Anti-tumoral effect of the non-nucleoside DNMT inhibitor RG108 in human prostate cancer cells

Background: Current therapeutic strategies for advanced prostate cancer (PCa) are largely ineffective. Because aberrant DNA methylation associated with inappropriate gene-silencing is a common feature of PCa, DNA methylation inhibitors might constitute an alternative therapy. In this study we aimed to evaluate the anti-cancer properties of RG108, a novel non-nucleoside inhibitor of DNA methyltransferases (DNMT), in PCa cell lines. Methods: The anti-tumoral impact of RG108 in LNCaP, 22Rv1, DU145 and PC-3 cell lines was assessed through standard cell viability, apoptosis and cell cycle assays. Likewise, DNMT activity, DNMT1 expression and global levels of DNA methylation were evaluated in the same cell lines. The effectiveness of DNA demethylation was further assessed through the determination of promoter methylation and transcript levels of GSTP1, APC and RAR-β2, by quantitative methylation-specific PCR and RT-PCR, respectively. Results: RG108 led to a significant dose and time dependent growth inhibition and apoptosis induction in LNCaP, 22Rv1 and DU145. LNCaP and 22Rv1 also displayed decreased DNMT activity, DNMT1 expression and global DNA methylation. Interestingly, chronic treatment with RG108 significantly decreased GSTP1, APC and RAR-β2 promoter hypermethylation levels, although mRNA re-expression was only attained GSTP1 and APC. Conclusions: RG108 is an effective tumor growth suppressor in most PCa cell lines tested. This effect is likely mediated by reversion of aberrant DNA methylation affecting cancer related-genes epigenetically silenced in PCa. However, additional mechanism might underlie the anti-tumor effects of RG108. In vivo studies are now mandatory to confirm these promising results and evaluate the potential of this compound for PCa therapy.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.