114 research outputs found

    Identification of Achaete-scute complex-like 1 (ASCL1) target genes and evaluation of DKK1 and TPH1 expression in pancreatic endocrine tumours

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    <p>Abstract</p> <p>Background</p> <p><it>ASCL1 </it>role in pancreatic endocrine tumourigenesis has not been established. Recently it was suggested that ASCL1 negatively controls expression of the Wnt signalling antagonist <it>DKK1</it>. Notch signalling regulates expression of TPH1, the rate limiting enzyme in the biosyntesis of serotonin. Understanding the development and proliferation of pancreatic endocrine tumours (PETs) is essential for the development of new therapies.</p> <p>Methods</p> <p><it>ASCL1 </it>target genes in the pancreatic endocrine tumour cell line BON1 were identified by RNA interference and microarray expression analysis. Protein expressions of selected target genes in PETs were evaluated by immunohistochemistry.</p> <p>Results</p> <p>158 annotated <it>ASCL1 </it>target genes were identified in BON1 cells, among them DKK1 and TPH1 that were negatively regulated by ASCL1. An inverse relation of ASCL1 to DKK1 protein expression was observed for 15 out of 22 tumours (68%). Nine tumours displayed low ASCL1/high DKK1 and six tumours high ASCL1/low DKK1 expression. Remaining PETs showed high ASCL1/high DKK1 (n = 4) or low ASCL1/low DKK1 (n = 3) expression. Nine of twelve analysed PETs (75%) showed TPH1 expression with no relation to ASCL1.</p> <p>Conclusion</p> <p>A number of genes with potential importance for PET tumourigenesis have been identified. <it>ASCL1 </it>negatively regulated the Wnt signalling antagonist <it>DKK1</it>, and <it>TPH1 </it>expression in BON1 cells. In concordance with these findings DKK1 showed an inverse relation to ASCL1 expression in a subset of PETs, which may affect growth control by the Wnt signalling pathway.</p

    The Annotation, Mapping, Expression and Network (AMEN) suite of tools for molecular systems biology

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    <p>Abstract</p> <p>Background</p> <p>High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently.</p> <p>Results</p> <p>We developed the Annotation, Mapping, Expression and Network (AMEN) software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i) uploading and pre-processing data from microarray expression profiling experiments, (ii) detecting groups of significantly co-expressed genes, and (iii) searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human.</p> <p>Conclusion</p> <p>AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.</p

    EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

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    <p>Abstract</p> <p>Background</p> <p>Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.</p> <p>Results</p> <p>EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.</p> <p>Conclusion</p> <p>EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from <url>http://www.ezarray.com/</url>.</p

    Molecular Characterization of Spontaneous Mesenchymal Stem Cell Transformation

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    Background. We previously reported the in vitro spontaneous transformation of human mesenchymal stem cells (MSC) generating a population with tumorigenic potential, that we termed transformed mesenchymal cells (TMC). Methodology/Principal Findings. Here we have characterized the molecular changes associated with TMC generation. Using microarrays techniques we identified a set of altered pathways and a greater number of downregulated than upregulated genes during MSC transformation, in part due to the expression of many untranslated RNAs in MSC. Microarray results were validated by qRT-PCR and protein detection. Conclusions/Significance. In our model, the transformation process takes place through two sequential steps; first MSC bypass senescence by upregulating c-myc and repressing p16 levels. The cells then bypass cell crisis with acquisition of telomerase activity, Ink4a/Arf locus deletion and Rb hyperphosphorylation. Other transformation-associated changes include modulation of mitochondrial metabolism, DNA damage-repair proteins and cell cycle regulators. In this work we have characterized the molecular mechanisms implicated in TMC generation and we propose a two-stage model by which a human MSC becomes a tumor cell

    Genome-Wide Analysis of the Complex Transcriptional Networks of Rice Developing Seeds

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    <div><h3>Background</h3><p>The development of rice (<em>Oryza sativa</em>) seed is closely associated with assimilates storage and plant yield, and is fine controlled by complex regulatory networks. Exhaustive transcriptome analysis of developing rice embryo and endosperm will help to characterize the genes possibly involved in the regulation of seed development and provide clues of yield and quality improvement.</p> <h3>Principal Findings</h3><p>Our analysis showed that genes involved in metabolism regulation, hormone response and cellular organization processes are predominantly expressed during rice development. Interestingly, 191 transcription factor (TF)-encoding genes are predominantly expressed in seed and 59 TFs are regulated during seed development, some of which are homologs of seed-specific TFs or regulators of <em>Arabidopsis</em> seed development. Gene co-expression network analysis showed these TFs associated with multiple cellular and metabolism pathways, indicating a complex regulation of rice seed development. Further, by employing a cold-resistant <em>cultivar</em> Hanfeng (HF), genome-wide analyses of seed transcriptome at normal and low temperature reveal that rice seed is sensitive to low temperature at early stage and many genes associated with seed development are down-regulated by low temperature, indicating that the delayed development of rice seed by low temperature is mainly caused by the inhibition of the development-related genes. The transcriptional response of seed and seedling to low temperature is different, and the differential expressions of genes in signaling and metabolism pathways may contribute to the chilling tolerance of HF during seed development.</p> <h3>Conclusions</h3><p>These results provide informative clues and will significantly improve the understanding of rice seed development regulation and the mechanism of cold response in rice seed.</p> </div

    Beta-carotene affects gene expression in lungs of male and female Bcmo1−/− mice in opposite directions

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    Molecular mechanisms triggered by high dietary beta-carotene (BC) intake in lung are largely unknown. We performed microarray gene expression analysis on lung tissue of BC supplemented beta-carotene 15,15′-monooxygenase 1 knockout (Bcmo1−/−) mice, which are—like humans—able to accumulate BC. Our main observation was that the genes were regulated in an opposite direction in male and female Bcmo1−/− mice by BC. The steroid biosynthetic pathway was overrepresented in BC-supplemented male Bcmo1−/− mice. Testosterone levels were higher after BC supplementation only in Bcmo1−/− mice, which had, unlike wild-type (Bcmo1+/+) mice, large variations. We hypothesize that BC possibly affects hormone synthesis or metabolism. Since sex hormones influence lung cancer risk, these data might contribute to an explanation for the previously found increased lung cancer risk after BC supplementation (ATBC and CARET studies). Moreover, effects of BC may depend on the presence of frequent human BCMO1 polymorphisms, since these effects were not found in wild-type mice

    Transcriptional analysis of adipose tissue during development reveals depot-specific responsiveness to maternal dietary supplementation

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    Brown adipose tissue (BAT) undergoes pronounced changes after birth coincident with the loss of the BAT-specifc uncoupling protein (UCP)1 and rapid fat growth. The extent to which this adaptation may vary between anatomical locations remains unknown, or whether the process is sensitive to maternal dietary supplementation. We, therefore, conducted a data mining based study on the major fat depots (i.e. epicardial, perirenal, sternal (which possess UCP1 at 7 days), subcutaneous and omental) (that do not possess UCP1) of young sheep during the frst month of life. Initially we determined what effect adding 3% canola oil to the maternal diet has on mitochondrial protein abundance in those depots which possessed UCP1. This demonstrated that maternal dietary supplementation delayed the loss of mitochondrial proteins, with the amount of cytochrome C actually being increased. Using machine learning algorithms followed by weighted gene co-expression network analysis, we demonstrated that each depot could be segregated into a unique and concise set of modules containing co-expressed genes involved in adipose function. Finally using lipidomic analysis following the maternal dietary intervention, we confrmed the perirenal depot to be most responsive. These insights point at new research avenues for examining interventions to modulate fat development in early life

    Covert Genetic Selections to Optimize Phenotypes

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    In many high complexity systems (cells, organisms, institutions, societies, economies, etc.), it is unclear which components should be regulated to affect overall performance. To identify and prioritize molecular targets which impact cellular phenotypes, we have developed a selection procedure (“SPI”–single promoting/inhibiting target identification) which monitors the abundance of ectopic cDNAs. We have used this approach to identify growth regulators. For this purpose, complex pools of S. cerevisiae cDNA transformants were established and we quantitated the evolution of the spectrum of cDNAs which was initially present. These data emphasized the importance of translation initiation and ER-Golgi traffic for growth. SPI provides functional insight into the stability of cellular phenotypes under circumstances in which established genetic approaches cannot be implemented. It provides a functional “synthetic genetic signature” for each state of the cell (i.e. genotype and environment) by surveying complex genetic libraries, and does not require specialized arrays of cDNAs/shRNAs, deletion strains, direct assessment of clonal growth or even a conditional phenotype. Moreover, it establishes a hierarchy of importance of those targets which can contribute, either positively or negatively, to modify the prevailing phenotype. Extensions of these proof-of-principle experiments to other cell types should provide a novel and powerful approach to analyze multiple aspects of the basic biology of yeast and animal cells as well as clinically-relevant issues

    Inflammation and breast cancer. Inflammatory component of mammary carcinogenesis in ErbB2 transgenic mice

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    This review addresses genes differentially expressed in the mammary gland transcriptome during the progression of mammary carcinogenesis in BALB/c mice that are transgenic for the rat neu (ERBB2, or HER-2/neu) oncogene (BALB-neuT664V-E mice). The Ingenuity knowledge database was used to characterize four functional association networks whose hub genes are directly linked to inflammation (specifically, the genes encoding IL-1β, tumour necrosis factor, interferon-γ, and monocyte chemoattractant protein-1/CC chemokine ligand-2) and are increasingly expressed during such progression. In silico meta-analysis in a human breast cancer dataset suggests that proinflammatory activation in the mammary glands of these mice reflects a general pattern of human breast cancer

    Citrullination of histone H3 drives IL-6 production by bone marrow mesenchymal stem cells in MGUS and multiple myeloma

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    Multiple myeloma (MM), an incurable plasma cell malignancy, requires localisation within the bone marrow. This microenvironment facilitates crucial interactions between the cancer cells and stromal cell types that permit the tumour to survival and proliferate. There is increasing evidence that the bone marrow mesenchymal stem cell (BMMSC) is stably altered in patients with MM – a phenotype also postulated to exist in patients with monoclonal gammopathy of undetermined significance (MGUS) a benign condition that precedes MM. In this study, we describe a mechanism by which increased expression of peptidyl arginine deiminase 2 (PADI2) by BMMSCs in patients with MGUS and MM directly alters malignant plasma cell phenotype. We identify PADI2 as one of the most highly upregulated transcripts in BMMSCs from both MGUS and MM patients, and that through its enzymatic deimination of histone H3 arginine 26, PADI2 activity directly induces the upregulation of interleukin-6 (IL-6) expression. This leads to the acquisition of resistance to the chemotherapeutic agent, bortezomib, by malignant plasma cells. We therefore describe a novel mechanism by which BMMSC dysfunction in patients with MGUS and MM directly leads to pro-malignancy signalling through the citrullination of histone H3R26
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