A mathematical model of tumor-immune interactions following oncogene inactivation

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The genesis of a wide variety of cancers is the expression of an oncogene, a damaged gene that can drive malignant tumor growth. Molecularly targeted therapy can inactivate the oncogene, which has been shown in many cases to lead to tumor regression. However, in many patients, there is tumor recurrence where the tumor becomes resistant to the targeted therapy. Understanding the complex interactions of the tumor's multi-faceted response to oncogene inactivation is key to tumor regression. The mathematical model that I have developed captures the cellular mechanisms that determine whether or not tumors recur, leading to directed hypotheses about how to design more effective therapeutic regimens. This novel model integrates different mathematical frameworks including differential equations and Galton-Watson branching processes in order to capture the stochastic fluctuation in subclonal populations of tumor cells. My work simultaneously incorporates multiple cellular fates for tumor cells and immune-mediated responses critical in determining tumor recurrence. This approach builds upon established theoretical models and adds newly established biological mechanisms of tumor physiology and the immune system specific to oncogene inactivation. My mathematical model will allow prediction and optimization of various therapeutic strategies that improve outcomes in cancer patients.


Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2014
Issuance monographic
Language English


Associated with Nwabugwu, Chinyere Ifeoma
Associated with Stanford University, Department of Electrical Engineering.
Primary advisor Paik, David
Thesis advisor Paik, David
Thesis advisor Gill, John T III
Thesis advisor Pauly, John (John M.)
Advisor Gill, John T III
Advisor Pauly, John (John M.)


Genre Theses

Bibliographic information

Statement of responsibility Chinyere Ifeoma Nwabugwu.
Note Submitted to the Department of Electrical Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2014.
Location electronic resource

Access conditions

© 2014 by Chinyere Ifeoma Nwabugwu
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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