Oncolytic virotherapy is an emerging cancer treatment that uses viruses to selectively infect and destroy tumor cells while stimulating immune responses. However, most mathematical models consider either spatial diffusion or intracellular viral delay separately, leaving a gap in understanding their combined influence on tumor dynamics and therapeutic outcomes. In this work, our objective is to...
Oncolytic viruses interact dynamically with cancer cells, healthy stromal cells, and immune cells in the tumor microenvironment. Therapeutic success therefore depends on the balance between viral spread, infection resistance, and immune activation. In this talk, I will present insights into these interactions using a spatiotemporal computational modeling framework. Our simulations reveal that...
Viral infection can substantially alter the selection of mutant cells, particularly in spatially structured settings. Understanding how infection shapes evolutionary dynamics is relevant both for cancer cells targeted by oncolytic viruses and for bacteria subject to bacteriophage infection. While cellular resistance to infection is one important dimension of this problem, I focus here on...
The interactions between oncolytic viruses (OVs) and innate immunity are crucial for the success of oncolytic therapies. Here we focus on a heterogeneous and plastic population of innate immune cells, the tumour-associated macrophages, that can be involved in the elimination of OVs, as well as in the replication of OVs and their spread across tumour tissue. Computational approaches are used to...
Oncolytic virotherapy has emerged as a promising modality for treating solid tumors by exploiting viruses that selectively infect and lyse cancer cells while stimulating antitumor immune responses. Mathematical modeling plays a pivotal role in understanding these multiscale and nonlinear biological dynamics. This minisymposium will focus on recent advances in predictive mathematical and...
