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

生成里氏综合症图谱：从分子理解到结果预测、检测和监测

• 批准号: 10491136
• 负责人: GAD A GETZ
• 金额: $ 38.03万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10491136
• 关键词: ATAC-seq; Atlases; Attention; B lymphoid malignancy; Biological Assay; Biological Markers; Biological Process; Biology; Blood; Cell physiology; Cells; Chromatin; Chronic Lymphocytic Leukemia; Clinical Trials; Collaborations; Collection; Data; Data Set; Detection; Disease; Dissection; Early Diagnosis; Epigenetic Process; Event; Evolution; Funding; Future; Genetic; Genetic study; Genome; Genomics; Goals; Histology; Individual; Indolent; Lead; Lymphoma; Malignant Neoplasms; Manuscripts; Maps; Mass Spectrum Analysis; Molecular; Molecular Genetics; Monitor; Mutate; Mutation; Outcome; Pathway interactions; Patient risk; Patient-Focused Outcomes; Patients; Pattern; Plasma; Proteins; Proteomics; Recurrence; Refractory; Relapse; Resolution; Richter' s Syndrome; Sampling; Signal Pathway; Signal Transduction; Testing; Therapeutic; Therapeutic Intervention; Venipunctures; accurate diagnostics; analytical method; anticancer research; base; bisulfite sequencing; cell free DNA; chronic lymphocytic leukemia cell; clinical decision-making; cohort; disorder control; epigenome; exome; genome analysis; genome sequencing; high risk; histone methylation; improved; large cell Diffuse non-Hodgkin' s lymphoma; leukemia; molecular subtypes; new therapeutic target; novel; novel strategies; outcome prediction; phenome; phosphoproteomics; predict clinical outcome; predicting response; prognostic model; risk stratification; single cell analysis; single-cell RNA sequencing; success; targeted treatment; therapeutic development; therapeutic target; therapeutically effective; tool; transcriptome sequencing; transcriptomics; whole genome

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.

项目摘要：最近的治疗进展极大地改善了慢性的患者结果 淋巴细胞白血病（CLL）。但是，里希特综合征（RS），这是CLL转换为 侵袭性淋巴瘤（每年发生0.5-1％的CLL患者）通常对现有治疗性难治性 方法。以我们当前P01成功创建世界上最大的遗传驱动力地图的基础 和Cll的子类型（n = 〜1100）并使用它来构建预后模型，此续订应用程序寻求应用 类似（和新的）方法可全面绘制卢比的遗传基础。目前，以及 与CLL形成鲜明对比的是，关于Rs的遗传学，克隆组成，驱动因素和细胞电路几乎不知情，因此 既没有基于分子的风险分层的框架，也没有治疗性发育的目标。 因此，了解转化的分子（遗传，表观遗传和蛋白质组学）基础 从CLL到RS，将为更有效的治疗干预，反应预测和 潜在的早期检测，所有目的都是改善患者结局。为了实现这些目标，我们建议 至：（1）定义RS的驱动程序，并描述RS与CLL和DLBCL的关系。使用全外观和 RNA测序，我们将研究> 300 rs病例的遗传和转录景观，包括分析 它们的预先转化CLL和RS样品。然后，我们将进一步描述 使用一部分病例的全基因组测序的CLL和RS，并使用其表观遗传景观绘制 染色质和组蛋白甲基化分析。此外，我们将追踪CLL细胞的演变为Rs，并 在单细胞分辨率下确定遗传，表观遗传和转录态状态的不同模式。最后， 我们将结合这些数据以识别Rs的分子亚型，并将它们与结果相关联。 （2）定义 与从CLL转换为Rs的转化相关的细胞电路的变化。我们将利用 显微镜蛋白质组学和磷酸蛋白质组学分析，以鉴定细胞过程的接线变化 与转换为RS并创建Rs的综合蛋白质组学图有关。我们将确定 放松调节的信号通路和潜在的治疗靶标。最后，我们将将蛋白质组学数据集成到 完善上面鉴定的分子亚型，并开发高通量蛋白质组学测定 检测这些亚型的生物标志物并在独立的RS患者中验证它们。 （3）开发 用于RS检测和监测的非侵入性工具。在我们对RS基因组的理解的基础上，我们将建立 基于低通的全基因组测序的健壮且廉价的无细胞DNA分析，旨在检测 血浆样品的RS特异性变化。我们将测试是否可以检测到患者血液中的RS克隆 监控Rs的出现，进展和复发。这些目标在一起将创造第一个综合 卢比的地图集，确定关键途径和潜在的治疗目标，并建立可能影响临床的工具 决策。