Quantitative high-throughput analysis of DNA methylation patterns by base-specific cleavage and mass spectrometry
Quantitative high-throughput analysis of DNA methylation patterns by base-specific cleavage and mass spectrometry
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DOI：
10.1073/pnas.0507816102
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发表时间：
2005-11-01
影响因子：
11.1
通讯作者：
van den Boom, D
中科院分区：
文献类型：
--
作者：
Ehrich, M;Nelson, MR;van den Boom, D
甲基化是对我们理解致癌作用至关重要的主要表观遗传过程之一。现在人们普遍认为 DNA 甲基化、染色质结构和人类恶性肿瘤之间存在关联。 DNA 甲基化可能是癌症分子诊断中的重要临床标志物。了解生物学背景下的表观遗传修饰涉及 DNA 甲基化分析的几个方面。这些方面包括差异甲基化基因的从头发现、甲基化模式的分析以及甲基化程度差异的确定。在这里，我们提出了一种以前未表征的高通量 DNA 甲基化分析方法，该方法利用 MALDI-TOF 质谱 (MS) 分析碱基特异性切割的扩增产物。我们使用 IGF2/H19 区域来证明单个碱基特异性切割反应足以发现甲基化位点并确定选定目标区域内的甲基化比率。裂解反应的组合能够完整评估 DNA 甲基化的所有相关方面，大多数 CpG 在多个反应中表现出来。我们成功地在高通量条件下应用该技术，定量评估了48名患者的正常和肿瘤性肺癌组织样本中47个基因的甲基化差异，并证明定量甲基化结果可以根据样本的组织病理学对样本进行准确分类。
Methylation is one of the major epigenetic processes pivotal to our understanding of carcinogenesis. It is now widely accepted that there is a relationship between DNA methylation, chromatin structure, and human malignancies. DNA methylation is potentially an important clinical marker in cancer molecular diagnostics. Understanding epigenetic modifications in their biological context involves several aspects of DNA methylation analysis. These aspects include the de novo discovery of differentially methylated genes, the analysis of methylation patterns, and the determination of differences in the degree of methylation. Here we present a previously uncharacterized method for high-throughput DNA methylation analysis that utilizes MALDI-TOF mass spectrometry (MS) analysis of base-specifically cleaved amplification products. We use the IGF2/H19 region to show that a single base-specific cleavage reaction is sufficient to discover methylation sites and to determine methylation ratios within a selected target region. A combination of cleavage reactions enables the complete evaluation of all relevant aspects of DNA methylation, with most CpGs represented in multiple reactions. We successfully applied this technology under high-throughput conditions to quantitatively assess methylation differences between normal and neoplastic lung cancer tissue samples from 48 patients in 47 genes and demonstrate that the quantitative methylation results allow accurate classification of samples according to their histopathology.