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: 10270037
• 负责人: GAD A GETZ
• 金额: $ 39.63万
• 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/10270037
• 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病患者的治疗结果 淋巴细胞白血病（CLL）。然而，里氏综合症 (RS) 是将 CLL 转变为 侵袭性淋巴瘤（每年在 0.5-1% 的 CLL 患者中发生），通常对现有治疗无效 接近。基于我们当前 P01 的成功，创建了世界上最大的遗传驱动力图 和 CLL 的亚型 (n=~1100) 并使用它来构建预后模型，此更新应用程序旨在应用 类似的（和新的）方法来全面绘制 RS 的遗传基础。目前，并在 与 CLL 相比，人们对 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框架，也没有治疗开发的目标。 因此，了解转化的分子（遗传、表观遗传和蛋白质组）基础 从 CLL 到 RS 将为更有效的治疗干预、反应预测和 潜在的早期发现，所有这些都是为了改善患者的治疗结果。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 个 RS 病例的遗传和转录组状况，包括分析 他们的转化前 CLL 和 RS 样本。接下来，我们将进一步阐明两者之间的亲缘关系。 CLL 和 RS 使用部分病例的全基因组测序，并使用 染色质和组蛋白甲基化分析。此外，我们将追踪 CLL 细胞向 RS 和 RS 的演变。 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， 我们将结合这些数据来识别 RS 的分子亚型并将其与结果相关联。 (2) 定义 与从 CLL 到 RS 的转变相关的细胞电路的变化。我们将利用的力量 微尺度蛋白质组学和磷酸化蛋白质组学分析，以识别细胞过程接线的变化 与向 RS 的转化相关并创建 RS 的全面蛋白质组图谱。我们将确定 解除管制的信号通路和潜在的治疗靶点。最后，我们将蛋白质组数据整合到 完善上述确定的分子亚型，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 用于 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，我们将构建 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，旨在检测 血浆样本中 RS 特异性的改变。我们将测试是否可以在患者血液中检测到RS克隆 监测 RS 的出现、进展和复发。这些目标共同将创造第一个全面的 RS 图集，确定关键途径和潜在治疗靶点，并构建可能影响临床的工具 决策。