Generating an atlas of Richter's Syndrome: from molecular understanding to outcome prediction, detection and monitoring

项目摘要：最近的治疗进展极大地改善了慢性 淋巴细胞白血病（CLL）。然而，里希特综合征（RS），这是CLL的转变， 侵袭性淋巴瘤（每年发生在0.5-1%的CLL患者中）通常对现有的治疗方法难治。 接近。在我们目前的P01成功创建世界上最大的遗传驱动因子地图的基础上 和CLL亚型（n=~1100），并使用它来建立预后模型，这个更新的应用程序旨在应用 类似的（和新的）方法来全面绘制RS的遗传基础。目前，在 与CLL相比，RS的遗传学、克隆组成、驱动因素和细胞回路知之甚少，因此 既没有基于分子的风险分层的框架，也没有治疗开发的目标。 因此，了解转化的分子基础（遗传、表观遗传和蛋白质组）， 从CLL到RS将为更有效的治疗干预，预测反应， 潜在的早期检测，所有这些都是为了改善患者的预后。为了实现这些目标，我们建议 （1）定义RS的驱动因素，并描述RS与CLL和DLBCL的关系。使用全外显子组和 RNA测序，我们将研究>300 RS病例的遗传和转录组学景观，包括分析 转化前的CLL和RS样本。然后我们将进一步描述 CLL和RS使用病例子集的全基因组测序，并使用 染色质和组蛋白甲基化分析。此外，我们将追踪CLL细胞到RS的进化， 以单细胞分辨率确定遗传、表观遗传和转录组状态的不同模式。最后， 我们将联合收割机这些数据来鉴定RS的分子亚型并将它们与结果相关联。(2)定义 与CLL向RS转化相关的细胞回路变化。我们将利用 微尺度蛋白质组学和磷酸蛋白质组学分析，以确定细胞过程布线的变化 与转化为RS相关，并创建RS的综合蛋白质组图谱。我们将确定 去调节的信号通路和潜在的治疗靶点。最后，我们将整合蛋白质组学数据， 完善上述分子亚型，并开发高通量蛋白质组学检测， 检测这些亚型的生物标志物，并在一组独立的RS患者中验证它们。(3)开发一个 RS检测和监测的非侵入性工具。基于我们对RS基因组的理解，我们将建立 一种基于低通全基因组测序的稳健且廉价的无细胞DNA测定法，旨在检测 血浆样本中RS特异性变化。我们将测试我们是否能在患者血液中检测到RS克隆， 监测RS的出现、进展和复发。这些目标将共同创造第一个全面的 RS图谱，确定关键途径和潜在的治疗靶点，并构建可能影响临床的工具 决策。

Project Summary: Recent therapeutic advances have dramatically improved patient outcomes in chronic lymphocytic leukemia (CLL). However, Richter's Syndrome (RS), which is the transformation of CLL to an aggressive lymphoma (that occurs in 0.5-1% of CLL patients annually), is often refractory to existing therapeutic approaches. Building on the success of our current P01 in creating the world's largest map of genetic drivers and subtypes of CLL (n=~1100) and using it to build prognostic models, this renewal application seeks to apply similar (and new) approaches to comprehensively map the genetic underpinnings of RS. Currently, and in contrast to CLL, little is known about the genetics, clonal composition, drivers and cell circuitry of RS, and hence there is neither a framework for molecularly based risk stratification nor targets for therapeutic development. Therefore, understanding the molecular (genetic, epigenetic and proteomic) underpinnings of the transformation from CLL to RS will create opportunities for more effective therapeutic interventions, prediction of response, and potentially early detection, all with the goal of improving patient outcome. To achieve these goals, we propose to: (1) Define the drivers of RS and delineate the relationship of RS to CLL and DLBCL. Using whole-exome and RNA sequencing, we will study the genetic and transcriptomic landscape of >300 RS cases, including analyzing their pre-transformation CLL and RS samples. We will then further delineate the genetic relationship between CLL and RS using whole-genome sequencing of a subset of cases, and chart their epigenetic landscape using chromatin and histone methylation profiling. Moreover, we will trace the evolution of the CLL cells to RS and determine distinct patterns of genetic, epigenetic, and transcriptomic states at a single-cell resolution. Finally, we will combine these data to identify molecular subtypes of RS and associate them with outcome. (2) Define the changes in cellular circuitry associated with transformation from CLL to RS. We will use the power of microscaled proteomic and phosphoproteomic analysis to identify changes in the wiring of cellular processes associated with transformation to RS and create a comprehensive proteomic map of RS. We will identify deregulated signaling pathways and potential therapeutic targets. Finally, we will integrate the proteomic data to refine the molecular subtypes identified above as well as develop a high-throughput proteomic assay for detecting biomarkers of these subtypes and validate them in an independent set of RS patients. (3) Develop a non-invasive tool for RS detection and monitoring. Building on our understanding of the RS genome, we will build a robust and inexpensive cell-free DNA assay based on low-pass whole-genome sequencing aimed at detecting RS-specific alterations in plasma samples. We will test whether we can detect RS clones in patients' blood to monitor the emergence, progression and relapse of RS. Together, these Aims will create the first comprehensive atlas of RS, identify key pathways and potential therapeutic targets and build tools that could impact clinical decision making.