Integrative Cancer Epigenomic Data Analysis Center (ICE-DAC) - 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.
