Proteases and their inhibitors as prognostic factors for high-grade serous ovarian cancer

Ovarian carcinoma is one of the most lethal malignancies, but only very few prognostic biomarkers are known. The degradome, comprising proteases, protease non-proteolytic homologues and inhibitors, have been involved in the prognosis of many cancer types, including ovarian carcinoma. The prognostic significance of the whole degradome family has not been specifically studied in high-grade serous ovarian cancer. A targeted DNA microarray known as the CLIP-CHIP microarray was used to identify potential prognostic factors in ten high-grade serous ovarian cancer women who had early recurrence (<1.6 years) or late/no recurrence after first line surgery and chemotherapy. In women with early recurrence, we identified seven upregulated genes (TMPRSS4, MASP1/3, SPC18, PSMB1, IGFBP2, CFI – encoding Complement Factor I – and MMP9) and one down-regulated gene (ADAM-10). Using immunohistochemistry, we evaluated the prognostic effect of these 8 candidate genes in an independent cohort of 112 high-grade serous ovarian cancer women. Outcomes were progression, defined according to CA-125 criteria, and death. Multivariate Cox proportional hazard regression models were done to estimate the associations between each protein and each outcome. High ADAM-10 expression (intensity of 2–3) was associated with a lower risk of progression (adjusted hazard ratio (HR): 0.51; 95% confidence interval (CI): 0.29-0.87). High complement factor I expression (intensity 2–3) was associated with a higher risk of progression (adjusted HR: 2.30, 95% CI: 1.17–4.53) and death (adjusted HR: 3.42; 95% CI: 1.72–6.79). Overall, we identified the prognostic value of two proteases, ADAM-10 and complement factor I, for high-grade serous ovarian cancer which could have clinical significance.     

„Sind opioidfreie Anästhesie (OFA) und volatile Anästhetika wirklich die einzigen Wege? Ein kritischer Kommentar“

Die Anaesthesiologie -     

Development and validation of a population pharmacokinetic model for ritonavir used as a booster or as an antiviral agent in HIV-1-infected patients

AIMS: The aim of this study was to develop and validate a population pharmacokinetic model of ritonavir, used as an antiviral agent or as a booster, in a large patient population and to identify factors influencing its pharmacokinetics. METHODS: Ambulatory HIV-1-infected patients from the outpatient clinic of the Slotervaart Hospital, Amsterdam, the Netherlands, who were being treated with a ritonavir-containing regimen were included. During regular visits, blood samples were collected for the determination of ritonavir plasma concentrations and several clinical chemistry parameters. Furthermore, complete pharmacokinetic curves were available in some patients. Single and multiple compartment models with zero-order and first-order absorption, with and without absorption lag-time, with linear and nonlinear elimination were tested, using nonlinear mixed effect modelling (NONMEM). Pharmacokinetic parameters and interindividual, interoccasion and residual variability were estimated. In addition, the influence of several factors (e.g. patient characteristics, comedication) on the pharmacokinetics of ritonavir was explored. RESULTS: From 186 patients 505 ritonavir plasma concentrations at a single time-point and 55 full pharmacokinetic profiles were available, resulting in a database of 1228 plasma ritonavir concentrations. In total 62% of the patients used ritonavir as a booster of their protease inhibitor containing antiretroviral regimen. First order absorption in combination with one-compartment disposition best described the pharmacokinetics of ritonavir. Clearance, volume of distribution and absorption rate constant were 10.5 l h(-1) (95% prediction interval (95% PI) 9.38-11.7), 96.6 l (95% PI 67.2-121) and 0.871 h(-1) (95% PI 0.429-1.47), respectively, with 38.3%, 80.0% and 169% interindividual variability, respectively. The interoccasion variability in the apparent bioavailability was 59.1%. The concomitant use of lopinavir resulted in a 2.7-fold increase in the clearance of ritonavir (P value < 0.001). No patients characteristics influenced the pharmacokinetics of ritonavir. CONCLUSIONS: The pharmacokinetic parameters of ritonavir were adequately described by our population pharmacokinetic model. Concomitant use of the protease inhibitor lopinavir strongly influenced the pharmacokinetics of ritonavir. The model has been validated and can be used for further investigation of the interaction between ritonavir and other protease inhibitors.     

Are adverse events of nevirapine and efavirenz related to plasma concentrations?

OBJECTIVE: The relationships between adverse events (AEs) and plasma concentrations of nevirapine (NVP) and efavirenz (EFV) were investigated as part of the large, international, randomized 2NN study. METHODS: Treatment-naive, HIV-1-infected patients received NVP (once or twice daily), EFV or their combination, each in combination with lamivudine and stavudine. Blood samples were collected on day 3 and weeks 1, 2, 4, 24 and 48. Concentrations of NVP and EFV were quantitatively assessed by a validated HPLC assay. Individual Bayesian estimates of the area under the plasma concentration-time curve over 24 h (AUC24h), and minimum and maximum plasma concentrations (Cmin and Cmax) as measures for drug exposure of NVP and EFV, were generated using a previously developed population pharmacokinetic model. Pharmacokinetic parameters were compared for patients with and without central nervous system (CNS) and psychiatric AEs, hepatic events, liver enzyme elevations (LEEs) and rash. Furthermore, it was investigated whether a clear cut-off for a pharmacokinetic parameter could be identified above which the incidence of AEs was clearly increased. AEs were also related to demographic parameters and baseline characteristics. RESULTS: In total, from 1077 patients, NVP (3024 samples) and EFV (1694 samples) plasma concentrations and AE data (825 observations) were available. For all patients Cmin, Cmax and AUC24h were determined. When corrected for known covariates of gender, CD4 cell count at baseline, region, hepatitis coinfection and possible interactions between these factors, no significant associations between AEs and any tested exposure parameter of NVP was observed. Also, no target Cmin value, above which patients were at increased risk for AEs, could be established. On the other hand, geographical region, hepatitis coinfection, CD4 cell count and gender were found to be significantly related with the incidence of CNS and psychiatric AEs, hepatic events, LEEs and rash during the treatment with NVP. The occurrence of elevated liver enzymes during the first 6 weeks in the EFV-containing arm was significantly (P = 0.036) correlated to the exposure of EFV (Cmin). Only hepatitis coinfection impacted on LEEs during the first 6 weeks of treatment. With an EFV Cmin above 2.18 mg/l during the induction phase, patients were 4.4 (range 1.3-15.5) times more at risk for elevated liver enzymes. No other correlations between AEs and EFV pharmacokinetics or patient characteristics could be identified. CONCLUSIONS: Pharmacokinetic parameters of NVP did not have a relationship to AEs in the 2NN trial when corrected for known covariates. The value of periodical drug monitoring of NVP as a way to prevent toxicity is therefore limited. Treating physicians should instead focus on factors that are more predictive of AEs (gender, CD4 count and hepatitis coinfection). High EFV Cmin levels resulted in elevated liver enzyme values during the first 6 weeks of treatment. Regular measurement of EFV levels and liver enzymes at the start of therapy may therefore be advised.     

How music alters a kiss: superior temporal gyrus controls fusiform–amygdalar effective connectivity

While watching movies, the brain integrates the visual information and the musical soundtrack into a coherent percept. Multisensory integration can lead to emotion elicitation on which soundtrack valences may have a modulatory impact. Here, dynamic kissing scenes from romantic comedies were presented to 22 participants (13 females) during functional magnetic resonance imaging scanning. The kissing scenes were either accompanied by happy music, sad music or no music. Evidence from cross-modal studies motivated a predefined three-region network for multisensory integration of emotion, consisting of fusiform gyrus (FG), amygdala (AMY) and anterior superior temporal gyrus (aSTG). The interactions in this network were investigated using dynamic causal models of effective connectivity. This revealed bilinear modulations by happy and sad music with suppression effects on the connectivity from FG and AMY to aSTG. Non-linear dynamic causal modeling showed a suppressive gating effect of aSTG on fusiform–amygdalar connectivity. In conclusion, fusiform to amygdala coupling strength is modulated via feedback through aSTG as region for multisensory integration of emotional material. This mechanism was emotion-specific and more pronounced for sad music. Therefore, soundtrack valences may modulate emotion elicitation in movies by differentially changing preprocessed visual information to the amygdala.     

Population pharmacokinetics of efavirenz in an unselected cohort of HIV-1-infected individuals

OBJECTIVE: The aim of this study was to characterise the population pharmacokinetics of efavirenz in a representative patient population and to identify patient characteristics influencing the pharmacokinetics of efavirenz, with the ultimate goal of further developing techniques that can be applied to optimise therapeutic drug monitoring of antiretroviral agents. METHODS: Ambulatory HIV-1-infected patients using an efavirenz-containing regimen were included. During regular visits, blood samples were collected for efavirenz plasma concentrations and clinical chemistry parameters. Concentrations of efavirenz were quantitatively assessed by a validated high-performance liquid chromatographic with ultraviolet detection method. Using nonlinear mixed-effect modelling (NONMEM), the pharmacokinetics of efavirenz were described. Disposition of efavirenz was described by a two-compartment model and absorption was modelled using a chain of three transition compartments. Apparent clearance (CL/F), volume of distribution after oral administration (V(d)/F), intercompartmental clearance, the peripheral volume of distribution and the intercompartmental transition rate constant (k(tr)) were estimated. Furthermore, interindividual, interoccasion and residual variability were estimated. The influence of patient characteristics on the pharmacokinetic parameters of efavirenz was explored. RESULTS: From 172 patients, 40 full pharmacokinetic curves and 315 efavirenz plasma concentrations at a single timepoint were available, resulting in a database of 1009 efavirenz plasma concentrations. CL/F, V(d)/F, and k(tr) were 11.7 L/h (4.3% relative standard error [RSE]), 189L (14.6% RSE) and 3.07 h(-1) (11.2% RSE), respectively. Residual variability in the model was composed of 0.14 mg/L additive error and 8.85% proportional error. Asian race and baseline total bilirubin (TBR) increased the relative bioavailability of efavirenz by 56% and 57%, respectively. No significant covariates were found for CL/F or V(d)/F. CONCLUSION: The pharmacokinetic parameters of efavirenz were adequately described with the developed population pharmacokinetic model. Asian race and baseline TBR were found to be significantly correlated with the bioavailability of efavirenz. The described model will be an essential tool in further optimisation of efavirenz-containing antiretroviral therapy, e.g. by the use of Bayesian estimation of individual pharmacokinetic parameters.