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.
Highlights
One approach to address this has been to treat toxicity as a ‘Systems Biology’ problem, considering activity in the whole system simultaneously, as opposed to e.g. activity against a single receptor
Whilst the concept of systems biology is over 50 years old,[6] only recently have advancements in high-throughput technologies led to the generation of sufficiently large data sets to assess the state of a biological system in a meaningful way.[7]
In order to investigate whether transcriptomic signatures could provide a signal of hERG inhibition, Connectivity Map (CMap) profiles of 673 drugs including 119 known hERG inhibitors were clustered using affinity propagation, a clustering algorithm based on the idea of communication between data points.[110]
Summary
It provides histopathological, hematologic and clinical chemistry data associated with compound treatments, allowing specific forms of toxicity to be investigated. When analysing and interpreting data from these repositories, the difference between specific cell lines and animal models should be taken into consideration, as it will play a significant role in the biological meaning of the toxic response Despite these considerations, the availability and size of these public databases allow for the development of methods that enable the identification of the biological processes taking place in vivo and in vitro. In early works and especially in the case of small sample size DEG determination
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