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accession-icon GSE14004
Re-expression of GATA2 Cooperates with PPAR gamma Depletion to Revert the Adipocyte Phenotype
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The nuclear receptor PPAR gamma is required for adipocyte differentiation, but its role in mature adipocytes is less clear. Here we report that knockdown of PPAR gamma expression in 3T3-L1 adipocytes returned the expression of most adipocyte genes towards preadipocyte levels. Consistently, down regulated but not up regulated genes showed strong enrichment of PPAR gamma binding. Surprisingly, not all adipocyte genes were reversed and the adipocyte morphology was maintained for an extended period after PPAR gamma depletion. To explain this, we focused on transcriptional regulators whose adipogenic regulation was not reversed upon PPAR gamma depletion. We identified GATA2, a transcription factor whose down-regulation early in adipogenesis is required for preadipocyte differentiation, remaining low after PPAR gamma knockdown. Forced expression of GATA2 in mature adipocytes complemented PPAR gamma depletion and impaired adipocyte functionality with a more preadipocyte- like gene expression profile. Ectopic expression of GATA2 in adipose tissue in vivo had similar effect on adipogenic gene expression. These results suggest that PPAR gamma-independent down regulation of GATA2 prevents reversion of mature adipocytes after PPAR gamma depletion.

Publication Title

Re-expression of GATA2 cooperates with peroxisome proliferator-activated receptor-gamma depletion to revert the adipocyte phenotype.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP067359
Transcriptome sequencing of skeletal muscle for PRMT7 knockout mouse
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

We report that whole body PRMT7-/- adult mice display a significant reduction in in muscle mass. RNA sequencing was performed to identify potential PRMT7 targets. We found that top canonical pathways affected by the loss of PRMT7 includes cell cycle and senescence. Overall design: RNA was extracted from tibialis anterior muscles harvested from 3 WT and 3 PRMT7 null mice at 8months. RNA sequencing was performed to compare mRNA in skeletal muscles between WT and KO mice.

Publication Title

PRMT7 Preserves Satellite Cell Regenerative Capacity.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject

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accession-icon GSE144248
Cholesterol homeostasis modulates platinum sensitivity in human ovarian cancer
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Here we show that platinum-resistant ovarian cancer cells also show reduced cholesterol biosynthesis, and mostly rely on uptake of exogenous cholesterol for their needs. Expression of FDPS and OSC, enzymes involved in cholesterol synthesis, are decreased both in drug-resistant cells and upon TRAP1 silencing, whereas the expression of LDL receptor, the main mediator of extracellular cholesterol uptake, is increased. Strikingly, treatment with different statins to inhibit cholesterol synthesis reduces cisplatin-induced apoptosis, whereas silencing of LIPG, an enzyme involved in lipid metabolism, increases sensitivity to the drug.

Publication Title

Cholesterol Homeostasis Modulates Platinum Sensitivity in Human Ovarian Cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE29341
Gene expression profile changes upon knock-down of Pax8
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

In order to define the transcriptional network functionally regulated by Pax8 as well as infer its direct targets, we performed RNAi to knock-down Pax8 gene in FRTL-5 thyroid cells. Expression data from three independent silencing experiments were analyzed by microarray technology unraveling 2815 genes differentially expressed between silenced cells and controls. Of these, 1421 genes were down-regulated and 1394 genes were up-regulated 72hrs after Pax8 silencing.

Publication Title

Identification of novel Pax8 targets in FRTL-5 thyroid cells by gene silencing and expression microarray analysis.

Sample Metadata Fields

Cell line

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accession-icon GSE65144
Gene array analysis of anaplastic thyroid carcinoma tissue versus matched and unmatched normal thyroid tissue
  • organism-icon Homo sapiens
  • sample-icon 25 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Currently there is a lack of effective therapies which result in long-term durable response for patients presenting with anaplastic thyroid carcinoma (ATC), a very rare and lethal variant of thyroid cancer. ATC is resistant to chemotherapy, radiation, and targeted therapies currently available. In an effort to identify novel tumor-specific therapeutic targets, we performed high throughput gene array analysis screening numerous patient ATC tumor tissues, and compared their gene expression levels to matched and unmatched normal thyroid tissue samples.

Publication Title

Aberrant lipid metabolism in anaplastic thyroid carcinoma reveals stearoyl CoA desaturase 1 as a novel therapeutic target.

Sample Metadata Fields

Specimen part

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accession-icon SRP151272
RNA-Seq: Smad4-iECKO vs Smad4f/f P7 isolated retinal endothelial cells (iECKO=inducible, endothelial cell specific knockout)
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

To identify potential biological targets of the TGFß pathway involved in AVM formation, we performed RNA-seq on endothelial cells (ECs) isolated from a Smad4 inducible, EC specific knockout (Smad4-iECKO; Smad4f/f;Cdh5-CreERT2) mouse model that develops retinal AVMs. Overall design: We sequenced a total of 6 samples. We used three wild type samples (Smad4f/f- samples names: Lit38s45, Lit38s6, Lit40s56) and three mutant samples (Smad4f/f;Cdh5-CreERT2- sample names: Lit38s12, Lit38s37, Lit40s12). For more detailed information please see supplemental document: GSE116230_Smad4ff_vs_Smad4iECKO.report.pdf

Publication Title

Angiopoietin-2 Inhibition Rescues Arteriovenous Malformation in a Smad4 Hereditary Hemorrhagic Telangiectasia Mouse Model.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE30427
Expression analysis of mouse thyroid tumors
  • organism-icon Mus musculus
  • sample-icon 31 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Anaplastic thyroid carcinoma (ATC) is the most aggressive form of thyroid cancer, and often derives from pre-existing well-differentiated tumors. We have engineered the first mouse model of ATC by combining in the mouse thyroid follicular cells two molecular hallmarks of human ATC: activation of PI3K (via Pten deletion) and inactivation of p53. By 9 months of age, over 75% of the compound mutant mice develop aggressive, undifferentiated thyroid tumors that evolve from pre-existing follicular hyperplasia and carcinoma. These tumors display all the features of their human counterpart, including pleomorphism, epithelial-mesenchymal transition, aneuploidy, local invasion and distant metastases.

Publication Title

Thyrocyte-specific inactivation of p53 and Pten results in anaplastic thyroid carcinomas faithfully recapitulating human tumors.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE7529
Two distinct gene signatures identify malignant Neuroblast and Schwannian stromal cells of Neuroblastic Tumors
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Tumor tissue heterogeneity is a well known feature of several solid tumors. Neuroblastic Tumors (NTs) is a group of paediatric cancers with a great tissue heterogeneity. Most of NTs are composed of undifferentiated, poorly differentiated or differentiating neuroblastic (Nb) cells with very few or absent Schwannian stromal (SS) cells: these tumors are grouped as Neuroblastoma (Schwannian stroma-poor). The remaining NTs are composed of abundant SS cells and classified as Ganglioneuroblastoma (Schwannian stroma-rich) intermixed or nodular and Ganglioneuroma. The importance to understand Nb and SS gene signatures in NTs, is to clarify the complex network mechanism of tumor growth and progression. In order to identify the Nb and SS cells gene signatures, we analyzed the gene expression profiling of 19 cases of neuroblastic tumors: 10 stroma poor (NTs-SP) and 9 stroma rich (NTs-SR), by high density oligonucleotide microarrays. Moreover, the analysis was performed in parallel on both whole and laser microdissected tumor samples: from 4 of 19 cases, was isolated different areas all composed of pure cellular populations.

Publication Title

Identification of low intratumoral gene expression heterogeneity in neuroblastic tumors by genome-wide expression analysis and game theory.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16130
Gene expression of TCR-alpha/beta CD4- CD8- human T cells
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The origin and function of human double negative (DN) TCR-alpha/beta T cells is unknown. They are thought to contribute to the pathogenesis of systemic lupus erythematosus because they expand and accumulate in inflamed organs. Here we provide evidence that human TCR-alpha/beta CD4- CD8- DN T cells derive exclusively from activated CD8+ T cells. Freshly isolated TCR-alpha/beta DN T cells display a distinct gene expression and cytokine production profile. DN cells isolated from peripheral blood as well as DN cells derived in vitro from CD8+ T cells, produce a defined array of pro-inflammatory mediators that includes IL-1, IL-17, IFN-gama, CXCL3, and CXCL2. These results indicate that, upon activation, CD8+ T cells have the capacity to acquire a distinct phenotype that grants them inflammatory capacity.

Publication Title

Human TCR-alpha beta+ CD4- CD8- T cells can derive from CD8+ T cells and display an inflammatory effector phenotype.

Sample Metadata Fields

Specimen part

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accession-icon SRP067737
Polycomb dysregulation in gliomagenesis targets a Zfp423-dependent differentiation network [RNA-Seq]
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Malignant gliomas constitute one of the most significant areas of unmet medical need, due to the invariable failure of surgical eradication and their marked molecular heterogeneity. Accumulating evidence has revealed a critical contribution by the Polycomb axis of epigenetic repression. However, a coherent understanding of the regulatory networks affected by Polycomb during gliomagenesis is still lacking. Here we integrate transcriptomic and epigenomic analyses to define Polycomb-dependent networks that promote gliomagenesis, validating them both in two independent mouse models and in a large cohort of human samples. We found that Polycomb dysregulation in gliomagenesis affects transcriptional networks associated to invasiveness and de-differentiation. The dissection of these networks uncovers Zfp423 as a crtitical Polycomb-dependent transcription factor whose silencing negatively impacts survival. The anti-gliomagenic activity of Zfp423 requires interaction with the SMAD proteins within the BMP signaling pathway, pointing to a novel synergic circuit through which Polycomb inhibits BMP signaling. Overall design: Transcriptomic analysis of two different stages of gliomagenesis

Publication Title

Polycomb dysregulation in gliomagenesis targets a Zfp423-dependent differentiation network.

Sample Metadata Fields

Specimen part, Cell line, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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