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Data from A Multiscale Mathematical Model for Oncolytic Virotherapy

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<div>Abstract<p>One of the most promising strategies to treat cancer is attacking it with viruses. Oncolytic viruses can kill tumor cells specifically or induce anticancer immune response. A multiscale model for virotherapy of cancer is investigated through simulations. It was found that, for intratumoral virus administration, a solid tumor can be completely eradicated or keep growing after a transient remission. Furthermore, the model reveals undamped oscillatory dynamics of tumor cells and virus populations, which demands new <i>in vivo</i> and <i>in vitro</i> quantitative experiments aiming to detect this oscillatory response. The conditions for which each one of the different tumor responses dominates, as well as the occurrence probabilities for the other nondominant therapeutic outcomes, were determined. From a clinical point of view, our findings indicate that a successful, single agent virotherapy requires a strong inhibition of the host immune response and the use of potent virus species with a high intratumoral mobility. Moreover, due to the discrete and stochastic nature of cells and their responses, an optimal range for viral cytotoxicity is predicted because the virotherapy fails if the oncolytic virus demands either a too short or a very large time to kill the tumor cell. This result suggests that the search for viruses able to destroy tumor cells very fast does not necessarily lead to a more effective control of tumor growth. [Cancer Res 2009;69(3):1205–11]</p></div>
Title: Data from A Multiscale Mathematical Model for Oncolytic Virotherapy
Description:
<div>Abstract<p>One of the most promising strategies to treat cancer is attacking it with viruses.
Oncolytic viruses can kill tumor cells specifically or induce anticancer immune response.
A multiscale model for virotherapy of cancer is investigated through simulations.
It was found that, for intratumoral virus administration, a solid tumor can be completely eradicated or keep growing after a transient remission.
Furthermore, the model reveals undamped oscillatory dynamics of tumor cells and virus populations, which demands new <i>in vivo</i> and <i>in vitro</i> quantitative experiments aiming to detect this oscillatory response.
The conditions for which each one of the different tumor responses dominates, as well as the occurrence probabilities for the other nondominant therapeutic outcomes, were determined.
From a clinical point of view, our findings indicate that a successful, single agent virotherapy requires a strong inhibition of the host immune response and the use of potent virus species with a high intratumoral mobility.
Moreover, due to the discrete and stochastic nature of cells and their responses, an optimal range for viral cytotoxicity is predicted because the virotherapy fails if the oncolytic virus demands either a too short or a very large time to kill the tumor cell.
This result suggests that the search for viruses able to destroy tumor cells very fast does not necessarily lead to a more effective control of tumor growth.
[Cancer Res 2009;69(3):1205–11]</p></div>.

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