Falk Schubert

Publications of Falk Schubert

• Breast cancer: a candidate gene approach across the estrogen metabolic pathway.

  Authors: Christina Justenhoven, Ute Hamann, Falk Schubert, Marc Zapatka, Christiane B Pierl, Sylvia Rabstein, Silvia Selinski, Tina Mueller, Katja Ickstadt, Michael Gilbert, Yon-Dschun Ko, Christian Baisch, Beate Pesch, Volker Harth, Hermann M Bolt, Caren Vollmert, Thomas Illig, Roland Eils, Jürgen Dippon, Hiltrud Brauch

  Breast cancer research and treatment. 04/2008; 108(1):137-49.

  Polymorphisms within the estrogen metabolic pathway are prime candidates for a possible association with breast cancer risk. We investigated 11 genes encoding key proteins of this pathway for theirPolymorphisms within the estrogen metabolic pathway are prime candidates for a possible association with breast cancer risk. We investigated 11 genes encoding key proteins of this pathway for their potential contribution to breast cancer risk. Of these CYP17A1, CYP19A1, EPHX1, HSD17B1, SRD5A2, and PPARG2 participate in biosynthesis, CYP1A1, CYP1B1, COMT, GSTP1, and SOD2 in catabolism and detoxification. We performed a population-based case-control study with 688 incident breast cancer cases and 724 controls from Germany and genotyped 18 polymorphisms by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR based RFLP (restriction fragment length polymorphism), and TaqMan allelic discrimination. Genotype frequencies were compared between cases and controls and odds ratios were calculated by conditional logistic regression. Further statistical analyses were based on cluster analysis, multifactor dimensionality reduction, logic regression, and global testing. Single factor analyses pointed to CYP1B1_1294_GG as a possible breast cancer risk modulator (OR = 2.57; 95% CI: 1.34-4.93) and two way stratification suggested associations between BMI > or = 30 kg/m(2) and COMT_472_GG (P = 0.0076 and P = 0.0026), BMI < 20 kg/m(2) and HSD17B1_937_GG (P = 0.0082) as well as CYP17A1_-34_CC and HRT use > or =10 years (P = 0.0063). Following correction for multiple testing none of these associations remained significant. No significant association between breast cancer risk and genetic polymorphisms was observed in multifactor analyses. The tested polymorphisms of the estrogen metabolic pathway may not play a direct role in breast cancer risk. Therefore, future association studies should be extended to other polymorphisms and other regulatory pathways.

• Systemic spread is an early step in breast cancer.

  Authors: Yves Hüsemann, Jochen B Geigl, Falk Schubert, Piero Musiani, Manfred Meyer, Elke Burghart, Guido Forni, Roland Eils, Tanja Fehm, Gert Riethmüller, Christoph A Klein

  Cancer cell. 02/2008; 13(1):58-68.

  It is widely accepted that metastasis is a late event in cancer progression. Here, however, we show that tumor cells can disseminate systemically from earliest epithelial alterations in HER-2 andIt is widely accepted that metastasis is a late event in cancer progression. Here, however, we show that tumor cells can disseminate systemically from earliest epithelial alterations in HER-2 and PyMT transgenic mice and from ductal carcinoma in situ in women. Wild-type mice transplanted with single premalignant HER-2 transgenic glands displayed disseminated tumor cells and micrometastasis in bone marrow and lungs. The number of disseminated cancer cells and their karyotypic abnormalities were similar for small and large tumors in patients and mouse models. When activated by bone marrow transplantation into wild-type recipients, 80 early-disseminated cancer cells sufficed to induce lethal carcinosis. Therefore, release from dormancy of early-disseminated cancer cells may frequently account for metachronous metastasis.

• GOPET: a tool for automated predictions of Gene Ontology terms.

  Authors: Arunachalam Vinayagam, Coral del Val, Falk Schubert, Roland Eils, Karl-Heinz Glatting, Sándor Suhai, Rainer König

  BMC bioinformatics. 02/2006; 7:161.

  BACKGROUND: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, eitherBACKGROUND: Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. DESCRIPTION: We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO). Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool). It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar CONCLUSION: Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

• High-resolution genomic profiling reveals association of chromosomal aberrations on 1q and 16p with histologic and genetic subgroups of invasive breast cancer.

  Authors: Daniel E Stange, Bernhard Radlwimmer, Falk Schubert, Frank Traub, Andreas Pich, Grischa Toedt, Frank Mendrzyk, Ulrich Lehmann, Roland Eils, Hans Kreipe, Peter Lichter

  Clinical cancer research : an official journal of the American Association for Cancer Research. 02/2006; 12(2):345-52.

  PURPOSE: Invasive ductal carcinoma and invasive lobular carcinoma (ILC) represent the major histologic subtypes of invasive breast cancer. They differ with regard to presentation, metastatic spread,PURPOSE: Invasive ductal carcinoma and invasive lobular carcinoma (ILC) represent the major histologic subtypes of invasive breast cancer. They differ with regard to presentation, metastatic spread, and epidemiologic features. To elucidate the genetic basis of these differences, we analyzed copy number imbalances that differentiate the histologic subtypes.EXPERIMENTAL DESIGN: High-resolution genomic profiling of 40 invasive breast cancers using matrix-comparative genomic hybridization with an average resolution of 0.5 Mb was conducted on bacterial artificial chromosome microarrays. The data were subjected to classification and unsupervised hierarchical cluster analyses. Expression of candidate genes was analyzed in tumor samples.RESULTS: The highest discriminating power was achieved when combining the aberration patterns of chromosome arms 1q and 16p, which were significantly more often gained in ILC. These regions were further narrowed down to subregions 1q24.2-25.1, 1q25.3-q31.3, and 16p11.2. Located within the candidate gains on 1q are two genes, FMO2 and PTGS2, known to be overexpressed in ILC relative to invasive ductal carcinoma. Assessment of four candidate genes on 16p11.2 by real-time quantitative PCR revealed significant overexpression of FUS and ITGAX in ILC with 16p copy number gain. Unsupervised hierarchical cluster analysis identified three molecular subgroups that are characterized by different aberration patterns, in particular concerning gain of MYC (8q24) and the identified candidate regions on 1q24.2-25.1, 1q25.3-q31.3, and 16p11.2. These genetic subgroups differed with regard to histology, tumor grading, frequency of alterations, and estrogen receptor expression.CONCLUSIONS: Molecular profiling using bacterial artificial chromosome arrays identified DNA copy number imbalances on 1q and 16p as significant classifiers of histologic and molecular subgroups.

• Genomic analysis of single cytokeratin-positive cells from bone marrow reveals early mutational events in breast cancer.

  Authors: Julian A Schardt, Manfred Meyer, Claudia H Hartmann, Falk Schubert, Oleg Schmidt-Kittler, Christine Fuhrmann, Bernhard Polzer, Marco Petronio, Roland Eils, Christoph A Klein

  Cancer cell. 10/2005; 8(3):227-39.

  Chromosomal instability in human breast cancer is known to take place before mammary neoplasias display morphological signs of invasion. We describe here the unexpected finding of a tumor cellChromosomal instability in human breast cancer is known to take place before mammary neoplasias display morphological signs of invasion. We describe here the unexpected finding of a tumor cell population with normal karyotypes isolated from bone marrow of breast cancer patients. By analyzing the same single cells for chromosomal aberrations, subchromosomal allelic losses, and gene amplifications, we confirmed their malignant origin and delineated the sequence of genomic events during breast cancer progression. On this trajectory of genomic progression, we identified a subpopulation of patients with very early HER2 amplification. Because early changes have the highest probability of being shared by genetically unstable tumor cells, the genetic characterization of disseminated tumor cells provides a novel rationale for selecting patients for targeted therapies.

• CGH-Profiler: data mining based on genomic aberration profiles.

  Authors: Falk Schubert, Bernhard Tausch, Stefan Joos, Roland Eils

  BMC bioinformatics. 02/2005; 6:188.

  BACKGROUND: CGH-Profiler is a program that supports the analysis of genomic aberrations measured by Comparative Genomic Hybridisation (CGH). Comparative genomic hybridisation (CGH) is aBACKGROUND: CGH-Profiler is a program that supports the analysis of genomic aberrations measured by Comparative Genomic Hybridisation (CGH). Comparative genomic hybridisation (CGH) is a well-established, molecular cytogenetic method that allows the detection of chromosomal imbalances in entire genomes. This technique is widely used in routine molecular diagnostics. Typically, chromosomal imbalances are described in a complex syntax based on the International Standard for Cytogenetic Nomenclature (ISCN). This semantic description of chromosomal imbalances hinders a large-scale statistical analysis across different experiments, e.g. for finding aberration patterns associated with a particular disease type or state. RESULTS: CGH-Profiler circumvents the semantic ISCN description by importing data from different CGH system vendors and by directly transferring the data into a table format that is readily accessible for subsequent statistical analysis. CGH-profiler comes with different consistency checks, calculates various statistics and automatically assigns a median copy number ratio to each chromosomal band.Import of CGH profiles from different CGH system vendors is already supported; its extension to other systems can be readily achieved through Perl scripts.CGH profiler can also be used to analyse comparative expressed sequence hybridisation (CESH) data. CESH reveals gene expression patterns according to chromosomal locations in a similar manner as CGH detects chromosomal imbalances. CONCLUSION: CGH-Profiler is a useful tool for processing of CGH and CESH data.

• Applying Support Vector Machines for Gene Ontology based gene function prediction.

  Authors: Arunachalam Vinayagam, Rainer König, Jutta Moormann, Falk Schubert, Roland Eils, Karl-Heinz Glatting, Sándor Suhai

  BMC bioinformatics. 09/2004; 5:116.

  BACKGROUND: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on aBACKGROUND: The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions. RESULTS: We have developed a large-scale annotation system that tackles all of these shortcomings. In our approach, annotation was provided through Gene Ontology terms by applying multiple Support Vector Machines (SVM) for the classification of correct and false predictions. The general performance of the system was benchmarked with a large dataset. An organism-wise cross-validation was performed to define confidence estimates, resulting in an average precision of 80% for 74% of all test sequences. The validation results show that the prediction performance was organism-independent and could reproduce the annotation of other automated systems as well as high-quality manual annotations. We applied our trained classification system to Xenopus laevis sequences, yielding functional annotation for more than half of the known expressed genome. Compared to the currently available annotation, we provided more than twice the number of contigs with good quality annotation, and additionally we assigned a confidence value to each predicted GO term. CONCLUSIONS: We present a complete automated annotation system that overcomes many of the usual problems by applying a controlled vocabulary of Gene Ontology and an established classification method on large and well-described sequence data sets. In a case study, the function for Xenopus laevis contig sequences was predicted and the results are publicly available at ftp://genome.dkfz-heidelberg.de/pub/agd/gene_association.agd_Xenopus.

• Understanding the classification of tumors with a support-vector-machine: A case-based explanation scheme.

  Authors: Falk Schubert, Jasmin Müller, Björn Fritz, Peter Lichter, Roland Eils

  Proceedings of the German Conference on Bioinformatics, GCB 2003, October 12-14, 2003, Neuherberg/Garching near Munich, Germany; 01/2003

• Quality markers of drug information on the Internet: an evaluation of sites about St. John's wort.

  Authors: Meret Martin-Facklam, Michael Kostrzewa, Falk Schubert, Christiane Gasse, Walter E Haefeli

  The American journal of medicine. 01/2003; 113(9):740-5.

  PURPOSE: We aimed to evaluate websites about St. John's wort for the quality of their content, including accuracy as reflected by statement of correct indication and mentioning of interacting drugs,PURPOSE: We aimed to evaluate websites about St. John's wort for the quality of their content, including accuracy as reflected by statement of correct indication and mentioning of interacting drugs, the presence of formal criteria as reflected by adherence to published standards for health information on the Internet, and the validity of individual formal criteria as markers of content quality. SUBJECTS AND METHODS: The Internet was searched with the metasearch engine WebFerret for sites about St. John's wort. A cross-sectional survey of a representative sample of randomly selected sites (n = 208) was performed. The main outcomes were the percentage of sites fulfilling the two criteria of content quality, the percentage of sites exhibiting eight formal criteria, and the associations between formal criteria and criteria of content quality, as determined by multivariate logistic regression analysis. RESULTS: Twenty-two percent (n = 45) of the websites correctly listed depression as the only indication for use of St. John's wort, and 22% (n = 46) identified at least one drug interaction with St. John's wort. Citing scientific publications was associated with mentioning the correct indication (odds ratio [OR] = 4.4; 95% confidence interval [CI]: 1.4 to 14) and mentioning of any interacting drug (OR = 6.0; 95% CI: 2.0 to 18). Absence of financial interest was associated with mentioning the correct indication (OR = 5.4; 95% CI: 2.2 to 14) and interacting drugs (OR = 3.1; 95% CI: 1.2 to 7.7). CONCLUSION: The content quality of sites about St. John's wort was generally poor. Our results suggest that Internet users should prefer noncommercial sites that reference the information to scientific publications when searching for drug information.

• Microarray-based copy number and expression profiling in dedifferentiated and pleomorphic liposarcoma.

  Authors: Björn Fritz, Falk Schubert, Gunnar Wrobel, Carsten Schwaenen, Swen Wessendorf, Michelle Nessling, Christian Korz, Ralf J Rieker, Kate Montgomery, Raju Kucherlapati, Gunhild Mechtersheimer, Roland Eils, Stefan Joos, Peter Lichter

  Cancer research. 07/2002; 62(11):2993-8.

  Sixteen dedifferentiated and pleomorphic liposarcomas were analyzed by comparative genomic hybridization (CGH) to genomic microarrays (matrix-CGH), cDNA-derived microarrays for expression profiling,Sixteen dedifferentiated and pleomorphic liposarcomas were analyzed by comparative genomic hybridization (CGH) to genomic microarrays (matrix-CGH), cDNA-derived microarrays for expression profiling, and by quantitative PCR. Matrix-CGH revealed copy number gains of numerous oncogenes, i.e., CCND1, MDM2, GLI, CDK4, MYB, ESR1, and AIB1, several of which correlate with a high level of transcripts from the respective gene. In addition, a number of genes were found differentially expressed in dedifferentiated and pleomorphic liposarcomas. Application of dedicated clustering algorithms revealed that both tumor subtypes are clearly separated by the genomic profiles but only with a lesser power by the expression profiles. Using a support vector machine, a subset of five clones was identified as "class discriminators." Thus, for the distinction of these types of liposarcomas, genomic profiling appears to be more advantageous than RNA expression analysis.