Date of Graduation

5-2025

Document Type

Thesis

Degree Name

Bachelor of Science in Biology

Degree Level

Undergraduate

Department

Biological Sciences

Advisor/Mentor

Dr. Leonard Harris

Committee Member

J.D. Willson

Second Committee Member

Jennifer Mortensen

Third Committee Member

Jeffrey A Gruenewald

Abstract

Ferroptosis is an iron-dependent, reactive oxygen species (ROS)-driven form of regulated cell death in which the cell membrane is degraded by lipid peroxidation. It is regulated by multiple enzymes, such as glutathione peroxidase 4 (GPX4), which prevents membrane degradation by reducing lipid peroxides and protecting cells from oxidative damage. When inhibitors like RSL3 target GPX4, lipid peroxides build up, and toxic ROS compromises membrane integrity. Traditional anticancer treatments, such as most chemotherapies, aim to eliminate tumor cells by damaging DNA and triggering apoptosis. However, resistance to apoptosis is a “hallmark of cancer,” often resulting in treatment failure. As a distinct form of programmed cell death, ferroptosis offers an alternative to traditional genotoxic treatment strategies. In this project, a mechanistic model of the ferroptosis pathway is developed to gain insights into molecular drivers and identify novel targets for enhancing ferroptosis activation. The model is constructed in PySB, a Python-based modeling and simulation platform for complex biological systems. Using PyDREAM, a Bayesian parameter estimation tool, the model is calibrated to experimental dose-response data from two cancer cell lines exposed to the ferroptosis inducer erastin. Parameter distributions generated by PyDREAM are compared against each other and reveal that differences associated with System Xc⁻, the cystine-glutamate antiporter, explain disparate drug responses between the two cell lines, i.e., System Xc⁻ is a potential target for modifying sensitivity to ferroptosis in these cells. Future research will focus on performing similar analyses for additional cell lines and utilizing time-course data with absolute (rather than relative) molecular concentrations. The model will also be expanded to include additional molecular components and models of related processes, like mitochondrial metabolism, enhancing its predictive power.

Keywords

Ferroptosis; Computational Modeling; Drug-Tolerant Cancer Cells; System Xc⁻; PySB; PyDREAM

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