The aim of this study is to develop a novel personalized post-surgical therapy concept using tailor-made Auger-e‒-emitting PSMA ligands. The proposed concept is thought to provide a specific class of prostate cancer patients, characterized by localized disease, but high risk of relapse after surgery, with a better long-term prognosis.
With this proposal we aim at achieving a critical step towards a personalized approach of prostate cancer treatment by means of PSMA-targeting using non-standard radionuclides for post-surgical eradication of surviving cancer cells. It is expected that after this PhD thesis, it is known (i) whether PSMA is a valid tumor target for this specific class of patients, (ii) whether it is possible to achieve PSMA targeting followed by shuttling the radioligand into the cellular nucleus and, (iii) whether Auger-e‒-emitting radionuclides would be more suited than pure β‒- particle emitters to effectively kill these cancer cells. Most importantly, it will be known (iv) whether post-surgical Auger-e‒ therapy can reduce the cases of relapse after removal of the primary tumor mass based on the in vitro/ex vivo and in vivo data obtained in diverse personalized preclinical models including organoids, tissue cultures and patient-derived xenograft (PDX)-models.
Prostate cancer is the most frequently diagnosed malignancy and second leading cause of cancer-specific deaths in men in Western countries. Prostate cancer manifestations can vary from indolent localized tumors to widespread metastases. The prostate-specific membrane antigen (PSMA) evolved as a very promising protein for targeting with radioactive ligands, a therapy concept currently implemented at many sites worldwide for patients with metastatic disease. The question arises on whether PSMA-targeted radionuclide therapy using Auger-e–emitting radionuclides could be employed for patients with localized disease, enabling post-surgical killing of surviving cancer cells and, hence, increase the prognosis of this specific class of prostate cancer patients.
