Kidney transplantation is the preferred treatment of patients with end stage renal disease, as it provides longer patient survival and better quality of life compared to dialysis. Prediction of... Show moreKidney transplantation is the preferred treatment of patients with end stage renal disease, as it provides longer patient survival and better quality of life compared to dialysis. Prediction of DGF, response to steroid resistant rejection and long-term graft outcome remain difficult when using merely clinical parameters. Numerous studies have reported on the predictive value of molecular markers for AR and worse graft outcome. However, the heterogeneity of AR and the variation among transplant centers leads to controversial results and preclude a more general clinical application. In the first part of this thesis, we aimed to investigate the molecular markers of steroid resistance and long-term graft survival on the basis of acute rejection biopsies. In the second part, we focused on genetic variants associated with acute rejection in kidney transplantation. In the final part we described the possible immune regulatory effect of S100 calcium binding proteins. Show less
Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand... Show moreBackground: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e. g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows.Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?".Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.Availability: The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/ro Show less
Even though treatment of several types of solid tumors has improved in the past few years with the introduction of the monoclonal antibodies against the epidermal growth factor receptor (EGFR) and... Show moreEven though treatment of several types of solid tumors has improved in the past few years with the introduction of the monoclonal antibodies against the epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF), the clinical benefit of these targeted therapies is modest. Pharmacogenetics has the potential to select patients with higher chance of response to agents that target these pathways. In the thesis, we describe the association of the FCGR3A Phe158Val polymorphism with progression-free survival in advanced colorectal cancer patients treated with cetuximab added to chemotherapy and bevacizumab. Following this finding, we found that cetuximab activates type 2 macrophages, which could have a negative effect on the clinical efficacy of cetuximab. Furthermore, we detected a genetic interaction profile consisting of the VEGF +405G>C and TYMS TSER polymorphisms, that was associated with the efficacy of capecitabine, oxaliplatin and bevacizumab in advanced colorectal cancer patients. Finally, we performed a genome wide association study with the same treatment, in which polymorphisms in the proximity of the AGPAT5 gene were associated with progression-free survival Show less
