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accession-icon SRP089875
Zebrafish microglia transcriptome
  • organism-icon Danio rerio
  • sample-icon 10 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2500

Description

Purpose: Identify zebrafish microglia transcriptome in the healthy and neurodegenerative brain. Methods: RNA sequencing was performed on FACS-sorted microglia (3x), other brain cells (3x) and activated microglia (4x). Microglia activation was induced using nitroreductase-mediated cell ablation. 10-20 million reads per sample were obtained. Reads were mapped to zebrafish genome GRC10. Results: We identified the zebrafish microglia transcriptome, which shows overlap with previously identified mouse microglia transcriptomes. Transcriptomes obtained 24h and 48h after treatment appeared highly similar. Therefore, these datasets were pooled. Additionally, we identified an acute proliferative response of microglia to induced neuronal cell death. Overall design: Zebrafish microglia transcriptomes of homeostatic microglia (triplicate), other brain cells (triplicate), activated microglia 24h (duplo), activated microglia 48h (duplo). In data analysis all activated microglia samples were pooled.

Publication Title

Identification of a conserved and acute neurodegeneration-specific microglial transcriptome in the zebrafish.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP174051
TNF induces Glucocorticoid Resistance by reshaping the GR Nuclear Cofactor Profile: Investigation of TNF mediated effects on the GR mediated gene expression
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

Glucocorticoid resistance (GCR) is defined as an unresponsiveness to the anti-inflammatory properties of glucocorticoids (GCs) and their receptor, the glucocorticoid receptor (GR). It is a serious problem in the management of inflammatory diseases and occurs frequently. The strong pro-inflammatory cytokine TNF induces an acute form of GCR, not only in mice, but also in several cell lines, e.g. in the hepatoma cell line BWTG3, as evidenced by impaired Dexamethasone (Dex)-induced GR-dependent gene expression. We report that TNF has a significant and broad impact on the transcriptional performance of GR, but no impact on nuclear translocation, dimerization or DNA binding capacity of GR. Proteome-wide proximity-mapping (BioID), however, revealed that the GR interactome is strongly modulated by TNF. One GR cofactor that interacts significantly less with the receptor under GCR conditions is p300. NF?B activation and p300 knockdown both reduce transcriptional output of GR, whereas p300 overexpression and NF?B inhibition revert TNF-induced GCR, which is in support of a cofactor reshuffle model. This hypothesis is supported by FRET studies. This mechanism of GCR opens new avenues for therapeutic interventions in GCR diseases Overall design: Examination of GR induced gene expression in 4 conditions (1 control: NI and 3 treated: DEX, TNF, TNFDEX) starting from 3 biological replicates

Publication Title

TNF-α inhibits glucocorticoid receptor-induced gene expression by reshaping the GR nuclear cofactor profile.

Sample Metadata Fields

Specimen part, Cell line, Treatment, Subject

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accession-icon GSE19188
Expression data for early stage NSCLC
  • organism-icon Homo sapiens
  • sample-icon 156 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of NSCLC. A prognostic signature of 17 genes showed the best association with post-surgery survival time. The performance of the signatures was validated using a patient cohort of similar size

Publication Title

Gene expression-based classification of non-small cell lung carcinomas and survival prediction.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE85044
Specific myelomonocytic cells heavily infiltrate orthotopic lung tumors and display a hypoxia-driven micro-RNA expression signature that directs tumor-supporting functions and negatively impacts on clinical outcome
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Targeting immunomodulatory pathways has ushered a new era in lung cancer therapy. Further progress requires deeper insights into the nature and dynamics of immune cells in the lung cancer micro-environment. Dendritic cells (DCs) represent a heterogenous and highly plastic immune cell system with a central role in controlling immune responses. The intratumoral infiltration and activation status of DCs emerge as clinically relevant parameters in lung cancer. In this study we used an orthotopic preclinical model of lung cancer to interrogate the transcriptome of lung tumor-infiltrating DCs and extract novel biologically and clinically relevant information. Lung tumor-infiltrating leukocytes expressing generic DC markers were found to predominantly consist of CD11b+ cells which, compared to peritumoral lung DC counterparts, strongly over-express the T cell inhibitory molecule PD-L1 and acquire classic markers of tumor-supporting macrophages (TAM) on their surface. Transcriptome analysis of these CD11b+ tumor-infiltrating DCs (TIDCs) indicates impaired anti-tumoral immunogenicity, confirms the skewing towards TAM-related features, and indicates exposure to a hypoxic environment. In paralled, TIDCs display a specific micro-RNA signature dominated by the prototypical lung cancer oncomir miR-31. Hypoxia was found to drive intrinsic miR-31 expression in CD11b+DCs. Conditioned medium of mir-31-overexpressing CD11b+DCs induces pro-invasive lung cancer cell shape changes and is enriched with the pro-metastatic factors S100A8 and S100A9. Finally, analysis of TCGA datasets reveals that the TIDC-associated miRNA signature has a negative prognostic impact in non-small cell lung cancer. Together, these data suggest a novel mechanism through which lung cancer co-opts the plasticity of the DC system to support tumoral progression. Targeting immunomodulatory pathways has ushered a new era in lung cancer therapy. Further progress requires deeper insights into the nature and dynamics of immune cells in the lung cancer micro-environment. Dendritic cells (DCs) represent a heterogenous and highly plastic immune cell system with a central role in controlling immune responses. The intratumoral infiltration and activation status of DCs emerge as clinically relevant parameters in lung cancer. In this study we used an orthotopic preclinical model of lung cancer to interrogate the transcriptome of lung tumor-infiltrating DCs and extract novel biologically and clinically relevant information. Lung tumor-infiltrating leukocytes expressing generic DC markers were found to predominantly consist of CD11b+ cells which, compared to peritumoral lung DC counterparts, strongly over-express the T cell inhibitory molecule PD-L1 and acquire classic markers of tumor-supporting macrophages (TAM) on their surface. Transcriptome analysis of these CD11b+ tumor-infiltrating DCs (TIDCs) indicates impaired anti-tumoral immunogenicity, confirms the skewing towards TAM-related features, and indicates exposure to a hypoxic environment. In paralled, TIDCs display a specific micro-RNA signature dominated by the prototypical lung cancer oncomir miR-31. Hypoxia was found to drive intrinsic miR-31 expression in CD11b+DCs. Conditioned medium of mir-31-overexpressing CD11b+DCs induces pro-invasive lung cancer cell shape changes and is enriched with the pro-metastatic factors S100A8 and S100A9. Finally, analysis of TCGA datasets reveals that the TIDC-associated miRNA signature has a negative prognostic impact in non-small cell lung cancer. Together, these data suggest a novel mechanism through which lung cancer co-opts the plasticity of the DC system to support tumoral progression.

Publication Title

The transcriptome of lung tumor-infiltrating dendritic cells reveals a tumor-supporting phenotype and a microRNA signature with negative impact on clinical outcome.

Sample Metadata Fields

Specimen part

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accession-icon GSE84179
Effects of digested onion extracts on intestinal gene expression using rat intestine slices
  • organism-icon Rattus norvegicus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.1 ST Array (ragene11st)

Description

Rat small intestine precision cut slices were exposed for 6 hours to in vitro digested yellow (YOd) and white onion extracts (WOd) that was followed by transcriptomics analysis. The digestion was performed to mimic the digestion that in vivo takes place in the stomach and small intestine. The transcriptomics response of the rat small intestine precision cut slices was compared to that of human Caco-2 cells and the pig in-situ small intestinal segment perfusion. The microarray data for the human Caco-2 cells (GSE83893) and the pig in-situ small intestinal segment perfusion (GSE83908) have been submitted separately from the current data on rat intestine. The goal was to obtain more insight into to which extent mode of actions depend on the experimental model. A main outcome was that each of the three models pointed to the same mode of action: induction of oxidative stress and particularly the Keap1-Nrf2 pathway.

Publication Title

Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE83893
The effect of onion exposure on gene expression profiles in intestinal Caco-2 cells
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Background: Human intestinal tissue samples are barely accessible to study potential health benefits of nutritional compounds. Numbers of animals used in animal trials, however, need to be minimalized. Therefore, in this study we explored the applicability of an in vitro model, namely human intestinal Caco-2 cells, to study the effect of food compounds on (intestinal) health. In vitro digested yellow (YOd) and white onion extracts (WOd) were used as model food compounds and transcriptomics was applied to obtain more insight into their mode of actions in the intestinal cells. Methods: Caco-2 cells were incubated with in vitro digested onion extracts for 6 hours, total RNA was extracted and Affymterix Human Gene 1.1 ST arrays were used to analyze the gene expression profiles. To identify onion-induced gene expression profiles in Caco-2 cells, digested yellow onion and white onion samples were compared to a digest control samples. Results: We found that yellow onion (n=5586, p<0.05) had a more pronounced effect on gene expression than white onion (n=3688, p<0.05). However, a substantial number of genes (n=3281, p<0.05) were affected by both onion variants in the same direction. Pathway analyses revealed that mainly processes related to oxidative stress, and especially the Keap1-Nrf2 pathway, were affected by onions. Our data fit with previous in vivo studies showing that the beneficial effects of onions are mostly linked to their antioxidant properties. Conclusion: our data indicate that the in vitro Caco-2 intestinal model can be used to determine modes of action of nutritional compounds and can thereby reduce the number of animals used in conventional nutritional intervention studies.

Publication Title

Effects of Digested Onion Extracts on Intestinal Gene Expression: An Interspecies Comparison Using Different Intestine Models.

Sample Metadata Fields

Cell line

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accession-icon GSE149619
Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE149618
Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection (microarray)
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The phenotypic and functional dichotomy between IRF8+ type 1 and IRF4+ type 2 conventional dendritic cells (cDC1-cDC2) is well accepted; it is unknown how robust this dichotomy is under inflammatory conditions, when additionally monocyte-derived cells (MCs) become competent antigen presenting cells (APC). Using single-cell technologies in models of respiratory viral infection, we found that lung cDC2s acquired expression of Fc receptor CD64 shared with MCs, and of IRF8 shared with cDC1s. These inflammatory (Inf-)cDC2s were superior in inducing CD4+ T helper (Th) cell polarization while simultaneously presenting antigen to CD8+ T cells. When carefully separated from inf-cDC2s, MCs lacked APC function. Inf-cDC2 matured in response to cell-intrinsic toll-like receptor and type 1 interferon receptor signaling, upregulated an IRF8-dependent maturation module and acquired antigens via convalescent serum and Fc receptors. Since hybrid inf-cDC2s are easily confused with monocyte-derived cells, their existence could explain why APC functions have been attributed to MCs.

Publication Title

Inflammatory Type 2 cDCs Acquire Features of cDC1s and Macrophages to Orchestrate Immunity to Respiratory Virus Infection.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16476
Integrated bioinformatic and wet-lab approach to identify potential oncogenic networks in neuroblastoma
  • organism-icon Homo sapiens
  • sample-icon 86 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

mRNA profiles of thousands of human tumors are available, but methods to deduce oncogenic signaling networks from these data lag behind. It is especially challenging to identify main-regulatory routes, and to generalize conclusions obtained from experimental models. We designed the bioinformatic platform R2 in parallel with a wet-lab approach of neuroblastoma. Here we demonstrate how R2 facilitates an integrated analysis of our neuroblastoma data. Analysis of the MYCN pathway suggested important regulatory connections to the polyamine synthesis route, the Notch pathway and the BMP/TGF pathway. A network of genes emerged connecting major oncogenes in neuroblastoma. Genes in the network carried strong prognostic values and were essential for tumor cell survival.

Publication Title

Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes.

Sample Metadata Fields

Specimen part

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accession-icon SRP111402
Next Generation Sequencing of total RNA from 9 bladder cancer cell lines and 3 fractionated bladder cancer cell lines
  • organism-icon Homo sapiens
  • sample-icon 57 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, NextSeq 500

Description

We profile the cell line expression of 279 circRNAs, that are highly expressed across 457 bladder cancer patient samples. Additionally, we investigate their cellular location in fractionated cell lines Overall design: 9 bladder cancer cell lines and 3 fractionated bladder cancer cell lines

Publication Title

Circular RNA expression is abundant and correlated to aggressiveness in early-stage bladder cancer.

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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