3D hydrogels reveal medulloblastoma subgroup differences and identify extracellular matrix subtypes that predict patient outcome

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Abstract

Medulloblastoma (MB) is the most common malignant brain tumour in children and is subdivided into four subgroups: WNT, SHH, Group 3, and Group 4. These molecular subgroups differ in their metastasis patterns and related prognosis rates. Conventional 2D cell culture methods fail to recapitulate these clinical differences. Realistic 3D models of the cerebellum are therefore necessary to investigate subgroup-specific functional differences and their role in metastasis and chemoresistance. A major component of the brain extracellular matrix (ECM) is the glycosaminoglycan hyaluronan. MB cell lines encapsulated in hyaluronan hydrogels grew as tumour nodules, with Group 3 and Group 4 cell lines displaying clinically characteristic laminar metastatic patterns and levels of chemoresistance. The glycoproteins, laminin and vitronectin, were identified as subgroup-specific, tumour-secreted ECM factors. Gels of higher complexity, formed by incorporation of laminin or vitronectin, revealed subgroup-specific adhesion and growth patterns closely mimicking clinical phenotypes. ECM subtypes, defined by relative levels of laminin and vitronectin expression in patient tissue microarrays and gene expression data sets, were able to identify novel high-risk MB patient subgroups and predict overall survival. Our hyaluronan model system has therefore allowed us to functionally characterize the interaction between different MB subtypes and their environment. It highlights the prognostic and pathological role of specific ECM factors and enables preclinical development of subgroup-specific therapies. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

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Linke, F., Aldighieri, M., Lourdusamy, A., Grabowska, A. M., Stolnik, S., Kerr, I. D., … Coyle, B. (2021). 3D hydrogels reveal medulloblastoma subgroup differences and identify extracellular matrix subtypes that predict patient outcome. Journal of Pathology, 253(3), 326–338. https://doi.org/10.1002/path.5591

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