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accession-icon GSE53403
Expression data from mouse adipose tissue macrophage
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

In mammals, expansion of adipose tissue mass induces accumulation of adipose tissue macrophages (ATMs). We isolated CD11c- (FB) and CD11c+ (FBC) perigonadal ATMs from SVCs of lean (C57BL/6J Lep +/+) and obese leptin-deficient (C57BL/6J Lep ob/ob) mice.

Publication Title

Obesity activates a program of lysosomal-dependent lipid metabolism in adipose tissue macrophages independently of classic activation.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE22432
TGF-1 Accelerates Dendritic Cell Differentiation from Common Dendritic Cell Progenitors (CDPs) and Directs Subset Specification Towards Conventional Dendritic Cells
  • organism-icon Mus musculus
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Dendritic cells (DCs) in lymphoid tissue comprise conventional DCs (cDCs) and plasmacytoid DCs (pDCs) that develop from common DC progenitors (CDPs). CDPs are Flt3+c-kitintM-CSFR+ and reside in bone marrow. Here we describe a two-step culture system that recapitulates DC development from c-kithiFlt3-/lo multipotent progenitors (MPPs) into CDPs and further into cDC and pDC subsets. MPPs and CDPs are amplified in vitro with Flt3 ligand, stem cell factor, hyper-IL-6 and insulin- like growth factor-1. The four-factor cocktail readily induces self-renewal of MPPs and their progression into CDPs and has no self-renewal activity on CDPs. The amplified CDPs respond to all known DC poietins and generate all lymphoid tissue DCs in vivo and in vitro. Additionally, in vitro CDPs recapitulate the cell surface marker and gene expression profile of in vivo CDPs and possess a DC-primed transcription profile. Transforming growth factor-1 (TGF-1) impacts on CDPs and directs their differentiation towards cDCs. Genome-wide gene expression profiling of TGF-1-induced genes identified transcription factors, such as interferon regulatory factor-4 (IRF-4) and RelB, that are implicated as instructive factors for cDC subset specification. TGF-1 also induced the transcription factor inhibitor of differentiation/DNA binding 2 (Id2) that suppresses pDC development. Thus, TGF-1 directs CDP differentiation into cDC by inducing both cDC instructive factors and pDC inhibitory factors.

Publication Title

TGF-beta1 accelerates dendritic cell differentiation from common dendritic cell progenitors and directs subset specification toward conventional dendritic cells.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE38614
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach
  • organism-icon Rattus norvegicus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE38584
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (7TF and control)
  • organism-icon Rattus norvegicus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE71482
Expression data from Caenorhabditis elegans fed with a Lactoferrin-based product
  • organism-icon Caenorhabditis elegans
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix C. elegans Genome Array (celegans)

Description

Lactoferrin is a highly multifunctional protein. Indeed, it is involved in many physiological functions, including regulation of iron absorption and immune responses.

Publication Title

A nutritional supplement containing lactoferrin stimulates the immune system, extends lifespan, and reduces amyloid <i>β</i> peptide toxicity in <i>Caenorhabditis elegans</i>.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE29241
Dendritic cell lineage commitment is instructed by distinct cytokine signals
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Dendritic cells (DC) develop from hematopoietic stem cells, which is guided by instructive signals through cytokines. DC development progresses from multipotent progenitors (MPP) via common DC progenitors (CDP) into DC. Flt3 ligand (Flt3L) signaling via the Flt3/Stat3 pathway is of pivotal importance for DC development under steady state conditions. Additional factors produced during steady state or inflammation, such as TGF-beta1 or GM-CSF, also influence the differentiation potential of MPP and CDP. Here, we studied how gp130, GM-CSF and TGF-beta1 signaling influence DC lineage commitment from MPP to CDP and further into DC. We observed that activation of gp130 signaling promotes expansion of MPP. Additionally, gp130 signaling inhibited Flt3L-driven DC differentiation, but had little effect on GM-CSF-driven DC development. The inflammatory cytokine GM-CSF induces differentiation of MPP into inflammatory DC and blocks steady state DC development. Global transcriptome analysis revealed a GM-CSF-driven gene expression repertoire that primes MPP for differentiation into inflammatory DC. Finally, TGF-beta1 induces expression of DC-lineage affiliated genes in MPP, including Flt3, Irf-4 and Irf-8. Under inflammatory conditions, however, the effect of TGF- beta1 is altered: Flt3 is not upregulated, indicating that an inflammatory environment inhibits steady state DC development. Altogether, our data indicate that distinct cytokine signals produced during steady state or inflammation have a different outcome on DC lineage commitment and differentiation.

Publication Title

Dendritic cell lineage commitment is instructed by distinct cytokine signals.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE5151
TGF-beta1 target genes in human dendritic cells (DC).
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U95 Version 2 Array (hgu95av2)

Description

CD34+ hematopoietic stem/progenitor cells were isolated from human cord blood and amplified in vitro for 10-14 days in serum-free medium with specific cytokines (Ju et al., Eur. J. Cell Biol. 82, 75-86, 2003; Hacker et al., Nat. Immunol. 4, 380-386, 2003). Cultured progenitor cells were induced to differentiate into DC in RPMI medium supplemented with 10% fetal calf serum, 2 mM L-glutamine, 0.1 microM Beta-mercaptoethanol, 100 U/ml penicillin and streptomycin (GIBCO-BRL) and 500 U/ml GM-CSF, 500 U/ml IL-4 for 6 days with or without 10 ng/ml TGF-beta1 as indicated (0.5x10E6 cells/ml). Every 2 days growth factors were added and cells were maintained at 0.5x10E6 cells/ml cell density. RNA was prepared and subjected to microarray analysis.

Publication Title

Transforming growth factor beta1 up-regulates interferon regulatory factor 8 during dendritic cell development.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE38585
Hierarchical regulation in a KRAS pathway-dependent transcriptional network revealed by a reverse-engineering approach (RAS-ROSE and ROSE with siRNA)
  • organism-icon Rattus norvegicus
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

RAS mutations are highly relevant for progression and therapy response of human tumours, but the genetic network that ultimately executes the oncogenic effects is poorly understood. Here we used a reverse-engineering approach in an ovarian cancer model to reconstruct KRAS oncogene-dependent cytoplasmic and transcriptional networks from perturbation experiments based on gene silencing and pathway inhibitor treatments. We measured mRNA and protein levels in manipulated cells by microarray, RT-PCR and Western Blot analysis, respectively. The reconstructed model revealed complex interactions among the transcriptional and cytoplasmic components, some of which were confirmed by double pertubation experiments. Interestingly, the transcription factors decomposed into two hierarchically arranged groups. To validate the model predictions we analysed growth parameters and transcriptional deregulation in the KRAS-transformed epithelial cells. As predicted by the model, we found two functional groups among the selected transcription factors. The experiments thus confirmed the predicted hierarchical transcription factor regulation and showed that the hierarchy manifests itself in downstream gene expression patterns and phenotype.

Publication Title

Reverse engineering a hierarchical regulatory network downstream of oncogenic KRAS.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE14359
Expression data from conventional osteosarcoma compared to primary non-neoplastic osteoblast cells
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

In osteosarcoma patients, the development of metastases, often to the lungs, is the most frequent cause of death. To improve this situation, a deeper understanding of the molecular mechanisms governing osteosarcoma development and dissemination and the identification of novel drug targets for an improved treatment are needed. Towards this aim, we characterized osteosarcoma tissue samples compared to primary osteoblast cells using Affymetrix HG U133A microarrays.

Publication Title

De novo expression of EphA2 in osteosarcoma modulates activation of the mitogenic signalling pathway.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP097691
Oncogenic PIK3CA(H1047R) and CTNNB1(stab) in intestinal organoids
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Goals of the study was to compare transcripional and phenotypic response of mouse intestinal organoid cultures to the PIK3CA(H1047R) and CTNNB1(stab) oncogenes. Overall design: Two biological replicates of organoids with transgenic tdTomato-Luciferase, tdTomato-PIK3CAH1047R, tdTomato-CTNNB1stab or td-Tomato-PIK3CAH1047R-CTNNB1stab were analysed by RNA-Seq By comparing 7-10 x 10E7 50bp paired end reads per library we identify transcriptional alterations in the intestinal epithelium following expression of each or both oncogenes,

Publication Title

Oncogenic β-catenin and PIK3CA instruct network states and cancer phenotypes in intestinal organoids.

Sample Metadata Fields

Specimen part, Cell line, Subject

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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