A multipathway phosphoproteomic signaling network model of idiosyncratic drug- and inflammatory cytokine-induced toxicity in human hepatocytes

Cosgrove, BD; Alexopoulos, LG; Saez-Rodriguez, J; Griffith, LG; Lauffenburger, DA

dc.contributor.author	Cosgrove, BD	en
dc.contributor.author	Alexopoulos, LG	en
dc.contributor.author	Saez-Rodriguez, J	en
dc.contributor.author	Griffith, LG	en
dc.contributor.author	Lauffenburger, DA	en
dc.date.accessioned	2014-03-01T02:45:55Z
dc.date.available	2014-03-01T02:45:55Z
dc.date.issued	2009	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32448
dc.subject	Animal Model	en
dc.subject	Cell Culture	en
dc.subject	Cell Death	en
dc.subject	Clinical Trial	en
dc.subject	Diversity Combining	en
dc.subject	Inflammatory Cytokine	en
dc.subject	Network Control	en
dc.subject	Partial Least Square Regression	en
dc.subject	Signaling Network	en
dc.subject	Signaling Pathway	en
dc.subject.other	Accurate prediction	en
dc.subject.other	Animal model	en
dc.subject.other	Clinical trial	en
dc.subject.other	Cytokines	en
dc.subject.other	Hepatocellular	en
dc.subject.other	Hepatocytes	en
dc.subject.other	Hepatotoxicity	en
dc.subject.other	Human hepatocytes	en
dc.subject.other	Human patients	en
dc.subject.other	Inflammatory cytokines	en
dc.subject.other	Partial least squares	en
dc.subject.other	Shared network	en
dc.subject.other	Signaling mechanisms	en
dc.subject.other	Signaling networks	en
dc.subject.other	Signaling pathways	en
dc.subject.other	Cell culture	en
dc.subject.other	Cell death	en
dc.subject.other	Signaling	en
dc.subject.other	Toxicity	en
dc.subject.other	Animal cell culture	en
dc.title	A multipathway phosphoproteomic signaling network model of idiosyncratic drug- and inflammatory cytokine-induced toxicity in human hepatocytes	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IEMBS.2009.5334019	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IEMBS.2009.5334019	en
heal.identifier.secondary	5334019	en
heal.publicationDate	2009	en
heal.abstract	Idiosyncratic drug hepatotoxicity is a hepatotoxicity subset that occurs in a very small fraction of human patients, is poorly predicted by standard preclinical models and in clinical trials, and frequently leads to post-approval drug failure. Animal models utilizing bacterial LPS co-administration to induce an inflammatory background and hepatocyte cell culture models utilizing cytokine mix cotreatment have successfully reproduced idiosyncratic hepatotoxicity signatures for certain drugs, but the hepatocyte signaling mechanisms governing these drug-cytokine toxicity synergizes are largely unclear. Here, we summarize our efforts to computationally model the signaling mechanisms regulating inflammatory cytokine-associated idiosyncratic drug hepatotoxicity. We collected a ""cue-signal-response"" (CSR) data compendium in cultured primary human hepatocytes treated with many combinations of idiosyncratic hepatotoxic drugs and inflammatory cytokine mixes (""cues"") and subjected this compendium to orthogonal partial-least squares regression (OPLSR) to computationally relate the measured intracellular phosphoprotein signals and hepatocellular death responses. This OPLSR model suggested that hepatocytes specify their cell death responses to toxic drug/cytokine conditions by integrating signals from four key pathways - Akt, p70 S6K, ERK, and p38. An OPLSR model focused on data from these four signaling pathways demonstrated accurate predictions of idiosyncratic drug- and cytokine-induced hepatotoxicities in a second human hepatocyte donor, suggesting that hepatocytes from different individuals have shared network control mechanisms governing toxicity responses to diverse combinations of idiosyncratic hepatotoxicants and inflammatory cytokines. ©2009 IEEE.	en
heal.journalName	Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009	en
dc.identifier.doi	10.1109/IEMBS.2009.5334019	en
dc.identifier.spage	5452	en
dc.identifier.epage	5455	en