Optimization of a toxicogenomics-based comparison approach to categorize chemicals based on their modes of action
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE53634 | GEO | 2016/12/23
SECONDARY ACCESSION(S): PRJNA232530
REPOSITORIES: GEO
Similar Datasets
Project description:Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was used here to provide proof-of-concept that toxicants with a related mode of action can be identified, and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for six days to benchmark concentration (BMC) of histone deacetylase inhibitors (HDACi) valproic acid, trichostatin-A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes, and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of ‘mercurials’ (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid) (BMCs). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1, LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate, how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system.
2015-07-21 | GSE71127 | GEO
Project description:As training dataset for Random Promoter DREAM Challenge 2022, we generated ~6.7 million synthetic promoters (in yeast) comprised of random DNA (N80) and measured their expression by FACS (sorting into 18 bins). As test dataset for Random Promoter DREAM Challenge 2022, we generated ~71k synthetic promoters (in yeast) comprised of designed DNA (NBT) and measured their expression by FACS (sorting into 18 bins).
2024-02-03 | GSE254493 | GEO
Project description:We aim to improve the yield and effectiveness of the Dutch colorectal cancer screening program by using a personalized screening strategy based on fecal Hemoglobin concentration in previous screening round for participants with a negative fecal immunochemical test (FIT).
| 2736193 | ecrin-mdr-crc
Project description:The current test strategy for carcinogenicity is generally based on in vitro and in vivo genotoxicity assays. Non-genotoxic carcinogens (NGTXC) are negative for genotoxicity and go undetected. Therefore, alternative tests to detect these chemicals are urgently needed. NGTXC act through different modes of action, which complicates the development of such assays. We have demonstrated recently in primary mouse hepatocytes that some, but certainly not all, NGTXC can be categorized according to their mode of action based on feature detection at a gene expression level (Schaap et al. 2012 (PMID 22710402)). Identification of a wider range of chemicals probably requires multiple in vitro systems. In the current study, we describe the added value of using mouse embryonic stem cells. In this study, the focus is on NGTXC, but we also included genotoxic carcinogens and non-carcinogens. This approach enables us to assess the robustness of this method and to evaluate the system for recognizing features of chemicals in general, which is important for application in future risk assessment.
2014-10-23 | GSE44088 | GEO
Project description:The application of toxicogenomics as a predictive tool for chemical risk assessment has been under evaluation by the toxicology community for more than a decade. However, toxicogenomics predominately remains a tool for investigative research rather than for regulatory risk assessment. In this study, we aimed to determine whether the current generation of microarray technology in combination with an in vitro experimental design was capable of generating robust, reproducible data of sufficient quality to show promise as a tool for regulatory risk assessment. To this end, we designed a prospective collaborative study to determine the level of inter- and intra-laboratory reproducibility between three independent laboratories. All test sites adopted the same protocols for all aspects of the toxicogenomic experiment including cell culture, chemical exposure, RNA extraction, microarray data generation and analysis. As a case study, the genotoxic carcinogen B[a]P and the human hepatocyte cell line HepG2 were used to generate three comparable toxicogenomic data sets. High levels of technical reproducibility were demonstrated using a widely employed gene expression microarray platform. While differences at the global transcriptome level were still observed between the test sites, a common subset of B[a]P responsive genes was identified across all test sites which included both genes previously reported in the literature as B[a]P responsive in addition to the same most highly up and down regulated genes. Pending further analysis, these preliminary data show promise that the current generation of microarray technology in combination with a standard in vitro experimental design can produce robust data that can be reproducibly generated in independent laboratories. Future work will need to determine whether in vitro model(s) can be not only reproducible but also predictive for a range of toxic chemicals with different mechanisms of action. Such an approach may potentially be part of future in vitro testing regimes for regulatory risk assessment.
2011-12-31 | GSE25936 | GEO
Project description:Stem-cell-based in vitro systems are promising tools to predict human teratogenicity. However, current in vitro assays are limited because they either capture effects on a certain germ layer or focus on a subset of predictive markers. Here we report the characterization and critical assessment of TeraTox, a newly developed multi-lineage differentiation assay using 3D human induced pluripotent stem cells. TeraTox probes stem-cell-derived embryoid bodies with two endpoints, one quantifying cytotoxicity and the other inferring the teratogenicity potential with gene expression as a molecular phenotypic readout. To derive teratogenicity potential from gene expression profiles, we applied both unsupervised machine-learning tools including factor analysis, and supervised tools including classification and regression. To identify the best predictive model for the teratogenicity potential that is explainable, we systematically tested 64 machine-learning model architectures and identified the optimal model, which uses the expression of 77 representative germ-layer genes, summarized by 10 latent germ-layer factors, as input for random-forest regression. We combined measured cytotoxicity and inferred teratogenicity potential to predict concentration-dependent teratogenicity profiles of 33 approved pharmaceuticals and 12 proprietary drug candidates with known in vivo data. Compared with the mouse embryonic stem cell test, which has been in routine use for more than a decade, the TeraTox assay shows higher sensitivity, particularly towards teratogens impairing ectodermal development or stem-cell renewal, and a more balanced prediction performance. We envision that further refinement and development of TeraTox has the potential to reduce and replace animal research in drug discovery and to improve preclinical assessment of teratogenicity.
2022-05-03 | GSE183534 | GEO
Project description:The application of toxicogenomics as a predictive tool for chemical risk assessment has been under evaluation by the toxicology community for more than a decade. However, toxicogenomics predominately remains a tool for investigative research rather than for regulatory risk assessment. In this study, we aimed to determine whether the current generation of microarray technology in combination with an in vitro experimental design was capable of generating robust, reproducible data of sufficient quality to show promise as a tool for regulatory risk assessment. To this end, we designed a prospective collaborative study to determine the level of inter- and intra-laboratory reproducibility between three independent laboratories. All test sites adopted the same protocols for all aspects of the toxicogenomic experiment including cell culture, chemical exposure, RNA extraction, microarray data generation and analysis. As a case study, the genotoxic carcinogen B[a]P and the human hepatocyte cell line HepG2 were used to generate three comparable toxicogenomic data sets. High levels of technical reproducibility were demonstrated using a widely employed gene expression microarray platform. While differences at the global transcriptome level were still observed between the test sites, a common subset of B[a]P responsive genes was identified across all test sites which included both genes previously reported in the literature as B[a]P responsive in addition to the same most highly up and down regulated genes. Pending further analysis, these preliminary data show promise that the current generation of microarray technology in combination with a standard in vitro experimental design can produce robust data that can be reproducibly generated in independent laboratories. Future work will need to determine whether in vitro model(s) can be not only reproducible but also predictive for a range of toxic chemicals with different mechanisms of action. Such an approach may potentially be part of future in vitro testing regimes for regulatory risk assessment. The aim of this study was to evaluate the inter- and intra-laboratory reproducibility of toxicogenomics data for toxicity testing in a regulatory setting. 3 Test Centres performed the same experimental protocol treating HepG2 cells with 3 mM Benzo[a]pyrene (B[a]P) (in 0.5% DMSO) for 24 hours prior to RNA extraction and microarray analysis. Three biological replicates of B[a]P and DMSO treatments were analysed by microarray analysis in each Test Centre. Two Test Centres analysed one sample in triplicate to determine technical reproducibility of the chosen array platform. One Centre analysed two samples in duplicate. 24 samples in total were used in this study
2011-12-31 | E-GEOD-25936 | biostudies-arrayexpress
Project description:Hematopoietic stem cells (HSCs) maintain lifelong hematopoiesis by remaining quiescent in the bone marrow niche. Recapitulation of a quiescent state in culture has not been achieved, as cells rapidly proliferate and differentiate in vitro. By modulating environmental factors mimicking physiological conditions, we were able to maintain engraftable quiescent HSCs for 1 month in culture under low cytokine concentrations, hypoxia, and high fatty acid concentration, the latter required due to suppression of intrinsic fatty acid synthesis. By contrast, high cytokine concentrations or normoxia induced HSC proliferation and differentiation. Our novel culture system provides a means to evaluate properties of steady state HSCs and test effects of defined factors in vitro under near-physiological conditions.
2018-07-24 | GSE117516 | GEO
Project description:The current test strategy for carcinogenicity is generally based on in vitro and in vivo genotoxicity assays. Non-genotoxic carcinogens (NGTXC) are negative for genotoxicity and go undetected. Therefore, alternative tests to detect these chemicals are urgently needed. NGTXC act through different modes of action, which complicates the development of such assays. We have demonstrated recently in primary mouse hepatocytes that some, but certainly not all, NGTXC can be categorized according to their mode of action based on feature detection at a gene expression level (Schaap et al. 2012, PMID22710402). Identification of a wider range of chemicals probably requires multiple in vitro systems. In the current study we describe the added value of using mouse embryonic stem cells. In this study the focus is on NGTXC, but we also included genotoxic carcinogens and non-carcinogens. This approach enables us to assess the robustness of this method and to evaluate the system for recognizing features of chemicals in general, which is important for application in future risk assessment. This serie consists of the gene expression data of the mouse embryonic stem cells. The expression data of the primary mouse hepatocytes cells is submitted separately under accession number GSE44088.
2014-10-27 | GSE47345 | GEO
Project description:Methylation-based liquid biopsies show promise in detecting cancer from circulating cell-free DNA, but current limitations impede clinical application. Most assays necessitate substantial DNA inputs, posing challenges. Underrepresented tumor DNA fragments may go undetected during exponential amplification steps of traditional sequencing methods. Here we report LABS (Linear Amplification based Bisulfite Sequencing), enabling linear amplification of bisulfite-treated DNA fragments in a genome-wide, unbiased fashion, detecting cancer abnormalities with sub-nanogram inputs. Applying LABS to 100 patient samples revealed cancer-specific patterns, copy number alterations, and enhanced cancer detection accuracy by identifying tissue-of-origin and immune cell composition.
2024-04-24 | GSE186007 | GEO