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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

Breast cancer cells exhibit different dielectric properties compared to non-tumor breast epithelial cells. It has been hypothesized that, based on this difference in dielectric properties, the two populations can be separated for immunotherapy purposes. To support this, we model a microfluidic device to sort MCF-7 and MCF-10A cells.

Abstract

Dielectrophoretic devices are capable of the detection and manipulation of cancer cells in a label-free, cost-effective, robust, and accurate manner using the principle of the polarization of the cancer cells in the sample volume by applying an external electric field. This article demonstrates how a microfluidic platform can be utilized for high-throughput continuous sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using hydrodynamic dielectrophoresis (HDEP) from the cell mixture. By generating an electric field between two electrodes placed side-by-side with a micron-sized gap between them in an HDEP microfluidic chip, non-tumor breast epithelial cells (MCF-10A) can be pushed away, exhibiting negative DEP inside the main channel, while the non-metastatic breast cancer cells follow their course unaffected when suspended in cell medium due to having conductivity higher than the membrane conductivity. To demonstrate this concept, simulations were performed for different values of medium conductivity, and the sorting of cells was studied. A parametric study was carried out, and a suitable cell mixture conductivity was found to be 0.4 S/m. By keeping the medium conductivity fixed, an adequate AC frequency of 0.8 MHz was established, giving maximum sorting efficiency, by varying the electric field frequency. Using the demonstrated method, after choosing the appropriate cell mixture suspension medium conductivity and frequency of the applied AC, maximum sorting efficiency can be achieved.

Introduction

A malignant tumor that develops in and around the breast tissue is a frequent cause of breast cancer in women worldwide, causing a critical health problem1. Breast tumors before metastasis can be treated through surgery if detected at an early stage, but if ignored, they can have severe implications on the patient's life by spreading to their lungs, brain, and bones. The treatments offered at later stages, such as radiation and chemical-based therapies, have severe side effects2. Recent studies have reported that an early diagnosis of breast cancer reduces the mortality rate by 60%3. Hence, it is imperative to work toward personalized early detection methods. To this end, researchers working in different fields of science and technology have used microfluidics to develop devices for the early diagnosis of breast cancer4. These methods include cell affinity micro-chromatography, magnetic-activated micro-cell sorters, size-based cancer cell capture and separation, and on-chip dielectrophoresis (DEP)5,6. These microfluidic techniques reported in the literature enable precise cell manipulation, real-time monitoring, and sorting of well-defined samples, which serve as an intermediate step in many diagnostic and therapeutic applications5. The integration of these sorting mechanisms with microfluidics offers flexible and reliable manipulation of the target cells7,8,9,10. One of the main advantages of such an integration is the ability to work with fluid samples in nano to microliter volumes and also being able to manipulate the electrical properties of the sample fluid. By adjusting the conductivity of the suspending fluid inside microfluidic devices, the biological cells can be sorted based on their sizes and differences in their dielectric properties11,12.

Among these techniques, on-chip DEP is often preferred as it is a label-free cell sorting technique that exploits the electric properties of the biological samples. DEP has been reported to manipulate bio-samples such as DNA13, RNA14, proteins15, bacteria16, blood cells17, circulating tumor cells (CTCs)18, and stem cells19. Microfluidic devices that employ DEP for sorting biological samples have been reported extensively in literature20. Reservoir-based DEP microfluidic (rDEP) devices for sorting viable and non-viable yeast cells have been reported that protect the cells from the adverse effects of electrochemical reactions21,22. Piacentini et al. reported a castellated microfluidic cell sorter that separated red blood cells from platelets with an efficiency of 97%23. On-chip DEP devices with asymmetric orifices and embedded electrodes have also been reported to sort viable and non-viable cells24. Valero and Demierre et al. modified the castellated microfluidic cell sorter by introducing two arrays of microelectrodes on both sides of the channel25,26. This helped in focusing the cells in the center of the channel. Zeynep et al. presented a DEP-based microfluidic device to separate and concentrate MCF7 breast cancer cells from leukocytes27. They reported an efficiency of extracting MCF7 cells from leukocytes between 74%-98% with a frequency of 1 MHz and an applied voltage ranging from 10-12 Vpp. Supplementary Table 1 represents a qualitative and quantitative comparison between the DEP-based microfluidic sorting devices based on their design, electrode configuration, and operating parameters (applied frequency and voltage).

More recently, researchers have tried to measure the differences in the dielectric behavior of breast epithelial cells (MCF-10A) and non-metastatic breast cancer cells (MCF-7) inside a microfluidic chip28,29. Jithin et al. also characterized the dielectric responses of different cancer cell lines using an open-ended coaxial probe technique with frequencies between 200 MHz and 13.6 GHz30. These differences in the dielectric responses of MCF-7 and MCF-10A cell lines can be exploited to separate them in runtime and can lead to the development of personalized early-stage diagnosis devices.

In this article, we simulate the controlled sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using AC dielectrophoresis. The region of change in the electric field influences the sorting inside the microfluidic chip. The proposed technique is easy to implement and allows for the integration of the sorting technique into various microfluidic chip layouts. Computational fluid dynamics (CFD) simulations were carried out to study the separation of non-metastatic breast cancer cells and non-tumor breast epithelial cells by varying the conductivity of the fluid medium in which cells were suspended. In these simulations, it is shown that, by keeping the conductivity constant and by changing the applied frequency, the separation of cancer cells and healthy cells can be controlled.

Protocol

NOTE: The protocol here uses COMSOL, a multiphysics simulation software, to simulate the controlled sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) using AC dielectrophoresis.

1. Chip design and parameter selection

  1. Open multiphysics software and select Blank Model. Right-click on the Global Definitions and select Parameters. Import the parameters given in Table 1 into global definitions as a text file or enter the values individually.
  2. Select Add Component from the home tab and add a 2D Component. Right-click on geometry and import the model file by double-clicking on the file.
  3. Choose a blank material and use the material properties from Table 1.
  4. Select Add Physics from the home tab, and type AC/DC. Under the AC/DC node, choose electric currents as Physics under the sub-node of electric fields and currents.
  5. Right-click on the Electric Current and choose the Current Conservation, Insulate, and Electric Potential sub-nodes to insulate the channel walls to assign potential to the electrodes.
  6. Select Add Physics from the home tab, and under the Fluid Flow node, choose Creeping Flow Physics under the sub-node of Single-Phase Flow. Right-click on Single-Phase Flow and render the chip boundaries as walls by using the Wall sub-node.
  7. Right click on Single-Phase Flow and add two inlet sub-nodes and one outlet sub-node.
  8. Assign the inlets using the inlet sub-node and use normal in Flow Velocity as the Boundary Condition. Assign the outlet using the outlet sub-node.
  9. Select Add Physics from the home tab, and under the Fluid Flow node, choose Particle Tracing Flow Physics under the sub node of Particle Tracing.
  10. Right-click on the Particle Tracing node and add the sub-nodes wall, two-particle property sub-nodes, two inlet sub-nodes, one outlet sub-node, two dielectrophoresis force sub-nodes, and one drag force sub-node.
    1. Set Particle Properties for both MCF-7 and MCF-10A cells using the Particle Properties sub-node. Choose the particle properties from parameters under the Global Definition section.
    2. Add the Drag Force sub-node to assign the dielectrophoretic force to both types of cells.
    3. Add Particle Properties in this case from the parameter section. Add the Shell sub-node to model mammalian cells.
  11. From the home tab, choose Add Mesh and select Fine Mesh. Choose Build Mesh from the home tab to build a mesh.
  12. From the home tab, click on Add Study to add three study steps. Study Step 1 is for simulating a frequency response; use a Frequency Domain sub-node.
    1. To simulate creeping flow, choose a Stationary Study node. Add two time-dependent steps to simulate conditions with dielectrophoretic force and without dielectrophoretic force.
    2. For the no dielectrophoretic condition, choose Physics and Variables Selection, check the box titled Modify Model Configuration for the study step, and disable the Dielectrophoretic Step. For dielectrophoretic conditions, do not disable. Save the file and press Compute for the simulation to run.
      NOTE: The microfluidic chip designed for the sorting of non-metastatic breast cancer cells (MCF-7) and non-tumor breast epithelial cells (MCF-10A) has two separate inlets for cell mixture flow and for hydrodynamic flow focusing, respectively, with widths of 20 µm and 40 µm, respectively, as shown in Supplementary Figure 1 and Supplementary Figure 2.
    3. Assign frequency (f0) under the Frequency Domain sub-node and voltage using the Electric Potential sub-node to the planer electrodes (295 µm in width) placed along the top side wall of the sorting chamber. At the outlet, use the "freeze" wall condition to visualize the sorted particles.

2. Mathematical model and computational analysis

  1. Verify the operating parameters for separating non-metastatic breast cancer cells and non-tumor breast epithelial cells inside the microfluidic device by setting up a computational fluid dynamic (CFD) study.
    NOTE: Multiphysics software (AC/DC, Microfluidics, and Particle Tracking modules) was used for this purpose. The governing equations and theoretical background are given in detail in Supplementary File 1. The model was tested by using the dielectric properties of non-metastatic breast cancer cells (MCF7) and non-tumor breast epithelial cells (MCF-10A) reported in literature31,32, which are summarized in Table 1.
  2. Perform the CFD simulations by introducing non-metastatic breast cancer (MCF7) and non-tumor breast epithelial (MCF-10A) cell lines with a ratio of 1:1 at the cell mixture inlet.
    1. Initially, perform a mesh independence study to optimize the mesh size for the simulations33.
      NOTE: A mesh independence study was performed to find the best solution for the operating parameters. A set of five different mesh sizes was chosen to quantify the best possible element size for the convergence of the solution. It was observed that, when the total number of elements defining a mesh was 635 (coarser mesh), as shown in Supplementary Figure 3A, the sorting efficiency was at its lowest, with some of the MCF7 cells moving to the bottom outlet, as depicted in Supplementary Figure 3B. When the mesh size was increased to fine, the number of elements defining the mesh also increased to 2,288. The sorting efficiency was at its maximum in this case, with both MCF7 and MCF-10A cells moving toward their respective outlets. The finer mesh was also simulated, with the number of elements defining the mesh increasing to 3,188. The sorting efficiency remained unaffected beyond this point. Hence, we can safely say that fine mesh size works the best in our case.
    2. Solve two sets of CFD studies.
    3. For the first set, right -click on Study 1 and add the Parametric Sweep sub-node. Press the + sign to add fluid medium conductivity "σm" as the sweep variable. Perform a parametric sweep study for the fluid medium conductivity σm ranging from 0.01 S/m to 2.5 S/m, keeping the applied frequency, f (Hz), constant at a value of 800 kHz.
    4. For the second set, conduct a Parametric Sweep study by varying the applied AC frequency from 100 kHz to 100 MHz while keeping the conductivity of the fluid medium, σm, fixed at 0.4 S/m for each case. This σm value was chosen based on the results of the first CFD study as a maximum separation between MCF-7 and MCF-10A was observed at this value.
    5. The strength of the dielectrophoresis (DEP) force, FDEP (-), exerted on a dielectric spherical particle in a conductive medium is given by Equation 1T34:
      FDEP figure-protocol-8112  [1]
      Use Equation 1 under the dielectrophoretic force sub-node. In equation 1, r shows the radius of the particle on which FDEP is applied; K (-) is known as the Clausius-Mossotti factor; εm (-) shows the dielectric permittivity of the medium; and E(V/m) is the root mean square value of the electric field.
    6. Use Equation 2 for a spherical particle under the dielectrophoretic force sub-node.
      figure-protocol-8681     [2]
      In Equation 2, figure-protocol-8818 (-) shows the complex permittivity of the particle on which the DEP force is applied; figure-protocol-8995 (-) shows the complex permittivity of the fluid surrounding the particle. The complex permittivity figure-protocol-9185 and figure-protocol-9280 are defined as follows35:
    7. Use Equation 3 for a spherical particle under the dielectrophoretic force sub-node:
      figure-protocol-9524     [3]
      In Equation 3, εp (-) shows the real part of the complex permittivity of the particle; εm (-) shows the real part of the complex permittivity of the fluid surrounding the particle; σp (S/m) shows the particle conductivity; σm (S/m) shows the conductivity of the medium surrounding the particle; and ω (Hz) is the frequency of the applied electric field.
      NOTE: The sign of Re(K) determines the polarity of the FDEP. If the sign of Re(K) is negative, then the particle experiences a negative dielectrophoretic force (nDEP); contrary to this, if the sign of Re(K) is positive, it implies a positive dielectrophoretic force (pDEP). For the Clausius-Mossotti factor (K), the variation lies within the range of -1 to 1.
  3. Use a modified form of Equation 3 to model biological cells such as mammalian cells, which are more complex and have a multilayered structure.
    K (figure-protocol-10639) = figure-protocol-10733     [4]
    In Equation 4, figure-protocol-10869 (-) incorporates both the complex permittivity of the cytoplasm, figure-protocol-11025 (-), and the complex permittivity of the cell membrane, figure-protocol-11173 (-), and is given as follows:36
  4. Use Equation 5 to solve "figure-protocol-11360":
    figure-protocol-11465     [5]
    In Equation 5, Rcyto (m) and Rmem (m) show the radius of the cell cytoplasm and cell membrane, respectively.
  5. Then, use Equation 4 to plot Re(K) as a function of the applied electric field for both cancer and healthy cells. Calculate the real part of the Clausius-Mossotti (CM) factor, Re(K), to quantify the dielectrophoretic force (DEP) that the particle experiences.
  6. Right-click on the Results node, add the Particle Evaluation sub-node, and in the expression section, type fpt.deff1.K to plot the CM factor for particle 1 and fpt.deff2.K for particle 2.
    NOTE: All the protocol steps listed in the main text can be viewed in the protocol video (Video 1).

Results

Investigating the optimal operational parameters for effective DEP-based sorting of non-metastatic breast cancer (MCF-7) and non-tumor breast epithelial (MCF-10A) cells
To achieve a successful separation of non-metastatic breast cancer (MCF-7) and non-tumor breast epithelial (MCF-10A) cells with divergent dielectric properties when undergoing dielectrophoresis, their K factors should be distinct by keeping the applied frequency fixed37,38. ...

Discussion

Microfluidic devices have been reported previously for cell culture, trapping, and sorting47,52,53. The fabrication of these devices in the cleanroom is an expensive process, and it is imperative to quantify the output and efficiency of a proposed microfluidic device through CFD simulations. This study presents the design and simulations of an AC-dielectrophoretic microfluidic device for the continuous separation of non-metastat...

Disclosures

The authors declare no potential conflicts of interest.

Acknowledgements

This study was supported by the Higher Education Commission of Pakistan.

Materials

NameCompanyCatalog NumberComments
COMSOLCOMSOLmultiphysics simulation software

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