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accession-icon SRP182665
The contribution of adenosine receptor 3-mediated signaling to TLR4-induced responses by human dendritic cells
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Human dendritic cells were exposed to LPS, in the absence and presence of adenosine receptor 3 inhibitor Overall design: 4 donors, 4 experimental conditions. VUF concentration used was 5 µM, LPS was 500 ng/ml. Exposure times were 6 hours

Publication Title

TLR-Induced IL-12 and CCL2 Production by Myeloid Cells Is Dependent on Adenosine A<sub>3</sub> Receptor-Mediated Signaling.

Sample Metadata Fields

Specimen part, Subject

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accession-icon SRP100088
Transcriptional and accessible chromatin profiles during conversion process of alternatively activated macrophages (RNA-Seq)
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Whether inflammatory macrophages can adopt features of the tissue resident niche and what mechanisms mediate phenotypic conversion remain unclear. In this study, we show by cell surface phenotyping, as well as by RNA-Seq transcriptional profiling and ATAC-Seq open chromatin regions profiling, that inflammatory monocyte can adopt a tissue resident phenotype, which is also accompanied by re-programming of the transcriptional profiles and remodeling of the open chromatin landscape. The conversion process is dependent on Vitamin A, suggesting that Vitamin A deficiency may lead to the failure to resolve inflammation, as inflammatory macrophages accumulate without adopting a tissue residency phenotype. Overall design: Monocyte-derived (N=3), tissue converted (N=3) and tissue resident (N=3) mouse peritoneal macrophages were FACS-sorted for RNASeq and ATACSeq.

Publication Title

Vitamin A mediates conversion of monocyte-derived macrophages into tissue-resident macrophages during alternative activation.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE30678
Profiling of Jurkat T cells activated with CD3, CD28 and PMA and multiple kinase inhibitors at 1 and 8 hours
  • organism-icon Homo sapiens
  • sample-icon 77 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Molecular pathway profiling of T lymphocyte signal transduction pathways; Th1 and Th2 genomic fingerprints are defined by TCR and CD28-mediated signaling.

Sample Metadata Fields

Cell line, Treatment, Time

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accession-icon GSE30674
Profiling of Jurkat T cells activated with CD3, CD28 and PMA and multiple kinase inhibitors
  • organism-icon Homo sapiens
  • sample-icon 53 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

T lymphocytes are orchestrators of adaptive immunity. Nave T cells may differentiate into the Th1, Th2, Th17 or iTreg phenotype, depending on environmental co-stimulatory signals. In order to identify the genes and pathways involved in differentiation of Jurkat T cells towards Th1 and Th2 subtypes we performed comprehensive transcriptome analyses of Jurkat T cells stimulated with various stimuli an pathway inhibitors

Publication Title

Molecular pathway profiling of T lymphocyte signal transduction pathways; Th1 and Th2 genomic fingerprints are defined by TCR and CD28-mediated signaling.

Sample Metadata Fields

Cell line, Treatment

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accession-icon GSE30676
Profiling of Jurkat T cells activated with CD3, CD28 and PMA at 1 and 8 hours
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

T lymphocytes are orchestrators of adaptive immunity. Nave T cells may differentiate into the Th1, Th2, Th17 or iTreg phenotype, depending on environmental co-stimulatory signals. In order to identify the genes and pathways involved in differentiation of Jurkat T cells towards Th1 and Th2 subtypes we performed comprehensive transcriptome analyses of Jurkat T cells stimulated with various stimuli an pathway inhibitors

Publication Title

Molecular pathway profiling of T lymphocyte signal transduction pathways; Th1 and Th2 genomic fingerprints are defined by TCR and CD28-mediated signaling.

Sample Metadata Fields

Cell line, Treatment, Time

View Samples
accession-icon SRP031459
MicroRNA profiling of primary cutaneous large B-cell lymphomas
  • organism-icon Homo sapiens
  • sample-icon 23 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

High-throughput sequencing of primary cutaneous follicle center lymphoma (PCFCL), primary cutaneous diffuse large B-cell lymphoma, leg type (PCLBCL-LT) and in vitro activated peripheral blood B-cells. We performed high-throughput sequencing analysis on frozen tumor biopsies from 19 cases of PCFCL and PCLBCL-LT to establish microRNA profiles. Cluster analysis of the complete microRNome could not distinguish between the two subtypes, but 16 single microRNAs were found to be differentially expressed. Overall design: Lymphoma miRNA profiles of were generated by deep sequencing, using Illumina Genome Analyzer II.

Publication Title

MicroRNA profiling of primary cutaneous large B-cell lymphomas.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE2665
Lymphe node vs. Tonsil
  • organism-icon Homo sapiens
  • sample-icon 19 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Lymph node vs. tonsil

Publication Title

Differential expression of a gene signature for scavenger/lectin receptors by endothelial cells and macrophages in human lymph node sinuses, the primary sites of regional metastasis.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE100020
Three-dimensional tumor cell growth stimulates autophagic flux and recapitulates chemotherapy resistance
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

Current preclinical models in tumor biology are limited in their ability to recapitulate relevant (patho-) physiological processes, including autophagy. Three-dimensional (3D) growth cultures have frequently been proposed to overcome the lack of correlation between two-dimensional (2D) monolayer cell cultures and human tumors in preclinical drug testing. Besides 3D growth, it is also advantageous to simulate shear stress, compound flux and removal of metabolites, e.g. via bioreactor systems, through which culture medium is constantly pumped at a flow rate reflecting physiological conditions. Here, we show that both Staticic 3D growth and 3D growth within a bioreactor system modulate key hallmarks of cancer cells, including proliferation and cell death as well as macroautophagy, a recycling pathway often activated by highly proliferative tumors to cope with metabolic stress. The autophagy-related gene expression profiles of 2D- and 3D-grown cells are substantially different, with the 3D-grown cells exhibiting an expression profile closely resembling the (patho-) physiological Statice of a tumor. Underscoring the importance of this pathway, autophagy-controlling transcription factors, such as TFEB and FOXO3, are upregulated in tumors, and 3D-grown cells have increased expression compared with cells grown in 2D conditions. Three-dimensional cultures depleted of the autophagy mediators BECN1, ATG5 or ATG7 or the transcription factor FOXO3, are more sensitive to cytotoxic treatment. Accordingly, combining cytotoxic treatment with compounds affecting late autophagic flux, such as chloroquine, renders the 3D-grown cells more susceptible to therapy and increases intracellular doxorubicin concentration to the level of 2D-grown cells. Altogether, 3D cultures are a valuable tool to study drug response of tumor cells, as these models recapitulate (patho-) physiologically relevant pathways, such as autophagy.

Publication Title

Three-dimensional tumor cell growth stimulates autophagic flux and recapitulates chemotherapy resistance.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE110817
A kinome-wide RNAi screen identifies ALK as a target to sensitize neuroblastoma cells for HDAC8-inhibitor treatment
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

The prognosis of advanced stage neuroblastoma patients remains poor and, despite intensive therapy, the 5-year survival rate remains less than 50%. We previously identified histone deacetylase (HDAC) 8 as an indicator of poor clinical outcome and a selective drug target for differentiation therapy in vitro and in vivo. Here we performed kinome-wide RNAi screening to identify genes that are synthetically lethal with HDAC8 inhibitors. These experiments identified the neuroblastoma predisposition gene ALK as a candidate gene. Accordingly, the combination of the ALK/MET inhibitor crizotinib and selective HDAC8 inhibitors (3-6M PCI-34051 or 10M 20a) efficiently killed neuroblastoma cell lines carrying wildtype ALK (SK-N-BE(2)-C, IMR5/75), amplified ALK (NB-1), and those carrying the activating ALK F1174L mutation (Kelly), and, in cells carrying the activating R1275Q mutation (LAN-5), combination treatment decreased viable cell count. The effective dose of crizotinib in neuroblastoma cell lines ranged from 0.05M (ALK-amplified) to 0.8M (wildtype ALK). The combinatorial inhibition of ALK and HDAC8 also decreased tumor growth in an in vivo zebrafish xenograft model. Bioinformatic analyses revealed that the mRNA expression level of HDAC8 was significantly correlated with that of ALK in two independent patient cohorts, the Academic Medical Center cohort (n=88) and the German Neuroblastoma Trial cohort (n=649), and co-expression of both target genes identified patients with very poor outcome. Mechanistically, HDAC8 and ALK converge at the level of receptor tyrosine kinase (RTK) signaling and their downstream survival pathways, such as ERK signaling. Combination treatment of HDAC8 inhibitor with crizotinib efficiently blocked the activation of growth receptor survival signaling and shifted the cell cycle arrest and differentiation phenotype toward effective cell death of neuroblastoma cell lines, including sensitization of resistant models, but not of normal cells. These findings reveal combined targeting of ALK and HDAC8 as a novel strategy for the treatment of neuroblastoma.

Publication Title

A kinome-wide RNAi screen identifies ALK as a target to sensitize neuroblastoma cells for HDAC8-inhibitor treatment.

Sample Metadata Fields

Specimen part

View Samples
accession-icon SRP172691
Single cell RNA sequencing of V?4 and V?6 ?dT cells from different tissue
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 4000

Description

IL17-producing ?d T cells (?d T17) mainly develop in the prenatal phase and persist as long-living self-renewing effector cell in all kind of tissues. They express polyclonal T-cell receptors (TCR), comprising public V?4+ and V?6+ TCRs with germline-like rearrangements. In particular, V?6+ T cells have recently been found in a variety of tissues including enthesis, gingiva or skin. However, their exchange between tissues and the mechanisms of tissue-specific adaptation and residency remain poorly understood. Here, we profiled V?6+ T cells isolated from thymus, peripheral lymph nodes (pLN) and skin through single-cell RNA-seq technology and compared those to V?4+ T cells. Our data demonstrated that V?6+ T cells formed highly homogenous cell populations that could be separated by tissue-specific gene expression signatures. Overall design: Sort V?4 and V?6 ?dT cells from peripheral lymph nodes, ear skin and thymus, then do 3'-RNA single cell sequencing (10x genomics).

Publication Title

Single-Cell Transcriptomics Identifies the Adaptation of Scart1<sup>+</sup> Vγ6<sup>+</sup> T Cells to Skin Residency as Activated Effector Cells.

Sample Metadata Fields

Age, 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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