Abstract
Proinflammatory cytokines, elevated during inflammation caused by infection and/or autoimmune disorders, result in reduced clearance of drugs eliminated primarily by cytochrome P450 enzymes (CYPs). However, the effect of cytokines on hepatic drug transporter expression or activity has not been well-studied. Here, using plated human hepatocytes (PHHs; n = 3 lots), we investigated the effect of interleukin (IL)-6, IL-1β, tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ), on the mRNA expression and activity of hepatic drug transporters. PHHs were incubated for 72 hours at their pathophysiologically relevant plasma concentrations, both individually (0.01, 0.1, 1, 10 ng/ml) or as a cocktail (i.e., when each was combined at 0.1 or 1 ng/ml). Following cytokine cocktail exposure (1 ng/ml), significant downregulation of mRNA expression of organic anion transporting polypeptide 1B1 (OATP1B1), OATP1B3, sodium/taurocholate cotransporting polypeptide (NTCP), breast cancer resistance protein (BCRP), P-glycoprotein (P-gp), multidrug and toxin extrusion protein 1, multidrug resistance proteins (MRP) 2, 3, and 4 was observed. While the mRNA expression of organic anion transporter (OAT) 2 and organic cation transporter (OCT) 1 was downregulated in two lots, it was upregulated in one lot. In agreement (mostly), the 1 ng/ml cytokine cocktail reduced OATP1B1/3, OATP2B1, OAT2, OCT1, and NTCP activity by 75%, 44%, 82%, 47%, and 80%, respectively. Interestingly, upregulation of OAT2 and OCT1 mRNA in one donor did not translate into the same directional change in activity. Although significant interlot variability was observed, in general, the above effects, using individual cytokines, could be attributed to IL-1β, TNF-α, and IFN-γ. SIGNIFICANCE STATEMENT: To date, this is the first comprehensive study to investigate the effect of four major proinflammatory cytokines, both individually and as a cocktail, on the mRNA expression and activity of human hepatic drug transporters. The data obtained can be used in the future to predict transporter-mediated drug clearance changes during inflammation through physiologically based pharmacokinetic modeling and simulation.