Treatment for advanced colorectal cancer (ACC) consists primarily of systemic treatment, mostly without curative intent. Systemic therapies are associated with potentially severe side effects.... Show moreTreatment for advanced colorectal cancer (ACC) consists primarily of systemic treatment, mostly without curative intent. Systemic therapies are associated with potentially severe side effects. Furthermore, treatment is not effective in all patients. Currently, pre-treatment predictors for efficacy and toxicity in systemic treatment of ACC are scarce. Germline genetic variation in genes encoding for enzymes involved in pharmacokinetics or pharmacodynamics of cytotoxic drugs could explain intra-patient differences in treatment effects. Pharmacogenetic studies aim at finding such germline genetic predictors. This thesis focusses on pharmacogenetics of capecitabine and oxaliplatin in treatment of ACC. First, it is established that results derived from DNA in archived tumor samples can be reliably compared to those using DNA from peripheral blood leukocytes. Then, germline genetic markers in MTHFR and MTRR, as well as markers derived from an in vitro genome-wide association study (GWAS) are tested for their association with capecitabine toxicity. Next, effects of ERCC1 genotype on oxaliplatin cytotoxicity in vitro and in clinical association analysis are addressed. The influence of genetic variation in organic cation transporters on oxaliplatin-induced neurotoxicity is examined. Lastly, the results of a GWAS searching for germline predictors of treatment efficacy of capecitabine, oxaliplatin and bevacizumab, with or without cetuximab, are presented. Show less
Aim of this thesis was to investigate pharmacogenetic effects on response to statin treatment and the genetics of lipid metabolism and cardiovascular disease. In chapter 4 the first results of the... Show moreAim of this thesis was to investigate pharmacogenetic effects on response to statin treatment and the genetics of lipid metabolism and cardiovascular disease. In chapter 4 the first results of the Genomic investigation of Statin Therapy (GIST) consortium are presented. We identified and validated two new GWAS loci to be associated with LDL-cholesterol response after statin treatment. In addition, we confirmed two previous identified loci. In chapter 5 we showed that we were not able to identify any loci associated with differential event reduction after statin therapy within the PROSPER study. The results presented in chapter 8 show that even at old age a genetic predisposition to high LDL-cholesterol is a risk factor for mortality. The results of this thesis show that currently the possibilities to personalize statin treatment based on genetic variants is limited. New research methods will hopefully give new opportunities to improve cardiovascular disease treatment and give more insight into the biological mechanisms of statin treatment. Show less
Model based approaches, integrating physiological parameters or linking exposure with response, are powerful tools to quantify and evaluate the impact of genetic differences that are reflected as... Show moreModel based approaches, integrating physiological parameters or linking exposure with response, are powerful tools to quantify and evaluate the impact of genetic differences that are reflected as variability of drug exposure and/or clinical response(s). This thesis __Pharmacogenomics in Drug Development: Implementation and Application of PKPD Model Based Approaches__ focused on genotype differences in explaining inter-individual variability in drug metabolism and clinical response. Population pharmacokinetic and pharmacodynamic models were developed to evaluate the relationship between exposure differences resulting from UGT2B15 genotype and their effects on both fasting plasma glucose and glycosylated haemoglobin for the type 2 diabetes drug, Sipoglitazar__. The model was used to quantify the optimal dose and regime (Single treatment/genotyped-based or titrated based upon response) for future clinical trials. Evaluating the potential impact of genetic differences early during development is important to appropriately design future clinical studies and to ensure that exposure response relationships for efficacy and safety can be identifed for all genetic subgroups. Ultimately, these model-based approaches can be used to determine if covariate-based dose individualization would be advantageous/beneficial to normalize exposure and minimize variability in clinical outcomes across heterogeneous clinical populations. Show less
