Adjuvant Therapeutics for Advanced Urothelial Cancer Control

• Applicant: Dr. Franz Friedrich Dreßler
• Subject Area: Reproductive Medicine, Urology ; Pathology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 567893136

Urothelial bladder cancer (UC) is a clinically challenging disease due to a wide tumor biological spectrum with rapid progression. Bladder-preserving and optimized management of high-risk and intermediate-stage tumors requires adjuvant instillation therapy, with only few options currently available. Since these therapeutics are effective only in few patients and with limited predictive stratification and efficacy of current instillation schemes, new predictive and therapeutic approaches are necessary. Based on multi-level method development and optimization, systematic drug repurposing for a large, all-stage comprehensive cohort of 180 samples was performed based on robust effector-level proteomic signatures. With frequently reoccurring predictions across these independent samples, four new subtype-specific drug candidates of different molecular mechanisms were successfully validated in vitro. With a cohort of primary patient tissue, cells and in ovo xenograft tumoroids, extensive functional characterization and proteogenomic contextualization will pave the way to clinical testing and optimal patient selection. To match trait and treatment, proteomic assays provide quantitative measurements of cellular effectors, which we used to identify highly robust prognostic and predictive UC subtypes. These will further be validated and refined in the current project proposal. Translating back to the individual patient, the proposed work will comprehensively characterize new candidate drugs for the personalized adjuvant therapy of UC and prepare their clinical application. To better tailor and expand the therapeutic repertoire, the proteogenomic, transcriptional and functional environment will extensively be contextualized. Together, this will enable further clinical testing and optimized patient selection through predictive diagnostics.

• DFG Programme: Research Grants
• Co-Investigators: Dr. Annika Fendler; Dr. Bianca Nitzsche