Leveraging natural phenotypic variations of heterogenous ALS populations-in-a-dish to enable scalable drug discovery

利用培养皿中异质 ALS 群体的自然表型变异来实现可扩展的药物发现

• 批准号: 10478452
• 负责人: Hani Goodarzi
• 金额: $ 100.78万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-18 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10478452
• 关键词: ALS patients; Address; Amyotrophic Lateral Sclerosis; Antisense Oligonucleotides; Biological Models; CRISPR interference; Cell Line; Cells; Clinical Trials; Complex; Data; Disease; Disease model; Drug Targeting; Genetic; Genetic Predisposition to Disease; Heterogeneity; Individual; Malignant Neoplasms; Maps; Molecular; Motor Neuron Disease; Motor Neurons; Mus; Mutation; Nerve Degeneration; Outcome; Patients; Pharmaceutical Preparations; Pharmacotherapy; Phase II Clinical Trials; Phenotype; Population; Population Study; Process; Research; Resolution; Specificity; Tauopathies; Testing; Therapeutic Uses; Variant; arm; base; case control; causal variant; clinical predictors; cohort; computerized tools; disease phenotype; disease-in-a-dish; drug discovery; effective therapy; genome wide screen; genome-wide; in vivo; individualized medicine; induced pluripotent stem cell; innovation; insight; mirror neuron; motor function improvement; neurodegenerative phenotype; new therapeutic target; novel; patient-level barriers; protein TDP-43; resistance mechanism; response; screening; single-cell RNA sequencing; stem cell model; superoxide dismutase 1; therapeutic target; therapeutically effective; transcriptomics; treatment response

Project Summary/Abstract ALS is a complex disease with diverse genetic etiologies. Although drugs targeting known causal mutations (e.g. SOD1 ASOs) may treat individual forms of ALS, this approach cannot address the vast majority of cases with unknown genetic etiology. Moreover, the large number of causal genes and rarity of each genetic form suggest that treating ALS will require many patient-specific therapies or broadly-effective treatments. Thus, there is a pressing need for new, scalable approaches that identify patient-specific or broadly-effective therapeutic strategies for multiple forms of ALS, particularly those with unknown genetic etiologies. Studies using induced motor neurons (iMNs) from iPSCs indicate that iMNs from most ALS patients, including those without known mutations, display ALS disease phenotypes including rapid degeneration. We performed phenotypic screening on ALS iMNs to identify the most efficacious therapeutic targets. However, iMN drug responses are heterogeneous across patient lines, and probing disease mechanisms and drug responses on a sufficient number of lines is prohibitively expensive and labor intensive. In this transformative project, we will overcome this critical barrier in ALS drug discovery by combining ALS iPSC disease modeling with GENEVA, a novel platform we developed for cancer therapeutics that uses single cell transcriptomics to assess drug effects on dozens of patient lines in one dish. GENEVA uses SNP-based computational demultiplexing of single-cell RNA-seq data to profile responses to therapies across pools of many iPSC lines. We developed computational tools that analyze the high-content readout of scRNA-seq to (i) precisely quantify the sensitivity of every line based on its representation within the population in the case and control arm, (ii) identify the molecular mechanisms that underlie the response to the drug and possible mechanisms of resistance, and (iii) reveal differences in response between subpopulations as a result of heterogeneity within every line. GENEVA will increase the scale of ALS lines in drug discovery by 10-50-fold and reveal disease and drug response mechanisms at single cell resolution, enabling the discovery of new therapeutic targets with either broad efficacy or high patient specificity. Using this “population-in-a-dish” approach, GENEVA-ALS will identify neurodegenerative and drug response mechanisms across ALS patient cohorts at an unprecedented scale, removing a critical bottleneck in ALS drug discovery. The proposed study will 1) establish the GENEVA-ALS population-in-a-dish platform, 2) establish temporal maps of iMN disease processes for 45 ALS lines, 3) validate 3 therapeutic targets with novel mechanisms of action that show broad efficacy across ALS iMN lines, 4) determine if GENEVA-ALS can predict efficacy in ALS patients in a phase 2 clinical trial, and 5) identify new therapeutic targets in a genome-wide CRISPRi screen on 30 ALS lines. Our study seeks to shift current research by overcoming the critical barrier of patient heterogeneity in drug discovery.

项目摘要/摘要 ALS是一种具有潜水遗传病因的复杂疾病。尽管靶向已知因果突变的药物 （例如SOD1 ASOS）可以对待ALS的个体形式，这种方法无法解决绝大多数案件 具有未知的遗传病因。此外，每种遗传形式的大量因果基因和稀有性 建议治疗ALS需要许多患者特定的疗法或广泛有效的治疗方法。那， 迫切需要新的，可扩展的方法来识别患者特异性或广泛有效的方法 多种形式的ALS的治疗策略，尤其是患有未知遗传病因的ALS。 使用IPSC的诱导运动神经元（IMN）的研究表明，来自大多数ALS患者的IMN，包括 那些没有已知突变的人，显示ALS疾病表型，包括快速变性。我们表演了 在ALS IMN上进行表型筛选，以识别最有效的治疗靶标。但是，IMN药物 反应在患者方面是异质的，探测疾病机制和药物反应 足够数量的线路被禁止昂贵且劳动密集型。在这个变革性的项目中，我们将 通过将ALS IPSC疾病建模与日内瓦（Geneva 我们为癌症治疗开发的新型平台，该平台使用单细胞转录组学评估药物 一道菜肴中数十个患者线的影响。日内瓦使用基于SNP的计算拼写 单细胞RNA-seq数据对跨许多IPSC线池的疗法的概况响应。我们开发了 分析scrna-seq高读数为（i）的计算工具，准确地量化了灵敏度 根据案件中人口中的代表和控制部门的每一行，（ii）确定 分子机制是对药物反应和抗药性机制的基础，（iii） 揭示了由于每条线内的异质性而导致亚群之间的响应差异。日内瓦 将增加10-50倍的药物发现中ALS系的规模，并显示出疾病和药物反应 单细胞分辨率的机制，可以发现新的治疗靶标的 有效或高患者特异性。使用这种“人口中的”方法，日内瓦人将确定 ALS患者队列的神经退行性和药物反应机制在空前 扩展，去除ALS药物发现中的关键瓶颈。拟议的研究将1）建立 日内瓦人在偏见平台中，2）为45个ALS建立IMN疾病过程的临时地图 线，3）验证3种具有新型作用机制的治疗靶标，这些靶标在ALS之间显示出广泛的效率 IMN线，4）确定Geneva-Als是否可以预测2期临床试验中ALS患者的效率，而5） 在30个ALS线上的全基因组CRISPRI筛选中确定新的治疗靶标。我们的研究试图转移 当前的研究通过克服药物发现中患者异质性的关键障碍。