PhD Proposal by Isaac Robinson

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Isaac Robinson

BioE Ph.D. Proposal Presentation

November 29, 2021

11:00 am 

BlueJeans Link: https://bluejeans.com/934499308/3123

Meeting ID: 934 499 308



Prof. Susan Thomas (School of Mechanical Engineering, Georgia Institute of Technology)


Prof. Shuichi Takayama (School of Biomedical Engineering, Georgia Institute of Technology)

Prof. Edward Botchwey (School of Biomedical Engineering, Georgia Institute of Technology)

Prof. Adam Marcus (School of Medicine, Winship Cancer Institute, Emory University)

Prof. Andrés Garcia (School of Mechanical Engineering, Georgia Institute of Technology)


Engineering method for characterization of dynamic cell migration with application for cancer metastasis investigation


Novel methods for understanding cell migration are constantly being engineered. However, such tools, while embraced by engineers, have not seen similar levels of adoption by mainstream biology research. There is, therefore, a need to develop not only useful investigational tools, but those that will also be largely accepted/implemented in biological studies. Despite the numerous microfluidic devices that have been recently developed by engineers specifically for biological or medical investigation, many biological and medical researchers have continued with conventional assays or in vivo studies. To address this, one such conventional assay was identified and enhanced: a simple but ubiquitously used technology in biology for understanding chemotaxis called the Boyden chamber assay (BCA). Rather than design a microfluidic system that more efficiently and precisely does the job of this assay, but with engineering complexities that might deter non-engineers from adoption, it could be more impactful to couple the platform with simple but enhancing technology. Thus, the overall objective is to design a system that combines the ubiquity of BCAs with the high throughput, high resolution analysis capability of a cell photoconversion system in order to provide single cell resolution of transmigration over time. The central hypothesis is that the development of a platform with the capacity to fluorescently tag a cell based on the time at which it first migrates will provide key insights into dynamic migration characteristics that relate to individual cellular protein expression of cancer cells in varied metastatic-mimicking microenvironments. Understanding single cell behavior in this way will provide insight into metastatic cancer progression for use in development of migrastatic therapy. Beyond the direct impact in cancer research, this work will provide a method that can be implemented across many fields involving cell migration to investigate heterogenous cell migration dynamics at high resolution.




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