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 该基因区域存在于多种人类癌症中，并且被认为是 与基因沉默有关。限制性地标基因组扫描 (RLGS) 是 目前唯一可以扫描数千个启动子的技术 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贡献者和早期事件 肿瘤发生，特别是急性髓系白血病（AML）的发展。 在此应用中，我们建议研究 DNA 甲基化在 AML 特别强调临床相关性。将使用的样本 本研究将来自 CALGB 白血病组织库。我们的假设是 表观遗传变化（DNA 甲基化）与遗传变化同等重要 白血病发生的改变，但其程度被低估了。自从 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潜在的分子缺陷 正常核型 AML。随后，可以使用异常甲基化的靶标 识别 AML 的新诊断或预后生物标志物。为了测试这个 假设我们的具体目标是（1）研究子集中的甲基化谱 原始细胞计数 >50% 的正常核型 AML。 （二）严格统计 生物信息分析将确定诊断和复发的具体情况 甲基化事件、预测甲基化事件的候选子类和 最后是与临床数据（例如持续时间）相关的甲基化目标 完全缓解。 (3) 高信息甲基化的一小部分 将通过亚硫酸氢盐测序对目标进行详细研究。 MS-PCR 检测将 开发允许（4）筛选更大的患者样本。统计 将进行分析以确定甲基化事件的价值 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.