cWe are developing oncolytic vesicular stomatitis viruses (VSVs) for systemic treatment of multiple myeloma, an incurable malignancy of antibody-secreting plasma cells that are specifically localized in the bone marrow. One of the presumed advantages for using VSV as an oncolytic virus is that human infections are rare and preexisting anti-VSV immunity is typically lacking in cancer patients, which is very important for clinical success. However, our studies show that nonimmune human and mouse serum can neutralize clinical-grade VSV, reducing the titer by up to 4 log units in 60 min. In addition, we show that neutralizing anti-VSV antibodies negate the antitumor efficacy of VSV, a concern for repeat VSV administration. We have investigated the potential use of covalent modification of VSV with polyethylene glycol (PEG) or a function-spacer-lipid (FSL)-PEG construct to inhibit serum neutralization and to limit hepatosplenic sequestration of systemically delivered VSV. We report that in mice passively immunized with neutralizing anti-VSV antibodies, PEGylation of VSV improved the persistence of VSV in the blood circulation, maintaining a more than 1-log-unit increase in VSV genome copies for up to 1 h compared to the genome copy numbers for the non-PEGylated virus, which was mostly cleared within 10 min after intravenous injection. We are currently investigating if this increase in PEGylated VSV circulating half-life can translate to increased virus delivery and better efficacy in mouse models of multiple myeloma.
Simple, inductive mathematical models of oncolytic virotherapy are needed to guide protocol design and improve treatment outcomes. Analysis of plasmacytomas regressing after a single intravenous dose of oncolytic vesicular stomatitis virus in myeloma animal models revealed that intratumoral virus spread was spatially constrained, occurring almost exclusively through radial expansion of randomly distributed infectious centers. From these experimental observations we developed a simple model to calculate the probability of survival for any cell within a treated tumor. The model predicted that small changes to the density of initially infected cells or to the average maximum radius of infected centers would have a major impact on treatment outcome, and this was confirmed experimentally. The new model provides a useful and flexible tool for virotherapy protocol optimization.
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