TY - JOUR
T1 - Exploring the potential of ToxCast™ data for mechanism-based prioritization of chemicals in regulatory context
T2 - Case study with priority existing chemicals (PECs) under K-REACH
AU - Kim, Donghyeon
AU - Jeong, Jaeseong
AU - Choi, Jinhee
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/8
Y1 - 2023/8
N2 - Recent studies have highlighted the potential of the ToxCast™ database for mechanism-based prioritization of chemicals. To explore the applicability of ToxCast data in the context of regulatory inventory chemicals, we screened 510 priority existing chemicals (PECs) regulated under the Act on the Registration and Evaluation, etc. of Chemical Substances (K-REACH) using ToxCast bioassays. In our analysis, a hit-call data matrix containing 298984 chemical-gene interactions was computed for 949 bioassays with the intended target genes, which enabled the identification of the putative toxicity mechanisms. Based on the reactivity to the chemicals, we analyzed 412 bioassays whose intended target gene families were cytochrome P450, oxidoreductase, transporter, nuclear receptor, steroid hormone, and DNA-binding. We also identified 141 chemicals based on their reactivity in the bioassays. These chemicals are mainly in consumer products including colorants, preservatives, air fresheners, and detergents. Our analysis revealed that in vitro bioactivities were involved in the relevant mechanisms inducing in vivo toxicity; however, this was not sufficient to predict more hazardous chemicals. Overall, the current results point to a potential and limitation in using ToxCast data for chemical prioritization in regulatory context in the absence of suitable in vivo data.
AB - Recent studies have highlighted the potential of the ToxCast™ database for mechanism-based prioritization of chemicals. To explore the applicability of ToxCast data in the context of regulatory inventory chemicals, we screened 510 priority existing chemicals (PECs) regulated under the Act on the Registration and Evaluation, etc. of Chemical Substances (K-REACH) using ToxCast bioassays. In our analysis, a hit-call data matrix containing 298984 chemical-gene interactions was computed for 949 bioassays with the intended target genes, which enabled the identification of the putative toxicity mechanisms. Based on the reactivity to the chemicals, we analyzed 412 bioassays whose intended target gene families were cytochrome P450, oxidoreductase, transporter, nuclear receptor, steroid hormone, and DNA-binding. We also identified 141 chemicals based on their reactivity in the bioassays. These chemicals are mainly in consumer products including colorants, preservatives, air fresheners, and detergents. Our analysis revealed that in vitro bioactivities were involved in the relevant mechanisms inducing in vivo toxicity; however, this was not sufficient to predict more hazardous chemicals. Overall, the current results point to a potential and limitation in using ToxCast data for chemical prioritization in regulatory context in the absence of suitable in vivo data.
KW - Mechanism-based prioritization
KW - New approach methodologies (NAMs)
KW - Priority existing chemicals
KW - Regulatory toxicology
KW - ToxCast
UR - http://www.scopus.com/inward/record.url?scp=85164332796&partnerID=8YFLogxK
U2 - 10.1016/j.yrtph.2023.105439
DO - 10.1016/j.yrtph.2023.105439
M3 - Article
C2 - 37392832
AN - SCOPUS:85164332796
SN - 0273-2300
VL - 142
JO - Regulatory Toxicology and Pharmacology
JF - Regulatory Toxicology and Pharmacology
M1 - 105439
ER -