In the past two decades, it has become clear that cancer arises not only as a consequence of genetic events, such as mutations, copy number alterations, and sequence rearrangements, but also as a result of extensive changes to the epigenome. Epigenetic alterations contribute causally to the origin and malignant progression of cancer, and affect clinical outcome. The USC-JHU Cancer Epigenome Characterization Center specializes in the production and analysis of genome-scale cancer epigenetic data. During the pilot phase of The Cancer Genome Atlas, our center has been responsible for the production and deposition of all high-throughput epigenomic data within TCGA. A key outcome of the TCGA pilot was our finding of a link in glioblastoma multiforme between MGMT promoter methylation, treatment with alkylating agents, and a hypermutator phenotype associated with mismatch repair deficiency, an observation with potential clinical implications. For the next phase of TCGA, we propose the following three objectives. Objective 1 is to characterize the DNA methylation status of 27,578 CpG dinucleotides located in 14,495 gene promoters in at least 10,000 human cancer samples and 1,000 control samples using the lllumina Infinium DNA Methylation analysis platform. Objective 2 is to transition epigenomic data production in TCGA to whole genome shotgun bisulfite sequence analysis to provide single-base-pair resolution DNA methylation data for TCGA cancer samples. Objective 3 is to implement quality control and quality assurance measures to ensure that epigenomic data deposited for public dissemination meets rigorous standards. Our group has considerable expertise in cancer epigenomics, with two founders of the field of cancer epigenetics and with members who collectively have pioneered the majority of widely used DNA methylation analysis techniques, and who have provided many of the biological insights. Epigenomic data are a necessary component for a full understanding of the relationship between alterations in the cancer genome and the origin and clinical diversity of individual tumors.
Ding, Li; Bailey, Matthew H; Porta-Pardo, Eduard et al. (2018) Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics. Cell 173:305-320.e10 |
Seiler, Michael; Peng, Shouyong; Agrawal, Anant A et al. (2018) Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types. Cell Rep 23:282-296.e4 |
Liu, Yang; Sethi, Nilay S; Hinoue, Toshinori et al. (2018) Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas. Cancer Cell 33:721-735.e8 |
Jayasinghe, Reyka G; Cao, Song; Gao, Qingsong et al. (2018) Systematic Analysis of Splice-Site-Creating Mutations in Cancer. Cell Rep 23:270-281.e3 |
Saltz, Joel; Gupta, Rajarsi; Hou, Le et al. (2018) Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images. Cell Rep 23:181-193.e7 |
Ellrott, Kyle; Bailey, Matthew H; Saksena, Gordon et al. (2018) Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines. Cell Syst 6:271-281.e7 |
Campbell, Joshua D; Yau, Christina; Bowlby, Reanne et al. (2018) Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas. Cell Rep 23:194-212.e6 |
Gao, Qingsong; Liang, Wen-Wei; Foltz, Steven M et al. (2018) Driver Fusions and Their Implications in the Development and Treatment of Human Cancers. Cell Rep 23:227-238.e3 |
Thorsson, Vésteinn; Gibbs, David L; Brown, Scott D et al. (2018) The Immune Landscape of Cancer. Immunity 48:812-830.e14 |
Radovich, Milan; Pickering, Curtis R; Felau, Ina et al. (2018) The Integrated Genomic Landscape of Thymic Epithelial Tumors. Cancer Cell 33:244-258.e10 |
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