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accession-icon GSE37623
Analysis of transcriptome changes in HeLa cells after knock-down of variant U1.8 snRNA
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

U1 small nuclear (sn)RNA, required for splicing of pre-mRNA, is encoded by genes on chromosome 1p36. Imperfect copies of these true (t)U1 snRNA genes, located on chromosome 1q12-21, were thought to be pseudogenes. However, many of these variant (v)U1 snRNA genes produce fully-processed transcripts that are packaged into potentially functional particles. Using antisense oligonucleotides, we have achieved functional knockdown of a specific vU1 snRNA in HeLa cells and identified over 400 transcriptome changes following interrogation of the Affymetrix Human Exon ST 1.0 array.

Publication Title

Differentially expressed, variant U1 snRNAs regulate gene expression in human cells.

Sample Metadata Fields

Cell line

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accession-icon SRP077921
RNA sequencing of patient derived cell lines in pancreatic cancer
  • organism-icon Homo sapiens
  • sample-icon 70 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Gene expression levels of pancreatic cell lines Overall design: RNA was extracted from cell lines and subjected to 50bp paired-end RNA sequencing

Publication Title

Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE48931
Master regulators of FGFR2 signalling and breast cancer risk
  • organism-icon Homo sapiens
  • sample-icon 260 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Master regulators of FGFR2 signalling and breast cancer risk.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE48927
Over-expression of FGFR2b from a tetracycline-inducible expression vector
  • organism-icon Homo sapiens
  • sample-icon 125 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Genome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways

Publication Title

Master regulators of FGFR2 signalling and breast cancer risk.

Sample Metadata Fields

Cell line

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accession-icon GSE48925
Activation of FGFR2-kinase domain (iF2 construct)
  • organism-icon Homo sapiens
  • sample-icon 71 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Genome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways

Publication Title

Master regulators of FGFR2 signalling and breast cancer risk.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE48924
Stimulation of endogenous FGFR1b and FGFR2b
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Genome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways

Publication Title

Master regulators of FGFR2 signalling and breast cancer risk.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE48928
Knockdown of breast cancer master regulators: siRNA targeting PTTG1 and SPDEF in MCF-7 cells.
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Genome-wide association studies for breast cancer have identified over 80 different risk regions in the genome, with the FGFR2 locus consistently identified as the most strongly associated locus. However, we know little about the mechanisms by which the FGFR2 locus mediates risk or the pathways in which multiple risk loci may combine to cause disease. Here we use a systems biology approach to elucidate the regulatory networks operating in breast cancer and examine the role of FGFR2 in mediating risk. Using model systems we identify FGFR2-regulated genes and, combining variant set enrichment and eQTL analysis, show that these are preferentially linked to breast cancer risk loci. Our results support the concept that cancer-risk associated genes cluster in pathways

Publication Title

Master regulators of FGFR2 signalling and breast cancer risk.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP135885
Effect of mutant TRP53 proteins on nutlin-3a treated mouse lymphoma cell lines (RNA-seq)
  • organism-icon Mus musculus
  • sample-icon 131 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Mutations in TRP53, prevalent in human cancers, reportedly drive tumorigenesis through dominant-negative-effects (DNE) over wt TRP53 and neomorphic gain-of-function (GOF) effects. We show that five TRP53 mutants do not accelerate lymphomagenesis on a TRP53-deficient background but strongly synergize with c-MYC over-expression. RNA-seq analysis revealed that mutant TRP53 does not globally repress wt TRP53 function but exerts a DNE with disproportionate impact on subsets of wt TRP53 target genes, particularly those involved in DNA repair, proliferation and metabolism. This reveals that the mutant TRP53 DNE drives tumorigenesis by modulating wt TRP53 function in a manner that is advantageous for neoplastic transformation. Overall design: Each of 5 mutant human TRP53 proteins, and a negative control, was expressed in 3 mouse lymphoma cell lines, both before and after activation of WT TRP53 with nutlin-3a.

Publication Title

Mutant TRP53 exerts a target gene-selective dominant-negative effect to drive tumor development.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP060655
Differential expression profiles of type I JAK inhibitor persistent vs. naïve MPN cells
  • organism-icon Homo sapiens
  • sample-icon 33 Downloadable Samples
  • Technology Badge IconIonTorrentProton

Description

The type I JAK inhibitor ruxolitinib is approved for therapy of MPN patients but evokes resistance with longer exposure. Several novel type I JAK inhibitors were studied and we show that they uniformly induce resistance via a shared mechanism of JAK family heterodimer formation.Here we studied the expression profiles of SET2 cell lines persistent to several different type I JAK inhibitors in comparison to naive SET2 cells or in comparison to SET2 cells with acute exposure to ruxolitinib. Overall design: Analysis of RNA isolated from several type I JAK inhibitor SET2 cell lines in comparison to naïve SET2 cells

Publication Title

CHZ868, a Type II JAK2 Inhibitor, Reverses Type I JAK Inhibitor Persistence and Demonstrates Efficacy in Myeloproliferative Neoplasms.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE2815
cMyb and vMyb in MCF7 cells
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The transcriptional activities of c-Myb and its oncogenic variant v-Myb were compared by expressing them in human MCF7 cells using recombinant adenovirus vectors. A hybrid construct, 3Mutc, which is a variant of c-Myb harboring three v-Myb-derived DNA binding domain mutations was also analyzed. All the samples were compared to cells infected with a control adenovirus. The results showed that v-Myb, which differs from c-Myb only by N- and C-terminal deletions and eleven amino acid substitutions, has a qualitatively different transcriptional activity.

Publication Title

Oncogenic mutations cause dramatic, qualitative changes in the transcriptional activity of c-Myb.

Sample Metadata Fields

No sample metadata fields

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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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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