The concept of tumor stem cells (TSCs) provides a new paradigm for understanding tumor biology, although it remains unclear whether TSCs will prove to be a more robust model than traditional cancer cell lines. We demonstrate marked phenotypic and genotypic differences between primary human tumor-derived TSCs and their matched glioma cell lines. TSCs derived directly from primary glioblastomas harbor extensive similarities to normal NSC and recapitulate the genotype, gene expression patterns and in vivo biology of human glioblastomas. By contrast, the matched, traditionally grown tumor cell lines do not secondary to in vitro genomic alterations. These findings suggest that TSCs may be a more reliable model than many commonly utilized cancer cell lines for understanding the biology of primary human tumors. Analysis of gene expression data is described in Lee et al., Cancer Cell, 2006.
Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines.
No sample metadata fields
View SamplesGliomas are mostly incurable secondary to their diffuse infiltrative nature. Thus, specific therapeutic targeting of invasive glioma cells is an attractive concept. As cells exit the tumor mass and infiltrate brain parenchyma, they closely interact with a changing micro-environmental landscape that sustains tumor cell invasion.
Identification of molecular pathways facilitating glioma cell invasion in situ.
Specimen part
View SamplesGoal of experiment: Identification of differentially expressed immune genes from male and female BWF1 lupus-prone mice. (Female incidence is higher than male--attempting to find sex hormone regulated genes that may contribute to this difference). Whole spleen was taken from pre-lupus (4 months old) BWF1 (females are lupus-prone) male and female mice. Preparation of cDNA. Double-stranded cDNA was synthesized from purified RNA. The first strand was synthesized by incubating 5 g of RNA with 100 pg/ml T7-(dT)24 primer (HPLC purified DNA primer sequence: 5-GGCCAGTGAATTGTAATACG ACTCACTATAGGGAGGCGG-(dT)24 -3 Genset Corp, San Diego, CA) at 70C for 10 minutes. Samples were incubated for 1 hour at 42C with the following mix: 1X first strand buffer, 10 mM dithiothreitol, 500 M each dNTP, 200 U SuperScript II in diethylpyrocarbonate (DEPC)-treated water up to 20 l. Second strand synthesis was performed by incubating the first strand with the following mix for 2 hours at 16C: 1X second strand reaction buffer, 200 M dntps, 10 U E. coli DNA ligase, 40 U E coli DNA Polymerase I, 2 U of E. coli RNase H up to 150 l with DEPC-treated water (all reagents were contained in SuperScript Choice System for cDNA Synthesis, Invitrogen). A phenol/chloroform extraction was performed on the ds-cDNA preparation before biotin-labeled cRNA was generated. Synthesis and fragmentation of biotin-labeled cRNA (in vitro transcription). The ENZO BioArrayTM HighYieldTM RNA Transcript Labeling Kit (T7) (Enzo diagnostics, Inc., Farmingdale, NY) was used to produce large amounts of hybridizable biotin-labeled RNA targets by in vitro transcription from the ds-cDNA. The following mix was incubated at 37C for 5 hours: 1 g of ds-cDNA, 1X HY reaction buffer, 1X biotin labeled ribonucleotides, 1X dithiothreitol, 1X T7 RNA Polymerase. Biotin-labeled cRNA was run over RNeasy spin columns (Qiagen), quantified, and run on an agarose gel to visualize the size distribution of labeled transcripts. Twenty micrograms of cRNA was incubated with 1X fragmentation buffer for 35 minutes at 94C. (5X fragmentation buffer: 200 mM Tris-acetate, pH 8.1, 500 mM KOAc, 150 mM MgOAc). After fragmentation, the samples were stored at -20C until the hybridization was performed. Sample hybridization. Oligonucleotide microarrays (MGU74v2 A, B, and C GeneChip probe arrays; Affymetrix) were hybridized with labeled cRNA derived from spleens from individual mice. For each array,15 g of fragmented cRNA was mixed with a hybridization cocktail consisting of 1X hybridization buffer (2X hybridization buffer: 100 mM MES, 1 M [Na+], 20 mM EDTA, 0.01% Tween), 0.5 mg/ml acetylated BSA (Invitrogen), 0.1 mg/ml herring sperm DNA (Promega), and water (BioWhittaker) up to 300 l). Biotin labeled cRNA transcripts of the E. coli and P1 bacteriophage genes, BioB, bioC, bioD, and cre (GeneChip Eukaryotic Hybridization control kit, Affymetrix) were spiked into each hybridization mix at 1.5, 5, 25, and 100 pM to evaluate sample hybridization efficiency for each array. The hybridization cocktail was heated to 99C and then 45C for 5 minutes each before it was centrifuged to remove any insoluble material. The array was equilibrated to room temperature, moistened with 1X hybridization buffer, and incubated for 10 minutes at 45C with rotation. After incubation, the buffer solution was removed from the array. The array was filled with 300 l of the hybridization cocktail, placed in a rotisserie box in a 45C oven, and incubated for 16 hours while rotating at 60 rpm. Washing and staining of array. The hybridization cocktail was removed and the GeneChip Fluidics Station 400 (Affymetrix) with Microarray Suite software (Affymetrix) was used to wash and stain the probe arrays with the following protocol: 10 cycles of 2 mixes/cycle with wash buffer A at 25C, 4 cycles of 15 mixes/cycle with wash buffer B at 50C, 30 minute incubation with staining solution at 25C, 10 cycles of 4 mixes/cycle with wash buffer A at 25C. Wash buffer A -- non-stringent wash buffer (6X sodium chloride sodium phosphate + ethylenediaminetetraacetic acid (SSPE), 0.01% Tween-20). (20X SSPE: 3 M NaCl, 0.2 M NaH2PO4, 0.02 EDTA) (BioWhittaker). Wash buffer B stringent wash buffer (100mM MES, 0.1 M [Na+], 0.1% Tween 20). Staining solution (1X 2-(N-Morpholino)ethanesulfonic Acid (MES) stain buffer, 2 mg/ml acetylated BSA, 10 g/ml Streptavidin Phycoerythrin (SAPE), and water up to 600 l). (12X MES stain buffer: 1.22 M MES, 0.89 M [Na+]). Analysis. After staining, the probe arrays were scanned using the GeneChip 3000 Scanner (Affymetrix) with Microarray Suite software (Affymetrix). Technical and assay variation between arrays was corrected for by multiplying or dividing the overall intensity of each array by a scaling factor so that the overall intensity of each array was equivalent to facilitate comparison analysis.
Identification of candidate genes that influence sex hormone-dependent disease phenotypes in mouse lupus.
No sample metadata fields
View SamplesThis is Rembrandt gene expression data (Affymetrix HG-U133Plus2).
Rembrandt: helping personalized medicine become a reality through integrative translational research.
Specimen part, Disease, Disease stage
View SamplesTranscriptome analysis of growth hormone dependant genes in glomerular podocytes
Growth hormone (GH)-dependent expression of a natural antisense transcript induces zinc finger E-box-binding homeobox 2 (ZEB2) in the glomerular podocyte: a novel action of gh with implications for the pathogenesis of diabetic nephropathy.
Specimen part, Treatment
View SamplesAnalyses of six Ts1Cje (Down syndrome) and six normal littermate (2N) mouse brains at postnatal day 0.
Dosage-dependent over-expression of genes in the trisomic region of Ts1Cje mouse model for Down syndrome.
No sample metadata fields
View SamplesAnalyses of six Ts1Cje (Down syndrome) and six normal littermate (2N) mouse brains at postnatal day 0.
Dosage-dependent over-expression of genes in the trisomic region of Ts1Cje mouse model for Down syndrome.
No sample metadata fields
View SamplesAnalyses of six Ts1Cje (Down syndrome) and six normal littermate (2N) mouse brains at postnatal day 0.
Dosage-dependent over-expression of genes in the trisomic region of Ts1Cje mouse model for Down syndrome.
No sample metadata fields
View SamplesWe developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer.
An integrated approach to uncover drivers of cancer.
Cell line
View SamplesThe key lipid metabolism transcription factor sterol regulatory element-binding protein (SREBP)-1a integrates gene regulatory effects of hormones, cytokines, nutrition and metabolites as lipids, glucose or cholesterol via stimuli specific phosphorylation by different MAPK cascades. We have formerly reported the systemic impact of phosphorylation in transgenic mouse models with liver-specific overexpression of the N-terminal transcriptional active domain of SREBP-1a (alb-SREBP-1a) or a MAPK kinase phosphorylation sites deficient variant (alb-SREBP-1aP; (S63A, S117A, T426V)), respectively. Here we investigated the molecular basis of the systemic observation in holistic hepatic gene expression analyses and lipid degrading organelles involved in the pathogenesis of metabolic syndrome, i.e. peroxisomes, by 2D-DIGE and mass spectrometry analyses. Although alb-SREBP-1a mice develop a severe phenotype with visceral adipositas and hepatic lipid accumulation featuring a fatty liver, the hepatic differential gene expression and alterations in peroxisomal protein patterns compared to control mice were surprisingly relative low. In contrast, phosphorylation site deficient alb-SREBP-1aP mice, protected from hepatic lipid accumulation phenotype, showed gross alteration in hepatic gene expression and peroxisomal proteome. Further knowledge based analyzes revealed that overexpression of SREBP-1a favored mainly acceleration in lipid metabolism and indicated a regular insulin signaling, whereas disruption of SREBP-1a phosphorylation resulted in massive alteration of cellular processes including signs for loss of lipid metabolic targets. These results could be the link to a disturbed lipid metabolism that overall resembles a state of insulin resistance.
Inactivation of SREBP-1a Phosphorylation Prevents Fatty Liver Disease in Mice: Identification of Related Signaling Pathways by Gene Expression Profiles in Liver and Proteomes of Peroxisomes.
Sex, Age, Specimen part
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