In partial fulfillment of the requirements for the degree of
Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences
Erin Connolly
Defended her thesis:
Contributions of Immune Effector Cells to Cancer and Sex-Biased Aging
Wednesday, August 21, 2024
10:00am Eastern
Krone Engineered Biosystems Building (EBB), Room #4029
Thesis advisor:
Dr. Greg Gibson School of Biological Sciences Georgia Institute of Technology
Committee members:
Dr. Zach Buchwald, Department of Radiation Oncology Emory University
Dr. Julia Babensee, Department of Biomedical Engineering Georgia Institute of Technology
Dr. I. King Jordan, School of Biological Sciences Georgia Institute of Technology
Dr. Denis Tsygankov, Department of Biomedical Engineering Georgia Institute of Technology
Abstract:
The immune system, a complex network of cells and molecules, is vital for defending the body against infections, malignancies, and other pathological conditions. Central to this system are immune effector cells, which play crucial roles in recognizing and eliminating pathogens and targeting cancerous cells. Despite their importance, the dynamics of these cells and their interactions with aging, cancer, and therapeutic interventions remain incompletely understood. This thesis aims to advance the understanding of immune effector cell dynamics by leveraging single-cell technologies to explore immune effector cell function and dysfunction in various contexts. To achieve this, we amalgamated publicly available scRNA-seq datasets, encompassing nearly four million cells from 90 studies and 2,606 donors. These comprehensive atlases provided a robust foundation for examining the transcriptional profiles and functional states of immune effector cells across different biological conditions and patient populations. First, we show that aging leads to a significant loss of cellular identity in effector immune cells, with sex-specific differences impacting their functional capabilities. These findings provide insights into the mechanisms driving immunosenescence and evaluate hypotheses that explain the observed patterns of age-related immune decline. Next, we identify a novel effector-stem CD8+ T cell population in tumor-draining lymph nodes, which mediates the synergistic effects of radiation therapy and anti-PD-L1 treatment, offering new avenues for improving cancer immunotherapy. Finally, we map the heterogeneity of plasma cells across various human tissues and cancers, identifying effector-like GZMA+ plasma cells as key players with cytotoxic and immunomodulatory transcriptional signatures, correlating with improved patient survival in certain cancers. These findings underscore the importance of context-specific analyses in understanding plasma cell biology and provide a framework for developing targeted immunotherapies. Overall, this thesis uncovers novel insights into immune effector cell dynamics, paving the way for innovative therapeutic strategies aimed at improving patient outcomes across a range of conditions, from aging-related immune decline to cancer.
Erin Connolly, Bioinformatics Thesis Defense
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