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dc.contributor.authorPritchard, Justin R.
dc.contributor.authorHemann, Michael
dc.contributor.authorLauffenburger, Douglas A
dc.date.accessioned2014-08-21T16:17:33Z
dc.date.available2014-08-21T16:17:33Z
dc.date.issued2012-10
dc.date.submitted2012-10
dc.identifier.issn13687646
dc.identifier.urihttp://hdl.handle.net/1721.1/88953
dc.descriptionavailable in PMC 2014 April 04en_US
dc.description.abstractThe current clinical application of combination chemotherapy is guided by a historically successful set of practices that were developed by basic and clinical researchers 50–60 years ago. Thus, in order to understand how emerging approaches to drug development might aid the creation of new therapeutic combinations, it is critical to understand the defining principles underlying classic combination therapy and the original experimental rationales behind them. One such principle is that the use of combination therapies with independent mechanisms of action can minimize the evolution of drug resistance. Another is that in order to kill sufficient cancer cells to cure a patient, multiple drugs must be delivered at their maximum tolerated dose – a condition that allows for enhanced cancer cell killing with manageable toxicity. In light of these models, we aim to explore recent genomic evidence underlying the mechanisms of resistance to the combination regimens constructed on these principles. Interestingly, we find that emerging genomic evidence contradicts some of the rationales of early practitioners in developing commonly used drug regimens. However, we also find that the addition of recent targeted therapies has yet to change the current principles underlying the construction of anti-cancer combinatorial regimens, nor have they made substantial inroads into the treatment of most cancers. We suggest that emerging systems/network biology approaches have an immense opportunity to impact the rational development of successful drug regimens. Specifically, by examining drug combinations in multivariate ways, next generation combination therapies can be constructed with a clear understanding of how mechanisms of resistance to multi-drug regimens differ from single agent resistance.en_US
dc.description.sponsorshipMassachusetts Institute of Technology (Eisen and Chang Career Development Associate Professor of Biology)en_US
dc.description.sponsorshipNational Cancer Institute (U.S.) (NCI Integrative Cancer Biology Program (ICBP), #U54-CA112967-06)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH RO1-CA128803-04)en_US
dc.language.isoen_US
dc.publisherElsevier B.V.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.drup.2012.10.003en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleUnderstanding resistance to combination chemotherapyen_US
dc.typeArticleen_US
dc.identifier.citationPritchard, Justin R., Douglas A. Lauffenburger, and Michael T. Hemann. “Understanding Resistance to Combination Chemotherapy.” Drug Resistance Updates 15, no. 5–6 (October 2012): 249–257.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.contributor.mitauthorHemann, Michaelen_US
dc.contributor.mitauthorLauffenburger, Douglas A.en_US
dc.contributor.mitauthorPritchard, Justin R.en_US
dc.relation.journalDrug Resistance Updatesen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPritchard, Justin R.; Lauffenburger, Douglas A.; Hemann, Michael T.en_US
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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