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accession-icon GSE61670
Modulation of the cancer cell transcriptome by culture media formulations and cell density
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

We investigated how varying the composition of cell culture formulations and growing cancer cells at different densities might affect tumor cells genotype. Specifically, we compared gene expression profiles generated by human MDA-MB-231 human breast cancer cells cultured in different media (MEM, DMEM, or RPMI 1640) containing different concentrations of fetal bovine serum (FBS) or different sera (equine or bovine) that were grown at different cell densities.

Publication Title

Modulation of the cancer cell transcriptome by culture media formulations and cell density.

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon SRP091764
Modeling signaling-dependent pluripotent cell states with boolean logic can predict cell fate transitions [II]
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Pluripotent stem cells (PSCs) exist in multiple stable states, each with specific cellular properties and molecular signatures. The process by which pluripotency is either maintained or destabilized to initiate specific developmental programs is poorly understood. We have developed a model to predict stabilized PSC gene regulatory network (GRN) states in response to combinations of input signals. While previous attempts to model PSC fate have been limited to static cell compositions, our approach enables simulations of dynamic heterogeneity by combining an Asynchronous Boolean Simulation (ABS) strategy with simulated single cell fate transitions using a Strongly Connected Components (SCCs). This computational framework was applied to a reverse-engineered and curated core GRN for mouse embryonic stem cells (mESCs) to simulate responses to LIF, Wnt/ß-catenin, FGF/ERK, BMP4, and Activin A/Nodal pathway activation. For these input signals, our simulations exhibit strong predictive power for gene expression patterns, cell population composition, and nodes controlling cell fate transitions. The model predictions extend into early PSC differentiation, demonstrating, for example, that a Cdx2-high/Oct4-low state can be efficiently generated from mESCs residing in a naïve and signal-receptive state sustained by combinations of signaling activators and inhibitors. Overall design: Examination of perturbed PSCs versus control PSCs and mesoderm progenitors Mouse pluripotent stem cells were grown on tissue culture plates for two days in serum-containing, feeder free medium supplemented with the following cytokines/small molecules: 2i = CHIR99021 (Reagents Direct 27-H76 – 3µM) & PD0325901 (Reagents Direct 39-C68 – 1µM) Jaki = JAK inhibitor (EMD Millipore 420097 – 2.0µM) BMP = BMP4 (R&D Systems 314-BP-010 – 10ng/ml) Alk5i = ALK5 inhibitor II (Cedarlane ALX-270-445 - 10µM)

Publication Title

Modeling signaling-dependent pluripotency with Boolean logic to predict cell fate transitions.

Sample Metadata Fields

Cell line, Treatment, Subject, Time

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accession-icon GSE29110
Fibrogenic and redox-related but not proinflammatory genes are upregulated in lewis rat model of chronic silicosis
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Silicosis, a fibrotic granulomatous lung disease, may occur through accidental high-dose or occupational inhalation of silica, leading to acute/accelerated and chronic silicosis, respectively. While chronic silicosis has a long asymptomatic latency, lung inflammation and apoptosis are hallmarks of acute silicosis. In animal models, histiocytic granulomas develop within days after high-dose intratracheal silica instillation. However, following chronic inhalation of occupationally relevant doses of silica, discrete granulomas resembling human silicosis arise months after the final exposure without significant lung inflammation/apoptosis. To identify molecular events associated with chronic silicosis, lung RNAs from controls or chronically silica-exposed rats were analyzed by Affymetrix at 28 wk after silica exposures. Results suggested a significant upregulation of 144 genes and downregulation of seven genes. The upregulated genes included complement cascade, chemokines/chemokine receptors, G-protein signaling components, metalloproteases, and genes associated with oxidative stress. To examine the kinetics of gene expression relevant to silicosis, qPCR, ELISA, Luminex-bead assays, Western blotting, and/or zymography were performed on lung tissues from 4 d, 28 wk, and intermediate times after chronic silica exposure and compared with 14 d acute silicosis samples. Results indicated that genes regulating fibrosis (secreted phosphoprotein-1, CCL2, and CCL7), redox enzymes (superoxide dismutase-2 and arginase-1), and the enzymatic activities of matrix metalloproteinases 2 and 9 were upregulated in acute and chronic silicosis; however, proinflammatory cytokines were strongly upregulated only in acute silicosis. Thus, inflammatory cytokines are associated with acute but not chronic silicosis; however, genes regulating fibrosis, oxidative stress, and metalloproteases may contribute to both acute and chronic silicosis.

Publication Title

Fibrogenic and redox-related but not proinflammatory genes are upregulated in Lewis rat model of chronic silicosis.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE24145
Soybean root hair cell response to Bradyrhizobium japonicum inoculation
  • organism-icon Glycine max
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Soybean Genome Array (soybean)

Description

Soybean root hair transcriptional response to their inoculation by the symbiotic bacteria B. japonicum involved in soybean nodulation. We used the first generation of an Affymetrix microarray to quantify the abundance of the transcripts from soybean root hair cells inoculated and mock-inoculated by B. japonicum. This experiment was performed on a time-course from 6 to 48 hours after inoculation.

Publication Title

Complete transcriptome of the soybean root hair cell, a single-cell model, and its alteration in response to Bradyrhizobium japonicum infection.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE47973
Expression data of LNCaP and MDA PCa 2b cells in absence or presence of IL6
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Prostate cancer (PCa) development and progression are associated with chronic inflammation. The cytokine interleukin (IL)-6 can influence progression, differentiation, survival, and angiogenesis of PCa. To identify novel pathways that are triggered by IL-6, we performed a gene expression profiling of two PCa cell lines, LNCaP and MDA PCa 2b, under treatment with 5 ng/ml IL-6. Interferon regulatory factor (IRF)9 was identified as one of the most prevalent IL-6 regulated genes in both cell lines. IRF9 is a mediator of type I interferon signaling and acts together with signal transduction and activator of transcription (STAT)1 and 2 to activate transcription of interferon responsive genes. The IL-6 regulation of IRF9 was confirmed at mRNA and protein levels by quantitative real-time PCR and Western blot, respectively, in both cell lines and could be blocked by the anti-IL-6 antibody Siltuximab. Three PCa cell lines with an autocrine IL-6 loop, PC3, DU145, and LNCaP-IL-6+, showed a high expression of IRF9. A tissue microarray with 36 malignant and adjacent 36 benign areas from prostate cancer specimens showed that IRF9 protein expression is moderately elevated in malignant areas and positively correlates with the tissue expression of IL-6. Downregulation and overexpression of IRF9 provided evidence for an interferon-independent role of IRF9 on cellular proliferation of different PCa cell lines. Furthermore, expression of IRF9 was essential to mediate the antiproliferative effects of IFN-2. We concluded that IL-6 is an inducer of IRF9 expression in prostate cancer and a sensitizer for the antiproliferative effects of IFN2.

Publication Title

IL6 sensitizes prostate cancer to the antiproliferative effect of IFNα2 through IRF9.

Sample Metadata Fields

Cell line, Treatment

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accession-icon SRP070064
The macrophage IRF8-IRF1 regulome is required for protection against infections, and is associated with chronic inflammation (RNA-Seq)
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

IRF8 and IRF1 are transcriptional regulators that play critical roles in the development and function of myeloid cells, including activation of macrophages by pro-inflammatory signals such as interferon gamma. Loss of IRF8 or IRF1 function causes severe susceptibility to infections in mice and in humans. We used chromatin immunoprecipitation sequencing and RNA sequencing in wild type, and in IRF8 and IRF1 mutant primary macrophages to systematically catalog all the genes bound by (cistromes) and transcriptionally activated (regulomes) by IRF8, IRF1, PU.1 and STAT1 including modulation of epigenetic histone marks. Of seven binding combinations identified, two (cluster 1: IRF8/IRF1/STAT1/PU.1; cluster 5: IRF1/STAT1/PU.1) were found to have a major role in controlling macrophage transcriptional programs both at basal level and following IFN? activation. They direct expression of a set of genes, the IRF8/IRF1 regulome, that play critical roles in host inflammatory and anti-microbial defenses in mouse models of neuroinflammation and of pulmonary tuberculosis, respectively. In addition, this IRF8/IRF1 regulome is enriched for genes mutated in human primary immuno-deficiencies, and with loci associated for several inflammatory diseases in humans. Overall design: Sequencing of RNA extracted for untreated or 3h IFNg-treated bone marrow derived macrophages (BMDM) obtained from wild type (B6) and in IRF8 or IRF1 mutant mice.

Publication Title

The macrophage IRF8/IRF1 regulome is required for protection against infections and is associated with chronic inflammation.

Sample Metadata Fields

Cell line, Treatment, Subject

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accession-icon GSE33341
Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 321 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the hosts inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 95 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.82). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.94, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

Publication Title

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans.

Sample Metadata Fields

Race

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accession-icon GSE19042
Synergistic Action of LIF and Glucocorticoids on pituitary corticotrophs cell line (AtT-20)
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

While the hypothalamo-pituitary-adrenal axis (HPA) activates a general stress response by increasing glucocorticoid (Gc) synthesis, biological stress resulting from infections triggers the inflammatory response through production of cytokines. The pituitary gland integrates some of these signals by responding to the pro-inflammatory cytokines IL6 and LIF and to a negative Gc feedback loop. The present work used whole-genome approaches to define the LIF/STAT3 regulatory network and to delineate cross-talk between this pathway and Gc action. Genome-wide ChIP-chip identified 3 449 STAT3 binding sites, whereas 2 396 genes regulated by LIF and/or Gc were found by expression profiling. Surprisingly, LIF on its own changed expression of only 85 genes but the joint action of LIF and Gc potentiated the expression of more than a thousand genes. Accordingly, activation of both LIF and Gc pathways also potentiated STAT3 and GR recruitment to many STAT3 targets. Our analyses revealed an unexpected gene cluster that requires both stimuli for delayed activation: 83% of the genes in this cluster are involved in different cell defense mechanisms. Thus, stressors that trigger both general stress and inflammatory responses lead to activation of a stereotypic innate cellular defense response.

Publication Title

Regulatory network analyses reveal genome-wide potentiation of LIF signaling by glucocorticoids and define an innate cell defense response.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE7253
Puberty and Diabetes in the Kidney
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

Puberty unmasks or accelerates nephropathies, including the nephropathy of diabetes mellitus (DM). A number of cellular systems implicated in the kidney disease of DM interweave, forming an interdependent functional web. We performed focused microarray analysis to test the hypothesis that one or more genes in the transforming growth factor beta (TGF-) signaling system would be differentially regulated in male rats depending on the age of onset of DM.

Publication Title

Prepubertal onset of diabetes prevents expression of renal cortical connective tissue growth factor.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP043678
Long-term survival of influenza virus infected club cells drives immunopathology
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Analysis of mRNA expression of influenza infected and uninfected pulmonary epithelial cells in vivo Overall design: Analysis of mRNA expression of influenza infected and uninfected pulmonary epithelial cells in vivo

Publication Title

Long-term survival of influenza virus infected club cells drives immunopathology.

Sample Metadata Fields

No sample metadata fields

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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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