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accession-icon GSE9013
Expression data from side-population sorted putative intestinal stem cells.
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

While the existence of intestinal epithelial stem cells (IESCs) has been well established, their study has been limited due to the inability to isolate them. Previous work has utilized side population (SP) sorting of the murine small intestinal mucosa to isolate a viable fraction of cells enriched for putative IESCs. We have used microarray analyses to characterize the molecular features of this potential stem cell population.

Publication Title

Molecular properties of side population-sorted cells from mouse small intestine.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE4260
Cumulus-oocyte complex temporal expression
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Cumulus-oocyte complexes were isolated a seperate time-points to generate temporal complexes. Targets from two biological replicates at each time point (0h, 8h, 16h post-hCG treatment) were generated and the expression profiles were determined using Affymetrix GeneChip Mouse Genome 430 2.0 Arrays. Comparisons between the sample groups allow the identification of genes with temporal expression patterns.

Publication Title

Gene expression profiles of cumulus cell oocyte complexes during ovulation reveal cumulus cells express neuronal and immune-related genes: does this expand their role in the ovulation process?

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE33232
Cancer Outlier Gene Profile Sets Elucidate Pathways and Patient-Specific Targets in Head and Neck Squamous Cell Carcinoma
  • organism-icon Homo sapiens
  • sample-icon 126 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

Sample Metadata Fields

Disease, Disease stage

View Samples
accession-icon GSE47018
Gene Expression Profiling in Polycythemia Vera (PV)
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

To define the molecular abnormalities at the stem cell level in polycythemia vera (PV), we examined global gene expression in circulating CD34+ cells from 19 JAK2 V617F-positive PV patients and 6 normal individuals using Affymetrix oligonucleotide microarray technology. We observed that CD34+ cell gene expression not only differed between the PV patients and the normal controls but also between men and women PV patients. Based on these gender-specific differences in gene expression, we were able to identify 102 genes differentially regulated concordantly by both men and women, which likely represent a core set of genes whose dysregulation is involved in the pathogenesis of PV. Gene expression was verified by Q-PCR of patient CD34+ cell RNA. Using the 102 gene set and unsupervised hierarchical clustering, the 19 PV patients could be separated in two groups that differed significantly with respect to hemoglobin level, thrombosis frequency, splenomegaly, splenectomy or chemotherapy exposure, leukemic transformation and overall survival. These results were confirmed using top scoring pairs, which identified a different set of 29 genes that independently segregated the 19 patients into the same two clinical groups: those with an aggressive form of the disease (7 patients), and those with an indolent form (12 patients).

Publication Title

Two clinical phenotypes in polycythemia vera.

Sample Metadata Fields

Sex, Disease

View Samples
accession-icon GSE6966
Transcriptional profiling of bipotential embryonic liver cells to identify liver progenitor cell surface markers.
  • organism-icon Mus musculus
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Mouse Expression 430A Array (moe430a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Transcriptional profiling of bipotential embryonic liver cells to identify liver progenitor cell surface markers.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE27390
Human bone marrow-derived mononuclear cells (BMMC): rheumatoid arthritis vs. osteoarthritis
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Gene expression profiling of BMMC from patients with rheumatoid arthritis (RA) vs. osteoarthritis (OA).

Publication Title

Abnormal networks of immune response-related molecules in bone marrow cells from patients with rheumatoid arthritis as revealed by DNA microarray analysis.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

View Samples
accession-icon GSE6942
Transcriptional profiling of bipotential embryonic liver cells to identify liver progenitor cell surface markers (430A)
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

The ability to purify to homogeneity a population of hepatic progenitor cells from adult liver is critical for their characterization prior to any therapeutic application. As a step in this direction, we have utilized gene profiling of a bipotential liver cell line from dpc 14 mouse embryonic liver to catalog genes expressed by liver progenitor cells. These cells, known as Bipotential Mouse Embryonic Liver (BMEL) cells, proliferate in an undifferentiated state and are capable of differentiating into hepatocyte-like and cholangiocyte-like cells in vitro. Upon transplantation, BMEL cells are capable of differentiating into hepatocytes and cholangiocytes in vivo. Microarray analysis of gene expression in the 9A1 and 14B3 BMEL cell lines grown under proliferating and differentiating conditions was used to identify cell surface markers preferentially expressed in the bipotential undifferentiated state. This analysis revealed that proliferating BMEL cells express many genes involved in cell cycle regulation whereas differentiation of BMEL cells by cell aggregation causes a switch in gene expression to functions characteristic of mature hepatocytes. In addition, microarray data and protein analysis indicated that the Notch signaling pathway could be involved in maintaining BMEL cells in an undifferentiated stem cell state. Using GO annotation, a list of cell surface markers preferentially expressed on undifferentiated BMEL cells was generated. One marker, Cd24a, is specifically expressed on progenitor oval cells in livers of DDC treated animals. We therefore consider Cd24a expression a candidate molecule for purification of hepatic progenitor cells.

Publication Title

Transcriptional profiling of bipotential embryonic liver cells to identify liver progenitor cell surface markers.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE6957
Transcriptional profiling of bipotential embryonic liver cells to identify liver progenitor cell surface markers (430)
  • organism-icon Mus musculus
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a), Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The ability to purify to homogeneity a population of hepatic progenitor cells from adult liver is critical for their characterization prior to any therapeutic application. As a step in this direction, we have utilized gene profiling of a bipotential liver cell line from dpc 14 mouse embryonic liver to catalog genes expressed by liver progenitor cells. These cells, known as Bipotential Mouse Embryonic Liver (BMEL) cells, proliferate in an undifferentiated state and are capable of differentiating into hepatocyte-like and cholangiocyte-like cells in vitro. Upon transplantation, BMEL cells are capable of differentiating into hepatocytes and cholangiocytes in vivo. Microarray analysis of gene expression in the 9A1 and 14B3 BMEL cell lines grown under proliferating and differentiating conditions was used to identify cell surface markers preferentially expressed in the bipotential undifferentiated state. This analysis revealed that proliferating BMEL cells express many genes involved in cell cycle regulation whereas differentiation of BMEL cells by cell aggregation causes a switch in gene expression to functions characteristic of mature hepatocytes. In addition, microarray data and protein analysis indicated that the Notch signaling pathway could be involved in maintaining BMEL cells in an undifferentiated stem cell state. Using GO annotation, a list of cell surface markers preferentially expressed on undifferentiated BMEL cells was generated. One marker, Cd24a, is specifically expressed on progenitor oval cells in livers of DDC treated animals. We therefore consider Cd24a expression a candidate molecule for purification of hepatic progenitor cells.

Publication Title

Transcriptional profiling of bipotential embryonic liver cells to identify liver progenitor cell surface markers.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE32975
Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma
  • organism-icon Homo sapiens
  • sample-icon 58 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Aberrant activation of signaling pathways controlled in normal epithelial cells by the epidermal growth factor receptor (EGFR) has been linked to cetuximab (a monoclonal antibody against EGFR) resistance in head and neck squamous cell carcinoma (HNSCC). To infer relevant and specific pathway activation downstream of EGFR from gene expression in HNSCC, we generated gene expression signatures using immortalized keratinocytes (HaCaT) subjected to either ligand stimulation or pharmacological inhibition of the signaling intermediaries PI-3-Kinase and MEK or transfected with EGFR, RELA/p65, or HRASVal12. The gene expression patterns that distinguished the various HaCaT variants and conditions were inferred using the Markov chain Monte Carlo (MCMC) matrix factorization algorithm Coordinated Gene Activity in Pattern Sets (CoGAPS). This approach inferred gene expression signatures with greater relevance to cell signaling pathway activation than the expression signatures inferred with standard linear models. Furthermore, the pathway signature generated using HaCaT-HRASVal12 further associated with the cetuximab treatment response in isogenic cetuximab-sensitive (UMSCC1) and -resistant (1CC8) cell lines. Our data suggest that the CoGAPS algorithm can generate gene expression signatures that are pertinent to downstream effects of receptor signaling pathway activation and potentially be useful in modeling resistance mechanisms to targeted therapies.

Publication Title

Gene expression signatures modulated by epidermal growth factor receptor activation and their relationship to cetuximab resistance in head and neck squamous cell carcinoma.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE7568
Effects of TGF-beta on mature macrophages
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The goal of the study was to identify the effects of TGF-beta on primary human macrophages maturated under different conditions.

Publication Title

Activation of a TGF-beta-specific multistep gene expression program in mature macrophages requires glucocorticoid-mediated surface expression of TGF-beta receptor II.

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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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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