Within- and between-host evolutionary effects on viral oncogenicity

Journal article

Cancer-inducing viruses (oncogenic viruses) are linked to over 10% of cancer cases. Although the molecular details of viral oncogenesis are well-documented, the evolutionary mechanisms by which viruses have acquired oncogenic properties remain poorly understood. Here, we investigate the evolutionary conditions affecting viral oncogenicity across both within- and between-host scales using mathematical models of oncovirus–immune system interactions, conceptualized as an extended shared enemy–victim relationship. We begin by examining how oncogenic traits impact within-host viral dynamics, focusing on the transformation rate of infected cells into pre-cancerous states and the pre-cancerous cell proliferation rate. In various scenarios reflecting different within-host conditions, we then identify the transformation and proliferation rates that maximize within- and between-host viral fitness. We find that the transformation rate maximizing the viral load depends on the viral production rate, immunogenicity, and the immune-mediated elimination rate of pre-cancerous cells. We also identify conditions under which an intermediate proliferation rate minimizes within- and between-host viral fitness: in that scenario, a lower or higher proliferation rate leads to a higher viral load, providing a possible explanation for the diversity of oncogenic viruses. The analyses presented here provide insights into the evolutionary drivers affecting viral oncogenicity and highlight the complexity of oncogenic virus–immune system interactions.

Authors: Koizumi, Y; Bonsall, MB

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: Virus Evolution
• Volume: 11
• Issue: 1
• Article number: veaf043
• Publication date: 2025-06-06
• Acceptance date: 2025-06-05
• DOI: 10.1093/ve/veaf043
• EISSN: 2057-1577
• Language: English
• Keywords: oncovirus; virus dynamics; mathematical modelling; apparent competition; fitness landscape; nested model