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Abstract

Pharmacogenomics (PGx) investigates how genetic factors influence the effects and side effects of drugs. Recently, however, PGx has moved beyond the genome and aims at also accounting for epigenetic and transcriptomic variation to further study differences in drug response between patients. Typically, PGx is mainly concerned with germline variation in pharmacogenes, encoding drug-metabolizing enzymes and transporters, that influence pharmacokinetics and drug metabolism. In contrast, somatic variation has so far been studied almost exclusively in drug target genes. In this thesis, the genomic, epigenetic, and transcriptomic variation of 60 selected pharmacogenes was analyzed based on germline DNA sequencing, tumor DNA and RNA sequencing, and tumor methylation profiling. The data was derived from matched tumor and germline control samples of 2,371 cancer patients suffering from rare or advanced cases of cancers that have already undergone all standard lines of treatment. The focus of this thesis was especially on somatic variation and its effects on pharmacokinetics in the tumor, which has so far been neglected in pharmacogenomic research but has already been hypothesized repeatedly as a potential mechanism for the development of drug resistance in tumors. First, a comprehensive and efficient in-silico PGx analysis pipeline was developed. Germline samples were analyzed for star-allele genotypes and phenotypes based on known functional single nucleotide polymorphisms and copy number variants. The pipeline was also integrated into a molecular tumor board workflow providing PGx recommendations. In addition, rare variants in the germline of these patients, and their functional effect were assessed using variant effect prediction tools. These rare variants were integrated into the germline PGx profiles which showed that they can superimpose on the phenotypes derived solely from star alleles. Comprehensive PGx analyses were also carried out for the tumor samples. The results showed that in rare cases somatic variants at star-allele positions can change the genotype between tumor and matched control sample. However, a large part of somatic variation of the pharmacogenes included copy number aberrations. Analyses of the expression in the tumor samples revealed that some (especially phase II genes and transporters) are expressed in multiple tumor types. In addition, the expression of some genes was strongly associated with the copy number aberrations while for others methylation seems to be the major regulating factor. Finally, a combined multivariate analysis of all the aforementioned data levels was done to assess the proportion of variance explained in tumor gene expression.