Show simple item record

dc.contributor.authorXu, Jinghai J.
dc.contributor.authorHendriks, Bart S.
dc.contributor.authorCosgrove, Benjamin D.
dc.contributor.authorKing, Bracken Matheny
dc.contributor.authorHasan, Maya A.
dc.contributor.authorAlexopoulos, Leonidas G.
dc.contributor.authorFarazi, Paraskevi A.
dc.contributor.authorSorger, Peter K.
dc.contributor.authorTidor, Bruce
dc.contributor.authorGriffith, Linda G.
dc.contributor.authorLauffenburger, Douglas A.
dc.date.accessioned2011-11-16T23:05:43Z
dc.date.available2011-11-16T23:05:43Z
dc.date.issued2009-06
dc.date.submitted2009-03
dc.identifier.issn0041-008X
dc.identifier.urihttp://hdl.handle.net/1721.1/67046
dc.description.abstractIdiosyncratic drug hepatotoxicity represents a major problem in drug development due to inadequacy of current preclinical screening assays, but recently established rodent models utilizing bacterial LPS co-administration to induce an inflammatory background have successfully reproduced idiosyncratic hepatotoxicity signatures for certain drugs. However, the low-throughput nature of these models renders them problematic for employment as preclinical screening assays. Here, we present an analogous, but high-throughput, in vitro approach in which drugs are administered to a variety of cell types (primary human and rat hepatocytes and the human HepG2 cell line) across a landscape of inflammatory contexts containing LPS and cytokines TNF, IFNγ, IL-1α, and IL-6. Using this assay, we observed drug–cytokine hepatotoxicity synergies for multiple idiosyncratic hepatotoxicants (ranitidine, trovafloxacin, nefazodone, nimesulide, clarithromycin, and telithromycin) but not for their corresponding non-toxic control compounds (famotidine, levofloxacin, buspirone, and aspirin). A larger compendium of drug–cytokine mix hepatotoxicity data demonstrated that hepatotoxicity synergies were largely potentiated by TNF, IL-1α, and LPS within the context of multi-cytokine mixes. Then, we screened 90 drugs for cytokine synergy in human hepatocytes and found that a significantly larger fraction of the idiosyncratic hepatotoxicants (19%) synergized with a single cytokine mix than did the non-hepatotoxic drugs (3%). Finally, we used an information theoretic approach to ascertain especially informative subsets of cytokine treatments for most highly effective construction of regression models for drug- and cytokine mix-induced hepatotoxicities across these cell systems. Our results suggest that this drug–cytokine co-treatment approach could provide a useful preclinical tool for investigating inflammation-associated idiosyncratic drug hepatotoxicity.en_US
dc.description.sponsorshipPfizer Inc.en_US
dc.description.sponsorshipInstitute for Collaborative Biotechnologiesen_US
dc.description.sponsorshipMIT Center for Cell Decision Processesen_US
dc.description.sponsorshipNational Institute of Mental Health (U.S.) (grant P50-GM68762)en_US
dc.description.sponsorshipNational Institute of Mental Health (U.S.) (grant T32-GM008334)en_US
dc.description.sponsorshipMassachusetts Institute of Technology. Biotechnology Process Engineering Centeren_US
dc.description.sponsorshipMassachusetts Institute of Technology. Center for Environmental Health Sciencesen_US
dc.description.sponsorshipNational Institute of Mental Health (U.S.) (grant U19ES011399)en_US
dc.description.sponsorshipWhitaker Foundationen_US
dc.language.isoen_US
dc.publisherElsevier Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.taap.2009.04.002en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourcePubMed Centralen_US
dc.titleSynergistic drug-cytokine induction of hepatocellular death as an in vitro approach for the study of inflammation-associated idiosyncratic drug hepatotoxicityen_US
dc.typeArticleen_US
dc.identifier.citationCosgrove, Benjamin D. et al. “Synergistic drug–cytokine induction of hepatocellular death as an in vitro approach for the study of inflammation-associated idiosyncratic drug hepatotoxicity.” Toxicology and Applied Pharmacology 237 (2009): 317-330. Web. 16 Nov. 2011. © 2009 Elsevier Ltd.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Biotechnology Process Engineering Centeren_US
dc.contributor.departmentMassachusetts Institute of Technology. Cell Decision Process Centeren_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverLauffenburger, Douglas A.
dc.contributor.mitauthorCosgrove, Benjamin D.
dc.contributor.mitauthorKing, Bracken Matheny
dc.contributor.mitauthorHasan, Maya A.
dc.contributor.mitauthorAlexopoulos, Leonidas G.
dc.contributor.mitauthorFarazi, Paraskevi A.
dc.contributor.mitauthorSorger, Peter K.
dc.contributor.mitauthorTidor, Bruce
dc.contributor.mitauthorGriffith, Linda G.
dc.contributor.mitauthorLauffenburger, Douglas A.
dc.relation.journalToxicology and Applied Pharmacologyen_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.orderedauthorsCosgrove, Benjamin D.; King, Bracken M.; Hasan, Maya A.; Alexopoulos, Leonidas G.; Farazi, Paraskevi A.; Hendriks, Bart S.; Griffith, Linda G.; Sorger, Peter K.; Tidor, Bruce; Xu, Jinghai J.; Lauffenburger, Douglas A.en
dc.identifier.orcidhttps://orcid.org/0000-0002-3320-3969
dc.identifier.orcidhttps://orcid.org/0000-0002-1801-5548
dspace.mitauthor.errortrue
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record