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accession-icon GSE89912
Expression data from Oct4+ cell fraction in SFEBq cultured mouse embryonic stem cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To further characterize residual undifferentiated cells after neural induction of embryonic stem cells, we performed DNA microarray analysis to identify genes expressed predominantly in residual undifferentiated cells expressing Oct4.

Publication Title

Dormant Pluripotent Cells Emerge during Neural Differentiation of Embryonic Stem Cells in a FoxO3-Dependent Manner.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE35512
Identification of targets specifically regulated by a 'super hybrid p53'
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

p63, like its homologue, the tumor suppressor p53, is also able to induce apoptosis in several cancer cell types. p53 family proteins are composed of three characteristic domains which are: 1) an N-terminal transactivation domain (TAD); 2) a central DNA-binding domain (DBD); and 3) an oligomerization domain (OD). In this study, we constructed recombinant adenoviruses containing hybrid genes composed of fragments of p53 and TAp63 genes by connecting coding sequences of their three functional domains. The potency of tumor growth suppression of these hybrid molecules was evaluated using in vitro and in vivo models. One of the p53-p63 hybrid molecules, p63-53O, was observed to be the most potent activator of human cancer cells to apoptosis when compared to the p53, TAp63 or several alternative p53-p63 hybrid molecules. p63-53O hybrid is composed of TAD and DBD of TAp63 and OD of p53. In an effort to identify specific targets regulated by pro-apoptotic hybrid p63-53O, we next performed Affymetrix Genechip analysis and compared expression patterns in a human osteosarcoma cell line Saos-2 transfected separately with Ad-p53, Ad-TAp63 and Ad-p63-53O.

Publication Title

A novel approach to cancer treatment using structural hybrids of the p53 gene family.

Sample Metadata Fields

Cell line

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accession-icon GSE13504
Identification of targets specifically regulated by TAp73
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The p53 family consists of three members, p53, p73, and p63. These proteins share a high degree of amino-acid sequence similarity and major functional domains. The p53 gene, the first member of the family to be identified, is the most frequent target gene for genetic alterations in human cancers. In contrast, p73 and p63 are mainly involved in normal development and differentiation. These differences among the p53 family are likely to depend on activation or repression of different sets of target genes. In this study, to identify targets specifically regulated by p73, we performed microarray analysis and compared expression patterns in a human steosarcoma cell line Saos-2 infected separately with p53 and TAp73beta expressing adenovirus.

Publication Title

p53 family members regulate the expression of the apolipoprotein D gene.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE86158
Microarray data of epidermis and dermis from virgin and pregnant mice
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Tbx3-dependent amplifying stem cell progeny drives interfollicular epidermal expansion during pregnancy and regeneration.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE86157
Microarray data of epidermal basal cells from ventral or dorsal skin of virgin and pregnant mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To identify genes expressed predominantly in the ventral skin epidermal basal cells of pregnant mice, we performed DNA microarray analysis by using FACS-purified epidermal basal cells from ventral skin at 0 and 16 dpc, and dorsal skin at 16 dpc.

Publication Title

Tbx3-dependent amplifying stem cell progeny drives interfollicular epidermal expansion during pregnancy and regeneration.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE86156
Microarray data of dermal cells from ventral or dorsal skin of virgin and pregnant mice
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

To identify genes expressed predominantly in the ventral skin dermis of pregnant mice, we performed DNA microarray analysis by using isolated dermal tissues from ventral skin at 0 and 15 dpc, PP2-injected ventral skin at 15 dpc, and dorsal skin at 15 dpc.

Publication Title

Tbx3-dependent amplifying stem cell progeny drives interfollicular epidermal expansion during pregnancy and regeneration.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon E-MEXP-466
Transcription profiling of two populations of non-hematopoetic stem cells (MSC and MAPC) isolated from human bone marrow
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Compare the behaviour of two populations of non-hematopoetic stem cells (MSC and MAPC) isolated from human bone marrow. The effect of culture conditions on the behaviour of MSC was also characterised by isolating MSC and then culturing the cells for 96h in MAPC growth conditions

Publication Title

Validation of COL11A1/procollagen 11A1 expression in TGF-β1-activated immortalised human mesenchymal cells and in stromal cells of human colon adenocarcinoma.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE98424
Expression data from Hm mutant
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Mouse Hammer toe (Hm) shows syndactyly. To reveal the molecular mechanisms of Hm phenotype, we performed microarray analysis to search differencially expressed genes in Hm limb.

Publication Title

Enhancer adoption caused by genomic insertion elicits interdigital <i>Shh</i> expression and syndactyly in mouse.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE84844
Multi-omics profiling of patients with primary Sjogren's syndrome
  • organism-icon Homo sapiens
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Publication Title

Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

View Samples
accession-icon GSE93683
CD8 T-cells from pSS patients and human healthy volunteers
  • organism-icon Homo sapiens
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Multi-omics study was conducted to elucidate the crucial molecular mechanisms of primary Sjgrens syndrome (SS) pathology. We generated multiple data set from well-defined patients with SS, which includes whole-blood transcriptomes, serum proteomes and peripheral immunophenotyping. Based on our newly generated data, we performed an extensive bioinformatic investigation. Our integrative analysis identified SS gene signatures (SGS) dysregulated in widespread omics layers, including epigenomes, mRNAs and proteins. SGS predominantly involved the interferon signature and ADAMs substrates. Besides, SGS was significantly overlapped with SS-causing genes indicated by a genome-wide association study and expression trait loci analyses. Combining the molecular signatures with immunophenotypic profiles revealed that cytotoxic CD8 T cells were associated with SGS. Further, we observed the activation of SGS in cytotoxic CD8 T cells isolated from patients with SS. Our multi-omics investigation identified gene signatures deeply associated with SS pathology and showed the involvement of cytotoxic CD8 T cells. These integrative relations across multiple layers will facilitate our understanding of SS at the system level.

Publication Title

Multiomic disease signatures converge to cytotoxic CD8 T cells in primary Sjögren's syndrome.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage, Subject

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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