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accession-icon GSE35364
Cancer-associated fibroblast transfected with miR-155, anti-miR-31 and anti-miR-214
  • organism-icon Homo sapiens
  • sample-icon 11 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

MicroRNAs reprogram normal fibroblasts into cancer-associated fibroblasts in ovarian cancer.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE35250
NOF vs. coCAF 7d
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Campare the difference between pairwise NOF and coCAF tissues for three patients

Publication Title

MicroRNAs reprogram normal fibroblasts into cancer-associated fibroblasts in ovarian cancer.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE35249
aNOF vs. CAF
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Compare the difference between pairwise aNOF and CAF samples for two patients

Publication Title

MicroRNAs reprogram normal fibroblasts into cancer-associated fibroblasts in ovarian cancer.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE35251
NOF vs. iCAF 2d
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Compare the difference between pairwise NOF and iCAF (2d) tissues for one patient

Publication Title

MicroRNAs reprogram normal fibroblasts into cancer-associated fibroblasts in ovarian cancer.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon SRP111653
CD95L derived si- and shRNAs kill cancer cells through an RNAi mechanism by targeting survival genes [shL3.shR6.RNAseq.lg]
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

The death receptor CD95/Fas can be activated by immune cells to kill cancer cells. However, most siRNAs or shRNAs targeting either CD95 or CD95L induce DICE (Death Induced by CD95/CD95L Elimination), a form of cell death in which a combination of different cell death pathways are activated, that is selective for transformed cells, and that preferentially affects cancer stem cells. We now provide evidence that both CD95 and CD95L are part of a network of genes that contain sequences that when expressed as either siRNAs or shRNAs are toxic to cancer cells. They act through canonical RNAi by targeting the 3''UTRs of critical survival genes. We propose that these embedded toxic sequences are part of a conserved mechanism that regulates cell death, and we predict the existence of endogenous siRNAs, that when produced, induce cell death to regulate genome fidelity. Our data have implications for cancer therapy and the use of RNAi. Overall design: 293T (shL3 site deleted) cells were infected with either pTIP-shScr or pTIP-shL3 and following puromycin selection large RNAs were analyzed by deep sequencing 50 or 100hrs after addition of doxycycline/HeyA8 (shR6 site deleted) cells were infected with either pLKO-shScr or pLKO-shR6 and following puromycin selection large RNAs were analyzed by deep sequencing 50 or 100hrs after addition of selection.

Publication Title

Many si/shRNAs can kill cancer cells by targeting multiple survival genes through an off-target mechanism.

Sample Metadata Fields

Specimen part, Cell line, Subject, Time

View Samples
accession-icon SRP111526
CD95L derived si- and shRNAs kill cancer cells through an RNAi mechanism by targeting survival genes [shL1.RNAseq.lg]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

We provide evidence that shRNAs and siRNAs derived from CD95 and CD95L preferentially target the 3'' UTRs of survival genes culminating in a very robust mode of cell death we call DISE (Death Induced by Survival gene Elimination) Overall design: 293T cells were infected with either pTIP-shScr or pTIP-shL1 and following puromycin selection RNA was analyzed by deep sequencing 100hrs after addition of doxycycline

Publication Title

Many si/shRNAs can kill cancer cells by targeting multiple survival genes through an off-target mechanism.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject, Time

View Samples
accession-icon SRP066166
Transcriptome Analysis of Drosophila Mushroom Body Neurons by Cell Type Reveals Memory-Related Changes in Gene Expression
  • organism-icon Drosophila melanogaster
  • sample-icon 176 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We report the application of low cell number sequencing of identifiable Drosophila melanogaster neurons following behavior. We demonstate the feasibility of identifying the transcriptome of 5 Mushroom Body output Neurons and 2 classes of Kenyon Cells. We find these neurons display a diverse repertoire of receptors and signaling transcripts. This information alone seems to be enough to identify each class of neurons in the study. In additional we show that aversive long-term memory induces changes in gene transcript levels in a subset of these neurons. This study provides a framework for identifying neuronal classes in Drosophila melanogaster and gaining insight into the interplay between behavior and gene regulation. Overall design: 5 Mushroom Body output neurons and 2 classes of kenyon cells are used to look at general gene expression and changes following aversive long term memory. Paired control and trained animals were used and a minimum of 4 pairs up to 6 pairs. Animals were of the same background (w1118). Animals were aged and parental matched. Cells were harvested at the same chronological time for the animals across all experiments. All animals were exposed to 1 minute of each odor and 1 minute of a series of 12 5second 60V shocks. This was considered one block and then the animals had spaced training of each block so there was a 10 minute break between 8 blocks of training. Trained animals had an odor paired with a shock, control animals received the shock then the odor stimulus. All cells were harvested usign a patch pipet from living animals on an electrophysiology rig within a half hour of the end of training. Cells were amplified using the Clontech SMARTer Ultra Low Input RNA version 2 High Volume kit. 2 Brain samples were also collected and 3-4 whole fly samples for each genotype were collected to account for background differences across flies.

Publication Title

Cell-Type-Specific Transcriptome Analysis in the Drosophila Mushroom Body Reveals Memory-Related Changes in Gene Expression.

Sample Metadata Fields

Subject

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accession-icon GSE46270
Bcl11a controls Flt3 expression in early hematopoietic progenitors and is required for pDC development in vivo
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Bcl11a is a transcription factor known to regulate lymphoid and erythroid development. Recent bioinformatic analysis of global gene expression patterns has suggested a role for Bcl11a in the development of dendritic cell (DC) lineages. We tested this hypothesis by analyzing the development of DC and other lineages in Bcl11a(-/-) mice. We show that Bcl11a is required for expression of IL-7 receptor (IL-7R) and Flt3 in early hematopoietic progenitor cells. The loss of IL-7R(+) common lymphoid progenitors accounts for previously described lymphoid defects in Bcl11a(-/-) mice. In addition, we found severely decreased numbers of plasmacytoid dendritic cells (pDCs) in Bcl11a(-/-) fetal livers and in the bone marrow of Bcl11a(-/-) fetal liver chimeras. Moreover, Bcl11a(-/-) cells show severely impaired in vitro development of Flt3L-derived pDCs and classical DCs (cDCs). In contrast, we found normal in vitro development of DCs from Bcl11a(-/-) fetal liver cells treated with GM-CSF. These results suggest that the persistent cDC development observed in Bcl11a(-/-) fetal liver chimeras reflects derivation from a Bcl11a- and Flt3-independent pathway in vivo.

Publication Title

Bcl11a controls Flt3 expression in early hematopoietic progenitors and is required for pDC development in vivo.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE141492
The MYCL and MXD1 transcription factors regulate the fitness of murine dendritic cells
  • organism-icon Mus musculus
  • sample-icon 35 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The present study reveals LMYC and MXD1 as novel regulators of a transcriptional program that is modulated during the maturation of Batf3-dependent dendritic cells (also known as type I classical dendritic cells or cDC1s).

Publication Title

The MYCL and MXD1 transcription factors regulate the fitness of murine dendritic cells.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE26524
Expression data from differentiating Flk1- and Flk1+ ES cells expressing Snail during Wnt inhibition
  • organism-icon Mus musculus
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

ES cells differentiated in the presence of the Wnt inhibitor DKK1 fail to express the transcription factor Snail and undergo EMT or mesoderm differentiation. We generated an ES cell line, A2.snail, that induced Snail expression upon addition of doxycycline addition.

Publication Title

Snail promotes the cell-autonomous generation of Flk1(+) endothelial cells through the repression of the microRNA-200 family.

Sample Metadata Fields

Specimen part, Cell line

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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