Chemical Neurobiology Laboratory, Departments of Neurology and Psychiatry, Massachusetts General Hospital, Center for Genomic Medicine, Harvard Medical School, Boston, Massachusetts.
Ann N Y Acad Sci. 2020 Jul;1471(1):18-56. doi: 10.1111/nyas.14012. Epub 2019 Mar 15.
Development of effective therapeutics for neurological disorders has historically been challenging partly because of lack of accurate model systems in which to investigate disease etiology and test new therapeutics at the preclinical stage. Human stem cells, particularly patient-derived induced pluripotent stem cells (iPSCs) upon differentiation, have the ability to recapitulate aspects of disease pathophysiology and are increasingly recognized as robust scalable systems for drug discovery. We review advances in deriving cellular models of human central nervous system (CNS) disorders using iPSCs along with strategies for investigating disease-relevant phenotypes, translatable biomarkers, and therapeutic targets. Given their potential to identify novel therapeutic targets and leads, we focus on phenotype-based, small-molecule screens employing human stem cell-derived models. Integrated efforts to assemble patient iPSC-derived cell models with deeply annotated clinicopathological data, along with molecular and drug-response signatures, may aid in the stratification of patients, diagnostics, and clinical trial success, shifting translational science and precision medicine approaches. A number of remaining challenges, including the optimization of cost-effective, large-scale culture of iPSC-derived cell types, incorporation of aging into neuronal models, as well as robustness and automation of phenotypic assays to support quantitative drug efficacy, toxicity, and metabolism testing workflows, are covered. Continued advancement of the field is expected to help fully humanize the process of CNS drug discovery.
开发针对神经紊乱的有效疗法一直具有挑战性,部分原因是缺乏准确的模型系统,无法在临床前阶段研究疾病病因和测试新疗法。人类干细胞,尤其是分化后的患者来源的诱导多能干细胞 (iPSC),具有再现疾病病理生理学某些方面的能力,并且越来越被认为是用于药物发现的强大可扩展系统。我们回顾了使用 iPSC 衍生人类中枢神经系统 (CNS) 疾病细胞模型的进展,以及研究与疾病相关表型、可转化生物标志物和治疗靶点的策略。鉴于它们有可能识别新的治疗靶点和先导化合物,我们专注于基于表型的小分子筛选,采用人干细胞衍生的模型。将患者 iPSC 衍生的细胞模型与经过深度注释的临床病理数据以及分子和药物反应特征进行整合,可能有助于患者分层、诊断和临床试验成功,推动转化科学和精准医学方法。涵盖了许多仍待解决的挑战,包括优化具有成本效益的 iPSC 衍生细胞类型的大规模培养、将衰老纳入神经元模型、以及表型测定的稳健性和自动化,以支持定量药物功效、毒性和代谢测试工作流程。预计该领域的持续进展将有助于使 CNS 药物发现过程完全实现个体化。