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accession-icon GSE64321
Differential expression of Rice genes upon Rhodotorula treatment
  • organism-icon Oryza sativa
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice (Chinese Build) Gene 1.0 ST Array (rcngene10st)

Description

The experiments were performed to understand the molecular basis of plant growth promotion in rice by Rhodotorula mucilaginosa JGTA-S1, an endophytic yeast from Typha angustifolia

Publication Title

Early changes in shoot transcriptome of rice in response to Rhodotorula mucilaginosa JGTA-S1.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE63558
Mesenchymal cancer cell-stromal crosstalk promotes niche activation, epithelial reversion and metastatic colonization
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

The experiment was design to address the intrinsic differences between metastatic cancer stem cells in the primary tumour and during metastatic colonization in the mouse mammary gland tumour model MMTV-pyMT.

Publication Title

Mesenchymal Cancer Cell-Stroma Crosstalk Promotes Niche Activation, Epithelial Reversion, and Metastatic Colonization.

Sample Metadata Fields

Specimen part

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accession-icon SRP062569
Transcriptome analysis upon overexpression of SIN3 187HA in Drosophila cultured cells
  • organism-icon Drosophila melanogaster
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

SIN3 is a master transcriptional scaffold protein. SIN3 interacts with RPD3 and other accessory proteins to form a histone modifying complex. A single Sin3A gene encodes multiple isoforms of SIN3, of which SIN3 187 and SIN3 220 are the predominant isoforms. Previous studies demonstrated that SIN3 isoforms play non-redundant roles during fly development. In the current study, we sought to investigate the genes regulated by SIN3 187. Overall design: S2 cells and cells carrying a stable transgene of SIN3 187HA (SIN3 187HA cells) were treated with 0.07 µM CuSO4. CuSO4 treatment led to ectopic expression of SIN3 187HA. S2 cells were used as a control. Following induction, total mRNA was extracted. mRNA profiling of these samples were performed by deep sequencing using Illumina Hiseq2500. Three biological replicates were performed.

Publication Title

Genome-wide studies reveal novel and distinct biological pathways regulated by SIN3 isoforms.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE39339
Expression data from glucocorticoid-treated ALL
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Erg and AP-1 as determinants of glucocorticoid response in acute lymphoblastic leukemia.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Cell line, Treatment, Subject, Time

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accession-icon GSE39335
Expression data from glucocorticoid-treated ALL (BCR-ABL patients)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The beneficial effects of glucocorticoids (GCs) in acute lymphoblastic leukemia (ALL) are based on their ability to induce apoptosis. Omics technologies such as DNA microarray analysis are widely used to study the changes in gene expression and have been successfully implemented in biomarker identification. In addition, time series studies of gene expression enable the identification of correlations between kinetic profiles of glucocorticoid receptor (GR) target genes and diverse modes of transcriptional regulation. This study presents a genome-wide microarray analysis of both our and published Affymetrix HG-U133 Plus 2.0 data in GCs-sensitive and -resistant ALL. GCs-sensitive CCRF-CEM-C7-14 cells were treated with dexamethasone at three time points (0 h, 2 h and 10 h). The treated samples were then compared to the control (0 h).

Publication Title

Erg and AP-1 as determinants of glucocorticoid response in acute lymphoblastic leukemia.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Treatment, Subject, Time

View Samples
accession-icon GSE39338
Expression data from glucocorticoid-treated ALL (CCRF-CEM-C7-14 cells)
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The beneficial effects of glucocorticoids (GCs) in acute lymphoblastic leukemia (ALL) are based on their ability to induce apoptosis. Omics technologies such as DNA microarray analysis are widely used to study the changes in gene expression and have been successfully implemented in biomarker identification. In addition, time series studies of gene expression enable the identification of correlations between kinetic profiles of glucocorticoid receptor (GR) target genes and diverse modes of transcriptional regulation. This study presents a genome-wide microarray analysis of both our and published Affymetrix HG-U133 Plus 2.0 data in GCs-sensitive and -resistant ALL. GCs-sensitive CCRF-CEM-C7-14 cells were treated with dexamethasone at three time points (0 h, 2 h and 10 h). The treated samples were then compared to the control (0 h).

Publication Title

Erg and AP-1 as determinants of glucocorticoid response in acute lymphoblastic leukemia.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Time

View Samples
accession-icon GSE19472
Esophageal keratinocyte invasion after loss of E-cadherin and TGF receptor type II
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Esophageal cancer is one of the deadliest cancers as patients present at late stages of disease. Frequent gene alterations include the loss of E-cadherin and TGFb receptor type II. The goal of this study was to establish a model of esophageal cancer by introducing dominant-negative mutants of E-cadherin and TGFb receptor II.

Publication Title

Imbalance of desmoplastic stromal cell numbers drives aggressive cancer processes.

Sample Metadata Fields

Cell line

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accession-icon GSE36776
Genome wide analysis of skin cancer cell gene expresison exposed to stromal cancer associated fibroblasts in 3D gel matrix
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

SCC12 cells were seeded ontop of organotypic gels with HN-CAF (head and neck carcinoma associated fibroblasts). Differential gene expression was analysed between cancer cells not exposed to CAFs or non-invading cancer cells exposed to CAFs.

Publication Title

Imbalance of desmoplastic stromal cell numbers drives aggressive cancer processes.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE18859
Gene expression in the colon of DSS-treated Pglyrp1-/-, Pglyrp2-/-, Pglyrp3-/-, and Pglyrp4-/- mice
  • organism-icon Mus musculus
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Pglyrp1-/-, Pglyrp2-/-, Pglyrp3-/-, and Pglyrp4-/- mice are all more sensitive than wild type (WT) mice to dextran sulfate sodium (DSS)-induced colitis. The purpose of this study was to determine which genes are differentially induced by DSS treatment in the colon of Pglyrp1-/-, Pglyrp2-/-, Pglyrp3-/-, and Pglyrp4-/- mice compared to WT mice. The results demonstrate higher induction of proinflammatory gene expression in Pglyrp1-/-, Pglyrp2-/-, Pglyrp3-/-, and Pglyrp4-/- mice than in WT mice after DSS treatment. The majority of genes whose expression is increased in Pglyrp1-/-, Pglyrp2-/-, Pglyrp3-/-, and Pglyrp4-/- mice but not in WT mice are interferon-inducible genes. Thus, Peptidoglycan Recognition Proteins Pglyrp1, Pglyrp2, Pglyrp3, and Pglyrp4 protect mice from excessive inflammatory response and damage to the colon by limiting expression of interferon-inducible genes in the colon.

Publication Title

Peptidoglycan recognition proteins protect mice from experimental colitis by promoting normal gut flora and preventing induction of interferon-gamma.

Sample Metadata Fields

Specimen part

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accession-icon GSE30296
Changes in follistatin levels by BRCA1 may serve as a regulator of ovarian carcinogenesis
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Follistatin is a folliculogenesis regulating protein that has been found in relatively high concentration in the female ovarian tissues. Follistatin acts as an antagonist to the function of Activin, which is often found elevated in ovarian carcinogenesis and thus presents a possibility for therapeutic intervention in controlling ovarian cancer. Most of the ovarian cancer occurs in its ovarian surface epithelium (OSE) cells. Although breast cancer susceptibility gene 1 (BRCA1) is a known tumor suppressor for breast cancer but its role in ovarian cancer is beginning to unfold. We have shown that in ovarian carcinoma cells (SKOV3), stable overexpression of BRCA1 stimulates Follistatin secretion and simultaneously downregulates Activin expression. Moreover, knock down of BRCA1 in immortalized OSE (IOSE) cells from human ovarian tissue demonstrates downregulation of Follistatin secretion with simultaneous up regulation of Activin expression. IOSE cells generated from an ovarian cancer patient with BRCA1 mutation failed to secrete Follistatin in the medium. Our results indicate a novel function for BRCA1 in the form of regulation of the expression of Follistatin in the ovarian cells.

Publication Title

BRCA1 regulates follistatin function in ovarian cancer and human ovarian surface epithelial cells.

Sample Metadata Fields

Specimen part, Cell line

View Samples
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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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