Integrative Cancer Epigenomic Data Analysis Center (ICE-DAC)

综合癌症表观基因组数据分析中心（ICE-DAC）

基本信息

批准号：
10684894
负责人：
PETER W LAIRD
金额：
$ 44.69万
依托单位：
VAN ANDEL RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10684894
关键词：
ATAC-seq Age Attention Base Sequence Binding Sites Biological Assay Cancer Biology Cancer Center Cancer Detection Cancer Model Categories Cells ChIP-seq Chemoresistance Chromatin Clinical Clinical Data Clinical Trials Cluster Analysis Code Competence Complement Custom Cytosine DNA DNA Integration DNA Methylation DNA Modification Process DNA Sequence Alteration Data Data Analyses Defect Development Enhancers Epigenetic Process Event Evolution Formalin Functional disorder Gastrointestinal Neoplasms Genes Genome Genome Data Analysis Network Genomics Growth Higher Order Chromatin Structure Human Hypermethylation MLH1 gene Malignant Neoplasms Malignant neoplasm of gastrointestinal tract Methylation Microsatellite Instability Mismatch Repair Mitosis Molecular Mutation Nature Oncogene Activation Outcome Paraffin Embedding Pathway Analysis Play Prevalence Productivity Proteins Proteomics Quality Control Race Reader Recurrent Malignant Neoplasm Role Sampling Somatic Mutation Specimen Tumor Suppressor Genes Validation Variant bioinformatics tool bisulfite bisulfite sequencing cancer cell cancer classification cancer genome cancer genomics cancer recurrence cancer subtypes chromatin remodeling clinical trial analysis clinically relevant data harmonization determinants of treatment resistance driver mutation epigenetic silencing epigenomic profiling epigenomics exceptional responders gene repair genetic information histone methylation histone modification innovation insight interest molecular pathology mouse model multiple data types novel programs promoter sample fixation sex temporal measurement tool transcription factor transcriptome sequencing transcriptomics tumor

项目摘要

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.

项目摘要 /摘要人类癌症表观遗传异常的广泛性质已越来越受到赞赏在过去的十年中，在癌症检测，癌症分类，化学抗性预测中产生临床影响，和治疗。大规模的癌症基因组筛查表明先前未认识到的患病率人类癌症（包括染色质重塑剂）的表观遗传调节剂之间的体细胞突变以及组蛋白或DNA甲基化读取器，作家和橡皮擦。表观遗传改变可以作为驾驶员事件通过失活肿瘤抑制基因来癌症。这些沉默事件是相互排斥的发现同一基因的结构或突变失活加强了表观遗传学的功能意义沉默。偶发人类肿瘤中的大多数微卫星不稳定性病例可以归因于 MLH1不匹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以及癌症的全面分子表征应包括表观基因组分析。 2015年，我们建立了一个综合性癌症基因因组数据分析中心（ICE-DAC）表观基因组数据分析方面的专业知识是基因组数据分析网络（GDAN）的一部分。我们在过去的五年中，已经为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），并为特殊的贡献做出了重大贡献响应者（ER）研究，睾丸发射肿瘤（TGCT），数据协调（QC），CCG血统内容丰富的标记（AIM）和许多其他项目。在这里，我们建议在继续进行ICE-DAC，将我们在表观基因组数据分析方面的深厚专业知识借给协作， NCI GDAN内临床标本的综合基因组和表观基因组分析。在特定的目标1中，我们将对由大量和单细胞癌表观基因组数据产生的高级专业分析 NCI癌症基因组学中心内的计划。我们已经开发了各种表观遗传学的工具分析并实施自动化工作流程，以提供及时的AWG主要数据分析。在具体目标2我们将实施创新工具，以从专业数据类型中提取其他信息。这个目的最大化生成的数据的实用性，并通过提供正交增加了分析的严格性验证。这些分析将包括对共同协变量（例如性别，年龄和种族）的预测样品，肿瘤纯度和组成分析，遗传信息的推断（包括遗传突变，拷贝数和较大的结构变体），全部来自DNA甲基化测定法。在特定目标3中我们将将表观基因组数据与其他基因组，转录组，蛋白质组学和临床数据整合在一起，以得出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需要核心能力，并补充了临床试验样本的其他基因组分析。