Massively Parallel Sequencing Technology for Cancer Epigenome.
Massively Parallel Sequencing Technology for Cancer Epigenome.
批准号:
7796888
负责人:
Lanlan Shen
金额:
$17.34万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-04-01 至 2013-03-31
关键词:
Aberrant DNA MethylationAddressAlgorithmsBiologicalBiological AssayBiological TestingCancer DetectionCancer PatientCancer PrognosisCancer cell lineColonCoupledCouplingCpG IslandsDNADNA LibraryDNA MethylationDataData AnalysesDevelopmentEmerging TechnologiesEnvironmental ExposureEpigenetic ProcessFutureGene MutationGene SilencingGenesGenomeGoalsHematologic NeoplasmsHumanLibrariesLiverMalignant NeoplasmsMeasuresMethodsMethylationNational Cancer InstituteNeoplasmsPatientsPerformancePhasePrimary NeoplasmProtocols documentationQuality ControlResearchResolutionSamplingSensitivity and SpecificitySimulateSpecificitySpecimenTechniquesTechnologyTimeTumor Cell LineValidationVariantanticancer researchcancer cellcancer therapycostcross reactivitydesigndrug discoverygenome-widehigh throughput analysisimprovedinnovationinsightnext generationpreventpromoterresponsesingle moleculetooltumortumorigenesis
中文摘要
描述(由申请人提供):甲基化CpG岛扩增(Methylated CpG island amplification, MCA)是一种DNA文库构建技术,可以在整个基因组中扩增146,148个富含甲基化CpG的区域,覆盖76%的所有基因和70%的真正CpG岛。当与微阵列相结合时,该技术已被证明是高度特异性的,对于正常细胞和癌细胞全基因组甲基化的高通量分析非常有用。然而,诸如探针性能不均匀、交叉反应性、标准化困难以及相关控制问题等问题阻碍了MCA的全部定量潜力的实现。我们建议通过将MCA与“下一代”Solexa 1G测序技术(MCA- seq)相结合,开发并验证一种高分辨率的DNA甲基化分析工具。在项目的R21阶段,我们将采用各种策略来优化MCA-Seq,以提高覆盖率并减少所需初始DNA的数量。此外,我们将为MCA-Seq建立质量控制,并为数据分析开发优化算法。然后,我们将验证优化的MCA-Seq方案,并使用模拟甲基化生物学变异的创新方法评估灵敏度、特异性和定量准确性。我们提出的研究将导致开发一种简单,稳健,可靠的DNA甲基化全基因组分析方法,这将在癌症研究中具有广泛的用途。我们的长期目标是利用这项技术来测试生物学假说。因此,在该项目的R33阶段,我们计划通过在一组具有良好特征的肿瘤细胞系和原发性癌症患者样本中应用MCA-Seq来全面实施这一新兴技术。这些未来的研究将进一步验证MCA-Seq准确描述高度可变和异常的癌症表观基因组的能力,并产生初步的生物学数据。MCA-Seq的开发和验证将使我们对导致癌症的基本生物学机制的理解取得重大进展,并可能有助于设计未来的癌症治疗方法。
英文摘要
DESCRIPTION (provided by applicant): Methylated CpG island amplification (MCA) is a DNA library construction technique that permits amplification of 146,148 methylated CpG rich regions throughout the whole genome, covering 76% of all genes and 70% of all bona fide CpG islands. When coupled with microarrays, this technique has proven to be highly specific and very useful for the high-throughput analysis of genome-wide methylation in normal and cancer cells. Problems such as non-uniform probe performance, cross-reactivity, difficulties of normalization, and issues of relevant controls, however, prevent the full quantitative potential of MCA from being realized. We propose to develop and validate a high-resolution tool for DNA methylation profiling by coupling MCA with 'next generation' Solexa 1G sequencing technology (MCA-Seq). During the R21 phase of the project, we will apply various strategies to optimize MCA-Seq to improve coverage and minimize the quantity of initial DNA required. Additionally, we will build quality controls for MCA-Seq and develop optimized algorithms for data analysis. We will then validate our optimized MCA-Seq protocols, and evaluate the sensitivity, specificity, and quantitative accuracy using an innovative approach that simulates biological variation in methylation. Our proposed research will result in the development of a simple, robust, and reliable genome-wide assay for DNA methylation which will have broad utility in cancer research. Our long term goal is to utilize this technology to test biological hypotheses. Therefore, in an R33 phase of this project, we plan to fully implement this emerging technology by applying MCA-Seq in a set of well characterized tumor cell lines and primary cancer patient samples. These future studies will further validate the ability of MCA-Seq to accurately profile highly variable and aberrant cancer epigenomes, and generate preliminary biological data. The development and validation of MCA-Seq will enable major advances in our understanding of the basic biological mechanisms that contribute to cancer, and likely contribute to the design of future cancer therapies.
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资助金额:$30.46万
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依托单位:
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批准号:10460369
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资助金额:$35.09万
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负责人:Lanlan Shen
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依托单位:
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批准号:10676178
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项目类别:
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资助金额:$35.09万
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财政年份:2019
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负责人:Lanlan Shen
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依托单位:
Massively Parallel Sequencing Technology for Cancer Epigenome.
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批准号:8012969
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项目类别:
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资助金额:$6.01万
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财政年份:2009
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负责人:Lanlan Shen
-
依托单位:
Massively Parallel Sequencing Technology for Cancer Epigenome.
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批准号:7586347
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项目类别:
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资助金额:$10.93万
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财政年份:2009
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负责人:Lanlan Shen
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依托单位:
海外基金