Background: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can... Show moreBackground: Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles.Methods: We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values < 0.05) of the next-gen TM-derived gene sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals.Results: Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals.Conclusions: Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect. Show less
Hettne, K.M.; Boorsma, A.; Dartel, D.A.M. van; Goeman, J.J.; Jong, E. de; Piersma, A.H.; ... ; Kors, J.A. 2013
ABSTRACT: BACKGROUND: Myostatin is a potent muscle growth inhibitor that belongs to the Transforming Growth Factor-beta (TGF-beta) family. Mutations leading to non functional myostatin have been... Show moreABSTRACT: BACKGROUND: Myostatin is a potent muscle growth inhibitor that belongs to the Transforming Growth Factor-beta (TGF-beta) family. Mutations leading to non functional myostatin have been associated with hypermuscularity in several organisms. By contrast, Duchenne muscular dystrophy (DMD) is characterized by a loss of muscle fibers and impaired regeneration. In this study, we aim to knockdown myostatin by means of exon skipping, a technique which has been successfully applied to reframe the genetic defect of dystrophin gene in DMD patients. METHODS: We targeted myostatin exon 2 using antisense oligonucleotides (AON) in healthy and DMD-derived myotubes cultures. We assessed the exon skipping level, transcriptional expression of myostatin and its target genes, and combined myostatin and several dystrophin AONs. These AONs were also applied in the mdx mice models via intramuscular injections. RESULTS: Myostatin AON induced exon 2 skipping in cell cultures and to a lower extent in the mdx mice. It was accompanied by decrease in myostatin mRNA and enhanced MYOG and MYF5 expression. Furthermore, combination of myostatin and dystrophin AONs induced simultaneous skipping of both genes. CONCLUSIONS: We conclude that two AONs can be used to target two different genes, MSTN and DMD, in a straightforward manner. Targeting multiple ligands of TGF-beta family will be more promising as adjuvant therapies for DMD. Show less
