Targeted Chemical-Genetic Screen Platform for Identifying Novel AML Therapeutics

用于识别新型 AML 疗法的靶向化学基因筛选平台

• 批准号: 10615603
• 负责人: Kevin Jeng-Yen Lin
• 金额: $ 4.03万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10615603
• 关键词: Acute Myelocytic Leukemia; Address; Algorithms; Biochemical; Biological; Biological Assay; Biological Process; Biological Sciences; Biology; CRISPR library; CRISPR screen; CRISPR/Cas technology; Cancer Patient; Cell Line; Cell Survival; Cells; Chemical Actions; Chemicals; Clinical; Clinical Oncology; Clustered Regularly Interspaced Short Palindromic Repeats; Collection; Computing Methodologies; Data; Drug Compounding; Drug Screening; Drug Targeting; FDA approved; Fingerprint; Future; Gene Mutation; Genes; Genetic; Genetic Screening; Genomics; Goals; Haploidy; Human; Human Cell Line; Human Genetics; Human Genome; In Vitro; Knock-out; Knowledge; Laboratories; Lead; Libraries; Malignant Neoplasms; Measurement; Measures; Methods; Molecular Target; Mutation; Oncology; Output; Patients; Pharmaceutical Preparations; Phenotype; Physicians; Process; Prognosis; Property; Resistance; Resources; Saccharomyces cerevisiae; Scientist; Speed; Survival Rate; TP53 gene; TP53-mutant acute myeloid leukemia; Testing; Therapeutic; Tissues; Training; Translating; Universities; Work; acute myeloid leukemia cell; analysis pipeline; chemical genetics; computational pipelines; computerized tools; cost; drug candidate; drug development; drug discovery; effective therapy; genetic predictors; genome wide screen; high-throughput drug screening; improved; inhibitor; interest; mutant; novel; novel therapeutics; patient subsets; precision medicine; precision oncology; response; screening; small molecule; small molecule inhibitor; targeted treatment; therapeutically effective; tool development; treatment strategy

PROJECT ABSTRACT Over 93% of cancer patients do not receive therapeutic benefit from oncology precision medicine. This can be partly attributed to 1) not understanding the genetic targets and modes-of-action of putative targeted therapies, and 2) lack of a well-characterized comprehensive drug compound library. To address these challenges, a shift in the drug discovery paradigm from “target-centric” to “chemical-centric” approaches is necessary. One such approach is chemical genomics, which involves screening drug compounds against a collection of defined gene mutants to identify mutations that sensitize or suppress a drug’s effect. These chemical-genetic interactions can be quantified by measuring mutants’ cell viability in the presence of compounds of interest. The entire set of mutant viability measurements for a given compound, called a “profile”, can then be used as a “fingerprint” to understand a drug’s modes-of-action. These screens can be performed in human cell lines using a pooled lentiviral CRISPR-Cas9 approach. While current genome-wide screens (~70,000 sgRNAs targeting ~18,000 genes) can inform candidate chemical compounds for drug development, many labs do not have the resources to perform these large-scale screens for more than a small number of compounds. Recent preliminary data from our labs show that screens with a small targeted CRISPR library (~3,000 sgRNAs targeting ~1,000 genes) can 1) recover similar biological information in a compressed library compared to genome-wide screens, and 2) reduce resource costs to allow for higher-throughput drug screening. TP53-mutant acute myeloid leukemia (AML) patients currently have very poor prognosis (1-2 year survival rates of 0-10%). There are currently no effective therapeutics for this patient subpopulation. However, a recent study showed that a TP53 KO AML cell line showed increased sensitivity to a panel of small-molecule inhibitors. The targeted chemical-genetic screen approach we develop here can reveal the genetic targets of these putative drugs to help with prioritizing lead compounds for drug development. The overall goal of this proposal is to develop a targeted CRISPR-Cas9 chemical-genetic screen approach and to develop a computational method to predict drug mode-of-action from chemical-genetic interaction data. I will pursue the following aims: (1a) develop and validate targeted screens in human cell lines, (1b) develop a computational method to score chemical-genetic interactions, rank candidate drug targets, and predict drug mode-of-action, and (2) elucidate mechanism-of-action of putative drug inhibitors for TP53-mutant AML using this targeted chemical-genetic screen approach. Completion of this study will result in a method for efficient discovery of drug mode-of-action and has implications for better understanding of how cancer (AML) therapeutics work. This work will also advance my understanding of computational tool development and application in clinical oncology, as well as further my training to become a computational physician-scientist.

项目摘要 超过93%的癌症患者没有从肿瘤精准医学中获得治疗益处。这可以 部分归因于1）不理解假定的靶向治疗的遗传靶点和作用模式， 和2）缺乏良好表征的综合药物化合物库。为了应对这些挑战， 在药物发现范式中，从"以靶标为中心"到"以化学为中心"的方法是必要的。 一种这样的方法是化学基因组学，其涉及针对一系列药物筛选药物化合物。 定义基因突变体，以确定敏感或抑制药物作用的突变。这些化学基因 可以通过在感兴趣的化合物存在下测量突变体的细胞活力来定量相互作用。 给定化合物的突变体生存力测量的整个集合，称为"概况"，然后可以用作 “指纹”来了解药物的作用模式。这些筛选可以在人类细胞系中进行 使用合并的慢病毒CRISPR-Cas9方法。虽然目前的全基因组筛选（约70，000个sgRNA 靶向约18，000个基因）可以为药物开发提供候选化合物，但许多实验室没有 有足够的资源来进行这些大规模的筛选，以获得更多的化合物。最近 我们实验室的初步数据显示，使用小的靶向CRISPR文库（约3，000个sgRNA）进行筛选， 靶向~1，000个基因）可以1）在压缩文库中恢复类似的生物信息， 全基因组筛选，以及2）降低资源成本以允许更高通量的药物筛选。 TP53突变型急性髓性白血病（AML）患者目前具有非常差的预后（1 - 2年存活 0 - 10%）。目前尚无针对该患者亚群的有效治疗方法。但最近的一项 一项研究表明，TP53 KO AML细胞系对一组小分子药物的敏感性增加， 抑制剂的我们在这里开发的靶向化学遗传筛选方法可以揭示 这些推定的药物，以帮助优先考虑药物开发的先导化合物。 该提案的总体目标是开发一种靶向CRISPR-Cas9化学遗传筛选方法， 开发一种计算方法，根据化学-遗传相互作用数据预测药物的作用模式。我会 追求以下目标：（1a）开发和验证人类细胞系中的靶向筛选，（1b）开发 对化学-遗传相互作用进行评分、对候选药物靶点进行排名并预测药物的计算方法 作用模式，和（2）阐明TP53突变AML的推定药物抑制剂的作用机制，使用 这种有针对性的化学基因筛选方法。这项研究的完成将导致一种有效的方法， 发现药物作用模式，并对更好地了解癌症（AML） therapeutic治疗work.这项工作也将促进我对计算工具开发的理解， 在临床肿瘤学中的应用，以及进一步培训我成为一名计算物理学家科学家。