We propose to operate a Genome Characterization Center for The Cancer Genome Atlas (TCGA) of the National Cancer Institute. Our goal is to characterize the genomes and transcriptomes of 10,000 human cancers over 5 years, together with the collaborators of TCGA Research Network. Given the ongoing revolution in genome analysis, our Center will transition from current-generation microarray technologies to next-generation sequencing technologies for cancer genome characterization. We will accomplish this by benchmarking the next-generation technologies against state-of-the-art array technologies used in the pilot project of TCGA. Our Center is uniquely qualified for this effort, because of our expertise in next-generation sequencing as well as current-generation microarray production and technology development, our knowledge and demonstrated accomplishments in cancer genomics, and our commitment to and experience with multi-institutional collaborations including the pilot project of TCGA. Specifically, we intend to accomplish the following aims for TCGA:
Aim 1. Using microarray technologies: Characterize DNA and RNA from 2000 cancer samples and appropriate controls during year 1.
Aim 2. Using next-generation sequencing: (i) Perform direct comparison and validation of the three alternative platforms during year 1, by characterizing DNA from 300 cancer/normal sample pairs and RNA from 100 cancer samples. (ii) Select the most cost-effective sequencing platform at the end of year 1, based on the results and in conjunction with NCI staff. (iii) Implement this sequencing platform to characterize DNA and RNA from 2000 cancer samples and appropriate controls in Years 2-5. (iv) Continue to decrease cost and increase resolution of genomic analysis.
Cancer is a genomic disease, caused by somatic and germ-line alterations in DNA and RNA. By discovering and enumerating these alterations, we can improve the diagnosis and treatment of cancer: this is the goal of The Cancer Genome Atlas. Our proposed Genome Characterization Center could contribute significantly to TCGA by advancing genomic technology and by rapidly accomplishing cancer genome discoveries.
| 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 |
| 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 |
| Hmeljak, Julija; Sanchez-Vega, Francisco; Hoadley, Katherine A et al. (2018) Integrative Molecular Characterization of Malignant Pleural Mesothelioma. Cancer Discov 8:1548-1565 |
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