Standardized orthotopic xenografts in zebrafish reveal glioma cell-line-specific characteristics and tumor cell heterogeneity

斑马鱼的标准化原位异种移植揭示了胶质瘤细胞系特异性特征和肿瘤细胞异质性

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作者:Alessandra M Welker, Brian D Jaros, Vinay K Puduvalli, Jaime Imitola, Balveen Kaur, Christine E Beattie

Abstract

Glioblastoma (GBM) is a deadly brain cancer, for which few effective drug treatments are available. Several studies have used zebrafish models to study GBM, but a standardized approach to modeling GBM in zebrafish was lacking to date, preventing comparison of data across studies. Here, we describe a new, standardized orthotopic xenotransplant model of GBM in zebrafish. Dose-response survival assays were used to define the optimal number of cells for tumor formation. Techniques to measure tumor burden and cell spread within the brain over real time were optimized using mouse neural stem cells as control transplants. Applying this standardized approach, we transplanted two patient-derived GBM cell lines, serum-grown adherent cells and neurospheres, into the midbrain region of embryonic zebrafish and analyzed transplanted larvae over time. Progressive brain tumor growth and premature larval death were observed using both cell lines; however, fewer transplanted neurosphere cells were needed for tumor growth and lethality. Tumors were heterogeneous, containing both cells expressing stem cell markers and cells expressing markers of differentiation. A small proportion of transplanted neurosphere cells expressed glial fibrillary acidic protein (GFAP) or vimentin, markers of more differentiated cells, but this number increased significantly during tumor growth, indicating that these cells undergo differentiation in vivo. By contrast, most serum-grown adherent cells expressed GFAP and vimentin at the earliest times examined post-transplant. Both cell types produced brain tumors that contained Sox2(+) cells, indicative of tumor stem cells. Transplanted larvae were treated with currently used GBM therapeutics, temozolomide or bortezomib, and this resulted in a reduction in tumor volume in vivo and an increase in survival. The standardized model reported here facilitates robust and reproducible analysis of glioblastoma tumor cells in real time and provides a platform for drug screening.

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