Modeling cancer’s ecological and evolutionary dynamics

Abstract

In this didactic paper, we present a theoretical modeling framework, called the G-function, that integrates both the ecology and evolution of cancer to understand oncogenesis. The G-function has been used in evolutionary ecology, but has not been widely applied to problems in cancer. Here, we build the G-function framework from fundamental Darwinian principles and discuss how cancer can be seen through the lens of ecology, evolution, and game theory. We begin with a simple model of cancer growth and add on components of cancer cell competition and drug resistance. To aid in exploration of eco-evolutionary modeling with this approach, we also present a user-friendly software tool. By the end of this paper, we hope that readers will be able to construct basic G function models and grasp the usefulness of the framework to understand the games cancer plays in a biologically mechanistic fashion.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

“…Evolutionary theories of tumor growth typically focus on tumor cells themselves; however, the tumor microenvironment (TME) is being increasingly recognized for its capacity to influence tumor progression and response to therapy. As such, it is necessary to view tumors from an ecological perspective to better understand the evolutionary dynamics that drive intratumoral heterogeneity and permit tumor progression ( Figure 1 ) ( Boddy, 2022 ; Bukkuri et al, 2023 ).…”

“…These different cells play an important role in tumor progression via their interactions with one another ( Zarrilli et al, 2020 ). Such communication provides selective pressures that modulate expression of those genes associated with the cancer hallmarks thereby facilitating tumor evolution strategies that drive cellular plasticity and tumor heterogeneity by permitting adaptations that enhance fitness ( Bechtel, 2019 ; Bukkuri et al, 2023 ). Ultimately this affects tumor cell phenotypic changes and mediates interactions with cells of the TME ( Zarrilli et al, 2020 ; Nagy et al, 2021 ; Danenberg et al, 2022 ).…”

“…The ability to identify the molecular underpinnings of a tumor allows for precise targeting to increase the chances of effectiveness and mitigate some adverse effects and collateral tissue damage that may influence recurrence or resistance to treatment. We propose that for more effective therapy, consideration must be given to the concept of speciation in cancer, whereby the generation of distinct clones predicated on the initial capacity of transformed cells to adapt to microenvironmental stressors or evolvability, leads to a heterogenous mass with clones that may either have an intrinsic resistance or develop an adaptive resistance, to therapies ( Pienta et al, 2020 ; Bukkuri et al, 2023 ). Moreover, in the context of the TME, while therapies may target specific tumor-related antigens, few therapeutic regimens exist that would prevent evolutionary rescue of the ‘cells left behind’ that ultimately drive recurrence and resistance.…”

“…Within the TME, tumors generate clones under selective pressures that enhance their capacity to thrive and change their ecological niche in the TME. These ecological niches are also spatiotemporally defined, permitting clones to adapt the TME landscape to enable invasion and metastasis as they acquire more aggressive phenotypes ( Bechtel, 2019 ; Bukkuri et al, 2023 ). This may reflect the accumulation of gradual microevolutionary changes or larger shifts that account for macroevolutionary changes, which while controversial in their mechanism ( Gerlinger et al, 2014 ), nevertheless result in intratumoral heterogeneity that highlights the evolvability and adaptability of tumors.…”

“…This may reflect the accumulation of gradual microevolutionary changes or larger shifts that account for macroevolutionary changes, which while controversial in their mechanism ( Gerlinger et al, 2014 ), nevertheless result in intratumoral heterogeneity that highlights the evolvability and adaptability of tumors. This potentially accounts for poor response to treatment, resistance and recurrence ( Gallaher et al, 2019 ; Lei, 2020 ; Boddy, 2022 ; Bukkuri et al, 2023 ). In this review, we will first revisit breast tumor subtypes that describe intertumoral heterogeneity and are affected by spatiotemporal dynamics that underlie acquisition of more aggressive phenotypes.…”