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accession-icon GSE7577
Toxicogenomic Effect of Burkholderia pseudomallei in a Human Macrophage Cell (THP-1) Model of Acute Melioidosis Using Whole-genome Microarray
  • organism-icon Homo sapiens
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Gene expression profiles of human cell (THP-1) lines exposed to a novel Daboiatoxin (DbTx) isolated from Daboia russelli russelli, and specific cytokines and inflammatory pathways involved in acute infection caused by Burkholderia pseudomallei.

Publication Title

Gene Microarray Analyses of Daboia russelli russelli Daboiatoxin Treatment of THP-1 Human Macrophages Infected with Burkholderia pseudomallei.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE51402
Gene expression patterns in response to IL-3 in human AML patient mononuclear cells
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Aberrant activation of -catenin is a common event in Acute Myeloid Leukemia (AML), and is recognized as an independent predictor of poor prognosis. Although increased -catenin signaling in AML has been associated with AML1-ETO and PML-RAR translocation products, and activating mutations in the FLT3 receptor, it remains unclear which mechanisms activate -catenin in AML more broadly. Here, we describe a novel link between interleukin-3 (IL-3) signaling and the regulation of -catenin in myeloid transformation and AML. Using a murine model of HoxB8 and IL-3 cooperation we show that IL-3 modulates -catenin protein levels, and Cre-induced deletion of -catenin abolishes IL-3 dependent growth and colony formation. In the erythroleukemic cell line TF-1.8, we observed increased -catenin protein levels and nuclear localization in response to IL-3, which correlated with transcriptional induction of -catenin target genes. Furthermore, IL-3 promoted -catenin accumulation in a subset of AML patient samples, and microarray gene expression analysis of these cells revealed induction of WNT/-catenin and TCF4 transcriptional gene signatures in an IL-3 dependent manner. This study is the first to link -catenin activation to IL-3 and suggests that targeting IL-3 signaling may be an effective approach for the inhibition of -catenin activity in some patients with AML.

Publication Title

Interleukin-3-mediated regulation of β-catenin in myeloid transformation and acute myeloid leukemia.

Sample Metadata Fields

Specimen part, Disease, Treatment

View Samples
accession-icon GSE99636
Gene expression profiles of multiple myeloma plasma cell fractions from bone marrow
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2), Affymetrix Human Exon 1.0 ST Array [CDF: huex10st_Hs_ENSG_20.0 (huex10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE107843
Gene expression profiles of multiple myeloma plasma cell fractions from bone marrow III
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Todays diagnostic tests for multiple myeloma (MM) reflect the criteria of the updated WHO classification based on biomarkers and clinicopathologic heterogeneity. To that end, we propose a new subtyping of myeloma plasma cells (PC) by B-cell subset associated gene signatures (BAGS), from the normal B-cell hierarchy in the bone marrow (BM). To do this, we combined FACS and GEP data from normal BM samples to generate classifiers by BAGS for the PreBI, PreBII, immature (Im), nave (N), memory (M) and PC subsets. The resultant tumor assignments in available clinical datasets exhibited similar BAGS subtype frequencies in four cohorts across 1302 individual cases. The prognostic impact of BAGS was analyzed in patients treated with high dose melphalan as first line therapy in three prospective trials: UAMS, HOVON65/GMMG-HD4 and MRC Myeloma IX with Affymetrix U133 plus 2.0 microarray data available from diagnostic myeloma PC samples. The BAGS subtypes were significantly associated with progression free (PFS) and overall survival (OS) (PFS, P=3.05e06 and OS, P=1.06e11) in a meta-analysis of 926 pts. The major impact was observed within the PreBII and M subtypes conferred with significant inferior prognosis compared to the Im, N and PC subtypes. Cox proportional hazard meta-analysis documented that the BAGS subtypes added significant and independent prognostic information to the TC classification system and ISS staging. BAGS subtype analysis identified transcriptome differences and a number of novel differentially spliced genes. We have identified hierarchal subtype differences in the myeloma plasma cells, with prognostic impact. This observation support an acquired reversible B-cell trait and phenotypic plasticity as a hallmark, also in MM.

Publication Title

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE99634
Gene expression profiles of multiple myeloma plasma cell fractions from bone marrow I
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [CDF: huex10st_Hs_ENSG_20.0 (huex10st)

Description

Todays diagnostic tests for multiple myeloma (MM) reflect the criteria of the updated WHO classification based on biomarkers and clinicopathologic heterogeneity. To that end, we propose a new subtyping of myeloma plasma cells (PC) by B-cell subset associated gene signatures (BAGS), from the normal B-cell hierarchy in the bone marrow (BM). To do this, we combined FACS and GEP data from normal BM samples to generate classifiers by BAGS for the PreBI, PreBII, immature (Im), nave (N), memory (M) and PC subsets. The resultant tumor assignments in available clinical datasets exhibited similar BAGS subtype frequencies in four cohorts across 1302 individual cases. The prognostic impact of BAGS was analyzed in patients treated with high dose melphalan as first line therapy in three prospective trials: UAMS, HOVON65/GMMG-HD4 and MRC Myeloma IX with Affymetrix U133 plus 2.0 microarray data available from diagnostic myeloma PC samples. The BAGS subtypes were significantly associated with progression free (PFS) and overall survival (OS) (PFS, P=3.05e06 and OS, P=1.06e11) in a meta-analysis of 926 pts. The major impact was observed within the PreBII and M subtypes conferred with significant inferior prognosis compared to the Im, N and PC subtypes. Cox proportional hazard meta-analysis documented that the BAGS subtypes added significant and independent prognostic information to the TC classification system and ISS staging. BAGS subtype analysis identified transcriptome differences and a number of novel differentially spliced genes. We have identified hierarchal subtype differences in the myeloma plasma cells, with prognostic impact. This observation support an acquired reversible B-cell trait and phenotypic plasticity as a hallmark, also in MM.

Publication Title

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Sample Metadata Fields

Disease

View Samples
accession-icon GSE59394
Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network
  • organism-icon Mus musculus
  • sample-icon 13 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

Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network.

Sample Metadata Fields

Sex, Specimen part, Time

View Samples
accession-icon GSE59392
Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network [expression]
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

In embryonic stem cell (ESCs), gene regulatory networks (GRNs) coordinate gene expression to maintain ESC identity; however, the complete repertoire of factors that regulate the ESC state are not fully understood. Our previous temporal microarray analysis of ESC commitment identified the E3 Ubiquitin Ligase Protein Makorin-1 (MKRN1) as a potential novel component of the ESC GRN. Here, using multilayered systems-level analyses we compiled a MKRN1-centered interactome in undifferentiated ESCs at the proteomic and ribonomic level. Proteomic analyses revealed that MKRN1 is a novel RNA-binding protein that exists within messenger ribonucleoprotein (mRNP) complexes in undifferentiated ESC populations. In accordance with its presence in mRNPs, MKRN1 is mobilized to stress granules (SG) upon arsenite-induced stress, yet MKRN1 is not required for SG formation. RIP-chip analysis revealed that MKRN1 associates with mRNAs encoding functionally related regulatory proteins involved in diverse processes such as cell differentiation, apoptosis, or secreted proteins. Thus, our unbiased systems level analyses supports a role for MKRN1 as a novel RNA-binding protein and a potential gene regulatory protein within the ESC GRN.

Publication Title

Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network.

Sample Metadata Fields

Sex, Specimen part, Time

View Samples
accession-icon GSE59393
Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network [RIP-chip]
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

In embryonic stem cell (ESCs), gene regulatory networks (GRNs) coordinate gene expression to maintain ESC identity; however, the complete repertoire of factors that regulate the ESC state are not fully understood. Our previous temporal microarray analysis of ESC commitment identified the E3 Ubiquitin Ligase Protein Makorin-1 (MKRN1) as a potential novel component of the ESC GRN. Here, using multilayered systems-level analyses we compiled a MKRN1-centered interactome in undifferentiated ESCs at the proteomic and ribonomic level. Proteomic analyses revealed that MKRN1 is a novel RNA-binding protein that exists within messenger ribonucleoprotein (mRNP) complexes in undifferentiated ESC populations. In accordance with its presence in mRNPs, MKRN1 is mobilized to stress granules (SG) upon arsenite-induced stress, yet MKRN1 is not required for SG formation. RIP-chip analysis revealed that MKRN1 associates with mRNAs encoding functionally related regulatory proteins involved in diverse processes such as cell differentiation, apoptosis, or secreted proteins. Thus, our unbiased systems level analyses supports a role for MKRN1 as a novel RNA-binding protein and a potential gene regulatory protein within the ESC GRN.

Publication Title

Integrative genomics positions MKRN1 as a novel ribonucleoprotein within the embryonic stem cell gene regulatory network.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon SRP001417
modENCODE RNA-Seq of Drosophila Kc167
  • organism-icon Drosophila melanogaster
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer

Description

Deep Sequencing of Kc167 mRNA. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Overall design: Seq of Poly-A+ RNA from D. melanogaster Kc167

Publication Title

The transcriptional diversity of 25 Drosophila cell lines.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE36098
Gene expression profile of human iPS cell-derived mesoangioblasts (HIDEMs)
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Mesoangioblasts are stem/progenitor cells derived from a subset of pericytes expressing alkaline phosphatase. They have been shown to ameliorate muscular dystrophies (currently incurable diseases) in different animal models and are now undergoing clinical experimentation for Duchenne muscular dystrophy. We show here that patients affected by limb-girdle muscular dystrophy 2D (LGMD2D, characterized by -sarcoglycan deficit) have a reduction of this subset of pericytes and hence mesoangioblast could not be derived for cell therapy. Therefore, we reprogrammed LGMD2D fibroblasts and myoblasts to induced pluripotent stem cells (iPSCs) and developed a protocol for the derivation of mesoangioblast-like cells from them. These cells can be expanded and genetically corrected with a muscle-specific lentiviral vector expressing human -sarcoglycan. Upon transplantation into ad hoc generated -sarcoglycan-null immunodeficient mice, they generate myofibers expressing -sarcoglycan. This approach may be useful for muscular dystrophies that show a reduction of resident progenitors and provides evidence of pre-clinical safety and efficacy of disease-specific iPSCs.

Publication Title

Transplantation of genetically corrected human iPSC-derived progenitors in mice with limb-girdle muscular dystrophy.

Sample Metadata Fields

Sex, Specimen part

View Samples
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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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