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accession-icon SRP132239
Transcriptomic analysis of multiple myeloma cell lines
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

We found that a small molecule inhibitor of PRMT4 inhibited cell growth of a subset of multiple myeloma cell lines. To identify biomarkers that predict the sensitivity of myeloma cells to PRMT4 inhibition, we performed transcriptomic analysis of multiple myeloma cell lines. Overall design: Amplicon sequencing of thirteen multiple myeloma cell lines was performed on the Ion Torrent platform. Steady-state gene expression profile of sensitive cells were compaired with that of insensitive cells.

Publication Title

TP-064, a potent and selective small molecule inhibitor of PRMT4 for multiple myeloma.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE19601
Gene expression profiling in murine Smad-deficient CD4+ T cells stimulated with TGF-b
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

TGF-b is an important pleiotropic cytokine with potent immunoregulatory properties. Although many previous reports have been proposed for the immunoregulatory functions of TGF-b on T cells, such as the suppression of cell proliferation, cytokine production and cytokine signaling, as well as the induction of apoptosis, it is not well elucidated whether the each effect of TGF-b on T cells is dependent on Smad signaling or Smad-independent other signaling pathways.

Publication Title

Smad2 and Smad3 are redundantly essential for the TGF-beta-mediated regulation of regulatory T plasticity and Th1 development.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE97969
Identification of mRNAs modulated by the HOXB7-MEK signaling cascade
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 2.0 ST Array (hugene20st)

Description

Transcripts upregulated or downregulated by HOXB7-MEK signaling were identified for use on the microarray using the Affymetrix GeneChip WT PLUS Reagent Kit in comparison with HOXB7-knockdown S2-013 cells that were transfected with rescue-HOXB7 plasmid and treated with MEK inhibitor, and HOXB7-knockdown S2-013 cells that were transfected with rescue-HOXB7 plasmid but not treated with MEK inhibitor.

Publication Title

The transcription factor HOXB7 regulates ERK kinase activity and thereby stimulates the motility and invasiveness of pancreatic cancer cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE60542
Revisiting the transcriptional analysis of primary tumors and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The biology underlying nodal metastasis is poorly understood. Transcriptome profiling has helped to characterize both primary tumors seeding nodal metastasis and the metastasis themselves. The interpretation of these data, however, is not without ambiguities. Here we profiled the transcriptomes of 17 papillary thyroid cancer (PTC) nodal metastases, associated primary tumors and primary tumors from N0 patients. We also included patient-matched normal thyroid and lymph node samples as controls to address some limits of previous studies. We found that the transcriptomes of patient-matched primary tumors and metastases were more similar than of unrelated metastases/primary pairs, a result also reported in other organ systems, and that part of this similarity reflected patient background. We found that the comparison of patient-matched primary tumors and metastases was heavily confounded by the presence of lymphoid tissues in the metastasis samples. An original data adjustment procedure was developed to circumvent this problem. It revealed a differential expression of stroma-related gene expression signatures also regulated in other organ systems. The comparison of N0 vs. N+ primary tumors uncovered a signal irreproducible across independent PTC datasets. This signal was also detectable when comparing the normal thyroid tissues adjacent to N0 and N+ tumors, suggesting a cohort specific bias also likely to be present in previous studies with similar statistical power. Classification of N0 vs. N+ yielded an accuracy of 63%, but additional statistical controls not presented in previous studies, revealed that this is likely to occur by chance alone. To address this issue, we used large datasets from The Cancer Genome Atlas and showed that N0 vs. N+ classification rates could not be reached randomly for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.

Publication Title

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer.

Sample Metadata Fields

Sex

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accession-icon SRP080939
RNA-seq of N2a cells treated with 100 nM Dexamethasone for 4 hours +/- siARGLU1
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

ARGLU1 was identified in a screen for new modulators of glucocorticoid signaling in the CNS. RNA-seq of neuronal cells ±siARGLU1 revealed significant changes in the expression and alternative splicing of distinct genes involved in neurogenesis. Treatment with dexamethasone, a GR activator, also induced changes in the pattern of alternatively spliced genes, highlighting an underappreciated global mechanism of glucocorticoid action in neuronal cells. Thus, in addition to its basal role, ARGLU1 links glucocorticoid-mediated transcription and alternative splicing in neural cells, providing new avenues from which to investigate the molecular underpinnings of cognitive stress disorders. Overall design: N2a cells were transfected with non-targeting control and ARGLU1 siRNAs for 48 hrs followed by Vehicle (EtOH) or 100 nM Dexamethasone treatment for 4 hrs. RNA was extracted and pooled by treatment group (n=3/group) and mRNA enriched Illumina TruSeq V2 RNA libraries were prepared. Samples were sequenced on Illumina HiSeq2500.

Publication Title

ARGLU1 is a transcriptional coactivator and splicing regulator important for stress hormone signaling and development.

Sample Metadata Fields

Specimen part, Cell line, Subject

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accession-icon GSE80026
Comparison between WT and apl in a novel in vitro tissue culture system, VISUAL
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Arabidopsis Gene 1.0 ST Array (aragene10st)

Description

We established a novel in vitro tissue culture system (named VISUAL), in which xylem and phloem differentiation can be induced with Arabidopsis thaliana cotyledons

Publication Title

Vascular Cell Induction Culture System Using Arabidopsis Leaves (VISUAL) Reveals the Sequential Differentiation of Sieve Element-Like Cells.

Sample Metadata Fields

Age, Specimen part, Time

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accession-icon GSE80027
Cell-sorting analysis with SEOR1pro::SEOR1-YFP in a novel in vitro tissue culture system, VISUAL
  • organism-icon Arabidopsis thaliana
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Arabidopsis Gene 1.0 ST Array (aragene10st)

Description

We established a novel in vitro tissue culture system (named VISUAL), in which xylem and phloem differentiation can be induced with Arabidopsis thaliana cotyledons

Publication Title

Vascular Cell Induction Culture System Using Arabidopsis Leaves (VISUAL) Reveals the Sequential Differentiation of Sieve Element-Like Cells.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE16219
Identification of genes that are regulated by TAK1 in human cutaneous T cell lymphoma HuT-102 cells
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We previously reported that human T cell lymphotropic virus 1 (HTLV-1) Tax oncoprotein constitutively activates TAK1. Here, we established Tax-positive HuT-102 cells stably downregulated TAK1 expression by short-hairpin RNA (HuT-shTAK1 cells), and investigated the physiological function of TAK1. Microarray analysis demonstrated that several interferon (IFN)-inducible genes including chemokines such as CXCL10 and CCL5 were significantly downregulated in HuT-shTAK1 cells. In contrast, Tax-mediated constitutive activation of NF-kB was intact in HuT-shTAK1 cells. IRF3, a critical transcription factor in innate immunity to viral infection, was constitutively activated in a Tax-dependent manner. Activation of IRF3 and IRF3-dependent gene expression were dependent on TAK1 and TBK1. On the other hand, IRF4, another IRF family of transcription factor overexpressed in a Tax-independent manner, negatively regulated the TAK1-dependent IRF3 transcriptional activity. Together, HTLV-1 manipulates IFN signaling by regulating both positive and negative IRFs.

Publication Title

Human T cell lymphotropic virus 1 manipulates interferon regulatory signals by controlling the TAK1-IRF3 and IRF4 pathways.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE22036
Identification of genes that regulated by IRF4 in human cutaneous T cell lymphoma HuT-102 cells
  • organism-icon Homo sapiens
  • sample-icon 3 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The microarray analysis showed an interesting up-regulation in the set of genes controlling the development of Th1, mainly IFN-gamma, and other type 1 interferon response genes including CXCL10 in IRF4 knocked-down HuT-102 cells.

Publication Title

Distinct roles of transforming growth factor-beta-activated kinase 1 (TAK1)-c-Rel and interferon regulatory factor 4 (IRF4) pathways in human T cell lymphotropic virus 1-transformed T helper 17 cells producing interleukin-9.

Sample Metadata Fields

Specimen part

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accession-icon GSE50647
Transcriptome analysis of adipose tissues of A. actinomycetemcomitans- and C. pneumoniae-infected apoE-deficient mice
  • organism-icon Mus musculus
  • sample-icon 42 Downloadable Samples
  • Technology Badge IconIllumina MouseWG-6 v2.0 expression beadchip

Description

The 14-week experiment included three groups: 1) the Acute Cpn group, with one C. pneumoniae inoculation at the age of 9 wks; 2) the Chronic Cpn group, with three C. pneumoniae inoculations at the age of 9, 11, and 13 wks; and 3) the control group, with three SPG inoculations at the age of 9, 11, and 13 wks. The mice were sacrificed at the age of 14 wks. The 24-week experiment included four groups: 1) the recurrent A. actinomycetemcomitans infection group, with ten A. actinomycetemcomitans inoculations once a week from the age of 14 to 23 wks; 2) the chronic C. pneumoniae infection group, with three C. pneumoniae inoculations at the age of 9, 11, and 13 wks; 3) the combined chronic C. pneumoniae and recurrent A. actinomycetemcomitans infection group, with three C. pneumoniae inoculations at the age of 9, 11, and 13 wks, and ten A. actinomycetemcomitans inoculations once a week from the age of 14 to 23 wks; and 4) the control group, with three SPG inoculations at the age of 9, 11, and 13 wks, and ten 0.9% NaCl inoculations once a week from the age of 14 to 23 wks. The mice were sacrificed at the age of 24 wks.Epididymal and inguinal AT gene expression was analyzed using an Illumina Mouse WG-6 v2.0 platform.

Publication Title

The effect of proatherogenic pathogens on adipose tissue transcriptome and fatty acid distribution in apolipoprotein E-deficient mice.

Sample Metadata Fields

Sex, Age, Specimen part

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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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