Physics

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 in vivo and in vitro 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.

Life, amazingly rich in diversity of shapes and functions, explores the limits of extreme complexity in nature. In this review we shall discuss in general terms the use of multiscale mathematical and computer models to study the dynamics of biological systems. These models permit integration of the rapidly expanding knowledge concerning the molecular basis of biology and its complex, nonlinear

One of the most promising strategies to treat cancer is attacking it with viruses designed to exploit specific altered pathways. Here, the effects of oncolytic virotherapy on tumors having compact, papillary, and disconnected morphologies are investigated through computer simulations of a multiscale model coupling macroscopic reaction-diffusion equations for the nutrients with microscopic stochastic rules for the actions of individual cells and viruses. The interaction among viruses and tumor cells involves cell infection, intracellular virus replication, and the release of new viruses in the tissue after cell lysis. The evolution over time of both the viral load and cancer cell population, as well as the probabilities for tumor eradication, were evaluated for a range of multiplicities of infection, viral entries, and burst sizes. It was found that in immunosuppressed hosts, the antitumor efficacy of a virus is primarily determined by its entry efficiency, its replicative capacity within the tumor, and its ability to spread over the tissue. However, the optimal traits for oncolytic viruses depend critically on the tumor growth dynamics and do not necessarily include rapid replication, cytolysis, or spreading, currently assumed as necessary conditions for a successful therapeutic outcome. Our findings have potential implications on the design of new vectors for the viral therapy of cancer.