Division of Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heid elberg, Germany.
Genome Med. 2014 Aug 30;6(8):66. doi: 10.1186/s13073-014-0066-6. eCollection 2014.
The comparison of DNA methylation patterns across cancer types (pan-cancer methylome analyses) has revealed distinct subgroups of tumors that share similar methylation patterns. Integration of these data with the wealth of information derived from cancer genome profiling studies performed by large international consortia has provided novel insights into the cellular aberrations that contribute to cancer development. There is evidence that genetic mutations in epigenetic regulators (such as DNMT3, IDH1/2 or H3.3) mediate or contribute to these patterns, although a unifying molecular mechanism underlying the global alterations of DNA methylation has largely been elusive. Knowledge gained from pan-cancer methylome analyses will aid the development of diagnostic and prognostic biomarkers, improve patient stratification and the discovery of novel druggable targets for therapy, and will generate hypotheses for innovative clinical trial designs based on methylation subgroups rather than on cancer subtypes. In this review, we discuss recent advances in the global profiling of tumor genomes for aberrant DNA methylation and the integration of these data with cancer genome profiling data, highlight potential mechanisms leading to different methylation subgroups, and show how this information can be used in basic research and for translational applications. A remaining challenge is to experimentally prove the functional link between observed pan-cancer methylation patterns, the associated genetic aberrations, and their relevance for the development of cancer.
对跨癌症类型的 DNA 甲基化模式(泛癌症甲基化组分析)进行比较,揭示了具有相似甲基化模式的肿瘤亚群。将这些数据与大型国际联盟进行的癌症基因组分析研究中得出的大量信息进行整合,为导致癌症发展的细胞异常提供了新的见解。有证据表明,表观遗传调节剂(如 DNMT3、IDH1/2 或 H3.3)中的遗传突变介导或促成了这些模式,尽管导致 DNA 甲基化全局改变的统一分子机制在很大程度上仍难以捉摸。从泛癌症甲基化组分析中获得的知识将有助于开发诊断和预后生物标志物,改善患者分层和发现新的治疗靶点,并基于甲基化亚群而不是癌症亚型为创新临床试验设计生成假设。在这篇综述中,我们讨论了肿瘤基因组中异常 DNA 甲基化的全局分析的最新进展,以及这些数据与癌症基因组分析数据的整合,强调了导致不同甲基化亚群的潜在机制,并展示了如何将这些信息用于基础研究和转化应用。一个遗留的挑战是通过实验证明观察到的泛癌症甲基化模式、相关的遗传异常及其与癌症发展的相关性之间的功能联系。