Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Details

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State: Public
Version: Final published version
Serval ID
serval:BIB_0F969B733169
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.
Journal
Angiogenesis
Author(s)
Weiss A., Ding X., van Beijnum J.R., Wong I., Wong T.J., Berndsen R.H., Dormond O., Dallinga M., Shen L., Schlingemann R.O., Pili R., Ho C.M., Dyson P.J., van den Bergh H., Griffioen A.W., Nowak-Sliwinska P.
ISSN
1573-7209 (Electronic)
ISSN-L
0969-6970
Publication state
Published
Issued date
2015
Peer-reviewed
Oui
Volume
18
Number
3
Pages
233-244
Language
english
Notes
pdf: original paper
Abstract
Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.
Pubmed
Web of science
Open Access
Yes
Create date
13/07/2015 10:38
Last modification date
20/08/2019 12:36
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