Graduation Year

2026

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Molecular Biosciences

Major Professor

Shari Pilon-Thomas, Ph.D.

Committee Member

Daniel Abate-Daga, Ph.D.

Committee Member

Dorina Avram, Ph.D.

Committee Member

Lawrence L. Stern, Ph.D.

Committee Member

Sungjune Kim, M.D., Ph.D.

Keywords

agent-based modeling, B-cell acute lymphoblastic leukemia, human papillomavirus, radiation therapy, T cell engager therapy, tumor-infiltrating lymphocyte therapy, head and neck squamous cell carcinoma

Abstract

T-cell–based immunotherapies are often constrained by limited trafficking and persistence in tumors and by functional exhaustion under chronic antigen exposure. This dissertation addresses these barriers through two distinct strategies: (i) preclinical studies testing how radiation therapy modulates tumor-infiltrating lymphocytes (TIL) therapy, and (ii) agent based modeling (ABM) to optimize treatment day treatment-free intervals (TFI) in T-cell engager (TCE) therapy. (i) In a human papillomavirus–positive (HPV⁺) head-and-neck cancer (HNC) model, a single local-dose of RT (8 Gy) delivered five days before tumor harvest increased the success and functional quality of ex vivo TIL outgrowth from tumor fragments, enriching polyfunctional CD8⁺ subsets. Delivering the same dose on the day of adoptive cell transfer (ACT) enhanced intratumoral accumulation of antigen-specific adoptively transferred T cells, improved control of both irradiated and shielded tumors, and generated durable tumor memory. (ii) To optimize TCE therapy in a B-cell acute lymphoblastic leukemia (B-ALL) setting, an ABM calibrated to published TCE data reproduced the reported advantage of a 7-day TFI over continuous exposure after 28 days, but showed that this advantage dissipates across a full 42-day clinical treatment cycle. Model-guided exploration of dosing schedules identified shorter, more frequent TFIs as superior for sustaining effector function and tumor control while limiting T cell exhaustion. Together, this work provides experimental and computational insights that may help refine the design of future T-cell–based therapies.

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