Orozco Javier Ij, Manughian-Peter Ayla O, Salomon Matthew P, Marzese Diego M
Cancer Epigenetics Laboratory, John Wayne Cancer Institute at Providence Saint John's Health Center, Santa Monica, CA, USA.
Computational Biology Laboratory, John Wayne Cancer Institute at Providence Saint John's Health Center, Santa Monica, CA, USA.
Epigenet Insights. 2019 Mar 31;12:2516865719840284. doi: 10.1177/2516865719840284. eCollection 2019.
DNA methylation profiling has proven to be a powerful analytical tool, which can accurately identify the tissue of origin of a wide range of benign and malignant neoplasms. Using microarray-based profiling and supervised machine learning algorithms, we and other groups have recently unraveled DNA methylation signatures capable of aiding the histomolecular diagnosis of different tumor types. We have explored the methylomes of metastatic brain tumors from patients with lung cancer, breast cancer, and cutaneous melanoma and primary brain neoplasms to build epigenetic classifiers. Our brain metastasis methylation (BrainMETH) classifier has the ability to determine the type of brain tumor, the origin of the metastases, and the clinical-therapeutic subtype for patients with breast cancer brain metastases. To facilitate the translation of these epigenetic classifiers into clinical practice, we selected and validated the most informative genomic regions utilizing quantitative methylation-specific polymerase chain reaction (qMSP). We believe that the refinement, expansion, integration, and clinical validation of BrainMETH and other recently developed epigenetic classifiers will significantly contribute to the development of more comprehensive and accurate systems for the personalized management of patients with brain metastases.
DNA甲基化谱分析已被证明是一种强大的分析工具,它可以准确识别多种良性和恶性肿瘤的组织起源。利用基于微阵列的谱分析和监督机器学习算法,我们和其他团队最近揭示了能够辅助不同肿瘤类型组织分子诊断的DNA甲基化特征。我们研究了肺癌、乳腺癌和皮肤黑色素瘤患者的转移性脑肿瘤以及原发性脑肿瘤的甲基化组,以构建表观遗传分类器。我们的脑转移甲基化(BrainMETH)分类器能够确定脑肿瘤的类型、转移灶的起源以及乳腺癌脑转移患者的临床治疗亚型。为了促进这些表观遗传分类器转化为临床实践,我们利用定量甲基化特异性聚合酶链反应(qMSP)选择并验证了最具信息性的基因组区域。我们相信,BrainMETH和其他最近开发的表观遗传分类器的完善、扩展、整合和临床验证将显著有助于开发更全面、准确的系统,用于脑转移患者的个性化管理。