Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Dissecting and rebuilding the glioblastoma microenvironment with engineered materials

Nature Reviews Materials volume 4, pages 651–668 (2019)Cite this article

Subjects

A Publisher Correction to this article was published on 24 September 2020

A Publisher Correction to this article was published on 04 September 2020

This article has been updated

Abstract

Glioblastoma (GBM) is the most aggressive and common form of primary brain cancer. Several decades of research have provided great insight into GBM progression; however, the prognosis remains poor, with a median patient survival time of ~15 months. The tumour microenvironment (TME) of GBM plays a crucial role in mediating tumour progression and thus is being explored as a therapeutic target. Progress in the development of treatments targeting the TME is currently limited by a lack of model systems that can accurately recreate the distinct extracellular matrix composition and anatomic features of the brain, such as the blood–brain barrier and axonal tracts. Biomaterials can be applied to develop synthetic models of the GBM TME to mimic physiological and pathophysiological features of the brain, including cellular and extracellular matrix composition, mechanical properties and topography. In this Review, we summarize key features of the GBM microenvironment and discuss different strategies for the engineering of GBM TME models, including 2D and 3D models featuring chemical and mechanical gradients, interfaces and fluid flow. Finally, we highlight the potential of engineered TME models as platforms for mechanistic discovery and drug screening, as well as preclinical testing and precision medicine.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Schematic of glioblastoma regions.
Fig. 2: Engineered glioblastoma models.
Fig. 3: Glioblastoma microenvironment models in the preclinical and clinical pipeline.

Similar content being viewed by others

Change history

  • 24 September 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

  • 04 September 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Ostrom, Q. T. et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the united states in 2011–2015. Neuro. Oncol. 20, iv1–iv86 (2018).

    Google Scholar 

  2. Koshy, M. et al. Improved survival time trends for glioblastoma using the SEER 17 population-based registries. J. Neurooncol. 107, 207–212 (2012).

    Google Scholar 

  3. Stupp, R. et al. Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol. 10, 459–466 (2009).

    CAS  Google Scholar 

  4. Watanabe, M., Tanaka, R. & Takeda, N. Magnetic resonance imaging and histopathology of cerebral gliomas. Neuroradiology 34, 463–469 (1992).

    CAS  Google Scholar 

  5. Young, R. M., Jamshidi, A., Davis, G. & Sherman, J. H. Current trends in the surgical management and treatment of adult glioblastoma. Ann. Transl. Med. 3, 121 (2015).

    Google Scholar 

  6. Sherriff, J. et al. Patterns of relapse in glioblastoma multiforme following concomitant chemoradiotherapy with temozolomide. Br. J. Radiol. 86, 20120414 (2013).

    CAS  Google Scholar 

  7. Eyler, C. E. & Rich, J. N. Survival of the fittest: cancer stem cells in therapeutic resistance and angiogenesis. J. Clin. Oncol. 26, 2839–2845 (2008).

    CAS  Google Scholar 

  8. Franceschi, E. et al. Treatment options for recurrent glioblastoma: pitfalls and future trends. Expert Rev. Anticancer. Ther. 9, 613–619 (2009).

    Google Scholar 

  9. Quail, D. F. & Joyce, J. A. The microenvironmental landscape of brain tumors. Cancer Cell 31, 326–341 (2017).

    CAS  Google Scholar 

  10. Levental, K. R. et al. Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 139, 891–906 (2009).

    CAS  Google Scholar 

  11. Nakasone, E. S. et al. Imaging tumor–stroma interactions during chemotherapy reveals contributions of the microenvironment to resistance. Cancer Cell 21, 488–503 (2012).

    CAS  Google Scholar 

  12. Ghajar, C. M. et al. The perivascular niche regulates breast tumour dormancy. Nat. Cell Biol. 15, 807–817 (2013).

    CAS  Google Scholar 

  13. Provenzano, P. P., Inman, D. R., Eliceiri, K. W. & Keely, P. J. Matrix density-induced mechanoregulation of breast cell phenotype, signaling and gene expression through a FAK–ERK linkage. Oncogene 28, 4326–4343 (2009).

    CAS  Google Scholar 

  14. Elahi-Gedwillo, K. Y., Carlson, M., Zettervall, J. & Provenzano, P. P. Antifibrotic therapy disrupts stromal barriers and modulates the immune landscape in pancreatic ductal adenocarcinoma. Cancer Res. 79, 372–386 (2019).

    CAS  Google Scholar 

  15. 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 

  16. De Vleeschouwer, S. & Bergers, G. in Glioblastoma Ch. 16 (ed De Vleeschouwer, S.) (Codon Publications, 2017).

  17. Jain, A. et al. Guiding intracortical brain tumour cells to an extracortical cytotoxic hydrogel using aligned polymeric nanofibres. Nat. Mater. 13, 308–316 (2014).

    CAS  Google Scholar 

  18. Gritsenko, P. G., Ilina, O. & Friedl, P. Interstitial guidance of cancer invasion. J. Pathol. 226, 185–199 (2012).

    CAS  Google Scholar 

  19. Bellail, A. C., Hunter, S. B., Brat, D. J., Tan, C. & Van Meir, E. G. Microregional extracellular matrix heterogeneity in brain modulates glioma cell invasion. Int. J. Biochem. Cell Biol. 36, 1046–1069 (2004).

    CAS  Google Scholar 

  20. van Tellingen, O. et al. Overcoming the blood–brain tumor barrier for effective glioblastoma treatment. Drug Resist. Updat. 19, 1–12 (2015).

    Google Scholar 

  21. de Vries, N. A., Beijnen, J. H., Boogerd, W. & van Tellingen, O. Blood–brain barrier and chemotherapeutic treatment of brain tumors. Expert Rev. Neurother. 6, 1199–1209 (2006).

    Google Scholar 

  22. Nimsky, C. et al. Preoperative and intraoperative diffusion tensor imaging-based fiber tracking in glioma surgery. Neurosurg. 56, 130–138 (2005).

    Google Scholar 

  23. Giese, A. & Westphal, M. Glioma invasion in the central nervous system. Neurosurg. 39, 235–252 (1996).

    Google Scholar 

  24. Miller, K., Chinzei, K., Orssengo, G. & Bednarz, P. Mechanical properties of brain tissue in-vivo: experiment and computer simulation. J. Biomech. 33, 1369–1376 (2000).

    CAS  Google Scholar 

  25. Budday, S. et al. Mechanical properties of gray and white matter brain tissue by indentation. J. Mech. Behav. Biomed. Mater. 46, 318–330 (2015).

    Google Scholar 

  26. Bernstein, J. J. & Woodard, C. A. Glioblastoma cells do not intravasate into blood vessels. Neurosurg. 36, 124–132 (1995).

    CAS  Google Scholar 

  27. Nakod, P. S., Kim, Y. & Rao, S. S. Biomimetic models to examine microenvironmental regulation of glioblastoma stem cells. Cancer Lett. 429, 41–53 (2018).

    CAS  Google Scholar 

  28. Lenting, K., Verhaak, R., ter Laan, M., Wesseling, P. & Leenders, W. Glioma: experimental models and reality. Acta Neuropathol. 133, 263–282 (2017).

    Google Scholar 

  29. Xiao, W., Sohrabi, A. & Seidlits, S. K. Integrating the glioblastoma microenvironment into engineered experimental models. Future Sci. OA 3, FSO189 (2017).

    CAS  Google Scholar 

  30. Novak, U. & Kaye, A. H. Extracellular matrix and the brain: components and function. J. Clin. Neurosci. 7, 280–290 (2000).

    CAS  Google Scholar 

  31. Zimmermann, D. R. & Dours-Zimmermann, M. T. Extracellular matrix of the central nervous system: from neglect to challenge. Histochem. Cell Biol. 130, 635–653 (2008).

    CAS  Google Scholar 

  32. Bertolotto, A., Magrassi, M. L., Orsi, L., Sitia, C. & Schiffer, D. Glycosaminoglycan changes in human gliomas. A biochemical study. J. Neurooncol. 4, 43–48 (1986).

    CAS  Google Scholar 

  33. Chintala, S. K., Sawaya, R., Gokaslan, Z. L., Fuller, G. & Rao, J. S. Immunohistochemical localization of extracellular matrix proteins in human glioma, both in vivo and in vitro. Cancer Lett. 101, 107–114 (1996).

    CAS  Google Scholar 

  34. Mahesparan, R. et al. Expression of extracellular matrix components in a highly infiltrative in vivo glioma model. Acta Neuropathol. 105, 49–57 (2003).

    CAS  Google Scholar 

  35. Cowman, M. K., Lee, H.-G., Schwertfeger, K. L., McCarthy, J. B. & Turley, E. A. The content and size of hyaluronan in biological fluids and tissues. Front. Immunol. 6, 261 (2015).

    Google Scholar 

  36. Dicker, K. T. et al. Hyaluronan: A simple polysaccharide with diverse biological functions. Acta Biomater. 10, 1558–1570 (2014).

    CAS  Google Scholar 

  37. Akiyama, Y. et al. Hyaluronate receptors mediating glioma cell migration and proliferation. J. Neurooncol. 53, 115–127 (2001).

    CAS  Google Scholar 

  38. Breyer, R. et al. Disruption of intracerebral progression of rat C6 glioblastoma by in vivo treatment with anti-CD44 monoclonal antibody. J. Neurosurg. 62, 140–149 (2000).

    Google Scholar 

  39. Ponta, H., Sherman, L. & Herrlich, P. A. CD44: from adhesion molecules to signalling regulators. Nat. Rev. Mol. Cell Biol. 4, 33–45 (2003).

    CAS  Google Scholar 

  40. Delpech, B. et al. Hyaluronan and hyaluronectin in the extracellular matrix of human brain tumour stroma. Eur. J. Cancer 29A, 1012–1017 (1993).

    CAS  Google Scholar 

  41. Yoo, K.-C. et al. Proinvasive extracellular matrix remodeling in tumor microenvironment in response to radiation. Oncogene 37, 3317–3328 (2018).

    CAS  Google Scholar 

  42. Valkonen, M. et al. Elevated expression of hyaluronan synthase 2 associates with decreased survival in diffusely infiltrating astrocytomas. BMC Cancer 18, 664 (2018).

    Google Scholar 

  43. Tian, X. et al. High-molecular-mass hyaluronan mediates the cancer resistance of the naked mole rat. Nature 499, 346–349 (2013).

    CAS  Google Scholar 

  44. Chanmee, T., Ontong, P. & Itano, N. Mini-review. Hyaluronan: a modulator of the tumor microenvironment. Cancer Lett. 375, 20–30 (2016).

    CAS  Google Scholar 

  45. Chen, J.-W. E. et al. Influence of hyaluronic acid transitions in tumor microenvironment on glioblastoma malignancy and invasive behavior. Front. Mater 5, 39 (2018).

    Google Scholar 

  46. Gladson, C. L. The extracellular matrix of gliomas: modulation of cell function. J. Neuropathol. Exp. Neurol. 58, 1029–1040 (1999).

    CAS  Google Scholar 

  47. Ljubimova, J. Y., Fujita, M., Khazenzon, N. M., Ljubimov, A. V. & Black, K. L. Changes in laminin isoforms associated with brain tumor invasion and angiogenesis. Front. Biosci. 11, 81–88 (2006).

    CAS  Google Scholar 

  48. Gamble, J. T. et al. Quantification of glioblastoma progression in zebrafish xenografts: Adhesion to laminin alpha 5 promotes glioblastoma microtumor formation and inhibits cell invasion. Biochem. Biophys. Res. Commun. 506, 833–839 (2018).

    CAS  Google Scholar 

  49. Lathia, J. D. et al. Laminin alpha 2 enables glioblastoma stem cell growth. Ann. Neurol. 72, 766–778 (2012).

    CAS  Google Scholar 

  50. Lathia, J. D. et al. Integrin alpha 6 regulates glioblastoma stem cells. Cell Stem Cell 6, 421–432 (2010).

    CAS  Google Scholar 

  51. Shannon, S. et al. Dexamethasone-mediated activation of fibronectin matrix assembly reduces dispersal of primary human glioblastoma cells. PLoS One 10, e0135951 (2015).

    Google Scholar 

  52. Serres, E. et al. Fibronectin expression in glioblastomas promotes cell cohesion, collective invasion of basement membrane in vitro and orthotopic tumor growth in mice. Oncogene 33, 3451–3462 (2014).

    CAS  Google Scholar 

  53. Sabari, J. et al. Fibronectin matrix assembly suppresses dispersal of glioblastoma cells. PLoS One 6, e24810 (2011).

    CAS  Google Scholar 

  54. Yuan, L. et al. Transglutaminase 2 inhibitor, KCC009, disrupts fibronectin assembly in the extracellular matrix and sensitizes orthotopic glioblastomas to chemotherapy. Oncogene 26, 2563–2573 (2007).

    CAS  Google Scholar 

  55. Ogawa, K., Oguchi, M., Nakashima, Y. & Yamabe, H. Distribution of collagen Type IV in brain tumors: An immunohistochemical study. J. Neurooncol. 7, 357–366 (1989).

    CAS  Google Scholar 

  56. Rojiani, A. M. & Dorovini-Zis, K. Glomeruloid vascular structures in glioblastoma multiforme: an immunohistochemical and ultrastructural study. J. Neurosurg. 85, 1078–1084 (1996).

    CAS  Google Scholar 

  57. Pointer, K. B. et al. Association of collagen architecture with glioblastoma patient survival. J Neurosurg 126, 1812–1821 (2017).

    Google Scholar 

  58. Rauch, U. Brain matrix: structure, turnover and necessity. Biochem. Soc. Trans. 35, 656–660 (2007).

    CAS  Google Scholar 

  59. Lundell, A. et al. Structural basis for interactions between tenascins and lectican C-type lectin domains: evidence for a crosslinking role for tenascins. Structure 12, 1495–1506 (2004).

    CAS  Google Scholar 

  60. Miroshnikova, Y. A. et al. Tissue mechanics promote IDH1-dependent HIF1α–tenascin C feedback to regulate glioblastoma aggression. Nat. Cell Biol. 18, 1336–1345 (2016).

    CAS  Google Scholar 

  61. Mirzaei, R. et al. Brain tumor-initiating cells export tenascin-C associated with exosomes to suppress T cell activity. Oncoimmunology 7, e1478647 (2018).

    Google Scholar 

  62. Sarkar, S., Nuttall, R. K., Liu, S., Edwards, D. R. & Yong, V. W. Tenascin-C stimulates glioma cell invasion through matrix metalloproteinase-12. Cancer Res. 66, 11771–11780 (2006).

    CAS  Google Scholar 

  63. Rascher, G. et al. Extracellular matrix and the blood–brain barrier in glioblastoma multiforme: spatial segregation of tenascin and agrin. Acta Neuropathol. 104, 85–91 (2002).

    CAS  Google Scholar 

  64. Pen, A., Moreno, M. J., Martin, J. & Stanimirovic, D. B. Molecular markers of extracellular matrix remodeling in glioblastoma vessels: microarray study of laser-captured glioblastoma vessels. Glia 55, 559–572 (2007).

    Google Scholar 

  65. Pietras, A. et al. Osteopontin-CD44 signaling in the glioma perivascular niche enhances cancer stem cell phenotypes and promotes aggressive tumor growth. Cell Stem Cell 14, 357–369 (2014).

    CAS  Google Scholar 

  66. Wei, J. et al. Osteopontin mediates glioblastoma-associated macrophage infiltration and is a potential therapeutic target. J. Clin. Invest. 129, 137–149 (2018).

    Google Scholar 

  67. Lamour, V. et al. Targeting osteopontin suppresses glioblastoma stem-like cell character and tumorigenicity in vivo. Int. J. Cancer 137, 1047–1057 (2015).

    CAS  Google Scholar 

  68. Oyinlade, O. et al. Targeting UDP-α-d-glucose 6-dehydrogenase inhibits glioblastoma growth and migration. Oncogene 37, 2615–2629 (2018).

    CAS  Google Scholar 

  69. Chauvet, D. et al. In vivo measurement of brain tumor elasticity using intraoperative shear wave elastography. Eur. J. Ultrasound 37, 584–590 (2015).

    Google Scholar 

  70. Stewart, D. C., Rubiano, A., Dyson, K. & Simmons, C. S. Mechanical characterization of human brain tumors from patients and comparison to potential surgical phantoms. PLoS One 12, e0177561 (2017).

    Google Scholar 

  71. Ciasca, G. et al. Nano-mechanical signature of brain tumours. Nanoscale 8, 19629–19643 (2016).

    CAS  Google Scholar 

  72. Ulrich, T. A. et al. The mechanical rigidity of the extracellular matrix regulates the structure, motility, and proliferation of glioma cells. Cancer Res. 69, 4167–4174 (2009).

    CAS  Google Scholar 

  73. Thomas, T. W. & DiMilla, P. A. Spreading and motility of human glioblastoma cells on sheets of silicone rubber depend on substratum compliance. Med. Biol. Eng. Comput. 38, 360–370 (2000).

    CAS  Google Scholar 

  74. Grundy, T. J. et al. Differential response of patient-derived primary glioblastoma cells to environmental stiffness. Sci. Rep. 6, 23353 (2016).

    CAS  Google Scholar 

  75. Wong, S. Y. et al. Constitutive activation of myosin-dependent contractility sensitizes glioma tumor-initiating cells to mechanical inputs and reduces tissue invasion. Cancer Res. 75, 1113–1122 (2015).

    CAS  Google Scholar 

  76. Ruiz-Ontañon, P. et al. Cellular plasticity confers migratory and invasive advantages to a population of glioblastoma-initiating cells that infiltrate peritumoral tissue. Stem Cells 31, 1075–1085 (2013).

    Google Scholar 

  77. Kim, Y. & Kumar, S. CD44-mediated adhesion to hyaluronic acid contributes to mechanosensing and invasive motility. Mol. Cancer Res. 12, 1416–1429 (2014).

    CAS  Google Scholar 

  78. Umesh, V., Rape, A. D., Ulrich, T. A. & Kumar, S. Microenvironmental stiffness enhances glioma cell proliferation by stimulating epidermal growth factor receptor signaling. PLoS One 9, e101771 (2014).

    Google Scholar 

  79. Mammoto, T. et al. Role of collagen matrix in tumor angiogenesis and glioblastoma multiforme progression. Am. J. Pathol. 183, 1293–1305 (2013).

    CAS  Google Scholar 

  80. Seano, G. et al. Solid stress in brain tumours causes neuronal loss and neurological dysfunction and can be reversed by lithium. Nat. Biomed. Eng. 3, 230–245 (2019).

    CAS  Google Scholar 

  81. Watkins, S. et al. Disruption of astrocyte–vascular coupling and the blood–brain barrier by invading glioma cells. Nat. Commun. 5, 4196 (2014).

    CAS  Google Scholar 

  82. Candiello, J. et al. Biomechanical properties of native basement membranes. FEBS J. 274, 2897–2908 (2007).

    CAS  Google Scholar 

  83. Charles, N. & Holland, E. C. The perivascular niche microenvironment in brain tumor progression. Cell Cycle 9, 3012–3021 (2010).

    CAS  Google Scholar 

  84. Giese, A. et al. Migration of human glioma cells on myelin. Neurosurg. 38, 755–764 (1996).

    CAS  Google Scholar 

  85. Hensel, T., Amberger, V. & Schwab, M. A metalloprotease activity from C6 glioma cells inactivates the myelin-associated neurite growth inhibitors and can be neutralized by antibodies. Br. J. Cancer 78, 1564–1572 (1998).

    CAS  Google Scholar 

  86. Amberger, V. R., Hensel, T., Ogata, N. & Schwab, M. E. Spreading and migration of human glioma and rat C6 cells on central nervous system myelin in vitro is correlated with tumor malignancy and involves a metalloproteolytic activity. Cancer Res. 58, 149–158 (1998).

    CAS  Google Scholar 

  87. Oellers, P., Schröer, U., Senner, V., Paulus, W. & Thanos, S. ROCKs are expressed in brain tumors and are required for glioma-cell migration on myelinated axons. Glia 57, 499–509 (2009).

    Google Scholar 

  88. Wang, J. et al. Invasion of white matter tracts by glioma stem cells is regulated by a NOTCH1–SOX2 positive-feedback loop. Nat. Neurosci. 22, 91–105 (2019).

    CAS  Google Scholar 

  89. Balzer, E. M. et al. Physical confinement alters tumor cell adhesion and migration phenotypes. FASEB J. 26, 4045–4056 (2012).

    CAS  Google Scholar 

  90. Monzo, P. et al. Mechanical confinement triggers glioma linear migration dependent on formin FHOD3. Mol. Biol. Cell 27, 1246–1261 (2016).

    CAS  Google Scholar 

  91. Heldin, C.-H., Rubin, K., Pietras, K., Ostman, A. & Östman, A. High interstitial fluid pressure — an obstacle in cancer therapy. Nat. Rev. Cancer 4, 806–813 (2004).

    CAS  Google Scholar 

  92. Swartz, M. A. & Fleury, M. E. Interstitial flow and its effects in soft tissues. Annu. Rev. Biomed. Eng. 9, 229–256 (2007).

    CAS  Google Scholar 

  93. Abbott, N. J. Evidence for bulk flow of brain interstitial fluid: significance for physiology and pathology. Neurochem. Int. 45, 545–552 (2004).

    CAS  Google Scholar 

  94. Geer, C. P. & Grossman, S. A. Interstitial fluid flow along white matter tracts: A potentially important mechanism for the dissemination of primary brain tumors. J. Neurooncol. 32, 193–201 (1997).

    CAS  Google Scholar 

  95. Kingsmore, K. M. et al. Interstitial flow differentially increases patient-derived glioblastoma stem cell invasion via CXCR4, CXCL12, and CD44-mediated mechanisms. Integr. Biol. 8, 1246–1260 (2016).

    CAS  Google Scholar 

  96. Munson, J. M., Bellamkonda, R. V. & Swartz, M. A. Interstitial flow in a 3D microenvironment increases glioma invasion by a CXCR4-dependent mechanism. Cancer Res. 73, 1536–1546 (2013).

    CAS  Google Scholar 

  97. Cornelison, R. C., Brennan, C. E., Kingsmore, K. M. & Munson, J. M. Convective forces increase CXCR4-dependent glioblastoma cell invasion in GL261 murine model. Sci. Rep. 8, 17057 (2018).

    Google Scholar 

  98. Monteiro, A., Hill, R., Pilkington, G. & Madureira, P. The role of hypoxia in glioblastoma invasion. Cells 6, 45 (2017).

    Google Scholar 

  99. Lee, C. G. et al. Anti-vascular endothelial growth factor treatment augments tumor radiation response under normoxic or hypoxic conditions. Cancer Res. 60, 5565–5570 (2000).

    CAS  Google Scholar 

  100. Figueroa, J. et al. Exosomes from glioma-associated mesenchymal stem cells increase the tumorigenicity of glioma stem-like cells via transfer of miR-1587. Cancer Res. 77, 5808–5819 (2017).

    CAS  Google Scholar 

  101. Hossain, A. et al. Mesenchymal stem cells isolated from human gliomas increase proliferation and maintain stemness of glioma stem cells through the IL-6/gp130/STAT3 pathway. Stem Cells 33, 2400–2415 (2015).

    CAS  Google Scholar 

  102. Brandao, M., Simon, T., Critchley, G. & Giamas, G. Astrocytes, the rising stars of the glioblastoma microenvironment. Glia 67, 779–790 (2019).

    Google Scholar 

  103. Poon, C. C., Sarkar, S., Yong, V. W. & Kelly, J. J. P. Glioblastoma-associated microglia and macrophages: targets for therapies to improve prognosis. Brain 140, 1548–1560 (2017).

    Google Scholar 

  104. Hambardzumyan, D., Gutmann, D. H. & Kettenmann, H. The role of microglia and macrophages in glioma maintenance and progression. Nat. Neurosci. 19, 20–27 (2016).

    CAS  Google Scholar 

  105. Venkatesh, H. S. et al. Neuronal activity promotes glioma growth through neuroligin-3 secretion. Cell 161, 803–816 (2015).

    CAS  Google Scholar 

  106. Infanger, D. W. et al. Glioblastoma stem cells are regulated by interleukin-8 signaling in a tumoral perivascular niche. Cancer Res. 73, 7079–7089 (2013).

    CAS  Google Scholar 

  107. Soda, Y. et al. Transdifferentiation of glioblastoma cells into vascular endothelial cells. Proc. Natl. Acad. Sci. USA 108, 4274–4280 (2011).

    CAS  Google Scholar 

  108. Hardee, M. E. & Zagzag, D. Mechanisms of glioma-associated neovascularization. Am. J. Pathol. 181, 1126–1141 (2012).

    CAS  Google Scholar 

  109. Davis, M. E. Glioblastoma: overview of disease and treatment. Clin. J. Oncol. Nurs. 20, S2–S8 (2016).

    Google Scholar 

  110. Brat, D. J. et al. Pseudopalisades in glioblastoma are hypoxic, express extracellular matrix proteases, and are formed by an actively migrating cell population. Cancer Res. 64, 920–927 (2004).

    CAS  Google Scholar 

  111. Lim, S. et al. Glioblastoma-secreted soluble CD44 activates tau pathology in the brain. Exp. Mol. Med. 50, 5 (2018).

    Google Scholar 

  112. Lacroix, M. et al. A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J. Neurosurg. 95, 190–198 (2001).

    CAS  Google Scholar 

  113. Shinoda, J. et al. Fluorescence-guided resection of glioblastoma multiforme by using high-dose fluorescein sodium. J. Neurosurg. 99, 597–603 (2003).

    Google Scholar 

  114. Bregy, A. et al. The role of Gliadel wafers in the treatment of high-grade gliomas. Expert Rev. Anticancer Ther. 13, 1453–1461 (2013).

    CAS  Google Scholar 

  115. Perry, J., Chambers, A., Spithoff, K. & Laperriere, N. Gliadel wafers in the treatment of malignant glioma: a systematic review. Curr. Oncol. 14, 189–194 (2007).

    CAS  Google Scholar 

  116. Stupp, R. et al. Effect of tumor-treating fields plus maintenance temozolomide vs maintenance temozolomide alone on survival in patients with glioblastoma. JAMA 318, 2306–2316 (2017).

    CAS  Google Scholar 

  117. Davies, A. M., Weinberg, U. & Palti, Y. Tumor treating fields: a new frontier in cancer therapy. Ann. N. Y. Acad. Sci. 1291, 86–95 (2013).

    Google Scholar 

  118. Calabrese, C. et al. A perivascular niche for brain tumor stem cells. Cancer Cell 11, 69–82 (2007). This paper demonstrated that interactions between endothelial cells and GSCs regulate the self-renewal and tumour-initiating capacity of GSCs, therefore acting as a perivascular niche.

    CAS  Google Scholar 

  119. Borovski, T., De Sousa E Melo, F., Vermeulen, L. & Medema, J. P. Cancer stem cell niche: the place to be. Cancer Res. 71, 634–639 (2011).

    CAS  Google Scholar 

  120. Silver, D. J. & Lathia, J. D. Revealing the glioma cancer stem cell interactome, one niche at a time. J. Pathol. 244, 260–264 (2018).

    Google Scholar 

  121. Brooks, M. D., Sengupta, R., Snyder, S. C. & Rubin, J. B. Hitting them where they live: targeting the glioblastoma perivascular stem cell niche. Curr. Pathobiol. Rep. 1, 101–110 (2013).

    Google Scholar 

  122. Shiraki, Y. et al. Significance of perivascular tumour cells defined by CD109 expression in progression of glioma. J. Pathol. 243, 468–480 (2017).

    CAS  Google Scholar 

  123. Wolf, K. J., Lee, S. & Kumar, S. A 3D topographical model of parenchymal infiltration and perivascular invasion in glioblastoma. APL Bioeng. 2, 031903 (2018).

    Google Scholar 

  124. Ngo, M. T. & Harley, B. A. C. Perivascular signals alter global gene expression profile of glioblastoma and response to temozolomide in a gelatin hydrogel. Biomater. 198, 122–134 (2019).

    CAS  Google Scholar 

  125. Zhu, T. S. et al. Endothelial cells create a stem cell niche in glioblastoma by providing NOTCH ligands that nurture self-renewal of cancer stem-like cells. Cancer Res. 71, 6061–6072 (2011).

    CAS  Google Scholar 

  126. Bao, S. et al. Stem cell-like glioma cells promote tumor angiogenesis through vascular endothelial growth factor. Cancer Res. 66, 7843–7848 (2006).

    CAS  Google Scholar 

  127. Charles, N. et al. Perivascular nitric oxide activates notch signaling and promotes stem-like character in PDGF-induced glioma cells. Cell Stem Cell 6, 141–152 (2010).

    CAS  Google Scholar 

  128. Tilghman, J. et al. HMMR maintains the stemness and tumorigenicity of glioblastoma stem-like cells. Cancer Res. 74, 3168–3179 (2014).

    CAS  Google Scholar 

  129. Chanmee, T., Ontong, P., Kimata, K. & Itano, N. Key roles of hyaluronan and its CD44 receptor in the stemness and survival of cancer stem cells. Front. Oncol. 5, 180 (2015).

    Google Scholar 

  130. Ferrandez, E., Gutierrez, O., Segundo, D. S. & Fernandez-Luna, J. L. NFκB activation in differentiating glioblastoma stem-like cells is promoted by hyaluronic acid signaling through TLR4. Sci. Rep. 8, 6341 (2018).

    Google Scholar 

  131. Chen, J. & Kumar, S. Biophysical regulation of cancer stem/initiating cells: Implications for disease mechanisms and translation. Curr. Opin. Biomed. Eng. 1, 87–95 (2017).

    Google Scholar 

  132. Barnes, J. M. et al. A tension-mediated glycocalyx–integrin feedback loop promotes mesenchymal-like glioblastoma. Nat. Cell Biol. 20, 1203–1214 (2018).

    CAS  Google Scholar 

  133. Iwadate, Y. Epithelial–mesenchymal transition in glioblastoma progression. Oncol. Lett. 11, 1615–1620 (2016).

    CAS  Google Scholar 

  134. Lau, J. et al. STAT3 blockade inhibits a radiation-induced proneural-to-mesenchymal transition in glioma. Cancer Res. 75, 4302–4311 (2015).

    CAS  Google Scholar 

  135. Bhat, K. P. L. et al. Mesenchymal differentiation mediated by NF-κB promotes radiation resistance in glioblastoma. Cancer Cell 24, 331–346 (2013).

    CAS  Google Scholar 

  136. Xiao, W. et al. Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Cancer Res. 78, 1358–1370 (2018).

    CAS  Google Scholar 

  137. Soeda, A. et al. Hypoxia promotes expansion of the CD133-positive glioma stem cells through activation of HIF-1α. Oncogene 28, 3949–3959 (2009).

    CAS  Google Scholar 

  138. Colwell, N. et al. Hypoxia in the glioblastoma microenvironment: shaping the phenotype of cancer stem-like cells. Neuro. Oncol. 19, 887–896 (2017).

    CAS  Google Scholar 

  139. Heddleston, J. M., Li, Z., McLendon, R. E., Hjelmeland, A. B. & Rich, J. N. The hypoxic microenvironment maintains glioblastoma stem cells and promotes reprogramming towards a cancer stem cell phenotype. Cell Cycle 8, 3274–3284 (2009).

    CAS  Google Scholar 

  140. Gupta, K. & Burns, T. C. Radiation-induced alterations in the recurrent glioblastoma microenvironment: therapeutic implications. Front. Oncol. 8, 503 (2018).

    Google Scholar 

  141. Bao, S. et al. Glioma stem cells promote radioresistance by preferential activation of the DNA damage response. Nature 444, 756–760 (2006).

    CAS  Google Scholar 

  142. Rath, B. H., Wahba, A., Camphausen, K. & Tofilon, P. J. Coculture with astrocytes reduces the radiosensitivity of glioblastoma stem-like cells and identifies additional targets for radiosensitization. Cancer Med. 4, 1705–1716 (2015).

    CAS  Google Scholar 

  143. De Pascalis, I. et al. Endothelial trans-differentiation in glioblastoma recurring after radiotherapy. Mod. Pathol. 31, 1361–1366 (2018).

    Google Scholar 

  144. Mao, L. et al. Enhancement of invadopodia activity in glioma cells by sublethal doses of irradiation and temozolomide. J. Neurosurg. 129, 598–610 (2018).

    CAS  Google Scholar 

  145. Tsidulko, A. Y. et al. Conventional anti-glioblastoma chemotherapy affects proteoglycan composition of brain extracellular matrix in rat experimental model in vivo. Front. Pharmacol. 9, 1104 (2018).

    CAS  Google Scholar 

  146. Yoshida, D., Piepmeier, J. M., Bergenheim, T., Henriksson, R. & Teramoto, A. Suppression of matrix metalloproteinase-2-mediated cell invasion in U87MG, human glioma cells by anti-microtubule agent: in vitro study. Br. J. Cancer 77, 21–25 (1998).

    CAS  Google Scholar 

  147. Sawyers, C. Targeted cancer therapy. Nature 432, 294–297 (2004).

    CAS  Google Scholar 

  148. Higgins, M. J. & Baselga, J. Targeted therapies for breast cancer. J. Clin. Invest. 121, 3797–3803 (2011).

    CAS  Google Scholar 

  149. Westphal, M., Maire, C. L. & Lamszus, K. EGFR as a target for glioblastoma treatment: an unfulfilled promise. CNS Drugs 31, 723–735 (2017).

    CAS  Google Scholar 

  150. Butowski, N. et al. Orally administered colony stimulating factor 1 receptor inhibitor PLX3397 in recurrent glioblastoma: an ivy foundation early phase clinical trials consortium phase II study. Neuro. Oncol. 18, 557–564 (2016).

    Google Scholar 

  151. Friedman, H. S. et al. Bevacizumab alone and in combination with irinotecan in recurrent glioblastoma. J. Clin. Oncol. 27, 4733–4740 (2009).

    CAS  Google Scholar 

  152. Kreisl, T. N. et al. Phase II trial of single-agent bevacizumab followed by bevacizumab plus irinotecan at tumor progression in recurrent glioblastoma. J. Clin. Oncol. 27, 740–745 (2009).

    CAS  Google Scholar 

  153. Wenger, K. J. et al. Bevacizumab as a last-line treatment for glioblastoma following failure of radiotherapy, temozolomide and lomustine. Oncol. Lett. 14, 1141–1146 (2017).

    CAS  Google Scholar 

  154. Pàez-Ribes, M. et al. Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell 15, 220–231 (2009).

    Google Scholar 

  155. Momeny, M. et al. Blockade of vascular endothelial growth factor receptors by tivozanib has potential anti-tumour effects on human glioblastoma cells. Sci. Rep. 7, 44075 (2017).

    CAS  Google Scholar 

  156. Batchelor, T. T. et al. Phase II study of cediranib, an oral pan-vascular endothelial growth factor receptor tyrosine kinase inhibitor, in patients with recurrent glioblastoma. J. Clin. Oncol. 28, 2817–2823 (2010).

    CAS  Google Scholar 

  157. Batchelor, T. T. et al. Phase III randomized trial comparing the efficacy of cediranib as monotherapy, and in combination with lomustine, versus lomustine alone in patients with recurrent glioblastoma. J. Clin. Oncol. 31, 3212–3218 (2013).

    CAS  Google Scholar 

  158. Kreisl, T. N. et al. Continuous daily sunitinib for recurrent glioblastoma. J. Neurooncol. 111, 41–48 (2013).

    CAS  Google Scholar 

  159. Neal, J. & Wakelee, H. AMG-386, a selective angiopoietin-1/-2-neutralizing peptibody for the potential treatment of cancer. Curr. Opin. Mol. Ther. 12, 487–495 (2010).

    CAS  Google Scholar 

  160. Reardon, D. A. et al. A review of VEGF/VEGFR-targeted therapeutics for recurrent glioblastoma. J. Natl. Compr. Canc. Netw. 9, 414–427 (2011).

    CAS  Google Scholar 

  161. Fang, H. & DeClerck, Y. A. Targeting the tumor microenvironment: from understanding pathways to effective clinical trials. Cancer Res. 73, 4965–4977 (2013).

    CAS  Google Scholar 

  162. Papadopoulos, K. P. et al. A phase 1 open-label, accelerated dose-escalation study of the hypoxia-activated prodrug AQ4N in patients with advanced malignancies. Clin. Cancer Res. 14, 7110–7115 (2008).

    CAS  Google Scholar 

  163. Albertella, M. R. et al. Hypoxia-selective targeting by the bioreductive prodrug AQ4N in patients with solid tumors: results of a phase I study. Clin. Cancer Res. 14, 1096–1104 (2008).

    CAS  Google Scholar 

  164. Patterson, L. H. & McKeown, S. R. AQ4N: a new approach to hypoxia-activated cancer chemotherapy. Br. J. Cancer 83, 1589–1593 (2000).

    CAS  Google Scholar 

  165. Jain, K. K. A critical overview of targeted therapies for glioblastoma. Front. Oncol. 8, 419 (2018).

    Google Scholar 

  166. Carbonell, W. S., DeLay, M., Jahangiri, A., Park, C. C. & Aghi, M. K. β1 integrin targeting potentiates antiangiogenic therapy and inhibits the growth of bevacizumab-resistant glioblastoma. Cancer Res. 73, 3145–3154 (2013).

    CAS  Google Scholar 

  167. Scaringi, C., Minniti, G., Caporello, P. & Enrici, R. M. Integrin inhibitor cilengitide for the treatment of glioblastoma: a brief overview of current clinical results. Anticancer. Res. 32, 4213–4223 (2012).

    CAS  Google Scholar 

  168. Stupp, R. et al. Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071-22072 study): a multicentre, randomised, open-label, phase 3 trial. Lancet Oncol. 15, 1100–1108 (2014).

    CAS  Google Scholar 

  169. Tucci, M., Stucci, S. & Silvestris, F. Does cilengitide deserve another chance? Lancet. Oncol. 15, e584–e585 (2014).

    Google Scholar 

  170. Vogelbaum, M. A. & Aghi, M. K. Convection-enhanced delivery for the treatment of glioblastoma. Neuro. Oncol. 17, ii3–ii8 (2015).

    CAS  Google Scholar 

  171. Brown, M. C. et al. Cancer immunotherapy with recombinant poliovirus induces IFN-dominant activation of dendritic cells and tumor antigen-specific CTLs. Sci. Transl. Med. 9, eaan4220 (2017).

    Google Scholar 

  172. Desjardins, A. et al. Recurrent glioblastoma treated with recombinant poliovirus. N. Engl. J. Med. 379, 150–161 (2018).

    CAS  Google Scholar 

  173. Rape, A., Ananthanarayanan, B. & Kumar, S. Engineering strategies to mimic the glioblastoma microenvironment. Adv. Drug Deliv. Rev. 79–80, 172–183 (2014).

    Google Scholar 

  174. Stylli, S. S., Luwor, R. B., Ware, T. M. B., Tan, F. & Kaye, A. H. Mouse models of glioma. J. Clin. Neurosci. 22, 619–626 (2015).

    Google Scholar 

  175. Joo, K. M. et al. Patient-specific orthotopic glioblastoma xenograft models recapitulate the histopathology and biology of human glioblastomas in situ. Cell Rep. 3, 260–273 (2013).

    CAS  Google Scholar 

  176. Simeonova, I. & Huillard, E. In vivo models of brain tumors: roles of genetically engineered mouse models in understanding tumor biology and use in preclinical studies. Cell. Mol. Life Sci. 71, 4007–4026 (2014).

    CAS  Google Scholar 

  177. Ismail Kola, J. L. Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov. 3, 711–715 (2004).

    Google Scholar 

  178. Wu, M. & Swartz, M. A. Modeling tumor microenvironments in vitro. J. Biomech. Eng. 136, 021011 (2014).

    Google Scholar 

  179. 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 

  180. Diao, W. et al. Behaviors of glioblastoma cells in in vitro microenvironments. Sci. Rep. 9, 85 (2019).

    Google Scholar 

  181. Fernandez-Fuente, G., Mollinedo, P., Grande, L., Vazquez-Barquero, A. & Fernandez-Luna, J. L. Culture dimensionality influences the resistance of glioblastoma stem-like cells to multikinase inhibitors. Mol. Cancer Ther. 13, 1664–1672 (2014).

    CAS  Google Scholar 

  182. Rape, A. D., Zibinsky, M., Murthy, N. & Kumar, S. A synthetic hydrogel for the high-throughput study of cell–ECM interactions. Nat. Commun. 6, 8129 (2015).

    Google Scholar 

  183. Ananthanarayanan, B., Kim, Y. & Kumar, S. Elucidating the mechanobiology of malignant brain tumors using a brain matrix–mimetic hyaluronic acid hydrogel platform. Biomater. 32, 7913–7923 (2011).

    CAS  Google Scholar 

  184. Wolf, K. J. & Kumar, S. Hyaluronic acid: incorporating the bio into the material. ACS Biomater. Sci. Eng. [epub ahead of print], (2019).

  185. Schanté, C. E., Zuber, G., Herlin, C. & Vandamme, T. F. Chemical modifications of hyaluronic acid for the synthesis of derivatives for a broad range of biomedical applications. Carbohydr. Polym. 85, 469–489 (2011).

    Google Scholar 

  186. Kaphle, P., Li, Y. & Yao, L. The mechanical and pharmacological regulation of glioblastoma cell migration in 3D matrices. J. Cell. Physiol. 234, 3948–3960 (2019).

    CAS  Google Scholar 

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

    CAS  Google Scholar 

  188. Ulrich, T. A., Lee, T. G., Shon, H. K., Moon, D. W. & Kumar, S. Microscale mechanisms of agarose-induced disruption of collagen remodeling. Biomater. 32, 5633–5642 (2011).

    CAS  Google Scholar 

  189. Yang, Y. et al. Influence of chondroitin sulfate and hyaluronic acid on structure, mechanical properties, and glioma invasion of collagen I gels. Biomater. 32, 7932–7940 (2011).

    CAS  Google Scholar 

  190. Yang, Y., Motte, S. & Kaufman, L. J. Pore size variable type I collagen gels and their interaction with glioma cells. Biomater. 31, 5678–5688 (2010).

    CAS  Google Scholar 

  191. Ylivinkka, I. et al. Motility of glioblastoma cells is driven by netrin-1 induced gain of stemness. J. Exp. Clin. Cancer Res. 36, 9 (2017).

    Google Scholar 

  192. Kumar, K. K. et al. Glioma stem cell invasion through regulation of the interconnected ERK, integrin α 6 and N-cadherin signaling pathway. Cell. Signal. 24, 2076–2084 (2012).

    Google Scholar 

  193. Wang, C., Tong, X., Jiang, X. & Yang, F. Effect of matrix metalloproteinase-mediated matrix degradation on glioblastoma cell behavior in 3D PEG-based hydrogels. J. Biomed. Mater. Res. A 105, 770–778 (2017).

    CAS  Google Scholar 

  194. Ma, N. K. L. et al. Collaboration of 3D context and extracellular matrix in the development of glioma stemness in a 3D model. Biomater. 78, 62–73 (2016).

    CAS  Google Scholar 

  195. Martínez-Ramos, C. & Lebourg, M. Three-dimensional constructs using hyaluronan cell carrier as a tool for the study of cancer stem cells. J. Biomed. Mater. Res. B Appl. Biomater. 103, 1249–1257 (2015).

    Google Scholar 

  196. Heffernan, J. M. et al. PNIPAAm-co-Jeffamine® (PNJ) scaffolds as in vitro models for niche enrichment of glioblastoma stem-like cells. Biomater. 143, 149–158 (2017).

    CAS  Google Scholar 

  197. Kievit, F. M. et al. Modeling the tumor microenvironment using chitosan-alginate scaffolds to control the stem-like state of glioblastoma cells. Biomater. Sci. 4, 610–613 (2016).

    CAS  Google Scholar 

  198. Koh, I. et al. The mode and dynamics of glioblastoma cell invasion into a decellularized tissue-derived extracellular matrix-based three-dimensional tumor model. Sci. Rep. 8, 4608 (2018).

    Google Scholar 

  199. Yi, H.-G. et al. A bioprinted human-glioblastoma-on-a-chip for the identification of patient-specific responses to chemoradiotherapy. Nat. Biomed. Eng. [epub ahead of print], (2019). This paper describes a 3D-printed, spatially organized model of perivascular invasion that includes brain-derived matrix and patient-derived tumour cells.

  200. Weiswald, L.-B., Bellet, D. & Dangles-Marie, V. Spherical cancer models in tumor biology. Neoplasia 17, 1–15 (2015).

    Google Scholar 

  201. Lee, J. et al. Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell 9, 391–403 (2006).

    CAS  Google Scholar 

  202. Timmins, N. E. & Nielsen, L. K. Generation of multicellular tumor spheroids by the hanging-drop method. Methods Mol. Med. 140, 141–151 (2007).

    CAS  Google Scholar 

  203. Mirab, F., Kang, Y. J. & Majd, S. Preparation and characterization of size-controlled glioma spheroids using agarose hydrogel microwells. PLoS One 14, e0211078 (2019).

    CAS  Google Scholar 

  204. Zhang, X.-P. et al. Notch activation promotes cell proliferation and the formation of neural stem cell-like colonies in human glioma cells. Mol. Cell. Biochem. 307, 101–108 (2007).

    Google Scholar 

  205. Herrera-Perez, R. M. et al. Presence of stromal cells in a bioengineered tumor microenvironment alters glioblastoma migration and response to STAT3 inhibition. PLoS One 13, e0194183 (2018).

    Google Scholar 

  206. Florczyk, S. J. et al. Porous chitosan–hyaluronic acid scaffolds as a mimic of glioblastoma microenvironment ECM. Biomaterials 34, 10143–10150 (2013).

    CAS  Google Scholar 

  207. Herrera-Perez, M., Voytik-Harbin, S. L. & Rickus, J. L. Extracellular matrix properties regulate the migratory response of glioblastoma stem cells in three-dimensional culture. Tissue Eng. Part A 21, 2572–2582 (2015).

    CAS  Google Scholar 

  208. Pedron, S., Becka, E. & Harley, B. A. C. C. Regulation of glioma cell phenotype in 3D matrices by hyaluronic acid. Biomaterials 34, 7408–7417 (2013).

    CAS  Google Scholar 

  209. Wang, C., Tong, X. & Yang, F. Bioengineered 3D brain tumor model to elucidate the effects of matrix stiffness on glioblastoma cell behavior using PEG-based hydrogels. Mol. Pharm. 11, 2115–2125 (2014).

    CAS  Google Scholar 

  210. Heffernan, J. M., Overstreet, D. J., Le, L. D., Vernon, B. L. & Sirianni, R. W. Bioengineered scaffolds for 3D analysis of glioblastoma proliferation and invasion. Ann. Biomed. Eng. 43, 1965–1977 (2014).

    Google Scholar 

  211. Pedron, S., Hanselman, J. S., Schroeder, M. A., Sarkaria, J. N. & Harley, B. A. C. Extracellular hyaluronic acid influences the efficacy of EGFR tyrosine kinase inhibitors in a biomaterial model of glioblastoma. Adv. Healthc. Mater. 6, 1700529 (2017).

    Google Scholar 

  212. Pedron, S. et al. Hyaluronic acid-functionalized gelatin hydrogels reveal extracellular matrix signals temper the efficacy of erlotinib against patient-derived glioblastoma specimens. Biomaterials 219, 119371 (2019).

  213. Shin, H. Fabrication methods of an engineered microenvironment for analysis of cell–biomaterial interactions. Biomaterials 28, 126–133 (2007).

    CAS  Google Scholar 

  214. Brown, T. E. & Anseth, K. S. Spatiotemporal hydrogel biomaterials for regenerative medicine. Chem. Soc. Rev. 46, 6532–6552 (2017).

    CAS  Google Scholar 

  215. Cortese, B., Gigli, G. & Riehle, M. Mechanical gradient cues for guided cell motility and control of cell behavior on uniform substrates. Adv. Funct. Mater. 19, 2961–2968 (2009).

    CAS  Google Scholar 

  216. Pedron, S., Becka, E. & Harley, B. A. Spatially gradated hydrogel platform as a 3D engineered tumor microenvironment. Adv. Mater. 27, 1567–1572 (2015). A microfluidic-based mixing tool was developed and applied to generate 3D materials with gradients of matrix and cellular composition, facilitating rapid investigation of TME parameters on tumour progression.

    CAS  Google Scholar 

  217. Rao, S. S. et al. Inherent interfacial mechanical gradients in 3D hydrogels influence tumor cell behaviors. PLoS One 7, e35852 (2012).

    CAS  Google Scholar 

  218. Pedron, S. & Harley, B. A. C. Impact of the biophysical features of a 3D gelatin microenvironment on glioblastoma malignancy. J. Biomed. Mater. Res. A 101, 3404–3415 (2013).

    CAS  Google Scholar 

  219. Gritsenko, P., Leenders, W. & Friedl, P. Recapitulating in vivo-like plasticity of glioma cell invasion along blood vessels and in astrocyte-rich stroma. Histochem. Cell Biol. 148, 1–12 (2017).

    Google Scholar 

  220. Rape, A. D. & Kumar, S. A composite hydrogel platform for the dissection of tumor cell migration at tissue interfaces. Biomaterials 35, 8846–8853 (2014).

    CAS  Google Scholar 

  221. Beliveau, A., Thomas, G., Gong, J., Wen, Q. & Jain, A. Aligned nanotopography promotes a migratory state in glioblastoma multiforme tumor cells. Sci. Rep. 6, 26143 (2016).

    CAS  Google Scholar 

  222. Kievit, F. M. et al. Aligned chitosan–polycaprolactone polyblend nanofibers promote the migration of glioblastoma cells. Adv. Healthc. Mater. 2, 1651–1659 (2013).

    CAS  Google Scholar 

  223. Sharma, P., Sheets, K., Elankumaran, S. & Nain, A. S. The mechanistic influence of aligned nanofibers on cell shape, migration and blebbing dynamics of glioma cells. Integr. Biol. 5, 1036–1044 (2013).

    CAS  Google Scholar 

  224. Grodecki, J. et al. Glioma–astrocyte interactions on white matter tract–mimetic aligned electrospun nanofibers. Biotechnol. Prog. 31, 1406–1415 (2015).

    CAS  Google Scholar 

  225. Rao, S. S. et al. Mimicking white matter tract topography using core–shell electrospun nanofibers to examine migration of malignant brain tumors. Biomaterials 34, 5181–5190 (2013).

    CAS  Google Scholar 

  226. Agudelo-Garcia, P. A. et al. Glioma cell migration on three-dimensional nanofiber scaffolds is regulated by substrate topography and abolished by inhibition of STAT3 signaling. Neoplasia 13, 831–840 (2011).

    CAS  Google Scholar 

  227. Sung, K. E. & Beebe, D. J. Microfluidic 3D models of cancer. Adv. Drug Deliv. Rev. 79–80, 68–78 (2014).

    Google Scholar 

  228. Ayuso, J. M. et al. Glioblastoma on a microfluidic chip: Generating pseudopalisades and enhancing aggressiveness through blood vessel obstruction events. Neuro. Oncol. 19, 503–513 (2017). This paper applied a microfluidic model to test how pseudopalisades form, which had previously only been inferred from in vivo data.

    CAS  Google Scholar 

  229. Truong, D. et al. A three-dimensional (3D) organotypic microfluidic model for glioma stem cells — Vascular interactions. Biomaterials 198, 63–77 (2019).

    CAS  Google Scholar 

  230. Chonan, Y., Taki, S., Sampetrean, O., Saya, H. & Sudo, R. Endothelium-induced three-dimensional invasion of heterogeneous glioma initiating cells in a microfluidic coculture platform. Integr. Biol. 9, 762–773 (2017).

    CAS  Google Scholar 

  231. Xiao, Y. et al. Ex vivo dynamics of human glioblastoma cells in a microvasculature-on-a-chip system correlates with tumor heterogeneity and subtypes. Adv. Sci. 6, 1801531 (2019).

    Google Scholar 

  232. Akay, M. et al. Drug screening of human GBM spheroids in brain cancer chip. Sci. Rep. 8, 15423 (2018).

    Google Scholar 

  233. Han, J. et al. Rapid emergence and mechanisms of resistance by U87 glioblastoma cells to doxorubicin in an in vitro tumor microfluidic ecology. Proc. Natl. Acad. Sci. USA 113, 14283–14288 (2016).

    CAS  Google Scholar 

  234. Fan, Y. et al. Engineering a brain cancer chip for high-throughput drug screening. Sci. Rep. 6, 25062 (2016).

    CAS  Google Scholar 

  235. Jie, M. et al. Evaluation of drug combination for glioblastoma based on an intestine–liver metabolic model on microchip. Analyst 142, 3629–3638 (2017).

    CAS  Google Scholar 

  236. Dai, X., Ma, C., Lan, Q. & Xu, T. 3D bioprinted glioma stem cells for brain tumor model and applications of drug susceptibility. Biofabrication 8, 045005 (2016).

    Google Scholar 

  237. Wang, X. et al. Bioprinting of glioma stem cells improves their endotheliogenic potential. Colloids Surf. B Biointerfaces 171, 629–637 (2018).

    CAS  Google Scholar 

  238. Heinrich, M. A. et al. 3D-Bioprinted mini-brain: a glioblastoma model to study cellular interactions and therapeutics. Adv. Mater. 31, 1806590 (2019).

    Google Scholar 

  239. Hubert, C. G. et al. A three-dimensional organoid culture system derived from human glioblastomas recapitulates the hypoxic gradients and cancer stem cell heterogeneity of tumors found in vivo. Cancer Res. 76, 2465–2477 (2016). The method used in this paper to derive and culture patient cells and matrix minimally disturbed cell–matrix interactions, preserved tumour cell heterogeneity and resulted in an accurate recapitulation of patient tumour response in an orthotopic xenograft culture.

    CAS  Google Scholar 

  240. Hattori, N. Cerebral organoids model human brain development and microcephaly. Mov. Disord. 29, 185–185 (2014).

    Google Scholar 

  241. Nayernia, Z. et al. The relationship between brain tumor cell invasion of engineered neural tissues and in vivo features of glioblastoma. Biomaterials 34, 8279–8290 (2013).

    CAS  Google Scholar 

  242. Huang, Y., Agrawal, B., Clark, P. A., Williams, J. C. & Kuo, J. S. Evaluation of cancer stem cell migration using compartmentalizing microfluidic devices and live cell imaging. J. Vis. Exp. 58, e3297 (2011).

    Google Scholar 

  243. Piccolo, S. R. & Frey, L. J. Clinical and molecular models of glioblastoma multiforme survival. Int. J. Data Min. Bioinform. 7, 245–265 (2013).

    Google Scholar 

  244. Verhaak, R. G. W. et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17, 98–110 (2010).

    CAS  Google Scholar 

  245. US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02060890 (2018).

  246. Wang, Y. I., Abaci, H. E. & Shuler, M. L. Microfluidic blood–brain barrier model provides in vivo-like barrier properties for drug permeability screening. Biotechnol. Bioeng. 114, 184–194 (2017).

    CAS  Google Scholar 

  247. van der Helm, M. W., van der Meer, A. D., Eijkel, J. C. T., van den Berg, A. & Segerink, L. I. Microfluidic organ-on-chip technology for blood–brain barrier research. Tissue Barriers 4, e1142493 (2016).

    Google Scholar 

  248. Randazzo, M., Pisapia, J. M., Singh, N. & Thawani, J. P. 3D printing in neurosurgery: A systematic review. Surg. Neurol. Int. 7, S801–S809 (2016).

    Google Scholar 

  249. Ploch, C. C., Mansi, C. S. S. A., Jayamohan, J. & Kuhl, E. Using 3D printing to create personalized brain models for neurosurgical training and preoperative planning. World Neurosurg. 90, 668–674 (2016).

    Google Scholar 

  250. Naftulin, J. S., Kimchi, E. Y. & Cash, S. S. Streamlined, inexpensive 3D printing of the brain and skull. PLoS One 10, e0136198 (2015).

    Google Scholar 

  251. Treiber, J. M. et al. Molecular physiology of contrast enhancement in glioblastomas: an analysis of The Cancer Imaging Archive (TCIA). J. Clin. Neurosci. 55, 86–92 (2018).

    CAS  Google Scholar 

  252. Gevaert, O. et al. Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features. Radiology 273, 168–174 (2014).

    Google Scholar 

  253. Chow, D. et al. Imaging genetic heterogeneity in glioblastoma and other glial tumors: review of current methods and future directions. Am. J. Roentgenol. 210, 30–38 (2018).

    Google Scholar 

  254. Lao, J. et al. A deep learning-based radiomics model for prediction of survival in glioblastoma multiforme. Sci. Rep. 7, 10353 (2017).

    Google Scholar 

  255. Dupont, C., Betrouni, N., Reyns, N. & Vermandel, M. On image segmentation methods applied to glioblastoma: state of art and new trends. IRBM 37, 131–143 (2016).

    Google Scholar 

  256. Tamimi, A. F. & Juweid, M. in Glioblastoma Ch. 8 (ed De Vleeschouwer, S.) (Codon Publications, 2017).

  257. Lee, J. H. et al. Human glioblastoma arises from subventricular zone cells with low-level driver mutations. Nature 560, 243–247 (2018).

    CAS  Google Scholar 

  258. Khalifa, J. et al. Subventricular zones: new key targets for glioblastoma treatment. Radiat. Oncol. 12, 67 (2017).

    CAS  Google Scholar 

  259. Chen, L. et al. Increased subventricular zone radiation dose correlates with survival in glioblastoma patients after gross total resection. Int. J. Radiat. Oncol. 86, 616–622 (2013).

    Google Scholar 

  260. Ohgaki, H. & Kleihues, P. Genetic pathways to primary and secondary glioblastoma. Am. J. Pathol. 170, 1445–1453 (2007).

    CAS  Google Scholar 

  261. Gupta, A. & Dwivedi, T. A simplified overview of World Health Organization classification update of central nervous system tumors 2016. J. Neurosci. Rural Pract. 8, 629–641 (2017).

    Google Scholar 

  262. Yan, H. et al. IDH1 and IDH2 mutations in gliomas. N. Engl. J. Med. 360, 765–773 (2009).

    CAS  Google Scholar 

  263. Hartmann, C. et al. Patients with IDH1 wild type anaplastic astrocytomas exhibit worse prognosis than IDH1-mutated glioblastomas, and IDH1 mutation status accounts for the unfavorable prognostic effect of higher age: implications for classification of gliomas. Acta Neuropathol. 120, 707–718 (2010).

    Google Scholar 

  264. Wilson, T. A., Karajannis, M. A. & Harter, D. H. Glioblastoma multiforme: state of the art and future therapeutics. Surg. Neurol. Int. 5, 64 (2014).

    Google Scholar 

  265. Mutter, N. & Stupp, R. Temozolomide: a milestone in neuro-oncology and beyond? Expert Rev. Anticancer Ther. 6, 1187–1204 (2006).

    CAS  Google Scholar 

  266. Hegi, M. E. et al. Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide. Clin. Cancer Res. 10, 1871–1874 (2004).

    CAS  Google Scholar 

  267. Kappelle, A. C. et al. PCV chemotherapy for recurrent glioblastoma multiforme. Neurology 56, 118–120 (2001).

    CAS  Google Scholar 

  268. Weller, M., Cloughesy, T., Perry, J. R. & Wick, W. Standards of care for treatment of recurrent glioblastoma — are we there yet? Neuro. Oncol. 15, 4–27 (2013).

    Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge financial support from the National Science Foundation (Graduate Research Fellowship to K.J.W.) and the National Institutes of Health (Ruth L. Kirschstein Predoctoral Individual National Research Service Award F31CA228317 to K.J.W.; Ruth L. Kirschstein Postdoctoral Individual National Research Service Award F32CA221366 to J.C.; R21EB025017, R01GM122375 and R01DK118940 to S.K.; and R01CA227136 to M.K.A. and S.K.). J.D.C. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 752097.

Author information

Authors and Affiliations

  1. University of California, Berkeley–University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA

    Kayla J. Wolf & Sanjay Kumar

  2. Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA

    Kayla J. Wolf, Joseph Chen, Jason D. Coombes & Sanjay Kumar

  3. Department of Inflammation Biology, Faculty of Life Sciences and Medicine, King’s College London, London, UK

    Jason D. Coombes

  4. Department of Neurosurgery, University of California, San Francisco (UCSF), San Francisco, CA, USA

    Manish K. Aghi

  5. Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, USA

    Sanjay Kumar

Authors
  1. Kayla J. Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joseph Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jason D. Coombes
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Manish K. Aghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sanjay Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

K.J.W., J.C. and J.D.C. researched data for the article. K.J.W. and S.K. made substantial contributions to manuscript writing and the discussion of content. All authors reviewed and edited the manuscript before submission.

Corresponding author

Correspondence to Sanjay Kumar.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wolf, K.J., Chen, J., Coombes, J.D. et al. Dissecting and rebuilding the glioblastoma microenvironment with engineered materials. Nat Rev Mater 4, 651–668 (2019). https://doi.org/10.1038/s41578-019-0135-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41578-019-0135-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer