Medical Biology - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 4 of 4
  • Item
    No Preview Available
    TERT structural rearrangements in metastatic pheochromocytomas
    Dwight, T ; Flynn, A ; Amarasinghe, K ; Benn, DE ; Lupat, R ; Li, J ; Cameron, DL ; Hogg, A ; Balachander, S ; Candiloro, ILM ; Wong, SQ ; Robinson, BG ; Papenfuss, AT ; Gill, AJ ; Dobrovic, A ; Hicks, RJ ; Clifton-Bligh, RJ ; Tothill, RW (BIOSCIENTIFICA LTD, 2018-01)
    Pheochromocytomas (PC) and paragangliomas (PGL) are endocrine tumors for which the genetic and clinicopathological features of metastatic progression remain incompletely understood. As a result, the risk of metastasis from a primary tumor cannot be predicted. Early diagnosis of individuals at high risk of developing metastases is clinically important and the identification of new biomarkers that are predictive of metastatic potential is of high value. Activation of TERT has been associated with a number of malignant tumors, including PC/PGL. However, the mechanism of TERT activation in the majority of PC/PGL remains unclear. As TERT promoter mutations occur rarely in PC/PGL, we hypothesized that other mechanisms - such as structural variations - may underlie TERT activation in these tumors. From 35 PC and four PGL, we identified three primary PCs that developed metastases with elevated TERT expression, each of which lacked TERT promoter mutations and promoter DNA methylation. Using whole genome sequencing, we identified somatic structural alterations proximal to the TERT locus in two of these tumors. In both tumors, the genomic rearrangements led to the positioning of super-enhancers proximal to the TERT promoter, that are likely responsible for the activation of the normally tightly repressed TERT expression in chromaffin cells.
  • Item
    Thumbnail Image
    Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads
    Schroeder, J ; Hsu, A ; Boyle, SE ; Macintyre, G ; Cmero, M ; Tothill, RW ; Johnstone, RW ; Shackleton, M ; Papenfuss, AT (OXFORD UNIV PRESS, 2014-04-15)
    MOTIVATION: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates. RESULTS: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools. AVAILABILITY AND IMPLEMENTATION: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates CONTACT: papenfuss@wehi.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
  • Item
    Thumbnail Image
    Genomic characterisation of Eμ-Myc mouse lymphomas identifies Bcor as a Myc co-operative tumour-suppressor gene
    Lefebure, M ; Tothill, RW ; Kruse, E ; Hawkins, ED ; Shortt, J ; Matthews, GM ; Gregory, GP ; Martin, BP ; Kelly, MJ ; Todorovski, I ; Doyle, MA ; Lupat, R ; Li, J ; Schroeder, J ; Wall, M ; Craig, S ; Poortinga, G ; Cameron, D ; Bywater, M ; Kats, L ; Gearhart, MD ; Bardwell, VJ ; Dickins, RA ; Hannan, RD ; Papenfuss, AT ; Johnstone, RW (NATURE PUBLISHING GROUP, 2017-03-06)
    The Eμ-Myc mouse is an extensively used model of MYC driven malignancy; however to date there has only been partial characterization of MYC co-operative mutations leading to spontaneous lymphomagenesis. Here we sequence spontaneously arising Eμ-Myc lymphomas to define transgene architecture, somatic mutations, and structural alterations. We identify frequent disruptive mutations in the PRC1-like component and BCL6-corepressor gene Bcor. Moreover, we find unexpected concomitant multigenic lesions involving Cdkn2a loss and other cancer genes including Nras, Kras and Bcor. These findings challenge the assumed two-hit model of Eμ-Myc lymphoma and demonstrate a functional in vivo role for Bcor in suppressing tumorigenesis.
  • Item
    Thumbnail Image
    Bioinformatics Pipelines for Targeted Resequencing and Whole-Exome Sequencing of Human and Mouse Genomes: A Virtual Appliance Approach for Instant Deployment
    Li, J ; Doyle, MA ; Saeed, I ; Wong, SQ ; Mar, V ; Goode, DL ; Caramia, F ; Doig, K ; Ryland, GL ; Thompson, ER ; Hunter, SM ; Halgamuge, SK ; Ellul, J ; Dobrovic, A ; Campbell, IG ; Papenfuss, AT ; McArthur, GA ; Tothill, RW ; Calogero, RA (PUBLIC LIBRARY SCIENCE, 2014-04-21)
    Targeted resequencing by massively parallel sequencing has become an effective and affordable way to survey small to large portions of the genome for genetic variation. Despite the rapid development in open source software for analysis of such data, the practical implementation of these tools through construction of sequencing analysis pipelines still remains a challenging and laborious activity, and a major hurdle for many small research and clinical laboratories. We developed TREVA (Targeted REsequencing Virtual Appliance), making pre-built pipelines immediately available as a virtual appliance. Based on virtual machine technologies, TREVA is a solution for rapid and efficient deployment of complex bioinformatics pipelines to laboratories of all sizes, enabling reproducible results. The analyses that are supported in TREVA include: somatic and germline single-nucleotide and insertion/deletion variant calling, copy number analysis, and cohort-based analyses such as pathway and significantly mutated genes analyses. TREVA is flexible and easy to use, and can be customised by Linux-based extensions if required. TREVA can also be deployed on the cloud (cloud computing), enabling instant access without investment overheads for additional hardware. TREVA is available at http://bioinformatics.petermac.org/treva/.