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|a Williams, Richard T.
|e author
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|a Massachusetts Institute of Technology. Department of Biological Engineering
|e contributor
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|a Massachusetts Institute of Technology. Department of Biology
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|a Koch Institute for Integrative Cancer Research at MIT
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|a Lauffenburger, Douglas A.
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|a Jiang, Hai
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|a Pritchard, Justin Robert
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|a Lauffenburger, Douglas A.
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|a Hemann, Michael
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|a Jiang, Hai
|e author
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|a Hemann, Michael
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|a Pritchard, Justin R.
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|a Lauffenburger, Douglas A
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|a A mammalian functional-genetic approach to characterizing cancer therapeutics
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|b Nature Publishing Group,
|c 2011-11-16T22:27:33Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/67043
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|a Supplementary information is available online at http://www.nature.com/naturechemicalbiology/. Reprints and permissions information is available online at http://npg.nature.com/reprintsandpermissions/.
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|a 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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|a National Institute of Mental Health (U.S.) (grant RO1 CA128803-03)
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|a American Association for Cancer Research
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|a Massachusetts Institute of Technology. Dept. of Biology
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|a National Cancer Institute (U.S.). Integrative Cancer Biology Program (grant 1-U54-CA112967)
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|a en_US
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|a Article
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|t Nature Chemical Biology
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