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  • Review Article
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Biomaterials to model and measure epithelial cancers

Nature Reviews Materials volume 3, pages 418–430 (2018)Cite this article

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Abstract

The use of biomaterials has substantially contributed to both our understanding of tumorigenesis and our ability to identify and capture tumour cells in vitro and in vivo. Natural and synthetic biomaterials can be applied as models to recapitulate key features of the tumour microenvironment in vitro, including architectural, mechanical and biological functions. Engineered biomaterials can further mimic the spatial and temporal properties of the surrounding tumour niche to investigate the specific effects of the environment on disease progression, offering an alternative to animal models for the testing of cancer cell behaviour. Biomaterials can also be used to capture and detect cancer cells in vitro and in vivo to monitor tumour progression. In this Review, we discuss the natural and synthetic biomaterials that can be used to recreate specific features of tumour microenvironments. We examine how biomaterials can be applied to capture circulating tumour cells in blood samples for the early detection of metastasis. We highlight biomaterial-based strategies to investigate local regions adjacent to the tumour and survey potential applications of biomaterial-based devices for diagnosis and prognosis, such as the detection of cellular deformability and the non-invasive surveillance of tumour-adjacent stroma.

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Fig. 1: Modelling the tumour microenvironment.
Fig. 2: Matrix stiffness regulates the epithelial-to-mesenchymal transition.

Figure is reproduced with permission from ref.3, Elsevier.

Fig. 3: Next-generation material-based cancer technologies.

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References

  1. Affo, S., Yu, L. X. & Schwabe, R. F. The role of cancer-associated fibroblasts and fibrosis in liver cancer. Annu. Rev. Pathol. 12, 153–186 (2017).

    CAS  Google Scholar 

  2. Pankova, D. et al. Cancer-associated fibroblasts induce a collagen cross-link switch in tumor stroma. Mol. Cancer Res. 14, 287–295 (2016).

    CAS  Google Scholar 

  3. Paszek, M. J. et al. Tensional homeostasis and the malignant phenotype. Cancer Cell 8, 241–254 (2005). This paper uses a hydrogel–Matrigel sandwich culture system to show that initial matrix stiffness can drive loss of mammary epithelial polarity.

    CAS  Google Scholar 

  4. Pickup, M. W., Mouw, J. K. & Weaver, V. M. The extracellular matrix modulates the hallmarks of cancer. EMBO Rep. 15, 1243–1253 (2014).

    CAS  Google Scholar 

  5. Levental, K. R. et al. Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 139, 891–906 (2009). This paper demonstrates that stiffer tissues can drive tumour growth and metastasis in vivo.

    CAS  Google Scholar 

  6. Mak, I. W., Evaniew, N. & Ghert, M. Lost in translation: animal models and clinical trials in cancer treatment. Am. J. Transl Res. 6, 114–118 (2014).

    Google Scholar 

  7. Bissell, M. J., Hall, H. G. & Parry, G. How does the extracellular matrix direct gene expression? J. Theor. Biol. 99, 31–68 (1982).

    CAS  Google Scholar 

  8. Kleinman, H. K. et al. Isolation and characterization of type IV procollagen, laminin, and heparan sulfate proteoglycan from the EHS sarcoma. Biochemistry 21, 6188–6193 (1982).

    CAS  Google Scholar 

  9. Orkin, R. W. et al. A murine tumor producing a matrix of basement membrane. J. Exp. Med. 145, 204–220 (1977).

    CAS  Google Scholar 

  10. Vukicevic, S. et al. Identification of multiple active growth factors in basement membrane Matrigel suggests caution in interpretation of cellular activity related to extracellular matrix components. Exp. Cell Res. 202, 1–8 (1992).

    CAS  Google Scholar 

  11. Barcellos-Hoff, M. H., Aggeler, J., Ram, T. G. & Bissell, M. J. Functional differentiation and alveolar morphogenesis of primary mammary cultures on reconstituted basement membrane. Development 105, 223–235 (1989).

    CAS  Google Scholar 

  12. Kenny, P. A. et al. The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression. Mol. Oncol. 1, 84–96 (2007).

    CAS  Google Scholar 

  13. Petersen, O. W., Ronnovjessen, L., Howlett, A. R. & Bissell, M. J. Interaction with basement membrane serves to rapidly distinguish growth and differentiation pattern of normal and malignant human breast epithelial cells. Proc. Natl Acad. Sci. USA 89, 9064–9068 (1992).

    CAS  Google Scholar 

  14. Paget, S. The distribution of secondary growths in cancer of the breast. Lancet 133, 571–573 (1889).

    Google Scholar 

  15. Kalluri, R. & Zeisberg, M. Fibroblasts in cancer. Nat. Rev. Cancer 6, 392–401 (2006).

    CAS  Google Scholar 

  16. Ozdemir, B. C. et al. Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival. Cancer Cell 25, 719–734 (2014).

    CAS  Google Scholar 

  17. Rhim, A. D. et al. Stromal elements act to restrain, rather than support, pancreatic ductal adenocarcinoma. Cancer Cell 25, 735–747 (2014).

    CAS  Google Scholar 

  18. Vennin, C. et al. Reshaping the tumor stroma for treatment of pancreatic cancer. Gastroenterology 54, 820–838 (2018).

    Google Scholar 

  19. Nguyen-Ngoc, K. V. et al. ECM microenvironment regulates collective migration and local dissemination in normal and malignant mammary epithelium. Proc. Natl Acad. Sci. USA 109, E2595–E2604 (2012).

    CAS  Google Scholar 

  20. Velez, D. O. et al. 3D collagen architecture induces a conserved migratory and transcriptional response linked to vasculogenic mimicry. Nat. Commun. 8, 1651 (2017).

    CAS  Google Scholar 

  21. Guzman, A., Ziperstein, M. J. & Kaufman, L. J. The effect of fibrillar matrix architecture on tumor cell invasion of physically challenging environments. Biomaterials 35, 6954–6963 (2014).

    CAS  Google Scholar 

  22. Mouw, J. K. et al. Tissue mechanics modulate microRNA-dependent PTEN expression to regulate malignant progression. Nat. Med. 20, 360–367 (2014).

    CAS  Google Scholar 

  23. Denais, C. M. et al. Nuclear envelope rupture and repair during cancer cell migration. Science 352, 353–358 (2016). This manuscript is the first to describe the mechanisms that enable cancer cells to migrate through pores in matrix that are smaller than the diameter of the nucleus.

    CAS  Google Scholar 

  24. Sodek, K. L., Brown, T. J. & Ringuette, M. J. Collagen I but not Matrigel matrices provide an MMP-dependent barrier to ovarian cancer cell penetration. BMC Cancer 8, 223 (2008).

    Google Scholar 

  25. Wolf, K. et al. Physical limits of cell migration: control by ECM space and nuclear deformation and tuning by proteolysis and traction force. J. Cell Biol. 201, 1069–1084 (2013).

    CAS  Google Scholar 

  26. Carey, S. P., Martin, K. E. & Reinhart-King, C. A. Three-dimensional collagen matrix induces a mechanosensitive invasive epithelial phenotype. Sci. Rep. 7, 42088 (2017).

    CAS  Google Scholar 

  27. Friedl, P. & Wolf, K. Plasticity of cell migration: a multiscale tuning model. J. Cell Biol. 188, 11–19 (2009).

    Google Scholar 

  28. Zaman, M. H. et al. Migration of tumor cells in 3D matrices is governed by matrix stiffness along with cell-matrix adhesion and proteolysis. Proc. Natl Acad. Sci. USA 103, 10889–10894 (2006).

    CAS  Google Scholar 

  29. Mason, B. N., Starchenko, A., Williams, R. M., Bonassar, L. J. & Reinhart-King, C. A. Tuning three-dimensional collagen matrix stiffness independently of collagen concentration modulates endothelial cell behavior. Acta Biomater. 9, 4635–4644 (2013).

    CAS  Google Scholar 

  30. Williams, C. M., Engler, A. J., Slone, R. D., Galante, L. L. & Schwarzbauer, J. E. Fibronectin expression modulates mammary epithelial cell proliferation during acinar differentiation. Cancer Res. 68, 3185–3192 (2008).

    CAS  Google Scholar 

  31. Fraley, S. I. et al. A distinctive role for focal adhesion proteins in three-dimensional cell motility. Nat. Cell Biol. 12, 598–604 (2010).

    CAS  Google Scholar 

  32. Anguiano, M. et al. Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis. PLOS One 12, e0171417 (2017).

    Google Scholar 

  33. Steinwachs, J. et al. Three-dimensional force microscopy of cells in biopolymer networks. Nat. Methods 13, 171–176 (2016).

    CAS  Google Scholar 

  34. Koch, T. M., Munster, S., Bonakdar, N., Butler, J. P. & Fabry, B. 3D Traction Forces in Cancer Cell Invasion. PLOS One 7, e33476 (2012).

    CAS  Google Scholar 

  35. Miller, J. P. et al. Clinical doses of radiation reduce collagen matrix stiffness. APL Bioeng. 2, 031901 (2018).

    Google Scholar 

  36. Beck, J. N., Singh, A., Rothenberg, A. R., Elisseeff, J. H. & Ewald, A. J. The independent roles of mechanical, structural and adhesion characteristics of 3D hydrogels on the regulation of cancer invasion and dissemination. Biomaterials 34, 9486–9495 (2013).

    CAS  Google Scholar 

  37. Wen, J. H. et al. Interplay of matrix stiffness and protein tethering in stem cell differentiation. Nat. Mater. 13, 979–987 (2014).

    CAS  Google Scholar 

  38. Taubenberger, A. V. et al. 3D extracellular matrix interactions modulate tumour cell growth, invasion and angiogenesis in engineered tumour microenvironments. Acta Biomater. 36, 73–85 (2016).

    CAS  Google Scholar 

  39. Loessner, D. et al. Bioengineered 3D platform to explore cell–ECM interactions and drug resistance of epithelial ovarian cancer cells. Biomaterials 31, 8494–8506 (2010).

    CAS  Google Scholar 

  40. Alcaraz, J. et al. Laminin and biomimetic extracellular elasticity enhance functional differentiation in mammary epithelia. EMBO J. 27, 2829–2838 (2008).

    CAS  Google Scholar 

  41. Reticker-Flynn, N. E. et al. A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis. Nat. Commun. 3, 1122 (2012). This paper highlights how non-additive matrix properties, specifically the combination of multiple matrix proteins, can drive metastatic behaviour.

    Google Scholar 

  42. Kraning-Rush, C. M., Califano, J. P. & Reinhart-King, C. A. Cellular traction stresses increase with increasing metastatic potential. PLOS One 7, e32572 (2012).

    CAS  Google Scholar 

  43. Leight, J. L., Wozniak, M. A., Chen, S., Lynch, M. L. & Chen, C. S. Matrix rigidity regulates a switch between TGF-β1-induced apoptosis and epithelial-mesenchymal transition. Mol. Biol. Cell 23, 781–791 (2012).

    CAS  Google Scholar 

  44. Stowers, R. S., Allen, S. C. & Suggs, L. J. Dynamic phototuning of 3D hydrogel stiffness. Proc. Natl Acad. Sci. USA 112, 1953–1958 (2015).

    CAS  Google Scholar 

  45. Wei, S. C. et al. Matrix stiffness drives epithelial–mesenchymal transition and tumor metastasis through a TWIST1–G3BP2 mechanotransduction pathway. Nat. Cell Biol. 17, 678–688 (2015).

    CAS  Google Scholar 

  46. Fenner, J. et al. Macroscopic stiffness of breast tumors predicts metastasis. Sci. Rep. 4, 5512 (2014).

    CAS  Google Scholar 

  47. Tse, J. R. & Engler, A. J. Preparation of hydrogel substrates with tunable mechanical properties. Curr. Protoc. Cell Biol 47, 10.16.1–10.16.16 (2010).

    Google Scholar 

  48. Emerman, J. T. & Pitelka, D. R. Maintenance and induction of morphological differentiation in dissociated mammary epithelium on floating collagen membranes. In Vitro 13, 316–328 (1977).

    CAS  Google Scholar 

  49. Bissell, M. J. The differentiated state of normal and malignant cells or how to define a “normal” cell in culture. Int. Rev. Cytol. 70, 27–100 (1981).

    CAS  Google Scholar 

  50. Pang, M. F. et al. Tissue stiffness and hypoxia modulate the integrin-linked kinase ILK to control breast cancer stem-like cells. Cancer Res. 76, 5277–5287 (2016).

    CAS  Google Scholar 

  51. Jabbari, E., Sarvestani, S. K., Daneshian, L. & Moeinzadeh, S. Optimum 3D matrix stiffness for maintenance of cancer stem cells is dependent on tissue origin of cancer cells. PLOS One 10, e0132377 (2015).

    Google Scholar 

  52. Shu, X. Z., Ahmad, S., Liu, Y. & Prestwich, G. D. Synthesis and evaluation of injectable, in situ crosslinkable synthetic extracellular matrices for tissue engineering. J. Biomed. Mater. Res. A 79, 902–912 (2006).

    Google Scholar 

  53. Young, J. L. & Engler, A. J. Hydrogels with time-dependent material properties enhance cardiomyocyte differentiation in vitro. Biomaterials 32, 1002–1009 (2011).

    CAS  Google Scholar 

  54. Guvendiren, M. & Burdick, J. A. Stiffening hydrogels to probe short- and long-term cellular responses to dynamic mechanics. Nat. Commun. 3, 792 (2012).

    Google Scholar 

  55. Ondeck, M. G. & Engler, A. J. Mechanical characterization of a dynamic and tunable methacrylated hyaluronic acid hydrogel. J. Biomech. Eng. 138, 021003 (2016).

    Google Scholar 

  56. Stowers, R. S. et al. Extracellular matrix stiffening induces a malignant phenotypic transition in breast epithelial cells. Cell. Mol. Bioeng. 10, 114–123 (2017). Temporal changes in matrix stiffness can modulate mammary epithelial cell responses in a different way than static materials, which when stiff, always induce phenotype transitions.

    CAS  Google Scholar 

  57. Kloxin, A. M., Kasko, A. M., Salinas, C. N. & Anseth, K. S. Photodegradable hydrogels for dynamic tuning of physical and chemical properties. Science 324, 59–63 (2009).

    CAS  Google Scholar 

  58. Maghdouri-White, Y., Elmore, L. W., Bowlin, G. L. & Dreau, D. Breast epithelial cell infiltration in enhanced electrospun silk scaffolds. J. Tissue Eng. Regen Med. 10, E121–131 (2016).

    CAS  Google Scholar 

  59. Chen, Z. et al. Electrospun nanofibers for cancer diagnosis and therapy. Biomater. Sci. 4, 922–932 (2016).

    CAS  Google Scholar 

  60. Kushiro, K., Yaginuma, T., Ryo, A. & Takai, M. Differences in three-dimensional geometric recognition by non-cancerous and cancerous epithelial cells on microgroove-based topography. Sci. Rep. 7, 4244 (2017).

    Google Scholar 

  61. Ning, D. et al. Mechanical and morphological analysis of cancer cells on nanostructured substrates. Langmuir 32, 2718–2723 (2016).

    CAS  Google Scholar 

  62. Chaudhuri, P. K., Pan, C. Q., Low, B. C. & Lim, C. T. Topography induces differential sensitivity on cancer cell proliferation via Rho-ROCK-Myosin contractility. Sci. Rep. 6, 19672 (2016).

    CAS  Google Scholar 

  63. Ulrich, T. A., Jaim, A., Tanner, K., MacKay, J. L. & Kumar, S. Probing cellular mechanobiology in three-dimensional culture with collagen-agarose matrices. Biomaterials 31, 1875–1884 (2010).

    CAS  Google Scholar 

  64. Pathak, A. & Kumar, S. Independent regulation of tumor cell migration by matrix stiffness and confinement. Proc. Natl Acad. Sci. USA 109, 10334–10339 (2012).

    CAS  Google Scholar 

  65. Attieh, Y. & Vignjevic, D. M. The hallmarks of CAFs in cancer invasion. Eur. J. Cell Biol. 95, 493–502 (2016).

    CAS  Google Scholar 

  66. Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

    CAS  Google Scholar 

  67. Gaggioli, C. et al. Fibroblast-led collective invasion of carcinoma cells with differing roles for RhoGTPases in leading and following cells. Nat. Cell Biol. 9, 1392–1400 (2007).

    CAS  Google Scholar 

  68. Goetz, J. G. et al. Biomechanical remodeling of the microenvironment by stromal caveolin-1 favors tumor invasion and metastasis. Cell 146, 148–163 (2011).

    CAS  Google Scholar 

  69. Glentis, A. et al. Cancer-associated fibroblasts induce metalloprotease-independent cancer cell invasion of the basement membrane. Nat. Commun. 8, 924 (2017).

    Google Scholar 

  70. Wang, K. et al. Stiffening and unfolding of early deposited-fibronectin increase proangiogenic factor secretion by breast cancer-associated stromal cells. Biomaterials 54, 63–71 (2015).

    CAS  Google Scholar 

  71. Labernadie, A. et al. A mechanically active heterotypic E-cadherin/N-cadherin adhesion enables fibroblasts to drive cancer cell invasion. Nat. Cell Biol. 19, 224–237 (2017).

    CAS  Google Scholar 

  72. Calvo, F. et al. Mechanotransduction and YAP-dependent matrix remodelling is required for the generation and maintenance of cancer-associated fibroblasts. Nat. Cell Biol. 15, 637–646 (2013).

    CAS  Google Scholar 

  73. Chen, M. B. et al. On-chip human microvasculature assay for visualization and quantification of tumor cell extravasation dynamics. Nat. Protoc. 12, 865–880 (2017).

    CAS  Google Scholar 

  74. Lee, H., Park, W., Ryu, H. & Jeon, N. L. A microfluidic platform for quantitative analysis of cancer angiogenesis and intravasation. Biomicrofluidics 8, 054102 (2014).

    Google Scholar 

  75. Zervantonakis, I. K. et al. Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function. Proc. Natl Acad. Sci. USA 109, 13515–13520 (2012).

    CAS  Google Scholar 

  76. Chen, M. B., Whisler, J. A., Jeon, J. S. & Kamm, R. D. Mechanisms of tumor cell extravasation in an in vitro microvascular network platform. Integr. Biol. 5, 1262–1271 (2013).

    CAS  Google Scholar 

  77. Bersini, S. et al. A microfluidic 3D in vitro model for specificity of breast cancer metastasis to bone. Biomaterials 35, 2454–2461 (2014).

    CAS  Google Scholar 

  78. Saquib, N., Saquib, J. & Ioannidis, J. P. Does screening for disease save lives in asymptomatic adults? Systematic review of meta-analyses and randomized trials. Int. J. Epidemiol. 44, 264–277 (2015).

    Google Scholar 

  79. Zhang, Z. et al. Expansion of CTCs from early stage lung cancer patients using a microfluidic co-culture model. Oncotarget 5, 12383–12397 (2014).

    Google Scholar 

  80. Mehta, S. et al. Predictive and prognostic molecular markers for cancer medicine. Ther. Adv. Med. Oncol. 2, 125–148 (2010).

    CAS  Google Scholar 

  81. Qian, W. Y., Zhang, Y. & Chen, W. Q. Capturing cancer: emerging microfluidic technologies for the capture and characterization of circulating tumor cells. Small 11, 3850–3872 (2015).

    CAS  Google Scholar 

  82. Chen, W. Q. et al. Nanoroughened surfaces for efficient capture of circulating tumor cells without using capture antibodies. ACS Nano 7, 566–575 (2013).

    CAS  Google Scholar 

  83. Park, G. S. et al. Full surface embedding of gold clusters on silicon nanowires for efficient capture and photothermal therapy of circulating tumor cells Nano Lett. 12, 2176–2176 (2012).

    CAS  Google Scholar 

  84. Zhai, T. T., Ye, D. K., Zhang, Q. W., Wu, Z. Q. & Xia, X. H. Highly efficient capture and electrochemical release of circulating tumor cells by using aptamers modified gold nanowire arrays. ACS Appl. Mater. Interfaces 9, 34706–34714 (2017).

    CAS  Google Scholar 

  85. Zhang, W., Zhao, K., Banks, C. E. & Zhang, Y. Antibody-modified hydroxyapatite surfaces for the efficient capture of bladder cancer cells in a patient’s urine without recourse to any sample pre-treatment. J. Mater. Chem. B 5, 8125–8132 (2017).

    CAS  Google Scholar 

  86. Xu, H. W. et al. Three-dimensional inverse opal photonic crystal substrates toward efficient capture of circulating tumor cells. ACS Appl. Mater. Interfaces 9, 30510–30518 (2017).

    CAS  Google Scholar 

  87. Zhang, J. et al. Surface chemistry induces mitochondria-mediated apoptosis of breast cancer cells via PTEN/PI3K/AKT signaling pathway. Biochim. Biophys. Acta Mol. Cell Res. 1865, 172–185 (2018).

    CAS  Google Scholar 

  88. Jan, Y. J. et al. NanoVelcro rare-cell assays for detection and characterization of circulating tumor cells. Adv. Drug Deliv. Rev. 125, 78–93 (2018).

    CAS  Google Scholar 

  89. Wang, L. X., Asghar, W., Demirci, U. & Wan, Y. Nanostructured substrates for isolation of circulating tumor cells. Nano Today 8, 374–387 (2013).

    CAS  Google Scholar 

  90. Wang, S. T. et al. Three-dimensional nanostructured substrates toward efficient capture of circulating tumor cells. Angew. Chem. Int. Ed. 48, 8970–8973 (2009).

    CAS  Google Scholar 

  91. Wang, S. T. et al. Highly efficient capture of circulating tumor cells by using nanostructured silicon substrates with integrated chaotic micromixers. Angew. Chem. Int. Ed. 50, 3084–3088 (2011).

    CAS  Google Scholar 

  92. Guo, S. et al. Degradable zinc-phosphate-based hierarchical nanosubstrates for capture and release of circulating tumor cells. ACS Appl. Mater. Interfaces 8, 15917–15925 (2016).

    CAS  Google Scholar 

  93. Lou, H. Y. et al. Dual-functional lipid coating for the nanopillar-based capture of circulating tumor cells with high purity and efficiency. Langmuir 33, 1097–1104 (2017).

    CAS  Google Scholar 

  94. Sun, N. et al. Chitosan nanofibers for specific capture and nondestructive release of CTCs assisted by pCBMA brushes. Small 12, 5090–5097 (2016).

    CAS  Google Scholar 

  95. Rao, S. S. et al. Enhanced survival with implantable scaffolds that capture metastatic breast cancer cells in vivo. Cancer Res. 76, 5209–5218 (2016).

    CAS  Google Scholar 

  96. Azarin, S. M. et al. In vivo capture and label-free detection of early metastatic cells. Nat. Commun. 6, 8094 (2015). This paper describes an implantable hydrogel-based method to capture cells that have intravasated from tumours.

    Google Scholar 

  97. Aguado, B. A. et al. Extracellular matrix mediators of metastatic cell colonization characterized using scaffold mimics of the pre-metastatic niche. Acta Biomater. 33, 13–24 (2016).

    CAS  Google Scholar 

  98. Qian, B. Z. et al. CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis. Nature 475, 222–U129 (2011).

    CAS  Google Scholar 

  99. Kitamura, T., Qian, B. Z. & Pollard, J. W. Immune cell promotion of metastasis. Nat. Rev. Immunol. 15, 73–86 (2015).

    CAS  Google Scholar 

  100. Hiratsuka, S., Watanabe, A., Aburatani, H. & Maru, Y. Tumour-mediated upregulation of chemoattractants and recruitment of myeloid cells predetermines lung metastasis. Nat. Cell Biol. 8, 1369–U1331 (2006).

    CAS  Google Scholar 

  101. Mauro, N., Scialabba, C., Pitarresi, G. & Giammona, G. Enhanced adhesion and in situ photothermal ablation of cancer cells in surface-functionalized electrospun microfiber scaffold with graphene oxide. Int. J. Pharm. 526, 167–177 (2017).

    CAS  Google Scholar 

  102. Ma, H. S. et al. A bifunctional biomaterial with photothermal effect for tumor therapy and bone regeneration. Adv. Funct. Mater. 26, 1197–1208 (2016).

    CAS  Google Scholar 

  103. Aguado, B. A. et al. Secretome identification of immune cell factors mediating metastatic cell homing. Sci. Rep. 5, 17566 (2015).

    CAS  Google Scholar 

  104. de la Fuente, A. et al. M-trap: exosome-based capture of tumor cells as a new technology in peritoneal metastasis. J. Natl Cancer Inst. 107, djv184 (2015).

    Google Scholar 

  105. Seib, F. P., Berry, J. E., Shiozawa, Y., Taichman, R. S. & Kaplan, D. L. Tissue engineering a surrogate niche for metastatic cancer cells. Biomaterials 51, 313–319 (2015).

    CAS  Google Scholar 

  106. Aguado, B. A., Bushnell, G. G., Rao, S. S., Jeruss, J. S. & Shea, L. D. Engineering the pre-metastatic niche. Nat. Biomed. Eng. 1, 0077 (2017).

    Google Scholar 

  107. Davidson, P. M., Denais, C., Bakshi, M. C. & Lammerding, J. Nuclear deformability constitutes a rate-limiting step during cell migration in 3-D environments. Cell. Mol. Bioeng. 7, 293–306 (2014).

    CAS  Google Scholar 

  108. Yao, N. et al. Structure and function analysis in circulating tumor cells: using nanotechnology to study nuclear size in prostate cancer. Am. J. Clin. Exp. Urol. 6, 43–54 (2018).

    Google Scholar 

  109. Chen, J. F. et al. Subclassification of prostate cancer circulating tumor cells by nuclear size reveals very small nuclear circulating tumor cells in patients with visceral metastases. Cancer 121, 3240–3251 (2015).

    Google Scholar 

  110. Alibert, C., Goud, B. & Manneville, J. B. Are cancer cells really softer than normal cells? Biol. Cell 109, 167–189 (2017).

    Google Scholar 

  111. Guo, Q., Park, S. & Ma, H. S. Microfluidic micropipette aspiration for measuring the deformability of single cells. Lab. Chip 12, 2687–2695 (2012).

    CAS  Google Scholar 

  112. Mak, M. & Erickson, D. A serial micropipette microfluidic device with applications to cancer cell repeated deformation studies. Integr. Biol. 5, 1374–1384 (2013).

    CAS  Google Scholar 

  113. Malboubi, M., Jayo, A., Parsons, M. & Charras, G. An open access microfiuidic device for the study of the physical limits of cancer cell deformation during migration in confined environments. Microelectron. Eng. 144, 42–45 (2015).

    CAS  Google Scholar 

  114. Gossett, D. R. et al. Hydrodynamic stretching of single cells for large population mechanical phenotyping. Proc. Natl Acad. Sci. USA 109, 7630–7635 (2012). This paper demonstrates a high-throughput single cell microfluidic-based deformability cytometry assay showing that mechanical properties of cells can be used to separate populations with different metastatic potentials.

    CAS  Google Scholar 

  115. Dudani, J. S., Gossett, D. R., Tse, H. T. K. & Di Carlo, D. Pinched-flow hydrodynamic stretching of single-cells. Lab. Chip 13, 3728–3734 (2013).

    CAS  Google Scholar 

  116. Qi, D. et al. Screening cell mechanotype by parallel microfiltration. Sci. Rep. 5, 17595 (2015).

    CAS  Google Scholar 

  117. Nyberg, K. D. et al. The physical origins of transit time measurements for rapid, single cell mechanotyping. Lab. Chip 16, 3330–3339 (2016).

    CAS  Google Scholar 

  118. Palmer, C. P. et al. Single cell adhesion measuring apparatus (SCAMA): application to cancer cell lines of different metastatic potential and voltage-gated Na+ channel expression. Eur. Biophys. J. 37, 359–368 (2008).

    CAS  Google Scholar 

  119. Veiseh, M. et al. Cellular heterogeneity profiling by hyaluronan probes reveals an invasive but slow-growing breast tumor subset. Proc. Natl Acad. Sci. USA 111, E1731–E1739 (2014).

    CAS  Google Scholar 

  120. Bijian, K. et al. Targeting focal adhesion turnover in invasive breast cancer cells by the purine derivative reversine. Br. J. Cancer 109, 2810–2818 (2013).

    CAS  Google Scholar 

  121. Fuhrmann, A., Banisadr, A., Beri, P., Tlsty, T. D. & Engler, A. J. Metastatic state of cancer cells may be indicated by adhesion strength. Biophys. J. 112, 736–745 (2017).

    CAS  Google Scholar 

  122. Seltzer, M. H., Rosato, F. E. & Fletcher, M. J. Serum and tissue magnesium levels in human breast carcinoma. J. Surg. Res. 10, 159–162 (1970).

    CAS  Google Scholar 

  123. Seltzer, M. H., Rosato, F. E. & Fletcher, M. J. Serum and tissue calcium in human breast carcinoma. Cancer Res. 30, 615–616 (1970).

    CAS  Google Scholar 

  124. Zhou, Z. X. & Lu, Z. R. Molecular imaging of the tumor microenvironment. Adv. Drug Deliv. Rev. 113, 24–48 (2017).

    CAS  Google Scholar 

  125. Chaabane, L. et al. In vivo MR imaging of fibrin in a neuroblastoma tumor model by means of a targeting Gd-containing peptide. Mol. Imag. Biol. 17, 819–828 (2015).

    CAS  Google Scholar 

  126. Starmans, L. W. E. et al. Noninvasive visualization of tumoral fibrin deposition using a peptidic fibrin-binding single photon emission computed tomography tracer. Mol. Pharm. 12, 1921–1928 (2015).

    CAS  Google Scholar 

  127. Obonai, T. et al. Tumour imaging by the detection of fibrin clots in tumour stroma using an anti-fibrin Fab fragment. Sci. Rep. 6, 23613 (2016).

    CAS  Google Scholar 

  128. van Mourik, T. R., Claesener, M., Nicolay, K. & Grull, H. Development of a novel, fibrin-specific PET tracer. J. Labelled Comp. Radiopharm. 60, 286–293 (2017).

    Google Scholar 

  129. Zhou, Z. X. et al. MRI detection of breast cancer micrometastases with a fibronectin-targeting contrast agent. Nat. Commun. 6, 7984 (2015).

    CAS  Google Scholar 

  130. Li, C. L. et al. Fibronectin induces epithelial-mesenchymal transition in human breast cancer MCF-7 cells via activation of calpain. Oncol. Lett. 13, 3889–3895 (2017).

    CAS  Google Scholar 

  131. Han, Z. & Lu, Z. R. Targeting fibronectin for cancer imaging and therapy. J. Mater. Chem. B 5, 639–654 (2017).

    CAS  Google Scholar 

  132. Heidari, P. et al. Imaging of secreted extracellular periostin, an important marker of invasion in the tumor microenvironment in esophageal cancer. J. Nuclear Med. 56, 1246–1251 (2015).

    CAS  Google Scholar 

  133. Khawar, I. A., Kim, J. H. & Kuh, H. J. Improving drug delivery to solid tumors: priming the tumor microenvironment. J. Control. Release 201, 78–89 (2015).

    CAS  Google Scholar 

  134. Grossman, M. et al. Tumor cell invasion can be blocked by modulators of collagen fibril alignment that control assembly of the extracellular matrix. Cancer Res. 76, 4249–4258 (2016).

    CAS  Google Scholar 

  135. Theocharis, A. D., Skandalis, S. S., Gialeli, C. & Karamanos, N. K. Extracellular matrix structure. Adv. Drug Deliv. Rev. 97, 4–27 (2016).

    CAS  Google Scholar 

  136. Provenzano, P. P. et al. Enzymatic targeting of the stroma ablates physical barriers to treatment of pancreatic ductal adenocarcinoma. Cancer Cell 21, 418–429 (2012).

    CAS  Google Scholar 

  137. Jacobetz, M. A. et al. Hyaluronan impairs vascular function and drug delivery in a mouse model of pancreatic cancer. Gut 62, 112–120 (2013).

    CAS  Google Scholar 

  138. Hingorani, S. R. et al. Phase Ib study of PEGylated recombinant human hyaluronidase and gemcitabine in patients with advanced pancreatic cancer. Clin. Cancer Res. 22, 2848–2854 (2016).

    CAS  Google Scholar 

  139. Lee, S. et al. Extracellular matrix remodeling in vivo for enhancing tumor-targeting efficiency of nanoparticle drug carriers using the pulsed high intensity focused ultrasound. J. Control. Release 263, 68–78 (2017).

    CAS  Google Scholar 

  140. Baronzio, G., Parmar, G. & Baronzio, M. Overview of methods for overcoming hindrance to drug delivery to tumors, with special attention to tumor interstitial fluid. Front. Oncol. 5, 165 (2015).

    Google Scholar 

  141. Yhee, J. Y. et al. Effects of tumor microenvironments on targeted delivery of glycol chitosan nanoparticles. J. Control. Release 267, 223–231 (2017).

    CAS  Google Scholar 

  142. Nicolas-Boluda, A., Silva, A. K. A., Fournel, S. & Gazeau, F. Physical oncology: new targets for nanomedicine. Biomaterials 150, 87–99 (2018).

    CAS  Google Scholar 

  143. Marangon, I. et al. Tumor stiffening, a key determinant of tumor progression, is reversed by nanomaterial-induced photothermal therapy. Theranostics 7, 329–343 (2017).

    CAS  Google Scholar 

  144. Raeesi, V. & Chan, W. C. W. Improving nanoparticle diffusion through tumor collagen matrix by photo-thermal gold nanorods. Nanoscale 8, 12524–12530 (2016).

    CAS  Google Scholar 

  145. Schuh, J. C. Trials, tribulations, and trends in tumor modeling in mice. Toxicol. Pathol. 32, 53–66 (2004).

    CAS  Google Scholar 

  146. Day, C. P., Merlino, G. & Van Dyke, T. Preclinical mouse cancer models: a maze of opportunities and challenges. Cell 163, 39–53 (2015).

    CAS  Google Scholar 

  147. Quintana, E. et al. Efficient tumour formation by single human melanoma cells. Nature 456, 593–598 (2008).

    CAS  Google Scholar 

  148. Tzvetkova-Chevolleau, T. et al. The motility of normal and cancer cells in response to the combined influence of the substrate rigidity and anisotropic microstructure. Biomaterials 29, 1541–1551 (2008).

    CAS  Google Scholar 

  149. Zhu, J. Bioactive modification of poly(ethylene glycol) hydrogels for tissue engineering. Biomaterials 31, 4639–4656 (2010).

    CAS  Google Scholar 

  150. Lewis, K. J. R. et al. Epithelial-mesenchymal crosstalk influences cellular behavior in a 3D alveolus-fibroblast model system. Biomaterials 155, 124–134 (2018).

    CAS  Google Scholar 

  151. Fischbach, C. et al. Engineering tumors with 3D scaffolds. Nat. Methods 4, 855–860 (2007).

    CAS  Google Scholar 

  152. Makadia, H. K. & Siegel, S. J. Poly lactic-co-glycolic acid (PLGA) as biodegradable controlled drug delivery carrier. Polymers 3, 1377–1397 (2011).

    CAS  Google Scholar 

  153. Choi, Y. S. et al. The alignment and fusion assembly of adipose-derived stem cells on mechanically patterned matrices. Biomaterials 33, 6943–6951 (2012).

    CAS  Google Scholar 

  154. Nasrollahi, S. et al. Past matrix stiffness primes epithelial cells and regulates their future collective migration through a mechanical memory. Biomaterials 146, 146–155 (2017).

    CAS  Google Scholar 

  155. Zustiak, S., Nossal, R. & Sackett, D. L. Multiwell stiffness assay for the study of cell responsiveness to cytotoxic drugs. Biotechnol. Bioeng. 111, 396–403 (2014).

    CAS  Google Scholar 

  156. Chaudhuri, O. et al. Extracellular matrix stiffness and composition jointly regulate the induction of malignant phenotypes in mammary epithelium. Nat. Mater. 13, 970–978 (2014).

    CAS  Google Scholar 

  157. Fang, J. Y., Tan, S. J., Yang, Z., Tayag, C. & Han, B. Tumor bioengineering using a transglutaminase crosslinked hydrogel. PLOS One 9, e105616 (2014).

    Google Scholar 

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Acknowledgements

Funding for this work was provided by US National Institutes of Health grants R01CA206880 (A.J.E. and J.Y.) and R21CA217735 (A.J.E.), a US National Science Foundation grant 1463689 (A.J.E.) and the Graduate Research Fellowship programme (P.B.). Additional fellowship support was provided by Brazilian Federal Agency for Support and Evaluation of Graduate Education award 88881.135357/2016-01 (B.F.M.).

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Authors and Affiliations

  1. Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA

    Pranjali Beri, Bibiana F. Matte & Adam J. Engler

  2. Department of Oral Pathology, Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Bibiana F. Matte

  3. Department of Pharmacology, University of California, San Diego, La Jolla, CA, USA

    Laurent Fattet, Daehwan Kim & Jing Yang

  4. Moores Cancer Center, University of California, San Diego, La Jolla, CA, USA

    Laurent Fattet, Daehwan Kim, Jing Yang & Adam J. Engler

  5. Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA

    Adam J. Engler

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P.B., J.Y. and A.J.E. organized the manuscript content. The manuscript was written by all authors.

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Correspondence to Adam J. Engler.

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Beri, P., Matte, B.F., Fattet, L. et al. Biomaterials to model and measure epithelial cancers. Nat Rev Mater 3, 418–430 (2018). https://doi.org/10.1038/s41578-018-0051-6

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