Literature DB >> 29529260

Differentiating Pathway-Specific From Nonspecific Effects in High-Throughput Toxicity Data: A Foundation for Prioritizing Adverse Outcome Pathway Development.

Kellie A Fay1,2, Daniel L Villeneuve3, Joe Swintek4, Stephen W Edwards5,6, Mark D Nelms5, Brett R Blackwell3, Gerald T Ankley3.   

Abstract

The U.S. Environmental Protection Agency's ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential apical effects relevant to risk assessors. Thus, efforts are underway to develop AOPs relevant to pathway-specific perturbations detected in ToxCast assays. Previous work identified a "cytotoxic burst" (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared with the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). The prioritization approaches did not appear to be influenced by inter-assay differences in chemical bioavailability. Furthermore, the outcomes were robust based on a variety of different parameters used to define the CTB.

Entities:  

Mesh:

Substances:

Year:  2018        PMID: 29529260      PMCID: PMC6820004          DOI: 10.1093/toxsci/kfy049

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  38 in total

Review 1.  Adverse outcome pathways: a conceptual framework to support ecotoxicology research and risk assessment.

Authors:  Gerald T Ankley; Richard S Bennett; Russell J Erickson; Dale J Hoff; Michael W Hornung; Rodney D Johnson; David R Mount; John W Nichols; Christine L Russom; Patricia K Schmieder; Jose A Serrrano; Joseph E Tietge; Daniel L Villeneuve
Journal:  Environ Toxicol Chem       Date:  2010-03       Impact factor: 3.742

2.  The ToxCast program for prioritizing toxicity testing of environmental chemicals.

Authors:  David J Dix; Keith A Houck; Matthew T Martin; Ann M Richard; R Woodrow Setzer; Robert J Kavlock
Journal:  Toxicol Sci       Date:  2006-09-08       Impact factor: 4.849

3.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

Authors:  Da Wei Huang; Brad T Sherman; Richard A Lempicki
Journal:  Nat Protoc       Date:  2009       Impact factor: 13.491

4.  Development of the adverse outcome pathway "alkylation of DNA in male premeiotic germ cells leading to heritable mutations" using the OECD's users' handbook supplement.

Authors:  Carole L Yauk; Iain B Lambert; M E Bette Meek; George R Douglas; Francesco Marchetti
Journal:  Environ Mol Mutagen       Date:  2015-05-22       Impact factor: 3.216

5.  Applying Adverse Outcome Pathways (AOPs) to support Integrated Approaches to Testing and Assessment (IATA).

Authors:  Knut Erik Tollefsen; Stefan Scholz; Mark T Cronin; Stephen W Edwards; Joop de Knecht; Kevin Crofton; Natalia Garcia-Reyero; Thomas Hartung; Andrew Worth; Grace Patlewicz
Journal:  Regul Toxicol Pharmacol       Date:  2014-09-27       Impact factor: 3.271

6.  Towards AOP application--implementation of an integrated approach to testing and assessment (IATA) into a pipeline tool for skin sensitization.

Authors:  Grace Patlewicz; Chanita Kuseva; Antonia Kesova; Ioanna Popova; Teodor Zhechev; Todor Pavlov; David W Roberts; Ovanes Mekenyan
Journal:  Regul Toxicol Pharmacol       Date:  2014-06-11       Impact factor: 3.271

7.  tcpl: the ToxCast pipeline for high-throughput screening data.

Authors:  Dayne L Filer; Parth Kothiya; R Woodrow Setzer; Richard S Judson; Matthew T Martin
Journal:  Bioinformatics       Date:  2017-02-15       Impact factor: 6.937

8.  MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development.

Authors:  M G Barron; C R Lilavois; T M Martin
Journal:  Aquat Toxicol       Date:  2015-02-07       Impact factor: 4.964

9.  Application of the narcosis target lipid model to algal toxicity and deriving predicted-no-effect concentrations.

Authors:  Joy A McGrath; Thomas F Parkerton; Dominic M Di Toro
Journal:  Environ Toxicol Chem       Date:  2004-10       Impact factor: 3.742

10.  Tumor necrosis factors alpha and beta protect neurons against amyloid beta-peptide toxicity: evidence for involvement of a kappa B-binding factor and attenuation of peroxide and Ca2+ accumulation.

Authors:  S W Barger; D Hörster; K Furukawa; Y Goodman; J Krieglstein; M P Mattson
Journal:  Proc Natl Acad Sci U S A       Date:  1995-09-26       Impact factor: 11.205

View more
  9 in total

Review 1.  In silico toxicology: From structure-activity relationships towards deep learning and adverse outcome pathways.

Authors:  Jennifer Hemmerich; Gerhard F Ecker
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2020-03-31

Review 2.  IVIVE: Facilitating the Use of In Vitro Toxicity Data in Risk Assessment and Decision Making.

Authors:  Xiaoqing Chang; Yu-Mei Tan; David G Allen; Shannon Bell; Paul C Brown; Lauren Browning; Patricia Ceger; Jeffery Gearhart; Pertti J Hakkinen; Shruti V Kabadi; Nicole C Kleinstreuer; Annie Lumen; Joanna Matheson; Alicia Paini; Heather A Pangburn; Elijah J Petersen; Emily N Reinke; Alexandre J S Ribeiro; Nisha Sipes; Lisa M Sweeney; John F Wambaugh; Ronald Wange; Barbara A Wetmore; Moiz Mumtaz
Journal:  Toxics       Date:  2022-05-01

3.  Identifying the link between chemical exposures and breast cancer in African American women via integrated in vitro and exposure biomarker data.

Authors:  Katelyn M Polemi; Vy K Nguyen; Julien Heidt; Adam Kahana; Olivier Jolliet; Justin A Colacino
Journal:  Toxicology       Date:  2021-09-30       Impact factor: 4.221

4.  Cytotoxicity Burst? Differentiating Specific from Nonspecific Effects in Tox21 in Vitro Reporter Gene Assays.

Authors:  Beate I Escher; Luise Henneberger; Maria König; Rita Schlichting; Fabian C Fischer
Journal:  Environ Health Perspect       Date:  2020-07-23       Impact factor: 9.031

5.  High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity.

Authors:  Susanna H Wegner; Caroline L Pinto; Caroline L Ring; John F Wambaugh
Journal:  Environ Int       Date:  2020-02-09       Impact factor: 9.621

6.  Risk-Based Prioritization of Organic Chemicals and Locations of Ecological Concern in Sediment From Great Lakes Tributaries.

Authors:  Austin K Baldwin; Steven R Corsi; Owen M Stefaniak; Luke C Loken; Daniel L Villeneuve; Gerald T Ankley; Brett R Blackwell; Peter L Lenaker; Michelle A Nott; Marc A Mills
Journal:  Environ Toxicol Chem       Date:  2022-02-28       Impact factor: 4.218

7.  Prioritizing Pharmaceutical Contaminants in Great Lakes Tributaries Using Risk-Based Screening Techniques.

Authors:  Matthew A Pronschinske; Steven R Corsi; Laura A DeCicco; Edward T Furlong; Gerald T Ankley; Brett R Blackwell; Daniel L Villeneuve; Peter L Lenaker; Michelle A Nott
Journal:  Environ Toxicol Chem       Date:  2022-07-21       Impact factor: 4.218

8.  Molecular Image-Based Prediction Models of Nuclear Receptor Agonists and Antagonists Using the DeepSnap-Deep Learning Approach with the Tox21 10K Library.

Authors:  Yasunari Matsuzaka; Yoshihiro Uesawa
Journal:  Molecules       Date:  2020-06-15       Impact factor: 4.411

9.  Identifying Chemicals and Mixtures of Potential Biological Concern Detected in Passive Samplers from Great Lakes Tributaries Using High-Throughput Data and Biological Pathways.

Authors:  David A Alvarez; Steven R Corsi; Laura A De Cicco; Daniel L Villeneuve; Austin K Baldwin
Journal:  Environ Toxicol Chem       Date:  2021-07-08       Impact factor: 3.742

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.