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Proteomic cellular signatures of kinase inhibitor-induced cardiotoxicity

ABSTRACT: Drug Toxicity Signature Generation Center (DToxS) at the Icahn School of Medicine at Mount Sinai is an integral part of the NIH Library of Integrated Network-Based Cellular Signatures (LINCS) program. A key aim of DToxS is to generate both proteomic and transcriptomic signatures that cab predict adverse effects, especially cardiotoxicity, of drugs approved by the Food and Drug Administration. Towards this goal, high throughput shot-gun proteomics experiments on 308 cell line/drug combinations (from four primary human cardiomyocyte cell lines purchased from PromoCell), 64 HeLa control lysates, and 9 auxiliary treatment samples have been conducted at the Center for Advanced Proteomics Research at Rutgers-New Jersey Medical School. The integrated proteomic and transcriptomic signatures have been used for computational network analysis to identify cellular signatures of cardiotoxicity that may predict drug-induced toxicity and possible mitigation of such toxicities by mixing different drugs. Both raw and processed proteomics data have been carefully controlled for quality and have been made publicly available via the PRoteomics IDEntifications (PRIDE) database. As such, this broad drug-stimulated proteomic dataset is valuable for the prediction drug toxicities and their mitigation. All data are available through CC BY 4.0 open license.

PROVIDER: LDS-1575 | LINCS | 2020-03-02

REPOSITORIES: LINCS

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Project description:In summary, we characterized genomic signatures of response to drugs of abuse and we found positive correlations between the drug-induced expression and various behavioral effects. These signatures are formed by two dynamically inducible transcriptional networks: (1) CREB/SRF-dependent gene pattern that appears to be related to drug-induced neuronal activity, (2) the pattern of genes controlled at least in part via release of glucocorticoids and androgens that are associated with rewarding and harmful drug effects. The discovery of co-expressed networks of genes allowed for the identification of master-switch controlling factors involved in molecular response to the drugs. Finally, using the pharmacological tools we were able to dissect and inhibit particular gene expression patterns from genomic profile. Type: Drug response, Time-course, Gene expression profiling with Illumina Microarrays Keywords: Addiction, Drugs of abuse, Time-course, Immediate Early Genes, Glucocorticoid receptor dependent genes, Cocaine, Heroin, Nicotine, Ethanol, Morphine, Methamphetamine The microarray experiment was performed to analyze time-course of drug-induced transcriptional response in C57BL/6J mouse striatum. Six the most addictive and harming drugs of abuse (morphine 20 mg/kg, heroin 10 mg/kg, ethanol 2 g/kg, nicotine 1 mg/kg, methamphetamine 2 mg/kg or cocaine 25 mg/kg, i.p.) were selected for the comparison. Drug doses were previously reported as rewarding in mice and further tested in our laboratory. To analyze dynamics of early, intermediate and relatively late changes of mRNA abundance the experiment was performed in four time points (1, 2, 4 and 8h after drug administration). To exclude influence of drug injection and circadian rhythm on gene expression profile, control groups of saline treated and naïve animals were prepared for each time point. Design of the experiment assumed pooling of two animals per each array and using of three independent arrays per group. To provide appropriate balance in the whole dataset groups were equally divided between the array hybridization batches. 'Complete' normalized data and non-normalized data (containing control rows not represented in Platform GPL6105) are linked below as supplementary files.

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Proteomic cellular signatures of kinase inhibitor-induced cardiotoxicity

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