Gene expression provides a snapshot of the cellular changes that promote tumor malignancy. Quantitative gene expression analysis, especially as implemented by DNA microarrays, has proven to be an extremely valuable tool for cancer genome characterization, and has lead to the development of new genomic-based clinical tests. Our own experience with DNA microarrays to study gene expression patterns for breast, head &neck, and lung cancers has lead to the identification of novel subtypes of tumors with distinct patient outcomes and has identified new tumor suppressor genes. In the pilot phase of The Cancer Genome Atlas (TCGA) project, multiple platforms were used including tools to study gene expression (our role), tumor genomic DNA copy number alterations, SNP genotypes, DNA methylation and gene mutational analyses. Our collaborative efforts identified new tumor subtypes of glioblastoma and painted an integrated picture linking mutations to copy number changes to expression patterns, which identified biologically distinct subtypes of disease with differences in patient outcomes. For the second phase of TCGA project, we propose to continue to perform quantitative gene expression profiling of all protein-coding genes, non-protein coding mRNAs(ncRNAs) and microRNAs, on -2000 tumors per year. This approach has proven to be one of the most informative and comprehensive cancer genome characterization tools available. In addition, we propose to generate global chromatin organization profiles of cancer to identify regions of """"""""open"""""""" chromatin domains (nucleosome-depleted regions). We will use FAIRE (Formaldehyde-Assisted isolation of Regulatory Elements), a simple, low-cost method amenable to use on small quantities of solid tissue, coupled to next-generation DNA sequencing. Since the function of most histone modifications and chromatin remodeling activities is to regulate nucleosome occupancy, FAIRE effectively summarizes the functional output of such epigenetic mechanisms in a single robust assay. Lastly, we propose to perform integrated analyses of transcript levels with chromatin stoicture to map important regulatory elements, which can be distant to the transcript(s) that they regulate. Our study of genome-wide transcript regulation with chromatin organization will provide a critical portrait of the cancer genome that can be integrated with (and indeed can sometimes generate) other important data, including mutations and copy number events.
Cancer is a disease caused by changes in many different genes, and these genes can be altered (or mutated) in many different ways. One way in which alterations can cause cancer is to turn particular genes on, or turn others off. We propose to comprehensively study all human genes and determine their expression levels in cancer and normal tissues, and thus, identify those genes that are inappropriately on or off in the tumors. In addition, we will also study important structural characteristics of person's tumor DNA, and combine these data with our expression measurement in order to provide an improved mechanistic understanding of why certain cancer causing genes are inappropriately expressed.
| Walter, Vonn; Du, Ying; Danilova, Ludmila et al. (2018) MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors. Cancer Res 78:3375-3385 |
| Way, Gregory P; Sanchez-Vega, Francisco; La, Konnor et al. (2018) Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas. Cell Rep 23:172-180.e3 |
| Ricketts, Christopher J; De Cubas, Aguirre A; Fan, Huihui et al. (2018) The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma. Cell Rep 23:313-326.e5 |
| Knijnenburg, Theo A; Wang, Linghua; Zimmermann, Michael T et al. (2018) Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas. Cell Rep 23:239-254.e6 |
| Peng, Xinxin; Chen, Zhongyuan; Farshidfar, Farshad et al. (2018) Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers. Cell Rep 23:255-269.e4 |
| Huang, Kuan-Lin; Mashl, R Jay; Wu, Yige et al. (2018) Pathogenic Germline Variants in 10,389 Adult Cancers. Cell 173:355-370.e14 |
| 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 |
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