Defining principles of combination drug mechanisms of action
Name
Pritchard-2012-Defining Principles of Combination Drug Mechanisms of Action.pdf
Size
1.57 MB
Format
Adobe PDF
Checksum (MD5)
d82cf74df225b1f02654e63f2e2ecc05
Author(s)
Bruno, Peter Michael
Gilbert, Luke Andrew
Capron, Kelsey L.
Hemann, Michael
Pritchard, Justin R.
Lauffenburger, Douglas A
Date Issued
December 2012
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Pritchard, J. R., P. M. Bruno, L. A. Gilbert, K. L. Capron, D. A. Lauffenburger, and M. T. Hemann. “PNAS Plus: Defining principles of combination drug mechanisms of action.” Proceedings of the National Academy of Sciences 110, no. 2 (January 8, 2013): E170-E179.
Version
Final published version
Abstract
Combination chemotherapies have been a mainstay in the treatment of disseminated malignancies for almost 60 y, yet even successful regimens fail to cure many patients. Although their single-drug components are well studied, the mechanisms by which drugs work together in clinical combination regimens are poorly understood. Here, we combine RNAi-based functional signatures with complementary informatics tools to examine drug combinations. This approach seeks to bring to combination therapy what the knowledge of biochemical targets has brought to single-drug therapy and creates a statistical and experimental definition of “combination drug mechanisms of action.” We show that certain synergistic drug combinations may act as a more potent version of a single drug. Conversely, unlike these highly synergistic combinations, most drugs average extant single-drug variations in therapeutic response. When combined to form multidrug regimens, averaging combinations form averaging regimens that homogenize genetic variation in mouse models of cancer and in clinical genomics datasets. We suggest surprisingly simple and predictable combination mechanisms of action that are independent of biochemical mechanism and have implications for biomarker discovery as well as for the development of regimens with defined genetic dependencies.
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
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1073/pnas.1210419110
