Hypoxia activates enhanced invasive potential and endogenous hyaluronic acid production by glioblastoma cells

Jee Wei Emily Chen, Jan Lumibao, Audrey Blazek, H. Rex Gaskins, Brendan Harley

Research output: Contribution to journalArticle


Glioblastoma (GBM) is the most common, aggressive, and deadly form of adult brain cancer, and is associated with a short survival rate (median 12-15 months, 5+ year less than 5%). The complex tumor microenvironment includes matrix transitions at the tumor margin, such as gradations in hyaluronic acid (HA). In addition, metabolic stress induced by decreased oxygen content across the tumor may contribute to tumor progression. However, cross-Talk between matrix composition and metabolic stress remains unclear. In this study, we fabricated an in vitro brain memetic HA-decorated gelatin hydrogel platform incorporating variable oxygen concentrations to mimic intra-Tumoral hypoxia. We observed that EGFR status (wildtype vs. a constitutively active EGFRvIII mutant) of U87 GBM cells affected proliferation and metabolic activity in response to hypoxia and matrix-bound HA. The use of an invasion assay revealed that invasion was significantly enhanced in both cell types under hypoxia. Moreover, we observed compensatory secretion of soluble HA in cases of enhanced GBM cell invasion, consistent with our previous findings using other GBM cell lines. Interestingly, U87 GBM cells adapted to hypoxia by shifting toward a more anaerobic metabolic state, a mechanism that may contribute to GBM cell invasion. Collectively, these data demonstrate that the use of a three-dimensional hydrogel provides a robust method to study the impact of matrix composition and metabolic challenges on GBM cell invasion, a key factor contributing to the most common, aggressive, and deadly form of adult brain cancer.

Original languageEnglish (US)
Pages (from-to)854-862
Number of pages9
JournalBiomaterials Science
Issue number4
StatePublished - Apr 2018


ASJC Scopus subject areas

  • Biomedical Engineering
  • Materials Science(all)

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