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Consistency in large pharmacogenomic studies

Nature volume 540, pages E1E2 (01 December 2016) | Download Citation

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  • 13 December 2016

    The received date and affiliation details for author P.G. were corrected in the HTML.


  1. 1.

    et al. Inconsistency in large pharmacogenomic studies. Nature 504, 389–393 (2013)

  2. 2.

    et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607 (2012)

  3. 3.

    et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature 483, 570–575 (2012)

  4. 4.

    et al. Activity of the dual kinase inhibitor lapatinib (GW572016) against HER-2-overexpressing and trastuzumab-treated breast cancer cells. Cancer Res. 66, 1630–1639 (2006)

  5. 5.

    , , , & DT-Diaphorase expression and tumor cell sensitivity to 17-allylamino, 17-demethoxygeldanamycin, an inhibitor of heat shock protein 90. J. Natl. Cancer Inst. 91, 1940–1949 (1999)

  6. 6.

    et al. BRAF mutation predicts sensitivity to MEK inhibition. Nature 439, 358–362 (2006)

  7. 7.

    et al. Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244). Cancer Res. 70, 2264–2273 (2010)

  8. 8.

    et al. Discovery of a selective inhibitor of oncogenic B-Raf kinase with potent antimelanoma activity. Proc. Natl Acad. Sci. USA 105, 3041–3046 (2008)

  9. 9.

    et al. Potential for treatment of liposarcomas with the MDM2 antagonist Nutlin-3A. Int. J. Cancer 121, 199–205 (2007)

  10. 10.

    & Crizotinib for the treatment of non-small-cell lung cancer. Am. J. Health Syst. Pharm. 70, 943–947 (2013)

  11. 11.

    , & Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. Genome Biol. 15, R47 (2014)

  12. 12.

    et al. Predicting response to multidrug regimens in cancer patients using cell line experiments and regularised regression models. BMC Cancer 15, 235 (2015)

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Author information


  1. Department of Medicine, The University of Chicago, Chicago, Illinois 60637, USA.

    • Paul Geeleher
    • , Eric R. Gamazon
    • , Nancy J. Cox
    •  & R. Stephanie Huang
  2. Division of Genetic Medicine, Vanderbilt University, Nashville, Tennessee 37232, USA.

    • Eric R. Gamazon
    •  & Nancy J. Cox
  3. Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands.

    • Eric R. Gamazon
  4. Department of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland.

    • Cathal Seoighe


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Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Nancy J. Cox or R. Stephanie Huang.

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    This file shows a summary of the results reported with the Supplementary Data of CGP and CCLE for the 15 compounds assessed by Haibe-Kains et al. These results were obtained from either the CGP web portal ( or the supplementary tables S6 & S7 or supplementary figure 9 provided with the publication of the CCLE data. These already published results show a very clear trend of both studies reliably identifying many canonical drug targets.

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