Patient-derived organoids to investigate drug response and treatment resistance mechanisms in prostate cancer

Servant, Raphaëlle. Patient-derived organoids to investigate drug response and treatment resistance mechanisms in prostate cancer. 2023, Doctoral Thesis, University of Basel, Faculty of Science.

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Prostate cancer (PCa) is one of the most diagnosed cancers in men worldwide. While the 5-year survival rate of local PCa is around 99%, it drops to 32% for metastasized PCa. Understanding the molecular mechanisms driving treatment failure and disease progression is key to developing new treatment strategies and improve the outcome of PCa patients. Relevant models of PCa are urgently needed to address these clinical challenges. In this context, my PhD project aimed at leveraging patient-derived organoid models and novel imaging technologies to study drug response and treatment resistance in advanced prostate cancer.
Chapter I of this thesis is dedicated to the development of 3D patient-derived organoid models. We exploited a large and diverse cohort of PCa to investigate determinants of organoid derivation success. Short-term organoid models exhibit molecular features of the tumor and are relevant models to test drug response in vitro.
Additionally, we have derived two new patient-derived organoid xenograft (PDOX) models of advanced PCa, described in Chapter II. Phenotypic, genomic, and transcriptomic features of the models were leveraged to study mechanisms driving response to androgen deprivation and castration-resistance and test anti-cancer drugs in vitro.
Finally, deciphering tumor cellular complexity and its effects on treatment response could help riskstratify patients and adjust therapy to improve the patient’s survival. In Chapter III, we describe the initial efforts to apply the CODEX imaging technology to PCa tissues, with the aim to identify cellular populations and patterns associated with androgen-deprivation therapy failure.
Taken together, this thesis highlights the importance of establishing novel modeling and imaging tools to study treatment response and resistance mechanisms in PCa.
Advisors:Bubendorf, Lukas
Committee Members:Odermatt, Alex and Metzger, Daniel
Faculties and Departments:03 Faculty of Medicine > Bereich Querschnittsfächer (Klinik) > Pathologie USB > Stammzellpathologie (Bubendorf)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Querschnittsfächer (Klinik) > Pathologie USB > Stammzellpathologie (Bubendorf)
05 Faculty of Science > Departement Pharmazeutische Wissenschaften > Pharmazie > Molecular and Systems Toxicology (Odermatt)
UniBasel Contributors:Bubendorf, Lukas and Odermatt, Alex
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:15208
Thesis status:Complete
Number of Pages:VII, 163
Identification Number:
  • urn: urn:nbn:ch:bel-bau-diss152088
edoc DOI:
Last Modified:09 Dec 2023 05:30
Deposited On:08 Dec 2023 09:33

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