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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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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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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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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