Modeling gliomas with organoids: Classification, fidelity, and guidelines for translational neuro-oncology

类有机物 胶质瘤 转化研究 计算机科学 计算生物学 神经科学 标准化 清晰 医学 钥匙(锁) 胶质母细胞瘤 精密医学 系统生物学 生物信息学 肿瘤微环境 生物 癌症研究 基础研究
作者
Christopher G. Hubert,Renee D Read,Tyler E. Miller,Uijin Kim,Xin Wang,Mohamed Ishan,Zhikun Wang,Zhikun Wang,Emily Z Y Miller,Yusha Sun,Albert Lai,Guo-Li Ming,Hongjun Song,Zhaohui Wang,Zhaohui Wang
出处
期刊:Neuro-oncology [Oxford University Press]
被引量:2
标识
DOI:10.1093/neuonc/noag085
摘要

Advances in organoid technology have transformed how gliomas are modeled and studied. Recent FDA and NIH initiatives further promote human-relevant organoid platforms for preclinical research. Glioma organoids can be broadly categorized into three main classes: Engineered organoids, which enable controlled modeling of gliomagenesis driven by specific mutations; patient-tissue derived organoids, which preserve key molecular and histopathological features of the original tumors; and assembloids, which are designed to model tumor-microenvironment interactions. Together, these systems provide a human cell-relevant framework for investigating glioma biology, tumor-microenvironment crosstalk, and therapeutic responses and resistance. In this review, we provide a comprehensive overview of the spectrum of glioma organoid models, recognizing that different systems offer distinct and complementary strengths, and offer practical guidance for selecting appropriate models and analytical readouts based on specific basic and translational research objectives. To address increasing methodological heterogeneity and fragmented terminology, we propose a foundational nomenclature framework for glioma organoid models to improve clarity and communication within the field. We highlight applications in technically challenging subtypes, including isocitrate dehydrogenase (IDH)-mutant gliomas and diffuse midline gliomas (DMGs), and discuss key challenges-including scalability, standardization, microenvironment fidelity, and vascularization-and emerging innovations addressing these limitations. Finally, we call for greater collaboration and standardization within the glioma organoid community to accelerate the integration of organoid models into translational pipelines to redefine and refine preclinical modeling in neuro-oncology.
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