S100A10 protein expression is associated with oxaliplatin sensitivity in human colorectal cancer cells

<p>Abstract</p> <p>Background</p> <p>Individual responses to oxaliplatin (L-OHP)-based chemotherapy remain unpredictable. The objective of our study was to find candidate protein markers for tumor sensitivity to L-OHP from intracellular proteins of human colorectal cancer (CRC) cell lines. We performed expression difference mapping (EDM) analysis of whole cell lysates from 11 human CRC cell lines with different sensitivities to L-OHP by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), and identified a candidate protein by liquid chromatography/mass spectrometry ion trap time-of-flight (LCMS-IT-TOF).</p> <p>Results</p> <p>Of the qualified mass peaks obtained by EDM analysis, 41 proteins were differentially expressed in 11 human colorectal cancer cell lines. Among these proteins, the peak intensity of 11.1 kDa protein was strongly correlated with the L-OHP sensitivity (50% inhibitory concentrations) (<it>P </it>< 0.001, <it>R²</it>= 0.80). We identified this protein as Protein S100-A10 (S100A10) by MS/MS ion search using LCMS-IT-TOF. We verified its differential expression and the correlation between S100A10 protein expression levels in drug-untreated CRC cells and their L-OHP sensitivities by Western blot analyses. In addition, S100A10 protein expression levels were not correlated with sensitivity to 5-fluorouracil, suggesting that S100A10 is more specific to L-OHP than to 5-fluorouracil in CRC cells. S100A10 was detected in cell culture supernatant, suggesting secretion out of cells.</p> <p>Conclusions</p> <p>By proteomic approaches including SELDI technology, we have demonstrated that intracellular S100A10 protein expression levels in drug-untreated CRC cells differ according to cell lines and are significantly correlated with sensitivity of CRC cells to L-OHP exposure. Our findings provide a new clue to searching predictive markers of the response to L-OHP, suggesting that S100A10 is expected to be one of the candidate protein markers.</p

Role of the DELSEED Loop in Torque Transmission of F1-ATPase

AbstractF1-ATPase is an ATP-driven rotary motor that generates torque at the interface between the catalytic β-subunits and the rotor γ-subunit. The β-subunit inwardly rotates the C-terminal domain upon nucleotide binding/dissociation; hence, the region of the C-terminal domain that is in direct contact with γ—termed the DELSEED loop—is thought to play a critical role in torque transmission. We substituted all the DELSEED loop residues with alanine to diminish specific DELSEED loop-γ interactions and with glycine to disrupt the loop structure. All the mutants rotated unidirectionally with kinetic parameters comparable to those of the wild-type F1, suggesting that the specific interactions between DELSEED loop and γ is not involved in cooperative interplays between the catalytic β-subunits. Glycine substitution mutants generated half the torque of the wild-type F1, whereas the alanine mutant generated comparable torque. Fluctuation analyses of the glycine/alanine mutants revealed that the γ-subunit was less tightly held in the α3β3-stator ring of the glycine mutant than in the wild-type F1 and the alanine mutant. Molecular dynamics simulation showed that the DELSEED loop was disordered by the glycine substitution, whereas it formed an α-helix in the alanine mutant. Our results emphasize the importance of loop rigidity for efficient torque transmissions

Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model

AIMS: Population pharmacokinetic (pop PK) modelling can be used for PK assessment of drugs in breast milk. However, complex mechanistic modelling of a parent and an active metabolite using both blood and milk samples is challenging. We aimed to develop a simple predictive pop PK model for milk concentration-time profiles of a parent and a metabolite, using data on fluoxetine (FX) and its active metabolite, norfluoxetine (NFX), in milk

Delineating the Role of Various Factors in Renal Disposition of Digoxin through Application of Physiologically Based Kidney Model to Renal Impairment Populations

Development of sub-models of organs within physiologically-based pharmacokinetic (PBPK) principles and beyond simple perfusion limitations may be challenging because of underdeveloped in vitro-in vivo extrapolation approaches or lack of suitable clinical data for model refinement. However, the advantage of such models in predicting clinical observations in divergent patient groups is now commonly acknowledged. Mechanistic understanding of altered renal secretion in renal impairment is one area that may benefit from such models, despite knowledge gaps in renal pathophysiology (Rowland Yeo et al., 2011; Sayama et al., 2014). In the current study a PBPK kidney model was developed for digoxin, accounting for the roles of organic anion transporting peptide 4C1 (OATP4C1) and P-glycoprotein (P-gp) in its tubular secretion, with the aim to investigate the impact of age and renal impairment (moderate to severe) on renal drug disposition. Initial PBPK simulations based on changes in glomerular filtration rate (GFR) underestimated the observed reduction in digoxin renal excretion clearance (CLR) in subjects with moderately impaired renal function relative to healthy. Reduction in either proximal tubule cell number or the OATP4C1 abundance in the mechanistic kidney model successfully predicted 59% decrease in digoxin CLR, in particular when these changes were proportional to reduction in GFR. In contrast, predicted proximal tubule concentration of digoxin was only sensitive to changes in the transporter expression/ million proximal tubule cells. Based on the mechanistic modelling, reduced proximal tubule cellularity and OATP4C1 abundance, and inhibition of OATP4C1-mediated transport, are proposed as possible causes of reduced digoxin renal secretion in renally impaired patients

Pharmacodynamic analysis of eribulin safety in breast cancer patients using real-world postmarketing surveillance data

Postmarketing surveillance is useful to collect safety data in real-world clinical settings. In this study, we applied postmarketing real-world data on a mechanistic model analysis for neutropenic profiles of eribulin in patients with recurrent or metastatic breast cancer. Demographic and safety data were collected using an active surveillance method from eribulin-treated recurrent or metastatic breast cancer patients. Changes in neutrophil counts over time were analyzed using a mechanistic pharmacodynamic model. Pathophysiological factors that might affect the severity of neutropenia were investigated, and neutropenic patterns were simulated for different treatment schedules. Clinical and laboratory data were collected from 401 patients (5199 neutrophil count measurements) who had not received granulocyte colony-stimulating factor and were eligible for pharmacodynamic analysis. The estimated mean parameters were as follows: mean transit time =\ua0104.5\ua0h, neutrophil proliferation rate constant =\ua00.0377\ua0h−1, neutrophil elimination rate constant =\ua00.0295\ua0h−1, and linear coefficient of drug effect =\ua00.0413\ua0mL/ng. Low serum albumin levels and low baseline neutrophil counts were associated with severe neutropenia. The probability of grade ≥3 neutropenia was predicted to be 69%, 27%, and 27% for patients on standard, biweekly, and triweekly treatment scenarios, respectively, based on virtual simulations using the developed pharmacodynamic model. In conclusion, this is the first application of postmarketing surveillance data to a model-based safety analysis. This analysis of safety data reflecting authentic clinical settings will provide useful information on the safe use and potential risk factors of eribulin

Significant effect of polymorphisms in CYP2D6 and ABCC2 on clinical outcomes of adjuvant tamoxifen therapy for breast cancer patients

Purpose The clinical efficacy of tamoxifen is suspected to be influenced by the activity of drug-metabolizing enzymes and transporters involved in the formation, metabolism, and elimination of its active forms. We investigated relationships of polymorphisms in transporter genes and CYP2D6 to clinical outcome of patients receiving tamoxifen. Patients and Methods We studied 282 patients with hormone receptor–positive, invasive breast cancer receiving tamoxifen monotherapy, including 67 patients who have been previously reported. We investigated the effects of allelic variants of CYP2D6 and haplotype-tagging single nucleotide polymorphisms (tag-SNPs) of ABCB1, ABCC2, and ABCG2 on recurrence-free survival using the Kaplan-Meier method and Cox regression analysis. Plasma concentrations of tamoxifen metabolites were measured in 98 patients receiving tamoxifen 20 mg/d. Results CYP2D6 variants were significantly associated with shorter recurrence-free survival (P = .000036; hazard ratio [HR] = 9.52; 95% CI, 2.79 to 32.45 in patients with two variant alleles v patients without variant alleles). Among 51 tag-SNPs in transporter genes, a significant association was found at rs3740065 in ABCC2 (P = .00017; HR = 10.64; 95% CI, 1.44 to 78.88 in patients with AA v GG genotypes). The number of risk alleles of CYP2D6 and ABCC2 showed cumulative effects on recurrence-free survival (P = .000000055). Patients carrying four risk alleles had 45.25-fold higher risk compared with patients with ≤ one risk allele. CYP2D6 variants were associated with lower plasma levels of endoxifen and 4-hydroxytamoxifen (P = .0000043 and .00052), whereas no significant difference was found among ABCC2 genotype groups. Conclusion Our results suggest that polymorphisms in CYP2D6 and ABCC2 are important predictors for the prognosis of patients with breast cancer treated with tamoxifen

Alteration of FHR pattern and cerebral metabolic rate of glucose of the fetus measured by positron emission tomography during progress of acidemia. The significance of overshoot acceleration in FHR

Peer Reviewe

Evaluation of the activity of CYP2C19 in Gujrati and Marwadi subjects living in Mumbai (Bombay)

BACKGROUND: Inherited differences in the metabolism and disposition of drugs, and genetic polymorphisms in the targets of drug therapy (e.g., receptors), can greatly influence efficacy and toxicity of medications. Marked interethnic differences in CYP2C19 (a member of the cytochrome P-450 enzyme superfamily catalyzing phase I drug metabolism) which affects the metabolism of a number of clinically important drugs have been documented. The present study evaluated the activity of CYP2C19 in normal, healthy Gujrati and Marwadi subjects by phenotyping (a western Indian population). METHODS: All subjects received 20 mg of omeprazole, which was followed by blood collection at 3 hrs to estimate the metabolic ratio of omeprazole to 5-hydroxyomeprazole. The analysis was done by HPLC. RESULTS: It was seen that 10.36% of this population were poor metabolizers(PM) whereas 89.63% were extensive metabolizers(EM). CONCLUSION: A genotyping evaluation would better help in identifying population specific genotypes and thus help individualize drug therapy