Date of Award
2023
Degree Type
Thesis
Degree Name
Master of Science in Biological and Environmental Sciences (MSBES)
Specialization
Cell and Molecular Biology
Department
Cell & Molecular Biology
First Advisor
Gongqin Sun
Abstract
Protein kinase inhibitors have been an effective treatment for cancers driven by an identifiable predominant protein kinase that drives cancer development. Most cancers, however, are supported by multiple independent drivers and cannot be effectively treated by targeted therapies that inhibits only a single driver. Instead, a combination targeted therapy with multiple targeted drugs to block all drivers is required. Developing combination targeted therapies for such cancers requires identification of the individual drivers and pharmacological understanding of the complex interactions between the drugs and the cancer targets. The current pharmacological models, based on the Hill equation, only describe the interaction between a drug and a single target in a biological system. Thereby, any observed effect is ascribed to the interaction with one target only. In practice, such drugs often inhibit multiple kinase targets, both on and off-target, and the resulting inhibition will be a compound of the effectiveness against all affected targets. Yet when such drugs are used for cancer therapy, only the target-specific inhibition is likely responsible for efficacy, while the off-target inhibition is likely the cause of toxicity. This perspective article discusses a recently developed biphasic pharmacological model for characterizing such complex interactions, assessing the contribution of individual drug targets, and predicting synergistic drug combinations for multi-driver cancers. This approach can produce mechanism-based and synergistic drug combinations against multi-driver cancers.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Recommended Citation
Yonchak, Alexander, "DEVELOPMENT OF TARGETED DRUG COMBINATIONS BLOCKING MULTI-DRIVER ONCOGENESIS" (2023). Open Access Master's Theses. Paper 2339.
https://digitalcommons.uri.edu/theses/2339