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accession-icon GSE59237
TSLP effects on primary human blood dendritic cells
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The ontogeny of human Langerhans cells (LCs) remains poorly characterized, in particular the nature of LC precursors and the factors that may drive LC differentiation. Through a systematic transcriptomic analysis of TSLP-activated dendritic cells (DCs), we unexpectedly identified markers that have been associated with a skin-homing potential as well as with a LC phenotype. We performed transcriptomic analysis of TSLP-activated blood DCs, as compared to freshly purified, Medium-, and TNF-activated DCs. Among TSLP up-regulated genes, we identified molecules associated with skin homing, LC phenotype, and LC function, as determined by a literature-based survey. Conversely, genes not expressed in LCs were not found among TSLP-induced genes. Further experiments showed that TGF- synergized with TSLP leading to the differentiation of blood BDCA-1+ DCs into bona fide Birbeck granule-positive LCs.

Publication Title

Human blood BDCA-1 dendritic cells differentiate into Langerhans-like cells with thymic stromal lymphopoietin and TGF-β.

Sample Metadata Fields

Specimen part

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accession-icon GSE54627
Combinatorial flexibility of cytokine during Human T helper cells differentiation
  • organism-icon Homo sapiens
  • sample-icon 47 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Transcriptional analysis of human T cells differentiated in 4 T Helper context ( Th0, Th1, Th2 and Th17) in the presence or not of Interferon alpha

Publication Title

Combinatorial flexibility of cytokine function during human T helper cell differentiation.

Sample Metadata Fields

Specimen part

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accession-icon GSE57915
The combinatorial code governing cellular responses to complex stimuli
  • organism-icon Homo sapiens
  • sample-icon 43 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Integration of multiple signals shapes cell adaptation to their microenvironment through synergistic and antagonistic interactions. The combinatorial complexity governing signal integration for multiple cellular output responses has not been resolved. For outputs measured in the conditions 0 (control), signals X, Y, X+Y, combinatorial analysis revealed 82 possible interaction profiles, which we biologically assimilated to 5 positive, and 5 negative interaction modes. To experimentally validate their use in living cells, we designed an original computational workflow, and applied it to transcriptomics data of innate immune cells integrating physiopathological signal combinations. Up to 9 of the 10 defined modes coexisted in context-dependent proportions. Each integration mode was enriched in specific molecular pathways, suggesting a coupling between genes involved in particular functions, and the corresponding mode of integration. We propose that multimodality and functional coupling are general principles underlying the systems level integration of physiopathological and pharmacological stimuli by mammalian cells.

Publication Title

Combinatorial code governing cellular responses to complex stimuli.

Sample Metadata Fields

Time

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accession-icon GSE40484
Human inflammatory dendritic cells induce Th17 differentiation
  • organism-icon Homo sapiens
  • sample-icon 22 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Transcriptome analysis of five population of Antigen Presenting Cells: inflammatory macrophages, Inflammatory dendritic cells, Cd14+CD16- monocytes, CD14 dim Cd16+ monocytes and BDCA1+ Dendritic cells.

Publication Title

Human inflammatory dendritic cells induce Th17 cell differentiation.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP174055
Wnt1 silences CC/CXC motif chemokine genes in dendritic cells and induces adaptive immune resistance in lung adenocarcinoma
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Lung adenocarcinoma (LUAD)-derived oncogenic Wnts increase cancer cell proliferative/stemness potential, but whether they also impact the immune microenvironment is unknown. Here we show that LUAD cells use paracrine Wnt1 signaling to induce immune resistance. Wnt1 correlated strongly with tolerogenic genes on the TCGA expression data. In another cohort, Wnt1 was inversely associated with T cell abundance. Altering Wnt1 expression profoundly affected growth of murine lung adenocarcinomas and this was strongly dependent on conventional dendritic cells and T cells. Mechanistically, Wnt1 lead to transcriptional silencing of CC/CXC chemokines in dendritic cells and T cell cross-tolerance. Wnt-target genes were up-regulated in human intratumoral dendritic cells and decreased upon silencing Wnt1, accompanied by enhanced T cell cytotoxicity. siWnt1-loaded nanoparticles as single therapy or part of combinatorial immunotherapies acted at both arms of the cancer-immune ecosystem to halt tumor growth. Collectively, our studies show that Wnt1 enhances adaptive immune rejection of lung adenocarcinomas and highlight its potential targeting as a novel therapeutic strategy  Overall design: RNAseq data of two DC subsets of 4 patients with lung adenocarcinomas (LUADs).

Publication Title

Wnt1 silences chemokine genes in dendritic cells and induces adaptive immune resistance in lung adenocarcinoma.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

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accession-icon SRP171054
Wnt1 silences CC/CXC motif chemokine genes in dendritic cells and induces adaptive immune resistance in lung adenocarcinoma
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

This study showed that the oncogenic ligand Wnt1 silences chemokine genes in dendritic cells, leading to impaired cross-priming of T cells in lung adenocarcinoma. Blocking Wnt1 enhanced rejection of tumors by acting concomitantly at the cancer and immune cell level. Overall design: 3' RNA-Seq (QuantSeq) profiling of sorted cDCs populations from WNT1 overexpressing and control (Empty) lung tumors.

Publication Title

Wnt1 silences chemokine genes in dendritic cells and induces adaptive immune resistance in lung adenocarcinoma.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP109541
Transcriptomic analysis of miR-19a-19b-20a subcluster-overexpressed fibroblasts in bleomycin-induced lung fibrosis
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

Lung fibroblasts play a pivotal role in pulmonary fibrosis, a devastating lung diseases, by producing extracellular matrix. MicroRNAs (miRNAs) suppress a lot of genes posttranscriptionally, but the dynamics and the role of miRNAs in activated lung fibroblasts in fibrotic lung has been poorly understood. We found miR-19a, 19b and 20a subcluster expression increased in activated lung fibroblasts as the fibrosis progression. To elucidate whether fibroblast-specific intervention against miR-19a, 19b and 20a subcluster modulates pathogenic activation of lung fibroblasts in vivo, we intratracheally-transferred the subcluster-overexpressed fibroblasts into bleomycin-treated lungs and performed global transcriptome analysis. Overall design: miR-19a, 19b and 20a subcluster-overexpressed fibroblasts and mock-expressed fibroblasts were intratracheally-transferred to B6 mice at day 7 post-administration of 2 mg/kg of bleomycin. Donor cells were recoverred at day 3 post-transfer by cell sotring. Global transcriptome of transferred fibroblasts was generated by 3'SAGE-seq using Ion Proton sequencer.

Publication Title

Lung fibroblasts express a miR-19a-19b-20a sub-cluster to suppress TGF-β-associated fibroblast activation in murine pulmonary fibrosis.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP070835
Transcriptomes of individual substantia nigra pars reticulata neurons
  • organism-icon Mus musculus
  • sample-icon 320 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Certain neuron types fire spontaneously at high rates, an ability that is crucial for their function in brain circuits. The spontaneously active GABAergic neurons of the substantia nigra pars reticulata (SNr), a major output of the basal ganglia, provide tonic inhibition of downstream brain areas. A depolarizing "leak" current supports this firing pattern, but its molecular basis remains poorly understood. To understand how SNr neurons maintain tonic activity, we used single-cell RNA sequencing to determine the transcriptome of individual SNr neurons. We discovered that SNr neurons express the sodium leak current, NaLCN and that SNr neurons lacking NaLCN have impaired spontaneous firing. Overall design: RNA sequencing profiles from 87 GFP-positive GABAergic SNr neurons and 9 GFP-negative SNr cells were carried out. However only 80 samples that passed initial quality control and that were included in the data processing are represented in this record.

Publication Title

The leak channel NALCN controls tonic firing and glycolytic sensitivity of substantia nigra pars reticulata neurons.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP072289
Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Gene expression heterogeneity in the pluripotent state of mouse embryonic stem cells (mESCs) has been increasingly well-characterized. In contrast, exit from pluripotency and lineage commitment have not been studied systematically at the single-cell level. Here we measured the gene expression dynamics of retinoic acid driven mESC differentiation using an unbiased single-cell transcriptomics approach. We found that the exit from pluripotency marks the start of a lineage bifurcation as well as a transient phase of susceptibility to lineage specifying signals. Our study revealed several transcriptional signatures of this phase, including a sharp increase of gene expression variability and a handover between two classes of transcription factors. In summary, we provide a comprehensive analysis of lineage commitment at the single cell level, a potential stepping stone to improved lineage control through timing of differentiation cues. Overall design: Bulk and single-cell RNA-seq (SCRB-seq and SMART-seq) of mouse embryonic stem cells after different periods of continuous exposure to retinoic acid. Bulk RNA-seq of cell lines derived after retinoic exposure and after differentiation with retinoic acid and MEK inhibitor combined.

Publication Title

Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells.

Sample Metadata Fields

Cell line, Subject

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accession-icon SRP169611
Next generation sequencing of human hepatic stellate cell line, LX-2 treated with recombinant human TGF-ß1, with DMSO or ML290 (5 µM) for 72h.
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

The overall aim of this experiment was to identify specific genes and molecular pathways regulated by ML290, a small molecule agonist of the relaxin receptor, RXFP1, in the context of liver fibrosis. Overall design: Whole transcriptome mRNA sequencing of transformed LX-2 cells using HiSeq platforms with paired-end 150 bp (PE 150) sequencing strategy, with four biological replicates in each treatment group.

Publication Title

Therapeutic effects of a small molecule agonist of the relaxin receptor ML290 in liver fibrosis.

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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