Paclitaxel-induced peripheral neuropathy (PIPN) is a common and dose-limiting adverse event. The role of P-glycoprotein (P-gp) in the neuronal efflux of paclitaxel was assessed using a translational approach. SH-SY5Y cells were differentiated to neurons and paclitaxel toxicity in the absence and presence of a P-gp inhibitor was determined. Paclitaxel caused marked dose-dependent toxicity in SH-SY5Y-derived neurons. Paclitaxel neurotoxicity was exacerbated with concomitant P-gp inhibition by valspodar and verapamil, consistent with increased intracellular accumulation of paclitaxel. Patients with cancer treated with paclitaxel and P-gp inhibitors had a 2.4-fold (95% confidence interval (CI) 1.3-4.3) increased risk of peripheral neuropathy-induced dose modification while a 4.7-fold (95% CI 1.9-11.9) increased risk for patients treated with strong P-gp inhibitors was observed, and a 7.0-fold (95% CI 2.3-21.5) increased risk in patients treated with atorvastatin. Atorvastatin also increased neurotoxicity by paclitaxel in SH-SY5Y-derived neurons. Clinicians should be aware that comedication with P-gp inhibitors may lead to increased risk of PIPN.

Aim

The aim of this study was to study potential cytochrome P450 (CYP) induction by dicloxacillin.

Methods

We performed an open-label, randomized, two-phase, five-drug clinical pharmacokinetic cocktail crossover study in 12 healthy men with and without pretreatment with 1 g dicloxacillin three times daily for 10 days. Plasma and urine were collected over 24 h and the concentration of all five drugs and their primary metabolites was determined using a liquid chromatography coupled to triple quadrupole mass spectrometry method. Cryopreserved primary human hepatocytes were exposed to dicloxacillin for 48 h and changes in gene expression and the activity of CYP3A4, CYP2C9, CYP2B6 and CYP1A2 were investigated. The activation of nuclear receptors by dicloxacillin was assessed using luciferase assays.

Results

A total of 10 days of treatment with dicloxacillin resulted in a clinically and statistically significant reduction in the area under the plasma concentration-time curve from 0 to 24 h for omeprazole (CYP2C19) {geometric mean ratio [GMR] [95% confidence interval (CI)]: 0.33 [0.24, 0.45]}, tolbutamide (CYP2C9) [GMR (95% CI): 0.73 (0.65, 0.81)] and midazolam (CYP3A4) [GMR (95% CI): 0.54 (0.41, 0.72)]. Additionally, other relevant pharmacokinetic parameters were affected, indicating the induction of CYP2C- and CYP3A4-mediated metabolism by dicloxacillin. Investigations in primary hepatocytes showed a statistically significant dose-dependent increase in CYP expression and activity by dicloxacillin, caused by activation of the pregnane X receptor.

Conclusions

Dicloxacillin is an inducer of CYP2C- and CYP3A-mediated drug metabolism, and we recommend caution when prescribing dicloxacillin to users of drugs with a narrow therapeutic window.

Animal studies have pointed at the liver as a hotspot for per- and polyfluoroalkyl substances (PFAS) accumulation and toxicity; however, these findings have not been replicated in human populations. We measured concentrations of seven PFAS in matched liver and plasma samples collected at the time of bariatric surgery from 64 adolescents in the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study. Liver:plasma concentration ratios were perfectly explained (r2 > 0.99) in a multilinear regression (MLR) model based on toxicokinetic (TK) descriptors consisting of binding to tissue constituents and membrane permeabilities. Of the seven matched plasma and liver PFAS concentrations compared in this study, the liver:plasma concentration ratio of perfluoroheptanoic acid (PFHpA) was considerably higher than the liver:plasma concentration ratio of other PFAS congeners. Comparing the MLR model with an equilibrium mass balance model (MBM) suggested that complex kinetic transport processes are driving the unexpectedly high liver:plasma concentration ratio of PFHpA. Intratissue MBM modeling pointed to membrane lipids as the tissue constituents that drive the liver accumulation of long-chain, hydrophobic PFAS, whereas albumin binding of hydrophobic PFAS dominated PFAS distribution in plasma. The liver:plasma concentration data set, empirical MLR model, and mechanistic MBM modeling allow the prediction of liver from plasma concentrations measured in human cohort studies. Our study demonstrates that combining biomonitoring data with mechanistic modeling can identify underlying mechanisms of internal distribution and specific target organ toxicity of PFAS in humans.