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accession-icon GSE24434
Host cell transcriptome response to expression of the human cytomegalovirus (hCMV) 72-kDa immediate-early 1 (IE1) protein
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Human cytomegalovirus (hCMV) is a highly prevalent pathogen that, upon primary infection, establishes life-long persistence in all infected individuals. Acute hCMV infections cause a variety of diseases in humans with developmental or acquired immune deficits. In addition, persistent hCMV infection may contribute to various chronic disease conditions even in immunologically normal people. The pathogenesis of hCMV disease has been frequently linked to inflammatory host immune responses triggered by virus-infected cells. Moreover, hCMV infection activates numerous host genes many of which encode pro-inflammatory proteins. However, little is known about the relative contributions of individual viral gene products to these changes in cellular transcription. We systematically analyzed the effects of the hCMV 72-kDa immediate-early 1 (IE1) protein, a major transcriptional activator and antagonist of type I interferon (IFN) signaling, on the human transcriptome. Following expression under conditions closely mimicking the situation during productive infection, IE1 elicits a global type II IFN-like host cell response. This response is dominated by the selective up-regulation of immune stimulatory genes normally controlled by IFN-gamma and includes the synthesis and secretion of pro-inflammatory chemokines. IE1-mediated induction of IFN-stimulated genes strictly depends on tyrosine-phosphorylated signal transducer and activator of transcription 1 (STAT1) and correlates with the nuclear accumulation and sequence-specific binding of STAT1 to IFN-gamma-responsive promoters. However, neither synthesis nor secretion of IFN-gamma or other IFNs seems to be required for the IE1-dependent effects on cellular gene expression. Our results demonstrate that a single hCMV protein can trigger a pro-inflammatory host transcriptional response via an unexpected STAT1-dependent but IFN-independent mechanism and identify IE1 as a candidate determinant of hCMV pathogenicity.

Publication Title

Human cytomegalovirus IE1 protein elicits a type II interferon-like host cell response that depends on activated STAT1 but not interferon-γ.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE46970
Gene expression of 4, 5, and 6 days differentiated Flk1+ WT ES cells, and of 6 days differentiated Flk1+ Runx1-/- and Tal-1-/- ES cells
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

In order to identify genes that are activated in differentiating WT ESCs, but are missing in Tal-1-/- and Runx1-/- ESCs, and which might be involved in the generation of definitive hematopoietic progenitors and their specification thereafter, we performed microarray analyses on purified Flk-1+ cells, differentiated from these ESCs for 4, 5, and 6 days in vitro.

Publication Title

Ectopic Runx1 expression rescues Tal-1-deficiency in the generation of primitive and definitive hematopoiesis.

Sample Metadata Fields

Specimen part, Cell line, Time

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accession-icon GSE39788
Mapping of Three Genetic Determinants of Susceptibility to Estrogen-Induced Mammary Cancer within the Emca8 Locus on Rat Chromosome 5
  • organism-icon Rattus norvegicus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

We are using the ACI rat model of 17beta-estradiol induced mammary cancer to define the mechanisms through which estrogens contribute to breast cancer development; identify and functionally characterize the genetic variants that determine susceptibility; and define the hormone-gene-environment interactions that influence development of mammary cancer in this physiologically relevant rat model. Female ACI rats are uniquely susceptible to development of mammary cancer when treated continuously with physiologic levels of 17beta-estradiol. Induction of mammary cancer in female ACI rats occurs through a mechanism that is largely dependent upon estrogen receptor-alpha. Interval mapping analyses of progeny generated in intercrosses between susceptible ACI rats and resistant Brown Norway (BN) rats revealed seven quantitative trait loci (QTL), designated Emca3 (Estrogen-induced mammary cancer) through Emca9, each of which harbors one or more genetic determinants of mammary cancer susceptibility. Genes that reside within Emca8 on RNO5 and were differentially expressed between 17beta-estradiol treated ACI and ACI.BN-Emca8 congenic rats were identified as Emca8 candidates.

Publication Title

Mapping of three genetic determinants of susceptibility to estrogen-induced mammary cancer within the Emca8 locus on rat chromosome 5.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE7638
Expression data from monocytes of individuals with different collateral flow index CFI
  • organism-icon Homo sapiens
  • sample-icon 160 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

using peripheral blood monocytes to identify marker genes for an extensively grown coronary collateral circulation.

Publication Title

Non-invasive gene-expression-based detection of well-developed collateral function in individuals with and without coronary artery disease.

Sample Metadata Fields

Sex, Age

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accession-icon GSE140939
Virus-induced immune response during pregnancy
  • organism-icon Homo sapiens
  • sample-icon 92 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Transcriptome Array 2.0 (hta20)

Description

We evaluated transcriptional profiles in peripheral blood mononuclear cells (PBMCs) from 54 pregnant women in Kenya, 19 of whom delivered preterm.

Publication Title

Influenza-Induced Interferon Lambda Response Is Associated With Longer Time to Delivery Among Pregnant Kenyan Women.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon SRP100686
Novel SF3B1 Deletion Mutations Result in Aberrant RNA Splicing in CLL Patients
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Recurrent mutations in RNA splicing factors SF3B1, U2AF1, and SRSF2 have been reported in hematologic cancers including myelodysplastic syndromes (MDS) and chronic lymphocytic leukemia (CLL). However, SF3B1 is the only splicing associated gene to be found mutated in CLL and has been shown to induce aberrant splicing. To investigate if any other genomic aberration caused similar transcriptome changes, we clustered RNASeq samples based on an alternative 3' splice site (ss) pattern previously identified in SF3B1-mutant CLL patients. Out of 215 samples, we identified 37 (17%) with alternative 3' ss usage, the majority of which harbored known SF3B1 hotspot mutations. Interestingly, 3 patient samples carried previously unreported in-frame deletions in SF3B1 around K700, the most frequent mutation hotspot. To study the functional effects of these deletions, we used various minigenes demonstrating that recognition of canonical 3' ss and alternative branchsite are required for aberrant splicing, as observed for SF3B1 p.K700E. The common mechanism of action of these deletions and substitutions result in similar sensitivity of primary cells towards splicing inhibitor E7107. Altogether, these data demonstrate that novel SF3B1 in-frame deletion events identified in CLL result in aberrant splicing, a common biomarker in spliceosome-mutant cancers. Overall design: 13 CLL samples, 5 SF3B1 WT, 5 SF3B1 p.K700E, and 3 with in-frame deletions around the K700 position of SF3B1

Publication Title

Novel <i>SF3B1</i> in-frame deletions result in aberrant RNA splicing in CLL patients.

Sample Metadata Fields

Disease, Disease stage, Subject

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accession-icon GSE25571
Expression analysis of genes located in the minimally deleted regions of 13q14 and 11q22-23 in chronic lymphocytic leukemia unexpected expression pattern of the RHO GTPase activator ARHGAP20
  • organism-icon Homo sapiens
  • sample-icon 199 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

In chronic lymphocytic leukemia (CLL), 13q14 and 11q22-23 deletions are found in 2/3 of the cases. 11q22-23 deletions are associated with poor survival, whereas 13q14 deletions as single abnormality are often found in indolent disease forms. The molecular basis for this difference in prognosis is not known.

Publication Title

Expression analysis of genes located in the minimally deleted regions of 13q14 and 11q22-23 in chronic lymphocytic leukemia-unexpected expression pattern of the RHO GTPase activator ARHGAP20.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE22762
An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia
  • organism-icon Homo sapiens
  • sample-icon 194 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Chronic lymphocytic leukemia (CLL) is a common and heterogeneous disease. An accurate prediction of outcome is highly relevant for the development of personalized treatment strategies. Microarray technology was shown to be a useful tool for the development of prognostic gene expression scores. However, there are no gene expression scores which are able to predict overall survival in CLL based on the expression of few genes that are better than established prognostic markers. We correlated 151 CLL microarray data sets with overall survival using Cox regression and supervised principal component analysis to derive a prognostic score. This score based on the expression levels of eight genes and was validated in an independent group of 149 CLL patients by quantitative real time PCR. The score was predictive for overall survival and time to treatment in univariate Cox regression in the validation data set (both: p<0.001) and in a multivariate analysis after adjustment for 17p and 11q deletions and the IgVH-status. The score achieved superior prognostic accuracy compared to models based on genomic aberrations and IgVH-status and may support personalized therapy.

Publication Title

An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE16200
Loss of Syk in normal breast cells
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Loss of Syk in normal breast cells in vivo and in vitro: gene expression and phenotypic switch to stem-cell like with induction of invadopodia

Publication Title

Tumor suppressor function of Syk in human MCF10A in vitro and normal mouse mammary epithelium in vivo.

Sample Metadata Fields

Cell line

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accession-icon SRP102949
RNA-Seq of ILC2p WT
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We have generated RNA-seq of ILC2 progenitors form WT bone marrow mice. Overall design: Sorted ILC2p from 8 week-old mice were analysed in RNA-seq. Each replicate is a pool of 8 mice.

Publication Title

Androgen signaling negatively controls group 2 innate lymphoid cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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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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