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accession-icon SRP043525
Extensive crosstalk between lncRNAs and mRNAs in mouse stem cells
  • organism-icon Mus musculus
  • sample-icon 25 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To determine the temporal variation of mRNA levels, we collected and sequenced poly-adenylated RNA from all cell extracts, cytoplasmic and nuclear fractions of a conditional Dicer mutant [DTCM23/49 XY (Nesterova et al. 2008)] mouse Embryonic Stem Cells before induction of Dicer excision (day 0) and at days 4, 8, 10 and 12 following Dicer loss of function. coverage. Overall design: RNA from whole cell extracts was collected at days 0, 4, 8, 10 and 12 following loss of Dicer function and from the cytoplasmic and nuclear fractions of cell at day 0 and 12. Three biological replicates were obtained for all samples. Poly-adenylated directional 100 base paired-end sequencing libraries were prepared for all extracts and sequenced by BGI solutions (Hong Kong).

Publication Title

Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE55860
A set of NF-KB-regulated microRNAs induce acquired TRAIL resistance in lung cancer
  • 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

A set of NF-κB-regulated microRNAs induces acquired TRAIL resistance in lung cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE55859
Gene expression profile of TRAIL-sensitive and -resistant H460 cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We generated H460 cells with acquired TRAIL resistance by exposing the parental sentisitve cells to subtoxic concentrations of TRAIL for 6 months. Then we compared the gene expression profile of the sensitive versus the resistant cells.

Publication Title

A set of NF-κB-regulated microRNAs induces acquired TRAIL resistance in lung cancer.

Sample Metadata Fields

Cell line

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accession-icon GSE32215
Reversal of glucocorticoid resistance by AKT inhibition in T-ALL
  • organism-icon Homo sapiens
  • sample-icon 225 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Glucocorticoid resistance is a major driver of therapeutic failure in T-cell acute lymphoblastic leukemia (T-ALL). Here we used a systems biology approach, based on the reverse engineering of signaling regulatory networks, which identified the AKT1 kinase as a signaling factor driving glucocorticoid resistance in T-ALL. Indeed, activation of AKT1 in T-ALL lymphoblasts impairs glucocorticoid-induced apoptosis. Mechanistically, AKT1 directly phosphorylates the glucocorticoid receptor NR3C1 protein at position S134 and blocks glucocorticoid-induced NR3C1 translocation to the nucleus. Consistently, inhibition of AKT1 with MK-2206 increases the response of T-ALL cells to glucocorticoid therapy both in T-ALL cell lines and in primary patient samples thus effectively reversing glucocorticoid resistance in vitro and in vivo. These results warrant the clinical testing of ATK1 inhibitors and glucocorticoids, in combination, for the treatment of T-ALL.

Publication Title

Direct reversal of glucocorticoid resistance by AKT inhibition in acute lymphoblastic leukemia.

Sample Metadata Fields

Specimen part

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accession-icon GSE41062
Expression of DND41 cell lines treated with 1M Dexamethasone for 24h after shPTEN infection
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Glucocorticoid resistance is a major driver of therapeutic failure in T-cell acute lymphoblastic leukemia (T-ALL). Here we identify the AKT1 kinase as a signaling factor driving glucocorticoid resistance in T-ALL. Mechanistically, AKT1 directly phosphorylates the glucocorticoid receptor NR3C1 protein and blocks glucocorticoid-induced NR3C1 transcription by inhibiting glucocorticoid-induced NT3C1 translocation to the nucleus. Consistently, pharmacologic inhibition of AKT1 increases the response of T-ALL cells to glucocorticoid therapy and effectively reverses glucocorticoid resistance in vitro and in vivo. These results warrant the clinical testing of AKT1 inhibitors and glucocorticoids in combination for the treatment of T-ALL.

Publication Title

Direct reversal of glucocorticoid resistance by AKT inhibition in acute lymphoblastic leukemia.

Sample Metadata Fields

Cell line

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accession-icon GSE41972
In vivo NCL-targeting affects breast cancer aggressiveness through miRNA regulation [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Numerous studies have described the altered expression and the causal role of miRNAs in human cancer. However, to date efforts to modulate miRNA levels for therapeutic purposes have been challenging to implement. Here, we find that Nucleolin (NCL), a major nucleolar protein, post-transcriptionally regulates the expression of a specific subset of miRNAs, including miR-21, miR-221, miR-222, and miR-103, causally involved in breast cancer initiation, progression and drug-resistance. We also show that NCL is commonly overexpressed in human breast tumors, and its expression correlates with that of NCL-dependent miRNAs. Finally, this study indicates that NCL-binding guanosine-rich aptamers affect the levels of NCL-dependent miRNAs and their target genes, reducing breast cancer cell aggressiveness, both in vitro and in vivo. These findings illuminate a path to novel therapeutic approaches based on NCL-targeting aptamers for the modulation of miRNA expression in the treatment of breast cancer.

Publication Title

In vivo NCL targeting affects breast cancer aggressiveness through miRNA regulation.

Sample Metadata Fields

Cell line

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accession-icon GSE6904
Expression data from mouse SCN after 30-min light pulse
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

The transmission of information about the photic environment to the circadian clock involves a complex array of neurotransmitters, receptors, and second messenger systems. Using laser capture microscopy and microarray analysis, a population of genes rapidly induced by light in the suprachiasmatic nucleus is identified.

Publication Title

Identification of novel light-induced genes in the suprachiasmatic nucleus.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP065478
Snai2 and Snai3 transcriptionally regulate cellular fitness and functionality of T cell lineages through distinct gene programs
  • organism-icon Mus musculus
  • sample-icon 23 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

T lymphocytes are essential contributors to the adaptive immune system and consist of multiple lineages that serve various effector and regulatory roles. As such, precise control of gene expression is essential to the proper development and function of these cells. Previously, we identified Snai2 and Snai3 as being essential regulators of immune tolerance partly due to the impaired function of CD4+ regulatory T cells in Snai2/3 conditional double knockout mice. Here we extend those previous findings using a bone marrow transplantation model to provide an environmentally unbiased view of the molecular changes imparted onto various T lymphocyte populations once Snai2 and Snai3 are deleted. The data presented here demonstrate that Snai2 and Snai3 transcriptionally regulate the cellular fitness and functionality of not only CD4+ regulatory T cells but effector CD8a+ and CD4+ conventional T cells as well. This is achieved through the modulation of gene sets unique to each cell type and includes transcriptional targets relevant to the survival and function of each T cell lineage. As such, Snai2 and Snai3 are essential regulators of T cell immunobiology. Overall design: GFP- CD3e+ CD8a+ CD4-, GFP- CD3e+ CD8a- CD4+ CD25- and GFP- CD3e+ CD8a- CD4+ CD25+ T cells were isolated from spleens of UBC-GFP mice transplanted with WT or cDKO lineage-depleted donor bone marrow following lethal irradiation of recipient mice. RNA-seq was performed on 3-4 biological replicates from each genotype for all T cell populations analyzed.

Publication Title

Snai2 and Snai3 transcriptionally regulate cellular fitness and functionality of T cell lineages through distinct gene programs.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP040561
Gene expression analysis of hair cell regeneration in the zebrafish lateral line
  • organism-icon Danio rerio
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Deafness due to the terminal loss of inner ear hair cells is one of the most common sensory diseases. However, non-mammalian animals (e.g. birds, amphibian and fish) regenerate damaged hair cells. In order to better understand the reasons underpinning such regeneration disparities in vertebrates, we set out to define the changes in gene expression associated with the regeneration of hair cells in the zebrafish lateral line at high resolution. We performed RNA-Seq analyses on regenerating support cells purified by fluorescence activated cell sorting (FACS). The zebrafish lateral line provides an experimentally accessible system to define the complex signaling events triggered by injury and regeneration, because these cells can be acutely killed by exposure to neomycin, after which they regenerate rapidly. Lateral line hair cells are located in the center of a mechanosensory organ known as the neuromast and are surrounded by inner support cells and an outer ring of mantle cells. Tg(sqET20) larvae express GFP strongly in mantle cells and to a lesser degree in inner support cells. We isolated GFP positive and GFP negative cells from 5 days post fertilization (dpf) Tg(sqET20) larvae at 1, 3 and 5 hours post neomycin treatment, as well as from a non-treated control. Overall design: Transgenic zebrafish Tg(sqET20) larvae at 5 days post fertilization were exposed to neomycin, dissociated, and FACS sorted into GFP positive and GFP negative populations at 1, 3, and 5 hours following treatment, along with a mock treated 1 hr control. The experiment was performed in triplicate, for a total of 24 samples.

Publication Title

Gene-expression analysis of hair cell regeneration in the zebrafish lateral line.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE20758
Expression data from LCM captured prostate cancer cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

The prostate represents a complex mix of cell types and there is a need to analyze distinct cell populations to better understand their potential interactions. This study of cell-type specific gene expression patterns will contribute to understanding of how tumor epithelial cells may be affected by adjacent interstitial stromal cells within the tumor microenvirnonment.

Publication Title

Analysis of gene expression in prostate cancer epithelial and interstitial stromal cells using laser capture microdissection.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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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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