Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures

Roland C. Grafström, Penny Nymark, Vesa Hongisto, Ola Spjuth, Rebecca Ceder, Egon Willighagen, Barry Hardy, Samuel Kaski, Pekka Kohonen

Research output: Contribution to journalArticleScientificpeer-review

31 Citations (Scopus)

Abstract

This paper outlines the work for which Roland Grafstrom and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafstrom laboratory have, for many years, covered cancer biology studies, as well as the development and application of toxicity-predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art cancer biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in toxicity testing with alternative methods, such as bioinformatics-driven analyses of data obtained from human cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose toxicity testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of toxicity pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to human health and environmental safety.

Original languageEnglish
Pages (from-to)325-332
Number of pages8
JournalATLA: Alternatives to Laboratory Animals
Volume43
Issue number5
Publication statusPublished - Nov 2015
MoE publication typeA1 Journal article-refereed

Keywords

  • alternative methods
  • adverse outcome pathway
  • benchmark dose
  • bioinformatics
  • databases
  • in silico
  • systems toxicology
  • toxicogenomics
  • RISK-ASSESSMENT
  • PREDICTIVE TOXICOLOGY
  • BIG DATA
  • TOXICITY
  • CANCER
  • CHEMICALS
  • PATHWAYS
  • MODELS
  • KERATINOCYTES
  • MECHANISMS

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