Biomedical subjects

Astrid Laegreid

Publications and source records attributed to Astrid Laegreid.

12 recordsLinked to original sources

PubMed2006

Inducible cAMP early repressor suppresses gastrin-mediated activation of cyclin D1 and c-fos gene expression.

The gastric hormone gastrin and its precursors promote proliferation in several gastrointestinal cell types. Here we show that gastrin induces transcription of cell cycle gene cyclin D1 and protooncogene c-fos in the neuroendocrine pancreatic cell line AR42J and that this gastrin response is inhibited by endogenous inducible cAMP early repressor (ICER). The transcriptional repressor ICER is known to downregulate both its own expression and the expression of other genes containing cAMP-responsive elements (CREs). Using siRNA, we also show that CRE promoter elements are the targets of endogenous ICER in AR42J cells as well as in the neuroendocrine cell line RIN5F. Our results suggest that ICER plays an important role in molecular mechanisms governing gastrin-mediated growth by modulating gastrin's transcriptional activation of growth-related genes. Our finding that ICER modulates pituitary adenylate cyclase-activating polypeptide-activated gene expression also indicates a regulatory effect of ICER in the responses of neuroendocrine cells to peptides other than gastrin.

Animals↗

PubMed2006

GeneTools--application for functional annotation and statistical hypothesis testing.

BACKGROUND: Modern biology has shifted from "one gene" approaches to methods for genomic-scale analysis like microarray technology, which allow simultaneous measurement of thousands of genes. This has created a need for tools facilitating interpretation of biological data in "batch" mode. However, such tools often leave the investigator with large volumes of apparently unorganized information. To meet this interpretation challenge, gene-set, or cluster testing has become a popular analytical tool. Many gene-set testing methods and software packages are now available, most of which use a variety of statistical tests to assess the genes in a set for biological information. However, the field is still evolving, and there is a great need for "integrated" solutions. RESULTS: GeneTools is a web-service providing access to a database that brings together information from a broad range of resources. The annotation data are updated weekly, guaranteeing that users get data most recently available. Data submitted by the user are stored in the database, where it can easily be updated, shared between users and exported in various formats. GeneTools provides three different tools: i) NMC Annotation Tool, which offers annotations from several databases like UniGene, Entrez Gene, SwissProt and GeneOntology, in both single- and batch search mode. ii) GO Annotator Tool, where users can add new gene ontology (GO) annotations to genes of interest. These user defined GO annotations can be used in further analysis or exported for public distribution. iii) eGOn, a tool for visualization and statistical hypothesis testing of GO category representation. As the first GO tool, eGOn supports hypothesis testing for three different situations (master-target situation, mutually exclusive target-target situation and intersecting target-target situation). An important additional function is an evidence-code filter that allows users, to select the GO annotations for the analysis. CONCLUSION: GeneTools is the first "all in one" annotation tool, providing users with a rapid extraction of highly relevant gene annotation data for e.g. thousands of genes or clones at once. It allows a user to define and archive new GO annotations and it supports hypothesis testing related to GO category representations. GeneTools is freely available through www.genetools.no

Algorithms↗

PubMed2006

Additional gene ontology structure for improved biological reasoning.

MOTIVATION: The Gene Ontology (GO) is a widely used terminology for gene product characterization in, for example, interpretation of biology underlying microarray experiments. The current GO defines term relationships within each of the independent subontologies: molecular function, biological process and cellular component. However, it is evident that there also exist biological relationships between terms of different subontologies. Our aim was to connect the three subontologies to enable GO to cover more biological knowledge, enable a more consistent use of GO and provide new opportunities for biological reasoning. RESULTS: We propose a new structure, the Second Gene Ontology Layer, capturing biological relations not directly reflected in the present ontology structure. Given molecular functions, these paths identify biological processes where the molecular functions are involved and cellular components where they are active. The current Second Layer contains 6271 validated paths, covering 54% of the molecular functions of GO and can be used to render existing gene annotation sets more complete and consistent. Applying Second Layer paths to a set of 4223 human genes, increased biological process annotations by 24% compared to publicly available annotations and reproduced 30% of them. AVAILABILITY: The Second GO is publicly available through the GO Annotation Toolbox (GOAT.no): http://www.goat.no.

Computational Biology↗

PubMed2006

Aetiology-specific patterns in end-stage heart failure patients identified by functional annotation and classification of microarray data.

BACKGROUND: The objective of the present study was to use gene expression profiling, functional annotations and classification to identify aetiology-specific biological processes and potential molecular markers for different aetiologies of end-stage heart failure. METHODS AND RESULTS: Individual left ventricular myocardial samples from eleven coronary artery disease and nine dilated cardiomyopathy transplant patients were co-hybridized with pooled RNA from four non-failing hearts on custom-made arrays of 7000 human genes. Significance analysis identified differential expression of 153 and 147 genes, respectively, in coronary artery disease or dilated cardiomyopathy versus non-failing hearts. Analysis of Gene Ontology biological process annotations indicated aetiology-specific patterns, primarily related to genes involved in catabolism and in regulation of protein kinase activity. Gene expression classifiers were obtained and used for class prediction of random samples of coronary artery diseased and dilated cardiomyopathic hearts. Best classifiers frequently included matrix metalloproteinase 3, fibulin 1, ATP-binding cassette, sub-family B member 1 and iroquois homeobox protein 5. CONCLUSION: Combining functional annotation from microarray data and classification analysis constitutes a potent strategy to identify disease-specific biological processes and gene expression markers in e.g. end-stage coronary artery disease and dilated cardiomyopathy.

Adult↗

PubMed2005

Distinct differences between TNF receptor 1- and TNF receptor 2-mediated activation of NFkappaB.

Tumor necrosis factor (TNF) signaling is mediated via two distinct receptors, TNFR2 and TNFR1, which shows partially overlapping signaling mechanisms and biological roles. In the present study, TNFR2 and TNFR1 signal transduction mechanisms involved in activation of NFkappaB and CMV promoter-enhancer were compared with respect to their susceptibility towards inhibitors of intracellular signaling. For this, we used SW480 cells, where we have shown that TNF-signaling can occur independently through each of the two receptors. The TNFR1 response was inhibited by D609, bromophenacyl bromide (BPB), nordihydroguararetic acid (NDGA), and by sodium salicylate, while TNFR2-mediated activation of NFkappaB and CMV promoter-enhancer was resistant to these compounds. The signaling mechanisms known to be affected by these inhibitors include phospholipases as well as redox- and pH-sensitive intracellular components. Our results imply that TNFR2 signaling involved in NFkappaB activation proceeds independently of these inhibitor-sensitive signaling components, indicating distinct signaling pathways not shared with TNFR1.

Cell Line, Tumor↗

PubMed2005

Molecular characterization of rat gastric mucosal response to potent acid inhibition.

Potent acid inhibition with proton pump inhibitors (PPIs) is widely used in clinical medicine, especially for gastroesophageal reflux disease. PPIs cause profound changes in the intragastric environment with near-neutral pH and increase serum concentration of the gastric secretagogue hormone gastrin. Long-term hypergastrinemia increases mucosal thickness and enterochromaffin-like cell density in gastric corpus mucosa and results in development of gastric carcinoids in experimental animals. Our aim was to study responses to potent acid inhibition by characterizing genome-wide gene expression changes in gastric corpus mucosa in rats dosed with the PPI omeprazole. Nine rats received 400 micromol/kg omeprazole daily for 10 wk. Seven rats received vehicle only. Analysis of gastric corpus with microarrays representing 11,848 genes identified 134 genes with changed gene expression levels in omeprazole-dosed rats. Several of the identified genes were previously known to be affected by potent acid inhibition. Of the 62 genes with known functions that changed gene expression levels after PPI dosing, 27 are known to be involved in proliferation and apoptosis and immune, inflammatory, and stress responses. Our study indicates that microarray analysis can detect relevant gene expression changes in the complex gastric tissue, and that cellular processes involved in cell growth and defense responses are strongly affected by PPI dosing. Many genes are identified that were not previously known to be affected by inhibition of gastric acid secretion or that have unknown biological functions. Characterization of the roles of these genes may give new insight into molecular responses to treatment with PPIs.

Animals↗

PubMed2004

XHM: a system for detection of potential cross hybridizations in DNA microarrays.

BACKGROUND: Microarrays have emerged as the preferred platform for high throughput gene expression analysis. Cross-hybridization among genes with high sequence similarities can be a source of error reducing the reliability of DNA microarray results. RESULTS: We have developed a tool called XHM (cross hybridization on microarrays) for assessment of the reliability of hybridization signals by detecting potential cross-hybridizations on DNA microarrays. This is done by comparing the sequences of the probes against an extensive database representing the transcriptome of the organism in question. XHM is available online at http://www.bioinfo.no/tools/xhm/. CONCLUSIONS: Using XHM with its user-adjustable parameters will enable scientists to check their lists of differentially expressed genes from microarray experiments for potential cross-hybridizations. This provides information that may be useful in the validation of the microarray results.

Animals↗

PubMed2004

Gene expression based classification of gastric carcinoma.

The aim of the present work is to identify molecular markers that allow classification of gastric carcinoma with respect to important clinicopathological parameters. Gastric adenocarcinomas were subjected to cDNA microarray analysis with a 2.504 gene probe set. Using the Rosetta rough-set based learning system, good classifiers were generated for gene-expression based prediction of intestinal or diffuse growth pattern according to Laurén's classification and presence of lymph node metastases. To our knowledge, this is the first study on gastric carcinoma in which molecular classification has been achieved for more than one clinicopathological parameter based on microarray gene expression profiles.

Adenocarcinoma↗

PubMed2004

Miniaturized fluorescent RNA dot blot method for rapid quantitation of gene expression.

BACKGROUND: RNA dot blot hybridization is a commonly used technique for gene expression assays. However, membrane based RNA dot/slot blot hybridization is time consuming, requires large amounts of RNA, and is less suited for parallel assays of more than one gene at a time. Here, we describe a glass-slide based miniaturized RNA dot blot (RNA array) procedure for rapid and parallel gene expression analysis using fluorescently labeled probes. RESULTS: RNA arrays were prepared by simple manual spotting of RNA onto amino-silane coated microarray glass slides, and used for two-color fluorescent hybridization with specific probes labeled with Cy3 and 18S ribosomal RNA house-keeping gene probe labeled with Cy5 fluorescent dyes. After hybridization, arrays were scanned on a fluorescent microarray scanner and images analyzed using microarray image analysis software. We demonstrate that this method gives comparable results to Northern blot analysis, and enables high throughput quantification of transcripts from nanogram quantities of total RNA in hundreds of samples. CONCLUSION: RNA array on glass slide and detection by fluorescently labeled probes can be used for rapid and parallel gene expression analysis. The method is particularly well suited for gene expression assays that involve quantitation of many transcripts in large numbers of samples.

Animals↗

PubMed2003

Liver gene expression in rats in response to the peroxisome proliferator-activated receptor-alpha agonist ciprofibrate.

Fibrate class hypolipidemic drugs such as ciprofibrate activate the peroxisome proliferator-activated receptor-alpha (PPARalpha), which is involved in processes including lipid metabolism and hepatocyte proliferation in rodents. We examined the effects of ciprofibrate (50 mg/kg body wt per day for 60 days) on liver gene expression in rats using cDNA microarrays. The 60-day dosing period was chosen to elucidate both the metabolic and proliferative actions of this substance, while avoiding confounding effects from the hepatic carcinogenesis seen during more long-term stimulation. Ciprofibrate changed the expression of many genes including previously known PPARalpha agonist-responsive genes involved in processes such as lipid metabolism and inflammatory responses. In addition, many novel candidate genes involved in sugar metabolism, transcription, signal transduction, cell proliferation, and stress responses appeared to be differentially regulated in ciprofibrate-dosed rats. Ciprofibrate also resulted in significant increases in liver weight and hepatocyte proliferation. The cDNA microarray results were confirmed by Northern blot analysis for selected genes. This study thus identifies many genes that appear to be differentially regulated in ciprofibrate-dosed rats, and some of these are potential targets of PPARalpha. The functional diversity of these candidate genes suggests that most of them are likely to be differentially regulated as indirect consequence of the many processes affected by ciprofibrate in rodent liver. Although caution is advisable in the interpretation of genome-wide expression data, the genes identified in the present study provide candidates for further studies that may give new insight into the mechanisms of action of peroxisome proliferators.

Animals↗

PubMed2003

Learning rule-based models of biological process from gene expression time profiles using gene ontology.

MOTIVATION: Microarray technology enables large-scale inference of the participation of genes in biological process from similar expression profiles. Our aim is to induce classificatory models from expression data and biological knowledge that can automatically associate genes with novel hypotheses of biological process. RESULTS: We report a systematic supervised learning approach to predicting biological process from time series of gene expression data and biological knowledge. Biological knowledge is expressed using gene ontology and this knowledge is associated with discriminatory expression-based features to form minimal decision rules. The resulting rule model is first evaluated on genes coding for proteins with known biological process roles using cross validation. Then it is used to generate hypotheses for genes for which no knowledge of participation in biological process could be found. The theoretical foundation for the methodology based on rough sets is outlined in the paper, and its practical application demonstrated on a data set previously published by Cho et al. (Nat. Genet., 27, 48-54, 2001). AVAILABILITY: The Rosetta system is available at http://www.idi.ntnu.no/~aleks/rosetta. SUPPLEMENTARY INFORMATION: http://www.lcb.uu.se/~hvidsten/bioinf_cho/

Algorithms↗

PubMed2002

Expression of chromogranin A and somatostatin receptors in pancreatic AR42J cells.

The exocrine pancreatic cell line AR42J is also known to display some neuroendocrine (NE) features. We have extended this fact by showing that AR42J cells express mRNA of chromogranin A (CgA), display immunoreactivity (IR) to CgA, and secrete its cleavage product pancreastatin. A sparse occurrence of typical NE secretion granules, together with only a faint IR to conventional NE markers, indicates that the NE cells are of a poorly differentiated type. CgA promoter reporter plasmid experiments showed that gastrin, epidermal growth factor, and phorbol 12-myristate 13-acetate, induce upregulation of CgA after 24 h. By RT-PCR, it was found that AR42J expresses all of the five subtypes of the somatostatin (SST) receptor (SSTR) family, except SSTR4. The existence of functional SSTRs was confirmed by showing that the SST analog octreotide could inhibit gastrin-induced proliferation. Thus, the AR42J cell line may function as a valuable experimental model to study the regulation of CgA and SSTRs in poorly differentiated NE tumor cells.

Animals↗