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  • The changes in transcript titers are described for Drosophila CME W1 Cl.8+ cells following 5-48 hr treatment with 20-hydroxyecdysone. Keywords: hormone response RNA from ecdysone-treated cells was compared to RNA from cells treated with carrier alone. A total of 4 slides were analyzed for each time point, each from a separate biological sample; dye-swaps were included.
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  • The changes in transcript titers are described for Drosophila ML-DmBG3-c2 cells following 5-48 hr treatment with 20-hydroxyecdysone. Keywords: hormone response RNA from ecdysone-treated cells was compared to RNA from cells treated with carrier alone. A total of 4 slides were analyzed for each time point, each from a separate biological sample; dye-swaps were included.
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  • Transcriptional profiling of Saccharomyces cerevisiae cells comparing the W303-1A wildtype with the W303-1A double mutant for MSN2 and MSN4 during zinc deficient conditions Keywords: Genetic modification with zinc limitation Two condition experiment, W303-1A vs W303-1A delta MSN2, MSN4. Biological replicates: 2 wildtype, 2 knock-out, independently grown and harvested.
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  • A customized targeted oligoarray was used to monitor the expression levels of 1000 genes, representative of the immature kernel transcriptome. Using this oligoarray we compared transcripts from 10 DAP kernels of two susceptible and two drought tolerant genotypes. These four genotypes were extracted from our RIL population (B73xH99) and grown under water stress and well watered field conditions. Keywords: Stress response Two-condition experiment: water stress field condition vs. well watered field condition. Transcriptional profiling of 10 DAP kernel (two susceptible and two drought tolerant genotypes) in the first condition vs 10 DAP kernel (two susceptible and two drought tolerant genotypes) in the second condition. Hybridization replicates: 4 in dye swap mode. Two probes per gene per array.
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  • Background: Lymphotoxin signaling via the lymphotoxin-β receptor (LTβR) has been implicated in several biological processes, ranging from development of secondary lymphoid organs, maintenance of splenic tissue, host defense against pathogens, autoimmunity, and lipid homeostasis. The major transcription factor that is activated by LTβR crosslinking is NF-κB. Two signaling pathways have been described that result in the activation of classical p50-RelA and alternative p52-RelB NF-κB heterodimers. Results: Using microarray analysis, we investigated the transcriptional response downstream of the LTβR in mouse embryoni fibroblasts (MEF) and its regulation by the RelA and RelB subunits of NF-κB. We describe novel LTβR-responsive genes that are regulated by RelA and/or RelB. Interestingly, we found that the majority of LTβR-regulated genes require the presence of both RelA and RelB, suggesting significant crosstalk between the two NF-κB activation pathways. Gene Ontology (GO) analysis confirmed that LTβR-NF-κB target genes are predominantly involved in the regulation of immune responses. However, other biological processes, such as apoptosis/cell death, cell cycle, angiogenesis, and taxis were also regulated by LTβR signaling. Moreover, we show that activation of the LTβR inhibits the expression of a key adipogenic transcription factor, peroxisome proliferator activated receptor-γ (pparg), suggesting that LTβR signaling may interfere with adipogenic differentiation. Conclusions: Thus, microarray analysis of LTβR-stimulated fibroblasts revealed further insight into the transcriptional response of LTβR signaling and its regulation by the NF-κB family members RelA and RelB. Keywords: cell type comparison (wt vs relA-/- vs relB-/-) after genetic modification using a time course for each cell type (wt, relA-/-, relB-/-) two time points were analysed (0h as control and 10h) using 3 technical replicates resulting in 18 samples in total
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  • Mice were fed for 6 months with a normal chow (NC) or a high fat diet (HFD). After 6 months of diet, high fat fed mice with Low, Medium and High body weight, but with similar glucose intolerance, were selected. These selected mice as well as NC mice were then treated with Rimonabant or Vehicle for 1 month. After treatment, mice were sacrificed and visceral and subcutaneous adipose tissues were collected and immediately frozen in liquid nitrogen. Total RNA from each sample was further extracted, purified, quality-controled before and after amplification, Cy5-labeled and co-hybridized with a Cy3-labeled mouse Universal Reference total RNA on the mouse 17K microarray. Keywords: diet response, pharmacological response Each individual RNA sample was hybridized with a mouse Universal Reference Total RNA
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  • In this study we analyzed the gene expression profiles of human monocytes and monocyte-dervied-macrophages. Keywords: Gene expression profiling Blood samples were obtained from 86 patients with symptoms of acute coronary syndrome who had undergone coronary angiography at the department of cardiology of the Pitié-Salpêtrière Hospital, Paris and who had on stenosis > 50 % diagnosed in at least one major coronary artery. 48 monocyte and 48 macrophage samples (38 pools of 2 samples and 10 individual samples for each type of RNA) were hybridized to the RNG/MRC platform.
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  • Expression profiling of breast cancer tumours, comparing 10 year survivors to deceased patients Background It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. Methods 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used to evaluate the gene lists on the different data sets, a correlation-based classifier and a VFI (Voting Features Interval) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients which had developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. Results A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). Conclusion The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients should have had different adjuvant treatment than they did. Keywords: Expression Microarray, Lymph-node-negative Breast Cancer, Clinical Outcome, Classification 23 fresh frozen primary node negative breast cancer tumours from 10 year survivors were compared to 23 tumours from deceased patients in order to find genes where the expression differed between the two groups Microarrays were produced at the Swegene DNA Microarray Resource Center, Department of Oncology, Lund University, Sweden (http://swegene.onk.lu.se). Frozen tumours were homogenized together with TRIzol Reagent (Invitrogen, Carlsbad, CA, USA). From the cell-suspension total RNA was extracted using RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s protocol. The quality of the RNA was evaluated with the Agilent 2100 BioAnalyser (Agilent Technologies, Palo Alto, CA, USA). Specimens where the 28S/16S ratio was lower than 1.0 or the RIN-value was lower than 6.7 were excluded from the study. For each sample, Cy3-dCTP (Amersham Biosciences, Buckinghamshire, UK) labelled probes were synthesized from 5 µg of the total tumour RNA and Cy5-dCTP (Amersham Biosciences) labelled reference were synthesized from 5 µg of commercial reference RNA (Universal Human Reference RNA, Stratagene, La Jolla, CA, USA) by reverse transcription. The probes were purified using ChipShot™ labelling cleanup system (Promega, Madison, WI, USA). The hybridizations were carried out using Pronto! Micro Array reagent systems (Corning Inc., Corning, NY, USA). For each sample, labelled tumour cDNA and reference cDNA were co-precipitated and hybridised to the microarray slide. The microarray slides were scanned with Agilent microarray scanner G2565AA (Agilent Technologies) and image analysis was performed using the Genepix 6.0.0.45 software (Axon Instruments, Union City, CA, USA).
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  • Metastatic clear cell renal cell carcinoma (ccRCC) has a poor prognosis and unpredictable course and there are no molecular markers that reliably predict ccRCC metastasis. In this study, specimens from 84 patients with ccRCC were directly cultured in vitro. The primary cultures from 38 of 94 specimens contained more than 90% tumor cells at 4th passages. After identified by immunostaining, the primary cultures of metastatic- and nonmetastatic ccRCC specimens from the age-, gender-matched patients were subjected to cDNA microrray assays. A total of 842 differentially expressed genes with FDR (false discovery rate) = 4.79% were identified by using SAM (Significance Analysis of Microarray) software. Pathway enrichment and co-occurrence with “cancer”, “metastasis” and “invasion” in the literature annotations enriched the functions of the 842 genes and indicated the reliability of our microarray assays. Novel genes associated with metastasis were selected based on intra-molecular interaction between 205 differentially expressed genes co-occurred with “metastasis” and those not appeared with “metastasis” on Medline, as well as co-expression analysis between 205 differentially expressed genes co-occurred with “metastasis” and those not appeared on Medline in 12 microarray data. FSTL1, AV722783, SLC15A1, DDX17, ORC2L and PKMYT1 were proved to be potential ccRCC metastasis-associated novel genes, based on its expression patterns in the cultures and tumor tissues. Interestingly, the up-regulated genes (CAV1, PKMYT1 and ORC2L) were up-regulated and the down-regulated genes (FSTL1, GSTM3, CYR61, SLC15A1 and AV722783) were down-regulated, in the primary ccRCC specimens as compared with its adjacent normal kidney in 37 patients (determined by semi-quantitative RT-PCR). This study provides potential biomarkers and novel molecular targets for the early diagnosis and treatment of ccRCC metastasis. Keywords: Homo sapiens Because of limited cell number of primary cultures, total RNA of the primary cultures from 2 age and gender matched patients was pooled for each microarray assay. Each assay was technically repeated once. Cy3-labeled 1st cDNA synthesized from total RNA of the metastatic ccRCC pool was mixed with Cy5-labeled 1st cDNA synthesized from total RNA of the non-metastatic ccRCC pool, and hybridized to 16K cDNA chips (GEO Platform ID: GPL6259; SBC-R-HC-100-22, National Engineering Center for Biochip, Shanghai, China) that included 14784 unigenes, 241 negative controls and 527 positive controls. In our study we used a co-expression analysis for the relationship between genes; three gastric cancer Samples were only introduced to this analysis methods.
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  • Adenovirus e1a induces quiescent human cells to divide. We found that e1a causes global relocalization of the RB-proteins (RB, p130, p107) and p300/CBP histone acetyltransferases on promoters that restricts H3K18ac to a limited set of genes to stimulate cell cycling and inhibit antiviral responses and cellular differentiation. Soon after expression, e1a binds transiently to cell cycle/growth genes, causing enrichment of p300/CBP, PCAF, H3K18ac, depletion of RB-proteins, and transcriptional activation. e1a also associates transiently with antiviral genes, causing enrichment for RB, p130, H4K16ac, increased nucleosome density, and repression. At later times, e1a and p107 bind mainly to development/differentiation genes, repressing transcription. The temporal order of e1a binding required its interactions with p300/CBP and RB-proteins. Our data uncover a defined transcriptional and epigenetic reprogramming leading to cellular transformation. Expression profiles and ChIP on chip genomewide experiments with R2G mutant virus (expressing a mutated version of small e1a).
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