Background: Drug resistance is a major problem in ovarian cancer. Triggering apoptosis using death ligands such as tumour necrosis factor-related apoptosis inducing ligand (TRAIL) might overcome chemoresistance. Methods: We investigated whether acquired cisplatin resistance affects sensitivity to recombinant human (rh) TRAIL alone or in combination with cisplatin in an ovarian cancer cell line model consisting of A2780 and its cisplatin-resistant subline CP70. Results: Combining cisplatin and rhTRAIL strongly enhanced apoptosis in both cell lines. CP70 expressed less caspase 8 protein, whereas mRNA levels were similar compared with A2780. Pre-exposure of particularly CP70 to cisplatin resulted in strongly elevated caspase 8 protein and mRNA levels. Caspase 8 mRNA turnover and protein stability in the presence or absence of cisplatin did not differ between both cell lines. Cisplatin-induced caspase 8 protein levels were essential for the rhTRAIL-sensitising effect as demonstrated using caspase 8 small-interfering RNA (siRNA) and caspase-8 overexpressing constructs. Cellular FLICE-inhibitory protein (c-FLIP) and p53 siRNA experiments showed that neither an altered caspase 8/c-FLIP ratio nor a p53-dependent increase in DR5 membrane expression following cisplatin were involved in rhTRAIL sensitisation. Conclusion: Cisplatin enhances rhTRAIL-induced apoptosis in cisplatin-resistant ovarian cancer cells, and induction of caspase 8 protein expression is the key factor of rhTRAIL sensitisation. © 2011 Cancer Research UK All rights reserved.
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Study goal: This study was carried out to answer the following research question: which motivation do healthy volunteers have to participate in phase I clinical trials? - Methods: A literature search was done through Google Scholar and Academic Search Premier, followed by three interviews with volunteers who had recently concluded their participation in a (non-commercial) phase I trial. - Results: Our literature search revealed mainly commercial motives for volunteers to participate in phase I clinical trials. The interviews (with volunteers in a non-commercial trial) showed that other factors may also play a decisive role, such as: (1) wish to support the investigator (2) wish to contribute to science, (3) access to more/better health care (4) sociability: possibility to relax and to communicate with other participants (5) general curiosity. Precondition is that risks and burden are deemed acceptable. - Conclusions: financial remuneration appears to be the predominant motive to participate voluntarily in a clinical trial. Other reasons were also mentioned however, such as general curiosity, the drive to contribute to science and the willingness to help the investigator. In addition, social reasons were given such as possibility to relax and to meet other people. Potential subjects state that they adequately assess the (safety) risks of participating in a trial as part of their decision process.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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