Seyfried, T. N., & Huysentruyt, L. C. (2013). On the origin of cancer metastasis. Critical Reviews in Oncogenesis, 18(1–2), 43–73. https://doi.org/10.1615/critrevoncog.v18.i1-2.40

Article  PubMed  PubMed Central  Google Scholar 

Jin X, Zhu Z, Shi Y. Metastasis mechanism and gene/protein expression in gastric cancer with distant organs metastasis. Bull Cancer. Published online October 1, 2014. https://doi.org/10.1684/bdc.2013.1882

Irani, S. (2019). Emerging insights into the biology of metastasis: A review article. Iranian Journal of Basic Medical Sciences, 22(8), 833–847. https://doi.org/10.22038/ijbms.2019.32786.7839

Article  PubMed  PubMed Central  Google Scholar 

Yin Z, Mancuso JJ, Li F, Wong STC. Chapter 2 - Genomics-based cancer theranostics. In: Chen X, Wong S, eds. Cancer Theranostics. Academic Press; 2014:9–20. https://doi.org/10.1016/B978-0-12-407722-5.00002-5

Yachida, S., Jones, S., Bozic, I., et al. (2010). Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature, 467(7319), 1114–1117. https://doi.org/10.1038/nature09515

Article  CAS  PubMed  PubMed Central  Google Scholar 

Faltas, B. (2012). Cornering metastases: Therapeutic targeting of circulating tumor cells and stem cells. Frontiers in Oncology., 2, 68. https://doi.org/10.3389/fonc.2012.00068

Article  PubMed  PubMed Central  Google Scholar 

Mitchell, M. J., & King, M. R. (2014). Physical biology in cancer 3 The role of cell glycocalyx in vascular transport of circulating tumor cells. American Journal of Physiology-Cell Physiology., 306(2), C89–C97. https://doi.org/10.1152/ajpcell.00285.2013

Article  CAS  PubMed  Google Scholar 

Potdar, P. D., & Lotey, N. K. (2015). Role of circulating tumor cells in future diagnosis and therapy of cancer. Journal of Cancer Metastasis and Treatment., 1, 44–56. https://doi.org/10.4103/2394-4722.158803

Article  CAS  Google Scholar 

Jahanban-Esfahlan, R., de la Guardia, M., Ahmadi, D., & Yousefi, B. (2018). Modulating tumor hypoxia by nanomedicine for effective cancer therapy. Journal of Cellular Physiology., 233(3), 2019–2031. https://doi.org/10.1002/jcp.25859

Article  CAS  PubMed  Google Scholar 

Baghban, R., Roshangar, L., Jahanban-Esfahlan, R., et al. (2020). Tumor microenvironment complexity and therapeutic implications at a glance. Cell Communication and Signaling., 18(1), 59. https://doi.org/10.1186/s12964-020-0530-4

Article  PubMed  PubMed Central  Google Scholar 

Perrault, C. M., Brugues, A., Bazellieres, E., Ricco, P., Lacroix, D., & Trepat, X. (2015). Traction forces of endothelial cells under slow shear flow. Biophysical Journal, 109(8), 1533–1536. https://doi.org/10.1016/j.bpj.2015.08.036

Article  CAS  PubMed  PubMed Central  Google Scholar 

Boldock L, Wittkowske C, Perrault CM. Microfluidic traction force microscopy to study mechanotransduction in angiogenesis. Microcirculation. 2017;24(5). https://doi.org/10.1111/micc.12361

Ma, S., Fu, A., Chiew, G. G. Y., & Luo, K. Q. (2017). Hemodynamic shear stress stimulates migration and extravasation of tumor cells by elevating cellular oxidative level. Cancer Letters., 388, 239–248. https://doi.org/10.1016/j.canlet.2016.12.001

Article  CAS  PubMed  Google Scholar 

Weth, A., Krol, I., Priesner, K., et al. (2020). A novel device for elimination of cancer cells from blood specimens. Science and Reports, 10(1), 10181. https://doi.org/10.1038/s41598-020-67071-w

Article  CAS  Google Scholar 

Landwehr, G. M., Kristof, A. J., Rahman, S. M., et al. (2018). Biophysical analysis of fluid shear stress induced cellular deformation in a microfluidic device. Biomicrofluidics, 12(5), 054109. https://doi.org/10.1063/1.5063824

Article  CAS  PubMed  PubMed Central  Google Scholar 

Marrella, A., Fedi, A., Varani, G., et al. (2021). High blood flow shear stress values are associated with circulating tumor cells cluster disaggregation in a multi-channel microfluidic device. PLoS ONE, 16(1), e0245536. https://doi.org/10.1371/journal.pone.0245536

Article  CAS  PubMed  PubMed Central  Google Scholar 

Khoo, B. L., Grenci, G., Lim, Y. B., Lee, S. C., Han, J., & Lim, C. T. (2018). Expansion of patient-derived circulating tumor cells from liquid biopsies using a CTC microfluidic culture device. Nature Protocols, 13(1), 34–58. https://doi.org/10.1038/nprot.2017.125

Article  CAS  PubMed  Google Scholar 

Wong, K. H. K., Tessier, S. N., Miyamoto, D. T., et al. (2017). Whole blood stabilization for the microfluidic isolation and molecular characterization of circulating tumor cells. Nature Communications, 8(1), 1733. https://doi.org/10.1038/s41467-017-01705-y

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mishra, A., Dubash, T. D., Edd, J. F., et al. (2020). Ultrahigh-throughput magnetic sorting of large blood volumes for epitope-agnostic isolation of circulating tumor cells. PNAS, 117(29), 16839–16847. https://doi.org/10.1073/pnas.2006388117

Article  CAS  PubMed  PubMed Central  Google Scholar 

Harouaka, R. A., Nisic, M., & Zheng, S. Y. (2013). Circulating Tumor Cell Enrichment Based on Physical Properties. Journal of Laboratory Automation, 18(6), 455–468. https://doi.org/10.1177/2211068213494391

Article  CAS  PubMed  Google Scholar 

Wu, P. H., Aroush, D. R. B., Asnacios, A., et al. (2018). A comparison of methods to assess cell mechanical properties. Nature Methods, 15(7), 491–498. https://doi.org/10.1038/s41592-018-0015-1

Article  CAS  PubMed  PubMed Central  Google Scholar 

Mak, M., & Erickson, D. (2013). A serial micropipette microfluidic device with applications to cancer cell repeated deformation studies. Integrative Biology., 5(11), 1374–1384. https://doi.org/10.1039/c3ib40128f

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, X., & Mak, M. (2021). Biophysical informatics approach for quantifying phenotypic heterogeneity in cancer cell migration in confined microenvironments. Bioinformatics, 37(14), 2042–2052. https://doi.org/10.1093/bioinformatics/btab053

Article  CAS  Google Scholar 

Chan, T. J., Zhang, X., & Mak, M. (2023). Biophysical informatics reveals distinctive phenotypic signatures and functional diversity of single-cell lineages. Bioinformatics., 39(1), btac833. https://doi.org/10.1093/bioinformatics/btac833

Article  CAS  PubMed  Google Scholar 

Huang, L., Liang, F., Feng, Y., Zhao, P., & Wang, W. (2020). On-chip integrated optical stretching and electrorotation enabling single-cell biophysical analysis. Microsystems & Nanoengineering, 6(1), 1–14. https://doi.org/10.1038/s41378-020-0162-2

Article  CAS  Google Scholar 

Mauritz, J. M. A., Tiffert, T., Seear, R., et al. (2010). Detection of Plasmodium falciparum-infected red blood cells by optical stretching. JBO., 15(3), 030517. https://doi.org/10.1117/1.3458919

Article  PubMed  Google Scholar 

Wu, P. H., Aroush, D. R. B., Asnacios, A., et al. (2018). Comparative study of cell mechanics methods. Nature Methods, 15(7), 491–498. https://doi.org/10.1038/s41592-018-0015-1

Article  CAS  PubMed  PubMed Central  Google Scholar 

Puig-De-Morales, M., Grabulosa, M., Alcaraz, J., et al. (2001). Measurement of cell microrheology by magnetic twisting cytometry with frequency domain demodulation. Journal of Applied Physiology., 91(3), 1152–1159. https://doi.org/10.1152/jappl.2001.91.3.1152

Article  CAS  PubMed  Google Scholar 

Tseng, Y., Kole, T. P., & Wirtz, D. (2002). Micromechanical mapping of live cells by multiple-particle-tracking microrheology. Biophysical Journal., 83(6), 3162–3176. https://doi.org/10.1016/S0006-3495(02)75319-8

Article  CAS  PubMed  PubMed Central