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用于溶酶体贮积症治疗方法开发的疾病模型。

Disease models for the development of therapies for lysosomal storage diseases.

作者信息

Xu Miao, Motabar Omid, Ferrer Marc, Marugan Juan J, Zheng Wei, Ottinger Elizabeth A

机构信息

National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, Maryland.

Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.

出版信息

Ann N Y Acad Sci. 2016 May;1371(1):15-29. doi: 10.1111/nyas.13052. Epub 2016 May 4.

Abstract

Lysosomal storage diseases (LSDs) are a group of rare diseases in which the function of the lysosome is disrupted by the accumulation of macromolecules. The complexity underlying the pathogenesis of LSDs and the small, often pediatric, population of patients make the development of therapies for these diseases challenging. Current treatments are only available for a small subset of LSDs and have not been effective at treating neurological symptoms. Disease-relevant cellular and animal models with high clinical predictability are critical for the discovery and development of new treatments for LSDs. In this paper, we review how LSD patient primary cells and induced pluripotent stem cell-derived cellular models are providing novel assay systems in which phenotypes are more similar to those of the human LSD physiology. Furthermore, larger animal disease models are providing additional tools for evaluation of the efficacy of drug candidates. Early predictors of efficacy and better understanding of disease biology can significantly affect the translational process by focusing efforts on those therapies with the higher probability of success, thus decreasing overall time and cost spent in clinical development and increasing the overall positive outcomes in clinical trials.

摘要

溶酶体贮积症(LSDs)是一组罕见疾病,其中溶酶体的功能因大分子的积累而受到破坏。LSDs发病机制的复杂性以及患者群体规模小且往往是儿童这一情况,使得开发针对这些疾病的疗法具有挑战性。目前的治疗方法仅适用于一小部分LSDs,并且在治疗神经症状方面效果不佳。具有高临床可预测性的疾病相关细胞和动物模型对于发现和开发LSDs的新疗法至关重要。在本文中,我们综述了LSD患者原代细胞和诱导多能干细胞衍生的细胞模型如何提供新的检测系统,其中的表型与人类LSD生理学的表型更为相似。此外,大型动物疾病模型为评估候选药物的疗效提供了额外的工具。疗效的早期预测指标以及对疾病生物学的更好理解可以通过将精力集中在那些成功可能性更高的疗法上,从而显著影响转化过程,进而减少临床开发中花费的总体时间和成本,并增加临床试验中的总体积极结果。

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