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accession-icon SRP095625
Generation of muscle stem cells from pluripotent stem cells
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We have developed a method to generate muscle stem cells from pluripotent stem cells via teratoma formation. The goal of this study is to compare the transcriptome of a7+ VCAM+ myogenic cells derived from pluripotent stem cells versus satellite cells Overall design: RNA from a7+ VCAM+ myogenic cells derived from teratoma, transplanted muscles, E14.5 mouse embryos, and hindlimbs of 8-week-old mice. In 3 biological replicates

Publication Title

Skeletal Muscle Stem Cells from PSC-Derived Teratomas Have Functional Regenerative Capacity.

Sample Metadata Fields

Cell line, Subject

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accession-icon GSE97372
Transcriptomic analysis of conditional THAP1 knockout mice brains using microarray
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

Loss of function mutations in the transcription factor THAP1 cause DYT6 dystonia, a childhood-onset motor disorder. DYT6 subjects display abnormalities in the white matter regions of the brain.

Publication Title

The DYT6 Dystonia Protein THAP1 Regulates Myelination within the Oligodendrocyte Lineage.

Sample Metadata Fields

Specimen part

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accession-icon GSE13732
CIS (multiple sclerosis) (case-control) (time-series)
  • organism-icon Homo sapiens
  • sample-icon 112 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Clinically isolated syndrome (CIS) refers to the earliest clinical manifestation of multiple sclerosis (MS). Currently there are no prognostic biological markers that accurately predict conversion of CIS to clinically definite MS (CDMS). Furthermore, the earliest molecular events in MS are still unknown. We used microarrays to study gene expression in nave CD4+ T cells from 37 CIS patients at time of diagnosis and after one year. Supervised machine-learning methods were used to build predictive models of disease conversion. We identified 975 genes whose expression segregated CIS patients into 4 distinct subgroups. A subset of 108 genes further discriminated patients from one of these (group#1) from other CIS patients. Remarkably, 92% of patients from group #1 converted to CDMS within 9 months. Consistent downregulation of TOB1, a critical regulator of cell proliferation, was characteristic of group #1 patients. Decreased TOB1 expression at the RNA and protein levels was also confirmed in experimental autoimmune encephalomyelitis (EAE). Finally, a genetic association was observed between TOB1 variation and MS progression in an independent cohort. These results indicate that CIS patients at high risk of conversion have impaired regulation of T cell quiescence resulting in earlier activation of pathogenic CD4+ cells.

Publication Title

Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP099844
Chemoprevention with COX2 and EGFR inhibition in FAP patients: mRNA signatures of duodenal neoplasia
  • organism-icon Homo sapiens
  • sample-icon 69 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNA sequencing of duodenal polyps in FAP patients treated with plabebo or the drug combination, erlotinib + sulindac Overall design: 69 duodenal RNA sequencing datasets (17 baseline uninvolved from 17 FAP patients, 10 endpoint uninvolved and 16 polyp from 10 FAP patients on placebo, 10 endpont uninvolved and 16 polyp from 10 FAP patients on drug)

Publication Title

Chemoprevention with Cyclooxygenase and Epidermal Growth Factor Receptor Inhibitors in Familial Adenomatous Polyposis Patients: mRNA Signatures of Duodenal Neoplasia.

Sample Metadata Fields

Specimen part, Treatment, Subject, Time

View Samples
accession-icon GSE63678
Expression data from Vulvar, Cervical, Endometrial Carcinoma tissue
  • organism-icon Homo sapiens
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

A growing number of studies on gynecological cancers (GCs) have revealed potential gene markers associated either with the pathogenesis and progression of the disease on representing putative targets for therapy and treatment of cervical (CC), endometrial (EC) and vulvar cancer (VC). However, quite a little overlap is found between these data. In this study we combined data from the three GCs integrating gene expression profile analysis.

Publication Title

Profiling of Discrete Gynecological Cancers Reveals Novel Transcriptional Modules and Common Features Shared by Other Cancer Types and Embryonic Stem Cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

View Samples
accession-icon GSE66072
Mcl-1 is a key determinant of breast cancer cell survival
  • organism-icon Homo sapiens
  • sample-icon 93 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

MCL-1 Is a Key Determinant of Breast Cancer Cell Survival: Validation of MCL-1 Dependency Utilizing a Highly Selective Small Molecule Inhibitor.

Sample Metadata Fields

Cell line

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accession-icon GSE66071
Mcl-1 is a key determinant of breast cancer cell survival [expression]
  • organism-icon Homo sapiens
  • sample-icon 93 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

mRNA expression profile of cultured Breast Cancer cell line measured by Affymetrix microarrays

Publication Title

MCL-1 Is a Key Determinant of Breast Cancer Cell Survival: Validation of MCL-1 Dependency Utilizing a Highly Selective Small Molecule Inhibitor.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE58516
Effects of bisphenol A on gene expression in adipocytes from lean children: association to metabolic disorders
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Bisphenol A (BPA) is a xenobiotic endocrine disrupting chemical. In vitro and in vivo studies indicated that BPA alters endocrine-metabolic pathways in adipose tissue increasing the risk of developing metabolic disorders. BPA effects on human adipocytes, specifically in children, are poorly investigated. To investigate in childhood the effect of exposure to BPA on metabolic disorders we analyzed in vitro the effects of environmentally relevant doses of BPA on gene expression of mature human adipocytes from pre-pubertal lean patients and on related physiological outcomes. Adipocytes from children were treated in vitro with BPA and gene expression was evaluated by qRT-PCR. Genome wide analyses were performed using GeneChip Human Gene 1.0 ST array. Lipid content in adipocytes was estimated by ORO staining and Triglyceride Quantification Kit. Secreted IL-1, in adipocytes culture medium, and insulin, in PANC-1 culture medium, were performed using ELISA assays. BPA was found to promote up-regulation of ER and ERR, and down-regulation of GPR30 expression modulating estrogen signaling and following a non-linear dose-response. Microarray data analysis demonstrated that BPA increases the gene expression of pro-inflammatory cytokines and lipid metabolism-related FABP4 and CD36 in adipocytes. PCSK1 resulted the most interesting gene being down-regulated by BPA thus impairing insulin production in pancreas. BPA promotes inflammation and lipid metabolism dysregulation in adipocytes from lean children. Moreover, PCSK1 can be a key gene in BPA action modulating insulin production. Exposure to BPA in childhood may be an important risk factor in developing obesity and metabolic disorders.

Publication Title

Bisphenol A effects on gene expression in adipocytes from children: association with metabolic disorders.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP065840
Genetic Diversity Through RNA Editing: Apobec1-mediated RNA editing in bulk and single cell macrophages and dendritic cells
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

RNA editing is a mutational mechanism that specifically alters the nucleotide content in sets of transcripts while leaving their cognate genomic blueprint intact. Editing has been detected from bulk RNA-seq data in thousands of distinct transcripts, but apparent editing rates can vary widely (from under 1% to almost 100%). These observed editing rates could result from approximately equal rates of editing within each individual cell in the bulk sample, or alternatively, editing estimates from a population of cells could reflect an average of distinct, biologically significant editing signatures that vary substantially between individual cells in the population. To distinguish between these two possibilities we have constructed a hierarchical Bayesian model which quantifies the variance of editing rates at specific sites using RNA-seq data from both single cells and a cognate bulk sample consisting of ~ 106 cells. The model was applied to data from murine bone-marrow derived macrophages and dendritic cells, and predicted high variance for specific edited sites in both cell types tested. We then 1 validated these predictions using targeted amplification of specific editable transcripts from individual macrophages. Our data demonstrate substantial variance in editing signatures between single cells, supporting the notion that RNA editing generates diversity within cellular populations. Such editing-mediated RNA-level sequence diversity could contribute to the functional heterogeneity apparent in cells of the innate immune system. Overall design: 26 samples were subjected to RNA-seq: 24 single WT macrophages, and 2 bulk samples (Apobec1 WT and KO macrophages), consisting of 500,000-1 million cells each.

Publication Title

RNA editing generates cellular subsets with diverse sequence within populations.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE14024
Reversal of oncogene transformation and suppression of tumor growth by the novel IGF1R kinase inhibitor A-928605.
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The insulin-like growth factor (IGF) axis is an important signaling pathway in the growth and survival of many cell types and has been implicated in multiple aspects of cancer progression from tumorigenesis to metastasis. The multiple roles of IGF signaling in cancer suggest that selective inhibition of the pathway might yield clinically effective therapeutics. Here we describe A-928605, a novel small molecule inhibitor of the receptor tyrosine kinase responsible for IGF signal transduction. This small molecule is able to abrogate activation of the pathway as shown by effects on the target and downstream effectors and is shown to be effective at inhibiting the proliferation of an oncogene addicted tumor model cell line (CD8-IGF1R 3T3) both in vitro and in vivo.

Publication Title

Reversal of oncogene transformation and suppression of tumor growth by the novel IGF1R kinase inhibitor A-928605.

Sample Metadata Fields

No sample metadata fields

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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