Modelling oncolytic virus diffusion in collagen-dense tumours

Abstract

Solid tumours develop much like a fortress, acquiring characteristics that protect them against invasion. A common trait observed in solid tumours is the synthesis of excess collagen which traps therapeutic agents, resulting in a lack of dispersion of treatment within the tumour mass. In most tumours, this results in only a localised treatment. Often the tumour quickly recovers and continues to invade surrounding regions. Anti-tumour viral therapy is no exception to this rule. Experimental results show collagen density affects virus diffusion and inhibits cell infection; therefore, accurately modelling virus dispersion is an important aspect of modelling virotherapy. To understand the underlying dynamics of viral diffusion in collagen, we derive a novel non-Fickian diffusion term from first principles. We demonstrate that this diffusion term captures experimentally observed virus dispersion in cancer-associated collagen, unlike the standard diffusion term, commonly used in virotherapy models. Then, using a system of partial differential equations, we explore virotherapy in relation to collagen density. We show that our model can predict therapy outcome in relation to collagen density. The results also suggest that modifications in virus performance, such as increased virus infectivity, is not effective in dense collagen; therefore, reducing collagen, might be the best approach when dealing with collagen-rich tumours. We also investigate virotherapy in relation to collagen structures and find that size of collagen deposits are as important to outcome as collagen density. Together, these results demonstrate that understanding virus diffusion in oncolytic virotherapy is a crucial step in capturing tumour response to treatment.