A Patient-Derived Glioblastoma Organoid Model and Biobank Recapitulates Inter- and Intra-tumoral Heterogeneity.

IF 5.7 1区 化学 Q2 CHEMISTRY, PHYSICAL
Fadi Jacob, Ryan D Salinas, Daniel Y Zhang, Phuong T T Nguyen, Jordan G Schnoll, Samuel Zheng Hao Wong, Radhika Thokala, Saad Sheikh, Deeksha Saxena, Stefan Prokop, Di-Ao Liu, Xuyu Qian, Dmitriy Petrov, Timothy Lucas, H Isaac Chen, Jay F Dorsey, Kimberly M Christian, Zev A Binder, MacLean Nasrallah, Steven Brem, Donald M O'Rourke, Guo-Li Ming, Hongjun Song
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引用次数: 0

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.

源自患者的胶质母细胞瘤类器官模型和生物库再现了肿瘤间和肿瘤内的异质性。
胶质母细胞瘤表现出巨大的瘤间和瘤内异质性,使有效治疗策略的开发变得复杂。目前的体外模型在保留亲代肿瘤的细胞和突变多样性方面受到限制,而且需要较长的生成时间。在这里,我们报告了生成和生物库保存源自患者的胶质母细胞瘤器官组织(GBOs)的方法,这些器官组织能再现相应亲代肿瘤的组织学特征、细胞多样性、基因表达和突变特征。GBOs 可以快速生成,可靠性高,而且在移植到成年啮齿类动物大脑时会表现出快速的侵袭性浸润。我们将GBO的突变谱与对特定药物的反应相关联,并模拟嵌合抗原受体T细胞免疫疗法,从而进一步证明了GBO在测试个性化疗法方面的实用性。我们的研究表明,GBO 保持了胶质母细胞瘤的许多关键特征,可以迅速用于研究针对患者的治疗策略。此外,我们的活体生物库为胶质母细胞瘤的基础研究和转化研究提供了丰富的资源。
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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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