Overcoming Drug Resistance in Multiple Myeloma

总体摘要 MM是一种位于骨髓中的浆细胞肿瘤，具有显著的复杂性和 分子水平上的异质性。尽管临床结果有所改善 通过较新的治疗方法实现，对治疗的反应在个体之间存在很大差异 在获得一致的治疗效果或治疗方面的主要限制。不是所有的病人 对最初的治疗(先天抵抗)有反应，以及那些经常复发的 顽固性疾病(获得性抗药性)。我们正在讨论的中心假设是 多发性骨髓瘤的合理治疗发展应该建立在对 肿瘤的遗传学和生物学基础，识别对 当前和未来的药物。在这份骨髓瘤博士论文中，我们提出了3个项目，这些项目将： 1)建立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；并利用该平台筛选原发患者肿瘤 用于最有效反应的细胞，包括联合疗法；2)发展 将与药物相关的全面突变和生殖系变异小组 体外和体内反应以及毒性；3)确定其作用机制 治疗多发性骨髓瘤最常用的两种药物的疗效和耐药性 治疗：IMID和蛋白酶体抑制剂；4)开发遗传和免疫表型 有效预测肿瘤反应、耐药性和患者毒性的信号；5) 确定可能导致新出现的耐药性的肿瘤亚群；以及6) 确定预测耐药性的策略和克服耐药性的方法。

OVERALL 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.