refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 45 results
Sort by

Filters

Technology

Platform

accession-icon GSE27306
IRE1-dependent transcriptome remodelling upon ER stress in human glioma cells
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

We investigate the contribution of IRE1 signaling to the modulation of U87 glioma cells transcriptome upon various stresses. To this end, IRE1 control and IRE1 dominant negative expressing U87 glioma cells were subjected to environmental or chemical challenges and their transcriptome monitored using Affymetrix microarrays.

Publication Title

Posttranscriptional regulation of PER1 underlies the oncogenic function of IREα.

Sample Metadata Fields

Cell line, Treatment

View Samples
accession-icon GSE107859
Transcriptomic analysis of glioblastoma cells bearing different IRE1a mutants
  • organism-icon Homo sapiens
  • sample-icon 40 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Glioblastoma multiforme is the most lethal form of glioma with an overall survival at 5 years nearly null, which mainly results from acquired resistance to therapies. Large scale sequencing studies on human cancer biopsies defined IRE1alpha as the fifth most oncogenic mutated kinase in human cancer. IRE1alpha is a major component of the Unfolded Protein Response signaling and increasing evidence suggests that it is a central player in GBM development.

Publication Title

Dual IRE1 RNase functions dictate glioblastoma development.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE6116
Transcriptional Biomarkers to Predict Female Mouse Lung Tumors in Rodent Cancer Bioassays - A 13 Chemical Training Set
  • organism-icon Mus musculus
  • sample-icon 70 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The primary goal of toxicology and safety testing is to identify agents that have the potential to cause adverse effects in humans. Unfortunately, many of these tests have not changed significantly in the past 30 years and most are inefficient, costly, and rely heavily on the use of animals. The rodent cancer bioassay is one of these safety tests and was originally established as a screen to identify potential carcinogens that would be further analyzed in human epidemiological studies. Today, the rodent cancer bioassay has evolved into the primary means to determine the carcinogenic potential of a chemical and generate quantitative information on dose-response behavior in chemical risk assessments. Due to the resource-intensive nature of these studies, each bioassay costs $2 to $4 million and takes over three years to complete. Over the past 30 years, only 1,468 chemicals have been tested in a rodent cancer bioassay. By comparison, approximately 9,000 chemicals are used by industry in quantities greater than 10,000 lbs and nearly 90,000 chemicals have been inventoried by the U.S. Environmental Protection Agency as part of the Toxic Substances Control Act. Given the disparity between the number of chemicals tested in a rodent cancer bioassay and the number of chemicals used by industry, a more efficient and economical system of identifying chemical carcinogens needs to be developed.

Publication Title

Application of genomic biomarkers to predict increased lung tumor incidence in 2-year rodent cancer bioassays.

Sample Metadata Fields

Sex, Age, Subject

View Samples
accession-icon GSE34779
A cross platform genome wide comparison of the relationship of promoter DNA methylation to gene expression
  • organism-icon Homo sapiens
  • sample-icon 8 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

A cross-platform genome-wide comparison of the relationship of promoter DNA methylation to gene expression.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE34776
Expression data from human lymphoblasts [Affymetrix]
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Transcriptional profiling of IAS subjects

Publication Title

A cross-platform genome-wide comparison of the relationship of promoter DNA methylation to gene expression.

Sample Metadata Fields

Specimen part, Subject

View Samples
accession-icon GSE5127
Gene Expression Biomarkers for Predicting Lung Tumors in Two-Year Rodent Bioassays
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Two-year rodent bioassays play a central role in evaluating both the carcinogenic potential of a chemical and generating quantitative information on the dose-response behavior for chemical risk assessments. The bioassays involved are expensive and time-consuming, requiring nearly lifetime exposures (two years) in mice and rats and costing $2 to $4 million per chemical. Since there are approximately 80,000 chemicals registered for commercial use in the United States and 2,000 more are added each year, applying animal bioassays to all chemicals of concern is clearly impossible. To efficiently and economically identify carcinogens prior to widespread use and human exposure, alternatives to the two-year rodent bioassay must be developed. In this study, animals were exposed for 13 weeks to two chemicals that were positive for lung tumors in the two-year rodent bioassay, two chemicals that were negative for tumors, and two vehicle controls. Gene expression analysis was performed on the lungs of the animals to assess the potential for identifying gene expression biomarkers that can predict tumor formation in a two-year bioassay following a 13 week exposure.

Publication Title

A comparison of transcriptomic and metabonomic technologies for identifying biomarkers predictive of two-year rodent cancer bioassays.

Sample Metadata Fields

Sex, Age, Subject

View Samples
accession-icon GSE5128
Gene Expression Biomarkers for Predicting Liver Tumors in Two-Year Rodent Bioassays
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Two-year rodent bioassays play a central role in evaluating both the carcinogenic potential of a chemical and generating quantitative information on the dose-response behavior for chemical risk assessments. The bioassays involved are expensive and time-consuming, requiring nearly lifetime exposures (two years) in mice and rats and costing $2 to $4 million per chemical. Since there are approximately 80,000 chemicals registered for commercial use in the United States and 2,000 more are added each year, applying animal bioassays to all chemicals of concern is clearly impossible. To efficiently and economically identify carcinogens prior to widespread use and human exposure, alternatives to the two-year rodent bioassay must be developed. In this study, animals were exposed for 13 weeks to two chemicals that were positive for liver tumors in the two-year rodent bioassay, two chemicals that were negative for liver tumors, and two vehicle controls. Gene expression analysis was performed on the livers of the animals to assess the potential for identifying gene expression biomarkers that can predict tumor formation in a two-year bioassay following a 13 week exposure.

Publication Title

A comparison of transcriptomic and metabonomic technologies for identifying biomarkers predictive of two-year rodent cancer bioassays.

Sample Metadata Fields

Sex, Age, Subject

View Samples
accession-icon GSE68110
Trancriptional profiling of rat liver after short-term (up tp 14 days) administration of carcinogenic and non-carcinogenic chemicals
  • organism-icon Rattus norvegicus
  • sample-icon 418 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

The carcinogenic potential of chemicals is currently evaluated with rodent life-time bioassays, which are time consuming, and expensive with respect to cost, number of animals and amount of compound required. Since the results of these 2-year bioassays are not known until quite late during development of new chemical entities, and since the short-term test battery to test for genotoxicity, a characteristic of genotoxic carcinogens, is hampered by low specificity, the identification of early biomarkers for carcinogenicity would be a big step forward. Using gene expression profiles from the livers of rats treated up to 14 days with genotoxic and non-genotoxic carcinogens we previously identified characteristic gene expression profiles for these two groups of carcinogens. We have now added expression profiles from further hepatocarcinogens and from non-carcinogens the latter serving as control profiles. We used these profiles to extract biomarkers discriminating genotoxic from non-genotoxic carcinogens and to calculate classifiers based on the support vector machine (SVM) algorithm. These classifiers then predicted a set of independent validation compound profiles with up to 88% accuracy, depending on the marker gene set. We would like to present this study as proof of the concept that a classification of carcinogens based on short-term studies may be feasible.

Publication Title

Cross-platform toxicogenomics for the prediction of non-genotoxic hepatocarcinogenesis in rat.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE53085
Cross-platform toxicogenomics for the prediction of nongenotoxic hepatocarcinogenesis in rat
  • organism-icon Rattus norvegicus
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Cross-platform toxicogenomics for the prediction of non-genotoxic hepatocarcinogenesis in rat.

Sample Metadata Fields

Sex, Specimen part

View Samples
accession-icon GSE53082
Cross-platform toxicogenomics for the prediction of nongenotoxic hepatocarcinogenesis in rat (mRNA)
  • organism-icon Rattus norvegicus
  • sample-icon 63 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Expression 230A Array (rae230a)

Description

In this study we performed microarray-based molecular profiling of liver samples from Wistar rats exposed to genotoxic carcinogens (GC), nongenotoxic carcinogens (NGC) or non-hepatocarcinogens (NC) for up to 14 days. In contrast to previous toxicogenomics studies aimed at the inference of molecular signatures for assessing the potential and mode of compound carcinogenicity, we considered multi-level omics data. Besides evaluating the predictive power of signatures observed on individual biological levels, such as mRNA, miRNA and protein expression, we also introduced novel feature representations which capture putative molecular interactions or pathway alterations by integrating expression profiles across platforms interrogating different biological levels.

Publication Title

Cross-platform toxicogenomics for the prediction of non-genotoxic hepatocarcinogenesis in rat.

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