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Application of 454 Sequencing to Cancer Epigenomics

454测序在癌症表观基因组学中的应用

基本信息

批准号：
8068210
负责人：
HUIDONG SHI
金额：
$ 30.54万
依托单位：
AUGUSTA UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-05-01 至 2013-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8068210
关键词：
Aberrant DNA Methylation Affect Anatomy Automobile Driving B-Lymphocytes Base Sequence Behavior Binding Proteins Bioinformatics Biological Biological Markers Blood specimen CD19 gene Cells Chronic Lymphocytic Leukemia Classification Clinical Clinical Management Clinical Research Complex CpG Islands Cytosine DNA DNA Library DNA Methylation Data Diagnosis Early Diagnosis Enzymes Epigenetic Process Future Gene Targeting Generations Genes Genome Genomic Library Genomics Goals Gold Hot Spot Human Human Genome Imagery Individual Investigation Large-Scale Sequencing Lymphoblastic Leukemia Malignant Neoplasms Maps Measurement Methods Methylation Modeling Monitor Pathologic Patients Pattern Phenotype Play Preparation Reaction Regulation Research Resolution Resources Role Running Sampling Signaling Pathway Gene System Technology Testing Therapeutic Intervention Time Work analytical method base bisulfite design digital disorder subtype epigenomics genome-wide human disease innovation novel novel strategies outcome forecast peripheral blood promoter prototype response single molecule tool tumor tumor initiation tumor progression

项目摘要

DESCRIPTION (provided by applicant): Although epigenetic components play a major role in driving tumor progression in many human cancers, the methylation landscape in cancer epigenomes is still largely unexplored. Systematic sequence-based methylation analyses are notably absent and as a result, the potential clinical value of specific methylation differences and their biological impacts in cancers remain largely untapped. By identifying the aberrant methylation "hot spots" in the cancer epigenome, we can target these genes for therapeutic intervention and develop them into DNA methylation biomarkers for early detection, diagnosis, prognosis, and monitoring the response to therapy. However, to fully understand the interactions between methylation and clinical behaviors, new methods are needed to determine single-base-level specific methylation patterns across the genome. As an important clinical model for our work, we will examine subsets of chronic lymphocytic leukemia (CLL) to discover DNA methylation alterations that distinguish the sub-types of CLL and suggest underlying mechanisms for differential clinical behaviors and tumor progression. Successful completion of this study will substantially influence the clinical management of CLL patients and allow "up-front" administration of epigenetic therapies. To accomplish this, we will develop a high-throughput, large-scale, sequencing-based approach to provide efficient methods for deeply exploring the CLL methylome. In our preliminary study, we demonstrated that bisulfite sequencing can be carried out using an innovative massively parallel sequencing system (454-sequencing) that is capable of analyzing millions of DNA bases in a single run. This new generation of bisulfite sequencing will provide highly quantitative single methyl-cytosine resolution for specific methylation mapping in multiple CpG islands (CGIs). In this R33 application, we propose to optimize and develop a prototype high-throughput bisulfite sequencing method for ultra-deep analyses of DNA methylation patterns in primary CLL samples from CD38+ and CD38- CLL B-cells and test the hypothesis that the clinical behavior of subclasses of CLL can be defined in part by their distinct DNA methylation profiles that in turn affect multiple genes and signaling pathways. Specifically, we will: (1) develop a multiplexed amplicon preparation method for high-throughput, ultra-deep bisulfite sequencing; (2) develop a genome-scale approach for bisulfite sequencing of methylation-enriched genomic DNA libraries; (3) apply the innovative high-throughput bisulfite sequencing method to investigation of the CLL methylome. We believe that the technology developed will revolutionize the current analytical methods of DNA methylation, provide digital profiles of aberrant DNA methylation for individual human diseases and offer a deep-sequencing, robust method for epigenetic classification of disease subtypes.

描述(申请人提供)：尽管表观遗传成分在许多人类癌症中起着推动肿瘤进展的主要作用，但癌症表观基因组中的甲基化图景仍然很大程度上仍未被探索。基于序列的系统甲基化分析明显缺乏，因此，特定甲基化差异的潜在临床价值及其对癌症的生物学影响在很大程度上仍未被开发。通过识别癌症表观基因组中的异常甲基化热点，我们可以针对这些基因进行治疗干预，并将它们发展为DNA甲基化生物标志物，用于早期检测、诊断、预后和监测治疗反应。然而，为了充分了解甲基化和临床行为之间的相互作用，需要新的方法来确定整个基因组中单碱基水平的特定甲基化模式。作为我们工作的一个重要临床模型，我们将研究慢性淋巴细胞白血病(CLL)的亚型，以发现区分CLL亚型的DNA甲基化变化，并提出不同临床行为和肿瘤进展的潜在机制。这项研究的成功完成将对慢性淋巴细胞性白血病患者的临床治疗产生重大影响，并允许“预先”给予表观遗传疗法。为了实现这一目标，我们将开发一种高通量、大规模、基于测序的方法，为深入探索CLL甲基组提供有效的方法。在我们的初步研究中，我们证明了亚硫酸盐测序可以使用一种创新的大规模并行测序系统(454-测序)进行，该系统能够在一次运行中分析数百万个DNA碱基。这一新一代的亚硫酸氢盐测序将为多个CpG岛(CGI)中的特定甲基化图谱提供高度定量的单甲基胞嘧啶分辨率。在这一R33应用中，我们建议优化和开发一个原型高通量亚硫酸氢盐测序方法，用于超深入分析CD38+和CD38-CLL B-细胞的初级CLL样本中的DNA甲基化模式，并测试CLL亚类的临床行为可以部分由其不同的DNA甲基化特征定义，这反过来又影响多个基因和信号通路。具体地说，我们将：(1)开发一种用于高通量、超深度亚硫酸氢盐测序的多重扩增子制备方法；(2)开发一种基因组规模的甲基化富含亚硫酸氢盐的基因组DNA文库测序方法；(3)将创新的高通量亚硫酸氢盐测序方法应用于CLL甲基组的研究。我们相信，开发的技术将彻底改变目前的DNA甲基化分析方法，提供单个人类疾病异常DNA甲基化的数字图谱，并为疾病亚型的表观遗传学分类提供一种深度测序、稳健的方法。