| Title |
Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer
|
|---|---|
| Published in |
Angiogenesis, April 2015
|
| DOI | 10.1007/s10456-015-9462-9 |
| Pubmed ID | |
| Authors |
Andrea Weiss, Xianting Ding, Judy R. van Beijnum, Ieong Wong, Tse J. Wong, Robert H. Berndsen, Olivier Dormond, Marchien Dallinga, Li Shen, Reinier O. Schlingemann, Roberto Pili, Chih-Ming Ho, Paul J. Dyson, Hubert van den Bergh, Arjan W. Griffioen, Patrycja Nowak-Sliwinska |
| 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 107 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 107 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 19% |
| Student > Master | 20 | 19% |
| Student > Bachelor | 17 | 16% |
| Researcher | 14 | 13% |
| Professor > Associate Professor | 7 | 7% |
| Other | 15 | 14% |
| Unknown | 14 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 15% |
| Agricultural and Biological Sciences | 14 | 13% |
| Medicine and Dentistry | 14 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 13 | 12% |
| Chemistry | 13 | 12% |
| Other | 21 | 20% |
| Unknown | 16 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 April 2016.
All research outputs
#20,318,358
of 22,860,626 outputs
Outputs from Angiogenesis
#439
of 536 outputs
Outputs of similar age
#224,068
of 264,665 outputs
Outputs of similar age from Angiogenesis
#2
of 5 outputs
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