Search bioRxiv⌕ Search

Biology subjects

Yu, A. P.

Publications and source records attributed to Yu, A. P..

2 recordsLinked to original sources

Volumetric mechanoplasticity couples melanoma drug tolerance to susceptibility to CD8+ T cell killing

Cell swelling has been reported in physiological tumor contexts, but whether sustained cell volume expansion leaves a durable state that reshapes drug and immune responses in melanoma is unknown. Using controlled hypotonic dilution as an experimental handle, we compare two priming regimens with comparable hypotonic exposure but different magnitude and persistence of volume expansion, enabling us to test which post-recovery phenotypes track with sustained enlargement beyond hypotonic exposure alone. Sustained enlargement produces a measurable size imprint after return to isotonic conditions, accompanied by nuclear lamina and chromatin remodeling with p53 pathway engagement and suppression of replication and growth programs. After recovery, primed cells reinforce F-actin organization, migrate faster in 3D collagen, and induce antioxidant and anti-ferroptosis defenses consistent with improved stress survival. A gene expression signature derived from this response is associated with poorer outcome in TCGA skin cutaneous melanoma. Unexpectedly, the same volume history also increases IFN-{gamma} response, elevates MHC-I, reduces sialylation, and increases susceptibility to CD8+ T cell killing. These findings indicate that persistent volume history can couple drug tolerance programs to an exploitable increase in immune visibility.

biophysics↗

Optimizing T-cell-mediated cancer killing: An agent-based model

Immunotherapies for cancer aim to improve immune cell function by helping immune cells recognize and kill tumors. A group of immunotherapies target T-cells, aiming to improve the patients prognosis. However, these therapies are not always successful, and the underlying mechanisms of T-cell elimination of tumors remain poorly understood. We developed a three-dimensional agent-based model to explore this behavior that probabilistically models cell growth, migration and interaction parameters. Through this project, we explore the influence of cytokines like IL-2 and CCL2 on T-cell behavior and optimize the interactions between T-cells and cancer cells to most efficiently kill tumors using modeling. How individual parameters such as T-cell killing rate, proliferation, infiltration and cytotoxicity is still largely unexplored, and our study aims to fill that gap by stochastically simulating T-cells as they attack a cancer spheroid in order to identify new potential strategies to enhance T-cell killing of tumors. Our study found that, from greatest to least effect, increasing the killing, proliferation, and infiltration rate of T-cells increased the clearance rate of the tumor. A 17% increase in killing rate was enough to control and shrink the tumor, while a 15% increase in their proliferation rate was sufficient to control the tumor without regressing it; a 30% increase in their proliferation rate was sufficient to shrink the tumor. Increasing the infiltration was only able to control the tumor, not cause it to regress.

cancer biology↗