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An unbiased metric of antiproliferative drug effect in vitro

Nature Methods volume 13, pages 497500 (2016) | Download Citation

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Abstract

In vitro cell proliferation assays are widely used in pharmacology, molecular biology, and drug discovery. Using theoretical modeling and experimentation, we show that current metrics of antiproliferative small molecule effect suffer from time-dependent bias, leading to inaccurate assessments of parameters such as drug potency and efficacy. We propose the drug-induced proliferation (DIP) rate, the slope of the line on a plot of cell population doublings versus time, as an alternative, time-independent metric.

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Change history

  • 13 May 2016

    In the version of this article initially published online, two funding sources were not listed in the Acknowledgments. The sentence "This work was also supported by the National Science Foundation (grant MCB-1411482 to C.F.L.) and the VICC (Young Ambassador Award to C.F.L.)." was added prior to the last sentence in the Acknowledgments.

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Acknowledgements

We are grateful to R. Feroze, J. Hao, K. Jameson, and C. Peng for support in experimental data acquisition; to J. Guinney, T. de Paulis, and J.R. Faeder for critical reviews of the manuscript; to W. Pao (Vanderbilt University, Nashville, Tennessee) for providing the PC9 cell line; and to M. Herlyn (Wistar Institute, Philadelphia, Pennsylvania) for providing the WM115 cell line. This work was supported by Uniting Against Lung Cancer 13020513 (D.R.T.), Vanderbilt Biomedical Informatics Training Program NLM 5T15-LM007450-14 (L.A.H.), and the National Cancer Institute U54-CA113007 (V.Q.), U01-CA174706 (V.Q.), and R01-CA186193 (V.Q.), and partially supported by the National Cancer Institute (P50-CA098131) and the National Center for Advancing Translational Sciences (UL1-TR000445-06). This work was also supported by the National Science Foundation (grant MCB-1411482 to C.F.L.) and the VICC (Young Ambassador Award to C.F.L.). Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Cancer Institute, the National Center for Advancing Translational Sciences, or the National Institutes of Health.

Author information

Author notes

    • Leonard A Harris
    •  & Peter L Frick

    These authors contributed equally to this work.

Affiliations

  1. Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.

    • Leonard A Harris
    • , Peter L Frick
    • , Shawn P Garbett
    • , Keisha N Hardeman
    • , B Bishal Paudel
    • , Carlos F Lopez
    • , Vito Quaranta
    •  & Darren R Tyson
  2. Center for Cancer Systems Biology at Vanderbilt, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.

    • Leonard A Harris
    • , Peter L Frick
    • , Shawn P Garbett
    • , Keisha N Hardeman
    • , B Bishal Paudel
    • , Vito Quaranta
    •  & Darren R Tyson
  3. Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.

    • Carlos F Lopez
  4. Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.

    • Carlos F Lopez

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Contributions

D.R.T., L.A.H., P.L.F., and S.P.G. conceived and designed the study; D.R.T., L.A.H., and S.P.G. built the mathematical models and performed simulations; B.B.P., K.N.H., and P.L.F. acquired experimental data; D.R.T., L.A.H., P.L.F., and S.P.G. analyzed and interpreted the experimental data; C.F.L., D.R.T., L.A.H., P.L.F., S.P.G., and V.Q. wrote, reviewed, and/or revised the manuscript; and C.F.L., D.R.T., and V.Q. supervised the study.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Darren R Tyson.

Integrated supplementary information

Supplementary information

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  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–9, Supplementary Tables 1 and 2, and Supplementary Note

Zip files

  1. 1.

    Supplementary Software

    Software for obtaining DIP rates automatically from raw cell count data.

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DOI

https://doi.org/10.1038/nmeth.3852

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