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Emerging Bioinformatic Tools in Toxicogenomics

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Front. Genet. | doi: 10.3389/fgene.2018.00412

Network, Transcriptomic And Genomic Features Differentiate Genes Relevant For Drug Response

 Janet Piñero1, 2, Abel Gonzalez-Perez3, Emre Guney1, 2, Joaquim Aguirre-Plans2, Ferran Sanz1, 2, Baldo Oliva2 and  Laura I. Furlong1, 2*
  • 1Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Spain
  • 2CEXS - Universidad Pompeu Fabra (UPF) - Parque de Investigación Biomédica de Barcelona (PRBB), Spain
  • 3Institute for Research in Biomedicine, Spain

Understanding the mechanisms underlying drug therapeutic action and toxicity is crucial for the prevention and management of drug adverse reactions, and paves the way for a more efficient and rational drug design. The characterization of drug targets, drug metabolism proteins, and proteins associated to side effects according to their expression patterns, their tolerance to genomic variation and their role in cellular networks, is a necessary step in this direction. In this contribution, we hypothesize that different classes of proteins involved in the therapeutic effect of drugs and in their adverse effects have distinctive transcriptomics, genomics and network features. We explored the properties of these proteins within global and organ-specific interactomes, using multi-scale network features, evaluated their gene expression profiles in different organs and tissues, and assessed their tolerance to loss-of-function variants leveraging data from 60K subjects. We found that drug targets that mediate side effects are more central in cellular networks, more intolerant to loss-of-function variation, and show a wider breadth of tissue expression than targets not mediating side effects. In contrast, drug metabolizing enzymes and transporters are less central in the interactome, more tolerant to deleterious variants, and are more constrained in their tissue expression pattern. Our findings highlight distinctive features for proteins related to drug effects, which could be applied to prioritize drugs with fewer probabilities of causing side effects.

Keywords: drug response, pharmacogenomics, Adverse Drug Reaction, Genomics, network biology, Gene Expression

Received: 05 Jul 2018; Accepted: 05 Sep 2018.

Edited by:

Danyel Jennen, Department of Toxicogenomics, Maastricht University, Netherlands

Reviewed by:

Xia Yang, University of California, Los Angeles, United States
Francesco Russo, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Denmark  

Copyright: © 2018 Piñero, Gonzalez-Perez, Guney, Aguirre-Plans, Sanz, Oliva and Furlong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Laura I. Furlong, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, 08003, Catalonia, Spain, lfurlong@imim.es