Literature DB >> 24261707

Pathways for ligand activated nuclear receptors to unravel the genomic responses induced by hepatotoxicants.

R R R Fijten, D G J Jennen, J H M van Delft1.   

Abstract

The liver is a vital organ in vertebrates that can be subject to disease, among others due to exposure to toxic xenobiotic compounds. A group of transcription factors named ligand activated nuclear receptors (LANR) influence and regulate important liver functions, and can be activated by many xenobiotic compounds, which thereby can cause hepatotoxicity. Systematic analysis of the gene pathways regulated by LANR using modern 'omics technologies is important for investigating modes-of-action of hepatotoxicants. So far, these pathways are not publicly available in a format that allows these studies. We used PathVisio to build liver-specific LANR pathways, both for rats and humans. Since many LANR pathways are linked to each other, we also merged them into a meta-pathway. The pathways are in a GPML-format that enables pathway statistics and visualisations, and will be made available to the public through WikiPathways. We demonstrate the performance of these novel pathways in evaluating transcriptomic studies from the Japanese toxicogenomics project database (Open TG-GATEs). We show that the new pathways can be used to accurately analyse and visualize the effects of prototypical hepatotoxicants in important liver processes, and thus to evaluate the possible mode-of-actions of hepatotoxic xenobiotic compounds by assessing which LANRs are possible targets.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 24261707     DOI: 10.2174/1389200214666131118234138

Source DB:  PubMed          Journal:  Curr Drug Metab        ISSN: 1389-2002            Impact factor:   3.731


  2 in total

Review 1.  Tools for visualization and analysis of molecular networks, pathways, and -omics data.

Authors:  Jose M Villaveces; Prasanna Koti; Bianca H Habermann
Journal:  Adv Appl Bioinform Chem       Date:  2015-06-04

2.  New insights in Rett syndrome using pathway analysis for transcriptomics data.

Authors:  Friederike Ehrhart; Susan L M Coort; Elisa Cirillo; Eric Smeets; Chris T Evelo; Leopold Curfs
Journal:  Wien Med Wochenschr       Date:  2016-08-12
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.