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    Discovering cancer vulnerabilities using high-throughput micro-RNA screening

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    Author
    Nikolic, I; Elsworth, B; Dodson, E; Wu, SZ; Gould, CM; Mestdagh, P; Marshall, GM; Horvath, LG; Simpson, KJ; Swarbrick, A
    Date
    2017-12-15
    Source Title
    Nucleic Acids Research
    Publisher
    OXFORD UNIV PRESS
    University of Melbourne Author/s
    Simpson, Kaylene
    Affiliation
    Clinical Pathology
    Metadata
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    Document Type
    Journal Article
    Citations
    Nikolic, I., Elsworth, B., Dodson, E., Wu, S. Z., Gould, C. M., Mestdagh, P., Marshall, G. M., Horvath, L. G., Simpson, K. J. & Swarbrick, A. (2017). Discovering cancer vulnerabilities using high-throughput micro-RNA screening. NUCLEIC ACIDS RESEARCH, 45 (22), https://doi.org/10.1093/nar/gkx1072.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/255639
    DOI
    10.1093/nar/gkx1072
    Abstract
    Micro-RNAs (miRNAs) are potent regulators of gene expression and cellular phenotype. Each miRNA has the potential to target hundreds of transcripts within the cell thus controlling fundamental cellular processes such as survival and proliferation. Here, we exploit this important feature of miRNA networks to discover vulnerabilities in cancer phenotype, and map miRNA-target relationships across different cancer types. More specifically, we report the results of a functional genomics screen of 1280 miRNA mimics and inhibitors in eight cancer cell lines, and its presentation in a sophisticated interactive data portal. This resource represents the most comprehensive survey of miRNA function in oncology, incorporating breast cancer, prostate cancer and neuroblastoma. A user-friendly web portal couples this experimental data with multiple tools for miRNA target prediction, pathway enrichment analysis and visualization. In addition, the database integrates publicly available gene expression and perturbation data enabling tailored and context-specific analysis of miRNA function in a particular disease. As a proof-of-principle, we use the database and its innovative features to uncover novel determinants of the neuroblastoma malignant phenotype.

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