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.

项目总结/摘要 ALS是一种具有多种遗传病因的复杂疾病。尽管针对已知致病突变的药物 (e.g. SOD 1 ASO）可以治疗个体形式的ALS，但这种方法不能解决绝大多数病例 遗传病因不明此外，大量的因果基因和罕见的每一个遗传形式 这表明治疗ALS将需要许多患者特异性治疗或广泛有效的治疗。因此，在本发明中， 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 多种形式的ALS的治疗策略，特别是那些具有未知遗传病因的ALS。 使用来自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，显示ALS疾病表型，包括快速变性。我们进行 对ALS iMN进行表型筛选以鉴定最有效的治疗靶标。然而，iMN药物 反应是异质性的患者线，并探讨疾病机制和药物反应， 足够数量的线路是极其昂贵的并且是劳动密集型的。在这个变革性的项目中，我们将 通过将ALS iPSC疾病建模与日内瓦相结合， 我们为癌症治疗开发的新平台，使用单细胞转录组学来评估药物 对一个培养皿中的数十条患者管路产生影响。日内瓦使用基于SNP的计算解复用， 单细胞RNA-seq数据，以分析许多iPSC系库对治疗的反应。我们开发 计算工具，其分析scRNA-seq的高含量读数，以（i）精确地量化灵敏度 基于其在病例组和对照组人群中的代表性，（ii）确定 对药物应答的分子机制和可能的耐药机制，以及（iii） 揭示了由于每个品系内的异质性而导致的亚群之间的应答差异。日内瓦 将使ALS细胞系的药物发现规模增加10-50倍，并揭示疾病和药物反应 在单细胞分辨率的机制，使新的治疗靶点的发现与广泛的 有效性或高患者特异性。使用这种“培养皿中的人口”方法，GENEVA-ALS将确定 ALS患者队列中的神经退行性疾病和药物反应机制， 规模，消除了ALS药物发现的关键瓶颈。拟议的研究将1）建立 GENEVA-ALS population-in-a-dish平台，2）建立45例ALS的iMN疾病过程的时间图 线，3）验证了3个具有新作用机制的治疗靶点，这些作用机制在ALS中显示出广泛的疗效 iMN系，4）确定GENEVA-ALS是否可以在2期临床试验中预测ALS患者的疗效，以及5） 在30个ALS细胞系的全基因组CRISPRi筛选中确定新的治疗靶点。我们的研究试图改变 通过克服药物发现中患者异质性的关键障碍来改善目前的研究。