Functional characterization and multi-factor analysis of exhaustion in chronic lymphocytic leukemia T cells
By: Joanne Haeun Lee
Publisher: [publisher not identified]
Published: 2021
Place of publication: [New York, N.Y.?]
Language: eng
Description: Adequate cell production for adoptive cell transfer therapies such as Chimeric Antigen Receptor (CAR)-T cell therapy remains a critical barrier to treatment for indications that fail to achieve clinical success. One such disease is Chronic Lymphocytic Leukemia (CLL), a B-cell lymphoma with their characteristically exhausted T cells, marked by a progressive loss of the ability to secrete cytokines and proliferate, as well as an increase in the expression of checkpoint inhibitor molecules such as PD-1. The goal of this thesis is to characterize the functional differences or specific biomarkers within the CLL patient population that is indicative of the proliferation outcomes. Conventional clinical markers such as Rai stage or PD-1 expression alone were inadequate to describe the complex variability among patients. In order to better characterize exhaustion using microscopy-based cell function assays, we developed a sample sparing microscopy chamber that requires as little as 1000 cells per sample.

The microscopy chambers were mass produced via injection molding, and made compatible with the antibody microcontact printing technique developed in the Kam lab. The chambers typically reduced cell usage per experiment by 20-fold. This reduction allowed us to measure IL-2 secretion, T cell arrest response to activating antibody patterns (pattern alignment), and motility of scarce human samples simultaneously from a single experiment. Results from these functional readouts along with other clinical markers were used as inputs for a multifactor exploratory analysis to cluster patients according to their functional similarities from the combination of responses in an unbiased manner. The resulting clusters based on the combination of the top 3 parameters IL-2, pattern alignment, and PD-1 resulted in better separation of patient groups and provided a basis for predicting max doubling outcomes from these inputs. We further used motility measurements as a way to understand initial T cell response to activation before the stop response, which was measured as pattern alignment previously.

The time it takes for cells to come to a stop at the signal was most informative for translating T cell activation response to a stop response, and eventually to downstream effector functions of cytokine secretion and proliferation. The results of this work provide a powerful framework to describe different donors, and can be applied to cells from additional donors to guide future cell expansion studies.
Notes: Department: Biomedical Engineering.

Thesis advisor: Lance C. Kam.

Thesis (Ph.D.)--Columbia University, 2021.