Issue 4, 2018

Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data

Abstract

The toxicogenomics field aims to understand and predict toxicity by using ‘omics’ data in order to study systems-level responses to compound treatments. In recent years there has been a rapid increase in publicly available toxicological and ‘omics’ data, particularly gene expression data, and a corresponding development of methods for its analysis. In this review, we summarize recent progress relating to the analysis of RNA-Seq and microarray data, review relevant databases, and highlight recent applications of toxicogenomics data for understanding and predicting compound toxicity. These include the analysis of differentially expressed genes and their enrichment, signature matching, methods based on interaction networks, and the analysis of co-expression networks. In the future, these state-of-the-art methods will likely be combined with new technologies, such as whole human body models, to produce a comprehensive systems-level understanding of toxicity that reduces the necessity of in vivo toxicity assessment in animal models.

Graphical abstract: Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data

Article information

Article type
Review Article
Submitted
16 Feb 2018
Accepted
08 May 2018
First published
19 Jun 2018
This article is Open Access
Creative Commons BY license

Mol. Omics, 2018,14, 218-236

Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data

B. Alexander-Dann, L. L. Pruteanu, E. Oerton, N. Sharma, I. Berindan-Neagoe, D. Módos and A. Bender, Mol. Omics, 2018, 14, 218 DOI: 10.1039/C8MO00042E

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