Unlocking the power of transcriptomic biomarkers in qualitative and quantitative genotoxicity assessment of chemicals
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ABSTRACT:
PROVIDER: PRJNA1006340 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25663300.fastq.gz | Fastqsanger.gz | |||
| SRR25663400.fastq.gz | Fastqsanger.gz | |||
| SRR25663301.fastq.gz | Fastqsanger.gz | |||
| SRR25663401.fastq.gz | Fastqsanger.gz | |||
| SRR25663302.fastq.gz | Fastqsanger.gz |
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Project description:Unlocking the power of transcriptomic biomarkers in qualitative and quantitative genotoxicity assessment of chemicals I
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Project description:Unlocking the power of transcriptomic biomarkers in qualitative and quantitative genotoxicity assessment of chemicals II
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Project description:There is a need to move from binary hazard assessment to more quantitative assessment of genotoxicity to better inform human health risk assessment and understand the relevance of positive in vitro genotoxicity findings. New approach methodologies (NAMs), including transcriptomic biomarkers combined with high-throughput technologies, enable the testing of a broad concentration range, which allows quantitative assessment of in vitro results. Initial work with the transcriptomic GENOMARK and TGx-DDI biomarkers demonstrate their potential use for hazard identification and chemical prioritization; however, no study has evaluated the concordance and complementarity of GENOMARK and TGx-DDI. The overall aim of this study is to examine if a combined approach of integrating both transcriptomic biomarkers for genotoxicity in human relevant HepaRGTM cells increases the certainty in hazard calls and potency rankings of chemicals. A sub-aim is to investigate whether GENOMARK is applicable to the TempO-Seq® high-throughput sequencing technology, to collect concentration-response data to rapidly perform hazard classification and potency ranking. Therefore, HepaRGTM cells were exposed to 10 chemicals (i.e. eight known in vivo genotoxicants and two in vivo non-genotoxicants) in increasing concentrations over 72h. TempO-Seq® was used to obtain concentration-response data for both biomarkers. Benchmark concentration (BMC) modelling of chemicals that were classified positive was conducted to obtain BMCs and transcriptomic points of departure (tPODs) for potency ranking. The results confirm that GENOMARK is applicable to TempO-Seq® since it achieved 100% predictive accuracy. In addition, a high concordance was observed in the hazard classifications and potency rankings between both biomarkers. Overall, our findings show that in vitro transcriptomic data can be used to rapidly and effectively identify genotoxic hazards while simultaneously providing additional insights on potency that is more informative in a modern hazard assessment paradigm. The results of this case study support the high value of integrating these NAMs in a weight of evidence evaluation of genotoxicity using the important human-liver cell line.
2024-03-27 | GSE241068 | GEO
Project description:There is a need to move from binary hazard assessment to more quantitative assessment of genotoxicity to better inform human health risk assessment and understand the relevance of positive in vitro genotoxicity findings. New approach methodologies (NAMs), including transcriptomic biomarkers combined with high-throughput technologies, enable the testing of a broad concentration range, which allows quantitative assessment of in vitro results. Initial work with the transcriptomic GENOMARK and TGx-DDI biomarkers demonstrate their potential use for hazard identification and chemical prioritization; however, no study has evaluated the concordance and complementarity of GENOMARK and TGx-DDI. The overall aim of this study is to examine if a combined approach of integrating both transcriptomic biomarkers for genotoxicity in human relevant HepaRGTM cells increases the certainty in hazard calls and potency rankings of chemicals. A sub-aim is to investigate whether GENOMARK is applicable to the TempO-Seq® high-throughput sequencing technology, to collect concentration-response data to rapidly perform hazard classification and potency ranking. Therefore, HepaRGTM cells were exposed to 10 chemicals (i.e. eight known in vivo genotoxicants and two in vivo non-genotoxicants) in increasing concentrations over 72h. TempO-Seq® was used to obtain concentration-response data for both biomarkers. Benchmark concentration (BMC) modelling of chemicals that were classified positive was conducted to obtain BMCs and transcriptomic points of departure (tPODs) for potency ranking. The results confirm that GENOMARK is applicable to TempO-Seq® since it achieved 100% predictive accuracy. In addition, a high concordance was observed in the hazard classifications and potency rankings between both biomarkers. Overall, our findings show that in vitro transcriptomic data can be used to rapidly and effectively identify genotoxic hazards while simultaneously providing additional insights on potency that is more informative in a modern hazard assessment paradigm. The results of this case study support the high value of integrating these NAMs in a weight of evidence evaluation of genotoxicity using the important human-liver cell line.
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Project description:To modernize genotoxicity assessment and reduce reliance on experimental animals, new approach methodologies (NAMs) that provide human-relevant dose-response data are needed. Two transcriptomic biomarkers, GENOMARK and TGx-DDI, have shown a high classification accuracy for genotoxicity. As these biomarkers were extracted from different training sets, we investigated whether combining the two biomarkers in a human-derived metabolically competent cell line (i.e., HepaRG) provides complementary information for the classification of genotoxic hazard identification and potency ranking. First, the applicability of GENOMARK to TempO-Seq, a high-throughput transcriptomic technology, was evaluated. HepaRG cells were exposed for 72 h to increasing concentrations of 10 chemicals (i.e., eight known in vivo genotoxicants and two in vivo nongenotoxicants). Gene expression data were generated using the TempO-Seq technology. We found a prediction performance of 100%, confirming the applicability of GENOMARK to TempO-Seq. Classification using TGx-DDI was then compared to GENOMARK. For the chemicals identified as genotoxic, benchmark concentration modeling was conducted to perform potency ranking. The high concordance observed for both hazard classification and potency ranking by GENOMARK and TGx-DDI highlights the value of integrating these NAMs in a weight of evidence evaluation of genotoxicity.
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Project description:Several genotoxic chemicals have been reported to produce threshold-shaped dose-response curves for mutation and genotoxicity assays, both in vivo and in vitro. These data challenge the current default practice for risk assessment of genotoxic chemicals, which assumes a linear dose-response below the lowest tested dose. Due to the inherent challenges in data collection and analysis, statistical methods cannot determine whether a biological threshold exists with sufficient confidence to overturn this assumption of linearity. Indeed, to truly define the shape of the dose-response curves, we must look to the underlying biology and develop targeted experiments to identify and measure the key processes governing cellular response at low doses. This chapter describes a series of studies aimed at defining the transcriptional responses to DNA damage in an effort to identify the key processes regulating low-dose DNA damage response.
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Project description:power plant metagenome Raw sequence reads
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Project description:In vitro toxicogenomics signatures to predict mode of action can facilitate chemical screening. We recently demonstrated the use of the TGx-28.65 genomic biomarker (representing: toxicogenomics (TGx), developed using a 28 chemical training set, and comprising 65 genes) in classifying agents as genotoxic (DNA damaging) and non-genotoxic in human lymphoblastoid TK6 cells. Because TK6 cells do not possess cytochrome P450 activity, we confirmed accurate classification in cells co-exposed to 1% 5,6 benzoflavone/phenobarbital-induced rat liver S9 for metabolic activation. However, chemicals may require different types of S9 for activation. Here we conducted experiments in TK6 cells exposed to chemicals in the presence of 2% or 10% Aroclor-induced, or 5% ethanol-induced rat liver S9 to expand TGx-28.65 biomarker application. Gene expression profiles were produced 3-4 hr following a 4 hr co-exposure of TK cells to test chemicals (seven genotoxic and two non-genotoxic, three concentrations, and concurrent solvent controls) and S9. Relative survival and micronucleus frequency was assessed by flow cytometry in cells 20 hr after the exposure. We found that genotoxicity/non-genotoxicity could be accurately predicted for the test compounds using the different S9s. One technical replicate of cells co-treated with dexamethasone and 10% Aroclor-induced S9 was falsely predicted as genotoxic, suggesting caution in using high concentrations of S9. TGx-28.65 correctly classified low concentrations of genotoxic chemicals (those not causing cytotoxicity or micronuclei) as genotoxic, demonstrating that it is a sensitive biomarker of genotoxicity. Overall, the work confirms that different S9s can be used in TK6 cells without impairing predictivity using the TGx-28.65 biomarker.
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