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accession-icon GSE39291
Expression Profiles of HepG2 cells treated with following oxidants: 100M menadione, 200M TBH or 50M H2O2
  • organism-icon Homo sapiens
  • sample-icon 124 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

The transcriptomic changes induced in the human liver cell line HepG2 by 100M menadione, 200M TBH or 50M H2O2 after treatment for 0.5, 1, 2, 4, 6, 8 and 24h.

Publication Title

Time series analysis of oxidative stress response patterns in HepG2: a toxicogenomics approach.

Sample Metadata Fields

Cell line

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accession-icon GSE38124
Characterization of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows a strong conservation of involved transcription factors
  • organism-icon Mus musculus, Homo sapiens
  • sample-icon 30 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

Characterisation of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows conservation of regulating transcription factor networks.

Sample Metadata Fields

Cell line, Treatment, Time

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accession-icon GSE38122
Expression Profiles of HepG2 cells treated with 7M of the genotoxic compound cisplatin
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The transcriptomic changes induced in the human liver cell line HepG2 by 7M of cisplatin after treatment for 12, 24 and 48h

Publication Title

Characterisation of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows conservation of regulating transcription factor networks.

Sample Metadata Fields

Cell line, Treatment, Time

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accession-icon GSE38123
Expression Profiles of PMH treated with 7M of the genotoxic compound cisplatin
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The transcriptomic changes induced in primary mouse hepatocytes (C57BL/6 ) by 7M of cisplatin after treatment for 24 and 48h

Publication Title

Characterisation of cisplatin-induced transcriptomics responses in primary mouse hepatocytes, HepG2 cells and mouse embryonic stem cells shows conservation of regulating transcription factor networks.

Sample Metadata Fields

Cell line, Treatment, Time

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accession-icon GSE28878
Expression Profiles of HepG2 cells treated with genotoxic and non-genotoxic agents
  • organism-icon Homo sapiens
  • sample-icon 560 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. The transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12h, 24h and 48h were used for the selection of gene-sets that can discriminate between in vivo genotoxins (GTX) and in vivo non-genotoxins (NGTX). By combining publicly available results for these chemicals from standard in vitro genotoxicity studies with transcriptomics, we developed several prediction models. These models were validated by means of an additional set of 28 chemicals.

Publication Title

A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo.

Sample Metadata Fields

Cell line, Time

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accession-icon GSE72088
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity
  • organism-icon Mus musculus
  • sample-icon 177 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), miRCURY LNA microRNA Array, 5th and 7th generation combined - hsa, mmu & rno (miRBase 19.0)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE72081
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity (mRNA)
  • organism-icon Mus musculus
  • sample-icon 177 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses.

Publication Title

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE57132
Evaluating mRNA and microRNA profiles reveals discriminative and compound-specific responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), miRCURY LNA microRNA Array, 5th and 7th generation combined - hsa, mmu & rno (miRBase 19.0)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE57129
Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes [Affymetrix]
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The study investigated differential gene expression in primary mouse hepatocyte mRNA following 24 and 48 hours of exposure to aflatoxin B1, cisplatin, benzo(a)pyrene, 2,3,7,8-tetrachloordibenzo-p-dioxine, cyclosporin A or Wy-14,643 or their responsive solvent. Three (four for Wy-14,643) biological replicates per compound/solvent.

Publication Title

Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.

Sample Metadata Fields

Specimen part, Compound

View Samples
accession-icon SRP152857
Functional characteristics of novel pancreatic Pax6 regulatory using a mouse pancreatic cell model
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Transcriptome profiling using RNA-seq of ß-TC3 cell, a mouse pancreatic cell line used in the study of novel Cis-regulatory elements for the Pax6 gene . Overall design: Total RNA was collected and a Illumina sequencing libraries prepared from two biological replicates of cultured ß-TC3 cells.

Publication Title

Functional characteristics of novel pancreatic Pax6 regulatory elements.

Sample Metadata Fields

Cell line, Subject

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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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