Bioengineered Models to Study Microenvironmental Regulation of Glioblastoma Metabolism. Issue 11 (15th September 2021)

• Record Type: Journal Article
• Authors: Chen, Joseph; Lee, Hyunchul; Schmitt, Philipp; Choy, Caleb J; Miller, Donald M; Williams, Brian J; Bearer, Elaine L; Frieboes, Hermann B
• Is Part Of: Journal of neuropathology and experimental neurology. Volume 80:Issue 11(2021)
• Page Start: 1012
• Page End: 1023
• Publication Date: 2021-09-15
• Subjects: Bioengineered platforms -- Biomimetics -- Cancer metabolism -- Glioblastoma -- Mathematical modeling -- Microphysiological platforms -- Tumor microenvironment; Neurology -- Diseases -- Periodicals; Neurology -- Diseases -- Physiopathology -- Periodicals; 616.8047
• DOI: 10.1093/jnen/nlab092
• Languages: English
• ISSNs: 0022-3069

Abstract

Abstract: Despite extensive research and aggressive therapies, glioblastoma (GBM) remains a central nervous system malignancy with poor prognosis. The varied histopathology of GBM suggests a landscape of differing microenvironments and clonal expansions, which may influence metabolism, driving tumor progression. Indeed, GBM metabolic plasticity in response to differing nutrient supply within these microenvironments has emerged as a key driver of aggressiveness. Additionally, emergent biophysical and biochemical interactions in the tumor microenvironment (TME) are offering new perspectives on GBM metabolism. Perivascular and hypoxic niches exert crucial roles in tumor maintenance and progression, facilitating metabolic relationships between stromal and tumor cells. Alterations in extracellular matrix and its biophysical characteristics, such as rigidity and topography, regulate GBM metabolism through mechanotransductive mechanisms. This review highlights insights gained from deployment of bioengineering models, including engineered cell culture and mathematical models, to study the microenvironmental regulation of GBM metabolism. Bioengineered approaches building upon histopathology measurements may uncover potential therapeutic strategies that target both TME-dependent mechanotransductive and biomolecular drivers of metabolism to tackle this challenging disease. Longer term, a concerted effort integrating in vitro and in silico models predictive of patient therapy response may offer a powerful advance toward tailoring of treatment to patient-specific GBM characteristics.