胶质瘤
医学
癌症研究
类有机物
体内
离体
转录组
化疗
肿瘤微环境
脑瘤
疾病
星形细胞瘤
病理
生物
肿瘤科
内科学
神经科学
肿瘤细胞
基因
基因表达
生物技术
生物化学
作者
Liyang Zhang,Fangkun Liu,Nathaniel Weygant,Junxia Zhang,Ping Hu,Zailong Qin,Jingxuan Yang,Quan Cheng,Fan Fan,Yu Zeng,Yongjian Tang,Yusheng Li,Anliu Tang,Fengqiong He,Jun Peng,Weihua Liao,Zhongliang Hu,Min Li,Zhixiong Liu
出处
期刊:Cancer Letters
[Elsevier BV]
日期:2020-12-10
卷期号:500: 87-97
被引量:51
标识
DOI:10.1016/j.canlet.2020.12.013
摘要
A physiologically relevant glioma tumor model is important to the study of disease progression and screening drug candidates. However, current preclinical glioma models lack the brain microenvironment, and the established tumor cell lines do not represent glioma biology and cannot be used to evaluate the therapeutic effect. Here, we reported a real-time integrated system by generating 3D ex vivo cerebral organoids and in vivo xenograft tumors based on glioma patient-derived tissues and cells. Our system faithfully recapitulated the histological features, response to chemotherapy drugs, and clinical progression of their corresponding parental tumors. Additionally, our model successfully identified a case from a grade II astrocytoma patient with typical grade IV GBM features in both organoids and xenograft models, which mimicked the disease progression of this patient. Further genomic and transcriptomic characterization was associated with individual clinical features. We have demonstrated the “GBM-&Normal-like” signature to predict prognosis. In conclusion, we developed an integrated system of parallel models from patient-derived glioma cerebral organoids and xenografts for understanding the glioma biology and prediction of response to chemotherapy drugs, which might lead to a new strategy for personalized treatment for this deadly disease.
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