refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 12 results
Sort by

Filters

Technology

Platform

accession-icon GSE62252
Expression data from kidney of Grhl1wt and Grhl1 ko mice.
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

The aim of our study was to investigate the functions of Grhl transcription factor in the kidney.

Publication Title

Consequences of the loss of the Grainyhead-like 1 gene for renal gene expression, regulation of blood pressure and heart rate in a mouse model.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE11943
Human Dendritic Cell Subtype Gene Arrays
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Among the dendritic cell (DC) subsets, plasmacytoid DCs are thought to be important in both generating antiviral and antitumor responses. These cells may be useful in developing dendritic cell-based tumor vaccines, however, the rarity of these cells in the peripheral blood have hampered attempts to understand their biology. To provide better insight into the biology of plasmacytoid DCs, we isolated these cells from the peripheral blood of healthy donors in order to further characterize their gene expression. Using gene array technology we compared the genetic profiles of these cells to those of CD14+ monocytes isolated from the same donors and found several immune related genes upregulated in this cell population. Understanding the genetic profiles of this dendritic cell subtype as well as others such as the BDCA-1 expressing myeloid DCs may enable us to manipulate these cells ex-vivo to generate enhanced DC-based tumor vaccines inducing more robust antitumor responses.

Publication Title

Genetic profiles of plasmacytoid (BDCA-4 expressing) DC subtypes-clues to DC subtype function in vivo.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE28015
Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.

Sample Metadata Fields

Sex, Disease, Disease stage, Treatment

View Samples
accession-icon GSE27943
Gene Expression Array of Human Ovarian Cancer.
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types.

Publication Title

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer.

Sample Metadata Fields

Sex, Disease, Disease stage

View Samples
accession-icon GSE42040
Diverse phospho-signaling networks mediate RTK dependent growth and survival in childhood ALL
  • organism-icon Homo sapiens
  • sample-icon 96 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

Combined inhibition of receptor tyrosine and p21-activated kinases as a therapeutic strategy in childhood ALL.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Time

View Samples
accession-icon GSE42038
Transcriptome profiling of T-lymphoblastic leukemia of childhood [gene expression]
  • organism-icon Homo sapiens
  • sample-icon 75 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The purpose of this study was the principal investigation and frequency of RTK expression in primary T-ALLs. Primary initial T-ALLs were assessed regarding their transcriptome-wide expression profiles and screend for prominent RTK expression.

Publication Title

Combined inhibition of receptor tyrosine and p21-activated kinases as a therapeutic strategy in childhood ALL.

Sample Metadata Fields

Disease, Disease stage

View Samples
accession-icon GSE42001
Diverse phospho-signaling networks mediate RTK dependent growth and survival in childhood ALL [gene expression]
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Deregulated RTK activity has been implicated as a causal leukemogenic factor in the context of molecular aberrations that perturb differentiation in the hematopoietic lineage such as in childhood ALL. A deeper understanding of RTK signaling processes on a system-wide scale will be key in defining critical components of signaling networks. To link RTK activity with in vivo output in primary ALL we took a functional approach, which combined SH2 domain binding, mass spectrometry, and transcriptome analyses. Structure and composition of evolving networks were highly diverse with few generic features determined by receptor and cell type. A combinatorial assembly of varying context-dependent and few generic signaling components at multiple levels likely generates output specificity. PAK2 was identified as a phosphoregulated FLT3 target, whose allosteric inhibition resulted in apoptosis of ALL cells. Our studies provide evidence that a functional approach to leukemia signaling may yield valuable information for a network-directed intervention.

Publication Title

Combined inhibition of receptor tyrosine and p21-activated kinases as a therapeutic strategy in childhood ALL.

Sample Metadata Fields

Specimen part, Time

View Samples
accession-icon GSE44783
Expression data from CD-1 mouse liver samples obtained from in-vivo treatment with genotoxic carcinogens, non-genotoxic carcinogens or non-hepatocarcinogens.
  • organism-icon Mus musculus
  • sample-icon 449 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), Affymetrix Rat Expression 230A Array (rae230a)

Description

Assessing the carcinogenic potential of drug candidates is a costly procedure which requires the life-long treatment of rodents at different dose levels. A promising approach, which may to a certain degree reduce the need for animal studies in the future is toxicogenomics. The idea is to employ microarray platforms for the genome-wide expression profiling of compounds, which may facilitate the discovery of biomarker genes and provide insights in molecular mechanisms.

Publication Title

A toxicogenomic approach for the prediction of murine hepatocarcinogenesis using ensemble feature selection.

Sample Metadata Fields

Sex, Specimen part, Treatment, Time

View Samples
accession-icon GSE29868
Inferring drug-induced gene regulatory relationships in primary human hepatocytes
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Statins are widely used cholesterol-lowering drugs that inhibit HMG-CoA reductase, a key enzyme in cholesterol synthesis. In some cases, however, these drugs may cause a number of toxic side effects in hepatocytes and skeletal muscle tissue. Currently, the specific molecular mechanisms that cause these adverse effects are not sufficiently understood. In this work, genome-wide RNA expression changes in primary human hepatocytes of six individuals were measured at five time points upon atorvastatin treatment. A novel systems-level analysis workflow was applied to reconstruct regulatory mechanisms based on these drug-response data and available knowledge about transcription factor binding specificities, protein-protein interactions and protein-drug interactions. Several previously unknown transcription factors, regulatory cofactors and signaling molecules were found to be involved in atorvastatin-responsive gene expression. Some novel relationships, e.g., the regulatory influence of nuclear receptor NR2C2 on CYP3A4, were successfully validated in wet-lab experiments.

Publication Title

Inferring statin-induced gene regulatory relationships in primary human hepatocytes.

Sample Metadata Fields

Specimen part, Treatment, Subject

View Samples
accession-icon GSE51358
Metabolic programs orchestrated by the activated Ha-ras and -catenin oncoproteins in mouse liver tumors
  • organism-icon Mus musculus
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Ha-ras and β-catenin oncoproteins orchestrate metabolic programs in mouse liver tumors.

Sample Metadata Fields

Sex, Specimen part

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