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159 Publications visible to you, out of a total of 159
A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment.
HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia

Abstract (Expand)

BACKGROUND: Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with … blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. RESULTS: To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers. Moreover, we modelled 15 different chemotherapeutic drugs by estimating their bone marrow toxicity. Taking into account different growth-factor schedules, this adds up to 33 different chemotherapy regimens explained by the model. CONCLUSIONS: We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis and erythropoiesis under combined chemotherapy, G-CSF, and EPO applications. We demonstrate how it can be used to make predictions regarding haematotoxicity of yet untested chemotherapy and growth-factor schedules.

Authors: S. Schirm, C. Engel, M. Loeffler, M. Scholz

Date Published: 26th May 2014

Publication Type: Not specified

Human Diseases: leukemia, anemia

Validation of a brief step-test protocol for estimation of peak oxygen uptake.
LIFE Heart

Abstract (Expand)

BACKGROUND: Physical exercise capacity has been shown to predict cardiovascular disease incidence and is increasingly measured in epidemiological studies. However, direct measurement of peak oxygen … uptake is too time consuming in large-scale studies. We therefore investigated whether a brief 3-minute step-test protocol can be used to estimate peak oxygen uptake in these settings. DESIGN AND METHODS: A group of 97 subjects performed the YMCA step test and a maximal treadmill test with continuous measurement of oxygen uptake. Correlation and linear regression analyses were used to identify VO2peak predictors obtained from the step test and to develop models for VO2peak estimation. RESULTS: The YMCA model, including the 1-minute heart beat count, predicted VO2peak with R = 0.83. A novel simplified model based on the heart rate at 45 s of recovery performed comparable (R = 0.83). However, models based on heart rate measures were only valid in subjects who completed the test according to protocol, but not in subjects who terminated prematurely. For the applicability in subjects with low exercise capacity, a new model including gas exchange analysis enabled prediction of VO2peak (R = 0.89). All models were validated in an independent sample (r = 0.86-0.91). Exercise time of the step test was less than one-hird of standard ergospirometry (treadmill test: 654 +/- 151 s, step test: 180 s, p < 0.001). CONCLUSION: In large-scale epidemiological studies with limited time slots for exercise testing and significant proportions of subjects with low exercise capacity a modified version of the YMCA step test may be used to predict VO2peak.

Authors: F. Beutner, R. Ubrich, S. Zachariae, C. Engel, M. Sandri, A. Teren, S. Gielen

Date Published: 1st May 2014

Publication Type: Not specified

DNA glycosylases involved in base excision repair may be associated with cancer risk in BRCA1 and BRCA2 mutation carriers
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

Single Nucleotide Polymorphisms (SNPs) in genes involved in the DNA Base Excision Repair (BER) pathway could be associated with cancer risk in carriers of mutations in the high-penetrance susceptibility … genes BRCA1 and BRCA2, given the relation of synthetic lethality that exists between one of the components of the BER pathway, PARP1 (poly ADP ribose polymerase), and both BRCA1 and BRCA2. In the present study, we have performed a comprehensive analysis of 18 genes involved in BER using a tagging SNP approach in a large series of BRCA1 and BRCA2 mutation carriers. 144 SNPs were analyzed in a two stage study involving 23,463 carriers from the CIMBA consortium (the Consortium of Investigators of Modifiers of BRCA1 and BRCA2). Eleven SNPs showed evidence of association with breast and/or ovarian cancer at p\textless0.05 in the combined analysis. Four of the five genes for which strongest evidence of association was observed were DNA glycosylases. The strongest evidence was for rs1466785 in the NEIL2 (endonuclease VIII-like 2) gene (HR: 1.09, 95% CI (1.03-1.16), p = 2.7 \times 10(-3)) for association with breast cancer risk in BRCA2 mutation carriers, and rs2304277 in the OGG1 (8-guanine DNA glycosylase) gene, with ovarian cancer risk in BRCA1 mutation carriers (HR: 1.12 95%CI: 1.03-1.21, p = 4.8 \times 10(-3)). DNA glycosylases involved in the first steps of the BER pathway may be associated with cancer risk in BRCA1/2 mutation carriers and should be more comprehensively studied.

Authors: Ana Osorio, Roger L. Milne, Karoline Kuchenbaecker, Tereza Vaclová, Guillermo Pita, Rosario Alonso, Paolo Peterlongo, Ignacio Blanco, Miguel de La Hoya, Mercedes Duran, Orland Díez, Teresa Ramón y Cajal, Irene Konstantopoulou, Cristina Martínez-Bouzas, Raquel Andrés Conejero, Penny Soucy, Lesley McGuffog, Daniel Barrowdale, Andrew Lee, Swe-Brca, Brita Arver, Johanna Rantala, Niklas Loman, Hans Ehrencrona, Olufunmilayo I. Olopade, Mary S. Beattie, Susan M. Domchek, Katherine Nathanson, Timothy R. Rebbeck, Banu K. Arun, Beth Y. Karlan, Christine Walsh, Jenny Lester, Esther M. John, Alice S. Whittemore, Mary B. Daly, Melissa Southey, John Hopper, Mary B. Terry, Saundra S. Buys, Ramunas Janavicius, Cecilia M. Dorfling, Elizabeth J. van Rensburg, Linda Steele, Susan L. Neuhausen, Yuan Chun Ding, Thomas v. O. Hansen, Lars Jønson, Bent Ejlertsen, Anne-Marie Gerdes, Mar Infante, Belén Herráez, Leticia Thais Moreno, Jeffrey N. Weitzel, Josef Herzog, Kisa Weeman, Siranoush Manoukian, Bernard Peissel, Daniela Zaffaroni, Giulietta Scuvera, Bernardo Bonanni, Frederique Mariette, Sara Volorio, Alessandra Viel, Liliana Varesco, Laura Papi, Laura Ottini, Maria Grazia Tibiletti, Paolo Radice, Drakoulis Yannoukakos, Judy Garber, Steve Ellis, Debra Frost, Radka Platte, Elena Fineberg, Gareth Evans, Fiona Lalloo, Louise Izatt, Ros Eeles, Julian Adlard, Rosemarie Davidson, Trevor Cole, Diana Eccles, Jackie Cook, Shirley Hodgson, Carole Brewer, Marc Tischkowitz, Fiona Douglas, Mary Porteous, Lucy Side, Lisa Walker, Patrick Morrison, Alan Donaldson, John Kennedy, Claire Foo, Andrew K. Godwin, Rita Katharina Schmutzler, Barbara Wappenschmidt, Kerstin Rhiem, Christoph Engel, Alfons Meindl, Nina Ditsch, Norbert Arnold, Hans Jörg Plendl, Dieter Niederacher, Christian Sutter, Shan Wang-Gohrke, Doris Steinemann, Sabine Preisler-Adams, Karin Kast, Raymonda Varon-Mateeva, Andrea Gehrig, Dominique Stoppa-Lyonnet, Olga M. Sinilnikova, Sylvie Mazoyer, Francesca Damiola, Bruce Poppe, Kathleen Claes, Marion Piedmonte, Kathy Tucker, Floor Backes, Gustavo Rodríguez, Wendy Brewster, Katie Wakeley, Thomas Rutherford, Trinidad Caldés, Heli Nevanlinna, Kristiina Aittomäki, Matti A. Rookus, Theo A. M. van Os, Lizet van der Kolk, J. L. de Lange, Hanne E. J. Meijers-Heijboer, A. H. van der Hout, Christi J. van Asperen, Encarna B. Gómez Garcia, Nicoline Hoogerbrugge, J. Margriet Collée, Carolien H. M. van Deurzen, Rob B. van der Luijt, Peter Devilee, Hebon, Edith Olah, Conxi Lázaro, Alex Teulé, Mireia Menéndez, Anna Jakubowska, Cezary Cybulski, Jacek Gronwald, Jan Lubinski, Katarzyna Durda, Katarzyna Jaworska-Bieniek, Oskar Th Johannsson, Christine Maugard, Marco Montagna, Silvia Tognazzo, Manuel R. Teixeira, Sue Healey, Kconfab Investigators, Curtis Olswold, Lucia Guidugli, Noralane Lindor, Susan Slager, Csilla I. Szabo, Joseph Vijai, Mark Robson, Noah Kauff, Liying Zhang, Rohini Rau-Murthy, Anneliese Fink-Retter, Christian F. Singer, Christine Rappaport, Daphne Geschwantler Kaulich, Georg Pfeiler, Muy-Kheng Tea, Andreas Berger, Catherine M. Phelan, Mark H. Greene, Phuong L. Mai, Flavio Lejbkowicz, Irene Andrulis, Anna Marie Mulligan, Gord Glendon, Amanda Ewart Toland, Anders Bojesen, Inge Sokilde Pedersen, Lone Sunde, Mads Thomassen, Torben A. Kruse, Uffe Birk Jensen, Eitan Friedman, Yael Laitman, Shani Paluch Shimon, Jacques Simard, Douglas F. Easton, Kenneth Offit, Fergus J. Couch, Georgia Chenevix-Trench, Antonis C. Antoniou, Javier Benitez

Date Published: 3rd Apr 2014

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Impact of compliance with infection management guidelines on outcome in patients with severe sepsis: a prospective observational multi-center study.
SepNet - German Competence Network Sepsis

Abstract (Expand)

INTRODUCTION: Current sepsis guidelines recommend antimicrobial treatment (AT) within one hour after onset of sepsis-related organ dysfunction (OD) and surgical source control within 12 hours. The … objective of this study was to explore the association between initial infection management according to sepsis treatment recommendations and patient outcome. METHODS: In a prospective observational multi-center cohort study in 44 German ICUs, we studied 1,011 patients with severe sepsis or septic shock regarding times to AT, source control, and adequacy of AT. Primary outcome was 28-day mortality. RESULTS: Median time to AT was 2.1 (IQR 0.8 - 6.0) hours and 3 hours (-0.1 - 13.7) to surgical source control. Only 370 (36.6%) patients received AT within one hour after OD in compliance with recommendation. Among 422 patients receiving surgical or interventional source control, those who received source control later than 6 hours after onset of OD had a significantly higher 28-day mortality than patients with earlier source control (42.9% versus 26.7%, P <0.001). Time to AT was significantly longer in ICU and hospital non-survivors; no linear relationship was found between time to AT and 28-day mortality. Regardless of timing, 28-day mortality rate was lower in patients with adequate than non-adequate AT (30.3% versus 40.9%, P < 0.001). CONCLUSIONS: A delay in source control beyond 6 hours may have a major impact on patient mortality. Adequate AT is associated with improved patient outcome but compliance with guideline recommendation requires improvement. There was only indirect evidence about the impact of timing of AT on sepsis mortality.

Authors: F. Bloos, D. Thomas-Ruddel, H. Ruddel, C. Engel, D. Schwarzkopf, J. C. Marshall, S. Harbarth, P. Simon, R. Riessen, D. Keh, K. Dey, M. Weiss, S. Toussaint, D. Schadler, A. Weyland, M. Ragaller, K. Schwarzkopf, J. Eiche, G. Kuhnle, H. Hoyer, C. Hartog, U. Kaisers, K. Reinhart

Date Published: 3rd Mar 2014

Publication Type: Not specified

Human Diseases: bacterial infectious disease

Fine-scale mapping of the FGFR2 breast cancer risk locus: putative functional variants differentially bind FOXA1 and E2F1
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in … case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ER\textgreeka to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease.

Authors: Kerstin B. Meyer, Martin O’Reilly, Kyriaki Michailidou, Saskia Carlebur, Stacey L. Edwards, Juliet D. French, Radhika Prathalingham, Joe Dennis, Manjeet K. Bolla, Qin Wang, Ines de Santiago, John L. Hopper, Helen Tsimiklis, Carmel Apicella, Melissa C. Southey, Marjanka K. Schmidt, Annegien Broeks, Laura J. van ’t Veer, Frans B. Hogervorst, Kenneth Muir, Artitaya Lophatananon, Sarah Stewart-Brown, Pornthep Siriwanarangsan, Peter A. Fasching, Michael P. Lux, Arif B. Ekici, Matthias W. Beckmann, Julian Peto, Isabel Dos Santos Silva, Olivia Fletcher, Nichola Johnson, Elinor J. Sawyer, Ian Tomlinson, Michael J. Kerin, Nicola Miller, Federick Marme, Andreas Schneeweiss, Christof Sohn, Barbara Burwinkel, Pascal Guénel, Thérèse Truong, Pierre Laurent-Puig, Florence Menegaux, Stig E. Bojesen, Børge G. Nordestgaard, Sune F. Nielsen, Henrik Flyger, Roger L. Milne, M. Pilar Zamora, Jose I. Arias, Javier Benitez, Susan Neuhausen, Hoda Anton-Culver, Argyrios Ziogas, Christina C. Dur, Hermann Brenner, Heiko Müller, Volker Arndt, Christa Stegmaier, Alfons Meindl, Rita K. Schmutzler, Christoph Engel, Nina Ditsch, Hiltrud Brauch, Thomas Brüning, Yon-Dschun Ko, Heli Nevanlinna, Taru A. Muranen, Kristiina Aittomäki, Carl Blomqvist, Keitaro Matsuo, Hidemi Ito, Hiroji Iwata, Yasushi Yatabe, Thilo Dörk, Sonja Helbig, Natalia V. Bogdanova, Annika Lindblom, Sara Margolin, Arto Mannermaa, Vesa Kataja, Veli-Matti Kosma, Jaana M. Hartikainen, Georgia Chenevix-Trench, Anna H. Wu, Chiu-Chen Tseng, David van den Berg, Daniel O. Stram, Diether Lambrechts, Bernard Thienpont, Marie-Rose Christiaens, Ann Smeets, Jenny Chang-Claude, Anja Rudolph, Petra Seibold, Dieter Flesch-Janys, Paolo Radice, Paolo Peterlongo, Bernardo Bonanni, Loris Bernard, Fergus J. Couch, Janet E. Olson, Xianshu Wang, Kristen Purrington, Graham G. Giles, Gianluca Severi, Laura Baglietto, Catriona McLean, Christopher A. Haiman, Brian E. Henderson, Fredrick Schumacher, Loic Le Marchand, Jacques Simard, Mark S. Goldberg, France Labrèche, Martine Dumont, Soo-Hwang Teo, Cheng-Har Yip, Sze-Yee Phuah, Vessela Kristensen, Grethe Grenaker Alnæs, Anne-Lise Børresen-Dale, Wei Zheng, Sandra Deming-Halverson, Martha Shrubsole, Jirong Long, Robert Winqvist, Katri Pylkäs, Arja Jukkola-Vuorinen, Saila Kauppila, Irene L. Andrulis, Julia A. Knight, Gord Glendon, Sandrine Tchatchou, Peter Devilee, Robert A. E. M. Tollenaar, Caroline M. Seynaeve, Montserrat García-Closas, Jonine Figueroa, Stephen J. Chanock, Jolanta Lissowska, Kamila Czene, Hartef Darabi, Kimael Eriksson, Maartje J. Hooning, John W. M. Martens, Ans M. W. van den Ouweland, Carolien H. M. van Deurzen, Per Hall, Jingmei Li, Jianjun Liu, Keith Humphreys, Xiao-Ou Shu, Wei Lu, Yu-Tang Gao, Hui Cai, Angela Cox, Malcolm W. R. Reed, William Blot, Lisa B. Signorello, Qiuyin Cai, Paul D. P. Pharoah, Maya Ghoussaini, Patricia Harrington, Jonathan Tyrer, Daehee Kang, Ji-Yeob Choi, Sue K. Park, Dong-Young Noh, Mikael Hartman, Miao Hui, Wei-Yen Lim, Shaik A. Buhari, Ute Hamann, Asta Försti, Thomas Rüdiger, Hans-Ulrich Ulmer, Anna Jakubowska, Jan Lubinski, Katarzyna Jaworska, Katarzyna Durda, Suleeporn Sangrajrang, Valerie Gaborieau, Paul Brennan, James McKay, Celine Vachon, Susan Slager, Florentia Fostira, Robert Pilarski, Chen-Yang Shen, Chia-Ni Hsiung, Pei-Ei Wu, Ming-Feng Hou, Anthony Swerdlow, Alan Ashworth, Nick Orr, Minouk J. Schoemaker, Bruce A. J. Ponder, Alison M. Dunning, Douglas F. Easton

Date Published: 1st Dec 2013

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

A biomathematical model of human erythropoiesis under erythropoietin and chemotherapy administration.
HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia

Abstract (Expand)

Anaemia is a common haematologic side effect of dose-dense multi-cycle cytotoxic polychemotherapy requiring erythrocyte transfusions or erythropoietin (EPO) administration. To simulate the effectiveness … of different EPO application schedules, we performed both modelling of erythropoiesis under chemotherapy and pharmacokinetic and dynamic modelling of EPO applications in the framework of a single comprehensive biomathematical model. For this purpose, a cell kinetic model of bone marrow erythropoiesis was developed that is based on a set of differential compartment equations describing proliferation and maturation of erythropoietic cell stages. The system is regulated by several feedback loops comprising those mediated by EPO. We added a model of EPO absorption after injection at different sites and a pharmacokinetic model of EPO derivatives to account for the effects of external EPO applications. Chemotherapy is modelled by a transient depletion of bone marrow cell stages. Unknown model parameters were determined by fitting the predictions of the model to data sets of circulating erythrocytes, haemoglobin, haematocrit, percentage of reticulocytes or EPO serum concentrations derived from the literature or cooperating clinical study groups. Parameter fittings resulted in a good agreement of model and data. Depending on site of injection and derivative (Alfa, Beta, Delta, Darbepoetin), nine groups of EPO applications were distinguished differing in either absorption kinetics or pharmacokinetics. Finally, eight different chemotherapy protocols were modelled. The model was validated on the basis of scenarios not used for parameter fitting. Simulations were performed to analyze the impact of EPO applications on the risk of anaemia during chemotherapy. We conclude that we established a model of erythropoiesis under chemotherapy that explains a large set of time series data under EPO and chemotherapy applications. It allows predictions regarding yet untested EPO schedules. Prospective clinical studies are needed to validate model predictions and to explore the feasibility and effectiveness of the proposed schedules.

Authors: S. Schirm, C. Engel, M. Loeffler, M. Scholz

Date Published: 12th Jun 2013

Publication Type: Not specified

Human Diseases: anemia

Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predicting BRCA1/2 mutation carrier probabilities: a study based on 7352 families from the German Hereditary Breast and Ovarian Cancer Consortium.
GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer

Abstract (Expand)

BACKGROUND: Risk prediction models are widely used in clinical genetic counselling. Despite their frequent use, the genetic risk models BOADICEA, BRCAPRO, IBIS and extended Claus model (eCLAUS), used … to estimate BRCA1/2 mutation carrier probabilities, have never been comparatively evaluated in a large sample from central Europe. Additionally, a novel version of BOADICEA that incorporates tumour pathology information has not yet been validated. PATIENTS AND METHODS: Using data from 7352 German families we estimated BRCA1/2 carrier probabilities under each model and compared their discrimination and calibration. The incremental value of using pathology information in BOADICEA was assessed in a subsample of 4928 pedigrees with available data on breast tumour molecular markers oestrogen receptor, progesterone receptor and human epidermal growth factor 2. RESULTS: BRCAPRO (area under receiver operating characteristic curve (AUC)=0.80 (95% CI 0.78 to 0.81)) and BOADICEA (AUC=0.79 (0.78-0.80)), had significantly higher diagnostic accuracy than IBIS and eCLAUS (p<0.001). The AUC increased when pathology information was used in BOADICEA: AUC=0.81 (95% CI 0.80 to 0.83, p<0.001). At carrier thresholds of 10% and 15%, the net reclassification index was +3.9% and +5.4%, respectively, when pathology was included in the model. Overall, calibration was best for BOADICEA and worst for eCLAUS. With eCLAUS, twice as many mutation carriers were predicted than observed. CONCLUSIONS: Our results support the use of BRCAPRO and BOADICEA for decision making regarding genetic testing for BRCA1/2 mutations. However, model calibration has to be improved for this population. eCLAUS should not be used for estimating mutation carrier probabilities in clinical settings. Whenever possible, breast tumour molecular marker information should be taken into account.

Authors: C. Fischer, K. Kuchenbacker, C. Engel, S. Zachariae, K. Rhiem, A. Meindl, N. Rahner, N. Dikow, H. Plendl, I. Debatin, T. Grimm, D. Gadzicki, R. Flottmann, J. Horvath, E. Schrock, F. Stock, D. Schafer, I. Schwaab, C. Kartsonaki, N. Mavaddat, B. Schlegelberger, A. C. Antoniou, R. Schmutzler

Date Published: 9th Apr 2013

Publication Type: Not specified

Human Diseases: hereditary breast ovarian cancer syndrome

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