Abstract
The growth and survival of cancer cells are greatly related to their surrounding microenvironment. To understand the regulation under the impact of anti-cancer drugs and their synergistic effects, we have developed a multiscale agent-based model that can investigate the synergistic effects of drug combinations with three innovations. First, it explores the synergistic effects of drug combinations in a huge dose combinational space at the cell line level. Second, it can simulate the interaction between cells and their microenvironment. Third, it employs both local and global optimization algorithms to train the key parameters and validate the predictive power of the model by using experimental data. The research results indicate that our multicellular system can not only describe the interactions between the microenvironment and cells in detail, but also predict the synergistic effects of drug combinations.
Highlights
As a complex disease caused by a variety of factors, cancer often involves with multiple gene mutations, signal pathway abnormalities and metabolic changes [1,2]
Since single drug therapy is prone to cause drug resistance, it is currently popular for the scientists and clinicians to explore efficient drug combination therapies from the list of existing drugs [3,4,5], which can increase treatment efficacy and reduce toxicity, and produce a better therapeutic outcome than a single drug under the same application dose condition [6,7]
If no space is available, the cell will become reversibly quiescent and will wait till the round. This 3D model is implemented in Matlab (R2014a(8.3.0.532),The MathWorks, Inc., Natick, MA, USA), which can describe the interactions between cancer cells and the microenvironment under the stimulation of the drugs, and can predict the synergistic effects of the combination therapy
Summary
As a complex disease caused by a variety of factors, cancer often involves with multiple gene mutations, signal pathway abnormalities and metabolic changes [1,2]. Since single drug therapy is prone to cause drug resistance, it is currently popular for the scientists and clinicians to explore efficient drug combination therapies from the list of existing drugs [3,4,5], which can increase treatment efficacy and reduce toxicity, and produce a better therapeutic outcome than a single drug under the same application dose condition [6,7]. There is potential to treat cancer by studying the synergistic effects of drug combination therapies [8,9]. With the development of information technology, cancer researchers started employing mathematical models to investigate the synergistic effects of drugs [10,11]. Sun et al [19]
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