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accession-icon GSE57194
In Vitro Transformation of Primary Human CD34+ Cells by AML Fusion Oncogenes: Early Gene Expression Profiling Reveals Possible Drug Target in AML
  • organism-icon Homo sapiens
  • sample-icon 29 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Different fusion oncogenes in acute myeloid leukemia (AML) have distinct clinical and laboratory features suggesting different modes of malignant transformation. Here we compare the in vitro effects of representatives of major groups of AML fusion oncogenes on primary human CD34+ cells.

Publication Title

In vitro transformation of primary human CD34+ cells by AML fusion oncogenes: early gene expression profiling reveals possible drug target in AML.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE35713
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes
  • organism-icon Homo sapiens
  • sample-icon 202 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

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35725
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114]
  • organism-icon Homo sapiens
  • sample-icon 114 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we analyzed larger RO T1D and HC cohorts. In addition, we examined T1D progression by looking at longitudinal, pre-onset and longstanding T1D samples.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35711
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [CF_S1S3_5Auto_20CF_10HC]
  • organism-icon Homo sapiens
  • sample-icon 49 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found between unrelated healthy controls and non-diabetic cystic fibrosis patients possessing Pseudomonas aeruginosa pulmonary tract infection.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35716
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [Pneu_S3S24_10Pneu_4HC]
  • organism-icon Homo sapiens
  • sample-icon 27 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously, we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found between unrelated healthy controls and patients with bacterial pneumonia.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE35712
Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [H1N1_S5_5Pre_5D0]
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The complex milieu of inflammatory mediators associated with many diseases is often too dilute to directly measure in the periphery, necessitating development of more sensitive measurements suitable for mechanistic studies, earlier diagnosis, guiding selection of therapy, and monitoring interventions. Previously we determined that plasma of recent-onset (RO) Type 1 diabetes (T1D) patients induce a proinflammatory transcriptional signature in fresh peripheral blood mononuclear cells (PBMC) relative to that of unrelated healthy controls (HC). Here, using an optimized cryopreserved PBMC-based protocol, we compared the signature found in pre H1N1 samples to the signature associated with active H1N1 flu.

Publication Title

Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP009639
High-resolution view of the yeast meiotic program revealed by ribosome profiling
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 70 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II, Illumina HiSeq 2000

Description

Meiosis is a complex developmental process that generates haploid cells from diploid progenitors. We measured mRNA abundance and protein production through yeast sporulation and found strong temporal control for most genes, achieved through both mRNA levels and translational regulation. Monitoring the timing of protein production revealed novel factors involved in recombination and helped to illuminate the molecular basis of the broad restructuring of meiotic cells. We also found a strong increase in noncanonical translation at short open reading frames (sORFs) on unannnotated transcripts and upstream regions of known transcripts (uORFs). Ribosome occupancy at near-cognate uORFs was associated with more efficient ORF translation; while some AUG uORFs, often on regulated leader extensions, acted comptetitively. This work reveals a pervasive role for meiotic translational control and great complexity in genomic coding. Overall design: Fine mapping of gene expression through meiosis reveals extensive regulation of protein synthesis and widespread non-canonical translation.

Publication Title

High-resolution view of the yeast meiotic program revealed by ribosome profiling.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon GSE113002
Gene expression data from mouse colon. AOM+DSS induced colitis. INSR fl/fl mice or villin-CRE INSR-/- mice
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The epithelial expression of the insulin receptor in the colon is previously reported to correlate with the extent of colonic inflammation. Here, we investigated the effect of inactivating the epithelial insulin receptor in the intestinal tract, in an experimental model of inflammation-induced colorectal cancer. We report increased susceptibility to chemically-induced colitis together with potentiated colonic tumorigenesis in the knockout mice. Furthermore, we show that topically administered insulin in inflamed colons of wildtype mice reduces inflammation-induced weight loss and improves remission in a dose-dependent manner. Mice receiving rectal insulin enemas exhibited lower colitis endoscopic scores and developed significantly fewer and smaller tumors compared with the control group receiving phosphate-buffered saline only. Rectal insulin therapy can potentially be a novel treatment targeting the epithelial layer to enhance mucosal healing in the ulcerated areas. Our findings open up new possibilities for combination treatments to synergize with the existing anti-inflammatory therapies.

Publication Title

Rectal Insulin Instillation Inhibits Inflammation and Tumor Development in Chemically Induced Colitis.

Sample Metadata Fields

Treatment

View Samples
accession-icon GSE13671
Expression data from mammary epithelial cells from BRCA1 mutation carriers and non BRCA1 mutation carriers
  • organism-icon Homo sapiens
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Female BRCA1 mutation carriers have a nearly 80% probability of developing breast cancer during their life-time. We hypothesized that the breast epithelium at risk in BRCA1 mutation carriers harbors mammary epithelial cells (MECs) with altered proliferation and differentiation properties.

Publication Title

Altered proliferation and differentiation properties of primary mammary epithelial cells from BRCA1 mutation carriers.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE4600
Identifying targets of MeCP2 during neuronal maturational differentiation
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Rett syndrome (RTT) is an X-linked dominant neurodevelopmental disorder caused by mutations in MECP2, encoding methyl-CpG binding protein 2. MeCP2 is a transcriptional repressor elevated in mature neurons and is predicted to be required for neuronal maturation by regulating multiple target genes. Identifying primary gene targets in either Mecp2-deficient mice or human RTT brain has proven to be difficult, perhaps because of the transient requirement for MeCP2 during neuronal maturation. In order to experimentally control the timing of MeCP2 expression and deficiency during neuronal maturation, human SH-SY5Y cells undergoing mature neuronal differentiation were transfected with methylated MeCP2 oligonucleotide decoy to disrupt the binding of MeCP2 to endogenous targets. Genome-wide expression microarray analysis identified all four known members of the inhibitors of differentiation or inhibitors of DNA binding (ID1, ID2, ID3 and ID4) subfamily of helix-loop-helix (HLH) genes as novel neuronal targets of MeCP2. Chromatin immunoprecipitation analysis confirmed binding of MeCP2 near or within the promoters of ID1, ID2 and ID3, and quantitative RT-PCR confirmed increased expression of all four Id genes in Mecp2-deficient mouse brain. All four ID proteins were significantly increased in Mecp2-deficient mouse and human RTT brain using immunofluorescence and laser scanning cytometric analyses. Because of their involvement in cell differentiation and neural development, ID genes are ideal primary targets for MeCP2 regulation of neuronal maturation that may explain the molecular pathogenesis of RTT.

Publication Title

Inhibitors of differentiation (ID1, ID2, ID3 and ID4) genes are neuronal targets of MeCP2 that are elevated in Rett syndrome.

Sample Metadata Fields

No sample metadata fields

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)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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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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