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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 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

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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

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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

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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

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accession-icon GSE84564
NK cell response to IL2 in vitro
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Here we analyzed the transcriptional response to IL2 in NK cells in vitro.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE84561
B cell response to IFNa in vitro
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Here we analyzed thetranscriptional response to IFNa in activated B cells in vitro. We found robust induction of ISGs as early as 2hrs.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE84566
CD4+ T cell response to IFNa in vitro
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Here we analyzed the transcriptional response to IFNa in activated CD4+ T cells in vitro. We found robust induction of ISGs as early as 2hrs.

Publication Title

Network pharmacology of JAK inhibitors.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
...

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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