Effect of Network-Correcting Molecules on NOTCH1 (N1)-Haploinsufficient Human Induced Pluripotent Stem Cell (iPSC)-Derived Endothelial Cells (ECs)

Discovery of small molecules that correct gene networks dysregulated in human disease may allow identification of therapies that treat disease at its fundamental basis by leveraging mechanism-based data. Here, we report the first broad gene network-based drug screen, which led to discovery of a drug candidate that effectively treats aortic valve disease in an animal model. We previously reported haploinsufficiency of NOTCH1 (N1) as a genetic cause of human aortic valve thickening and calcification, the third most common form of heart disease, and described the resulting gene network dysregulation in human induced pluripotent stem cell (iPSC)-derived endothelial cells (ECs). We exposed isogenic N1+/+ or N1+/– iPSC-derived ECs to each of 1595 small molecules or control and developed a machine learning approach that accurately distinguished WT or N1-haploinsufficient cells based on expression of 119 genes assayed by targeted RNA-sequencing. 9 small molecules corrected the gene network of N1+/– ECs sufficiently to be classified as WT. Among hits tested in vivo, the estrogen receptor-related alpha inverse agonist XCT790 significantly reduced aortic valve thickening, calcification, and stenosis in N1-haploinsufficient mice with shortened telomeres, which model the range of age-dependent cardiac disease observed in humans. This strategy, made feasible by human iPSC technology, next generation sequencing approaches, and machine learning, may represent a more effective path for drug discovery compared to conventional screening approaches. Overall design: RNA-seq on WT vs N1-haploinsufficient iPSC-derived ECs exposed to DMSO or one of 9 network-correcting small molecules (Fmoc-leu, RO4929097, Cytochalasin, GSK837149A, CB1954, Biperiden, TG003, Putrescine, XCT790)

发现可纠正人类疾病中失调基因网络的小分子，或可借助基于机制的数据，识别从根本上治疗疾病的疗法。本研究首次报道了基于宽泛基因网络的药物筛选，由此发现了一种可在动物模型中有效治疗主动脉瓣疾病的候选药物。此前我们曾报道，NOTCH1（N1）的单倍体剂量不足（haploinsufficiency）是人类主动脉瓣增厚与钙化的遗传病因——这是第三大常见心脏病——并描述了人类诱导多能干细胞（induced pluripotent stem cell, iPSC）来源的内皮细胞（endothelial cells, ECs）中由此产生的基因网络失调情况。我们将同基因背景的N1+/+或N1+/- iPSC来源的ECs分别用1595种小分子及对照进行处理，并开发了一种机器学习方法，可基于靶向RNA测序检测的119个基因的表达水平，准确区分野生型（wild type, WT）或N1单倍体剂量不足的细胞。共有9种小分子可充分纠正N1+/- ECs的基因网络，使其表达特征被归类为野生型。在体内测试的命中化合物中，雌激素受体相关α反向激动剂XCT790可显著改善端粒缩短的N1单倍体剂量不足小鼠的主动脉瓣增厚、钙化与狭窄症状；该小鼠模型可模拟人类中观察到的各类年龄相关性心脏病。这一依托人类iPSC技术、下一代测序技术与机器学习方法得以实现的策略，相较于传统筛选方法，或可成为更高效的药物开发路径。总体实验设计：对暴露于二甲基亚砜（DMSO）或9种可纠正基因网络的小分子（Fmoc-亮氨酸、RO4929097、细胞松弛素、GSK837149A、CB1954、比哌立登、TG003、腐胺、XCT790）的WT与N1单倍体剂量不足iPSC来源的ECs进行RNA测序。