DNA methylation as a diagnostic marker in AML

描述（由申请人提供）：启动子中的异常DNA甲基化 在多种人类癌症中发现了一个基因区域， 与基因沉默有关。限制性标志基因组扫描（RLGS） 目前唯一的技术，允许扫描数千启动子， 人类癌症中异常DNA甲基化的序列。异常DNA 甲基化最近被证明是一个主要的贡献者和早期事件， 在肿瘤发生中，尤其是在急性髓性白血病（AML）的发展中。 在本申请中，我们提出研究DNA甲基化在以下方面的作用： AML，特别强调临床相关性。将使用的样本 将来自CALGB白血病组织库。我们的假设是 表观遗传变化（DNA甲基化）与遗传变化同样重要。 白血病发生的改变，但其程度被低估了。以来 甲基化变化可能会影响基因的转录， 这些表观遗传差异导致了 核型正常的AML。随后，可以使用异常甲基化的靶标 鉴定AML中新的诊断或预后生物标志物。为了验证这一 假设我们的具体目标是（1）研究亚组中的甲基化谱 核型正常的AML，原始细胞计数> 50%。(2)严格的统计 生物信息学分析将确定诊断和复发特异性 甲基化事件、预测甲基化事件的候选亚类和 最后，甲基化靶点与临床数据相关， 完全缓解。(3)一小部分高信息甲基化 将通过亚硫酸氢盐测序详细研究靶。MS-PCR检测将 开发了允许（4）筛选较大患者样本的方法。统计 将进行分析以确定甲基化事件的值，作为甲基化事件的一部分。 诊断生物标志物或作为具有预测价值的标志物。

DESCRIPTION (Provided by applicant): Aberrant DNA methylation in the promoter region of genes is found in a variety of human cancers and is thought to be associated with gene silencing. Restriction Landmark Genomic Scanning (RLGS) is currently the only technique that allows the scanning of thousands of promoter sequences for aberrant DNA methylation in human cancer. Aberrant DNA methylation was recently shown to be a major contributor and an early event in tumorigenesis, especially in the development of acute myeloid leukemia (AML). In this application we propose to investigate the role of DNA methylation in AML with special emphasis on clinical correlates. The samples that will be used for this study will come from the CALGB Leukemia Tissue Bank. Our hypothesis is that epigenetic changes (DNA methylation) are equally important as genetic alterations in leukemogenesis but have been underestimated in its extend. Since methylation changes could affect the transcription of genes it is likely that these epigenetic differences contribute to the molecular defects that underlie normal karyotype AML. Subsequently, aberrantly methylated targets can be used to identify novel diagnostic or prognostic biomarkers in AML. To test this hypothesis our specific aims are (1) to study methylation profiles in a subset of normal karyotype AML with blast counts >50 percent. (2) Rigorous statistical and bioinformatical analysis will identify diagnosis and relapse specific methylation events, candidate subclass predicting methylation events and finally methylation targets that correlate with clinical data such as duration of complete remission. (3) A small subset of highly informative methylation targets will be studied in detail by bisulfite sequencing. MS-PCR tests will be developed that allow (4) screening of larger patient samples. Statistical analysis will be performed to determine the value of a methylation event as a diagnostic biomarker or as a marker with predictive value.