Math Modeling Seminar: Towards Optimization of Monoclonal Antibody Therapeutics Using a 3D Model of Cancer-Immune Interaction

Math Modeling Seminar
Towards Optimization of Monoclonal Antibody Therapeutics Using a 3D Model of Cancer-Immune Interaction

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Dr. Jordana O’Brien
Postdoctoral Associate
University at Buffalo

Abstract:
T cell exhaustion is a dysfunctional state that develops after prolonged antigen exposure, in which T cells progressively lose their ability to proliferate, secrete cytokines, and eliminate malignant cells. A hallmark of exhaustion is the sustained expression of inhibitory receptors, including Programmed Cell Death protein 1 (PD-1) and Cytotoxic T-Lymphocyte Associated protein 4 (CTLA-4), which transmit suppressive signals that limit immune activity. Cancer cells exploit these regulatory pathways by upregulating inhibitory receptor ligands on their surface, further driving the exhausted phenotype. Furthermore, recent studies indicate that the 24 hour period after initial antigen exposure is a critical window in the determination of T cell fate. Monoclonal therapeutic antibodies (mAbs) that target inhibitory receptors boost immune function by disrupting suppressive signaling pathways and have been shown to aid in the recovery of cytotoxic function. In this project, we explore trajectories of early phase T cell exhaustion and the impact of immune checkpoint intervention within the first 12 hours of antigen exposure. To do so, we construct a multiscale, off-lattice 3D model of the tumor microenvironment (TME). This framework couples an agent-based model of cell–cell interactions with a reaction–diffusion model for antibody transport and infiltration. Cell motility is modeled through intermolecular forces based on a combined Hertz/Lennard-Jones potential, and T cell chemotaxis is characterized by a prescribed cytokine signaling function. In the current model iteration, we consider αPD-1 mAbs, which bind to PD-1 on T cells and block the PD-1/PD-L1 pathway, thereby limiting exhaustion. Our model tracks both exhausting interactions between cancer and effector T cells and the infiltration capacity of T cells into the TME. We assess parameter sensitivity by computing first-order and total-order Sobol indices. We highlight key factors that influence T cell migration and progression into an exhaustive state. Our analysis provides insights into how microenvironmental and therapeutic parameters influence T cell function and may inform future modeling strategies for immunotherapy optimization.

Speaker Bio:
Jordana is a first year post doctoral researcher in the Talkington Lab at the University at Buffalo. She received her PhD in mathematical modeling from the Rochester Institute of Technology, where she conducted her dissertation on the modeling of pulmonary drug transport and delivery. She dabbled in PKPD modeling as a summer intern at Merck, and she worked for three years as a student researcher at Los Alamos National Lab while completing her degree. Aside from mathing, she enjoys pole dancing, creating art, planning her next trip, and dance parties with her nine year old daughter.

Intended Audience:
Beginners, undergraduates, graduates. Those with interest in the topic.

Interpreters have been requested.