Mining toxicogenomic data for dose-responsive pathways: implications in advancing next-generation risk assessment DOI Creative Commons
A. Rasim Barutcu, Michael B. Black, Andy Nong

et al.

Frontiers in Toxicology, Journal Year: 2023, Volume and Issue: 5

Published: Nov. 17, 2023

Introduction: While targeted investigation of key toxicity pathways has been instrumental for biomarker discovery, unbiased and holistic analysis transcriptomic data provides a complementary systems-level perspective. However, in systematic context, this approach yet to receive comprehensive methodical implementation. Methods: Here, we took an integrated bioinformatic by re-analyzing publicly available MCF7 cell TempO-seq 44 ToxCast chemicals using alternative pipeline demonstrate the power approach. The original study focused on analyzing gene signature comparing them vitro biological pathway altering concentrations determined from HTS assays. Our workflow, comparison, involves sequential differential expression, set enrichment, benchmark dose modeling, identification commonly perturbed network visualization. Results: Using approach, identified dose-responsive molecular changes, pathways, points departure untargeted manner. Critically, modeling based recapitulated apical endpoints, while also revealing additional mechanisms missed single endpoint analyses. Discussion: This systems-toxicology multifaceted insights into complex effects chemical exposures. work highlights importance data-driven techniques, alongside methods, comprehensively evaluating initiating events, dose-response relationships, pathways. Overall, integrating omics assays with robust bioinformatics holds promise improving risk assessment advancing new methodologies (NAMs).

Language: Английский

New Approach Methods (NAMs) for Genotoxicity Assessment of Nano- and Advanced Materials; Advantages and Challenges DOI

Arno C Gutleb,

Sivakumar Murugadoss,

Maciej Stępnik

et al.

Mutation Research/Genetic Toxicology and Environmental Mutagenesis, Journal Year: 2025, Volume and Issue: unknown, P. 503867 - 503867

Published: March 1, 2025

Language: Английский

Citations

0

In vitro to in vivo extrapolation modeling to facilitate the integration of transcriptomics data into genotoxicity assessment DOI Creative Commons
Anouck Thienpont, Eunnara Cho, Andrew Williams

et al.

Toxicology, Journal Year: 2025, Volume and Issue: unknown, P. 154165 - 154165

Published: April 1, 2025

Language: Английский

Citations

0

Molecular response of Chironomus riparius to antibiotics DOI Creative Commons
Judit Kálmán,

Yolanda Valcárcel-Rivera,

José‐Luis Martínez‐Guitarte

et al.

Current Research in Toxicology, Journal Year: 2025, Volume and Issue: unknown, P. 100239 - 100239

Published: May 1, 2025

Language: Английский

Citations

0

Unlocking the future of Environmental Safety: a Framework for Integrating New Approach Methodologies in Decision-Making DOI Creative Commons
Claudia Rivetti,

Jade Houghton,

Manuel Pablo Rubio

et al.

NAM journal., Journal Year: 2025, Volume and Issue: unknown, P. 100028 - 100028

Published: May 1, 2025

Language: Английский

Citations

0

Mining toxicogenomic data for dose-responsive pathways: implications in advancing next-generation risk assessment DOI Creative Commons
A. Rasim Barutcu, Michael B. Black, Andy Nong

et al.

Frontiers in Toxicology, Journal Year: 2023, Volume and Issue: 5

Published: Nov. 17, 2023

Introduction: While targeted investigation of key toxicity pathways has been instrumental for biomarker discovery, unbiased and holistic analysis transcriptomic data provides a complementary systems-level perspective. However, in systematic context, this approach yet to receive comprehensive methodical implementation. Methods: Here, we took an integrated bioinformatic by re-analyzing publicly available MCF7 cell TempO-seq 44 ToxCast chemicals using alternative pipeline demonstrate the power approach. The original study focused on analyzing gene signature comparing them vitro biological pathway altering concentrations determined from HTS assays. Our workflow, comparison, involves sequential differential expression, set enrichment, benchmark dose modeling, identification commonly perturbed network visualization. Results: Using approach, identified dose-responsive molecular changes, pathways, points departure untargeted manner. Critically, modeling based recapitulated apical endpoints, while also revealing additional mechanisms missed single endpoint analyses. Discussion: This systems-toxicology multifaceted insights into complex effects chemical exposures. work highlights importance data-driven techniques, alongside methods, comprehensively evaluating initiating events, dose-response relationships, pathways. Overall, integrating omics assays with robust bioinformatics holds promise improving risk assessment advancing new methodologies (NAMs).

Language: Английский

Citations

9