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Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs

Quantitative prediction of cellular responses to drugs and drug combinations is a challenging and valuable topic in pharmaceutical research. In the past decade, microarray technology has become a routine tool for monitoring genome-wide expression changes and has been widely adopted for exploring dru...

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Detalles Bibliográficos
Autores principales: Zhao, J, Zhang, X-S, Zhang, S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3944117/
https://www.ncbi.nlm.nih.gov/pubmed/24573337
http://dx.doi.org/10.1038/psp.2013.79
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author Zhao, J
Zhang, X-S
Zhang, S
author_facet Zhao, J
Zhang, X-S
Zhang, S
author_sort Zhao, J
collection PubMed
description Quantitative prediction of cellular responses to drugs and drug combinations is a challenging and valuable topic in pharmaceutical research. In the past decade, microarray technology has become a routine tool for monitoring genome-wide expression changes and has been widely adopted for exploring drug response in the pharmaceutical field. However, how to predict the synergistic effect of drug combinations using microarray data is a challenging task. In this article, we report a simple prediction framework based on the genome-wide and quantitative profiling of cellular responses to individual drugs. By exploring the differential expression profiles, our correlation-based strategy can reveal the synergistic effects of drug combinations. The comparison with gold-standard experimental results demonstrates the strengths and weaknesses in relation to prediction based only on cellular response to individual drugs. Specifically, the prediction strategy may work for a drug combination whose individual drugs show related transcriptomic mechanisms but not for others.
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spelling pubmed-39441172014-03-18 Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs Zhao, J Zhang, X-S Zhang, S CPT Pharmacometrics Syst Pharmacol Original Article Quantitative prediction of cellular responses to drugs and drug combinations is a challenging and valuable topic in pharmaceutical research. In the past decade, microarray technology has become a routine tool for monitoring genome-wide expression changes and has been widely adopted for exploring drug response in the pharmaceutical field. However, how to predict the synergistic effect of drug combinations using microarray data is a challenging task. In this article, we report a simple prediction framework based on the genome-wide and quantitative profiling of cellular responses to individual drugs. By exploring the differential expression profiles, our correlation-based strategy can reveal the synergistic effects of drug combinations. The comparison with gold-standard experimental results demonstrates the strengths and weaknesses in relation to prediction based only on cellular response to individual drugs. Specifically, the prediction strategy may work for a drug combination whose individual drugs show related transcriptomic mechanisms but not for others. Nature Publishing Group 2014-02 2014-02-26 /pmc/articles/PMC3944117/ /pubmed/24573337 http://dx.doi.org/10.1038/psp.2013.79 Text en Copyright © 2014 American Society for Clinical Pharmacology and Therapeutics http://creativecommons.org/licenses/by-nc-nd/3.0/ CPT: Pharmacometrics and Systems Pharmacology is an open-access journal published by Nature Publishing Group. This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Original Article
Zhao, J
Zhang, X-S
Zhang, S
Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
title Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
title_full Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
title_fullStr Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
title_full_unstemmed Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
title_short Predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
title_sort predicting cooperative drug effects through the quantitative cellular profiling of response to individual drugs
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3944117/
https://www.ncbi.nlm.nih.gov/pubmed/24573337
http://dx.doi.org/10.1038/psp.2013.79
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