Bioelectric spectra characterization of individual cancer cells with electrochemical impedance spectroscopy
Becerra Arias, Marco A
AdvisorDiaz Rivera, Ruben E.
CollegeCollege of Engineering
DepartmentDepartment of Mechanical Engineering
MetadataShow full item record
In the field of Biomedical Science and Engineering, microfluidic systems have been used for the analysis of cellular structures at the micro and nano-scales. Predominantly, work in the field is geared towards multicell-multiarray analysis for high throughput processing of clinical samples. Studies have also focused on the “dissection” of the DNA and RNA to identify disorders and mutations that can lead to cancer. The work presented herein proposes a different approach towards the advancement of cancer cell research, which integrates microfluidics and electrical recordings at the single cell level by Electrochemical Impedance Spectroscopy (EIS). EIS is normally used to measure the impedance across an electrochemical cell by the application of an external AC voltage in a specified frequency range. By performing a frequency sweep and recording the electrical response of the material under study, one can elucidate surface and volumetric characteristics of interest. Since the scientific literature suggest that each biological cell type has an unique bioelectric spectra, it is possible to employ EIS to identify unknown cells based on electrical recordings. Toward this end, a biosensing platform to interrogate individual cells with EIS was developed. Extensive testing was conducted with two cancer cells lines (i.e. Hela cervical cancer cells, MDA-MB-231 breast metastatic cancer cells) and a healthy tissue cell line (i.e. MCF12a breast cells). Results show different electrical behavior in certain frequency ranges among the studied cell lines with a 99% confidence interval of the entire population. Ergo, cell line identification is possible by EIS. With further development, this technology has the potential to detect anomalous/cancerous cells in blood biopsies, which will be an important step towards the early detection of diseases such as cancer.