Matching Items (4)
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- All Subjects: Evolution & development
- Creators: Maley, Carlo C
Description
A notable feature of advanced eusocial insect groups is a division of labor within the sterile worker caste. However, the physiological aspects underlying the differentiation of behavioral phenotypes are poorly understood in one of the most successful social taxa, the ants. By starting to understand the foundations on which social behaviors are built, it also becomes possible to better evaluate hypothetical explanations regarding the mechanisms behind the evolution of insect eusociality, such as the argument that the reproductive regulatory infrastructure of solitary ancestors was co-opted and modified to produce distinct castes. This dissertation provides new information regarding the internal factors that could underlie the division of labor observed in both founding queens and workers of Pogonomyrmex californicus ants, and shows that changes in task performance are correlated with differences in reproductive physiology in both castes. In queens and workers, foraging behavior is linked to elevated levels of the reproductively-associated juvenile hormone (JH), and, in workers, this behavioral change is accompanied by depressed levels of ecdysteroid hormones. In both castes, the transition to foraging is also associated with reduced ovarian activity. Further investigation shows that queens remain behaviorally plastic, even after worker emergence, but the association between JH and behavioral bias remains the same, suggesting that this hormone is an important component of behavioral development in these ants. In addition to these reproductive factors, treatment with an inhibitor of the nutrient-sensing pathway Target of Rapamycin (TOR) also causes queens to become biased towards foraging, suggesting an additional sensory component that could play an important role in division of labor. Overall, this work provides novel identification of the possible regulators behind ant division of labor, and suggests how reproductive physiology could play an important role in the evolution and regulation of non-reproductive social behaviors.
ContributorsDolezal, Adam G (Author) / Amdam, Gro V (Thesis advisor) / Brent, Colin S. (Committee member) / Gadau, Juergen (Committee member) / Hoelldobler, Bert (Committee member) / Liebig, Juergen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Resistance to existing anti-cancer drugs poses a key challenge in the field of medical oncology, in that it results in the tumor not responding to treatment using the same medications to which it responded previously, leading to treatment failure. Adaptive therapy utilizes evolutionary principles of competitive suppression, leveraging competition between drug resistant and drug sensitive cells, to keep the population of drug resistant cells under control, thereby extending time to progression (TTP), relative to standard treatment using maximum tolerated dose (MTD). Development of adaptive therapy protocols is challenging, as it involves many parameters, and the number of parameters increase exponentially for each additional drug. Furthermore, the drugs could have a cytotoxic (killing cells directly), or a cytostatic (inhibiting cell division) mechanism of action, which could affect treatment outcome in important ways. I have implemented hybrid agent-based computational models to investigate adaptive therapy, using either a single drug (cytotoxic or cytostatic), or two drugs (cytotoxic or cytostatic), simulating three different adaptive therapy protocols for treatment using a single drug (dose modulation, intermittent, dose-skipping), and seven different treatment protocols for treatment using two drugs: three dose modulation (DM) protocols (DM Cocktail Tandem, DM Ping-Pong Alternate Every Cycle, DM Ping-Pong on Progression), and four fixed-dose (FD) protocols (FD Cocktail Intermittent, FD Ping-Pong Intermittent, FD Cocktail Dose-Skipping, FD Ping-Pong Dose-Skipping). The results indicate a Goldilocks level of drug exposure to be optimum, with both too little and too much drug having adverse effects. Adaptive therapy works best under conditions of strong cellular competition, such as high fitness costs, high replacement rates, or high turnover. Clonal competition is an important determinant of treatment outcome, and as such treatment using two drugs leads to more favorable outcome than treatment using a single drug. Switching drugs every treatment cycle (ping-pong) protocols work particularly well, as well as cocktail dose modulation, particularly when it is feasible to have a highly sensitive measurement of tumor burden. In general, overtreating seems to have adverse survival outcome, and triggering a treatment vacation, or stopping treatment sooner when the tumor is shrinking seems to work well.
ContributorsSaha, Kaushik (Author) / Maley, Carlo C (Thesis advisor) / Forrest, Stephanie (Committee member) / Anderson, Karen S (Committee member) / Cisneros, Luis H (Committee member) / Arizona State University (Publisher)
Created2023
Description
This review aims to provide a comprehensive review of the most recent literature on adaptive therapy, a promising new approach to cancer treatment that leverages evolutionary theory to prolong tumor control1. By capitalizing on the competition between drug-sensitive and drug-resistant cells, adaptive therapy has led to a paradigm shift in oncology. Through mathematical and in silico models, researchers have examined key factors such as dose timing, cost of resistance, and spatial dynamics in tumor response to adaptive therapy. With a partial focus on preclinical experiments involving ovarian and breast cancer, this review will discuss the demonstrated effectiveness of adaptive therapy in improving progression free survival and tumor control. Through the review process, it was determined that dose modulation outperformed drug-vacation strategies, emphasizing the significance of tumor heterogeneity and spatial structure in accurately modeling adaptive therapy mechanisms. The potential of ongoing clinical trials to improve patient outcomes and long-term treatment efficacy is emphasized, while a thorough analysis of study methodologies shapes the future direction of adaptive therapy research.
ContributorsRichker, Harley (Author) / Maley, Carlo C (Thesis advisor) / Compton, Carolyn (Committee member) / Wilson, Melisaa (Committee member) / Arizona State University (Publisher)
Created2023
Description
Cancer is a disease which can affect all animals across the tree of life. Certain species have undergone natural selection to reduce or prevent cancer. Mechanisms to block cancer may include, among others, a species possessing additional paralogues of tumor suppressor genes, or decreasing the number of oncogenes within their genome. To understand cancer prevention patterns across species, I developed a bioinformatic pipeline to identify copies of 545 known tumor suppressor genes and oncogenes across 63 species of mammals. I used phylogenetic regressions to test for associations between cancer gene copy numbers and a species’ life history. I found a significant association between cancer gene copies and species’ longevity quotient. Additional paralogues of tumor suppressor genes and oncogenes is not solely dependent on body size, but rather the balance between body size and longevity. Additionally, there is a significance association between life history traits and genes that are both germline and somatic tumor suppressor genes. The bioinformatic pipeline identified large tumor suppressor gene and oncogene copy numbers in the naked mole rat (Heterocephalus glaber), armadillo (Dasypus novemcinctus), and the two-fingered sloth (Choloepus hoffmanni). These results suggest that increased paralogues of tumor suppressor genes and oncogenes are these species’ modes of cancer resistance.
ContributorsSchneider-Utaka, Aika Kunigunda (Author) / Maley, Carlo C (Thesis advisor) / Wilson, Melissa A. (Committee member) / Tollis, Marc (Committee member) / Arizona State University (Publisher)
Created2019