Abstract 5138: Proteomic analyses of the urothelial cancer landscape reveal highly distinct prognostic and predictive subtypes
Authors: Dressler Franz Friedrich , Diedrichs Falk , Sabtan Deema , Hinrichs Sofie , Mackedanz Paulina , Schlotfeldt Mareile , Krisp Christoph , Hennig Martin , Schlueter Hartmut , Wetterauer Ulrich , Zubarev Roman , Horst David , Perner Sven , Wolf Philipp , Végvári Ákos 
Published: March 2024

Introduction: Urothelial cancer (UC) is a challenging disease with a wide tumor-biological spectrum. Most molecular classifications cover only muscle-invasive bladder cancer and are transcriptome-based, relating only indirectly to the therapeutically relevant and more stable protein level. Also, the recent introduction of antibody-drug conjugates (ADCs) requires quantitative data about the tumor specificity of their target proteins. We turned to the proteome to address these questions.

Methods: We performed deep proteomic profiling of a comprehensive cohort by optimized tandem mass tag-labelled liquid chromatography-coupled tandem mass spectrometry. Data acquisition was validated internally with immunoblotting and externally by bioinformatic reclassification within existing, filtered transcriptomic data. After bioinformatics, the top cluster defining proteins were quantified immunohistochemically under real-world conditions. Protein profiles were individualized and separately evaluated with drug repurposing libraries. Cell viability assays were performed for a panel of twelve UC cell lines to validate these predictions in vitro.

Results: We analyzed 434 samples with 242 tumors and 192 paired normal mucosae, covering all stages of UC. 9542 proteins were quantified and revealed five distinct proteomic subtypes. These were validated internally and externally, showing relevant survival stratification also in the TCGA dataset. The proteomic subtypes were independent from pathological groups with relevant stratification of progression- free and overall survival (low vs. high-risk: median 103 vs. 27 months). Tumor specificity of all proteins was highly heterogeneous across stages and subtypes. As an example, the ADC target NECTIN4 was generally overexpressed mainly in non-muscle-invasive UC. Drug repurposing revealed several new candidate drugs, each specific to different proteomic subtypes. In vitro data showed increased sensitivity by subtype in line with four out of seven representative predictions.

Conclusions: Proteomic subtypes add independent prognostic information and carry predictive value for several newly identified adjuvant drug candidates. The actual tumor specificity of biomarkers and ADC targets is highly dependent on stage and subtype and calls for individualized patient-specific predictive testing.

Citation Format: Franz Friedrich Dressler, Falk Diedrichs, Deema Sabtan, Sofie Hinrichs, Paulina Mackedanz, Mareile Schlotfeldt, Christoph Krisp, Martin Hennig, Hartmut Schlueter, Ulrich Wetterauer, Roman Zubarev, David Horst, Sven Perner, Philipp Wolf, Ákos Végvári. Proteomic analyses of the urothelial cancer landscape reveal highly distinct prognostic and predictive subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5138.