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Optimal drug combinations and minimal hitting sets

BACKGROUND: Identifying effective drug combinations that significantly improve over single agents is a challenging problem. Pairwise combinations already represent a huge screening effort. Beyond two drug combinations the task seems unfeasible. RESULTS: In this work we introduce a method to uncover...

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Detalles Bibliográficos
Autor principal: Vazquez, Alexei
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2738654/
https://www.ncbi.nlm.nih.gov/pubmed/19660129
http://dx.doi.org/10.1186/1752-0509-3-81
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author Vazquez, Alexei
author_facet Vazquez, Alexei
author_sort Vazquez, Alexei
collection PubMed
description BACKGROUND: Identifying effective drug combinations that significantly improve over single agents is a challenging problem. Pairwise combinations already represent a huge screening effort. Beyond two drug combinations the task seems unfeasible. RESULTS: In this work we introduce a method to uncover drug combinations with a putative effective response when presented to a heterogeneous population of malignant agents (strains), such as cancer cell lines or viruses. Using data quantifying the effect of single drugs over several individual strains, we search for minimal drug combinations that successfully target all strains. We show that the latter problem can be mapped to a minimal hitting set problem in mathematics. We illustrate this approach using data for the NCI60 panel of tumor derived cell lines, uncovering 14 anticancer drug combinations. CONCLUSION: The drug-response graph and the associated minimal hitting set method can be used to uncover effective drug combinations in anticancer drug screens and drug development programs targeting heterogeneous populations of infectious agents such as HIV.
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spelling pubmed-27386542009-09-05 Optimal drug combinations and minimal hitting sets Vazquez, Alexei BMC Syst Biol Research Article BACKGROUND: Identifying effective drug combinations that significantly improve over single agents is a challenging problem. Pairwise combinations already represent a huge screening effort. Beyond two drug combinations the task seems unfeasible. RESULTS: In this work we introduce a method to uncover drug combinations with a putative effective response when presented to a heterogeneous population of malignant agents (strains), such as cancer cell lines or viruses. Using data quantifying the effect of single drugs over several individual strains, we search for minimal drug combinations that successfully target all strains. We show that the latter problem can be mapped to a minimal hitting set problem in mathematics. We illustrate this approach using data for the NCI60 panel of tumor derived cell lines, uncovering 14 anticancer drug combinations. CONCLUSION: The drug-response graph and the associated minimal hitting set method can be used to uncover effective drug combinations in anticancer drug screens and drug development programs targeting heterogeneous populations of infectious agents such as HIV. BioMed Central 2009-08-06 /pmc/articles/PMC2738654/ /pubmed/19660129 http://dx.doi.org/10.1186/1752-0509-3-81 Text en Copyright © 2009 Vazquez; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Vazquez, Alexei
Optimal drug combinations and minimal hitting sets
title Optimal drug combinations and minimal hitting sets
title_full Optimal drug combinations and minimal hitting sets
title_fullStr Optimal drug combinations and minimal hitting sets
title_full_unstemmed Optimal drug combinations and minimal hitting sets
title_short Optimal drug combinations and minimal hitting sets
title_sort optimal drug combinations and minimal hitting sets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2738654/
https://www.ncbi.nlm.nih.gov/pubmed/19660129
http://dx.doi.org/10.1186/1752-0509-3-81
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