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Numerical Simulation of Separation of Circulating Tumor Cells from Blood Stream in Deterministic Lateral Displacement (DLD) Microfluidic Channel

Published online by Cambridge University Press:  21 December 2015

F. Khodaee ,
S. Movahed ,
N. Fatouraee  and
F. Daneshmand
F. Khodaee
Affiliation:
Biological Fluid Mechanics Research Laboratory Biomechanics Department Amirkabir University of Technology Tehran, Iran
S. Movahed*
Affiliation:
Department of Mechanical Engineering Amirkabir University of Technology Tehran, Iran
N. Fatouraee
Affiliation:
Biological Fluid Mechanics Research Laboratory Biomechanics Department Amirkabir University of Technology Tehran, Iran
F. Daneshmand
Affiliation:
Department of Mechanical Engineering McGill University Montreal, Canada Department of Bioresource Engineering McGill University Montreal, Canada
*
*Corresponding author ([email protected])

Abstract

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Deterministic Lateral Displacement (DLD) microfluidic devices provide a reliable label-free separation method for detection of circulating tumor cells (CTCs) in blood samples based on their biophysical properties. In this paper, we proposed an effective design of the DLD microfluidic device for the CTC separation in the blood stream. A typical DLD array is designed and numerical simulations are performed to separate the CTC and leukocyte (white blood cells) in different fluid flow conditions. Fluid-Solid Interaction method is used to investigate the behaviour of these deformable cells in fluid flow. In this study, the effects of critical parameters affecting cell separation in the DLD microfluidic devices (e.g. flow condition, cell deformability, and stress) have been investigated. The obtained results show that unlike leukocytes, the CTC’s motion is independent of the flow condition and is laterally displaced even in higher Reynolds number. Larger cells (CTCs) cannot intercept the low-velocity fluid near the wall of the posts; thus, they move faster and become separated from leukocytes. To reduce the cellular stress during separation process, which causes increase of cell viability and more effective design of microfluidic device, the results obtained here may be used as a significant design parameter for the DLD fabrication.

Keywords

Deterministic lateral displacement (DLD)Circulating tumor cell (CTC)MicrofluidicsFluid-solid interaction (FSI)
Type
Research Article
Information
Journal of Mechanics , Volume 32 , Issue 4 , August 2016 , pp. 463 - 471
Copyright
Copyright © The Society of Theoretical and Applied Mechanics 2016 

References

1. Ashworth, T., “A Case of Cancer in Which Cells Similar to Those in the Tumours Were Seen in the Blood After Death,” Medical Journal of Australia, 14, pp. 146–149 (1869).Google Scholar
2. Norton, L. and Massague, J., “Is Cancer a Disease of Self-Seeding?,” Nature Medicine, 12(8), pp. 875–878 (2006).Google Scholar
3. Allan, A. L. and Keeney, M., “Circulating Tumor Cell Analysis: Technical and Statistical Considerations for Application to the Clinic,” Journal of Oncology (2009).Google Scholar
4. Williams, A., Balic, M., Datar, R. and Cote, R., “Size-Based Enrichment Technologies for CTC Detection and Characterization,” Minimal Residual Disease and Circulating Tumor Cells in Breast Cancer, Springer Berlin Heidelberg, pp. 87–95 (2012).Google Scholar
5. Miller, M. C., Doyle, G. V. and Terstappen, L. W. M. M., “Significance of Circulating Tumor Cells Detected by the CellSearch System in Patients with Metastatic Breast Colorectal and Prostate Cancer,” Journal of Oncology, 2010, Article ID 617421 (2009).Google Scholar
6. Jin, C., et al., “Technologies for Label-Free Separation of Circulating Tumor Cells: From Historical Foundations to Recent Developments,” Lab on a Chip, 14, pp. 32–44 (2013).CrossRefGoogle Scholar
7. Polyak, K. and Weinberg, R. A., “Transitions Between Epithelial and Mesenchymal States: Acquisition of Malignant and Stem Cell Traits,” Nature Review Cancer, 9, pp. 265–273 (2009).Google Scholar
8. Esmaeilsabzali, H., Beischlag, T. V., Cox, M. E., Parameswaran, A. M. and Park, E. J., “Detection and Isolation of Circulating Tumor Cells: Principles and Methods,” Biotechnology Advances, 31, pp. 1063–1084 (2013).Google Scholar
9. Li, P., Station, Z. S., Dao, M., Ritz, J. and Huang, T. J., “Probing Circulating Tumor Cells in Microfluidics,” Lab on a Chip, 13, pp. 602–609 (2013).CrossRefGoogle ScholarPubMed
10. Movahed, S. and Li, D., “A Theoretical Study of Single-Cell Electroporation in a MicroChannel,” The Journal of Membrane Biology, 246, pp. 151–160 (2013).CrossRefGoogle Scholar
11. Movahed, S. and Li, D., “Electrokinetic Transport of Nanoparticles to Opening of Nanopores on Cell Membrane During Electroporation,” Journal of Nanoparticle Research, 15, pp. 1–17 (2013).Google Scholar
12. Lim, L. S., et al., “Microsieve Lab-Chip Device for Rapid Enumeration and Fluorescence in Situ Hybridization of Circulating Tumor Cells,” Lab on a Chip, 12, pp. 4388–4396 (2012).CrossRefGoogle ScholarPubMed
13. Wang, G., et al., “Stiffness Dependent Separation of Cells in A Microfluidic Device,” PLoS ONE, 8 (2013).Google Scholar
14. Warkiani, M. E., et al., “Slanted Spiral Microfluidics for the Ultra-Fast, Label-Free Isolation of Circulating Tumor Cells,” Lab on a Chip, 14, pp. 128–137 (2014).Google Scholar
15. Hou, H. W., et al., “Isolation and Retrieval of Circulating Tumor Cells Using Centrifugal Forces,” Scientific Reports, 3 (2013).Google Scholar
16. Lin, B. K., McFaul, S. M., Jin, C., Black, P. C. and Ma, H., “Highly Selective Biomechanical Separation of Cancer Cells from Leukocytes Using Microfluidic Ratchets and Hydrodynamic Concentrator,” Biomicrofluidics, 1, Article ID 034114 (2013).Google Scholar
17. Zheng, S., et al., “3D Microfilter Device for Viable Circulating Tumor Cell (CTC) Enrichment From Blood,” Biomedical Microdevices, 13, pp. 203–213 (2011).CrossRefGoogle Scholar
18. Lin, H. K., et al., “Portable Filter-Based Microdevice for Detection and Characterization of Circulating Tumor Cells,” Clinical Cancer Research, 16, pp. 5011–5018 (2010).Google Scholar
19. Moon, H.-S., et al., “Continuous Separation of Breast Cancer Cells from Blood Samples Using Multi-Orifice Flow Fractionation (MOFF) and Dielectrophoresis (DEP),” Lab on a Chip, 11, pp. 1118–1125 (2011).Google Scholar
20. Shim, S., Gascoyne, P., Noshari, J. and Hale, K. S., “Dynamic Physical Properties of Dissociated Tumor Cells Revealed by Dielectrophoretic Field-Flow Fractionation,” Integrative Biology, 3, pp. 850–862 (2011).Google Scholar
21. Huang, L. R., Cox, E. C., Austin, R. H. and Sturm, J. C., “Continuous Particle Separation Through Deterministic Lateral Displacement,” Science, 304, pp. 987–990 (2004).CrossRefGoogle ScholarPubMed
22. Zheng, S., Tai, Y. C. and Kasdan, H., “A Micro Device for Separation of Erythrocytes and Leukocytes in Human Blood,” Engineering in Medicine and Biology Society, 27th Annual International Conference of the IEEE, 1, pp. 1024–1027 (2005).Google Scholar
23. Li, N., Kamei, D. T. and Ho, C.-M., “On-Chip Continuous Blood Cell Subtype Separation by Deterministic Lateral Displacement,” 2nd IEEE International Conference on Nano/Micro Engineered and Molecular Systems, Thailand (2007).Google Scholar
24. Davis, J. A., et al., “Deterministic Hydrodynamics: Taking Blood Apart,” Proceedings of the National Academy of Sciences, 103, pp. 14779–14784 (2006).Google Scholar
25. Holm, S. H., Beech, J. P., Barrett, M. P. and Tegenfeldt, J. O., “Separation of Parasites from Human Blood Using Deterministic Lateral Displacement,” Lab on a Chip, 11, pp. 1326–1332 (2011).Google Scholar
26. Holm, S. H., Beech, J. P., Barrett, M. P. and Tegenfeldt, J. O., “A High-Throughput Deterministic Lateral Displacement Device for Rapid and Sensitive Field-Diagnosis of Sleeping Sickness,” 16th International Conference on Miniaturized Systems for Chemistry and Life Sciences. Okinawa, Japan, pp. 530–532 (2012).Google Scholar
27. Inglis, D. W., Herman, N. and Vesey, G., “Highly Accurate Deterministic Lateral Displacement Device and Its application to Purification of Fungal Spores,” Biomicrofluidics, 4, Article ID 024109 (2010).Google Scholar
28. Morton, K. J., et al., “Crossing Microfluidic Streamlines to Lyse, Label and Wash Cells,” Lab on a Chip, 8, pp. 1448–1453 (2008).CrossRefGoogle ScholarPubMed
29. Inglis, D. W., et al., “Determining Blood Cell Size Using Microfluidic Hydrodynamics,” Journal of Immunological Methods, 329, pp. 151–156 (2008).Google Scholar
30. Liu, Z., et al., “Rapid Isolation of Cancer Cells Using Microfluidic Deterministic Lateral Displacement Structure,” Biomicrofluidics, 7, Article ID 011801 (2013).Google Scholar
31. Loutherback, K., et al., “Deterministic Separation of Cancer Cells from Blood at 10 Ml/Min,” AIP Advances, 2, Article ID 042107 (2012).Google Scholar
32. Liu, Z., et al., “High Throughput Capture of Circulating Tumor Cells Using an Integrated Microfluidic System,” Biosensors and Bioelectronics, 47, pp. 113–119 (2013).Google Scholar
33. Long, B. R., et al., “Multidirectional Sorting Modes in Deterministic Lateral Displacement Devices,” Physical Review E, 78, Article ID 046304 (2008).Google Scholar
34. Quek, R., Le, D. V. and Chiam, K. H., “Separation of Deformable Particles in Deterministic Lateral Displacement Devices,” Physical Review E, 83, Article ID 056301 (2011).Google Scholar
35. D’Avino, G., “Non-Newtonian Deterministic Lateral Displacement Separator: Theory and Simulations,” Rheologica Ada, 52, pp. 221–236 (2013).Google Scholar
36. Inglis, D. W., Davis, J. A., Austin, R. H. and Sturm, J. C., “Critical Particle Size for Fractionation by Deterministic Lateral Displacement,” Lab on a Chip, 6, pp. 655–658 (2006).Google Scholar
37. Meng, S., et al., “Circulating Tumor Cells in Patients with Breast Cancer Dormancy,” Clinical Cancer Research, 10, pp. 8152–8162 (2004).CrossRefGoogle ScholarPubMed
38. Beech, J. P., Holm, S. H., Adolfsson, K. and Tegenfeldt, J. O., “Sorting Cells by Size, Shape and Deformability,” Lab on a Chip, 12, pp. 1048–1051 (2012).Google Scholar
39. Inglis, D. W., et al., “Microfluidic Device for Label-Free Measurement of Platelet Activation,” Lab on a Chip, 8, pp. 925–931 (2008).Google Scholar
40. Chen, C. L., et al., “Single- Cell Analysis of Circulating Tumor Cells Identifies Cumulative Expression Patterns of EMT-Related Genes in Metastatic Prostate Cancer,” Prostate, 73, pp. 813–826 (2013).Google Scholar
41. Shirai, A. and Masuda, S., “Numerical Simulation of Passage of a Neutrophil Through a Rectangular Channel with a Moderate Constriction,” PLoS One, 8, Article ID e59416 (2013).CrossRefGoogle ScholarPubMed
42. Bathe, M., Shirai, A., Doerschuk, C. M. and Kamm, R. D., “Neutrophil Transit Times Through Pulmonary Capillaries: The Effects of Capillary Geometry and Fmlp-Stimulation,” Biophysical Journal, 83, pp. 1917–1933 (2002).Google Scholar
43. Donea, J., Giuliani, S. and Halleux, J. P., “An Arbitrary Lagrangian-Eulerian Finite Element Method for Transient Dynamic Fluid-Structure Interactions,” Computer Methods in Applied Mechanics and Engineering, 33, pp. 689–723 (1982).Google Scholar
44. Bathe, K.-J. and Zhang, H., “A Mesh Adaptivity Procedure for CFD and Fluid-Structure Interactions,” Computers & Structures, 87, pp. 604–617 (2009).Google Scholar
45. Vahidi, B. and Fatouraee, N., “Large Deforming Buoyant Embolus Passing Through a Stenotic Common Carotid Artery: A Computational Simulation,” Journal of Biomechanics, 45, pp. 1312–1322 (2012).Google Scholar
46. Kulrattanarak, T., Sman, R. G. M., Schroën, C. G. P. H. and Boom, R. M., “Analysis of Mixed Motion in Deterministic Ratchets Via Experiment and Particle Simulation,” Microfluidics and Nanofluidics, 10, pp. 843–853 (2011).Google Scholar
47. Kuo, J. S., et al., “Deformability Considerations in Filtration of Biological Cells,” Lab on a Chip, 10, pp. 837–842 (2010).Google Scholar