Wertheim Gerald B W, Luskin Marlise R, Carroll Martin, Master Stephen R
Department of Pathology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, 5140 Floor Main Building, 324 S. 34th St., Philadelphia, PA, 19104, USA.
Methods Mol Biol. 2017;1633:125-136. doi: 10.1007/978-1-4939-7142-8_8.
Epigenetic dysregulation, including aberrant methylation of cytosine residues in DNA, is a hallmark of cancer and clearly results in oncogenic cellular alterations such as transcriptional attenuation of tumor suppressors and genomic instability. A number of studies have examined DNA methylation alterations in patients with acute myeloid leukemia (AML) and have shown that analysis of multilocus methylation patterns can identify biologically distinct AML subclasses and can predict patient prognosis. In order to utilize the prognostic capability of methylation analysis in a clinical setting, we have developed a microsphere-based HpaII tiny fragment enrichment by ligation-mediated PCR (xMELP) assay to interrogate the methylation state of genomic multiple loci along with a random forest-based classification algorithm that correlates DNA methylation status with patient prognosis. These tools can be easily implemented in a clinical molecular pathology laboratory and can be utilized for more accurate risk stratification of AML patients.
表观遗传失调，包括DNA中胞嘧啶残基的异常甲基化，是癌症的一个标志，并且明显导致致癌性细胞改变，如肿瘤抑制因子的转录衰减和基因组不稳定。许多研究已经检测了急性髓系白血病（AML）患者的DNA甲基化改变，并表明多位点甲基化模式分析可以识别生物学上不同的AML亚类，并能预测患者的预后。为了在临床环境中利用甲基化分析的预后能力，我们开发了一种基于微球的连接介导PCR的HpaII小片段富集（xMELP）检测方法，以询问基因组多个位点的甲基化状态，同时开发了一种基于随机森林的分类算法，将DNA甲基化状态与患者预后相关联。这些工具可以很容易地在临床分子病理实验室中实施，并可用于更准确地对AML患者进行风险分层。
