Current Institution: Arizona State University
Wrinkle Cellomics: Screening for Cancer Cells using an Ultra-Thin Silicone Membrane
Bladder cancer is the fifth most common in the United States, with the highest recurrence rate of any cancer. Therefore necessitating lifelong patient surveillance as often as every 3 months following initial treatment. Currently, there are two employed surveillance techniques: urine cytology—the microscopic examination of naturally exfoliated and expelled cells in urine—and cystoscopy—where a small probe with a camera is inserted into the bladder through the urethra for visual inspection of the bladder lining. Each technique has shortcomings for different types or grades of bladder cancer. Therefore, I developed a novel detection platform, which capitalizes on the inherent physical differences that distinguish cancerous from healthy cells. This platform is as noninvasive urine cytology, yet is highly sensitive and selective for cancer. Numerous studies have revealed the inherent physical differences between cancerous cells and their healthy counterparts; cancerous cells have consistently demonstrated greater flexibility, stretch-ability, and malleability. Several distinct methods have been employed to observe and discern these unique physical differences, unfortunately these methodologies collectively suffer from reliance on expensive complex equipment, highly specialized personnel, and very low-throughput of single-cells and are infeasible for patient diagnostic screening. To overcome these obstacles, I have developed a highly paralleled, high-throughput platform to simultaneously analyze all cells in a patient sample for the presence of cancer. The increased cellular malleability and traction forces of cancerous cells selectively deform this detection platform for rapid cancer diagnosis. The detection platform consists of an ultra-thin silicone membrane that is approximately 30 nm thick and floats upon liquid silicone. Cancerous and healthy cells adhere and spread upon this silicone membrane platform, however, cancerous cells exclusively exert sufficient force to deform the membrane. This cancer-specific membrane deformation is easily visualized as distinct membrane wrinkle patterns. Thus, this detection platform translates the inherent physical differences amongst cancerous and healthy cells into visual differences that are easily observed, even when cancerous cells are within a mixed cell population. I have successful employed this detection platform to preliminarily diagnosis bladder cancer from human patient urine samples.
Jennie is a PhD student in Electrical Engineering at Arizona State University and received her B.E. from Auburn University. She is an NSF Graduate Research Fellow, an Ira A. Fulton Dean’s Fellow, and an ARCS Scholar. Her research interests include the application of MEMStechnology in a biological context, specifically for the diagnosis and treatment of humandiseases, and has been presented at the 27th and the 29th IEEE International Conference onMEMS. Jennie’s dissertation work is focused on the development of a diagnosis platform for theearly detection of bladder cancer and novel therapeutic microscale implants to treathydrocephalic fluid retention in the skull. Her long-term research goals are centered on thebetterment of human health and wellness through the mindful use of technology. Additionally,Jennie is active in her community, mentoring with Big Brothers Big Sisters and volunteering atthe local Science Center.