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.
| 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 |
| Shen, Hui; Shih, Juliann; Hollern, Daniel P et al. (2018) Integrated Molecular Characterization of Testicular Germ Cell Tumors. Cell Rep 23:3392-3406 |
| Berger, Ashton C; Korkut, Anil; Kanchi, Rupa S et al. (2018) A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers. Cancer Cell 33:690-705.e9 |
| Zhou, Wanding; Dinh, Huy Q; Ramjan, Zachary et al. (2018) DNA methylation loss in late-replicating domains is linked to mitotic cell division. Nat Genet 50:591-602 |
| Hoadley, Katherine A; Yau, Christina; Hinoue, Toshinori et al. (2018) Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer. Cell 173:291-304.e6 |
| Schaub, Franz X; Dhankani, Varsha; Berger, Ashton C et al. (2018) Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas. Cell Syst 6:282-300.e2 |
| Liu, Jianfang; Lichtenberg, Tara; Hoadley, Katherine A et al. (2018) An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell 173:400-416.e11 |
| Bailey, Matthew H; Tokheim, Collin; Porta-Pardo, Eduard et al. (2018) Comprehensive Characterization of Cancer Driver Genes and Mutations. Cell 173:371-385.e18 |
Showing the most recent 10 out of 77 publications
