Resource Consumption, Sustainability, and Cancer

Abstract

Preserving a system's viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter-or intraspecies, may increase population fragility, either decreasing its ability to adapt e ectively to environmental changes or facilitating the survival and success of ordinarily rare phenotypes. The latter may result in over-representation of individuals who may participate in resource utilization patterns that can lead to over-exploitation, exhaustion, and, ultimately, collapse of both the resource and the population that depends on it. Here, we aim to identify regimes that can signal whether a consumer-resource system is capable of supporting viable degrees of heterogeneity. The framework used here is an expansion of a previously introduced consumer-resource type system of a population of individuals classi ed by their resource consumption. Application of the Reduction Theorem to the system enables us to evaluate the health of the system through tracking both the mean value of the parameter of resource (over)consumption, and the population variance, as both change over time. The article concludes with a discussion that highlights applicability of the proposed system to investigation of systems that are a ected by particularly devastating overly-adapted populations, namely, cancerous cells. Potential intervention approaches for system management are discussed in the context of cancer therapies.

Eco‐oncology: Applying ecological principles to understand and manage cancer

“…The recognition that cancer is a complex, evolving ecological system has led to Darwinian approaches to understanding and treating this disease (Crespi & Summers, 2005, 2006; Greaves, 2007, 2013; Merlo et al, 2006). This manner of thinking has inspired physicians and scientists to consider alternatives to the standard of care treatment regimens based on the maximum dosage of chemotherapy that a patient can tolerate [referred to as maximum tolerated dose (MTD] (Kareva, Morin, & Castillo‐Chavez, 2015; Kareva, Waxman, et al, 2015). For example, metronomic therapy is characterized by the administration of cytotoxic drugs and therapies at lower but more frequent doses (Fidler et al, 2000; Hanahan & Weinberg, 2000, 2011; Kareva, Morin, et al, 2015; Kareva, Waxman, et al, 2015; Scharovsky, Mainetti, & Rozados, 2009).…”

“…This manner of thinking has inspired physicians and scientists to consider alternatives to the standard of care treatment regimens based on the maximum dosage of chemotherapy that a patient can tolerate [referred to as maximum tolerated dose (MTD] (Kareva, Morin, & Castillo‐Chavez, 2015; Kareva, Waxman, et al, 2015). For example, metronomic therapy is characterized by the administration of cytotoxic drugs and therapies at lower but more frequent doses (Fidler et al, 2000; Hanahan & Weinberg, 2000, 2011; Kareva, Morin, et al, 2015; Kareva, Waxman, et al, 2015; Scharovsky, Mainetti, & Rozados, 2009). This approach focuses on minimizing the toxic effect on patients, reducing the selection pressure for the therapy‐resistant cancer cell phenotypes, and can modify the tumor niche to reduce angiogenesis, vasculogenesis and may even stimulate the immune response.…”

Learning about the Importance of Mutation Prevention from Curable Cancers and Benign Tumors

“…Cancer cells not only collaborate with each other as abovementioned but also compete with each other for resources 49 ; 50 , which may be due to, and is also one reason for, the intra-tumor heterogeneity 10 ; 11 ; 51 ; 52 . From the viewpoint of cell-autonomy, invasive and metastatic cells are considered stronger than the others because they are more aggressive and perverse.…”

Pools versus Queues: The Variable Dynamics of Stochastic “Steady States”

“…The second form of stochastic extinction, which is possible with either form of stability, is the extinction of one of several compartments or subpopulations within the model without the extinction of the entire model population. This phenomenon, which I term C-extinction, is less dramatic but may be of central interest to many research questions[ 8 – 12 ]. For example, the vast majority of epidemiological models are more concerned with the population of infected individuals within a model than with the state of the modeled population as a whole[ 13 ].…”