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A mammalian functional-genetic approach to characterizing cancer therapeutics

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Abstract

Identifying mechanisms of drug action remains a fundamental impediment to the development and effective use of chemotherapeutics. Here we describe an RNA interference (RNAi)–based strategy to characterize small-molecule function in mammalian cells. By examining the response of cells expressing short hairpin RNAs (shRNAs) to a diverse selection of chemotherapeutics, we could generate a functional shRNA signature that was able to accurately group drugs into established biochemical modes of action. This, in turn, provided a diversely sampled reference set for high-resolution prediction of mechanisms of action for poorly characterized small molecules. We could further reduce the predictive shRNA target set to as few as eight genes and, by using a newly derived probability-based nearest-neighbors approach, could extend the predictive power of this shRNA set to characterize additional drug categories. Thus, a focused shRNA phenotypic signature can provide a highly sensitive and tractable approach for characterizing new anticancer drugs.

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Figure 1: Functional characterization of chemotherapeutic drugs according to patterns of shRNA-conferred drug resistance or sensitivity.
Figure 2: RNAi-based characterization of a compound derivative of bendamustine.
Figure 3: Identification and functional characterization of ill-defined genotoxic drugs.
Figure 4: A feature reduction identifies a reduced eight-shRNA set.
Figure 5: A reduced shRNA signature can accurately predict drug mechanism of action.
Figure 6: Adaptation of the eight-shRNA signature to a distinct cell line.

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Acknowledgements

The MM1S cell line was a generous gift from S. Rosen (Northwestern University). CY190602 and Hsp90 inhibitors were kindly provided by Nextwave Biotech. We thank L. Gilbert, H. Criscione, Stephanie Wu, S. Alford and Shan Wu for their experimental or analytical assistance. We are grateful to L. Samson, C. Pallasch and C. Meacham for critically reading the manuscript and the entire Hemann lab for helpful discussions. M.T.H. is a Rita Allen Fellow, and M.T.H. and H.J. are supported by US National Institutes of Health grant RO1 CA128803-03. J.R.P. is supported by the Massachusetts Institute of Technology Department of Biology training grant. R.T.W. is the recipient of an American Association for Cancer Research Career Development Award. Additional funding was provided by the Integrated Cancer Biology Program grant 1-U54-CA112967 to D.A.L. and M.T.H.

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Authors and Affiliations

  1. The Koch Institute for Integrative Cancer Research at MIT, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Hai Jiang, Justin R Pritchard, Douglas A Lauffenburger & Michael T Hemann

  2. Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA

    Richard T Williams

  3. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Douglas A Lauffenburger

Authors
  1. Hai Jiang
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  2. Justin R Pritchard
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  3. Richard T Williams
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  4. Douglas A Lauffenburger
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  5. Michael T Hemann
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Contributions

H.J., J.R.P. and M.T.H. designed experiments. H.J. and J.R.P. performed RNAi knockdown and treatment studies. J.R.P. developed the computational approaches and performed all of the computational analyses. R.T.W. developed and characterized the B-ALL cell line. H.J., J.R.P., D.A.L. and M.T.H. analyzed the data and wrote the manuscript.

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Correspondence to Michael T Hemann.

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The authors declare no competing financial interests.

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Supplementary Methods, Supplementary Figures 1–7 and Supplementary Tables 1–3 (PDF 367 kb)

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Jiang, H., Pritchard, J., Williams, R. et al. A mammalian functional-genetic approach to characterizing cancer therapeutics. Nat Chem Biol 7, 92–100 (2011). https://doi.org/10.1038/nchembio.503

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  • DOI: https://doi.org/10.1038/nchembio.503

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