From Oncogenesis to Immunotherapy: Mathematical Modeling of Heterogeneous Cancers

We utilize mathematical modeling to study two types of cancer with substantial mutational heterogeneity: chronic lymphocytic leukemia (CLL) and mismatch-repair deficient colorectal cancer (MMR-D CRC). First, to study the progression of CLL into an aggressive lymphoma, Richter’s Syndrome (RS), we analyze data from a recent mouse model and utilize a Bayesian modeling approach to show that growth patterns present in human disease are recapitulated in murine CLL/RS. Next, we use a stochastic branching process model to simulate the acquisition of tumor-specific neoantigens in MMR-D CRC. By using these in-silico tumors as initial conditions in a dynamical systems model of tumor-immune interactions, parameterized using clinical trial data, we characterize features associated with a durable response to immune checkpoint inhibitor (ICI) immunotherapy in MMR-D CRC.

Author dc:creator

• Sholokhova, Alanna Pauline

Advisor dc:contributor.advisor

• Bozic, Ivana

• cancer
• clonal evolution
• dynamical systems
• immunotherapy
• mathematical oncology
• stochastic processes
• Applied mathematics
• Biology
• Medicine

Statement dc:rights

• none

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/1773/55130

OAI identifier oai:identifier

oai:digital.lib.washington.edu:1773/55130