| Literature DB >> 31883794 |
Fadi Jacob1, Ryan D Salinas2, Daniel Y Zhang3, Phuong T T Nguyen4, Jordan G Schnoll5, Samuel Zheng Hao Wong6, Radhika Thokala2, Saad Sheikh7, Deeksha Saxena7, Stefan Prokop8, Di-Ao Liu9, Xuyu Qian10, Dmitriy Petrov2, Timothy Lucas2, H Isaac Chen11, Jay F Dorsey12, Kimberly M Christian5, Zev A Binder13, MacLean Nasrallah12, Steven Brem13, Donald M O'Rourke14, Guo-Li Ming15, Hongjun Song16.
Abstract
Glioblastomas exhibit vast inter- and intra-tumoral heterogeneity, complicating the development of effective therapeutic strategies. Current in vitro models are limited in preserving the cellular and mutational diversity of parental tumors and require a prolonged generation time. Here, we report methods for generating and biobanking patient-derived glioblastoma organoids (GBOs) that recapitulate the histological features, cellular diversity, gene expression, and mutational profiles of their corresponding parental tumors. GBOs can be generated quickly with high reliability and exhibit rapid, aggressive infiltration when transplanted into adult rodent brains. We further demonstrate the utility of GBOs to test personalized therapies by correlating GBO mutational profiles with responses to specific drugs and by modeling chimeric antigen receptor T cell immunotherapy. Our studies show that GBOs maintain many key features of glioblastomas and can be rapidly deployed to investigate patient-specific treatment strategies. Additionally, our live biobank establishes a rich resource for basic and translational glioblastoma research.Entities:
Keywords: CAR-T cells; Organoid; biobank; cancer modeling; drug testing; glioblastoma; personalized therapies; translational; tumor heterogeneity; xenograft
Mesh:
Year: 2019 PMID: 31883794 PMCID: PMC7556703 DOI: 10.1016/j.cell.2019.11.036
Source DB: PubMed Journal: Cell ISSN: 0092-8674 Impact factor: 41.582