
Diverse, well-characterised models to advance discovery and translational impact in bladder cancer
The UM-UC cell line collection brings together 11 patient-derived urothelial carcinoma cell lines (UM-UC-1 through to UM-UC-14), originally developed by Prof. H. Barton Grossman and Dr. Anita Sabichi at the University of Michigan.
Each cell line originates from a different patient, capturing the heterogeneity of bladder cancer and making the collection a robust, reliable tool to support meaningful discoveries and translational progress.
Why the UM-UC panel matters

The UM-UC panel has been extensively characterised in peer-reviewed literature (1-3), providing trusted data to support confident experimental design. These patient-derived cell lines offer:
- Diverse patient representation: Capturing a broad spectrum of genetic and clinical backgrounds, the panel reflects the real-world complexity and biology of bladder cancer.
- Tumorigenicity data: Enabling translational research by supporting in vivo modelling, mechanism-of-action studies, and validation of therapeutic targets and biomarkers.
- Suitability for adenovirus-mediated gene transfer: Facilitating model adaptation and functional studies of specific genes of interest through efficient gene delivery.
Collated Insights for Confident Research

To support your decision-making, we have collated essential data on each cell line, providing a clear overview of their genomic and phenotypic characteristics, helping you select the right model for your studies.
By scientists for scientists, the UM-UC cell line panel was developed to provide a trusted, ready-to-use resource for advancing bladder cancer research. Bringing together 11 well-studied, patient-derived cell lines into a single panel, it offers a powerful tool for reliable, reproducible, and meaningful results.
References
- Sabichi et al. 2006. J Urol. 175(3 Pt 1):1133-7. PMID: 16469639
- Earl et al. 2015. BMC genomics, 16(1), 403. PMIDP: 25997541
- Zuiverloon et al. 2018. Bladder Cancer, Apr 26;4(2):169-183, PMID: 29732388
