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DGIdb: mining the druggable genome


The Drug-Gene Interaction database (DGIdb) mines existing resources that generate hypotheses about how mutated genes might be targeted therapeutically or prioritized for drug development. It provides an interface for searching lists of genes against a compendium of drug-gene interactions and potentially 'druggable' genes. DGIdb can be accessed at

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Figure 1: Druggability of genes recurrently mutated in breast cancer.


  1. Hopkins, A.L. & Groom, C.R. Nat. Rev. Drug Discov. 1, 727–730 (2002).

    Article  CAS  Google Scholar 

  2. Russ, A.P. & Lampel, S. Drug Discov. Today 10, 1607–1610 (2005).

    Article  Google Scholar 

  3. Flicek, P. et al. Nucleic Acids Res. 39, D800–D806 (2011).

    Article  CAS  Google Scholar 

  4. Maglott, D., Ostell, J., Pruitt, K.D. & Tatusova, T. Nucleic Acids Res. 39, D52–D57 (2011).

    Article  CAS  Google Scholar 

  5. Wang, Y. et al. Nucleic Acids Res. 40, D400–D412 (2012).

    Article  CAS  Google Scholar 

  6. Knox, C. et al. Nucleic Acids Res. 39, D1035–D1041 (2011).

    Article  CAS  Google Scholar 

  7. McDonagh, E.M., Whirl-Carrillo, M., Garten, Y., Altman, R.B. & Klein, T.E. Biomarkers Med. 5, 795–806 (2011).

    Article  CAS  Google Scholar 

  8. Somaiah, N. & Simon, G.R. J. Thorac. Oncol. 6, S1758–S1785 (2011).

    Article  Google Scholar 

  9. Rask-Andersen, M., Almen, M.S. & Schioth, H.B. Nat. Rev. Drug Discov. 10, 579–590 (2011).

    Article  CAS  Google Scholar 

  10. Zhu, F. et al. Nucleic Acids Res. 38, D787–D791 (2010).

    Article  CAS  Google Scholar 

  11. Ashburner, M. et al. Nat. Genet. 25, 25–29 (2000).

    Article  CAS  Google Scholar 

  12. Kumar, R.D., Chang, L.W., Ellis, M.J. & Bose, R. PLoS One 8, e67980 (2013).

    Article  CAS  Google Scholar 

  13. Banerji, S. et al. Nature 486, 405–409 (2012).

    Article  CAS  Google Scholar 

  14. Cancer Genome Atlas Network. Nature 490, 61–70 (2012).

  15. Kan, Z. et al. Nature 466, 869–873 (2010).

    Article  CAS  Google Scholar 

  16. Shah, S.P. et al. Nature 486, 395–399 (2012).

    Article  CAS  Google Scholar 

  17. Stephens, P.J. et al. Nature 486, 400–404 (2012).

    Article  CAS  Google Scholar 

  18. Bose, R. et al. Cancer Discov. 3, 224–237 (2013).

    Article  CAS  Google Scholar 

  19. Yeh, P. et al. Clin. Cancer Res. 19, 1894–1901 (2013).

    Article  CAS  Google Scholar 

  20. Hunter, S. et al. Nucleic Acids Res. 40, D306–D312 (2012).

    Article  CAS  Google Scholar 

  21. Punta, M. et al. Nucleic Acids Res. 40, D290–D301 (2012).

    Article  CAS  Google Scholar 

  22. Kuhn, M. et al. Nucleic Acids Res. 40, D876–D880 (2012).

    Article  CAS  Google Scholar 

  23. Hecker, N. et al. Nucleic Acids Res. 40, D1113–D1117 (2012).

    Article  CAS  Google Scholar 

  24. Gaulton, A. et al. Nucleic Acids Res. 40, D1100–D1107 (2012).

    Article  CAS  Google Scholar 

  25. von Eichborn, J. et al. Nucleic Acids Res. 39, D1060–D1066 (2011).

    Article  CAS  Google Scholar 

  26. Davis, A.P. et al. Nucleic Acids Res. 41, D1104–D1114 (2013).

    Article  CAS  Google Scholar 

  27. Gao, Z. et al. BMC Bioinformatics 9, 104 (2008).

    Article  Google Scholar 

  28. Manning, G., Whyte, D.B., Martinez, R., Hunter, T. & Sudarsanam, S. Science 298, 1912–1934 (2002).

    Article  CAS  Google Scholar 

  29. Orth, A.P., Batalov, S., Perrone, M. & Chanda, S.K. Expert Opin. Ther. Targets 8, 587–596 (2004).

    Article  CAS  Google Scholar 

  30. Lamb, J. et al. Science 313, 1929–1935 (2006).

    Article  CAS  Google Scholar 

  31. Liu, T., Lin, Y., Wen, X., Jorissen, R.N. & Gilson, M.K. Nucleic Acids Res. 35, D198–D201 (2007).

    Article  CAS  Google Scholar 

  32. Yang, W. et al. Nucleic Acids Res. 41, D955–D961 (2013).

    Article  CAS  Google Scholar 

  33. Barretina, J. et al. Nature 483, 603–607 (2012).

    Article  CAS  Google Scholar 

  34. Lim, E. et al. Nucleic Acids Res. 38, D781–D786 (2010).

    Article  CAS  Google Scholar 

  35. Preissner, S. et al. Nucleic Acids Res. 38, D237–D243 (2010).

    Article  CAS  Google Scholar 

  36. Kuhn, M., Campillos, M., Letunic, I., Jensen, L.J. & Bork, P. Mol. Syst. Biol. 6, 343 (2010).

    Article  Google Scholar 

  37. Lounkine, E. et al. Nature 486, 361–367 (2012).

    Article  CAS  Google Scholar 

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We thank the creators of each source we used as input and all users of DGIdb who have contributed feedback, R. Altman, Stanford University and PharmGKB for granting us a license to mine their data, W. Pao of My Cancer Genome for agreeing to collaborate with us, and the individuals who participated in research that led to the breast cancer data used to demonstrate the utility of DGIdb. This work was funded by an US National Institutes of Health NHGRI center grant (U54 HG003079) to R.K.W.

Author information

Authors and Affiliations



O.L.G. and M.G. wrote the manuscript, were responsible for the selection and manual curation of data sources, creation of importers, initial design of the web interface, testing, analysis and figure creation for the manuscript. I.D. and J.F.M. helped create figures. A.C.C. and J.V.W. conceived and lead the Ruby implementation of the web interface, database, importers and application programming interface (API). J.K., M.G., O.L.G., S.M.S., I.D. and J.F.M. made contributions to the code. J.F.M. was the lead user experience web developer. S.M.S., J.M.E., J.R.W. and D.J.D. supervised software development. M.B.C. facilitated the public deployment of DGIdb and all related systems requirements. R.B., R.D.K., C.A.M. and D.E.L. provided beta testing feedback. J.S. and R.G. provided and curated the 'targeted agents in lung cancer' data set. R.B. and R.D.K. contributed the dGene data set and the breast cancer data used for analysis demonstration purposes. N.C.S. contributed manual curation of data sources and documentation. S.M.S., J.M.E., D.J.D., L.D., T.J.L., E.R.M. and R.K.W. contributed ideas and use case requirements. A.C.C., J.V.W., C.A.M., R.D.K., R.B., D.E.L. and E.R.M. contributed text and revised the manuscript. E.R.M. and R.K.W. are mentors of M.G. and O.L.G.

Corresponding authors

Correspondence to Malachi Griffith or Obi L Griffith.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7 and Supplementary Tables 1–4 (PDF 7218 kb)

Supplementary Table 5

Breast cancer druggable candidates. (XLSX 51 kb)

Supplementary Table 6

Breast cancer known druggability by patient. (XLSX 1114 kb)

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Griffith, M., Griffith, O., Coffman, A. et al. DGIdb: mining the druggable genome. Nat Methods 10, 1209–1210 (2013).

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