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- Genre: Academic theses
- Creators: Compton, Carolyn
- Creators: Kuang, Yang
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
Efforts to treat prostate cancer have seen an uptick, as the world’s most commoncancer in men continues to have increasing global incidence. Clinically, metastatic
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
ContributorsReckell, Trevor (Author) / Kostelich, Eric (Thesis advisor) / Kuang, Yang (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2020