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A Computational Model for Investigating Tumor Apoptosis Induced by Mesenchymal Stem Cell-Derived Secretome

View Article: PubMed Central - PubMed

ABSTRACT

Apoptosis is a programmed cell death that occurs naturally in physiological and pathological conditions. Defective apoptosis can trigger the development and progression of cancer. Experiments suggest the ability of secretome derived from mesenchymal stem cells (MSC) to induce apoptosis in cancer cells. We develop a hybrid discrete-continuous multiscale model to further investigate the effect of MSC-derived secretome in tumor growth. The model encompasses three biological scales. At the molecular scale, a system of ordinary differential equations regulate the expression of proteins involved in apoptosis signaling pathways. At the cellular scale, discrete equations control cellular migration, phenotypic switching, and proliferation. At the extracellular scale, a system of partial differential equations are employed to describe the dynamics of microenvironmental chemicals concentrations. The simulation is able to produce both avascular tumor growth rate and phenotypic patterns as observed in the experiments. In addition, we obtain good quantitative agreements with the experimental data on the apoptosis of HeLa cancer cells treated with MSC-derived secretome. We use this model to predict the growth of avascular tumor under various secretome concentrations over time.

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Simulation result of avascular tumor development with various concentrations of secretome up to t = 50 days. (a) Comparison of tumor volume treated without secretome (green) and with 0.2% secretome (black), 2% secretome (red), and 20% secretome (blue). (b) Comparison of the number of live cells in untreated tumors and those treated with 0.2%, 2%, and 20% secretome.
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fig7: Simulation result of avascular tumor development with various concentrations of secretome up to t = 50 days. (a) Comparison of tumor volume treated without secretome (green) and with 0.2% secretome (black), 2% secretome (red), and 20% secretome (blue). (b) Comparison of the number of live cells in untreated tumors and those treated with 0.2%, 2%, and 20% secretome.

Mentions: We run the simulations with secretome concentrations of 0% (no secretome), 0.2%, 2%, and 20%. Tumor diameter during the first 50 days of the development is then measured and the volume is estimated by applying the formula V = (4/3)π(d/2)3, where d is the diameter of the tumor. Figure 7 shows that secretome affects tumor growth in concentration dependent manner. During the first 10 days, there is no significant difference in volume between the untreated tumors and those treated with secretome. Starting day 11, the difference becomes more prominent with tumor treated with 20% secretome only grows up to 0.128 mm3, while the untreated tumor grows up to 0.30 mm3 at the end of 50-day period (see Figure 7(a)). This shows that 20% secretome concentration can effectively suppress tumor growth by approximately 57%.


A Computational Model for Investigating Tumor Apoptosis Induced by Mesenchymal Stem Cell-Derived Secretome
Simulation result of avascular tumor development with various concentrations of secretome up to t = 50 days. (a) Comparison of tumor volume treated without secretome (green) and with 0.2% secretome (black), 2% secretome (red), and 20% secretome (blue). (b) Comparison of the number of live cells in untreated tumors and those treated with 0.2%, 2%, and 20% secretome.
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Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC5120213&req=5

fig7: Simulation result of avascular tumor development with various concentrations of secretome up to t = 50 days. (a) Comparison of tumor volume treated without secretome (green) and with 0.2% secretome (black), 2% secretome (red), and 20% secretome (blue). (b) Comparison of the number of live cells in untreated tumors and those treated with 0.2%, 2%, and 20% secretome.
Mentions: We run the simulations with secretome concentrations of 0% (no secretome), 0.2%, 2%, and 20%. Tumor diameter during the first 50 days of the development is then measured and the volume is estimated by applying the formula V = (4/3)π(d/2)3, where d is the diameter of the tumor. Figure 7 shows that secretome affects tumor growth in concentration dependent manner. During the first 10 days, there is no significant difference in volume between the untreated tumors and those treated with secretome. Starting day 11, the difference becomes more prominent with tumor treated with 20% secretome only grows up to 0.128 mm3, while the untreated tumor grows up to 0.30 mm3 at the end of 50-day period (see Figure 7(a)). This shows that 20% secretome concentration can effectively suppress tumor growth by approximately 57%.

View Article: PubMed Central - PubMed

ABSTRACT

Apoptosis is a programmed cell death that occurs naturally in physiological and pathological conditions. Defective apoptosis can trigger the development and progression of cancer. Experiments suggest the ability of secretome derived from mesenchymal stem cells (MSC) to induce apoptosis in cancer cells. We develop a hybrid discrete-continuous multiscale model to further investigate the effect of MSC-derived secretome in tumor growth. The model encompasses three biological scales. At the molecular scale, a system of ordinary differential equations regulate the expression of proteins involved in apoptosis signaling pathways. At the cellular scale, discrete equations control cellular migration, phenotypic switching, and proliferation. At the extracellular scale, a system of partial differential equations are employed to describe the dynamics of microenvironmental chemicals concentrations. The simulation is able to produce both avascular tumor growth rate and phenotypic patterns as observed in the experiments. In addition, we obtain good quantitative agreements with the experimental data on the apoptosis of HeLa cancer cells treated with MSC-derived secretome. We use this model to predict the growth of avascular tumor under various secretome concentrations over time.

No MeSH data available.


Related in: MedlinePlus