The advancement of cancer immunotherapy, especially in the manipulation of NK cells, holds promise for targeted cancer treatment. NK cell effectiveness is currently assessed using cell populations in cytotoxicity assays, but these lack the details to observe individual cellular behaviours in real time. Droplet-based microfluidics is emerging as a solution to address these limitations by allowing the encapsulation of cells at specific ratios in controlled microenvironments. This advancement enhances the accuracy of immunotherapeutic assessments by providing a more detailed understanding of cellular interactions.
In our study, we employed droplet microfluidics to encapsulate and analyze the interactions between NK cells and K562 cancer cells at predetermined effector-to-target (E:T) ratios. Each droplet served as an isolated microreactor, where individual NK cell interactions with cancer cells could be monitored in real-time. The results of our study revealed that droplet-based microfluidics provide detailed insights into the differential cytotoxic capacities of primary (Pri), suppressed (Supp), expanded (Exp), and post-expansion suppressed (PES) NK cells. Notably, expanded NK cells exhibited not only higher cytotoxic activity at a faster rate but also greater serial killing capabilities across different donors and varying E:T ratios, indicating their potential for effective immunotherapy. Additionally, suppressed NK cells showed reduced cytotoxic abilities, emphasizing the importance of overcoming the suppressive factors within the tumour microenvironment. These findings are pivotal for the field of immunotherapy and hold promising implications for the selection and optimization of NK cell-based treatments tailored to individual patient needs. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/30389 |
| Date | 11 1900 |
| Creators | Ozcan, Rana S. |
| Contributors | Didar, Tohid, Biomedical Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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