Abstract
A major goal of cancer genome sequencing is to identify mutations or other somatic alterations that can be targeted by selective and specific drugs. dGene is an annotation tool designed to rapidly identify genes belonging to one of ten druggable classes that are frequently targeted in cancer drug development. These classes were comprehensively populated by combining and manually curating data from multiple specialized and general databases. dGene was used by The Cancer Genome Atlas squamous cell lung cancer project, and here we further demonstrate its utility using recently released breast cancer genome sequencing data. dGene is designed to be usable by any cancer researcher without the need for support from a bioinformatics specialist. A full description of dGene and options for its implementation are provided here.
Citation: Kumar RD, Chang L-W, Ellis MJ, Bose R (2013) Prioritizing Potentially Druggable Mutations with dGene: An Annotation Tool for Cancer Genome Sequencing Data. PLoS ONE 8(6): e67980. doi:10.1371/journal.pone.0067980
Editor: Patrick Tan, Duke-National University of Singapore Graduate Medical School, Singapore
Received: February 27, 2013; Accepted: May 24, 2013; Published: June 27, 2013
Copyright: © 2013 Kumar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Financial support for this work was provided by NIH grants R01CA095614 and U01HG00651701 (to MJE), and the Edward Mallinckrodt, Jr. Foundation and the ‘Ohana Breast Cancer Research Fund (to RB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Cancer genome sequencing studies are now analyzing 50 to 500 patients per study and are documenting thousands of somatic mutations . New tools for annotation and analysis are needed to predict the functional relevance of these genetic alterations and guide subsequent investigations. Here, we introduce a tool based on druggable genes which, in combination with other annotation and filtering steps, can rapidly prioritize a large set of mutations into a more focused set that can be tested in functional studies.
This tool, which we call dGene (collection of Druggable Genes), is based on the concept of the druggable genome introduced by Hopkins and Groom in 2002 . They identified protein classes that can potentially bind small molecule drugs and proposed that disease-modifying genes belonging to a druggable class should be prioritized for drug development . This set of druggable genes was based on the observation that FDA approved drugs and compounds in development do not target the human genome uniformly, with some gene classes, such as G-protein coupled receptors (GPCR) and protein kinases, being more frequently targeted by small molecules.
dGene adds to their work by expanding and updating the set of druggable classes based on current drug development efforts, populating classes comprehensively and maintaining quality through manual curation. In this article, we describe the rationale and construction of dGene, demonstrate its utility in a recently released set of breast cancer whole-genome and whole-exome sequence data and provide instructions for using dGene.
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