Project 3 - Modeling Proteasome Inhibitor Response and Resistance in Cell Lines and Patient Samples with Single Cell Analysis of Subpopulations

项目3摘要 MM是一种位于骨髓中的浆细胞肿瘤，具有显著的复杂性和异质性。 分子水平。尽管较新的治疗方法在临床结果方面有所改善，但 对治疗反应的个体差异是实现一致治疗效果的主要限制，或者 治愈。并不是所有的患者对最初的治疗(先天抵抗)都有反应，而那些经常复发的患者 顽固性疾病(获得性抗药性)。我们正在讨论的中心假设是理性治疗 多发性骨髓瘤的发展应该建立在对肿瘤的潜在遗传学和生物学的了解的基础上 确定对当前和未来药物的敏感性和耐药性。在这个骨髓瘤-DrSc中，我们提出了3个 项目将：1)为代表骨髓瘤细胞系的高通量药物筛选平台 多发性骨髓瘤生物学的广泛多样性；并使用该平台筛选原始患者肿瘤细胞以获得最有效的 反应，包括联合治疗；2)发展全面的突变和生殖系变异 将与体外和体内药物反应以及毒性相关的专家小组；3)确定 多发性骨髓瘤治疗中两种最常见疗法的反应和耐药机制： IMID和蛋白酶体抑制剂；4)开发有效预测的遗传和免疫表型特征 肿瘤反应、耐药性和患者毒性；5)确定可能有助于 新出现的耐药性；以及6)确定预测耐药性的战略和克服的方法 抵抗。

PROJECT 3 ABSTRACT MM is a plasma cell neoplasm within the bone marrow with significant complexity and heterogeneity at the molecular level. Despite improvements in the clinical outcomes achieved with newer therapies, wide inter- individual variation in response to treatment is a major limitation in achieving consistent therapeutic effects, or cures. Not all patients respond to initial therapies (innate resistance), and those that do frequently relapse with refractory disease (acquired resistance). The central hypothesis we are addressing is that rational therapeutic development in MM should be based on an understanding of the underlying genetics and biology of the tumor that identify sensitivity and resistance to current and future drugs. In this Myeloma-DRSC we are proposing 3 Projects that will: 1) develop a high throughput drug screening platform for myeloma cell lines representing the wide diversity of MM biology; and use this platform to screen primary patient tumor cells for most effective responses, including combination therapies; 2) develop a comprehensive mutational and germline variation panel that will be correlated to drug responses in vitro and in vivo, as well as toxicities; 3) identify the mechanism of response and resistance for two of the most common therapeutics used in MM treatment: IMiDS and proteasome inhibitors; 4) develop genetic and immunophenotypic signatures that effectively predict tumor response, resistance, and patient toxicities; 5) identify tumor sub-populations that may contribute to emerging resistance; and 6) identify strategies to predict drug resistance and approaches to overcome resistance.