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诱导性多能干细胞与神经系统疾病模型的构建(英文) 被引量:4

Induced pluripotent stem cells and neurological disease models
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摘要 利用外源性转录因子将已分化成熟的细胞诱导为多能干细胞(induced pluripotent stem cells,iPS细胞)对构建神经发育性和神经退行性疾病的体外模型具有重要意义。从患有特定疾病或具有明确遗传基因异常的患者身上获取体细胞进行诱导建立的iPS细胞具有潜在的疾病原特质,这种疾病特异性iPS细胞可以用来研究疾病的发病机制和病理过程,也为药物筛选、药物毒性检测以及个体化治疗方案的制定提供了可能。本文概述了目前用于建立神经系统疾病模型的干细胞类型,重点讨论了利用iPS细胞技术建立脊髓性肌萎缩症、肌萎缩性脊髓侧索硬化症和帕金森病等常见中枢神经系统疾病模型和药物干预的最新进展,并对该研究领域所面临的问题进行了详尽的分析。 The availability of human stem cells heralds a new era for in vitro cell-based modeling of neurodevelopmental and neuro- degenerative diseases. Adding to the excitement is the discovery that somatic cells of patients can be reprogrammed to a pluripotent state from which neural lineage cells that carry the disease genotype can be derived. These in vitro cell-based models of neurological diseases hold promise for monitoring of disease initiation and progression, and for testing of new drug treatments on the patient- derived cells. In this review, we focus on the prospective applications of different stem cell types for disease modeling and drug screening. We also highlight how the availability of patient-specific induced pluripotent stern cells (iPS cells) offers a unique opportunity for studying and modeling human neurodevelopmental and neurodegenerative diseases in vitro and for testing small molecules or other potential therapies for these disorders. Finally, the limitations of this technology from the standpoint of reprogramming efficiency and therapeutic safety are discussed.
出处 《生理学报》 CAS CSCD 北大核心 2014年第1期55-66,共12页 Acta Physiologica Sinica
基金 supported in part by the HKRGC-General Research Fund(No.777810) NSFC/RGC-Joint Research Scheme(No.N_HKU741/11) Innovation and Technology Fund(No.100/10) SK Yee Medical Research Fund,the National Natural Science Foundation of China(No.81000011,81272080) the Strategic Research Theme of the University Research Committee,The University of Hong Kong
关键词 胚胎干细胞 诱导性多能干细胞 神经系统疾病 疾病模型 药物筛选 embryonic stem cells induced pluripotent stem cells neurological diseases disease modeling drug screening
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