Our objective is to establish and operate a high throughput Genome Characterization Centre (GCC) that specializes in sequencing libraries, prepared from mRNAs and microRNAs purified from cancer cells and tissues. To achieve our objective, we will build upon existing """"""""next generation"""""""" sequencing and analysis strengths at the BC Genome Sciences Centre. We have accumulated world-leading experience in the operation of lllumina sequencers as a consequence of becoming one of the four Early Access Partners originally engaged by Solexa (now lllumina) in November of 2006. Since then, we have led in the development and implementation of protocols for preparing and sequencing numerous library types on the lllumina GA platform, including both microRNA and mRNA libraries. To build sequencing libraries, we have established an lllumina library construction core that has constructed 1,075 libraries, from which we have generated more than 934 billion base-pairs of high quality sequence information. These data have so far provided the basis for 19 publications describing results obtained from sequencing genomes and transcriptomes, and describing the creation of new software tools and algorithms to manage and analyze the wealth of data such instruments produce. To develop and critically appraise instrument upgrades, new instruments and new protocols, we have established a next generation technology development core. Technologies developed and appraised by this group are approved for use by our lllumina production sequencing core. Under-pinning this enterprise is a formal system for quality assurance and quality control that encompasses laboratory and bioinformatics activities, and a laboratory information management system that regulates and monitors laboratory activity, inventory, and features real time error avoidance. Our experience in assembling these teams and this infrastructure will serve as a basis for scaling up our library production capacity to meet our objectives, which are to sequence 4,400 transcriptome libraries in the first year of our operation. Using bioinformatics tools already in production, we will analyze these sequences to profile the expression of genes, individual exons and microRNAs, and analyze the sequences to discover mutations and RNA editing events in expressed sequences. These analyses will provide an unprecedented view of transcription in cancer cells;identify promising new mutated and expressed therapeutic targets, and identify genes and pathways that are drivers of oncogenesis.

Public Health Relevance

Mutations and other perturbations in genes can cause cancer, or affect the way patients respond to cancer treatments. We aim to develop a deep understanding of the cancer genes that are mutated or inappropriately turned on, or off, in cancer cells. We will do this using a powerful new DNA analysis tool called next generation sequencing, to analyze thousands of genes from thousands of cancer samples.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Resource-Related Research Projects--Cooperative Agreements (U24)
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Special Emphasis Panel (ZCA1-SRLB-U (O1))
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Tarnuzzer, Roy W
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British Columbia Cancer Agency
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V5 1-L3
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, V├ęsteinn; 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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