Limits...
Computational modeling of tumor response to vascular-targeting therapies--part I: validation.

Gevertz JL - Comput Math Methods Med (2011)

Bottom Line: Mathematical modeling techniques have been widely employed to understand how cancer grows, and, more recently, such approaches have been used to understand how cancer can be controlled.In this manuscript, a previously validated hybrid cellular automaton model of tumor growth in a vascularized environment is used to study the antitumor activity of several vascular-targeting compounds of known efficacy.The results presented herein suggest that vascular-targeting agents, as currently administered, cannot lead to cancer eradication, although a highly efficacious agent may lead to long-term cancer control.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ 08628-0718, USA. gevertz@tcnj.edu

ABSTRACT
Mathematical modeling techniques have been widely employed to understand how cancer grows, and, more recently, such approaches have been used to understand how cancer can be controlled. In this manuscript, a previously validated hybrid cellular automaton model of tumor growth in a vascularized environment is used to study the antitumor activity of several vascular-targeting compounds of known efficacy. In particular, this model is used to test the antitumor activity of a clinically used angiogenesis inhibitor (both in isolation, and with a cytotoxic chemotherapeutic) and a vascular disrupting agent currently undergoing clinical trial testing. I demonstrate that the mathematical model can make predictions in agreement with preclinical/clinical data and can also be used to gain more insight into these treatment protocols. The results presented herein suggest that vascular-targeting agents, as currently administered, cannot lead to cancer eradication, although a highly efficacious agent may lead to long-term cancer control.

Show MeSH

Related in: MedlinePlus

Sensitivity analysis of the AI treatment parameter. The treatment parameter was tested over two orders of magnitude, and the average area of the active tumor region predicted by the algorithm is shown for each parameter value.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3065055&req=5

fig4: Sensitivity analysis of the AI treatment parameter. The treatment parameter was tested over two orders of magnitude, and the average area of the active tumor region predicted by the algorithm is shown for each parameter value.

Mentions: A sensitivity analysis of the treatment parameter reveals that a bevacizumab-like drug will lead to a significant clinical response at all levels of inhibition tested, although the larger the efficacy of the AI, the more measurable the antitumor activity (Figure 4). In fact, when the most efficacious AI is administered (T1 = 1000), only approximately 1% of the active cell population remaining after eight months of AI treatment are proliferative cancer cells. In other words, this highly efficacious AI has almost entirely reduced the tumor to a mass of hypoxic cells; through this mass does maintain slow growth due to the surviving population of proliferative cells. Whether this level of drug efficacy is clinically achievable is not clear.


Computational modeling of tumor response to vascular-targeting therapies--part I: validation.

Gevertz JL - Comput Math Methods Med (2011)

Sensitivity analysis of the AI treatment parameter. The treatment parameter was tested over two orders of magnitude, and the average area of the active tumor region predicted by the algorithm is shown for each parameter value.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3065055&req=5

fig4: Sensitivity analysis of the AI treatment parameter. The treatment parameter was tested over two orders of magnitude, and the average area of the active tumor region predicted by the algorithm is shown for each parameter value.
Mentions: A sensitivity analysis of the treatment parameter reveals that a bevacizumab-like drug will lead to a significant clinical response at all levels of inhibition tested, although the larger the efficacy of the AI, the more measurable the antitumor activity (Figure 4). In fact, when the most efficacious AI is administered (T1 = 1000), only approximately 1% of the active cell population remaining after eight months of AI treatment are proliferative cancer cells. In other words, this highly efficacious AI has almost entirely reduced the tumor to a mass of hypoxic cells; through this mass does maintain slow growth due to the surviving population of proliferative cells. Whether this level of drug efficacy is clinically achievable is not clear.

Bottom Line: Mathematical modeling techniques have been widely employed to understand how cancer grows, and, more recently, such approaches have been used to understand how cancer can be controlled.In this manuscript, a previously validated hybrid cellular automaton model of tumor growth in a vascularized environment is used to study the antitumor activity of several vascular-targeting compounds of known efficacy.The results presented herein suggest that vascular-targeting agents, as currently administered, cannot lead to cancer eradication, although a highly efficacious agent may lead to long-term cancer control.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics and Statistics, The College of New Jersey, Ewing, NJ 08628-0718, USA. gevertz@tcnj.edu

ABSTRACT
Mathematical modeling techniques have been widely employed to understand how cancer grows, and, more recently, such approaches have been used to understand how cancer can be controlled. In this manuscript, a previously validated hybrid cellular automaton model of tumor growth in a vascularized environment is used to study the antitumor activity of several vascular-targeting compounds of known efficacy. In particular, this model is used to test the antitumor activity of a clinically used angiogenesis inhibitor (both in isolation, and with a cytotoxic chemotherapeutic) and a vascular disrupting agent currently undergoing clinical trial testing. I demonstrate that the mathematical model can make predictions in agreement with preclinical/clinical data and can also be used to gain more insight into these treatment protocols. The results presented herein suggest that vascular-targeting agents, as currently administered, cannot lead to cancer eradication, although a highly efficacious agent may lead to long-term cancer control.

Show MeSH
Related in: MedlinePlus