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      Integrative genomic analyses reveal clinically relevant long non-coding RNA in human cancer

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          Abstract

          Despite growing appreciations of the importance of long non-coding RNA (lncRNA) in normal physiology and disease, our knowledge of cancer-related lncRNA remains limited. By repurposing microarray probes, we constructed the expression profile of 10,207 lncRNA genes in approximately 1,300 tumors over four different cancer types. Through integrative analysis of the lncRNA expression profiles with clinical outcome and somatic copy number alteration (SCNA), we identified lncRNA that are associated with cancer subtypes and clinical prognosis, and predicted those that are potential drivers of cancer progression. We validated our predictions by experimentally confirming prostate cancer cell growth dependence on two novel lncRNA. Our analysis provided a resource of clinically relevant lncRNA for development of lncRNA biomarkers and identification of lncRNA therapeutic targets. It also demonstrated the power of integrating publically available genomic datasets and clinical information for discovering disease associated lncRNA.

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          Ab initio reconstruction of transcriptomes of pluripotent and lineage committed cells reveals gene structures of thousands of lincRNAs

          Mitchell Guttman, Manuel Garber, Joshua Levin … (2010)
          RNA-Seq provides an unbiased way to study a transcriptome, including both coding and non-coding genes. To date, most RNA-Seq studies have critically depended on existing annotations, and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We apply it to mouse embryonic stem cells, neuronal precursor cells, and lung fibroblasts to accurately reconstruct the full-length gene structures for the vast majority of known expressed genes. We identify substantial variation in protein-coding genes, including thousands of novel 5′-start sites, 3′-ends, and internal coding exons. We then determine the gene structures of over a thousand lincRNA and antisense loci. Our results open the way to direct experimental manipulation of thousands of non-coding RNAs, and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.
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            Ensembl 2012

            Paul Flicek, M. Amode, Daniel Barrell … (2011)
            The Ensembl project (http://www.ensembl.org) provides genome resources for chordate genomes with a particular focus on human genome data as well as data for key model organisms such as mouse, rat and zebrafish. Five additional species were added in the last year including gibbon (Nomascus leucogenys) and Tasmanian devil (Sarcophilus harrisii) bringing the total number of supported species to 61 as of Ensembl release 64 (September 2011). Of these, 55 species appear on the main Ensembl website and six species are provided on the Ensembl preview site (Pre!Ensembl; http://pre.ensembl.org) with preliminary support. The past year has also seen improvements across the project.
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              Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma.

              Levi A Garraway, Hans R. Widlund, Mark Rubin … (2005)
              Systematic analyses of cancer genomes promise to unveil patterns of genetic alterations linked to the genesis and spread of human cancers. High-density single-nucleotide polymorphism (SNP) arrays enable detailed and genome-wide identification of both loss-of-heterozygosity events and copy-number alterations in cancer. Here, by integrating SNP array-based genetic maps with gene expression signatures derived from NCI60 cell lines, we identified the melanocyte master regulator MITF (microphthalmia-associated transcription factor) as the target of a novel melanoma amplification. We found that MITF amplification was more prevalent in metastatic disease and correlated with decreased overall patient survival. BRAF mutation and p16 inactivation accompanied MITF amplification in melanoma cell lines. Ectopic MITF expression in conjunction with the BRAF(V600E) mutant transformed primary human melanocytes, and thus MITF can function as a melanoma oncogene. Reduction of MITF activity sensitizes melanoma cells to chemotherapeutic agents. Targeting MITF in combination with BRAF or cyclin-dependent kinase inhibitors may offer a rational therapeutic avenue into melanoma, a highly chemotherapy-resistant neoplasm. Together, these data suggest that MITF represents a distinct class of 'lineage survival' or 'lineage addiction' oncogenes required for both tissue-specific cancer development and tumour progression.
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                Author and article information

                Journal
                Journal ID (nlm-journal-id): 101186374
                Journal ID (pubmed-jr-id): 31761
                Journal ID (nlm-ta): Nat Struct Mol Biol
                Journal ID (iso-abbrev): Nat. Struct. Mol. Biol.
                Title: Nature structural & molecular biology
                ISSN (Print): 1545-9993
                ISSN (Electronic): 1545-9985
                Publication date Nihms-submitted: 14 May 2013
                Publication date (Electronic): 02 June 2013
                Publication date (Print): July 2013
                Publication date PMC-release: 01 January 2014
                Volume: 20
                Issue: 7
                Pages: 908-913
                Affiliations
                [1 ]Department of Bioinformatics, School of Life Sciences and Technology, Tongji University, Shanghai, China
                [2 ]Center for Functional Cancer Epigeneitcs, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
                [3 ]Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
                [4 ]Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
                [5 ]Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts, USA
                [6 ]Department of Bioinformatics and Computational Biology, Division of Quantitative Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
                [7 ]College of Biological Sciences, China Agriculture University, Beijing, China
                Author notes
                [* ]To whom correspondence should be addressed: X. Shirley Liu ( xsliu@ 123456jimmy.harvard.edu ) or Yiwen Chen ( ywchen@ 123456jimmy.harvard.edu ) or Myles Brown ( myles_brown@ 123456dfci.harvard.edu )
                [#]

                These authors contributed equally

                Article
                Manuscript ID: NIHMS469463
                DOI: 10.1038/nsmb.2591
                PMC ID: 3702647
                PubMed ID: 23728290
                SO-VID: b9e97d19-7c03-46c7-8fa9-60a802cb6907
                License:

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Funding
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: R01 GM099409 || GM
                Categories
                Subject: Article

                ScienceOpen disciplines: Molecular biology
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                ScienceOpen disciplines: Molecular biology

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