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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

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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 GSE13699
Immune response to the yellow fever vaccine 17D.
  • organism-icon Homo sapiens
  • sample-icon 142 Downloadable Samples
  • Technology Badge IconIllumina humanRef-8 v2.0 expression beadchip

Description

Correlates of immune mediated protection to most viral and cancer vaccines are still unknown. This impedes the development of novel vaccines to incurable diseases such as HIV and cancer. In this study, we have used functional genomics and polychromatic flow cytometry to define the signature of the immune response to the yellow fever (YF) vaccine 17D (YF17D) in a cohort of forty volunteers followed for up to one year after vaccination. We show that immunization with YF17D leads to an integrated immune response that includes several effector arms of innate immunity including complement, the inflammasome and interferons, as well as adaptive immunity as shown by an early T cell response followed by a brisk and variable B cell response. Development of these responses is preceded, as demonstrated in three independent vaccination trials and in a novel in vitro system of primary immune responses (Modular IMmune In vitro Construct (MIMIC) system), by the coordinated up-regulation of transcripts for specific transcription factors including STAT1, IRF7 and ETS2 that are upstream of the different effector arms of the immune response. These results clearly show that the immune response to a strong vaccine is preceded by coordinated induction of masters transcription factors, that lead to the development of a broad, polyfunctional and persistent immune response that integrates all effector cells of the immune system.

Publication Title

Yellow fever vaccine induces integrated multilineage and polyfunctional immune responses.

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 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
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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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