Literature DB >> 20493898

Predicting human developmental toxicity of pharmaceuticals using human embryonic stem cells and metabolomics.

Paul R West1, April M Weir, Alan M Smith, Elizabeth L R Donley, Gabriela G Cezar.   

Abstract

Teratogens, substances that may cause fetal abnormalities during development, are responsible for a significant number of birth defects. Animal models used to predict teratogenicity often do not faithfully correlate to human response. Here, we seek to develop a more predictive developmental toxicity model based on an in vitro method that utilizes both human embryonic stem (hES) cells and metabolomics to discover biomarkers of developmental toxicity. We developed a method where hES cells were dosed with several drugs of known teratogenicity then LC-MS analysis was performed to measure changes in abundance levels of small molecules in response to drug dosing. Statistical analysis was employed to select for specific mass features that can provide a prediction of the developmental toxicity of a substance. These molecules can serve as biomarkers of developmental toxicity, leading to better prediction of teratogenicity. In particular, our work shows a correlation between teratogenicity and changes of greater than 10% in the ratio of arginine to asymmetric dimethylarginine levels. In addition, this study resulted in the establishment of a predictive model based on the most informative mass features. This model was subsequently tested for its predictive accuracy in two blinded studies using eight drugs of known teratogenicity, where it correctly predicted the teratogenicity for seven of the eight drugs. Thus, our initial data shows that this platform is a robust alternative to animal and other in vitro models for the prediction of the developmental toxicity of chemicals that may also provide invaluable information about the underlying biochemical pathways. (c) 2010 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20493898     DOI: 10.1016/j.taap.2010.05.007

Source DB:  PubMed          Journal:  Toxicol Appl Pharmacol        ISSN: 0041-008X            Impact factor:   4.219


  39 in total

Review 1.  Cellular reprogramming: a new technology frontier in pharmaceutical research.

Authors:  Amy Brock; Hui-Tong Goh; Binxia Yang; Yu Lu; Hu Li; Yuin-Han Loh
Journal:  Pharm Res       Date:  2011-11-09       Impact factor: 4.200

2.  The validated embryonic stem cell test to predict embryotoxicity in vitro.

Authors:  Andrea E M Seiler; Horst Spielmann
Journal:  Nat Protoc       Date:  2011-06-16       Impact factor: 13.491

3.  Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline.

Authors:  Christina Ranninger; Marc Rurik; Alice Limonciel; Silke Ruzek; Roland Reischl; Anja Wilmes; Paul Jennings; Philip Hewitt; Wolfgang Dekant; Oliver Kohlbacher; Christian G Huber
Journal:  J Biol Chem       Date:  2015-06-08       Impact factor: 5.157

4.  MALDI-mass spectrometric imaging for the investigation of metabolites in Medicago truncatula root nodules.

Authors:  Erin Gemperline; Lingjun Li
Journal:  J Vis Exp       Date:  2014-03-05       Impact factor: 1.355

Review 5.  Teratogen screening with human pluripotent stem cells.

Authors:  Kathryn E Worley; Jennifer Rico-Varela; Dominic Ho; Leo Q Wan
Journal:  Integr Biol (Camb)       Date:  2018-09-17       Impact factor: 2.192

6.  The Opportunities of Metabolomics in Drug Safety Evaluation.

Authors:  Pengcheng Wang; Amina I Shehu; Xiaochao Ma
Journal:  Curr Pharmacol Rep       Date:  2017-01-03

7.  In vivo toxicology of carbon dots by 1H NMR-based metabolomics.

Authors:  Wei Hong; Yan Liu; Ming-Hui Li; Yue-Xiao Xing; Ting Chen; Yong-Hong Fu; Lei Jiang; He Zhao; Ai-Qun Jia; Jun-Song Wang
Journal:  Toxicol Res (Camb)       Date:  2018-04-18       Impact factor: 3.524

Review 8.  Energy metabolism in nuclear reprogramming.

Authors:  Clifford D L Folmes; Timothy J Nelson; Andre Terzic
Journal:  Biomark Med       Date:  2011-12       Impact factor: 2.851

9.  Methods for evaluating variability in human health dose-response characterization.

Authors:  Daniel A Axelrad; R Woodrow Setzer; Thomas F Bateson; Michael DeVito; Rebecca C Dzubow; Julie W Fitzpatrick; Alicia M Frame; Karen A Hogan; Keith Houck; Michael Stewart
Journal:  Hum Ecol Risk Assess       Date:  2019-11-06       Impact factor: 5.190

10.  Advances in Applications of Metabolomics in Pluripotent Stem Cell Research.

Authors:  Vijesh J Bhute; Xiaoping Bao; Sean P Palecek
Journal:  Curr Opin Chem Eng       Date:  2016-12-15       Impact factor: 5.163

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.