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    Single Cell Tracking of Breast Cancer Cells Removes Aggregation and Allows Prediction of Sphere Formation Using Information From Early Cell Divisions

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    Author
    Bailey, Patrick Christian
    Advisor
    Martin, Stuart S.
    Date
    2019
    Type
    dissertation
    
    Metadata
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    Abstract
    The mammosphere assay has become widely employed to quantify stem-like cells in a population. Problematically, there is no standard protocol employed by the field. Cell seeding densities of 1000 to 100,000 cells/mL have been reported. These high densities lead to cellular aggregation. To address this, we have individually tracked 1,127 single MCF-7 and 696 single T47D human breast tumor cells over the course of 14 days. This tracking has given us detailed information for the commonly used endpoints of 5, 7 and 14 days that is unclouded by cellular aggregation. This includes mean sphere sizes, sphere forming efficiencies and a well-defined minimum size for both lines. Importantly, we have correlated early cell division with eventual sphere formation. At 24 hours post seeding, we can predict total spheres on day 14 with 98% accuracy in both lines. This approach removes cell aggregation and potentially shortens a 5-14 day assay to 24 hours. To increase the throughput of the assay while still addressing the effects of aggregation, we incorporated a technology that uses lipid tethering on a low attach surface. Tethering individual tumor cells to lipid anchors prevents cell drift while maintaining free-floating characteristics. This enables real-time monitoring of single tumor cells as they divide to form mammospheres. We observed that Day 7 spheres in lipid-coated wells contained significantly more clonal spheres than traditional low attachment plates. These results indicate that using lipid tethering for mammosphere growth assays can reduce the confounding factor of cell aggregation and increase the formation of clonal mammospheres.
    Description
    2019
    Biochemistry
    University of Maryland, Baltimore
    Ph.D.
    Keyword
    Molecular biology
    aggregation
    mammosphere
    prediction
    single cell tracking
    tethering
    Breast--Cancer
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/11583
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    Theses and Dissertations School of Medicine
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