refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 41 results
Sort by

Filters

Technology

Platform

accession-icon GSE33538
Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miRs targets is a considerable bioinformatic challenge of great importance for inferring the miRs function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methodsit identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs function in a specific context.

Publication Title

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.

Sample Metadata Fields

Cell line

View Samples
accession-icon GSE24391
Coupled pre-mRNA and mRNA dynamics unveil the operation strategies underlying transcriptional responses
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)

Description

Transcriptional responses to stimuli are regulated by tuning rates of transcript production and degradation. Here we show that stimulation-induced changes in transcript production and degradation rates can be inferred from simultaneously measured precursor mRNA (pre-mRNA) and mature mRNA profiles. Our studies on the transcriptome-wide responses to extracellular stimuli in different cellular model systems revealed hitherto unanticipated dynamics of transcript production and degradation rates. Intriguingly, genes with similar mRNA profiles often exhibit marked differences in the amplitude and onset of their production. Moreover, we identify a group of genes, which take advantage of the unexpectedly large dynamic range of production rates to expedite their induction by a transient production overshoot. These findings provide an unprecedented quantitative view on processes governing transcriptional responses, and may have broad implications for understanding their regulation at the transcriptional and post-transcriptional levels.

Publication Title

Coupled pre-mRNA and mRNA dynamics unveil operational strategies underlying transcriptional responses to stimuli.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE54820
Strigolactone analogs induce apoptosis through activation of p38 and the stress response pathway in cancer cell lines and in conditionally reprogrammed primary prostate cancer cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Strigolactones are a novel class of plant hormones produced in roots and regulate shoot and root development. We have previously shown that synthetic strigolactone analogues potently inhibit growth of breast cancer cells and breast cancer stem cells. Here we show that strigolactone analogues inhibit the growth and survival of an array of cancer-derived cell lines representing solid and non-solid cancer cells including: prostate, colon, lung, melanoma, osteosarcoma and leukemic cell lines, while normal cells were minimally affected. Furthermore, we tested the response of patient-matched conditionally reprogrammed normal and prostate cancer cells. The tumor cells exhibited significantly higher sensitivity to the two most potent SL analogues with increased apoptosis compared to their normal counterpart cells. Treatment of cancer cells with strigolactone analogues was hallmarked by increased expression and activity of genes involved in stress signaling, cell cycle arrest and apoptosis. All five strigolactone analogues induced G2/M cell cycle arrest, accompanied with a decrease in the expression level of cyclin B1. Apoptosis was marked by increased percentages of cells in the sub-G1 fraction and was confirmed by Annexin V staining. In conditionally reprogramed matched tumor and normal prostate cells, the cleavage of PARP1 confirmed the specific increase in apoptosis of tumor cells. In summary, Strigolactone analogues are promising candidates for anticancer therapy by their ability to specifically induce cell cycle arrest, cellular stress and apoptosis in tumor cells with minimal effects on growth and survival of normal cells.

Publication Title

Strigolactone analogues induce apoptosis through activation of p38 and the stress response pathway in cancer cell lines and in conditionally reprogrammed primary prostate cancer cells.

Sample Metadata Fields

Cell line, Time

View Samples
accession-icon GSE18938
Effect of EGF and/or HER2 on the growth of MCF10A cells on extracellular matrix: time course
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Mammary epithelial cells MCF10A and HER2 overexpressing MCF10A cells were grown on matrigel in the absence or presence of epidermal growth factor. Cells were lysed and RNA was collected at 1.5,3,5,7,9 days.

Publication Title

Modeling ductal carcinoma in situ: a HER2-Notch3 collaboration enables luminal filling.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE27629
Two phases of mitogenic signaling unveil roles for p53 and EGR1 in elimination of inconsistent growth signals
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Normal cells require continuous exposure to growth factors, in order to cross a restriction point and commit to cell cycle progression. This can be replaced by two short, appropriately spaced pulses of growth factors, where the first pulse primes a process, which is completed by the second pulse, and enables restriction point crossing. Through integration of comprehensive proteomic and transcriptomic analyses of each pulse, we identified three processes that regulate restriction point crossing: (i) The first pulse induces essential metabolic enzymes and activates p53-dependent restraining processes. (ii) The second pulse eliminates, via the PI3K/AKT pathway, the suppressive action of p53, as well as (iii) sets an ERK-EGR1 threshold mechanism, which digitizes graded external signals into an all-or-none decision obligatory for S-phase entry. Together, our findings uncover novel gating mechanisms, which ensure that cells ignore fortuitous growth factors, and undergo proliferation only in response to consistent mitogenic signals.

Publication Title

Two phases of mitogenic signaling unveil roles for p53 and EGR1 in elimination of inconsistent growth signals.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE6786
HeLa cells and MCF10A cells subject to EGF stimulation
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A module of negative feedback regulators defines growth factor signaling.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE6783
Expression data from HELA cells subject to EGF stimulation
  • organism-icon Homo sapiens
  • sample-icon 7 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

HELA cells derived from human cervical tumor were subjected to EGF stimulation for 0,20,40,60,120,240 and 480 minutes.

Publication Title

A module of negative feedback regulators defines growth factor signaling.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE6784
Expression data from MCF10A cells subject to EGF stimulation
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge Icon

Description

MCF10A cells derived from spontaneously immortalized normal human mammary epithel were subjected to EGF/SERUM stimulation for 0,20,40,60,120,240 and 480 minutes.

Publication Title

A module of negative feedback regulators defines growth factor signaling.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP098688
Epigenetic mechanisms underlie the crosstalk between growth factors and a steroid hormone [HCT RNA-Seq]
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Growth factors (GFs) suppression by steroid hormones recurs in embryology and is co-opted in pathology. While studying mammary cell migration, which is stimulated by GFs and antagonized by glucocorticoids (GCs), we found that GCs inhibit positive feedback loops activated by GFs and stimulate the reciprocal negative loops. Although no alterations in DNA methylation accompany the transcriptional events instigated by either stimulus, forced demethylation of distal regions broadened the repertoire of inducible genes. Our data indicate that the crosstalk involve transcription factors like p53 and NF-kB, along with reduced pausing (and traveling) of RNA polymerase II (RNAPII) at the promoters (and bodies) of GF-inducible genes. In addition, while GFs hyper-acetylated chromatin at unmethylated promoters and enhancers of genes involved in motility, GCs hypo-acetylated the corresponding regions. In conclusion, stably unmethylated genomic regions that encode feedback regulatory modules and differentially recruit RNAPII and acetylases/deacetylases underlie suppression of growth factor signaling by glucocorticoids. Overall design: RNA-Seq – EGF treatemnt for 60 min of WT and DNMT1a and DNMT3b double-knockout HCT116 cells

Publication Title

Epigenetic mechanisms underlie the crosstalk between growth factors and a steroid hormone.

Sample Metadata Fields

Treatment, Subject

View Samples
accession-icon GSE60157
Bird Factors integrate positional signals to coordinate asymmetric cell division and cell fate
  • organism-icon Arabidopsis thaliana
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

We sorted for GFP+ cells using the enhancer trap J0571 with the UAS promoter driving the expression of different BIRD genes. Different genetic backgrounds are use and listed below.

Publication Title

Transcriptional control of tissue formation throughout root development.

Sample Metadata Fields

Specimen part

View Samples
...

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact