Modelling the ageing dependence of cancer evolutionary trajectories

Abstract

Ageing is the single most important prognostic factor for cancer development. Despite this knowledge, experimental models of cancer have historically omitted incorporating the impact of age on cancer initiation, progression and treatment outcomes. Ageing interacts with other lifestyle factors, including cigarette smoking, obesity and physical activity, but these intersections are rarely studied in experimental models. Given that cancer-related mortality rates increase with age, there is a growing emphasis on modelling ageing-associated mutational and microenvironmental changes in cancer research. In this Review, we provide guidance on the technological advancements and experimental strategies that have increased our ability to model how ageing impacts various stages of cancer evolution, from mutation-driven clonal expansions, to pre-malignant lesions, and then to progression to more malignant phenotypes and metastasis, and responses to therapies. We discuss the benefits and limitations of methods and models used. The wider adoption of age-appropriate models of cancer will enable the development of improved approaches for the detection, prevention and therapeutic intervention of human cancers.