Abstract SY36-02: Exploiting evolutionary dynamics in optimizing cancer treatment

Abstract

Abstract Evolution by natural selection is the result of environmental properties interacting with heritable phenotypic properties within a population in ways that determine the proliferation of each individual. In tumors, the fittest cancer cells survive and proliferate at the expense of those less-fit, but each cell’s fitness is entirely determined by the environmental context and can change rapidly in temporally varying conditions. This contextual dependence is perhaps most evident in cancer treatment. Here, the addition of treatment agents can cause a step-wise change in fitness in which the dominant (and, therefore, fittest) cell populations dies rapidly. On the other hand, rare individuals (and, therefore, previously less-fit than the dominant population) that have properties conferring resistance to treatment can suddenly become the fittest and most proliferative phenotype within the context of environmental selection pressures that include therapy. Although most metastatic cancers now have at least one effective therapy, evolution of resistance almost invariably leads to treatment failure and patient death. Investigating tumor progression during treatment has generally focused on defining the molecular machinery that permits resistance. While often viewed as the result of a “resistance mutation,” many adaptive strategies simply involve increased expression of genes (e.g. xenobiotic metabolism) already in the human genome. Furthermore, clinical treatments to block the resistance mechanism (e.g. the MDR proteins) have generally been unsuccessful reflecting the multiplicity of available strategies. In an evolutionary context, however, the mere presence of a resistant phenotype is not sufficient for treatment failure. Rather, tumor progression requires proliferation of the resistant phenotype at a rate sufficient to produce the billions of cells necessary for clinically evident progressive disease. Importantly, the necessary molecular, cellular, and population dynamics necessary for cancer progression during treatment are deeply connected because there are often significant phenotypic costs from synthesis, maintenance, and operation of the molecular machinery of resistance that can reduce cellular proliferation and invasion particularly in the substrate-poor environment often present in clinical cancers. Evolution-based cancer treatment assumes that resistant phenotypes are invariably present prior to initiation of therapy and seeks to exploit evolutionary dynamics to delay or prevent proliferation of these cells. A specific example of this approach is adaptive therapy which is used in clinical settings in which cure is not achievable. Similar to widely accepted practices in pest management, adaptive therapy reduces or periodically withdraws treatment to maintain a stable population of treatment-sensitive cells that can use their fitness advantage (i.e. absence of the cost of resistance) to suppress proliferation of resistant phenotypes. This approach has been investigated in both pre-clinical and clinical conditions. An ongoing clinical trial in metastatic castrate-resistant prostate cancer will be discussed. Finally, when cure from a cancer treatment is possible but rare, evolutionary dynamics, based on observations in background extinctions, can theoretically be used to increase the probability of complete eradication of the malignant population. Citation Format: Robert A. Gatenby. Exploiting evolutionary dynamics in optimizing cancer treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr SY36-02.