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Project 1 - High Throughtput Drug Screening and Correlations with Mutational Status in Myeloma Cell Lines and Patient Samples

项目 1 - 高通量药物筛选及其与骨髓瘤细胞系和患者样本突变状态的相关性

基本信息

批准号：
10006208
负责人：
ALEXANDER KEITH STEWART
金额：
$ 33.27万
依托单位：
MAYO CLINIC ARIZONA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10006208
关键词：
Acoustics Address Aftercare Alternative Therapies Animal Model Biological Markers Bromodomain Cancer Therapy Evaluation Program Cell Line Cells Characteristics Chronic Clinical Clinical Data Clinical Trials DNA Library DNA Sequence Alteration Data Data Analyses Data Set Databases Disease Dose Drug Combinations Drug Costs Drug Screening Drug resistance Elements Epigenetic Process FDA approved Feedback Frequencies Genetic Transcription Genomics Goals Grant Human Immunomodulators In Vitro Investigation Laboratories Light Link Measures Methodology Mosaicism Multiple Myeloma Mus Mutation Oncology Outcome Patients Pharmaceutical Preparations Phase II Clinical Trials Proteasome Inhibition Proteasome Inhibitor Proteomics RNA Relapse Resistance Robotics Route Sampling Source Technology Testing Therapeutic Therapeutic Clinical Trial Toxic effect Work base clinical phenotype drug sensitivity experience gene panel high throughput screening high-throughput drug screening improved in vivo individual patient individualized medicine inhibitor/antagonist innovation mutational status novel drug combination prevent programs resistance gene resistance mechanism response robotic system screening single-cell RNA sequencing synergism targeted treatment

项目摘要

PROJECT 1 SUMMARY/ABSTRACT Despite recent advances in therapy the majority of multiple myeloma (MM) patients are not cured but rather suffer from a chronic relapsing, yet ultimately fatal disease. Two challenges immediately become evident. Most urgent is the need to find alternative therapies for patients who fail existing potent drug classes. Second, is to understand why patients may be resistant in the first place and to seek methodologies, dosing strategies and new drug combinations which can prevent or overcome drug-resistant relapse. We propose an innovative strategy of “direct to drug” screening of 500 primary patient samples with chemogenomic interrogation which addresses both of these two big questions. Our hypothesis is that a direct to drug analysis of individual patients will improve response rates, lower unnecessary toxicity and reduce drug costs through identification of the most effective combinations of FDA approved drugs for each patient. This strategy will also, for the purposes of this proposal, provide a database of samples and clinical data sets from which to explore genomic or clinical correlates of drug sensitivity and resistance. Our goal will be attained through the successful pursuit of three specific aims, building upon extensive cell line and primary patient sample data. First, we will measure the in vitro sensitivity of 79 MM therapeutics including CTEP compounds in 500 primary myeloma patient samples. Second, we will conduct combination screens to seek synergistic combinations of IMiDs and proteasome inhibitors as base compounds with other active MM therapeutics such as bromodomain inhibitors which can be tested in animal models such as the human CRBN mouse in project 2. Third, using our M3P mutation panels, we will conduct a chemogenomic interrogation to examine specific correlates of drug sensitivity and resistance utilizing pre-treatment and surviving cells from primary patient robotic screens. These studies will determine the frequency of specific genetic mutation or cellular subsets resistant to the most active drugs or drug combinations used in MM therapy and will be shared throughout the program for further epigenetic and transcriptional analysis and bi-directional feedback derived from both Projects 2 and 3. Critical to the current U54 application this strategy will provide a database of 500 multiple myeloma samples and linked clinical data sets which together build a mosaic of drug sensitivity and clinical phenotype from which all elements of this program grant can exploit to explore genomic or clinical correlates of drug sensitivity and resistance.

项目 1 摘要/摘要尽管治疗方面最近取得了进展，但大多数多发性骨髓瘤 (MM) 患者并未治愈，而是患有慢性复发但最终致命的疾病。两个挑战立即变得显而易见。最多迫切需要为现有有效药物类别失败的患者找到替代疗法。其次，就是为了首先了解患者为何可能产生耐药性，并寻求方法、剂量策略和可以预防或克服耐药性复发的新药物组合。我们提出了一项创新策略，即对 500 份主要患者样本进行“直接药物”筛查化学基因组学审讯解决了这两大问题。我们的假设是直接对个体患者进行药物分析将提高反应率、降低不必要的毒性并减少药物用量通过确定 FDA 批准的药物对每位患者最有效的组合来降低成本。这出于本提案的目的，战略还将提供来自以下来源的样本和临床数据集的数据库：探索药物敏感性和耐药性的基因组或临床相关性。我们的目标将通过在广泛的细胞系的基础上成功追求三个具体目标来实现和主要患者样本数据。首先，我们将测量 79 种 MM 疗法的体外敏感性，包括 500 名原发性骨髓瘤患者样本中的 CTEP 化合物。其次，我们将进行组合筛选寻求 IMiD 和蛋白酶体抑制剂作为基础化合物与其他活性 MM 的协同组合治疗药物，例如溴结构域抑制剂，可以在人类 CRBN 等动物模型中进行测试项目 2 中的小鼠。第三，使用我们的 M3P 突变面板，我们将进行化学基因组学询问利用预处理和存活细胞检查药物敏感性和耐药性的特定相关性主要患者机器人屏幕。这些研究将确定特定基因突变的频率或对 MM 治疗中使用的最活性药物或药物组合具有耐药性的细胞亚群将被共享在整个计划中进行进一步的表观遗传和转录分析以及衍生的双向反馈来自项目 2 和 3。该策略对当前 U54 应用至关重要，将提供包含 500 个多发性骨髓瘤样本的数据库并链接临床数据集，共同构建药物敏感性和临床表型的镶嵌图该计划拨款的所有要素均可用于探索药物敏感性的基因组或临床相关性以及反抗。