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accession-icon GSE93645
Comparative analysis of gene expression profile of pre-defined niches within demyelinated white matter in rats
  • organism-icon Rattus norvegicus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina ratRef-12 v1.0 expression beadchip

Description

Microenviromental niche characterization by comparative transcriptome profiling. The hypothesis tested in the present study was that unique properties of the perivascular niche within remyelinating white matter would create microenvironment that favor the alternative differentiation of oligodendrocyte precursor cells.

Publication Title

Injury-induced perivascular niche supports alternative differentiation of adult rodent CNS progenitor cells.

Sample Metadata Fields

Sex, Specimen part, Time

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accession-icon SRP051320
Bromodomain inhibition of the transcriptional coactivators CBP/EP300 as a therapeutic strategy to target the IRF4 network in multiple myeloma (RNA-Seq)
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Pharmacological inhibition of chromatin co-regulatory factors represents a clinically validated strategy to modulate oncogenic signaling through selective attenuation of gene expression. Here, we demonstrate that CBP/EP300 bromodomain inhibition preferentially abrogates the viability of multiple myeloma cell lines. Phenotypic effects are preceded by the direct transcriptional suppression of the lymphocyte-specific transcription factor IRF4 and the subsequent down-regulation of the IRF4 transcriptional program. Ectopic expression of IRF4 antagonizes the phenotypic effects of CBP/EP300 bromodomain inhibition and prevents the suppression of the IRF4 target c-MYC. These findings suggest that CBP/EP300 bromodomain inhibition represents a viable therapeutic strategy for targeting multiple myeloma and other lymphoid malignancies dependent on the IRF4 network. Overall design: Through the use of CBP/EP300 bromodomain inhibitors (CBP/EP300i), we demonstrate that MYC expression in BETi-resistant cells is dependent on CBP/EP300 bromodomains and that treatment with CBP/EP300i restores phenotypic sensitivity.

Publication Title

Bromodomain inhibition of the transcriptional coactivators CBP/EP300 as a therapeutic strategy to target the IRF4 network in multiple myeloma.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE38390
Expression data from leaves of GA-deficient and GA-insensitive transgenic poplar
  • organism-icon Populus tremula x populus alba
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Poplar Genome Array (poplar)

Description

We used whole-genome microarrays to identify differentially expressed genes in leaves of GA-deficient (35S::PcGA2ox) and/or GA-insensitive (35S::rgl1) transgenics as compared to WT poplar (717-1B4 genotype).

Publication Title

Roles of gibberellin catabolism and signaling in growth and physiological response to drought and short-day photoperiods in Populus trees.

Sample Metadata Fields

Specimen part

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accession-icon SRP007569
SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Monocytes are a heterogeneous cell population with subset-specific functions and phenotypes. The differential expression of CD14 and CD16 distinguishes classical CD14++CD16-, intermediate CD14++CD16+ and non-classical CD14+CD16++ monocytes. However, CD14++CD16+ monocytes remain the most poorly characterized subset so far. Therefore we analyzed the transcriptomes of the three monocyte subsets using SuperSAGE in combination with high-throughput sequencing. Analysis of 5,487,603 tags revealed unique identifiers of CD14++CD16+ monocytes, delineating these cells from the two other monocyte subsets. CD14++CD16+ monocytes were linked to antigen processing and presentation (e.g. CD74, HLA-DR, IFI30, CTSB), to inflammation and monocyte activation (e.g. TGFB1, AIF1, PTPN6), and to angiogenesis (e.g. TIE2, CD105). Therefore we provide genetic evidence for a distinct role of CD14++CD16+ monocytes in human immunity. Overall design: Human monocyte subsets (CD14++CD16-, CD14++CD16+, CD14+CD16++) were isolated from 12 healthy volunteers based on MACS technology. Total RNA from monocyte subsets was isolated and same aliquots from each donor and monocyte subset were matched for SuperSAGE. Three SuperSAGE libraries (CD14++CD16-, CD14++CD16+ and CD14+CD16++) were generated.

Publication Title

SuperSAGE evidence for CD14++CD16+ monocytes as a third monocyte subset.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP060499
Regulatory T cell modulation by CBP/EP300 bromodomain inhibition [RNA-seq]
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Genome-wide gene expression changes in response to CBP inhibitor treatment in Treg cells using RNA sequencing (RNA-seq). Overall design: Expression profiling by RNA-seq of Treg cells treated with DMSO or CBP inhibitor

Publication Title

Regulatory T Cell Modulation by CBP/EP300 Bromodomain Inhibition.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE66596
Regulatory T cell modulation by CBP/EP300 bromodomain inhibition [array]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Genome-wide gene expression changes in response to CBP inhibitor treatment in Treg cells using microarray.

Publication Title

Regulatory T Cell Modulation by CBP/EP300 Bromodomain Inhibition.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE73935
Expression data from A2780 cell line and wild type ovarian cancer cell line (with resistant sublines)
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The development of cytostatic-drug resistance renders chemotherapy ineffective in treating ovarian cancer, the most lethal gynaecological malignancy. In many cases, it is difficult to explain the development of drug resistance based on the expression patterns of genes known to be involved in this process. Microarray-based assays can provide information about new genes that are involved in the resistance to cytostatic drugs. This report describes alterations in the level of expression of genes in cisplatin- (CisPt), doxorubicin- (Dox), topotecan- (Top), and paclitaxel- (Pac) resistant variants of W1 and A2780 ovarian cancer cell lines. These drug-resistant variants of the W1 and A2780 cell lines were generated through the stepwise selection of cells tolerant of exposure to the indicated drugs at incrementally increased concentrations. Affymetrix GeneChip Human Genome Array Strips were used for hybridization assays. The genes with significantly altered expression levels (upregulated by more than fivefold or downregulated by less than fivefold relative to the level in the parental line) in the drug-resistant sublines were selected and were filtered using volcano plotting.

Publication Title

Microarray-based detection and expression analysis of extracellular matrix proteins in drug‑resistant ovarian cancer cell lines.

Sample Metadata Fields

Cell line

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accession-icon SRP044917
Discovery of biomarkers predictive of GSI response in triple negative breast cancer and adenoid cystic carcinoma
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Next generation sequencing was used to identify Notch mutations in a large collection of diverse solid tumors. NOTCH1 and NOTCH2 rearrangements leading to constitutive receptor activation were confined to triple negative breast cancers (TNBC, 6 of 66 tumors). TNBC cell lines with NOTCH1 rearrangements associated with high levels of activated NOTCH1 (N1-ICD) were sensitive to the gamma-secretase inhibitor (GSI) MRK-003, both alone and in combination with pacitaxel, in vitro and in vivo, whereas cell lines with NOTCH2 rearrangements were resistant to GSI. Immunohistochemical staining of N1-ICD in TNBC xenografts correlated with responsiveness, and expression levels of the direct Notch target gene HES4 correlated with outcome in TNBC patients. Activating NOTCH1 point mutations were also identified in other solid tumors, including adenoid cystic carcinoma (ACC). Notably, ACC primary tumor xenografts with activating NOTCH1 mutations and high N1-ICD levels were sensitive to GSI, whereas N1-ICD low tumors without NOTCH1 mutations were resistant. Overall design: Gene expression profiling for Notch-sensitive cancer cell lines using RNA-seq, each sample with triplicates

Publication Title

Discovery of biomarkers predictive of GSI response in triple-negative breast cancer and adenoid cystic carcinoma.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP057986
Context- and cell-type specific function of miR155-Socs1 interaction in immune regulation
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The microRNA (miRNA) dependent regulation of gene expression confers robustness to cellular phenotypes and controls responses to extracellular stimuli. Although a single miRNA can regulate expression of hundreds of target genes, it is unclear whether any of its distinct biological functions can be due to the regulation of a single target. To explore in vivo the function of a single miRNA-mRNA interaction, we mutated the 3'' UTR of a major miR-155 target SOCS1 to specifically disrupt its regulation by miR-155. We found that under physiologic conditions and during autoimmune inflammation or viral infection some immunological functions of miR-155 were fully or largely attributable to the regulation of SOCS1, whereas others could be accounted only partially or not at all by this interaction. Our data suggest that the role of a single miRNA-mRNA interaction is cell type- and biological context-dependent. Overall design: Naïve WT, SOCS1KI and miR-155KO OVA-specific OT-1 TCR transgenic CD8+ T cells (1x10e4 per mouse) were adoptively transferred into CD45.1+ wt mice prior to infection with MCMV-OVA. WT, SOCS1KI and miR-155KO NK cells (2x10e5 per mouse) were adoptively transferred into CD45.1+ Klra8KO (Ly49H-deficient) mice prior to infection with MCMV. On d4 post infection, CD45.2+ CD44+ CD8+ OT-1 and CD45.2+ Ly49H+ NK1.1+ CD3- NK cells were FACS-sorted (BD FACS ARIA2). Each condition has 3 sequencing replicates.

Publication Title

A Single miRNA-mRNA Interaction Affects the Immune Response in a Context- and Cell-Type-Specific Manner.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP153037
Response of triple negative breast cancer to BAZ2A/B inhibition and BET bromodomain inhibition alone and in combination (RNAseq)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Three triple negative breast cancer cell lines (MDAMB231, SUM159, and HCC1806) were treated with small molecule inhibitors (JQ1, BET bromodomain inhibitor; GSK2801, BAZ2A/B bromodomain inhibitor) alone and in combination for 72 hours Overall design: 12 experimental samples

Publication Title

GSK2801, a BAZ2/BRD9 Bromodomain Inhibitor, Synergizes with BET Inhibitors to Induce Apoptosis in Triple-Negative Breast Cancer.

Sample Metadata Fields

Cell line, Treatment, 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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Developed by the Childhood Cancer Data Lab

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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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