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  • MICROARRAY DATA  (6)
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  • 1
    Keywords: GENE-EXPRESSION ; GENE ; microarray ; EXPRESSION ; gene expression ; MICROARRAY DATA
    Type of Publication: Book chapter
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  • 2
    Keywords: EXPRESSION ; CELL ; Germany ; GENE ; GENES ; transcription ; MOLECULAR CHARACTERIZATION ; TISSUE ; MECHANISM ; TRANSCRIPTION FACTOR ; REDUCTION ; TISSUES ; mechanisms ; TARGET ; MUTANT ; STAGE ; TRANSCRIPTION FACTORS ; IDENTIFICATION ; IN-SITU ; MICROARRAY DATA ; NUMBER ; RT-PCR ; sensitivity ; max ; expression profiling ; TRANSCRIPTIONAL REGULATION ; COMPLEXITY ; MOLECULAR-MECHANISM ; ARABIDOPSIS-THALIANA ; BETA-GLUCOSIDASE ; CELL-WALL PROTEIN ; FLORAL ORGAN IDENTITY ; GENOME-WIDE ANALYSIS ; GERBERA-HYBRIDA ; HOMEOTIC GENE ; LIPID-TRANSFER PROTEIN
    Abstract: The class B MADS box transcription factors DEFICIENS (DEF) and GLOBOSA (GLO) of Antirrhinum majus together control the organogenesis of petals and stamens. Toward an understanding of how the downstream molecular mechanisms controlled by DEF contribute to petal organogenesis, we conducted expression profiling experiments using macroarrays comprising 〉11,600 annotated Antirrhinum unigenes. First, four late petal developmental stages were compared with sepals. More than 500 ESTs were identified that comprise a large number of stage-specifically regulated genes and reveal a highly dynamic transcriptional regulation. For identification of DEF target genes that might be directly controlled by DEF, we took advantage of the temperature-sensitive def-101 mutant. To enhance the sensitivity of the profiling experiments, one petal developmental stage was selected, characterized by increased transcriptome changes that reflect the onset of cell elongation processes replacing cell division processes. Upon reduction of the DEF function, 49 upregulated and 52 downregulated petal target genes were recovered. Eight target genes were further characterized in detail by RT-PCR and in situ studies. Expression of genes responding rapidly toward an altered DEF activity is confined to different petal tissues, demonstrating the complexity of the DEF function regulating diverse basic processes throughout petal morphogenesis
    Type of Publication: Journal article published
    PubMed ID: 15539471
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  • 3
    Keywords: Germany ; TOOL ; GENE ; GENES ; microarray ; SACCHAROMYCES-CEREVISIAE ; transcription ; COMPLEX ; COMPLEXES ; IDENTIFICATION ; MICROARRAY DATA ; NUMBER ; COLORECTAL-CANCER ; adenocarcinoma ; CLUSTER ; SINGLE ; GENE ONTOLOGY
    Abstract: Motivation: The functional interpretation of microarray datasets still represents a time-consuming and challenging task. Up to now functional categories that are relevant for one or more experimental context(s) have been commonly extracted from a set of regulated genes and presented in long lists. Results: To facilitate interpretation, we integrated Gene Ontology (GO) annotations into Correspondence Analysis to display genes, experimental conditions and gene-annotations in a single plot. The position of the annotations in these plots can be directly used for the functional interpretation of clusters of genes or experimental conditions without the need for comparing long lists of annotations. Correspondence Analysis is not limited in the number of experimental conditions that can be compared simultaneously, allowing an easy identification of characterizing annotations even in complex experimental settings. Due to the rapidly increasing amount of annotation data available, we apply an annotation filter. Hereby the number of displayed annotations can be significantly reduced to a set of descriptive ones, further enhancing the interpretability of the plot. We validated the method on transcription data from Saccharomyces cerevisiae and human pancreatic adenocarcinomas
    Type of Publication: Journal article published
    PubMed ID: 15746280
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  • 4
    Keywords: EXPRESSION ; IN-VIVO ; THERAPY ; GENE ; GENE-EXPRESSION ; GENES ; GENOME ; PROTEIN ; DNA ; INFECTION ; cell cycle ; CELL-CYCLE ; IDENTIFICATION ; MICROARRAY DATA ; VECTOR ; CANCER-CELLS ; ORIGIN ; COMPETENT ADENOVIRUS ; E1A
    Abstract: Adenoviruses (Ads), especially HAdV-5, have been genetically equipped with tumor-restricted replication potential to enable applications in oncolytic cancer therapy. Such oncolytic adenoviruses have been well tolerated in cancer patients, but their anti-tumor efficacy needs to be enhanced. In this regard, it should be considered that cancer cells, dependent on their tissue of origin, can differ substantially from the normal host cells to which Ads are adapted by complex virus-host interactions. Consequently, viral replication efficiency, a key determinant of oncolytic activity, might be suboptimal in cancer cells. Therefore, we have analyzed both the replication kinetics of HAdV-5 and the virus-induced transcriptome in human bronchial epithelial cells (HBEC) in comparison to cancer cells. This is the first report on genome-wide expression profiling of Ads in their native host cells. We found that E1A expression and onset of viral genome replication are most rapid in HBEC and considerably delayed in melanoma cells. In squamous cell lung carcinoma cells, we observed intermediate HAdV-5 replication kinetics. Infectious particle production, viral spread and lytic activity of HAdV-5 were attenuated in melanoma cells versus HBEC. Expression profiling at the onset of viral genome replication revealed that HAdV-5 induced the strongest changes in the cellular transcriptome in HBEC, followed by lung cancer and melanoma cells. We identified prominent regulation of genes involved in cell cycle and DNA metabolism, replication and packaging in HBEC, which is in accord with the necessity to induce S phase for viral replication. Strikingly, in melanoma cells HAdV-5 triggered opposing regulation of said genes and, in contrast to lung cancer cells, no weak S phase induction was detected when using the E2F promoter as reporter. Our results provide a rationale for improving oncolytic adenoviruses either by adaptation of viral infection to target tumor cells or by modulating tumor cell functions to better support viral replication
    Type of Publication: Journal article published
    PubMed ID: 22140489
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  • 5
    Keywords: APOPTOSIS ; CANCER ; CANCER CELLS ; CELLS ; EXPRESSION ; GROWTH ; IN-VITRO ; INHIBITOR ; SURVIVAL ; tumor ; TUMOR-CELLS ; CELL ; Germany ; human ; PATHWAY ; PATHWAYS ; THERAPY ; VITRO ; COMMON ; GENE ; GENE-EXPRESSION ; GENES ; GENOME ; microarray ; LINES ; ACTIVATION ; MECHANISM ; prognosis ; mechanisms ; CELL-LINES ; DNA TOPOISOMERASE-II ; gene expression ; MICROARRAY DATA ; ASSAY ; SIGNALING PATHWAY ; SIGNALING PATHWAYS ; CANCER-CELLS ; POOR-PROGNOSIS ; FLOW-CYTOMETRY ; cell lines ; expression profiling ; pancreatic cancer ; DISSECTION ; signaling ; AGENT ; PANCREATIC-CANCER ; THERAPIES ; CANDIDATE GENES ; RIBONUCLEOTIDE REDUCTASE ; artemisinin ; artesunate ; ANTIMALARIAL ARTESUNATE ; pharmacology ; FALCIPARUM-MALARIA ; anti-tumor activity ; therapeutic ; CANCER-CELL-LINES ; FUNCTIONAL-ROLE ; CLINICAL BENEFIT ; Ingenuity Pathway Analysis ; Topoisomerase
    Abstract: Pancreatic cancer is one of the most aggressive human malignancies, with an extremely poor prognosis. The paucity of curative therapies has translated into an overall 5-year survival rate of less than 5%, underscoring a desperate need for new therapeutic options. Artesunate (ART), clinically used as antimalarial agent, has recently revealed remarkable anti-tumor activity. However, the mechanisms underlying those activities in pancreatic cancer are not yet known. Here we evaluated the anti-tumor activity of Artesunate and the possible underlying mechanisms in pancreatic cancer. MiaPaCa-2 (poorly differentiated) and BxPC-3 (moderately differentiated) pancreatic cancer cell lines were treated with Artesunate and the effect was monitored by a tetrazolium-based assay (MTS) for evaluating cell viability and by flow cytometry and caspase 3/7 activation for apoptosis evaluation. In addition cDNA arrays were used to identify differentially expressed genes. The microarray data were then validated by RT-PCR and Western blotting. Moreover, pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis. The expression analysis identified a common set of genes that were regulated by Artesunate in pancreatic cancer. Our results provide the first in vitro evidence for the therapeutic utility of Artesunate in pancreatic cancer. Moreover, we identified Artesunate as a novel topoisomerase Hot inhibitor that inhibits pancreatic cancer growth through modulation of multiple signaling pathways. The present analysis is a starting point for the generation of hypotheses on candidate genes and for a more detailed dissection of the functional role of individual genes for the activity of Artesunate in tumor cells. (C) 2009 Elsevier Inc. All rights reserved
    Type of Publication: Journal article published
    PubMed ID: 19393226
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  • 6
    Keywords: CANCER ; Germany ; ALGORITHM ; INFORMATION ; GENE ; GENES ; microarray ; validation ; MOTIFS ; BIOLOGY ; CELL-CYCLE ; SEQUENCE ; MICROARRAY DATA ; ARRAYS ; NUMBER ; DATABASE ; B-CELLS ; SCIENCE ; METAANALYSIS ; methods ; PROFILES ; STEM ; Species ; PROBABILITIES ; CO-INERTIA ANALYSIS ; EXPRESSION DATA ; SISTER-CHROMATID COHESION
    Abstract: Motivation: Cross-species meta-analyses of microarray data usually require prior affiliation of genes based on orthology information that often relies on sequence similarity. Results: We present an algorithm merging microarray datasets on the basis of co-expression alone, without any requirement for orthology information to affiliate genes. Combining existing methods such as co-inertia analysis, back-transformation, Hungarian matching and majority voting in an iterative non-greedy hill-climbing approach, it affiliates arrays and genes at the same time, maximizing the co-structure between the datasets. To introduce the method, we demonstrate its performance on two closely and two distantly related datasets of different experimental context and produced on different platforms. Each pair stems from two different species. The resulting cross-species dynamic Bayesian gene networks improve on the networks inferred from each dataset alone by yielding more significant network motifs, as well as more of the interactions already recorded in KEGG and other databases. Also, it is shown that our algorithm converges on the optimal number of nodes for network inference. Being readily extendable to more than two datasets, it provides the opportunity to infer extensive gene regulatory networks
    Type of Publication: Journal article published
    PubMed ID: 20200011
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