» Articles » PMID: 31501805

Considerations for Strategic Use of High-Throughput Transcriptomics Chemical Screening Data in Regulatory Decisions

Overview
Date 2019 Sep 11
PMID 31501805
Citations 43
Authors
Affiliations
Soon will be listed here.
Abstract

Recently, numerous organizations, including governmental regulatory agencies in the U.S. and abroad, have proposed using data from New Approach Methodologies (NAMs) for augmenting and increasing the pace of chemical assessments. NAMs are broadly defined as any technology, methodology, approach or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. High-throughput transcriptomics (HTTr) is a type of NAM that uses gene expression profiling as an endpoint for rapidly evaluating the effects of large numbers of chemicals on cell culture systems. As compared to targeted high-throughput screening (HTS) approaches that measure the effect of chemical on target , HTTr is a non-targeted approach that allows researchers to more broadly characterize the integrated response of an intact biological system to chemicals that may affect a specific biological target or many biological targets under a defined set of treatment conditions (time, concentration, etc.). HTTr screening performed in concentration-response mode can provide potency estimates for the concentrations of chemicals that produce perturbations in cellular response pathways. Here, we discuss study design considerations for HTTr concentration-response screening and present a framework for the use of HTTr-based biological pathway-altering concentrations (BPACs) in a screening-level, risk-based chemical prioritization approach. The framework involves concentration-response modeling of HTTr data, mapping gene level responses to biological pathways, determination of BPACs, -to- extrapolation (IVIVE) and comparison to human exposure predictions.

Citing Articles

Leveraging a comprehensive unbiased RNAseq database to characterize human monocyte-derived macrophage gene expression profiles within commonly employed in vitro polarization methods.

Smyth T, Payton A, Hickman E, Rager J, Jaspers I Sci Rep. 2024; 14(1):26753.

PMID: 39500943 PMC: 11538326. DOI: 10.1038/s41598-024-78000-6.


Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study.

Ortega-Vallbona R, Palomino-Schatzlein M, Tolosa L, Benfenati E, Ecker G, Gozalbes R Int J Mol Sci. 2024; 25(20).

PMID: 39456937 PMC: 11508863. DOI: 10.3390/ijms252011154.


New approach methodologies (NAMs) for the assessment of cleaning products for respiratory irritation: workshop report.

Haber L, Bradley M, Buerger A, Behrsing H, Burla S, Clapp P Front Toxicol. 2024; 6:1431790.

PMID: 39439531 PMC: 11493779. DOI: 10.3389/ftox.2024.1431790.


Community-Engaged Research and the Use of Open Access ToxVal/ToxRef In Vivo Databases and New Approach Methodologies (NAM) to Address Human Health Risks From Environmental Contaminants.

Silva M, Capps S, London J Birth Defects Res. 2024; 116(9):e2395.

PMID: 39264239 PMC: 11407745. DOI: 10.1002/bdr2.2395.


Progress in toxicogenomics to protect human health.

Meier M, Harrill J, Johnson K, Thomas R, Tong W, Rager J Nat Rev Genet. 2024; 26(2):105-122.

PMID: 39223311 DOI: 10.1038/s41576-024-00767-1.


References
1.
Zhang , Chung , OLDENBURG . A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays. J Biomol Screen. 2000; 4(2):67-73. DOI: 10.1177/108705719900400206. View

2.
Slob W . Dose-response modeling of continuous endpoints. Toxicol Sci. 2002; 66(2):298-312. DOI: 10.1093/toxsci/66.2.298. View

3.
Filipsson A, Sand S, Nilsson J, Victorin K . The benchmark dose method--review of available models, and recommendations for application in health risk assessment. Crit Rev Toxicol. 2003; 33(5):505-42. View

4.
Subramanian A, Tamayo P, Mootha V, Mukherjee S, Ebert B, Gillette M . Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005; 102(43):15545-50. PMC: 1239896. DOI: 10.1073/pnas.0506580102. View

5.
Tietjen K, Drewes M, Stenzel K . High throughput screening in agrochemical research. Comb Chem High Throughput Screen. 2005; 8(7):589-94. DOI: 10.2174/138620705774575300. View