Electromechanical transducer for rapid detection, discrimination and quantification of lung cancer cells.

Nanotechnology

Nano-Bio Lab, University of Texas at Arlington, Arlington, Texas 76019, USA. Department of Electrical Engineering, University of Texas at Arlington, Arlington, Texas 76019, USA. Nanotechnology Research Center, University of Texas at Arlington, Arlington, Texas 76019, USA.

Published: May 2016

Tumor cells are malignant derivatives of normal cells. There are characteristic differences in the mechanophysical properties of normal and tumor cells, and these differences stem from the changes that occur in the cell cytoskeleton during cancer progression. There is a need for viable whole blood processing techniques for rapid and reliable tumor cell detection that do not require tagging. Micropore biosensors have previously been used to differentiate tumor cells from normal cells and we have used a micropore-based electromechanical transducer to differentiate one type of tumor cells from the other types. This device generated electrical signals that were characteristic of the cell properties. Three non-small cell lung cancer (NSCLC) cell lines, NCl-H1155, A549 and NCI-H460, were successfully differentiated. NCI-H1155, due to their comparatively smaller size, were found to be the quickest in translocating through the micropore. Their translocation through a 15 μm micropore caused electrical pulses with an average translocation time of 101 ± 9.4 μs and an average peak amplitude of 3.71 ± 0.42 μA, whereas translocation of A549 and NCI-H460 caused pulses with average translocation times of 126 ± 17.9 μs and 148 ± 13.7 μs and average peak amplitudes of 4.58 ± 0.61 μA and 5.27 ± 0.66 μA, respectively. This transformation of the differences in cell properties into differences in the electrical profiles (i.e. the differences in peak amplitudes and translocation times) with this electromechanical transducer is a quantitative way to differentiate these lung cancer cells. The solid-state micropore device processed whole biological samples without any pre-processing requirements and is thus ideal for point-of-care applications.

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Source
http://dx.doi.org/10.1088/0957-4484/27/19/195101DOI Listing

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