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accession-icon GSE85543
Transcriptional effects of soluble CD40 ligand on human nave B cells
  • organism-icon Homo sapiens
  • sample-icon 39 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

We performed microarray analysis to derive gene signatures down-stream of soluble CD40 ligand stimulation in human naive B cells. Nave B cells were purified from healthy donor PBMC using negative selection beads (Miltenyi) and cultured with sCD40L at 2.5ug/ml for 6hr before microarray analysis. In the same study, cells were also harvested at day 5 post-stimulation to confirm sCD40L-induced B cell activation and proliferation. FACS analysis confirmed soluble CD40L induced up-regulation of CD86 and CD69 at 24hr. B cell proliferation was measured at day 4 post-stimulation by EdU incorporation.

Publication Title

CD40L-Dependent Pathway Is Active at Various Stages of Rheumatoid Arthritis Disease Progression.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE85544
Transcriptional effects of soluble CD40 ligand on human immature dendritic cells
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

We performed microarray analysis of sCD40L-stimulated iDC to derive a signature of CD40 activation. Human monocytes from normal healthy donors were differentiated to iDCs with GM-CSF and IL4. FACS analysis demonstrated the immature status of these cells, illustrated by low expression of CD80, CD40, and CD86. We confirmed that sCD40L induces the maturation of DCs, characterized by higher expression of CD80, HLA-DR, CD86, CD83 and CD40 and secretion of pro-inflammatory cytokines at 24hr post-stimulation. Cells were harvested at 1, 3 and 24hr post-stimulation for microarray analysis.

Publication Title

CD40L-Dependent Pathway Is Active at Various Stages of Rheumatoid Arthritis Disease Progression.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP143395
Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 134 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina Genome Analyzer IIx, Illumina HiSeq 2000

Description

Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The Assay for Transposase Accessible Chromatin (ATAC)-seq, coupled with transcription-factor motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to influence gene expression modeling.   We rigorously test our methods in the context of T Helper Cell Type  17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources (plentiful gene expression data, TF knock-outs and ChIP-seq experiments).  In this resource-rich mammalian setting our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF KO, ChIP-seq). We highlight new roles for individual TFs and groups of TFs (“TF-TF modules”) in Th17 gene regulation.  Given the popularity of ATAC-seq (a widely adapted protocol with high resolution and low sample input requirements),  we anticipate that application of our methods will improve TRN inference in new mammalian systems and be of particular use for rare, uncharacterized cell types. Overall design: Gene expression (RNA-seq) of naive and Th17- and Th0-polarized CD4 T Cells

Publication Title

Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon SRP111130
Genetic deletion or small molecule inhibition of the arginine methyltransferase PRMT5 exhibit anti-tumoral activity in mouse models of MLL-rearranged AML
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

The hematological malignancies classified as Mixed Lineage leukemias (MLL) harbor fusions of the MLL1 gene to partners that are members of transcriptional elongation complexes. MLL-rearranged leukemias are associated with extremely poor prognosis and response to conventional therapies and efforts to identify molecular targets are urgently needed. Using mouse models of MLL-rearranged acute myeloid leukemia (AML), here we show that genetic inactivation or small molecule inhibition of the protein arginine methyltransferase PRMT5 exhibit anti-tumoral activity in MLL-fusion protein driven transformation. Genome wide transcriptional analysis revealed that inhibition of PRMT5 methyltransferase activity overrides the differentiation block in leukemia cells without affecting the expression of MLL-fusion direct oncogenic targets. Furthermore, we find that this differentiation block is mediated by transcriptional silencing of the cyclin-dependent kinase inhibitor p21 (CDKN1a) gene in leukemia cells. Our study provides pre-clinical rationale for targeting PRMT5 using small molecule inhibitors in the treatment of leukemias harboring MLL-rearrangements. Overall design: RNA-seq data from 72h-treated DMSO and EPZ 015666 (PRMT5i) MLL-ENL/NrasG12D leukemia cells, three independent replicates.

Publication Title

Genetic deletion or small-molecule inhibition of the arginine methyltransferase PRMT5 exhibit anti-tumoral activity in mouse models of MLL-rearranged AML.

Sample Metadata Fields

Specimen part, Treatment, 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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