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accession-icon GSE19428
Expression data from human melanoma cell lines treated or not with inflammatory cytokines
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Melanomas are often infiltrated by activated inflammatory cells. Thus, melanoma cells are very likely stimulated by inflammatory cytokines.

Publication Title

Interleukins 1alpha and 1beta secreted by some melanoma cell lines strongly reduce expression of MITF-M and melanocyte differentiation antigens.

Sample Metadata Fields

Cell line

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accession-icon GSE154558
Cytokines gene signatures on primary human cells
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

We derived gene set signature for GSEA investigation study from primary cell culture derived from healthy patients. Cells were exposed or not to cytokine for 24H before RNA collection and microarray analysis

Publication Title

Selective inhibition of TGF-β1 produced by GARP-expressing Tregs overcomes resistance to PD-1/PD-L1 blockade in cancer.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE51191
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1 in the regulation of the hypoxic gene program
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II, Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE51190
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1 in the regulation of the hypoxic gene program [microarray: kD_AP1]
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st), Illumina Genome Analyzer II

Description

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.

Publication Title

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Sample Metadata Fields

Treatment

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accession-icon GSE80521
The genomic context and co-recruitment of SP1 affect ERR co-activation by PGC-1 in muscle cells [array]
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The peroxisome proliferator-activated receptor co-activator 1 (PGC-1) coordinates the transcriptional network response to promote an improved endurance capacity in skeletal muscle, e.g. by co-activating the estrogen-related receptor (ERR) in the regulation of oxidative substrate metabolism. Despite a close functional relationship, the interaction between these two proteins has not been studied on a genomic level. We now mapped the genome-wide binding of ERR to DNA in skeletal muscle cell line with elevated PGC-1 and linked the DNA recruitment to global PGC-1 target gene regulation. We found that, surprisingly, ERR co-activation by PGC-1 is only observed in the minority of all PGC-1 recruitment sites. Nevertheless, a majority of PGC-1 target gene expression is dependent on ERR. Intriguingly, the interaction between these two proteins is controlled by the genomic context of response elements, in particular the relative GC and CpG content, monomeric and dimeric repeat binding site configuration for ERR, and adjacent recruitment of the transcription factor SP1. These findings thus not only reveal an unprecedented insight into the regulatory network underlying muscle cell plasticity, but also strongly link the genomic context of DNA response elements to control transcription factor - co-regulator interactions.

Publication Title

The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE51189
Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1 in the regulation of the hypoxic gene program [microarray: PGC1a_vs_GFP]
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II, Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor coactivator 1 (PGC-1), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1 and gene expression upon PGC-1 over-expression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto underestimated number of transcription factor partners involved in mediating PGC-1 action. In particular, principal component analysis of TFBSs at PGC-1 binding regions predicts that, besides the well-known role of the estrogen-related receptor (ERR), the activator protein-1 complex (AP-1) plays a major role in regulating the PGC-1-controlled gene program of hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1.

Publication Title

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE80522
The genomic context and co-recruitment of SP1 affect ERR co-activation by PGC-1 in muscle cells
  • organism-icon Mus musculus
  • sample-icon 9 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

The Genomic Context and Corecruitment of SP1 Affect ERRα Coactivation by PGC-1α in Muscle Cells.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP047171
Delineating Tumor-infiltrating Antigen Presenting Cell populations
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

The goal of this study is to compare tumor-infiltrating antigen presenting cell populations by global transcriptome profiling (RNA-seq) to help further delineate sub-populations of infiltrating myeloid cells in tumor. Methods: Four tumor antigen presenting cell populations were sorted from digested B78chOVA (melanoma variant) tumors in biological triplicate Results: RNA was extracted from the 4 groups (n=3 per group) and prepared for RNAseq. Sequencing yielded ~405 million reads with an average read depth of 33.7 million reads/sample. Reads were then aligned to the mouse genome (UCSC mm10) and those that mapped uniquely to known mRNAs were used to assess differential expression. Overall design: Examination of four tumor infiltrating myeliod populations

Publication Title

Dissecting the tumor myeloid compartment reveals rare activating antigen-presenting cells critical for T cell immunity.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP028155
Transcriptomic analysis of ERR alpha orphan nuclear receptor
  • organism-icon Homo sapiens
  • sample-icon 73 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Determination of the genes regulated by ERRalpha nuclear receptor in MDA-MB231 cells Overall design: MDA-MB231 cells were inactivated for ERRalpha using siRNA. Three different siRNAs were used (siE1, siE2, siE3). Cells treated with a control siRNA (siC samples) were used for comparison. Duplicate samples were analyzed. Transcriptomic analysis was performed by RNA-Seq

Publication Title

ERRα induces H3K9 demethylation by LSD1 to promote cell invasion.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP043217
Transcriptomic analysis of LSD1
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Determination of the genes regulated by LSD1 in MDA-MB231 cells Overall design: MDA-MB231 cells were inactivated for LSD1 using siRNA. Two different siRNAs were used (siL1, siL2). Cells treated with a control siRNA (siC samples) were used for comparison. Duplicate samples were analyzed. Transcriptomic analysis was performed by RNA-Seq

Publication Title

ERRα induces H3K9 demethylation by LSD1 to promote cell invasion.

Sample Metadata Fields

No sample metadata fields

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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)

fund-icon Fund the CCDL

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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