Interaction between gemcitabine and topotecan in human non-small-cell lung cancer cells: effects on cell survival, cell cycle and pharmacogenetic profile

The pyrimidine analogue gemcitabine is an established effective agent in the treatment of non-small-cell lung cancer (NSCLC). The present study investigates whether gemcitabine would be synergistic with the topoisomerase I inhibitor topotecan against the NSCLC A549 and Calu-6 cells. Cells were treated with gemcitabine and topotecan for 1 h and the type of drug interaction was assessed using the combination index (CI). Cell cycle alterations were analysed by flow cytometry, while apoptosis was examined by the occurrence of DNA internucleosomal fragmentation, nuclear condensation and caspase-3 activation. Moreover, the possible involvement of the PI3K-Akt signalling pathway was investigated by the measurement of Akt phosphorylation. Finally, quantitative, real-time PCR (QRT-PCR) was used to study modulation of the gemcitabine-activating enzyme deoxycytidine kinase (dCK) and the cellular target enzyme ribonucleotide reductase (RR). In results, it was found that simultaneous and sequential topotecan → gemcitabine treatments were synergistic, while the reverse sequence was antagonistic in both cell lines. DNA fragmentation, nuclear condensation and enhanced caspase-3 activity demonstrated that the drug combination markedly increased apoptosis in comparison with either single agent, while cell cycle analysis showed that topotecan increased cells in S phase. Furthermore, topotecan treatment significantly decreased the amount of the activated form of Akt, and enhanced the expression of dCK (+155.0 and +115.3% in A549 and Calu-6 cells, respectively), potentially facilitating gemcitabine activity. In conclusion, these results indicate that the combination of gemcitabine and topotecan displays schedule-dependent activity in vitro against NSCLC cells. The gemcitabine → topotecan sequence is antagonistic while drug synergism is obtained with the simultaneous and the sequential topotecan → gemcitabine combinations, which are associated with induction of decreased Akt phosphorylation and increased dCK expression

The human equilibrative nucleoside transporter 1 mediates in vitro cytarabine sensitivity in childhood acute myeloid leukaemia

Cytarabine (ara-C) is the most effective agent for the treatment of acute myeloid leukaemia (AML). Aberrant expression of enzymes involved in the transport/metabolism of ara-C could explain drug resistance. We determined mRNA expression of these factors using quantitative-real-time-PCR in leukemic blasts from children diagnosed with de novo AML. Expression of the inactivating enzyme pyrimidine nucleotidase-I (PN-I) was 1.8-fold lower in FAB-M5 as compared to FAB-M1/2 (P=0.007). In vitro sensitivity to deoxynucleoside analogues was determined using the MTT-assay. Human equilibrative nucleoside transporter-1 (hENT1) mRNA expression and ara-C sensitivity were significantly correlated (rp=−0.46; P=0.001), with three-fold lower hENT1 mRNA levels in resistant patients (P=0.003). hENT1 mRNA expression also seemed to correlate inversely with the LC50 values of cladribine (rp=−0.30; P=0.04), decitabine (rp=−0.29; P=0.04) and gemcitabine (rp=−0.33; P=0.02). Deoxycytidine kinase (dCK) and cytidine deaminase (CDA) mRNA expression seemed to correlate with in vitro sensitivity to gemcitabine (rp=−0.31; P=0.03) and decitabine (rp=0.33; P=0.03), respectively. The dCK/PN-I ratio correlated inversely with LC50 values for gemcitabine (rp=−0.45, P=0.001) and the dCK/CDA ratio seemed to correlate with LC50 values for decitabine (rp=−0.29; 0.04). In conclusion, decreased expression of hENT1, which transports ara-C across the cell membrane, appears to be a major factor in ara-C resistance in childhood AML

Adaptive Aggregation of Markov Chains: Quantitative Analysis of Chemical Reaction Networks

Quantitative analysis of Markov models typically proceeds through numerical methods or simulation-based evaluation. Since the state space of the models can often be large, exact or approximate state aggregation methods (such as lumping or bisimulation reduction) have been proposed to improve the scalability of the numerical schemes. However, none of the existing numerical techniques provides general, explicit bounds on the approximation error, a problem particularly relevant when the level of accuracy affects the soundness of verification results. We propose a novel numerical approach that combines the strengths of aggregation techniques (state-space reduction) with those of simulation-based approaches (automatic updates that adapt to the process dynamics). The key advantage of our scheme is that it provides rigorous precision guarantees under different measures. The new approach, which can be used in conjunction with time uniformisation techniques, is evaluated on two models of chemical reaction networks, a signalling pathway and a prokaryotic gene expression network: it demonstrates marked improvement in accuracy without performance degradation, particularly when compared to known state-space truncation techniques

Liraglutide and Renal Outcomes in Type 2 Diabetes.

BACKGROUND: In a randomized, controlled trial that compared liraglutide, a glucagon-like peptide 1 analogue, with placebo in patients with type 2 diabetes and high cardiovascular risk who were receiving usual care, we found that liraglutide resulted in lower risks of the primary end point (nonfatal myocardial infarction, nonfatal stroke, or death from cardiovascular causes) and death. However, the long-term effects of liraglutide on renal outcomes in patients with type 2 diabetes are unknown. METHODS: We report the prespecified secondary renal outcomes of that randomized, controlled trial in which patients were assigned to receive liraglutide or placebo. The secondary renal outcome was a composite of new-onset persistent macroalbuminuria, persistent doubling of the serum creatinine level, end-stage renal disease, or death due to renal disease. The risk of renal outcomes was determined with the use of time-to-event analyses with an intention-to-treat approach. Changes in the estimated glomerular filtration rate and albuminuria were also analyzed. RESULTS: A total of 9340 patients underwent randomization, and the median follow-up of the patients was 3.84 years. The renal outcome occurred in fewer participants in the liraglutide group than in the placebo group (268 of 4668 patients vs. 337 of 4672; hazard ratio, 0.78; 95% confidence interval [CI], 0.67 to 0.92; P=0.003). This result was driven primarily by the new onset of persistent macroalbuminuria, which occurred in fewer participants in the liraglutide group than in the placebo group (161 vs. 215 patients; hazard ratio, 0.74; 95% CI, 0.60 to 0.91; P=0.004). The rates of renal adverse events were similar in the liraglutide group and the placebo group (15.1 events and 16.5 events per 1000 patient-years), including the rate of acute kidney injury (7.1 and 6.2 events per 1000 patient-years, respectively). CONCLUSIONS: This prespecified secondary analysis shows that, when added to usual care, liraglutide resulted in lower rates of the development and progression of diabetic kidney disease than placebo. (Funded by Novo Nordisk and the National Institutes of Health; LEADER ClinicalTrials.gov number, NCT01179048 .)