Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Benedikt Brors is active.

Publication


Featured researches published by Benedikt Brors.


Nature | 2012

Dissecting the genomic complexity underlying medulloblastoma

David T. W. Jones; Natalie Jäger; Marcel Kool; Thomas Zichner; Barbara Hutter; Marc Sultan; Yoon-Jae Cho; Trevor J. Pugh; Volker Hovestadt; Adrian M. Stütz; Tobias Rausch; Hans-Jörg Warnatz; Marina Ryzhova; Sebastian Bender; Dominik Sturm; Sabrina Pleier; Huriye Cin; Elke Pfaff; Laura Sieber; Andrea Wittmann; Marc Remke; Hendrik Witt; Sonja Hutter; Theophilos Tzaridis; Joachim Weischenfeldt; Benjamin Raeder; Meryem Avci; Vyacheslav Amstislavskiy; Marc Zapatka; Ursula Weber

Medulloblastoma is an aggressively growing tumour, arising in the cerebellum or medulla/brain stem. It is the most common malignant brain tumour in children, and shows tremendous biological and clinical heterogeneity. Despite recent treatment advances, approximately 40% of children experience tumour recurrence, and 30% will die from their disease. Those who survive often have a significantly reduced quality of life. Four tumour subgroups with distinct clinical, biological and genetic profiles are currently identified. WNT tumours, showing activated wingless pathway signalling, carry a favourable prognosis under current treatment regimens. SHH tumours show hedgehog pathway activation, and have an intermediate prognosis. Group 3 and 4 tumours are molecularly less well characterized, and also present the greatest clinical challenges. The full repertoire of genetic events driving this distinction, however, remains unclear. Here we describe an integrative deep-sequencing analysis of 125 tumour–normal pairs, conducted as part of the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. Tetraploidy was identified as a frequent early event in Group 3 and 4 tumours, and a positive correlation between patient age and mutation rate was observed. Several recurrent mutations were identified, both in known medulloblastoma-related genes (CTNNB1, PTCH1, MLL2, SMARCA4) and in genes not previously linked to this tumour (DDX3X, CTDNEP1, KDM6A, TBR1), often in subgroup-specific patterns. RNA sequencing confirmed these alterations, and revealed the expression of what are, to our knowledge, the first medulloblastoma fusion genes identified. Chromatin modifiers were frequently altered across all subgroups. These findings enhance our understanding of the genomic complexity and heterogeneity underlying medulloblastoma, and provide several potential targets for new therapeutics, especially for Group 3 and 4 patients.


Journal of Experimental Medicine | 2005

Promiscuous gene expression in thymic epithelial cells is regulated at multiple levels

Jens Derbinski; Jana Gäbler; Benedikt Brors; Sascha Tierling; Sunitha Jonnakuty; Manfred Hergenhahn; Leena Peltonen; Jörn Walter; Bruno Kyewski

The role of central tolerance induction has recently been revised after the discovery of promiscuous expression of tissue-restricted self-antigens in the thymus. The extent of tissue representation afforded by this mechanism and its cellular and molecular regulation are barely defined. Here we show that medullary thymic epithelial cells (mTECs) are specialized to express a highly diverse set of genes representing essentially all tissues of the body. Most, but not all, of these genes are induced in functionally mature CD80hi mTECs. Although the autoimmune regulator (Aire) is responsible for inducing a large portion of this gene pool, numerous tissue-restricted genes are also up-regulated in mature mTECs in the absence of Aire. Promiscuously expressed genes tend to colocalize in clusters in the genome. Analysis of a particular gene locus revealed expression of clustered genes to be contiguous within such a cluster and to encompass both Aire-dependent and –independent genes. A role for epigenetic regulation is furthermore implied by the selective loss of imprinting of the insulin-like growth factor 2 gene in mTECs. Our data document a remarkable cellular and molecular specialization of the thymic stroma in order to mimic the transcriptome of multiple peripheral tissues and, thus, maximize the scope of central self-tolerance.


Nature Genetics | 2013

Recurrent somatic alterations of FGFR1 and NTRK2 in pilocytic astrocytoma

David T. W. Jones; Barbara Hutter; Natalie Jäger; Andrey Korshunov; Marcel Kool; Hans-Jörg Warnatz; Thomas Zichner; Sally R. Lambert; Marina Ryzhova; Dong Anh Khuong Quang; Adam M. Fontebasso; Adrian M. Stütz; Sonja Hutter; Marc Zuckermann; Dominik Sturm; Jan Gronych; Bärbel Lasitschka; Sabine Schmidt; Huriye Şeker-Cin; Hendrik Witt; Marc Sultan; Meryem Ralser; Paul A. Northcott; Volker Hovestadt; Sebastian Bender; Elke Pfaff; Sebastian Stark; Damien Faury; Jeremy Schwartzentruber; Jacek Majewski

Pilocytic astrocytoma, the most common childhood brain tumor, is typically associated with mitogen-activated protein kinase (MAPK) pathway alterations. Surgically inaccessible midline tumors are therapeutically challenging, showing sustained tendency for progression and often becoming a chronic disease with substantial morbidities. Here we describe whole-genome sequencing of 96 pilocytic astrocytomas, with matched RNA sequencing (n = 73), conducted by the International Cancer Genome Consortium (ICGC) PedBrain Tumor Project. We identified recurrent activating mutations in FGFR1 and PTPN11 and new NTRK2 fusion genes in non-cerebellar tumors. New BRAF-activating changes were also observed. MAPK pathway alterations affected all tumors analyzed, with no other significant mutations identified, indicating that pilocytic astrocytoma is predominantly a single-pathway disease. Notably, we identified the same FGFR1 mutations in a subset of H3F3A-mutated pediatric glioblastoma with additional alterations in the NF1 gene. Our findings thus identify new potential therapeutic targets in distinct subsets of pilocytic astrocytoma and childhood glioblastoma.


Journal of Experimental Medicine | 2004

Medullary Epithelial Cells of the Human Thymus Express a Highly Diverse Selection of Tissue-specific Genes Colocalized in Chromosomal Clusters

Jörn Gotter; Benedikt Brors; Manfred Hergenhahn; Bruno Kyewski

Promiscuous expression of tissue-specific self-antigens in the thymus imposes T cell tolerance and protects from autoimmune diseases, as shown in animal studies. Analysis of promiscuous gene expression in purified stromal cells of the human thymus at the single and global gene level documents the species conservation of this phenomenon. Medullary thymic epithelial cells overexpress a highly diverse set of genes (>400) including many tissue-specific antigens, disease-associated autoantigens, and cancer-germline genes. Although there are no apparent structural or functional commonalities among these genes and their products, they cluster along chromosomes. These findings have implications for human autoimmune diseases, immuno-therapy of tumors, and the understanding of the nature of this unorthodox regulation of gene expression.


Proceedings of the National Academy of Sciences of the United States of America | 2001

Correspondence analysis applied to microarray data.

Kurt Fellenberg; Nicole Hauser; Benedikt Brors; Albert Neutzner; Jörg D. Hoheisel; Martin Vingron

Correspondence analysis is an explorative computational method for the study of associations between variables. Much like principal component analysis, it displays a low-dimensional projection of the data, e.g., into a plane. It does this, though, for two variables simultaneously, thus revealing associations between them. Here, we demonstrate the applicability of correspondence analysis to and high value for the analysis of microarray data, displaying associations between genes and experiments. To introduce the method, we show its application to the well-known Saccharomyces cerevisiae cell-cycle synchronization data by Spellman et al. [Spellman, P. T., Sherlock, G., Zhang, M. Q., Iyer, V. R., Anders, K., Eisen, M. B., Brown, P. O., Botstein, D. & Futcher, B. (1998) Mol. Biol. Cell 9, 3273–3297], allowing for comparison with their visualization of this data set. Furthermore, we apply correspondence analysis to a non-time-series data set of our own, thus supporting its general applicability to microarray data of different complexity, underlying structure, and experimental strategy (both two-channel fluorescence-tag and radioactive labeling).


Proceedings of the National Academy of Sciences of the United States of America | 2002

Acute myeloid leukemias with reciprocal rearrangements can be distinguished by specific gene expression profiles

Claudia Schoch; Alexander Kohlmann; Susanne Schnittger; Benedikt Brors; Martin Dugas; Susanne Mergenthaler; Wolfgang Kern; Wolfgang Hiddemann; Roland Eils; Torsten Haferlach

Acute myeloid leukemia (AML) is a heterogeneous group of genetically defined diseases. Their classification is important with regard to prognosis and treatment. We performed microarray analyses for gene expression profiling on bone marrow samples of 37 patients with newly diagnosed AML. All cases had either of the distinct subtypes AML M2 with t(8;21), AML M3 or M3v with t(15;17), or AML M4eo with inv(16). Diagnosis was established by cytomorphology, cytogenetics, fluorescence in situ hybridization, and reverse transcriptase–PCR in every sample. By using two different strategies for microarray data analyses, this study revealed a unique correlation between AML-specific cytogenetic aberrations and gene expression profiles.


Journal of Clinical Oncology | 2006

Customized Oligonucleotide Microarray Gene Expression–Based Classification of Neuroblastoma Patients Outperforms Current Clinical Risk Stratification

André Oberthuer; Frank Berthold; Patrick Warnat; Barbara Hero; Yvonne Kahlert; Rüdiger Spitz; Karen Ernestus; Rainer König; Stefan A. Haas; Roland Eils; Manfred Schwab; Benedikt Brors; Frank Westermann; Matthias Fischer

PURPOSE To develop a gene expression-based classifier for neuroblastoma patients that reliably predicts courses of the disease. PATIENTS AND METHODS Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses (n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifiers predictive power was evaluated in an independent second set (n = 174) by comparing results of the gene expression-based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. RESULTS The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [favorable; n = 115] v 0.52 +/- 0.07 [unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P < .0001) and separated risk groups of current neuroblastoma trials into subgroups with divergent outcome (NB2004: low-risk 3-year EFS 0.86 +/- 0.04 v 0.25 +/- 0.15, P < .0001; intermediate-risk 1.00 v 0.57 +/- 0.19, P = .018; high-risk 0.81 +/- 0.10 v 0.56 +/- 0.08, P = .06). In a multivariate Cox regression model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States (P < .001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). CONCLUSION Integration of gene expression-based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.


Nature Genetics | 2012

Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing

Julia Richter; Matthias Schlesner; Steve Hoffmann; Markus Kreuz; Ellen Leich; Birgit Burkhardt; Maciej Rosolowski; Ole Ammerpohl; Rabea Wagener; Stephan H. Bernhart; Dido Lenze; Monika Szczepanowski; Maren Paulsen; Simone Lipinski; Robert B. Russell; Sabine Adam-Klages; Gordana Apic; Alexander Claviez; Dirk Hasenclever; Volker Hovestadt; Nadine Hornig; Jan O. Korbel; Dieter Kube; David Langenberger; Chris Lawerenz; Jasmin Lisfeld; Katharina Meyer; Simone Picelli; Jordan Pischimarov; Bernhard Radlwimmer

Burkitt lymphoma is a mature aggressive B-cell lymphoma derived from germinal center B cells. Its cytogenetic hallmark is the Burkitt translocation t(8;14)(q24;q32) and its variants, which juxtapose the MYC oncogene with one of the three immunoglobulin loci. Consequently, MYC is deregulated, resulting in massive perturbation of gene expression. Nevertheless, MYC deregulation alone seems not to be sufficient to drive Burkitt lymphomagenesis. By whole-genome, whole-exome and transcriptome sequencing of four prototypical Burkitt lymphomas with immunoglobulin gene (IG)-MYC translocation, we identified seven recurrently mutated genes. One of these genes, ID3, mapped to a region of focal homozygous loss in Burkitt lymphoma. In an extended cohort, 36 of 53 molecularly defined Burkitt lymphomas (68%) carried potentially damaging mutations of ID3. These were strongly enriched at somatic hypermutation motifs. Only 6 of 47 other B-cell lymphomas with the IG-MYC translocation (13%) carried ID3 mutations. These findings suggest that cooperation between ID3 inactivation and IG-MYC translocation is a hallmark of Burkitt lymphomagenesis.


BMC Bioinformatics | 2005

Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

Patrick Warnat; Roland Eils; Benedikt Brors

BackgroundThe extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods.ResultsIn contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85%) were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis.ConclusionCross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and microarray technologies. Predictive models generated by this approach are better validated than those generated on a single data set, while showing high predictive power and improved generalization performance.


Nature | 2014

Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing

Volker Hovestadt; David T. W. Jones; Simone Picelli; Wei Wang; Marcel Kool; Paul A. Northcott; Marc Sultan; Katharina Stachurski; Marina Ryzhova; Hans Jörg Warnatz; Meryem Ralser; Sonja Brun; Jens Bunt; Natalie Jäger; Kortine Kleinheinz; Serap Erkek; Ursula Weber; Cynthia C. Bartholomae; Christof von Kalle; Chris Lawerenz; Jürgen Eils; Jan Koster; Rogier Versteeg; Till Milde; Olaf Witt; Sabine Schmidt; Stephan Wolf; Torsten Pietsch; Stefan Rutkowski; Wolfram Scheurlen

Epigenetic alterations, that is, disruption of DNA methylation and chromatin architecture, are now acknowledged as a universal feature of tumorigenesis. Medulloblastoma, a clinically challenging, malignant childhood brain tumour, is no exception. Despite much progress from recent genomics studies, with recurrent changes identified in each of the four distinct tumour subgroups (WNT-pathway-activated, SHH-pathway-activated, and the less-well-characterized Group 3 and Group 4), many cases still lack an obvious genetic driver. Here we present whole-genome bisulphite-sequencing data from thirty-four human and five murine tumours plus eight human and three murine normal controls, augmented with matched whole-genome, RNA and chromatin immunoprecipitation sequencing data. This comprehensive data set allowed us to decipher several features underlying the interplay between the genome, epigenome and transcriptome, and its effects on medulloblastoma pathophysiology. Most notable were highly prevalent regions of hypomethylation correlating with increased gene expression, extending tens of kilobases downstream of transcription start sites. Focal regions of low methylation linked to transcription-factor-binding sites shed light on differential transcriptional networks between subgroups, whereas increased methylation due to re-normalization of repressed chromatin in DNA methylation valleys was positively correlated with gene expression. Large, partially methylated domains affecting up to one-third of the genome showed increased mutation rates and gene silencing in a subgroup-specific fashion. Epigenetic alterations also affected novel medulloblastoma candidate genes (for example, LIN28B), resulting in alternative promoter usage and/or differential messenger RNA/microRNA expression. Analysis of mouse medulloblastoma and precursor-cell methylation demonstrated a somatic origin for many alterations. Our data provide insights into the epigenetic regulation of transcription and genome organization in medulloblastoma pathogenesis, which are probably also of importance in a wider developmental and disease context.

Collaboration


Dive into the Benedikt Brors's collaboration.

Top Co-Authors

Avatar

Roland Eils

German Cancer Research Center

View shared research outputs
Top Co-Authors

Avatar

Barbara Hutter

German Cancer Research Center

View shared research outputs
Top Co-Authors

Avatar

Marc Zapatka

German Cancer Research Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Roland Eils

German Cancer Research Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Hanno Glimm

German Cancer Research Center

View shared research outputs
Top Co-Authors

Avatar

Peter Lichter

German Cancer Research Center

View shared research outputs
Researchain Logo
Decentralizing Knowledge