But understanding the circumstances under which the immune system succeeds or fails to contain a cancer population remains challenging. The intrinsically dynamic nature of the immune system makes it an excellent tool for the host to counter cancer cells. The co-evolutionary arms race therefore occurs within the human body between immune cells and evolving pathogens or transformed cells. Populations of immune cells will change and respond when a pathogen evolves, or when a novel pathogen arises. These receptors are unique for each B or T cell clone and are generated stochastically early in the cell’s development ( 1, 2). Vertebrates employ specialized lymphocytes (B cells and T cells) equipped with diverse recognition receptors (BCR and TCR, respectively). In contrast, even though single-celled pathogens can evolve rapidly relative to their hosts, vertebrate immune systems break a conundrum of ecological and evolutionary time scales. In time, the ash trees may evolve resistance, but this will require decades as new trees grow from seedlings to mature trees. Once infected, mortality rates are near 100% ( 1). For instance, the invasive ash borer beetle has decimated its host, the ash trees of North America. In the co-evolutionary arms race between a pathogen and a host, pathogens often replicate faster, and therefore can evolve and adapt rapidly, while a host cannot. Co-evolution occurs when close interactions between two or more species affect each other’s selective pressures. Like natural food webs, the immune-tumor community of cell types forms an immune-web of different and identifiable interactions.Įvolution is the change in a population’s heritable traits over time subject to selection pressures through population turnover. The immune system is not just predator-prey. Finally, we propose a way forward to reconcile differences between model predictions and empirical observations. Key processes include “safety in numbers”, resource availability, time delays, interference competition, and immunoediting. Here we discuss the applicability of predator-prey models in the context of cancer immunology and evaluate possible causes for discrepancies. Standard predator-prey models can show a perpetual cycling in both prey and predator population sizes, while in oncology we see increases in tumor volume and decreases in infiltrating immune cell populations. The second concerns oscillatory dynamics. In standard predator-prey models, the predator relies on the prey for nutrients, while in the tumor microenvironment the predator and prey compete for resources (e.g. The first concerns the conversion of prey killed into predator biomass. However, two aspects of predator-prey type models are not typically observed in immuno-oncology. It allows for evaluation of tumor cell populations that change over time during immunoediting and it also considers how the immune system changes in response to these alterations. This imperfect analogy describes how immune cells (the predators) hunt and kill immunogenic tumor cells (the prey). Tumor-immune interactions are often framed as predator-prey. 4Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL, United States.3School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland.Lee Moffitt Cancer Center, Tampa, FL, United States 1EMD Serono, Merck KGaA, Billerica, MA, United States.
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