refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 36 results
Sort by

Filters

Technology

Platform

accession-icon GSE15245
Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells
  • organism-icon Homo sapiens
  • sample-icon 90 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Background: The ability to predict the spatial frequency of relapses in multiple sclerosis (MS) would enable treating physicians to decide when to intervene more aggressively and to plan clinical trials more accurately. Methods: In the current study our objective was to determine if subsets of genes can predict the time to the next acute relapse in patients with MS. Data-mining and predictive modeling tools were utilized to analyze a gene-expression dataset of 94 non-treated patients; 62 patients with definite MS and 32 patients with clinically isolated syndrome (CIS). The dataset included the expression levels of 10,594 genes and annotated sequences corresponding to 22,215 gene-transcripts that appear in the microarray. Results: We designed a two stage predictor. The first stage predictor was based on the expression level of 10 genes, and predicted the time to next relapse with a resolution of 500 days (error rate 0.079, p< 0.001). If the predicted relapse was to occur in less than 500 days, a second stage predictor based on an additional different set of 9 genes was used, resulting in a prediction with a resolution of 50 days as to the timing of the next relapse. The error rate of this predictor was 2.3 fold lower than the error rate of random predictions (error rate = 0.35, p<0.001). The predictors were further evaluated and found effective not only in untreated patients but were also valid for MS patients which subsequently received immunomodulatory treatments after the initial testing (the error rate of the first level predictor was < 0.18 with p<0.001 for all the patient groups). Conclusions: We conclude that gene expression analysis is a valuable tool that can be used in clinical practice to predict future MS disease activity. Similar approach can be also useful for dealing with other autoimmune diseases that characterized by relapsing-remitting nature

Publication Title

Prediction of acute multiple sclerosis relapses by transcription levels of peripheral blood cells.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE47032
Genome-wide analysis of differentially expressed genes and splicing isoforms in clear cell Renal Cell Carcinoma
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

In this study we performed a genome wide analysis of the entire complement of mRNAs in clear cell renal cell carcinomas (ccRCC) by means of the Affymetrix Exon Array platform. The analyses were performed both at gene and exon level.

Publication Title

Genome-wide analysis of differentially expressed genes and splicing isoforms in clear cell renal cell carcinoma.

Sample Metadata Fields

Sex, Age, Specimen part, Subject

View Samples
accession-icon GSE14833
Expression data from different stages of hematopoietic cells development
  • organism-icon Mus musculus
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

18 different population of cells in different developmental stages in hematopoietic hierarchy have been purifyed by FACS analyses from wild type C57Bl6 mice and subjected to Micrroarray Affymetrix mouse 430.2 platform

Publication Title

CCAAT/enhancer binding protein alpha (C/EBP(alpha))-induced transdifferentiation of pre-B cells into macrophages involves no overt retrodifferentiation.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE32330
Expression data from C/EBP alpha induced transdifferentiation of pre-B cells into macrophages
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Earlier work has shown that pre-B cells can be converted into macrophages by the transcription factor C/EBP? at very high frequencies. Using this system we have now performed a systematic analysis of the question whether during transdifferentiation the cells transiently reactivate progenitor restricted genes or even retrodifferentiate. A transcriptome analysis of transdifferentiating cells showed that most genes are continuously up or downregulated, acquiring a macrophage phenotype within 5 days. In addition, we observed the transient reactivation of a subset of immature myeloid markers, as well as low levels of the progenitor markers Kit and Flt3 and a few lineage inappropriate genes. However, we were unable to observe the re-expression of cell surface marker combinations that characterize hematopoietic stem and progenitor cells (HSPCs), including c-Kit and Flt3. This was the case even when C/EBPalpha was activated in pre-B cells under culture conditions that favor HSPC growth or when the transcription factor was activated in a time limited fashion. Together, our findings are consistent with the notion that the conversion from pre-B cells to macrophages is mostly direct and does not involve overt retrodifferentiation.

Publication Title

CCAAT/enhancer binding protein alpha (C/EBP(alpha))-induced transdifferentiation of pre-B cells into macrophages involves no overt retrodifferentiation.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE61643
PGC-1 Promotes Enterocyte Lifespan and Tumorigenesis in the Intestine
  • organism-icon Mus musculus
  • sample-icon 17 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

PGC-1β promotes enterocyte lifespan and tumorigenesis in the intestine.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE61642
Genome-wide analysis expression of ileum tumor samples from FVBN/APCmin and iPGC-1/APCmin
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

Analysis of metabolic pathway gene expression. The hypothesis tested in the present study is to assess mRNA level changes in metabolic genes in intestinal tumors from APCmin mice overexpressing PGC-1 specifically in the intestine.

Publication Title

PGC-1β promotes enterocyte lifespan and tumorigenesis in the intestine.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE61640
Genome-wide analysis expression of ileum samples from PGC-1 fl/? and iKOPGC-1
  • organism-icon Mus musculus
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

Analysis of metabolic pathway gene expression. The hypothesis tested in the present study is to assess mRNA level changes in metabolic genes in enterocytes from intestine specific PGC-1 konckout mice.

Publication Title

PGC-1β promotes enterocyte lifespan and tumorigenesis in the intestine.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE44073
Liver X Receptors play an antitumoral role in the intestine
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip, Illumina MouseRef-8 v2.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Liver X receptors inhibit proliferation of human colorectal cancer cells and growth of intestinal tumors in mice.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon GSE44071
Genome-wide analysis of gene expression profile of Intestinal (ILEUM) Tumors from APCmin/+/VP16LXRa vs APCmin/+/VP16
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina MouseRef-8 v2.0 expression beadchip

Description

Changes in gene expression profile of intestinal (ILEUM) Tumors from APCmin/+/VP16LXRa vs APCmin/+/VP16. The hypothesis tested in the present study was that LXRa overexpression influence cancer growth modulating lipid metabolism in cancer cells. Results provide the information that LXRa induces genes encoding proteins able to regulate cholesterol efflux.

Publication Title

Liver X receptors inhibit proliferation of human colorectal cancer cells and growth of intestinal tumors in mice.

Sample Metadata Fields

Age, Specimen part

View Samples
accession-icon SRP091722
Genome-wide effect of AML engraftment on bone marrow endothelial cells
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

We analysed the transcriptional signature in endothelial cells extracted from the bone marrow of mice engrafted with human AML and compared it to the one of mice engrafted with human normal hematopoietic cells Overall design: Immunodeficient mice were transplanted with human AML cells derived from patients, or with normal human hematopoietic cells derived from cord blood. Mice were sacrificed once assessed the bone marrow engraftment, and the bones were processed to isolate endothelial cells using the CD31 marker. RNA was extracted, sequencing libraries were prepared and sequenced.

Publication Title

Increased Vascular Permeability in the Bone Marrow Microenvironment Contributes to Disease Progression and Drug Response in Acute Myeloid Leukemia.

Sample Metadata Fields

Specimen part, Disease, Subject

View Samples

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

Powered by Alex's Lemonade Stand Foundation

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.

BSD 3-Clause LicensePrivacyTerms of UseContact