Although anti-cancer treatments have significantly advanced over the past decades, obstacles to accomplishing successful treatment still exist. The occurrence of treatment resistance is one of the... Show moreAlthough anti-cancer treatments have significantly advanced over the past decades, obstacles to accomplishing successful treatment still exist. The occurrence of treatment resistance is one of the major factors that limit the long-lasting efficacy of anti-cancer treatment. Additionally, substantial variability in pharmacokinetics (PK) / pharmacodynamics (PD) of anti-cancer drugs also challenges successful oncology treatment. Therefore, gaining knowledge of and ultimately better suppressing evolutionary resistance development during treatment, and applying personalized treatment are desired to improve anti-cancer treatment. In this thesis, we have applied quantitative modeling approaches to address these needs, aiming for improved treatment for oncology patients. Our work demonstrated that with the quantitative models, the evolutionary progression of tumors could be characterized and predicted, accounting for interactions among heterogeneous tumor cells and supported by mutant gene variants detected in circulating tumor DNA (ctDNA). In addition, we developed population PK /PD models which enabled quantitative description of the PK and PD of anti-cancer drugs and corresponding variabilities in real-world patients. The developed models have been further applied to support the identification of optimal treatment strategies and guide individualized treatment for oncology patients. Show less
In this thesis, different preclinical strategies were explored aiming at the identification of putative novel therapies for prostate and bladder cancer. The first part of this thesis (Chapter 2 and... Show moreIn this thesis, different preclinical strategies were explored aiming at the identification of putative novel therapies for prostate and bladder cancer. The first part of this thesis (Chapter 2 and Chapter 3) describes the generationof preclinical, patient-derived model systems of prostate and bladder cancer. In Chapter 2, an overview is provided of the most commonly used patient-derived model systems for urological tumors, and a framework on how these patient derived tumor models can be employed to address preclinical and clinical unmet needs is presented. In Chapter 3, we developed and optimized the culture of ex vivo tumor tissue slices and employed this model to detect anti-tumor responses of chemotherapeutic agents Docetaxel and Gemicitabin. Subsequently in Chapters 4, 5 and 6, we describe the use of multiple preclinical translational models, including patient-derived tumor models. In Chapter 4 and 5 the translational potential of the approved antipsychotic drug penfluridol was determined in bladder and prostate cancer. In Chapter 6, the use of oncolytic reovirus jin-3 as putative novel therapeutic strategy for the treatment of prostate is investigated. Finally, in Chapter 7, we describe a novel preclinical screening strategy based on E-cadherin (re)induction and inhibition of invasion for the identification of a new class of small molecules for the treatment of aggressive epithelial cancers. Show less
Sunitinib treatment requires a personalized approach, since patients can respond very differently to this drug. Pharmacogenetics may improve our ability to provide a tailored therapy by studying... Show moreSunitinib treatment requires a personalized approach, since patients can respond very differently to this drug. Pharmacogenetics may improve our ability to provide a tailored therapy by studying how genetic variations could influence drug response. The objective of this thesis was to find genetic markers that can predict toxicity and efficacy of sunitinib in patients with metastatic renal cell carcinoma. This research builds upon previous findings from candidate gene studies by testing a selection of SNPs based on plausible involvement in pharmacokinetics or pharmacodynamics of the drug of interest. We observed that SNPs located in genes involved in metabolism and drug absorption (CYP3A4, CYP3A5, and ABCB1) are potentially associated with the clearance of sunitinib and its active metabolite. In analogy to this, we confirmed SNP associations from previous studies for SNPs in CYP3A5 and ABCB1 that predict the need for dose reductions and improvement of PFS on sunitinib. Sunitinib-induced toxicity is possibly related to SNPs in CYP3A4 and CYP3A5, and in interleukin genes IL8 and IL13. VEGFR-2 (KDR) rs34231037 G-allele variant carriers were potentially associated with a favorable response to sunitinib. A GWAS learned us that SNPs in chromosome 21 are involved in sunitinib efficacy, probably by influencing drug resistance mechanisms. Show less
