Abstract 6869: Multi-omic profiling identified three molecular clusters in urothelial carcinoma: A path towards clinical precision.

Abstract Introduction: Urothelial carcinoma (UC) is a molecularly heterogeneous disease, and transcriptome-based classification systems have given important insights into its biology. The current consensus classifications for UC represent a major step toward biological stratification; however, its prognostic and predictive relevance remains uncertain, limiting use in clinical guidelines. Furthermore, most molecular schemes have been developed either for non-muscle invasive (NMIBC) or muscle-invasive disease (MIBC), relying only on bulk transcriptomic data. This fragmentation hinders comparability across studies and integration with proteomic or single-cell datasets. A simplified molecular framework is therefore needed to capture UC heterogeneity more comprehensively and to support personalized therapeutic approaches. Materials & Methods: Using the TCGA bulk bladder cancer transcriptome dataset, we developed three distinct molecular UC clusters, which were validated using 18 transcriptome, 3 proteome and 33 UC cell line datasets. Making use of in silico predictions, we selected promising treatment strategies, which were further screened in vitro using the IncucyteS3 live-cell imaging system and RNA-sequencing on representative cell lines. Results: Our transcriptomic and proteomic analyses revealed three UC clusters with distinct molecular, biological and clinical features. Each cluster showed specific mRNA and protein expression patterns, metabolic profiles, and driver gene alterations, translating into divergent prognoses and predicted therapeutic sensitivities. Novel approaches, like liquid biopsy-based stratification using ECM-derived urinary peptides or IHC-based profiling of the proposed distinct markers, are currently being investigated. The stroma-rich, high-risk cluster #1 was associated with responsiveness to ferroptosis inducers and PARP inhibition. Cluster #2, which is highly proliferative and immune-infiltrated with basal/squamous traits, showed predicted benefit from cytotoxic agents and inhibition of EGFR or MEK signaling pathways. Cluster #3, dominated by luminal papillary, low-risk tumors with minimal stromal and immune components, appeared susceptible to epigenetic therapies and EGFR/FGFR inhibition. Conclusion: Our new integrative molecular classification scheme provides a practical framework for patient stratification, personalized transcriptome- and proteome-based risk assessment, preclinical research and clinical trial design, including both NMIBC and MIBC. Citation Format: Nils Cornelis van Creij, Piotr Tymoszuk, Florian Handle, Andreas Seeber, Teresa Sellemond, Agnieszka Martowicz, Eva Compérat, Hamed Wafa, Steffen Ormanns, Michael Günther, Walther Parson, Maxim Noeparast, Frederic Romain Santer, Jose Daniel Subiela, Petros Grivas, Roger Li, Zoran Culig, Renate Pichler. Multi-omic profiling identified three molecular clusters in urothelial carcinoma: A path towards clinical precision [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6869.

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Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-6869
Primary Topic
Bladder and Urothelial Cancer Treatments
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article

Abstract 6869: Multi-omic profiling identified three molecular clusters in urothelial carcinoma: A path towards clinical precision.

Zoran Čulig, Steffen Ormanns, Agnieszka Martowicz, Piotr Tymoszuk et al.
Cancer Research
Bladder and Urothelial Cancer Treatments
article

Abstract 6869: Multi-omic profiling identified three molecular clusters in urothelial carcinoma: A path towards clinical precision.

Zoran Čulig, Steffen Ormanns, Agnieszka Martowicz, Piotr Tymoszuk, Frédéric R. Santer, Hamed Wafa, Florian Handle, Éva Compérat, Amir Noeparast, Andreas Seeber, Michael Günther, Teresa Sellemond, Walther Parson, Nils Cornelis van Creij, Petros Grivas, Roger Li, Jose Daniel Subiela, Renate Pichler
article en

Abstract

Abstract Introduction: Urothelial carcinoma (UC) is a molecularly heterogeneous disease, and transcriptome-based classification systems have given important insights into its biology. The current consensus classifications for UC represent a major step toward biological stratification; however, its prognostic and predictive relevance remains uncertain, limiting use in clinical guidelines. Furthermore, most molecular schemes have been developed either for non-muscle invasive (NMIBC) or muscle-invasive disease (MIBC), relying only on bulk transcriptomic data. This fragmentation hinders comparability across studies and integration with proteomic or single-cell datasets. A simplified molecular framework is therefore needed to capture UC heterogeneity more comprehensively and to support personalized therapeutic approaches. Materials & Methods: Using the TCGA bulk bladder cancer transcriptome dataset, we developed three distinct molecular UC clusters, which were validated using 18 transcriptome, 3 proteome and 33 UC cell line datasets. Making use of in silico predictions, we selected promising treatment strategies, which were further screened in vitro using the IncucyteS3 live-cell imaging system and RNA-sequencing on representative cell lines. Results: Our transcriptomic and proteomic analyses revealed three UC clusters with distinct molecular, biological and clinical features. Each cluster showed specific mRNA and protein expression patterns, metabolic profiles, and driver gene alterations, translating into divergent prognoses and predicted therapeutic sensitivities. Novel approaches, like liquid biopsy-based stratification using ECM-derived urinary peptides or IHC-based profiling of the proposed distinct markers, are currently being investigated. The stroma-rich, high-risk cluster #1 was associated with responsiveness to ferroptosis inducers and PARP inhibition. Cluster #2, which is highly proliferative and immune-infiltrated with basal/squamous traits, showed predicted benefit from cytotoxic agents and inhibition of EGFR or MEK signaling pathways. Cluster #3, dominated by luminal papillary, low-risk tumors with minimal stromal and immune components, appeared susceptible to epigenetic therapies and EGFR/FGFR inhibition. Conclusion: Our new integrative molecular classification scheme provides a practical framework for patient stratification, personalized transcriptome- and proteome-based risk assessment, preclinical research and clinical trial design, including both NMIBC and MIBC. Citation Format: Nils Cornelis van Creij, Piotr Tymoszuk, Florian Handle, Andreas Seeber, Teresa Sellemond, Agnieszka Martowicz, Eva Compérat, Hamed Wafa, Steffen Ormanns, Michael Günther, Walther Parson, Maxim Noeparast, Frederic Romain Santer, Jose Daniel Subiela, Petros Grivas, Roger Li, Zoran Culig, Renate Pichler. Multi-omic profiling identified three molecular clusters in urothelial carcinoma: A path towards clinical precision [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6869.

Cancer ResearchVol. 86(7_Supplement)
Technische Hochschule Augsburg (DE), University of Augsburg (DE), Universität Innsbruck (AT), University of Washington (US), Moffitt Cancer Center (US), Tirol Kliniken (AT), Alpine Quantum Technologies (Austria) (AT), Hospital Universitario Ramón y Cajal (ES), Medical University of Vienna (AT)
Good health and well-being
Openalex Percentile: Top 29%
Bladder and Urothelial Cancer Treatments
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