Hepatic transcriptomic alterations for N,N-dimethyl-p-toluidine (DMPT) and p-toluidine after 5-day exposure in rats

Dunnick, June K.; Shockley, Keith R.; Morgan, Daniel L.; Brix, Amy E.; Travlos, Gregory S.; Gerrish, Kevin; Sanders, J. Michael; Ton, Thai-Vu; Pandiri, Arun R.

doi:10.1007/s00204-016-1831-7

Cited by 10 publications

(9 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A detailed workflow diagram can be found in Supplementary Figure S1. In addition, a parallel workflow diagram of an example analysis using previously published genomic dose-response data (Dunnick et al, 2017) can be found in Supplementary Figure S2.…”

Section: Discussionmentioning

confidence: 99%

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow

et al. 2018

View full text Add to dashboard Cite

A new version (version 2) of the genomic dose-response analysis software, BMDExpress, has been created. The software addresses the increasing use of transcriptomic dose-response data in toxicology, drug design, risk assessment and translational research. In this new version, we have implemented additional statistical filtering options (e.g. Williams' trend test), curve fitting models, Linux and Macintosh compatibility and support for additional transcriptomic platforms with up-to-date gene annotations. Furthermore, we have implemented extensive data visualizations, onthe-fly data filtering, and a batch-wise analysis workflow. We have also significantly re-engineered the code base to reflect contemporary software engineering practices and streamline future development. The first version of BMDExpress was developed in 2007 to meet an unmet demand for easy-touse transcriptomic dose-response analysis software. Since its original release, however, transcriptomic platforms, technologies, pathway annotations and quantitative methods for data analysis have undergone a large change necessitating a significant redevelopment of BMDExpress. To that end, as of 2016, the National Toxicology Program assumed stewardship of BMDExpress. The result is a modernized and updated BMDExpress 2 that addresses the needs of the growing toxicogenomics user community.

show abstract

Section: Discussionmentioning

confidence: 99%

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Raw expression data for livers of male Harlan Sprague Dawley or male F344/N rats exposed orally for 5 days to crude 4-methylcyclohexanemethanol (crude-MCHM), or neat 4-methylcyclohexanemethanol (MCHM), and for kidneys of rats exposed orally to propylene glycol phenyl ether (PPH) were accessed from the Gene Expression Omnibus (GEO) as series GSE75655, GSE75657 and GSE75656, respectively. Hepatic transcriptomics data for F344/N rats exposed orally to N,N-dimethyl-p-toluidine (DMPT) or p-toluidine for 5 days [17] were accessed from the GEO as series GSE100502. All.cel files available for each replicated exposure level and vehicle controls were included in this analysis.…”

Section: Gene Expression Datamentioning

confidence: 99%

“…N,N-dimethyl-p-toluidine (DMPT) is an accelerant for methyl methacrylate monomers in medical devices that has been shown to induce liver carcinogenesis in male and female F344/N rats and B6C3F1 mice in a 2-year oral exposure study. p-toluidine, structurally-related to DMPT, is reportedly a liver carcinogen in mice [17].…”

Section: Gene Expression Datamentioning

confidence: 99%

“…In this article we demonstrate the influence of different normalizations of expression microarrays on the findings from 5-day in vivo genomic dose-response studies of crude 4-methylcyclohexanemethanol (crude MCHM) [16], neat 4-methylcyclohexanemethanol (MCHM) [16], N,N-dimethyl-p-toluidine (DMPT) [17] and p-toluidine [17] in liver tissues, and propylene glycol phenyl ether (PPH) [16] in kidney tissues of orally-exposed rats. Our results indicate that normalization remarkably impacts the number of detected differentially expressed genes and responsive gene sets.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization

Mezencev

Auerbach

2020

PLoS ONE

View full text Add to dashboard Cite

Whole-genome expression data generated by microarray studies have shown promise for quantitative human health risk assessment. While numerous approaches have been developed to determine benchmark doses (BMDs) from probeset-level dose responses, sensitivity of the results to methods used for normalization of the data has not yet been systematically investigated. Normalization of microarray data converts raw hybridization signals to expression estimates that are expected to be proportional to the amounts of transcripts in the profiled specimens. Different approaches to normalization have been shown to greatly influence the results of some downstream analyses, including biological interpretation. In this study we evaluate the influence of microarray normalization methods on the transcriptomic BMDs. We demonstrate using in vivo data that the use of alternative pipelines for normalization of Affymetrix microarray data can have a considerable impact on the number of detected differentially expressed genes and pathways (processes) determined to be treatment responsive, which may lead to alternative interpretations of the data. In addition, we found that normalization can have a considerable effect (as much as~30-fold in this study) on estimation of the minimum biological potency (transcriptomic point of departure). We argue for consideration of alternative normalization methods and their data-informed selection to most effectively interpret microarray data for use in human health risk assessment.

show abstract

“…Raw expression data for livers of male Harlan Sprague Dawley or male F344/N rats exposed orally for 5 days to crude 4-methylcyclohexanemethanol (crude-MCHM), or neat 4-methylcyclohexanemethanol (MCHM), and for kidneys of rats exposed orally to propylene glycol phenyl ether (PPH) were accessed from the Gene Expression Omnibus (GEO) as series GSE75655, GSE75657 and GSE75656, respectively. Hepatic transcriptomics data for F344/N rats exposed orally to N,N-dimethyl-p-toluidine (DMPT) or ptoluidine for 5 days [17] were accessed from the GEO as series GSE100502. All .cel files available for each replicated exposure level and vehicle controls were included in this analysis.…”

Section: Gene Expression Datamentioning

confidence: 99%

The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization

Mezencev

Auerbach

2019

Preprint

View full text Add to dashboard Cite

Whole-genome expression data generated by microarray studies have shown promise for quantitative human health risk assessment. While numerous approaches have been developed to determine benchmark doses (BMDs) from probeset-level dose responses, sensitivity of the results to methods used for normalization of the data has not yet been systematically investigated. Normalization of microarray data converts raw hybridization signals to expression estimates that are expected to be proportional to the amounts of transcripts in the profiled specimens. Different approaches to normalization have been shown to greatly influence the results of some downstream analyses, including biological interpretation. In this study we evaluate the influence of microarray normalization methods on the transcriptomic BMDs. We demonstrate using in vivo data that the use of alternative pipelines for normalization of Affymetrix microarray data can have a considerable impact on the number of detected differentially expressed genes and pathways (processes) determined to be treatment responsive, which may lead to alternative interpretations of the data. In addition, we found that normalization can have a considerable effect (as much as ~30-fold in this study) on estimation of the minimum biological potency (transcriptomic point of departure). We argue for consideration of alternative normalization methods and their data-informed selection to most effectively interpret microarray data for use in human health risk assessment.

show abstract

Hepatic transcriptomic alterations for N,N-dimethyl-p-toluidine (DMPT) and p-toluidine after 5-day exposure in rats

Cited by 10 publications

References 49 publications

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow

The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization

The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization

Contact Info

Product

Resources

About