A mammalian functional-genetic approach to characterizing cancer therapeutics
Name
Lauffenburger-2011-A Mammalian Functional-Genetic Approach.pdf
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1.2 MB
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Author(s)
Williams, Richard T.
Jiang, Hai
Hemann, Michael
Pritchard, Justin R.
Lauffenburger, Douglas A
Date Issued
December 2010
Journal
Nature Chemical Biology
Publisher
Nature Publishing Group
Citation
Jiang, Hai et al. “A mammalian functional-genetic approach to characterizing cancer therapeutics.” Nature Chemical Biology 7 (2010): 92-100. Web. 16 Nov. 2011. © 2010 Nature Publishing Group
Version
Author's final manuscript
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.
Description
Supplementary information is available online at http://www.nature.com/naturechemicalbiology/. Reprints and permissions information is available online at http://npg.nature.com/reprintsandpermissions/.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Koch Institute for Integrative Cancer Research at MIT
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1038/nchembio.503
