High-Frequency Dielectrophoresis Reveals That Distinct Bio-Electric Signatures of Colorectal Cancer Cells Depend on Ploidy and Nuclear Volume

Author:

Duncan Josie L.1ORCID,Bloomfield Mathew2ORCID,Swami Nathan3ORCID,Cimini Daniela2ORCID,Davalos Rafael V.14ORCID

Affiliation:

1. Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24061, USA

2. Department of Biological Sciences and Fralin Life Sciences Institute, Virginia Tech, Blacksburg, VA 24061, USA

3. Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22908, USA

4. Department of Biomedical Engineering and Mechanics, Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Blacksburg, VA 24061, USA

Abstract

Aneuploidy, or an incorrect chromosome number, is ubiquitous among cancers. Whole-genome duplication, resulting in tetraploidy, often occurs during the evolution of aneuploid tumors. Cancers that evolve through a tetraploid intermediate tend to be highly aneuploid and are associated with poor patient prognosis. The identification and enrichment of tetraploid cells from mixed populations is necessary to understand the role these cells play in cancer progression. Dielectrophoresis (DEP), a label-free electrokinetic technique, can distinguish cells based on their intracellular properties when stimulated above 10 MHz, but DEP has not been shown to distinguish tetraploid and/or aneuploid cancer cells from mixed tumor cell populations. Here, we used high-frequency DEP to distinguish cell subpopulations that differ in ploidy and nuclear size under flow conditions. We used impedance analysis to quantify the level of voltage decay at high frequencies and its impact on the DEP force acting on the cell. High-frequency DEP distinguished diploid cells from tetraploid clones due to their size and intracellular composition at frequencies above 40 MHz. Our findings demonstrate that high-frequency DEP can be a useful tool for identifying and distinguishing subpopulations with nuclear differences to determine their roles in disease progression.

Funder

NSF SBIR Phase II

Virginia Biosciences Health Research Corporation Catalyst Grant

U.S. National Institutes of Health

Virginia Tech College of Science through a Dean’s Discovery Fund

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering

Reference37 articles.

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