Abstract
Drug development has been hampered by a high failure rate in clinical trials due to efficacy or safety issues not predicted by preclinical studies in model systems. A key contributor is our incomplete understanding of drug functions across organ systems and species. Therefore, elucidating species- and tissue-specific actions of drugs can provide systems level insights into therapeutic efficacy, potential adverse effects, and interspecies differences that are necessary for more effective translational medicine. Here, we present a comprehensive drug knowledgebase and analytical tool, PharmOmics, comprised of genomic footprints of drugs in individual tissues from human, mouse, and rat transcriptome data from GEO, ArrayExpress, TG-GATEs, and DrugMatrix. Using multi-species and multi-tissue gene expression signatures as molecular indicators of drug functions, we developed gene network-based approaches for drug repositioning. We demonstrate the potential of PharmOmics to predict drugs for new disease indications and validated two predicted drugs for non-alcoholic fatty liver disease in mice. We also examined the potential of PharmOmics to identify drugs related to hepatoxicity and nephrotoxicity. By combining tissue- and species-specific in vivo drug signatures with biological networks, PharmOmics serves as a complementary tool to support drug characterization.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Updated with new drug signatures and new drug toxicity investigation methods.
List of abbreviations
- ADR
- adverse drug reactions
- CTD
- comparative toxicogenomics database
- KEGG
- Kyoto Encyclopedia of Genes and Genomes
- DEG
- differential expressed genes
- FDR
- false discovery rate
- wKDA
- weighted key driver analysis
- NAFLD
- non-alcoholic fatty liver disease
- LDL
- low-density lipoprotein cholesterol
- GWAS
- genome-wide association study
- BN
- Bayesian gene regulatory network
- ROC
- Receiver operating characteristic
- HMGCR
- β-Hydroxy β-methylglutaryl-CoA receptor
- PPAR
- Peroxisome proliferator-activated receptor
- GPCR
- G-protein coupled receptor