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Dive into the research topics where Andreas Buness is active.

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Featured researches published by Andreas Buness.


Lung Cancer | 2009

Global gene expression analysis reveals specific patterns of cell junctions in non-small cell lung cancer subtypes.

Ruprecht Kuner; Thomas Muley; Michael Meister; Markus Ruschhaupt; Andreas Buness; Elizabeth C. Xu; Phillipp Schnabel; Arne Warth; Annemarie Poustka; Holger Sültmann; Hans Hoffmann

Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC). Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: more than 1700 genes were found to be differentially expressed. The assignment of these genes to biological processes pointed to the deregulation of distinct sets of genes coding for cell junctions in both tumor subtypes. We focused on 17 cell adhesion genes and 11 reported marker genes for epithelial-mesenchymal transition (EMT), and investigated their expression in matched tumor-normal specimens by quantitative real-time PCR. The majority of the cell adhesion genes was significantly up-regulated in at least one tumor subtype compared to normal tissue, predominantly desmosomes and gap junctions in SCC, and tight junctions in AC. The higher expression of EMT marker transcripts in tumor specimens suggested a large potential for invasion and migration processes in NSCLC. Our results indicate that AC and SCC in the lung are characterized by the expression of distinct sets of cell adhesion molecules which may represent promising targets for novel specific therapies.


International Journal of Cancer | 2009

Down‐regulation of HLA Class I and NKG2D ligands through a concerted action of MAPK and DNA methyltransferases in colorectal cancer cells

Christine Sers; Ruprecht Kuner; Christine S. Falk; Per Lund; Holger Sueltmann; Monika Braun; Andreas Buness; Markus Ruschhaupt; Janine Conrad; Shila Mang-Fatehi; Iwona Stelniec; Ulf Krapfenbauer; Annemarie Poustka; Reinhold Schäfer

Most malignant features of cancer cells are triggered by activated oncogenes and the loss of tumor suppressors due to mutation or epigenetic inactivation. It is still unclear, to what extend the escape of emerging cancer cells from recognition and elimination by the immune system is determined by similar mechanisms. We compared the transcriptomes of HCT116 colorectal cancer cells deficient in DNA methyltransferases (DNMTs) and of cells, in which the RAS pathway as the major growth‐promoting signaling system is blocked by inhibition of MAPK. We identified the MHC Class I genes HLA‐A1/A2 and the ULBP2 gene encoding 1 of the 8 known ligands of the activating NK receptor NKG2D among a cluster of immune genes up‐regulated under the conditions of both DNMT‐deficiency and MEK‐inhibition. Bisulphite sequencing analyses of HCT116 with DNMT deficiency or after MEK‐inhibition showed that de‐methylation of the ULPB2 promoter correlated with its enhanced surface expression. The HLA‐A promoters were not methylated indicating that components of the HLA assembly machinery were also suppressed in DNMT‐deficient and MEK‐inhibited cells. Increased HLA‐A2 surface expression was correlated with enhanced recognition and lysis by A2‐specific CTL. On the contrary, elevated ULBP2 expression was not reflected by enhanced recognition and lysis by NK cells. Cosuppression of HLA Class I and NKG2D ligands and genes encoding peptide transporters or proteasomal genes mediates a strong functional link between RAS activation, DNMT activity and disruption of the antigen presenting system controlling immune recognition in colorectal cancer cells.


Molecular Cell | 2016

Nuclear Architecture Organized by Rif1 Underpins the Replication-Timing Program

Rossana Foti; Stefano Gnan; Daniela Cornacchia; Vishnu Dileep; Aydan Bulut-Karslioglu; Sarah Diehl; Andreas Buness; Felix A. Klein; Wolfgang Huber; Ewan Johnstone; Remco Loos; Paul Bertone; David M. Gilbert; Thomas Manke; Thomas Jenuwein; Sara C.B. Buonomo

Summary DNA replication is temporally and spatially organized in all eukaryotes, yet the molecular control and biological function of the replication-timing program are unclear. Rif1 is required for normal genome-wide regulation of replication timing, but its molecular function is poorly understood. Here we show that in mouse embryonic stem cells, Rif1 coats late-replicating domains and, with Lamin B1, identifies most of the late-replicating genome. Rif1 is an essential determinant of replication timing of non-Lamin B1-bound late domains. We further demonstrate that Rif1 defines and restricts the interactions between replication-timing domains during the G1 phase, thereby revealing a function of Rif1 as organizer of nuclear architecture. Rif1 loss affects both number and replication-timing specificity of the interactions between replication-timing domains. In addition, during the S phase, Rif1 ensures that replication of interacting domains is temporally coordinated. In summary, our study identifies Rif1 as the molecular link between nuclear architecture and replication-timing establishment in mammals.


Bioinformatics | 2005

arrayMagic: two-colour cDNA microarray quality control and preprocessing

Andreas Buness; Wolfgang Huber; Klaus Steiner; Holger Sültmann; Annemarie Poustka

UNLABELLED arrayMagic is a software package for quality control and preprocessing of two-colour cDNA microarray data. The automated analysis pipeline comprises data import, normalization, replica merging, quality diagnostics and data export. The script-based processing combines reproducibility and flexibility at high-throughput and provides quality-assured and preprocessed microarray data to high-level follow-up analysis. AVAILABILITY The R package arrayMagic is available with BSD license at http://www.bioconductor.org CONTACT [email protected] SUPPLEMENTARY INFORMATION The package contains documentation in the form of manual pages and a vignette with a guided tour of a typical workflow.


Journal of Molecular Medicine | 2007

Identification of cellular targets for the human papillomavirus E6 and E7 oncogenes by RNA interference and transcriptome analyses

Ruprecht Kuner; Markus Vogt; Holger Sültmann; Andreas Buness; Susanne Dymalla; Julia Bulkescher; Mark Fellmann; Karin Butz; Annemarie Poustka; Felix Hoppe-Seyler

Specific types of human papillomaviruses (HPVs) cause cervical cancer, the second most common tumor in women worldwide. Both cellular transformation and the maintenance of the oncogenic phenotype of HPV-positive tumor cells are linked to the expression of the viral E6 and E7 oncogenes. To identify downstream cellular target genes for the viral oncogenes, we silenced endogenous E6 and E7 expression in HPV-positive HeLa cells by RNA interference (RNAi). Subsequently, we assessed changes of the cellular transcriptome by genome-wide microarray analysis. We identified 648 genes, which were either downregulated (360 genes) or upregulated (288 genes), upon inhibition of E6/E7 expression. A large fraction of these genes is involved in tumor-relevant processes, such as apoptosis control, cell cycle regulation, or spindle formation. Others may represent novel cellular targets for the HPV oncogenes, such as a large group of C-MYC-associated genes involved in RNA processing and splicing. Comparison with published microarray data revealed a substantial concordance between the genes repressed by RNAi-mediated E6/E7 silencing in HeLa cells and genes reported to be upregulated in HPV-positive cervical cancer biopsies.


Bioinformatics | 2007

Identification of aberrant chromosomal regions from gene expression microarray studies applied to human breast cancer

Andreas Buness; Ruprecht Kuner; Markus Ruschhaupt; Annemarie Poustka; Holger Sültmann; Achim Tresch

MOTIVATION In cancer, chromosomal imbalances like amplifications and deletions, or changes in epigenetic mechanisms like DNA methylation influence the transcriptional activity. These alterations are often not limited to a single gene but affect several genes of the genomic region and may be relevant for the disease status. For example, the ERBB2 amplicon (17q21) in breast cancer is associated with poor patient prognosis. We present a general, unsupervised method for genome-wide gene expression data to systematically detect tumor patients with chromosomal regions of distinct transcriptional activity. The method aims to find expression patterns of adjacent genes with a consistently decreased or increased level of gene expression in tumor samples. Such patterns have been found to be associated with chromosomal aberrations and clinical parameters like tumor grading and thus can be useful for risk stratification or therapy. RESULTS Our approach was applied to 12 independent human breast cancer microarray studies comprising 1422 tumor samples. We prioritized chromosomal regions and genes predominantly found across all studies. The result highlighted not only regions which are well known to be amplified like 17q21 and 11q13, but also others like 8q24 (distal to MYC) and 17q24-q25 which may harbor novel putative oncogenes. Since our approach can be applied to any microarray study it may become a valuable tool for the exploration of transcriptional changes in diverse disease types. AVAILABILITY The R source codes which implement the method and an exemplary analysis are available at http://www.dkfz.de/mga2/people/buness/CTP/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.


European Urology | 2009

Molecular Cancer Phenotype in Normal Prostate Tissue

Thorsten Schlomm; Olaf Hellwinkel; Andreas Buness; Markus Ruschhaupt; Andreas Lübke; Felix K.-H. Chun; Ronald Simon; Lars Budäus; Andreas Erbersdobler; Markus Graefen; Hartwig Huland; Annemarie Poustka; Holger Sültmann

BACKGROUND Insufficient sensitivity and specificity of prostate biopsies for cancer detection. OBJECTIVES Based on evidence from our microarray analyses, we hypothesized that considerable molecular changes precede morphologically detectable malignant transformation of prostate epithelial tissues. The identification of such changes could lead to novel strategies in the clinical management of prostate cancer. DESIGN, SETTING, AND PARTICIPANTS Histologically normal, fresh prostate tissue from prostate cancer patients, healthy donors, and cancer suspect patients with continuous negative biopsies were analyzed. MEASUREMENTS To identify molecular changes between 29 tumor-free prostate tissues from healthy donors and 27 patients with proven prostate cancer, we performed a global microarray screening. Based on this screening as well as literature data, we selected a subset of 29 genes for validation by arrayed real-time reverse transcription-polymerase chain reaction (RT-PCR) using histologically tumor-free biopsy samples from 114 patients representing three prostate cancer risk groups. RESULTS AND LIMITATIONS We identified five genes (FOS, EGR1, MYC, TFRC, and FOLH1), which displayed significant differential expression between morphologically normal prostate tissues from men of each of the three risk groups. These results were independent from age, prostate-specific antigen (PSA), frequency and timing of previous prostate biopsies, tissue composition, tumor stage, and tumor grade. In univariate logistic regression analyses, the transcript levels of these genes were found to be highly indicative for the presence or absence of cancer in the entire prostate. The study was designed as a proof of principle. The clinical relevance of our results has to be evaluated in a larger clinical setting. CONCLUSIONS Our results suggest a measurable molecular cancer phenotype in histologically normal prostate tissue indicating the presence of prostate cancer elsewhere in the organ.


Physiological Genomics | 2008

Genomic analysis reveals poor separation of human cardiomyopathies of ischemic and nonischemic etiologies.

Ruprecht Kuner; Andreas S. Barth; Markus Ruschhaupt; Andreas Buness; Ludwig Zwermann; Eckart Kreuzer; Gerhard Steinbeck; Annemarie Poustka; Holger Sültmann; Michael Nabauer

Clinically, the differentiation between ischemic (ICM) and nonischemic (NICM) human cardiomyopathies is highly relevant, because ICM and NICM differ with respect to prognosis and certain aspects of pharmacological therapy, despite a common final phenotype characterized by ventricular dilatation and reduced contractility. So far, it is unclear whether microarray-based signatures can be used to infer the etiology of heart failure. Using three different classification algorithms, we independently analyzed one cDNA and two publicly available high-density oligonucleotide microarray studies comprising a total of 279 end-stage human heart failure samples. When classifiers identified in a single study were applied to the remaining studies, misclassification rates >25% for ICM and NICM specimens were noted, indicating poor separation of both etiologies. However, data mining of 458 classifier genes that were concordantly identified in at least two of the three data sets points to different biological processes in ICM vs. NICM. Consistent with the underlying ischemia, cytokine signaling pathways and immediate-early response genes were overrepresented in ICM samples, whereas NICM samples displayed a deregulation of cytoskeletal transcripts, genes encoding for the major histocompatibility complex, and antigen processing and presentation pathways, potentially pointing to immunologic processes in NICM. Overall, our results suggest that ICM and NICM exhibit substantial heterogeneity at the transcriptomic level. Prospective studies are required to test whether etiology-specific gene expression patterns are present at earlier disease stages or in subsets of both etiologies.


BMC Cancer | 2011

Loss of aquaporin-4 expression and putative function in non-small cell lung cancer.

Arne Warth; Thomas Muley; Michael Meister; Esther Herpel; Anita Pathil; Hans Hoffmann; Philipp A. Schnabel; Christian Bender; Andreas Buness; Peter Schirmacher; Ruprecht Kuner

BackgroundAquaporins (AQPs) have been recognized to promote tumor progression, invasion, and metastasis and are therefore recognized as promising targets for novel anti-cancer therapies. Potentially relevant AQPs in distinct cancer entities can be determined by a comprehensive expression analysis of the 13 human AQPs.MethodsWe analyzed the presence of all AQP transcripts in 576 different normal lung and non-small cell lung cancer (NSCLC) samples using microarray data and validated our findings by qRT-PCR and immunohistochemistry.ResultsVariable expression of several AQPs (AQP1, -3, -4, and -5) was found in NSCLC and normal lung tissues. Furthermore, we identified remarkable differences between NSCLC subtypes in regard to AQP1, -3 and -4 expression. Higher transcript and protein levels of AQP4 in well-differentiated lung adenocarcinomas suggested an association with a more favourable prognosis. Beyond water transport, data mining of co-expressed genes indicated an involvement of AQP4 in cell-cell signalling, cellular movement and lipid metabolism, and underlined the association of AQP4 to important physiological functions in benign lung tissue.ConclusionsOur findings accentuate the need to identify functional differences and redundancies of active AQPs in normal and tumor cells in order to assess their value as promising drug targets.


Journal of Computational Biology | 2007

Discrimination of direct and indirect interactions in a network of regulatory effects.

Achim Tresch; Tim Beissbarth; Holger Sültmann; Ruprecht Kuner; Annemarie Poustka; Andreas Buness

The matter of concern are algorithms for the discrimination of direct from indirect regulatory effects from an interaction graph built up by error-prone measurements. Many of these algorithms can be cast as a rule for the removal of a single edge of the graph, such that the remaining graph is still consistent with the data. A set of mild conditions is given under which iterated application of such a rule leads to a unique minimal consistent graph. We show that three of the common methods for direct interactions search fulfill these conditions, thus providing a justification of their use. The main issues a reconstruction algorithm has to deal with, are the noise in the data, the presence of regulatory cycles, and the direction of the regulatory effects. We introduce a novel rule that, in contrast to the previously mentioned methods, simultaneously takes into account all these aspects. An efficient algorithm for the computation of the minimal graph is given, whose time complexity is cubic in the number of vertices of the graph. Finally, we demonstrate the utility of our method in a simulation study.

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Annemarie Poustka

German Cancer Research Center

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Ruprecht Kuner

German Cancer Research Center

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Holger Sültmann

German Cancer Research Center

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Markus Ruschhaupt

German Cancer Research Center

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Holger Sueltmann

German Cancer Research Center

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Vladimir Benes

European Bioinformatics Institute

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