Functional identification of drug response and resistance in Richter's Syndrome

摘要(30行，宽泛，长期) 随着慢性淋巴细胞性白血病更有效的治疗方法的出现，人们更加重视寻找更好的治疗方法。 里希特综合征(RS)，因为这已成为最重要的未得到满足的医疗需求之一 慢性淋巴细胞性白血病患者。该项目的主要目标是利用功能精确医学技术来更好地 了解里希特细胞的生物脆弱性并确定新的药物干预措施 增加这些细胞中的凋亡信号。我们的首要任务是对RS患者的活样本进行直接研究 是与生物群落核心合作获得的。我们试图确定最有希望的组合，以 随后探索在RS患者的早期临床试验中，由其他机制资助。这份工作 精准医学的关键是将正确的病人与正确的药物相匹配。一种基因组测序策略已经 取得了几项成功，例如用EGFR抑制剂治疗EGFR突变肺癌；然而，到目前为止 RS在识别有针对性的基因异常方面没有让步，这将是项目的重点 1.在项目3中，我们提出了一种替代方法，我们称之为功能精准医学。而不是 依靠静态组学数据，我们建议通过干扰细胞功能的方式来识别活性药物。 这一策略的核心是BH3图谱，这是一种我们将活细胞的线粒体暴露于 合成BH3多肽并测量线粒体通透性。从这项测试中我们可以了解到哪个反病毒 细胞赖以生存的凋亡蛋白，无论是bcl2、bclxl、mcl1、它们的某种组合，还是 这些蛋白质都不是。这些信息具有直接的翻译应用，作为临床BH3模拟抑制剂 所有列出的三种蛋白质现在都存在。事实上，BH3图谱被用来指导bcl2抑制剂的治疗 Venotclax用于CLL和AML，这两种适应症现在已经获得FDA的批准。我们 建议使用BH3图谱来确定哪个BH3模拟物(S)在RS中最活跃。BH3分析可以 还提供了一个细胞离凋亡阈值有多近的综合衡量标准。当与一个 在药物暴露之前，动态BH3图谱(DBP)可以识别任何类别的药物 癌细胞中的凋亡信号，使它们更接近凋亡的阈值。我们之前已经 在几种液体和固体肿瘤环境中证明，该策略准确地将药物与体内的药物进行识别 对于单个肿瘤的活动性，并可以预测患者的临床反应。我们建议使用DBP来识别 活性药物，之后我们将探索它们相互结合并与适当的BH3一起使用 上面所说的模仿。当我们为RS样本小组确定药物脆弱性时，将在本 项目，我们将把它们与由 本P01中的其他项目和核心。我们希望利用这些信息来洞察上游 驱动药物诱导的细胞凋亡信号的信号机制。

Summary (30 lines, broad, long-term) With the advent of more effective therapies in CLL, there is a greater priority on identifying better treatment of Richter's Syndrome (RS), as this has become one of the most important unmet medical needs to address for CLL patients. The main goals of this Project are to utilize functional precision medicine techniques to better understand biological vulnerabilities in Richter's cells and to identify novel pharmacologic interventions to increase apoptotic signaling in these cells. Our priority is on the direct study of viable samples from RS patients obtained in collaboration with the Biospecimens core. We seek to identify the most promising combinations to subsequently explore in early phase clinical trials for patients with RS, funded by other mechanisms. The job of precision medicine is to match the right patient to the right drug. A strategy of genomic sequencing has yielded several successes, such as treating EGFR mutant lung cancer with EGFR inhibitors; however, to date RS has not yielded to the identification of targetable genetic abnormalities, and this will be the focus of Project 1. In Project 3, we propose an alternative approach, which we call functional precision medicine. Rather than rely on static -omic data, we propose to perturb cellular function in ways that allow us to identify active drugs. Central to this strategy is BH3 profiling, a technique in which we expose mitochondria from living cells to synthetic BH3 peptides and measure mitochondrial permeabilization. From this assay we can learn which anti- apoptotic proteins the cell relies on for survival, whether BCL-2, BCL-XL, MCL-1, some combination thereof, or none of these proteins. This information has direct translational application, as clinical BH3 mimetic inhibitors of all three listed proteins now exist. In fact, BH3 profiling was used to direct therapy of the BCL-2 inhibitor venetoclax to CLL and AML, two indications for which venetoclax has now received FDA approval. We propose to use BH3 profiling to identify which BH3 mimetic(s) would be most active in RS. BH3 profiling can also provide a summary measure of how close a cell is to the threshold of apoptosis. When coupled with a brief preceding drug exposure, dynamic BH3 profiling (DBP) can identify drugs from any class that induce apoptotic signaling in cancer cells, moving them closer to the threshold of apoptosis. We have previously demonstrated in several liquid and solid tumor contexts that this strategy accurately identifies drugs with in vivo activity for individual tumors, and can predict clinical response in patients. We propose to use DBP to identify active drugs, after which we will explore their use in combination with each other and with the appropriate BH3 mimetics identified above. As we identify drug vulnerabilities for the panel of RS samples to be studied in this Project, we will compare them with clinical, genomic, transcriptomic, and proteomic annotations prepared by other Projects and Cores in this P01. We hope to use this information to gain insight into the upstream signaling mechanisms that drive drug-induced apoptotic signaling.