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accession-icon GSE14491
TGF/mutant-p53 jointly controlled genes
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

TGF ligands act as tumor suppressors in early stage tumors but are paradoxically diverted into potent prometastatic factors in advanced cancers. The molecular nature of this switch remains enigmatic. We now show that TGF-dependent cell migration, invasion and metastasis are empowered by mutant-p53.

Publication Title

A Mutant-p53/Smad complex opposes p63 to empower TGFbeta-induced metastasis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP053363
Analysis of wildtype and Xbp1-deficient hematopoietic progenitor cell transcriptomes
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Purpose: The goals of this study are to assess the transcriptional networks governed by the transcription factor XBP1 in lineage-uncommitted myeloid progenitors and in eosinophil-committed myeloid progenitors. Methods: mRNA profiles of FACS-purified granulocyte-macrophage progenitors (GMPs) from XBP1 flox/flox or XBP1 flox/flox Vav1-Cre mice were generated by sequencing, in biological triplicates, using an Illumina HiSeq2000 sequencer. The Illumina HiSeq2000 sequencer was also used to obtain mRNA profiles of FACS-purified GMPs transduced with the transcription factor GATA2, resorted 36 hours post-transduction, and cultured for 48 hours, again in biological triplicates per genotype. Sequence data from Illumina''s HiSeq2000 sequencer were demuxed to generate FASTQ files for each sample using Illumina''s CASAVA pipeline (version 1.8.2). The reads that passed illumina''s quality/purity filter were aligned to the mouse genome (Illumina iGenomes mm9 build) using STAR aligner (version 2.3.0) with default parameters. The resulting SAM alignment files were then converted to the BAM file format, sorted and indexed using SAMtools (version 0.1.14).  Mapped reads were counted with the python module HTSeq, and differential expression analyzed with the Bioconductor package DESeq. Results and conclusions: By monitoring XBP1-dependent transcriptional changes at different stages of eosinophil development, we demonstrated that classical XBP1-dependent networks such as glycosylation, chaperone production, and ERAD were downregulated in GMPs prior to eosinophil commitment, though there were no major defects in differentiation or survival. However, mRNA profiling clearly demonstrated that XBP1 deficiency causes a state of cellular stress upon eosinophil commitment. The eosinophil transcriptome was largely intact, and most dysregulated genes were associated with ER stress. However key granule protein genes required for eosinophil development such as Prg2 and Epx were selectively downregulated only after eosinophil commitment, but not in pre-committed myeloid progenitors, and this correlated with Ingenuity Pathway Analysis predictions that GATA1 function was impaired. This study documents the interplay between cellular stress and the ability to maintain key facets of cellular differentiation. Overall design: Analyses of XBP1-dependent transcriptional networks at two stages of eosinophil development.

Publication Title

The transcription factor XBP1 is selectively required for eosinophil differentiation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE40278
A multiply redundant genetic switch locks in the transcriptional signature of T regulatory cells
  • organism-icon Mus musculus
  • sample-icon 60 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

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE40274
Gene profiling data of CD4+ T cells transduced with FOXP3 and candidate cofactors
  • organism-icon Mus musculus
  • sample-icon 33 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The transcription factor FoxP3 partakes dominantly in the specification and function of FoxP3+ CD4+ T regulatory cells (Tregs), but is neither strictly necessary nor sufficient to determine the characteristic Treg transcriptional signature. Computational network inference and experimental testing assessed the contribution of several other transcription factors (TFs). Enforced expression of Helios or Xbp1 elicited specific signatures, but Eos, Irf4, Satb1, Lef1 and Gata1 elicited exactly the same outcome, synergizing with FoxP3 to activate most of the Treg signature, including key TFs, and enhancing FoxP3 occupancy at its genomic targets. Conversely, the Treg signature was robust to inactivation of any single cofactor. A redundant genetic switch thus locks-in the Treg phenotype, a model which accounts for several aspects of Treg physiology, differentiation and stability.

Publication Title

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE40273
Gene expression profiling in Treg cells deficient or mutant in candidate FoxP3 cofactors
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The transcription factor FoxP3 partakes dominantly in the specification and function of FoxP3+ CD4+ T regulatory cells (Tregs), but is neither strictly necessary nor sufficient to determine the characteristic Treg transcriptional signature. Computational network inference and experimental testing assessed the contribution of several other transcription factors (TFs). Enforced expression of Helios or Xbp1 elicited specific signatures, but Eos, Irf4, Satb1, Lef1 and Gata1 elicited exactly the same outcome, synergizing with FoxP3 to activate most of the Treg signature, including key TFs, and enhancing FoxP3 occupancy at its genomic targets. Conversely, the Treg signature was robust to inactivation of any single cofactor. A redundant genetic switch thus locks-in the Treg phenotype, a model which accounts for several aspects of Treg physiology, differentiation and stability.

Publication Title

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE40277
Gene profiling data of CD4+ T cells doubly transduced with EOS+LEF1 or GATA1+SATB1
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The transcription factor FoxP3 partakes dominantly in the specification and function of FoxP3+ CD4+ T regulatory cells (Tregs), but is neither strictly necessary nor sufficient to determine the characteristic Treg transcriptional signature. Computational network inference and experimental testing assessed the contribution of several other transcription factors (TFs). Enforced expression of Helios or Xbp1 elicited specific signatures, but Eos, Irf4, Satb1, Lef1 and Gata1 elicited exactly the same outcome, synergizing with FoxP3 to activate most of the Treg signature, including key TFs, and enhancing FoxP3 occupancy at its genomic targets. Conversely, the Treg signature was robust to inactivation of any single cofactor. A redundant genetic switch thus locks-in the Treg phenotype, a model which accounts for several aspects of Treg physiology, differentiation and stability.

Publication Title

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE40276
Gene profiling data of CD4+ T cells transduced with FOXP3 and GATA1, then sorted into different fractions, based on the expression of Thy1.1 (FOXP3)
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The transcription factor FoxP3 partakes dominantly in the specification and function of FoxP3+ CD4+ T regulatory cells (Tregs), but is neither strictly necessary nor sufficient to determine the characteristic Treg transcriptional signature. Computational network inference and experimental testing assessed the contribution of several other transcription factors (TFs). Enforced expression of Helios or Xbp1 elicited specific signatures, but Eos, Irf4, Satb1, Lef1 and Gata1 elicited exactly the same outcome, synergizing with FoxP3 to activate most of the Treg signature, including key TFs, and enhancing FoxP3 occupancy at its genomic targets. Conversely, the Treg signature was robust to inactivation of any single cofactor. A redundant genetic switch thus locks-in the Treg phenotype, a model which accounts for several aspects of Treg physiology, differentiation and stability.

Publication Title

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

Sample Metadata Fields

Sex, Age, Specimen part

View Samples
accession-icon GSE49955
Genome-wide maps of XBP1 binding sites in different breast cancer cell lines.
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

XBP1 promotes triple-negative breast cancer by controlling the HIF1α pathway.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE49953
Expression data from two breast cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

During cancer progression, carcinoma cells encounter a variety of cytotoxic stresses such as hypoxia, nutrient deprivation, and low pH as a result of inadequate vascularization. To maintain survival and growth in the face of these physiologic stressors, a set of adaptive response pathways are induced. One adaptive pathway well studied in other contexts is the unfolded protein response (UPR), of which XBP1 is an important component.

Publication Title

XBP1 promotes triple-negative breast cancer by controlling the HIF1α pathway.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE69408
Expression data from human HSPCs
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Aging within the human hematopoietic system associates with increased incidence of anemia and myeloid neoplasms, decreased bone marrow (BM) cellularity and reduced adaptive immune responses. Similar phenotypes have been observed in mice and shown, at least in part, to involve hematopoietic stem cells (HSCs). However, evidence supporting such an association within human hematopoiesis is still sparse and prompted us to detail characteristics of human hematopoietic stem and progenitor cells throughout ontogeny.

Publication Title

Human and Murine Hematopoietic Stem Cell Aging Is Associated with Functional Impairments and Intrinsic Megakaryocytic/Erythroid Bias.

Sample Metadata Fields

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)

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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