Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Jun 27;8(6):e67980.
doi: 10.1371/journal.pone.0067980. Print 2013.

Prioritizing Potentially Druggable Mutations With dGene: An Annotation Tool for Cancer Genome Sequencing Data

Free PMC article

Prioritizing Potentially Druggable Mutations With dGene: An Annotation Tool for Cancer Genome Sequencing Data

Runjun D Kumar et al. PLoS One. .
Free PMC article


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.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Figure 1
Figure 1. Rationale and process for construction of the dGene list.
A, Druggability serves as a rational screen in a hypothetical pipeline for reducing a raw gene list to an experimentally workable number. B, Lung cancer drugs in the pipeline classified by target type, with some target types considered broadly druggable and included in dGene. C, NHRs required a simple workflow. Russ et al, 2005 and NucleaRDB provided input. One gene mapped to neither the NCBI gene nor synonyms list. Six genes were identified in only one source and were manually checked against UniProt and Gene Ontology (GO) , . None could be confirmed as NHRs, leaving the final class with 48 members. D, The elaborated workflow for proteases is analogous to that of the NHRs and other classes. Because UniProt served as input, curation involved searching the primary literature in addition to querying GO.
Figure 2
Figure 2. Applying the dGene list to SNVs in 77 breast cancer tumours.
A, 368 SNVs occurred in genes considered to be druggable out of 2622 events total. B, 2199 genes had at least one SNV, of which 255 are considered druggable. C, Screening for commonly altered genes further reduces target list. D, 37 dGene entries present in at least 2 out of 77 samples, organized by class and patients affected.
Figure 3
Figure 3. Applying the dGene list to CNVs in 46 breast cancer tumours.
A, 5421 CNVs were detected in 1752 druggable genes across the sample. The 20th (0.7×) and 80th (1.5×) percentiles served as cutoffs. B, Gains only (>1.5×). C, Losses only (<0.7×). D, Displaying PTEN family CNV values. TPTE2 is the most frequently altered. Cutoffs are relaxed to <0.85× and >1.15× for display purposes.

Similar articles

See all similar articles

Cited by 11 articles

See all "Cited by" articles


    1. The Cancer Genome Atlas Research Network (2012) Comprehensive genomic characterization of squamous cell lung cancers. Nature 489: 519–525. - PMC - PubMed
    1. Ellis MJ, Ding L, Shen D, Luo J, Suman VJ, et al. (2012) Whole Genome Sequencing to Characterise Breast Cancer Response to Aromatase Inhibition. Nature 486: 353–360. - PMC - PubMed
    1. Hopkins AL & Groom CR (2002) The druggable genome. Nat Rev Drug Discov 1: 727–730. - PubMed
    1. Russ AP & Lampel S (2005) The druggable genome: an update. Drug Discov Today 10: 1607–1610. - PubMed
    1. Somaiah N & Simon GR (2011) Molecular targeted agents and biologic therapies for lung cancer. J Thorac Oncol 6: S1758–1785. - PubMed

Publication types