dc.contributor.author | Xu, Jinghai J. | |
dc.contributor.author | Hendriks, Bart S. | |
dc.contributor.author | Cosgrove, Benjamin D. | |
dc.contributor.author | King, Bracken Matheny | |
dc.contributor.author | Hasan, Maya A. | |
dc.contributor.author | Alexopoulos, Leonidas G. | |
dc.contributor.author | Farazi, Paraskevi A. | |
dc.contributor.author | Sorger, Peter K. | |
dc.contributor.author | Tidor, Bruce | |
dc.contributor.author | Griffith, Linda G. | |
dc.contributor.author | Lauffenburger, Douglas A. | |
dc.date.accessioned | 2011-11-16T23:05:43Z | |
dc.date.available | 2011-11-16T23:05:43Z | |
dc.date.issued | 2009-06 | |
dc.date.submitted | 2009-03 | |
dc.identifier.issn | 0041-008X | |
dc.identifier.uri | http://hdl.handle.net/1721.1/67046 | |
dc.description.abstract | Idiosyncratic 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.sponsorship | Pfizer Inc. | en_US |
dc.description.sponsorship | Institute for Collaborative Biotechnologies | en_US |
dc.description.sponsorship | MIT Center for Cell Decision Processes | en_US |
dc.description.sponsorship | National Institute of Mental Health (U.S.) (grant P50-GM68762) | en_US |
dc.description.sponsorship | National Institute of Mental Health (U.S.) (grant T32-GM008334) | en_US |
dc.description.sponsorship | Massachusetts Institute of Technology. Biotechnology Process Engineering Center | en_US |
dc.description.sponsorship | Massachusetts Institute of Technology. Center for Environmental Health Sciences | en_US |
dc.description.sponsorship | National Institute of Mental Health (U.S.) (grant U19ES011399) | en_US |
dc.description.sponsorship | Whitaker Foundation | en_US |
dc.language.iso | en_US | |
dc.publisher | Elsevier Ltd. | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.taap.2009.04.002 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike 3.0 | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/ | en_US |
dc.source | PubMed Central | en_US |
dc.title | Synergistic drug-cytokine induction of hepatocellular death as an in vitro approach for the study of inflammation-associated idiosyncratic drug hepatotoxicity | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Cosgrove, 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.department | Massachusetts Institute of Technology. Biotechnology Process Engineering Center | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Cell Decision Process Center | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Biological Engineering | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.contributor.approver | Lauffenburger, Douglas A. | |
dc.contributor.mitauthor | Cosgrove, Benjamin D. | |
dc.contributor.mitauthor | King, Bracken Matheny | |
dc.contributor.mitauthor | Hasan, Maya A. | |
dc.contributor.mitauthor | Alexopoulos, Leonidas G. | |
dc.contributor.mitauthor | Farazi, Paraskevi A. | |
dc.contributor.mitauthor | Sorger, Peter K. | |
dc.contributor.mitauthor | Tidor, Bruce | |
dc.contributor.mitauthor | Griffith, Linda G. | |
dc.contributor.mitauthor | Lauffenburger, Douglas A. | |
dc.relation.journal | Toxicology and Applied Pharmacology | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Cosgrove, 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.orcid | https://orcid.org/0000-0002-3320-3969 | |
dc.identifier.orcid | https://orcid.org/0000-0002-1801-5548 | |
dspace.mitauthor.error | true | |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |