycki C. DMSO affects the success of bovine IVP embryo vitrification. Reprod Biol 2013. [DOI: 10.1016/j.repbio.2013.01.109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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15
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Poppicht F, Burmester N, Stinshoff H, Hanstedt A, Wilkening S, Wrenzycki C. Low oxygen concentration affects mRNA expression in bovine oocytes during IVM. Reprod Biol 2013. [DOI: 10.1016/j.repbio.2013.01.121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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16
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Wilkening S, Pelechano V, Järvelin AI, Tekkedil MM, Anders S, Benes V, Steinmetz LM. An efficient method for genome-wide polyadenylation site mapping and RNA quantification. Nucleic Acids Res 2013; 41:e65. [PMID: 23295673 PMCID: PMC3597643 DOI: 10.1093/nar/gks1249] [Citation(s) in RCA: 85] [Impact Index Per Article: 7.7] [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] [Indexed: 12/16/2022] Open
Abstract
The use of alternative poly(A) sites is common and affects the post-transcriptional fate of mRNA, including its stability, subcellular localization and translation. Here, we present a method to identify poly(A) sites in a genome-wide and strand-specific manner. This method, termed 3′T-fill, initially fills in the poly(A) stretch with unlabeled dTTPs, allowing sequencing to start directly after the poly(A) tail into the 3′-untranslated regions (UTR). Our comparative analysis demonstrates that it outperforms existing protocols in quality and throughput and accurately quantifies RNA levels as only one read is produced from each transcript. We use this method to characterize the diversity of polyadenylation in Saccharomyces cerevisiae, showing that alternative RNA molecules are present even in a genetically identical cell population. Finally, we observe that overlap of convergent 3′-UTRs is frequent but sharply limited by coding regions, suggesting factors that restrict compression of the yeast genome.
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Affiliation(s)
- Stefan Wilkening
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
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17
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Schlüter N, Hanstedt A, Stinshoff H, Knauer K, Wilkening S, Wrenzycki C. 204 PERIPHERAL PROGESTERONE CONCENTRATION AFFECTS BOVINE OOCYTE QUALITY AT THE MOLECULAR LEVEL. Reprod Fertil Dev 2013. [DOI: 10.1071/rdv25n1ab204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The developmental competence of cumulus–oocyte complexes (COC) used for in vitro production is dependent on several factors including the stage of the oestrus cycle. In a recent study, we were able to show that circulating progesterone (P4) had no effect on follicle number, size, recovery rate, or in vitro production suitability of recovered COC (Schlüter et al. 2012 Reprod. Fertil. Dev. 24, 175–176). The aim of the present study was to determine the influence of circulating P4 concentrations on the molecular quality of bovine COC collected during repeated OPU sessions. The COC were aspirated twice per week for 5 to 6 weeks from 12 Holstein Friesian heifers. The first OPU session took place on Day 7 of the oestrous cycle after spontaneous ovulation (ovulation = Day 0). Blood samples were taken at the time of each OPU session, and P4 concentrations were determined using a radioimmunoassay. All animals showed clinical signs of oestrus and large follicles (≥8.5 mm) during the course of the OPU sessions. Following the aspiration of a large follicle, a CL-like structure (induced CL) could be detected. According to the P4 concentrations, the cycle was divided into 3 phases: CL phase after spontaneous ovulation (oCL; P4: ≥1 ng mL–1), follicle phase 1 (Fp; P4 <1 ng mL–1), and induced CL phase (iCL; P4: ≥1 ng mL–1). The length of the cycle after spontaneous ovulation did not differ significantly from that after induced ovulation (22.4 ± 3.1 days v. 23.8 ± 1.8 days, respectively). During the oCL-phase, blood P4 concentrations were significantly higher than during the iCL-phase (4.9 ± 2.3 ng mL–1 v. 3.0 ± 1.6 ng mL–1). For mRNA analysis, denuded COC were individually frozen at –80°C to analyse the relative transcript abundance using RT-qPCR. The transcripts studied play important roles during oocyte development [growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15), glucose transporter 1 (SCL2A1), hypoxia inducible factor 2α (HIF2α), progesterone receptor (PGR), progestin and adipoQ receptor 5 (PAQR5), progesterone receptor membrane component 1 and 2 (PGRMC1, PGRMC2)]. Data were tested using analysis of variance (ANOVA) followed by multiple pairwise comparisons using Tukey’s test. A P-value of ≤0.05 was considered significant. The relative abundance of all transcripts except SCL2A1 was significantly increased in oocytes collected from follicles of the oCL phase compared with that from oocytes that had been aspirated during the iCL phase. A significant increase in the relative amount of PGR, PGRMC1, PGRMC2, and BMP15 transcripts was detected in oocytes stemming from the follicular phase to those from the iCL phase. No differences in the relative abundance of all transcripts were seen comparing oocytes from oCL phase and oocytes from the follicular phase. In summary, circulating P4 concentrations had an effect on the molecular quality of COC recovered during repeated OPU session, which might affect further development.
The financial support of the FBF (Förderverein Biotechnologieforschung) e.V. is gratefully acknowledged.
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Knauer K, Stinshoff H, Wilkening S, Wrenzycki C. 235 PROGESTERONE AFFECTS THE MESSENGER RNA EXPRESSION OF IN VITRO-PRODUCED BOVINE EMBRYOS. Reprod Fertil Dev 2013. [DOI: 10.1071/rdv25n1ab235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
It is known that the progesterone (P4) provided by the corpus luteum is essential for the maintenance of pregnancy. It has been suggested that supplying external P4 in vivo is beneficial to the establishment and upkeep of pregnancy. The aim of the present study was to assess the effects of supplementation with different concentrations of P4 on either of 2 days of in vitro culture (IVC) on early bovine embryo development in an in vitro model. A total of 5073 cumulus–oocyte complexes were matured and fertilized in vitro. Before culture, they were collected in groups of 30 and allocated to 1 of 9 groups. The groups were supplemented with 10, 20, or 100 ng of P4 on Days 4 or 5 of IVC (IVF = Day 0). Alcohol (ETOH) was used as the solvent, so 8 µL of ETOH was used per supplementation. Therefore, two additional groups were supplemented with only ETOH on Day 4 or 5 of IVC. The presumptive zygotes allocated to group 9 were not supplemented. A culture system without oil overlay was used to prevent the lipophilic P4 from moving into the oil. Embryo cleavage and development rates were determined solely on Day 8 of IVC. Single expanded blastocysts were stored at –80°C for RT-qPCR. Subsequently, the relative amounts of six developmentally important gene transcripts (IGF1R, SLC2A1, HSD3B1, IFNT, PGRMC1, and PGRMC2) were analysed in single embryos of all groups. Statistical analysis was performed using one-way and two-way ANOVA, and the level of significance was set at P ≤ 0.05. Cleavage and development rates did not differ among groups (see Table 1). The relative abundance of IGF1R, SLC2A1, PGRMC1, and PGRMC2 was not affected by either the concentration or the timing of P4 supplementation. Nevertheless, there was a statistically significant interaction between the day of treatment and the concentration used for the expression of HSD3B1 mRNA. When 20 ng of P4 was added on Day 5 of IVC, significantly more HSD3B1 transcripts were detected than if 10 ng, 100 ng, or ETOH alone was added. The expression of IFNT was not affected by the day of supplementation, only by the concentration used. Thus, supplementation with 20 ng of P4 resulted in a significantly higher level of transcripts than when 10 ng or ETOH was supplemented. The results indicate that the amount of P4 present during early embryonic development and the timing of its presence had an impact on molecular developmental competence. However, no effects concerning morphological development up to the blastocyst stage could be detected.
Table 1.Cleavage and development rates (± SEM) of embryos supplemented with 10, 20, or 100 ng on Day 4 or 5 of in vitro culture (P ≥ 0.05)
The financial support of the FBF e.V. is acknowledged.
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Abstract
Alternative polyadenylation site usage gives rise to variation in 3' ends of transcripts in diverse organisms ranging from yeast to human. Accurate mapping of polyadenylation sites of transcripts is of major biological importance, since the length of the 3'UTR can have a strong influence on transcript stability, localization, and translation. However, reads generated using total mRNA sequencing mostly lack the very 3' end of transcripts. Here, we present a method that allows simultaneous analysis of alternative 3' ends and transcriptome dynamics at high throughput. By using transcripts produced in vitro, the high precision of end mapping during the protocol can be controlled. This method is illustrated here for budding yeast. However, this method can be applied to any natural or artificially polyadenylated RNA.
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Affiliation(s)
- Vicent Pelechano
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
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Stinshoff H, Onnen-Lübben E, Wilkening S, Hanstedt A, Bollwein H, Wrenzycki C. 57 DIETARY CLA SUPPLEMENTATION AFFECTS LUTEAL GENE EXPRESSION AND PERIPHERAL BLOOD PROGESTERONE CONCENTRATION IN CATTLE. Reprod Fertil Dev 2012. [DOI: 10.1071/rdv24n1ab57] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Shortly after parturition the metabolic situation of high-yielding dairy cows is often dominated by a negative energy balance. These effects affect the whole animal and may especially be detected in the reproductive tract, where they result in reduced fertility. An oral supplementation with dietary fats is often used to counteract by reducing milk fat content and, thus, supplying the individual animal with an increased amount of energy. The focus of the present study was to analyse the effects of an oral supplementation with conjugated linoleic acids (CLA) on corpus luteum (CL) function. Healthy Holstein-Friesian cows and heifers were randomly allocated to 2 treatment groups (Group 1: 50 g of CLA day–1 per animal, 2 heifers, 6 cows; Group 2: 100 g of CLA day–1 per animal, 2 heifers, 6 cows) and 1 control group (Ctl; 0 g of CLA day–1 per animal, 3 heifers, 4 cows). Feeding of the supplement began shortly after calving. After calving, all animals were subjected to a standard synchronisation protocol and experienced AI on Day 59 ± 3. Following AI, transvaginal biopsies of the corpus luteum were obtained of pregnant (Group I: n = 4; Group II: n = 4; Ctl: n = 4) and nonpregnant (Group I: n = 4; Group II: n = 4; Ctl: n = 3) animals on Days 6, 13 and 20 post-AI. Animals deemed pregnant on Day 28 were again biopsied on Day 42. Additionally, blood samples were taken from the vena sacralis mediana at the time of each biopsy. The biopsies were analysed regarding the relative abundance of 8 gene transcripts (VEGF, ECE1, PLA2G4A, PTGS2, PTGFR, PPARG, STAR and HSD3B1) via RT-qPCR. Blood samples were analysed for their concentration of progesterone through a radioimmunoassay (RIA). Statistical analysis for both datasets was performed via a 3-way ANOVA with adjoining Tukey test. The expression of 7 of these genes was affected by 1, 2, or all 3 of the following factors: day of cycle (VEGF, ECE1, PLA2G4A, PTGFR, STAR and HSD3B1), pregnancy status (ECE1, PTGFR and HSD3B1) and CLA supplementation (ECE1, PTGS2, PTGFR, STAR and HSD3B1). The effects of the CLA supplementation could be seen as a down-regulation in the mentioned gene transcripts. Progesterone concentrations differed significantly in dependency of the pregnancy status (significantly higher in pregnant vs nonpregnant individuals) of the animals, as well as during the days of the oestrous cycle (physiological progesterone curve with highest values on Day 13 of these samples). An effect of the oral supplementation with CLA could be detected during the early luteal phase (Day 6) where animals that had received 100 g of CLA day–1 had a significantly lower blood progesterone concentration than those receiving 50 g of CLA day–1 or no CLA. In conclusion, dietary CLA supplementation has an effect on luteal gene expression and functionality.
The authors thank the DFG (German Research Foundation) for their financial support (PAK286/1; WR154/1-1).
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Stinshoff H, Wilkening S, Hanstedt A, Brüning K, Wrenzycki C. Cryopreservation affects the quality of in vitro produced bovine embryos at the molecular level. Theriogenology 2011; 76:1433-41. [DOI: 10.1016/j.theriogenology.2011.06.013] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2011] [Revised: 06/06/2011] [Accepted: 06/13/2011] [Indexed: 11/26/2022]
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Beilby KH, de Graaf SP, Evans G, Maxwell WMC, Wilkening S, Wrenzycki C, Grupen CG. Quantitative mRNA expression in ovine blastocysts produced from X- and Y-chromosome bearing sperm, both in vitro and in vivo. Theriogenology 2011; 76:471-81. [PMID: 21497386 DOI: 10.1016/j.theriogenology.2011.02.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2010] [Revised: 02/22/2011] [Accepted: 02/24/2011] [Indexed: 11/17/2022]
Abstract
Artificial insemination (AI) of sex-sorted sperm results in decreased fertility, compared with non-sorted sperm, in most species. However, this has not been the case in sheep, where the low-dose AI of sex-sorted ram sperm produced similar, if not superior, fertility to non-sorted controls. The aim of the present study was to determine the impact of sex-sorting technology on ovine embryo gene expression following embryo production in vivo and in vitro. After semen collection, ejaculates were split and either sex-sorted by flow cytometry and frozen, or diluted and frozen. Embryos were produced in vivo by inseminating superovulated ewes with either X- or Y-chromosome enriched sperm, or non-sorted control sperm, and collected by uterine flushing on Day 6 after AI. Embryos were produced in vitro using the same sperm treatments and cultured in vitro for 6 d. The relative abundance of selected gene transcripts was measured in high-grade blastocysts, defined by morphological assessment, using RT-qPCR. The mRNA expression of DNMT3A and SUV39H1 was upregulated in embryos cultured in vitro, compared to those cultured in vivo (DNMT3A: 3.61 ± 1.08 vs 1.99 ± 0.15; SUV39H1: 1.88 ± 0.11 vs 0.88 ± 0.07; mean ± SEM; P < 0.05). Both G6PD and SLC2A3 transcripts were reduced in embryos produced from sex-sorted sperm, in vivo (SLC2A3: 0.23 ± 0.03 vs 0.64 ± 0.10; G6PD: 0.32 ± 0.04 vs 1.01 ± 0.16; P < 0.05). The expression of DNMT3A was up-regulated in male (3.85 ± 0.31), compared to female embryos (2.34 ± 0.15; P < 0.05). This study contributes to the growing body of evidence citing aberrant patterns of gene expression resulting from in vitro culture. Whereas the process of sex-sorting altered the expression of several of the genes examined, no effect on embryo development was detected.
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Affiliation(s)
- K H Beilby
- Faculty of Veterinary Science, The University of Sydney, NSW 2006, Australia.
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Kuzmany A, Havlicek V, Wrenzycki C, Wilkening S, Brem G, Besenfelder U. 76 EFFECT OF CULTURE METHOD ON THE mRNA EXPRESSION BEFORE AND AFTER CRYOPRESERVATION IN BOVINE BLASTOCYSTS. Reprod Fertil Dev 2011. [DOI: 10.1071/rdv23n1ab76] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Blastocyst mRNA expression and cryopreservability are thought to be suitable indicators of embryo quality and developmental competence and have been shown to be affected by production methods and culture systems. The aim of the present study was to assess cryosurvival and levels of mRNA expression of selected genes [occludin, desmocollin 2, solute carrier family 2 member 3 (formerly glucose transporter 3), BAX, BCL xL, heat shock protein A1A (formerly heat shock protein 70.1), aquaporin 3, and DNA methyltransferase 1a] of bovine blastocysts derived by 4 different, established culture methods [in vitro production (IVP); multiple-ovulation embryo transfer (MOET); transfer into the heifer oviducts of gametes (GIFT); or in vitro derived cleaved stage embryos (Days 2–7)]. Linear models were used for the comparison of the relative abundances of the blastocyst mRNA transcripts. Separate 1-way ANOVA were used. The production methods were used as factors, except for the comparisons between pre- and post-cryopreservation, where 2-way ANOVA were used. The level of significance was set at P ≤ 0.05. A significant difference in re-expansion rates was found only at 24 h post-thawing, with significantly higher rates in blastocysts produced in vitro compared to embryos of the Days 2–7 group. Levels of mRNA expression were assessed using RT-qPCR. Before cryopreservation of embryos, no significant inter-group differences were seen. However, significantly more desmocollin 2 mRNA expression was detected in embryos of the MOET group compared with blastocysts derived by the other production methods. Post-cryopreservation, blastocysts of 3 embryo production groups (IVP, MOET, Days 2–7) were available for analysis. Compared with levels of mRNA expression before cryopreservation, re-expanded blastocysts after cryopreservation showed a significant up-regulation of heat shock protein A1A transcripts in all groups, and of solute carrier family 2 member 3 transcripts only in the IVP-derived group. The BAX, BCL-xL, occludin, and desmocollin 2 were significantly up-regulated in embryos of the MOET and IVP groups after cryopreservation, as compared with their counterparts before cryopreservation. None of the culture groups showed any pre- v. post-cryopreservation differences in the aquaporin 3 and the DNA methyltransferase 1 mRNA levels. Blastocysts derived by transfer of in vitro derived cleaved stage embryos into the oviduct of synchronised heifers (Days 2–7) did not show any pre- v. post-cryopreservation differences in the mRNA levels of any of the assessed genes. These results merit further investigation. After the process of cryopreservation and thawing, re-expanded embryos of the MOET and IVP groups do increase their mRNA levels to prepare for hatching and further development.
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Abele E, Stinshoff H, Hanstedt A, Wilkening S, Meinecke-Tillmann S, Wrenzycki C. 109 INTRAFOLLICULAR GLUCOSE CONCENTRATION HAS AN INFLUENCE ON THE SEX OF BOVINE BLASTOCYSTS PRODUCED IN VITRO. Reprod Fertil Dev 2011. [DOI: 10.1071/rdv23n1ab109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Several factors have been shown to alter the sex ratio of bovine embryos generated in vitro, i.e. the maturity of the oocyte at the time of insemination, the duration of sperm-oocyte co-incubation and the culture conditions after in vitro fertilization. It has been shown that the presence of glucose during in vitro culture reduced the development of female embryos to the blastocyst stage compared with controls cultured in the absence of glucose. The sex ratio of bovine embryos has also been linked with changes in the composition of the follicular fluid in which the oocyte undergoes growth and maturation, i.e. the intrafollicular testosterone concentration. However, no information is available regarding the effect of intrafollicular glucose concentration on the sex ratio of embryos after in vitro production (IVP). The purpose of this study was to determine whether different glucose concentrations in the follicular fluid at the time of cumulus–oocyte complex (COC) collection have an effect on the sex ratio of the resulting blastocysts after IVP. Ovaries from a local abattoir were transported to the laboratory within 2 h of slaughter. Follicles (3–8 mm) were individually dissected and the glucose concentration of each follicle was measured using a blood glucose monitoring system (Freestyle Freedom Lite, Abbott, Germany). Based on a glucose concentration, COC [low glucose: <1.1 mM (group 1) and high glucose: >1.1 mM (group 2)] were pooled in groups and used for blastocyst production employing standard protocols for IVP. Developmental rates were recorded at Day 3 (cleavage) and Day 7/8 (blastocyst stage). Total cell number of blastocysts was determined after Hoechst staining. Sex of the embryos was analysed via PCR using bovine X- and Y-chromosome specific primers. Developmental rates for COC stemming from follicles with different glucose concentrations did not show significant differences (P > 0.05) compared to each other [Cleavage rate: group 1: 81.8 ± 4.7% (93/117); group 2: 79.3 ± 4.9% (94/123); blastocyst rate: group 1: 35.6 ± 5.2% (38/117); group 2: 31.6 ± 5.2% (38/123)]. Total cell numbers were similar in embryos of both groups [Group 1: 117.7 ± 8.1 (n = 18); group 2: 117.2 ± 6.4 (n = 18)]. The overall sex ratio significantly differed (P < 0.05) from 1:1 in favour of females in both groups [Group 1: 85 v. 15% (n = 20); group 2: 63.6 v. 36.4% (n = 22)]. No significant difference (P > 0.05) in the overall sex ratio was detected in blastocysts produced under standard IVP conditions employed in the laboratory [without measurement of follicular glucose concentration, 55.0 v. 45.0%, (n = 20)]. In conclusion, under the conditions used in the present study, the intrafollicular glucose concentration from which the immature COC was collected affects the sex of the resulting embryo after IVP, favouring females. Further studies are needed to confirm these findings in living cows using the ovum pickup technique.
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Hanstedt A, Wilkening S, Brüning K, Honnens Ä, Wrenzycki C. 128 EFFECT OF PERIFOLLICULAR BLOOD FLOW ON THE QUALITY OF OOCYTES COLLECTED DURING REPEATED OPU SESSIONS. Reprod Fertil Dev 2010. [DOI: 10.1071/rdv22n1ab128] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Approximately 20% of the cumulus-oocyte complexes (COC) collected from living animals during repeated ovum pick-up (OPU) sessions develop to the blastocyst stage. An increase in the blood supply to individual follicles appears to be associated with follicular growth rates, while a reduction seems to be closely related to follicular atresia (Acosta TJ et al. 2003; Reproduction, 125, 759-767). Recently, it has been shown that differences in perifollicular blood flow during repeated OPU sessions once weekly were predictive of oocyte competence. The purpose of this study was to determine whether qualitative perifollicular blood flow changes affect the quality of oocytes collected during repeated OPU sessions once or twice weekly as well as the quality of the resulting blastocysts. Lactating Holstein cows (n = 20) were used as oocyte donors. After dominant follicle removal, OPU was performed twice (group 1, for 3 weeks) or once (group 2, for six weeks) weekly employing a 7.5 MHz transducer (GE 8C-RS) of an ultrasound scanner (GE Logiq Book). Doppler characteristics were recorded by transvaginal ultrasonography just before COC collection using the color flow imaging. Because of technical limitations for measurement of blood flow in small individual follicles, only the presence or absence of blood flow was assessed for each follicle. When a clearly visible blue or red spot (blood flow) was detected in the follicle wall, it was considered a follicle with detectable blood flow. Follicles with or without detectable blood flow from each individual cow were aspirated separately. After morphological classification of COC, standard protocols for IVP were used for blastocyst production. For mRNA analysis, denuded COC and blastocysts were frozen at -80°C to analyze the relative transcript abundance using RT-qPCR. The transcripts studiedplay important roles during oocyte and embryo development [DNA methyltransferase 1a, 1b, 3a (DNMT1a, DNMT1b, DNMT3a); histone deacetylase 2 (HDAC2); growth differentiation factor 9 (GDF9); bone morphogenetic protein 15 (BMP15); maternal effect gene zygotic arrest (ZAR); heat shock protein 70.1 (HSP); glucose transporter1, 3 (GLUT1, GLUT3); glucose-6-phosphate dehydrogenase (G6PD); and desmocollin II (DCII)]. Data were tested using analysis of variance (ANOVA) followed by multiple pairwise comparisons using Tukey’s test. The relative abundances of ZAR, BMP15, GDF9, DNMT1a, DNMT3a, and HDAC2 transcripts were significantly upregulated in oocytes stemming from OPU sessions twice weekly, whereas qualitative blood flow changes did not influence the mRNA abundance. At the blastocyst stage, G6PD mRNA was upregulated in blastocysts generated from oocytes collected in OPU sessions twice weekly. These results show that the time interval between the individual OPU sessions had an effect on the quality of oocyte and embryos at the molecular level, whereas differences in the perifollicular blood flow did not.
Ruthe Research Farm, Germany for providing the animals; Masterrind GmbH, Germany for donation of the semen, and the HW Schaumann Stiftung for financial support.
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Beilby KH, Wilkening S, de Graaf SP, Wrenzycki C, Grupen CG. 364 QUANTIFICATION OF DEVELOPMENTALLY IMPORTANT GENE TRANSCRIPTS EXPRESSED IN EMBRYOS PRODUCED IN VIVO AND IN VITRO USING SEX-SORTED AND NON-SORTED RAM SPERMATOZOA. Reprod Fertil Dev 2010. [DOI: 10.1071/rdv22n1ab364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The AI of sex-sorted spermatozoa results in decreased levels of fertility in most species. This is not the case in sheep, where low-doseAI of sex-sorted ram spermatozoa produces similar, if not superior levels of fertility to non-sorted controls (Beilby et al. 2009 Theriogenology, 71, 829-835). In an effort to provide insight into the molecular basis for this difference in fertility between species, the aim of the present study was to examine the impact of sex-sorting technology on ovine embryo gene expression. After semen collection, ejaculates (n = 8) were split and either sex-sorted by flow cytometry and frozen, or diluted and frozen (non-sorted control). Embryos were produced in vivo by inseminating superovulated ewes with either X- or Y-chromosome enriched spermatozoa, or non-sorted control spermatozoa, and collected by flushing uterine horns on Day 6 after AI. Embryos were produced in vitro by using established oocyte in vitro maturation and in vitro fertilization procedures (using X, Y or non-sorted spermatozoa), and cultured in vitro for 6 days. The relative abundance of Glut-3, G6PD, SUV39H1, DnMT3a, and HSP70 was measured in high grade blastocysts (in vivo Day 6: n = 23; in vitro Day 6: n = 21) using quantitative, real-time PCR (iCycler5TM, BioRad, Hercules, CA, USA). Blastocyst cell numbers were quantified to ensure embryos were at a similar stage of development. The sex of all embryos was identified by PCR to allow comparison between treatments. Fold differences in gene expression, acquired through the A ACt method, were calculated and compared by an ANOVA. The expression of HSP70 was up-regulated in in vitro embryos derived from sex-sorted spermatozoa compared to those produced in vivo (P < 0.05). For all other genes examined, there was no effect of sex or sperm treatment on gene expression. Glut-3, G6PD, SUV39H1, andDnMT3a were all up-regulated in in vitro embryos compared with in vivo embryos (P < 0.05). These results suggest that fertilization with sex-sorted ram spermatozoa does not result in aberrant patterns of gene expression in embryos produced in vivo. The data from the present study provide further evidence that in vitro culture induces epigenetic modification within the embryonic genome, when compared to the in vivo physiological standard. It would be of interest to conduct a similar in vivo study in cattle, where sex-sorting technology has not been as biologically successful. The altered expression of HSP70, which is associated with cellular stress, may demonstrate a cumulative impact of in vitro reproductive technologies on the preimplantation embryo.
Research supported by XY, Inc.
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Stinshoff H, Brüning K, Hanstedt A, Müller D, Wilkening S, Wrenzycki C. 117 EFFECT OF DIFFERENT CRYOPRESERVATION METHODS ON THE QUALITY OF IN VITRO-PRODUCED BOVINE EMBRYOS. Reprod Fertil Dev 2010. [DOI: 10.1071/rdv22n1ab117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
In vitro production (IVP) of bovine embryos has been greatly improved over the last couple of years. However, only one-third of the total number of embryos transferred worldwide are of in vitro origin. The IVP embryos still show remarkable differences compared with their in vivo-derived counterparts (i.e. bovine embryos produced in vitro are more sensitive to cryopreservation). So far, vitrification seems to be the most promising method to cryopreserve in vitro-produced bovine embryos. The aim of this study was to determine the effect of 2 different cryopreservation methods on the quality of in vitro-produced bovine embryos at the molecular level using a sensitive RT-qPCR assay. Bovine blastocysts were produced using abattoir ovaries and a standard protocol for IVP (Wrenzycki et al. 2001). They were randomly vitrified employing PBS plus ethylene glycol and DMSO or cryopreserved using a programmable freezer and 1.5 M ethylene glycol. After thawing, embryos from both groups were cultured for 48 h. After 24 h of culture re-expansion rates were documented, and after 48 h hatching rates were documented. After hatching, blastocysts were stored at -80°C for subsequent RT-qPCR analysis. The following gene transcripts known to play important roles during preimplantation development were analyzed: HSP70, GLUT-1, GLUT-3, E-CAD, ZO-1, DNMT3a, IFNτ, DCII. Re-expansion rates were 74.7% (68/91) and 75.0% (87/116) for vitrified and conventionally cryopreserved blastocysts, and 57.1% (52/91) and 55.2% (64/116) of re-expanded embryos hatched. The relative abundances of HSP70, GLUT-1, and ZO-1 transcripts were significantly affected in both groups of cryopreservation compared with the control group (hatched blastocysts without cryopreservation). Conventional cryopreservation had a significant effect on the amount of GLUT-3, DNMT3a, and IFNτ mRNA, whereas vitrification significantly affected DCII transcripts. E-CAD mRNA expression was similar in all groups of embryos. These results suggest that not only the cryopreservation process itself but also the method used to freeze the embryos had a significant influence on the mRNA expression of developmentally important genes in hatched bovine blastocysts.
The support of the H.W. Schaumann Stiftung (Germany) and Gynemed Medizinprodukte GmbH & Co. KG (Germany) is gratefully acknowledged.
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Chen B, Wilkening S, Drechsel M, Hemminki K. SNP_tools: A compact tool package for analysis and conversion of genotype data for MS-Excel. BMC Res Notes 2009; 2:214. [PMID: 19852806 PMCID: PMC2771038 DOI: 10.1186/1756-0500-2-214] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2009] [Accepted: 10/23/2009] [Indexed: 11/23/2022] Open
Abstract
Background Single nucleotide polymorphism (SNP) genotyping is a major activity in biomedical research. Scientists prefer to have a facile access to the results which may require conversions between data formats. First hand SNP data is often entered in or saved in the MS-Excel format, but this software lacks genetic and epidemiological related functions. A general tool to do basic genetic and epidemiological analysis and data conversion for MS-Excel is needed. Findings The SNP_tools package is prepared as an add-in for MS-Excel. The code is written in Visual Basic for Application, embedded in the Microsoft Office package. This add-in is an easy to use tool for users with basic computer knowledge (and requirements for basic statistical analysis). Conclusion Our implementation for Microsoft Excel 2000-2007 in Microsoft Windows 2000, XP, Vista and Windows 7 beta can handle files in different formats and converts them into other formats. It is a free software.
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Affiliation(s)
- Bowang Chen
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
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Wilkening S, Chen B, Bermejo JL, Canzian F. Is there still a need for candidate gene approaches in the era of genome-wide association studies? Genomics 2009; 93:415-9. [PMID: 19162167 DOI: 10.1016/j.ygeno.2008.12.011] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2008] [Revised: 12/01/2008] [Accepted: 12/30/2008] [Indexed: 11/26/2022]
Abstract
Most genetic variants associated with complex diseases in humans are believed to have a small impact on risk. With traditional candidate gene/pathway approaches several associations with disease risk could be identified. However, now that genome-wide association studies are feasible, the question arises if there is still a need for these approaches. By using HapMap data, we evaluated to which extent commercially available microarrays cover, through linkage disequilibrium, all currently known genes and biological processes in different populations. Furthermore, we estimated the power to detect an association with any specific SNP. Our study shows that coverage of individual genes and pathways by current commercial genotyping platforms is satisfactory for the vast majority of RefSeq gene regions. However, depending on the gene or the population, there may still be a need for candidate gene approaches, especially when looking at polymorphisms with low allele frequencies.
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Affiliation(s)
- Stefan Wilkening
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
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Dossus L, McKay JD, Canzian F, Wilkening S, Rinaldi S, Biessy C, Olsen A, Tjonneland A, Jakobsen MU, Overvad K, Clavel-Chapelon F, Boutron-Ruault MC, Fournier A, Linseisen J, Lukanova A, Boeing H, Fisher E, Trichopoulou A, Georgila C, Trichopoulos D, Palli D, Krogh V, Tumino R, Vineis P, Quiros JR, Sala N, Martinez-Garcia C, Dorronsoro M, Chirlaque MD, Barricarte A, van Duijnhoven FJ, Bueno-de-Mesquita H, van Gils CH, Peeters PH, Hallmans G, Lenner P, Bingham S, Khaw KT, Key TJ, Travis RC, Ferrari P, Jenab M, Riboli E, Kaaks R. Polymorphisms of genes coding for ghrelin and its receptor in relation to anthropometry, circulating levels of IGF-I and IGFBP-3, and breast cancer risk: a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). Carcinogenesis 2008; 29:1360-6. [DOI: 10.1093/carcin/bgn083] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
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Wilkening S, Tavelin B, Canzian F, Enquist K, Palmqvist R, Altieri A, Hallmans G, Hemminki K, Lenner P, Försti A. Interleukin promoter polymorphisms and prognosis in colorectal cancer. Carcinogenesis 2008; 29:1202-6. [PMID: 18448485 DOI: 10.1093/carcin/bgn101] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
There is strong evidence that cancer-associated inflammation promotes tumor growth and progression. This is especially true for colorectal cancer (CRC). Interleukins (ILs) are important modulators for inflammation. We examined whether promoter polymorphisms in key IL genes (IL4, IL4R, IL6, IL8 and IL10) are associated with the risk or clinical outcome of CRC. Five single-nucleotide polymorphisms (SNPs) were analyzed in genomic DNA from a cohort including 308 Swedish incident cases of CRC with data on Dukes' stage and up to 16 years of follow-up and 585 healthy controls. The selected SNPs have previously been shown to be functional and/or associated with cancer. None of the analyzed SNPs associated with the risk of CRC. When stratifying by tumor stage, significantly more patients carrying at least one G allele of IL10-1082 had tumors with Dukes' stages A + B than with stages C + D (P(trend) = 0.035 for genotype distribution). Analyzing associations with overall survival time, we found the rare T allele of IL4-590 to be related to a longer survival [CT versus CC Cox proportional hazard ratio 0.69, 95% confidence intervals 0.46-1.03, TT versus CC 0.32 (0.10-1.03)]. For IL6-174, the CG genotype was associated with a longer survival when compared with the CC genotype [0.64 (0.40-1.01)]. The present study was particularly suitable for survival analysis because all patients were sampled before the diagnosis of CRC. Our results suggest that the SNPs IL4-590 and IL6-174 may be useful markers for CRC prognosis. The predicted biological effect of these SNPs in relation to promotion of cancer progression is consistent with the observed increased survival time.
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Affiliation(s)
- Stefan Wilkening
- Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
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Tenesa A, Farrington SM, Prendergast JGD, Porteous ME, Walker M, Haq N, Barnetson RA, Theodoratou E, Cetnarskyj R, Cartwright N, Semple C, Clark AJ, Reid FJL, Smith LA, Kavoussanakis K, Koessler T, Pharoah PDP, Buch S, Schafmayer C, Tepel J, Schreiber S, Völzke H, Schmidt CO, Hampe J, Chang-Claude J, Hoffmeister M, Brenner H, Wilkening S, Canzian F, Capella G, Moreno V, Deary IJ, Starr JM, Tomlinson IPM, Kemp Z, Howarth K, Carvajal-Carmona L, Webb E, Broderick P, Vijayakrishnan J, Houlston RS, Rennert G, Ballinger D, Rozek L, Gruber SB, Matsuda K, Kidokoro T, Nakamura Y, Zanke BW, Greenwood CMT, Rangrej J, Kustra R, Montpetit A, Hudson TJ, Gallinger S, Campbell H, Dunlop MG. Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat Genet 2008; 40:631-7. [PMID: 18372901 DOI: 10.1038/ng.133] [Citation(s) in RCA: 456] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2007] [Accepted: 02/29/2008] [Indexed: 12/12/2022]
Abstract
In a genome-wide association study to identify loci associated with colorectal cancer (CRC) risk, we genotyped 555,510 SNPs in 1,012 early-onset Scottish CRC cases and 1,012 controls (phase 1). In phase 2, we genotyped the 15,008 highest-ranked SNPs in 2,057 Scottish cases and 2,111 controls. We then genotyped the five highest-ranked SNPs from the joint phase 1 and 2 analysis in 14,500 cases and 13,294 controls from seven populations, and identified a previously unreported association, rs3802842 on 11q23 (OR = 1.1; P = 5.8 x 10(-10)), showing population differences in risk. We also replicated and fine-mapped associations at 8q24 (rs7014346; OR = 1.19; P = 8.6 x 10(-26)) and 18q21 (rs4939827; OR = 1.2; P = 7.8 x 10(-28)). Risk was greater for rectal than for colon cancer for rs3802842 (P < 0.008) and rs4939827 (P < 0.009). Carrying all six possible risk alleles yielded OR = 2.6 (95% CI = 1.75-3.89) for CRC. These findings extend our understanding of the role of common genetic variation in CRC etiology.
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Affiliation(s)
- Albert Tenesa
- Colon Cancer Genetics Group, Institute of Genetics and Molecular Medicine, University of Edinburgh and MRC Human Genetics Unit, Edinburgh EH4 2XU, UK
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Abstract
A paper by Bond et al. reported that a single-nucleotide polymorphism (SNP) in the intronic promoter region of the mouse double minute 2 (MDM2) gene (called SNP309) can significantly change the expression of MDM2 and thereby suppress the p53 pathway. Furthermore, it was shown that SNP309 accelerates tumor formation in Li-Fraumeni patients. This initial report aroused the attention of many researchers, which investigated the role of SNP309 for the risk and the onset of cancer in different tissues. To provide a more robust estimate of the effect of this polymorphism on cancer risk, we combined the available genotype data for breast, colorectal and lung cancers. For breast cancer, we combined the data from 11 studies including 5737 cases and 6703 controls. For colorectal cancer, we combined the data from five studies with 1620 cases and 886 controls. For lung cancer, we performed a fixed-effect meta-analysis from seven studies including 4276 cases and 5318 controls. Our results suggest that the SNP309 variant does not have an impact on the risk of breast [odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.87-1.08] or colorectal cancers (OR = 0.97, 95% CI = 0.76-1.25). However, the combined estimate of the ORs for lung cancer revealed an increased risk for GG versus TT (OR = 1.27, 95% CI = 1.12-1.44). The data show that SNP309 alone has little or no effect on the risk of common cancers, but it might modify the time of tumor onset and prognosis.
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Affiliation(s)
- Stefan Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
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Wilkening S, Hemminki K, Rudnai P, Gurzau E, Koppova K, Försti A, Kumar R. No association between MDM2 SNP309 promoter polymorphism and basal cell carcinoma of the skin. Br J Dermatol 2007; 157:375-7. [PMID: 17553029 DOI: 10.1111/j.1365-2133.2007.07994.x] [Citation(s) in RCA: 264] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND The MDM2 oncoprotein promotes cell survival and cell cycle progression by inhibiting the p53 tumour suppressor protein. Further, overexpression of the MDM2 gene can inhibit DNA double-strand break repair in a p53-independent manner. Recent studies have shown that a single nucleotide polymorphism (SNP) in the intronic promoter region of MDM2 (called SNP309) can significantly change the expression of MDM2 and thereby suppress the p53 pathway. This SNP was also found to be associated with the onset and risk of different cancer types. Basal cell carcinoma of the skin (BCC) is one of the most common neoplasms in the world. BCC development is associated with environmental factors (especially sun exposure) as well as heritable factors. OBJECTIVES The present case-control study investigated the association of the MDM2 SNP309 with the risk and the age at onset of BCC. Methods Data from 509 individuals affected by BCC and 513 healthy controls were genotyped with TaqMan polymerase chain reaction. RESULTS Cases and controls showed a similar genotype distribution and the SNP did not modify the age at onset of BCC. CONCLUSIONS These results suggest that the MDM2 SNP309 alone affects neither the risk nor the age at onset of BCC.
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Affiliation(s)
- S Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
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Wilkening S, Chen B, Wirtenberger M, Burwinkel B, Försti A, Hemminki K, Canzian F. Allelotyping of pooled DNA with 250 K SNP microarrays. BMC Genomics 2007; 8:77. [PMID: 17367522 PMCID: PMC1839100 DOI: 10.1186/1471-2164-8-77] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [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: 02/13/2007] [Accepted: 03/16/2007] [Indexed: 12/02/2022] Open
Abstract
Background Genotyping technologies for whole genome association studies are now available. To perform such studies to an affordable price, pooled DNA can be used. Recent studies have shown that GeneChip Human Mapping 10 K and 50 K arrays are suitable for the estimation of the allele frequency in pooled DNA. In the present study, we tested the accuracy of the 250 K Nsp array, which is part of the 500 K array set representing 500,568 SNPs. Furthermore, we compared different algorithms to estimate allele frequencies of pooled DNA. Results We could confirm that the polynomial based probe specific correction (PPC) was the most accurate method for allele frequency estimation. However, a simple k-correction, using the relative allele signal (RAS) of heterozygous individuals, performed only slightly worse and provided results for more SNPs. Using four replicates of the 250 K array and the k-correction using heterozygous RAS values, we obtained results for 104.141 SNPs. The correlation between estimated and real allele frequency was 0.983 and the average error was 0.046, which was comparable to the results obtained with the 10 K array. Furthermore, we could show how the estimation accuracy depended on the SNP type (average error for A/T SNPs: 0.043 and for G/C SNPs: 0.052). Conclusion The combination of DNA pooling and analysis of single nucleotide polymorphisms (SNPs) on high density microarrays is a promising tool for whole genome association studies.
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Affiliation(s)
- Stefan Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Bowang Chen
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Michael Wirtenberger
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Barbara Burwinkel
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Helmholtz University Group Molecular Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Asta Försti
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Center for Family Medicine, Karolinska Institute, SE-14183 Huddinge, Sweden
| | - Kari Hemminki
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Center for Family Medicine, Karolinska Institute, SE-14183 Huddinge, Sweden
| | - Federico Canzian
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
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Wilkening S, Hemminki K, Rudnai P, Gurzau E, Koppova K, Kumar R, Försti A. Case-control study in basal cell carcinoma of the skin: single nucleotide polymorphisms in three interleukin promoters pre-analysed in pooled DNA. Br J Dermatol 2006; 155:1139-44. [PMID: 17107380 DOI: 10.1111/j.1365-2133.2006.07440.x] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
BACKGROUND Basal cell carcinoma (BCC) is one of the most common neoplasms in the world. Development of BCC is associated with environmental factors (especially sun exposure) as well as heritable factors. OBJECTIVES To analyse three single nucleotide polymorphisms (SNPs) in the promoter regions of interleukin (IL) genes in genomic DNA from 527 cases of BCC and 530 matched controls and to examine if DNA pooling is a useful method on which to base decisions regarding further SNP analysis. METHODS The SNPs analysed were IL6-597, IL10-1082 and IL1B-511. The SNPs were first analysed from pooled DNA and afterwards from individual samples. The DNA pools resulted from a division of the samples into cases and controls, female and male, and three age groups. In these pools the allele frequencies were estimated by two methods, real-time polymerase chain reaction with allele-specific primers, and quantitative sequencing. RESULTS No significant association was found when the allele frequencies in cases and controls were compared. However, by analysis of the individual genotypes we found SNP IL6-597 G/A to be significantly associated with BCC risk (P =0.007). Hereby the heterozygous genotype 'GA' had a protective effect (odds ratio 0.64, 95% confidence interval 0.49-0.84). No significant association was found for IL10-1082 and IL1B-511. CONCLUSIONS The association of SNP IL6-597 with BCC could be found only by individual genotyping, but would have been missed if only data from the pooling analysis had been known.
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Affiliation(s)
- S Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany.
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Wilkening S, Bermejo JL, Burwinkel B, Klaes R, Bartram CR, Meindl A, Bugert P, Schmutzler RK, Wappenschmidt B, Untch M, Hemminki K, Försti A. The single nucleotide polymorphism IVS1+309 in mouse double minute 2 does not affect risk of familial breast cancer. Cancer Res 2006; 66:646-8. [PMID: 16423991 DOI: 10.1158/0008-5472.can-05-3168] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The mouse double minute 2 (MDM2) oncoprotein promotes cell survival and cell cycle progression by inhibiting the p53 tumor suppressor protein. Further, MDM2 overexpression can inhibit DNA double-strand break repair in a p53-independent manner. Recently, it was shown that a single nucleotide polymorphism (SNP) in the MDM2 promoter was associated with an accelerated tumor formation in individuals with a p53 mutation. The present case-control study investigated the association of this SNP (IVS1+309) with the risk and the age of onset of familial breast cancer in patients with unknown p53 mutation status. Data from 549 women affected by familial breast cancer and 1,065 healthy controls were analyzed. The cases did not carry BRCA1/2 mutations. Cases and controls showed a similar genotype distribution and the SNP did not seem to modify the age of onset of familial breast cancer. The data were also examined taking into account the presence of any additional cancer after breast cancer and the family history of cases; however, no association was found. These results suggest that the SNP IVS1+309 alone affects neither the risk nor the age of onset of heritable breast cancer.
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Affiliation(s)
- Stefan Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (Deutsches Krebsforschungszentrum), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
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Abstract
The analysis of short tandem repeats is a widely used method to estimate relatedness between closely related populations or individuals. The AmpFlSTR PCR Amplification Kit has 15 highly variable autosomal markers of tetranucleotide repeats and is principally made to identify individuals and first- or second-degree relatives. However, in many studies one is searching for individuals who are related through more than one generation. We wanted to test whether the amplification kit can also be used to identify more distantly related individuals. Therefore we compared 16 different methods that calculate genetic distance with regard to each method's ability to cluster more distantly related individuals from two test families. Among all the tested methods Nei et al.'s (1983) DA distance performed well in clustering family members within a group of unrelated individuals for a broad range of scenarios. However, second-degree relatives were difficult to cluster with any of the examined methods when other family members were absent. With a simulation we further estimated how many markers would actually be needed to detect a certain degree of relatedness. According to this simulation, one would need at least 123 independent microsatellite markers to detect third-degree relatives with 90% probability. In conclusion, the 15 STR markers in the amplification kit are suitable for detecting only very closely related individuals or entire families.
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Affiliation(s)
- Stefan Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg
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Wilkening S, Hemminki K, Thirumaran RK, Bermejo JL, Bonn S, Försti A, Kumar R. Determination of allele frequency in pooled DNA: comparison of three PCR-based methods. Biotechniques 2005; 39:853-8. [PMID: 16382903 DOI: 10.2144/000112027] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Determination of allele frequency in pooled DNA samples is a powerful and efficient tool for large-scale association studies. In this study, we tested and compared three PCR-based methods for accuracy, reproducibility, cost, and convenience. The methods compared were: (i) real-time PCR with allele-specific primers, (ii) real-time PCR with allele-specific TaqMan® probes, and (iii) quantitative sequencing. Allele frequencies of three single nucleotide polymorphisms in three different genes were estimated from pooled DNA. The pools were made of genomic DNA samples from 96 cases with basal cell carcinoma of the skin and 96 healthy controls with known genotypes. In this study, the allele frequency estimation made by real-time PCR with allele-specific primers had the smallest median deviation (MD) from the real allele frequency with 1.12% (absolute percentage points) and was also the cheapest method. However, this method required the most time for optimization and showed the highest variation between replicates (SD = 6.47%). Quantitative sequencing, the simplest method, was found to have intermediate accuracies (MD = 1.44%, SD = 4.2%). Real-time PCR with TaqMan probes, a convenient but very expensive method, had an MD of 1.47% and the lowest variation between replicates (SD = 3.18%).
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Affiliation(s)
- Stefan Wilkening
- German Cancer Research Center, Molecular Genetic Epidemiology, Heidelberg, Germany.
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Wilkening S, Burwinkel B, Grzybowska E, Klaes R, Pamula J, Pekala W, Zientek H, Hemminki K, Försti A. Polyglutamine repeat length in the NCOA3 does not affect risk in familial breast cancer. Cancer Epidemiol Biomarkers Prev 2005; 14:291-2. [PMID: 15668512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/01/2023] Open
Affiliation(s)
- Stefan Wilkening
- Department of Molecular Genetic Epidemiology, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
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Wilkening S, Burwinkel B, Grzybowska E, Klaes R, Pamula J, Pekala W, Zientek H, Hemminki K, Försti A. Polyglutamine Repeat Length in the NCOA3 Does Not Affect Risk in Familial Breast Cancer. Cancer Epidemiol Biomarkers Prev 2005. [DOI: 10.1158/1055-9965.291.14.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Stefan Wilkening
- 1Department of Molecular Genetic Epidemiology, German Cancer Research Center
| | - Barbara Burwinkel
- 1Department of Molecular Genetic Epidemiology, German Cancer Research Center
| | - Ewa Grzybowska
- 3Department of Tumor Biology, Centre of Oncology, Maria Sklodowska-Curie Institute, Gliwice, Poland; and
| | - Rüdiger Klaes
- 2Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany
| | - Jolanta Pamula
- 3Department of Tumor Biology, Centre of Oncology, Maria Sklodowska-Curie Institute, Gliwice, Poland; and
| | - Wioletta Pekala
- 3Department of Tumor Biology, Centre of Oncology, Maria Sklodowska-Curie Institute, Gliwice, Poland; and
| | - Helena Zientek
- 3Department of Tumor Biology, Centre of Oncology, Maria Sklodowska-Curie Institute, Gliwice, Poland; and
| | - Kari Hemminki
- 1Department of Molecular Genetic Epidemiology, German Cancer Research Center
- 4Department of Biosciences at Novum, Karolinska Institute, Huddinge, Sweden
| | - Asta Försti
- 1Department of Molecular Genetic Epidemiology, German Cancer Research Center
- 4Department of Biosciences at Novum, Karolinska Institute, Huddinge, Sweden
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Affiliation(s)
- Stefan Wilkening
- German Research Centre for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany.
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Wilkening S, Bader A. Quantitative real-time polymerase chain reaction: methodical analysis and mathematical model. J Biomol Tech 2004; 15:107-11. [PMID: 15190083 PMCID: PMC2291683] [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] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Real-time polymerase chain reaction was established for 16 genes using the LightCycler system to evaluate gene expression in human hepatocytes. During the experiments a large set of data has been obtained. These data have now been evaluated with respect to template stability, accuracy of melting curve analysis, and reproducibility. In addition, the statistical evaluation of the efficiencies of all 16 polymerase chain reactions led to a new mathematical model. To examine template stability, the degradation of mRNA and cDNA was determined at different temperatures. Surprisingly, cDNA, which was obtained by first-strand synthesis, appeared to degrade significantly faster than the respective mRNA. Melting curve analysis is a fast and sensitive method to check for polymerase chain reaction specificity. However, we show that two transcription variants of the glutathione S-transferase 1 gene, with over 100 bp length difference, could not be distinguished by this method. Furthermore, an equation was set up describing the correlation between polymerase chain reaction efficiency and crossing point. This equation can be used to estimate the number of template molecules without having a standard of known concentration. Finally, experimental reproducibility of the real-time polymerase chain reaction was defined.
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Affiliation(s)
- Stefan Wilkening
- German Research Centre for Biotechnology, Braunschweig, Germany.
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Wilkening S, Bader A. Influence of culture time on the expression of drug-metabolizing enzymes in primary human hepatocytes and hepatoma cell line HepG2. J Biochem Mol Toxicol 2004; 17:207-13. [PMID: 12898644 DOI: 10.1002/jbt.10085] [Citation(s) in RCA: 78] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Primary cultures of human hepatocytes and hepatoma cell line HepG2 are frequently used to evaluate the hepatic disposition of drugs and other xenobiotics. To check the variability of the expression of drug-metabolizing enzymes in these in vitro models, expression of genes coding for several cytochrome P450 isoforms and phase II enzymes was quantified during culture time by real-time RT-PCR. Gene expression was determined daily for primary hepatocytes maintained in a sandwich culture over 1 week and for HepG2, during the first 10 passages. In primary hepatocytes characteristic expression trends were observed which could be abstracted into three major classes of time curves. Genes of the first and the second class had an expression maximum around day 6 and day 4 in culture, respectively. The third class of genes had two expression peaks: at day 1 and 5 in culture. Surprisingly, also the cell line HepG2 showed significant expression changes during passages. For example, gene expression of cytochrome 1A1 varied 8-fold, that of cytochrome 2B6 30-fold, and that of NADP-quinone reductase 1 more than 200-fold within the first 10 passages. In conclusion, neither primary hepatocytes nor HepG2 cell line display a model for constant expression of drug-metabolizing enzymes.
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Affiliation(s)
- Stefan Wilkening
- German Research Centre for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany.
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Wilkening S, Stahl F, Bader A. Comparison of primary human hepatocytes and hepatoma cell line Hepg2 with regard to their biotransformation properties. Drug Metab Dispos 2003; 31:1035-42. [PMID: 12867492 DOI: 10.1124/dmd.31.8.1035] [Citation(s) in RCA: 564] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Cultures of primary hepatocytes and hepatoma cell line HepG2 are frequently used in in vitro models for human biotransformation studies. In this study, we characterized and compared the capacity of these model systems to indicate the presence of different classes of promutagens. Genotoxic sensitivity, enzyme activity, and gene expression were monitored in response to treatment with food promutagens benzo[a]pyrene, dimethylnitrosamine (DMN), and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP). DNA damage could be detected reliably with the comet assay in primary human hepatocytes, which were maintained in sandwich culture. All three promutagens caused DNA damage in primary cells, but in HepG2 no genotoxic effects of DMN and PhIP could be detected. We supposed that the lack of specific enzymes accounts for their inability to process these promutagens. Therefore, we quantified the expression of a broad range of genes coding for drug-metabolizing enzymes with real-time reverse transcription-polymerase chain reaction. The genes code for cytochromes p450 and, in addition, for a series of important phase II enzymes. The expression level of these genes in human hepatocytes was similar to those previously reported for human liver samples. On the other hand, expression levels in HepG2 differed significantly from that in human. Activity and expression, especially of phase I enzymes, were demonstrated to be extremely low in HepG2 cells. Up-regulation of specific genes by test substances was similar in both cell types. In conclusion, human hepatocytes are the preferred model for biotransformation in human liver, whereas HepG2 cells may be useful to study regulation of drug-metabolizing enzymes.
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Affiliation(s)
- Stefan Wilkening
- German Research Centre for Biotechnology, Organ-und Gewebekultur, Braunschweig, Germany.
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Borrmann L, Wilkening S, Bullerdiek J. The expression of HMGA genes is regulated by their 3'UTR. Oncogene 2001; 20:4537-41. [PMID: 11494149 DOI: 10.1038/sj.onc.1204577] [Citation(s) in RCA: 51] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2001] [Revised: 04/03/2001] [Accepted: 04/30/2001] [Indexed: 11/08/2022]
Abstract
Many benign mesenchymal tumors are characterized by chromosomal abnormalities of the regions 12q15 or 6p21.3 leading to aberrant expression of either HMGA2 (formerly HMGIC) or HMGA1 (formerly HMGIY). The proteins of both genes belong to the HMGA (formerly HMGI(Y)) family of architectural transcription factors. As a rule, aberrant HMGA transcripts found in a variety of benign tumors have intact coding regions at least for the DNA binding domains with a truncation of their 3' untranslated regions. Adding this to the finding that an altered HMGA protein level is not always correlated with an increased amount of corresponding mRNA indicates a posttranscriptional expression control mediated by regulatory elements within the 3'UTR. To check if HMGA expression is under control of such elements we performed luciferase assays with several HMGA2 and HMGA1 3'UTRs of different length. Experiments showed that an up to 12-fold increase in luciferase activity is obtained by the truncation of the 3'UTRs suggesting that the expression of HMGA2 and HMGA1 is controlled by negatively acting regulatory elements within their 3'UTR. Chromosomal aberrations affecting the HMGA genes may therefore influence their expression by an altered stability of the truncated transcripts as a result of the cytogenetic aberrations.
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Affiliation(s)
- L Borrmann
- Center for Human Genetics, University of Bremen, Leobenerstr. ZHG, 28359 Bremen, Germany
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Yang HY, Wilkening S, Iadarola MJ. Spinal cord genes enriched in rat dorsal horn and induced by noxious stimulation identified by subtraction cloning and differential hybridization. Neuroscience 2001; 103:493-502. [PMID: 11246163 DOI: 10.1016/s0306-4522(00)00573-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Persistent nociceptive input increases neuronal excitability and induces a program of gene expression in the dorsal spinal cord. The alteration in gene expression commences with phosphorylation and induction of immediate early genes and proceeds to target genes. Only a few target genes have been identified as yet. The present report uses a polymerase chain reaction-based subtraction cloning procedure to obtain an "anatomically focused" complementary DNA library enriched in transcripts related to sensory spinal cord (rat dorsal horn minus ventral horn). A subset of clones from this library (n=158) was screened to verify dorsal horn enrichment and to identify those regulated by carrageenan-induced peripheral inflammation. Molecular classes which displayed enriched expression included a proto-oncogene not previously associated with sensory processes, two regulators of the Rho/Rac pathway which controls cell shape, and three genes involved in cytoskeletal regulation and scaffolding. Additional transcripts coded for proteins involved in intercellular communication or intracellular function. Within the set of 158 transcripts, one known and two unknown genes were induced by persistent noxious input. The known gene codes for the secreted cysteine proteinase inhibitor, cystatin C, suggesting that modulation of extracellular proteolytic activity occurs. Since it is secreted, cystatin C may also provide a cerebrospinal fluid bio-marker for persistent pain states. Using a combined anatomical and functional approach, we have extended the molecular repertoire of genes expressed and induced in second-order neurons or supporting glial cells in several new directions, with particular emphasis on regulation of cell morphology and plasma membrane dynamics. Some of these proteins reveal new pathways for information signaling in the sensory half of the spinal cord and require further research to understand their role in the adult spinal cord. The induced genes may provide new molecular targets for therapeutic development and provide new probes for investigating the dynamic state of cellular activity that occurs during persistent pain states.
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Affiliation(s)
- H Y Yang
- Neuronal Gene Expression Unit, Pain and Neurosensory Mechanisms Branch, National Institute of Dental and Craniofacial Research, National Institutes of Health, Building 49, 49 Convent Drive, MSC 4410, Bethesda, MD 20892-4410, USA.
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