Department of Neurosurgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410008, China; Department of Medicine, The University of Oklahoma Health Sciences Center, 975 NE 10th Street, BRC 1262A, Oklahoma City, OK, 73104, USA; Clinical Diagnosis and Therapy Center for Glioma of Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410008, China.
Department of Neurosurgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410008, China; Clinical Diagnosis and Therapy Center for Glioma of Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410008, China.
Cancer Lett. 2021 Mar 1;500:87-97. doi: 10.1016/j.canlet.2020.12.013. Epub 2020 Dec 10.
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.
建立与生理相关的神经胶质瘤肿瘤模型对于研究疾病进展和筛选药物候选物非常重要。然而，目前的临床前神经胶质瘤模型缺乏大脑微环境，且已建立的肿瘤细胞系不能代表神经胶质瘤生物学，也不能用于评估治疗效果。在这里，我们报道了一个实时的综合系统，该系统基于神经胶质瘤患者来源的组织和细胞生成 3D 离体脑类器官和体内异种移植肿瘤。我们的系统忠实地再现了其相应亲本肿瘤的组织学特征、对化疗药物的反应和临床进展。此外，我们的模型成功地从一名二级星形细胞瘤患者中鉴定出一个病例，该病例在类器官和异种移植模型中均具有典型的四级 GBM 特征，模拟了该患者的疾病进展。进一步的基因组和转录组特征分析与个体临床特征相关。我们已经证明了“GBM-正常样”特征可用于预测预后。总之，我们从患者来源的神经胶质瘤脑类器官和异种移植中开发了一种平行模型的综合系统，用于了解神经胶质瘤生物学和预测对化疗药物的反应，这可能为治疗这种致命疾病提供一种新的个体化治疗策略。
