Integrative Cancer Epigenomic Data Analysis Center (ICE-DAC)

项目总结/摘要 表观遗传异常在人类癌症中的广泛性已经越来越受到重视 在过去的十年中，随着癌症检测、癌症分类、化学抗性预测 和心理治疗大规模的癌症基因组筛查揭示了一种以前未被认识到的 人类癌症中表观遗传调节因子的体细胞突变，包括染色质重塑，以及 组蛋白或DNA甲基化读取器、写入器和擦除器。表观遗传改变可以作为驱动事件， 通过使肿瘤抑制基因失活来治疗癌症。这些沉默事件是相互排斥的， 同一基因的结构或突变失活增强了表观遗传的功能意义， 沉默散发性人类肿瘤中的大多数微卫星不稳定性病例可归因于 MLH 1错配修复基因的表观遗传沉默。显然，表观遗传机制在 人类癌症，癌症的全面分子表征应包括表观基因组谱。 2015年，我们成立了综合癌症表观基因组数据分析中心（ICE-DAC）， 作为基因组数据分析网络（GDAN）的一部分，我们拥有表观基因组数据分析方面的专业知识。我们 在过去的五年里，他们为GDAN做出了重大贡献，开发了尖端的DNA甲基化 生物信息学工具，PanCanAtlas、ATAC-Seq、Pan-Gastrointestinal（Pan-GI）的领先分析团队 癌症和肿瘤分子病理学（TMP），并作出重大贡献， 应答者（ER）研究，睾丸生殖细胞肿瘤（TGCT），数据协调（QC），CCG分类 信息标记（AIM）和许多其他项目。在这里，我们建议以一种 ICE-DAC的延续，将我们在表观基因组数据分析方面的深厚专业知识用于合作， NCI GDAN内临床标本的综合基因组和表观基因组分析。具体目标1、 我们将提供先进的专业分析散装和单细胞癌症表观基因组数据产生的 NCI癌症基因组学中心内的项目。我们已经开发了各种工具， 分析和实施自动化工作流程，为特设工作组提供及时的原始数据分析。在 具体目标2：我们将实施创新工具，从专门的数据类型中提取额外的信息。 该目标最大限度地提高了所生成数据的效用，并通过提供正交 验证。这些分析将包括对常见协变量（如性别、年龄和人种）的预测， 样本，肿瘤纯度和组成的分析，遗传信息（包括遗传信息）的推断， 突变、拷贝数和大的结构变体），所有这些都来自DNA甲基化测定。具体目标3 我们将整合表观基因组数据与其他基因组学，转录组学，蛋白质组学和临床数据， 生物学和临床相关的新见解。我们在专业表观基因组学方面的深厚专业知识将解决 GDAN所需的核心能力，并补充临床试验样本的其他基因组分析。

PROJECT SUMMARY / ABSTRACT The widespread nature of epigenetic abnormalities in human cancers has become increasingly appreciated in the past decade, with clinical impacts in cancer detection, cancer classification, chemoresistance prediction, and therapy. Large-scale cancer genomic screens have revealed a previously unrecognized prevalence of somatic mutations among epigenetic regulators in human cancers, including chromatin remodelers, as well as histone or DNA methylation readers, writers, and erasers. Epigenetic alterations can serve as driver events in cancer by inactivating tumor-suppressor genes. The finding that these silencing events are mutually exclusive with structural or mutational inactivation of the same gene reinforces the functional significance of epigenetic silencing. The majority of cases of microsatellite instability in sporadic human tumors can be attributed to epigenetic silencing of the MLH1 mismatch repair gene. Clearly, epigenetic mechanisms play a key role in human cancer, and a comprehensive molecular characterization of cancer should include epigenomic profiling. In 2015 we established an Integrative Cancer Epigenomic Data Analysis Center (ICE-DAC) to provide specialized expertise in epigenomic data analysis as part of the Genome Data Analysis Network (GDAN). We have made major contributions to the GDAN in the past five years, developing cutting-edge DNA methylation bioinformatics tools, leading analysis teams in PanCanAtlas, ATAC-Seq, Pan-Gastrointestinal (Pan-GI) Cancers and Tumor Molecular Pathology (TMP), and making major contributions to the Exceptional Responders (ER) study, testicular germcell tumors (TGCT), data harmonization (QC), CCG Ancestry Informative Markers (AIM), and many other projects. Here we propose to sustain this productive activity in a continuation of the ICE-DAC, lending our deep expertise in epigenomic data analysis to collaborative, integrative genomic and epigenomic analyses of clinical specimens within the NCI GDAN. In Specific Aim 1, we will provide advanced specialized analysis of bulk and single-cell cancer epigenomic data generated by programs within the NCI Center for Cancer Genomics. We have developed various tools for epigenetic analysis and implemented an automated workflow to provide timely primary data analysis for AWGs. In Specific Aim 2 we will implement innovative tools to extract additional information from specialized data types. This Aim maximizes the utility of the data generated, and adds to the rigor of analysis by providing orthogonal validation. These analyses will include prediction of common covariates (such as sex, age and race) for the samples, analysis of tumor purity and composition, inferences of genetic information (including genetic mutation, copy number and large structural variants), all from the DNA methylation assays. In Specific Aim 3 we will integrate epigenomic data with other genomic, transcriptomic, proteomic, and clinical data to derive biologically and clinically relevant novel insights. Our deep expertise in specialized epigenomics will address a core competency required in GDAN, and complement other genomic analyses of clinical trial samples.