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accession-icon SRP162188
Bulk RNA-seq U2OS cells treated with small molecules
  • organism-icon Homo sapiens
  • sample-icon 68 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

We report the transcriptional changes associated with treatment of U2OS osteosarcoma cell line with DMSO, AML108, AMN107, BGW675, JAA804, LEE837 and LHD510. Overall design: U2OS cells were treated with 100nM, 1000nM and 10000nM of DMSO, AML108, AMN107, BGW675, JAA804, LEE837 and LHD510 for 12 hrs and subjected to RNA-seq.

Publication Title

DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

View Samples
accession-icon GSE29156
Serous ovarian benign tumor and type II carcinoma data set for expression and paracrine signaling investigation
  • organism-icon Homo sapiens
  • sample-icon 72 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

A data set of normal epithelium, serous ovarian surface epithelial-stromal tumors (benign and type II malignancies), stroma distal to tumor, and stroma adjacent to tumor (50 samples total). Additional cel files are included which represent replicate sampling from patients, and cel files that failed quality control but may be bioinformatically interesting. Additional replicate or failed cel files were not included in the final analysis (and so these samples were not included in the matrix).

Publication Title

Dysregulation of AKT3 along with a small panel of mRNAs stratifies high-grade serous ovarian cancer from both normal epithelia and benign tumor tissues.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE65018
The epithelial cell transcriptome after alpha-toxin treatment
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Responsiveness of cells to alpha-toxin (Hla) from Staphylococcus aureus appears to occur in a cell-type dependent manner. Here, we compare two human bronchial epithelial cell lines, i.e. Hla-susceptible 16HBE14o- and Hla-resistant S9 cells, by a quantitative multi-omics strategy for a better understanding of Hla-induced cellular programs. Phosphoproteomics revealed a substantial impact on phosphorylation-dependent signaling in both cell models and highlights alterations in signaling pathways associated with cell-cell and cell-matrix contacts as well as the actin cytoskeleton as key features of early rHla-induced effects. Along comparable changes in down-stream activity of major protein kinases significant differences between both models were found upon rHla-treatment including activation of EGFR and MAPK1/3 signaling in S9 and repression in 16HBE14o- cells. System-wide transcript and protein expression profiling indicate induction of an immediate early response in either model. In addition, EGFR and MAPK1/3-mediated changes in gene expression suggest cellular recovery and survival in S9 cells but cell death in 16HBE14o- cells. Strikingly, inhibition of the EGFR sensitized S9 cells to Hla indicating that the cellular capacity of activation of the EGFR is a major protective determinant against Hla-mediated cytotoxic effects.

Publication Title

A multi-omics approach identifies key hubs associated with cell type-specific responses of airway epithelial cells to staphylococcal alpha-toxin.

Sample Metadata Fields

Cell line

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accession-icon SRP033095
Transcriptome analysis reveals differential splicing events in IPF lung tissue
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Objectives: Idiopathic pulmonary fibrosis (IPF) is a complex disease in which a multitude of proteins and networks are disrupted. Interrogation of genome-wide transcription through RNA sequencing (RNA-Seq) enables the determination of genes whose differential expression is most significant in IPF, as well as the detection of alternative splicing events which are not easily observed with traditional microarray experiments. Methods: Messenger RNA extracted from 8 IPF lung samples and 7 healthy controls was sequenced on an Illumina HiSeq. Analysis of differential expression and exon usage was performed using Bioconductor packages. The gene periostin was selected for validation of alternative splicing by quantitative PCR, and pathway analysis was performed to determine enrichment for differentially expressed and spliced genes. Results: There were 873 genes differentially expressed in IPF (FDR 5%), and 440 unique genes had significant differential splicing events (FDR 5%). In particular, cassette exon 21 of the gene periostin was significantly more likely to be spliced out in IPF samples (adj pval = 2.06e-09), and this result was confirmed by qPCR (Wilcoxon pval = 3.11e-4). We also found that genes close to SNPs in the discovery set of a recent IPF GWAS were enriched for genes differentially expressed in our data, including genes like mucin5B and desmoplakin which have been previously associated with IPF. Conclusions: There is significant differential splicing and expression in IPF lung samples as compared with healthy controls. We found a strong signal of differential cassette exon usage in periostin, an extracellular matrix protein whose increased gene-level expression has been associated with IPF and its clinical progression, but for which differential splicing has not been studied in the context of IPF. Our results suggest that alternative splicing of periostin and other genes may be involved in the pathogenesis of IPF. Overall design: mRNA sequencing of 8 IPF and 7 control lung tissue samples.

Publication Title

Transcriptome analysis reveals differential splicing events in IPF lung tissue.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP046732
RNA-Seq analysis of mouse small intestine enteroendocrine cells
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

We generated knock-in mice expressing GFP under the control of the endogenous GIP (Glucose-dependent Insulinotropic Polypeptide) promoter that enable the isolation of a purified population of small intestine K cells. Using RNA-Seq, we comprehensively characterized the transcriptomes of GIP-GFP cells as well as the entire enteroendocrine lineage derived from Neurogenin3 (Ngn3)-expressing progenitors. Overall design: We interrogated the whole transcriptome of FACS-isolated small intestine GIPGFP cells using high-throughput mRNA sequencing. We also obtained the global gene expression patterns of the entire enteroendocrine cell lineage as well as the non-enteroendocrine cell population, comprising enterocytes, goblet cells and Paneth cells. To achieve this, small intestine epithelial cells from male mice resulting from the breeding of Neurogenin3 (Ngn3)-Cre mice with ROSA26-LoxP-STOP-LoxP-tomato indicator mice were isolated based on Tomato fluorescence and negative staining for CD45. Due to the small cell numbers, we constructed each of the three RNA-Seq libraries (GIPGFP, Ngn3TOMATO, and Ngn3-) using a pool of equal amounts of individual RNA samples without RNA amplification.

Publication Title

RNA-Seq analysis of enteroendocrine cells reveals a role for FABP5 in the control of GIP secretion.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE84568
Immuno-genomic effects of JAK blockade
  • organism-icon Mus musculus
  • sample-icon 332 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part, Compound

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accession-icon GSE84853
Immuno-genomic effects of JAK blockade in vivo
  • organism-icon Mus musculus
  • sample-icon 238 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Small molecule inhibitors of JAK kinases have shown clinical effcacy in the treatment of certain autoimmune diseases. While these are known to block upstream JAK signalling events, their broader impact on the transcriptional footprint in immunocytes are unknown. Here we explore the effects of pan- and isoform-specific JAK blockade on the immuno-genomic network by genomic profiling.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part, Compound

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accession-icon GSE84560
Effect of JAK blockade on IFNa response in B cells in vitro
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

B cells respond robustly to type 1 interferons which signal through JAK1 and TYK2. Here we analyzed the effects of a panel of JAK inhibitors on the IFNa transcriptional response in activated B cells in vitro.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE84562
Effect of JAK1/3 blockade on IL2 response in NK cells
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

IL2 signals are transmitted through JAK1 and JAK3, but the transcriptomic consequences of each to the overall response is unclear. Here we analyzed the relative contribution of JAK1 and JAK3 to the NK cell IL2 response in vitro using titrated doses of isoform specific JAK inhibitors. Blockade of JAK1 and JAK3 have unequal effects on IL2-induced transcripts at pharmacologically relevant doses.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE84565
Effect of JAK blockade on IFNa response in CD4+ T cells in vitro
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

CD4+ T cells respond robustly to type 1 interferons which signal through JAK1 and TYK2. Here we analyzed the effects of a panel of JAK inhibitors on the IFNa transcriptional response in activated CD4+ T cells in vitro.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part

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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