Characterization of drug‐induced transcriptional modules: towards drug repositioning and functional understanding

• Published in: Molecular systems biology Vol. 9; no. 1; pp. 662 - n/a
• Main Authors: Iskar, Murat, Zeller, Georg, Blattmann, Peter, Campillos, Monica, Kuhn, Michael, Kaminska, Katarzyna H, Runz, Heiko, Gavin, Anne‐Claude, Pepperkok, Rainer, van Noort, Vera, Bork, Peer
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 2013; EMBO Press; Nature Publishing Group; Springer Nature
• Subjects: Adrenergic receptors; Animals; Biotechnology; Cell cycle; Cell Cycle - drug effects; Cell Cycle - genetics; cell line models in drug discovery; Cell Line, Tumor; Cell lines; Cholesterol; Cholesterol - genetics; Cholesterol - metabolism; Conservation; Databases, Genetic; DNA microarrays; Drug Repositioning; Drugs; drug‐induced transcriptional modules; Estrogens; Gene expression; Gene Expression Profiling; gene function prediction; Gene Regulatory Networks - drug effects; Genome; Genomes; Hepatocytes; Homeostasis; Humans; Liver; Liver - cytology; Liver - drug effects; Liver - metabolism; Menopause; Modulators; Modules; Organisms; Peroxisome Proliferator-Activated Receptors - genetics; Peroxisome Proliferator-Activated Receptors - metabolism; Pharmacogenetics; Pharmacology; Rats; Receptors, Adrenergic, alpha - genetics; Receptors, Adrenergic, alpha - metabolism; Receptors, Estrogen - genetics; Receptors, Estrogen - metabolism; Regulators; Species Specificity; Structure-Activity Relationship; Transcription; Transcription, Genetic - drug effects; transcriptome conservation across cell types and organisms
• ISSN: 1744-4292; 1744-4292
• DOI: 10.1038/msb.2013.20

In pharmacology, it is crucial to understand the complex biological responses that drugs elicit in the human organism and how well they can be inferred from model organisms. We therefore identified a large set of drug‐induced transcriptional modules from genome‐wide microarray data of drug‐treated human cell lines and rat liver, and first characterized their conservation. Over 70% of these modules were common for multiple cell lines and 15% were conserved between the human in vitro and the rat in vivo system. We then illustrate the utility of conserved and cell‐type‐specific drug‐induced modules by predicting and experimentally validating (i) gene functions, e.g., 10 novel regulators of cellular cholesterol homeostasis and (ii) new mechanisms of action for existing drugs, thereby providing a starting point for drug repositioning, e.g., novel cell cycle inhibitors and new modulators of α‐adrenergic receptor, peroxisome proliferator‐activated receptor and estrogen receptor. Taken together, the identified modules reveal the conservation of transcriptional responses towards drugs across cell types and organisms, and improve our understanding of both the molecular basis of drug action and human biology. Drug‐induced transcriptional modules (biclusters) were identified and annotated in three human cell lines and rat liver. These were used to assess conservation across systems and to infer and experimentally validate novel drug effects and gene functions. Synopsis Drug‐induced transcriptional modules (biclusters) were identified and annotated in three human cell lines and rat liver. These were used to assess conservation across systems and to infer and experimentally validate novel drug effects and gene functions. Biclustering of drug‐induced gene expression profiles resulted in modules of drugs and genes, which were enriched in both drug and gene annotations. Identifying drug‐induced transcriptional modules separately in three human cell lines and rat liver allows assessment of their conservation across model systems. About 70% of modules are conserved across cell lines, a lower bound of 15% was estimated for their conservation across organisms, and between the in vitro and in vivo systems. Drug‐induced transcriptional modules can predict novel gene functions. A conserved module associated with (chole)sterol metabolism revealed novel regulators of cellular cholesterol homeostasis; 10 of them were validated in functional imaging assays. Analysis of drugs clustered into modules can give new insights into their mechanisms of action and provide leads for drug repositioning. We predicted and experimentally validated novel cell cycle inhibitors and modulators of PPARγ, estrogen and adrenergic receptors, with potential for developing new therapies against diabetes and cancer.