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
基本信息
- 批准号:10270037
- 负责人:
- 金额:$ 39.63万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:ATAC-seqAtlasesAttentionB lymphoid malignancyBiological AssayBiological MarkersBiological ProcessBiologyBloodCell physiologyCellsChromatinChronic Lymphocytic LeukemiaClinical TrialsCollaborationsCollectionDataData SetDetectionDiseaseDissectionEarly DiagnosisEpigenetic ProcessEventEvolutionFundingFutureGeneticGenetic studyGenomeGenomicsGoalsHistologyIndividualIndolentLeadLymphomaMalignant NeoplasmsManuscriptsMapsMass Spectrum AnalysisMolecularMolecular GeneticsMonitorMutateMutationOutcomePathway interactionsPatient riskPatient-Focused OutcomesPatientsPatternPlasmaProteinsProteomicsRecurrenceRefractoryRelapseResolutionRichter&aposs SyndromeSamplingSignal PathwaySignal TransductionTestingTherapeuticTherapeutic InterventionVenipuncturesaccurate diagnosticsanalytical methodanticancer researchbasebisulfite sequencingcell free DNAchronic lymphocytic leukemia cellclinical decision-makingcohortdisorder controlepigenomeexomegenome analysisgenome sequencinghigh riskhistone methylationimprovedlarge cell Diffuse non-Hodgkin&aposs lymphomaleukemiamolecular subtypesnew therapeutic targetnovelnovel strategiesoutcome predictionphenomephosphoproteomicspredict clinical outcomepredicting responseprognostic modelrisk stratificationsingle cell analysissingle-cell RNA sequencingsuccesstargeted treatmenttherapeutic developmenttherapeutic targettherapeutically effectivetooltranscriptome sequencingtranscriptomicswhole genome
项目摘要
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
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
他们的转化前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
血浆样本中的RS特异性改变。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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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{{ truncateString('GAD A GETZ', 18)}}的其他基金
Center for comprehensive proteogenomic data analysis
综合蛋白质组数据分析中心
- 批准号:
10440579 - 财政年份:2022
- 资助金额:
$ 39.63万 - 项目类别:
Center for comprehensive proteogenomic data analysis
综合蛋白质组数据分析中心
- 批准号:
10644013 - 财政年份:2022
- 资助金额:
$ 39.63万 - 项目类别:
Comprehensive analysis of point mutations in cancer
癌症点突变综合分析
- 批准号:
10301857 - 财政年份:2021
- 资助金额:
$ 39.63万 - 项目类别:
Comprehensive analysis of point mutations in cancer
癌症点突变综合分析
- 批准号:
10491092 - 财政年份:2021
- 资助金额:
$ 39.63万 - 项目类别:
Comprehensive analysis of point mutations in cancer
癌症点突变综合分析
- 批准号:
10676830 - 财政年份:2021
- 资助金额:
$ 39.63万 - 项目类别:
Global Infrastructure for Collaborative High-throughput Cancer Genomics Analysis
协作高通量癌症基因组分析的全球基础设施
- 批准号:
9571405 - 财政年份:2016
- 资助金额:
$ 39.63万 - 项目类别:
Global Infrastructure for Collaborative High-throughput Cancer Genomics Analysis
协作高通量癌症基因组分析的全球基础设施
- 批准号:
9355157 - 财政年份:2016
- 资助金额:
$ 39.63万 - 项目类别:
Global Infrastructure for Collaborative High-throughput Cancer Genomics Analysis
协作高通量癌症基因组分析的全球基础设施
- 批准号:
10011769 - 财政年份:2016
- 资助金额:
$ 39.63万 - 项目类别:
Discovery of clinically distinct CLL subgroups by integrative mapping of large-scale CLL genetic, expression and clinical data
通过大规模 CLL 遗传、表达和临床数据的综合绘图发现临床上不同的 CLL 亚组
- 批准号:
10005157 - 财政年份:2016
- 资助金额:
$ 39.63万 - 项目类别:
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