Publications

468 Publications visible to you, out of a total of 468

Abstract (Expand)

As revealed by optical coherence tomography (OCT), the shape of the fovea may vary greatly among individuals. However, none of the hitherto available mathematical descriptions comprehensively reproduces all individual characteristics such as foveal depth, slope, naso-temporal asymmetry, and others. Here, a novel mathematical approach is presented to obtain a very accurate model of the complete 3D foveal surface of an individual, by utilizing recent developments in OCT. For this purpose, a new formula was developed serving as a simple but very flexible way to represent a given fovea. An extensive description of the used model parameters, as well as, of the complete method of reconstructing a foveal surface from OCT data, is presented. Noteworthy, the formula analytically provides characteristic foveal parameters and thus allows for extensive quantification. The present approach was verified on 432 OCT scans and has proved to be able to capture the whole range of asymmetric foveal shapes with high accuracy (i.e. a mean fit error of 1.40 mum).

Authors: P. Scheibe, A. Lazareva, U. D. Braumann, A. Reichenbach, P. Wiedemann, M. Francke, F. G. Rauscher

Date Published: 3rd Dec 2013

Publication Type: Not specified

Human Diseases: eye disease

Abstract (Expand)

We present an analytic framework based on Self-Organizing Map (SOM) machine learning to study large scale patient data sets. The potency of the approach is demonstrated in a case study using gene expression data of more than 200 mature aggressive B-cell lymphoma patients. The method portrays each sample with individual resolution, characterizes the subtypes, disentangles the expression patterns into distinct modules, extracts their functional context using enrichment techniques and enables investigation of the similarity relations between the samples. The method also allows to detect and to correct outliers caused by contaminations. Based on our analysis, we propose a refined classification of B-cell Lymphoma into four molecular subtypes which are characterized by differential functional and clinical characteristics.

Authors: L. Hopp, K. Lembcke, H. Binder, H. Wirth

Date Published: 2nd Dec 2013

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma, B-cell lymphoma

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

Abstract (Expand)

The systematic analysis of miRNA expression and its potential mRNA targets constitutes a basal objective in miRNA research in addition to miRNA gene detection and miRNA target prediction. In this chapter we address methodical issues of miRNA expression analysis using self-organizing maps (SOM), a neural network machine learning algorithm with strong visualization and second-level analysis capabilities widely used to categorize large-scale, high-dimensional data. We shortly review selected experimental and theoretical aspects of miRNA expression analysis. Then, the protocol of our SOM method is outlined with special emphasis on miRNA/mRNA coexpression. The method allows extracting differentially expressed RNA transcripts, their functional context, and also characterization of global properties of expression states and profiles. In addition to the separate study of miRNA and mRNA expression landscapes, we propose the combined analysis of both entities using a covariance SOM.

Authors: H. Wirth, M. V. Cakir, L. Hopp, H. Binder

Date Published: 26th Nov 2013

Publication Type: Not specified

Abstract (Expand)

Based on the assumption that molecular mechanisms involved in cancerogenesis are characterized by groups of coordinately expressed genes, we developed and validated a novel method for analyzing transcriptional data called Correlated Gene Set Analysis (CGSA). Using 50 extracted gene sets we identified three different profiles of tumors in a cohort of 364 Diffuse large B-cell (DLBCL) and related mature aggressive B-cell lymphomas other than Burkitt lymphoma. The first profile had high level of expression of genes related to proliferation whereas the second profile exhibited a stromal and immune response phenotype. These two profiles were characterized by a large scale gene activation affecting genes which were recently shown to be epigenetically regulated, and which were enriched in oxidative phosphorylation, energy metabolism and nucleoside biosynthesis. The third and novel profile showed only low global gene activation similar to that found in normal B cells but not cell lines. Our study indicates novel levels of complexity of DLBCL with low or high large scale gene activation related to metabolism and biosynthesis and, within the group of highly activated DLBCLs, differential behavior leading to either a proliferative or a stromal and immune response phenotype.

Authors: M. Rosolowski, J. Lauter, D. Abramov, H. G. Drexler, M. Hummel, W. Klapper, R. A. Macleod, S. Pellissery, F. Horn, R. Siebert, M. Loeffler

Date Published: 14th Nov 2013

Publication Type: Not specified

Human Diseases: diffuse large B-cell lymphoma

Abstract (Expand)

PURPOSE: To study clinical presentation, outcome, and the role of radiotherapy in patients with aggressive B-cell lymphoma and skeletal involvement treated with and without rituximab. PATIENTS AND METHODS: Outcome of patients with skeletal involvement was analyzed in a retrospective study of nine consecutive prospective trials of the German High-Grade Non-Hodgkin lymphoma Study Group. RESULTS: Of 3,840 patients, 292 (7.6%) had skeletal involvement. In the MabThera International Trial (MInT) for young good-prognosis patients and the Rituximab With CHOP Over 60 Years (RICOVER-60) study for elderly patients, the randomized addition of rituximab improved event-free survival (EFS; hazard ratio for MInT [HRMInT] = 0.4, P > 001; hazard ratio for RICOVER-60 [HRRICOVER-60] = 0.6, P > .001) and overall survival (OS; HRMInT = 0.4, P < .001; HRRICOVER-60 = 0.7, P = .002) in patients without skeletal involvement, but failed to improve the outcome of patients with skeletal involvement (EFS: HRMInT = 1.4, P = .444; HRRICOVER-60 = 0.8, P = .449; OS: HRMInT = 0.6, P = .449; HRRICOVER-60 = 1.0, P = .935). Skeletal involvement was associated with a worse outcome after cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) plus rituximab (HREFS = 1.5, P = .048; HROS = 1.1; P = .828), but not after CHOP without rituximab (HREFS = 0.8, P = .181; HROS = 0.7, P = .083). In contrast to rituximab, additive radiotherapy to sites of skeletal involvement was associated with a decreased risk (HREFS = 0.3, P = .001; HROS = 0.5; P = .111). CONCLUSION: Rituximab failed to improve the outcome of patients with diffuse large B-cell lymphoma with skeletal involvement, although our data suggest a beneficial effect of radiotherapy to sites of skeletal involvement. Whether radiotherapy to sites of skeletal involvement can be spared in cases with a negative positron emission tomography after immunochemotherapy should be addressed in appropriately designed prospective trials.

Authors: G. Held, S. Zeynalova, N. Murawski, M. Ziepert, B. Kempf, A. Viardot, M. Dreyling, M. Hallek, M. Witzens-Harig, J. Fleckenstein, C. Rube, C. Zwick, B. Glass, N. Schmitz, M. Pfreundschuh

Date Published: 10th Nov 2013

Publication Type: Not specified

Human Diseases: B-cell lymphoma

Abstract (Expand)

Introduction LIFE is a large epidemiological study aiming at causes of common civilization diseases including adiposity, dementia, and depression. Participants of the study are probands and patients. Probands are randomly selected and invited from the set of Leipzig (Germany) inhabitants while patients with known diseases are recruited from several local hospitals. The management of these participants, their invitation and contact after successful attendance as well as the support of nearly all ambulance processes requires a complex ambulance management. Each participant is examined by a set of investigation instruments including interviews, questionnaires, device-specific investigations, specimen extrac- tions and analyses. This necessitates a complex management of the participantspecific examination program but also specific input forms and systems allowing to capture administrative (measurement and process environment or specific set-ups) and scientific data. Additionally, the taken and prepared specimens need to be labeled and registered from which participant they stem and in which fridge or bio-tank they are stored. At the end, all captured data from ambu- lance management, investigation instruments and laboratory analyses need to be integrated before they can be analyzed. These complex processes and requirements necessitate a comprehensive IT-infrastructure. Methods Our IT-infrastructure modularly consists of several software applications. A main application is responsible for the complex participant and ambulance man- agement. The participant management cope with selected participant data and contact information. To protect participant’s privacy, a participant identifier (PID) is created for each participant that is associated to all data which is managed and captured in the following. In ambulance management, each participant is associated with a predefined investigation program. This investigation program is represented in our systems by a tracking card that is available as print-out and electronically. The electronic version of tracking cards is utilized by two software applications, the Assessment Battery and the CryoLab. The former system coordinates the input of scientific data into online input forms. The input forms are designed in the open source system LimeSurvey. Moreover, the Assessment Battery is used to monitor the input process, i.e., it shows which investigations are already completed and which of them are still to do. The Cryolab system registers and tracks all taken specimens and is used to annotate extraction and specific preparation processes, e.g., for DNA isolation. Moreover, it tracks specimen storage in fridges and bio-tanks. A central component is the metadata repository collecting metadata from ambulance management and data input systems. It is the base for the integra- tion of relevant scientific data into a central research database. The integration follows a mapping-based approach. The research database makes raw data and special pre-computations called derivatives available for later data analysis. Results & Discussion We designed and implemented a complex and comprehensive IT-infrastructure for the epidemiological research in LIFE. This infrastructure consists of several software applications which are loosely coupled over specified interfaces. Most of the software applications are new implementations; only for capturing scientific data external software application are applied.

Authors: Toralf Kirsten, A. Kiel, M. Kleinert, R. Speer, M. Rühle, Hans Binder, Markus Löffler

Date Published: 30th Sep 2013

Publication Type: Not specified

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