  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 release of new viruses in the tissue after
cell lysis. The evolution in time of both 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 depends critically on the tumor growth dynamics
and do not necessarily include rapid replication, cytolysis and spreading
currently assumed as necessary conditions to a successful therapeutic outcome.
Our findings have potential implications on the design of new vectors for the
viral therapy of cancer.
