bioRxivCancer Biology
Molecular characterization reveals genomic and transcriptomic subtypes of metastatic urothelial carcinoma
J. A. Nakauma-Gonzalez, M. Rijnders, J. van Riet, M. S. van der Heijden, J. Voortman, E. P. J. G. Cuppen, N. Mehra, S. van Wilpe, S. F. Oosting, L. L. Rijstenberg, H. M. Westgeest, E. Zwarthoff, R. de Wit, A. A. M. van der Veldt, H. J. G. van de Werken, M. P. J. Lolkema, J. L. Boormans
Abstract
BackgroundMolecular characterization of primary urothelial carcinoma (UC) revealed molecular subtypes with different genomic, transcriptomic, and clinicopathological characteristics, which might guide therapeutic decision making. A comprehensive molecular characterization of metastatic UC (mUC), however, is currently lacking in the literature. Because of the lethality of mUC, with few therapeutic options available for patients, a multi-omics characterization of mUC could aid to improve patient selection for new and existing therapies. MethodsTo define the molecular landscape of mUC and to identify potential targets for therapy, we performed whole genome DNA sequencing on fresh-frozen metastatic tumor biopsies of 116 mUC patients, and mRNA sequencing on 90 matched biopsies. ResultsHierarchical clustering based on mutational signatures revealed two major genomic subtypes. The most prevalent subtype (67%) consisted almost exclusively of tumors with high APOBEC mutagenesis. APOBEC mutagenesis was detected in 91% of the samples, and appeared to be an ongoing process in mUC based on analysis of eight patients from whom serial biopsies were obtained during treatment. Contrary to the overall distribution of mutations, APOBEC associated mutations occurred throughout the genome, and independently of predicted accessible or transcribed genomic regions, suggesting that these mutations were generated during replication. Transcriptomic analysis revealed five mRNA-based subtypes: two luminal subtypes (40%), a stroma-rich (24%), basal/squamous (23%), and non-specified subtype (12%). The transcriptomic subtypes were different regarding driver gene alterations (e.g. ELF3 and TSC1), gene amplifications (NECTIN4 and PPARG), pathway activity, and immune cell infiltration. By integrating the genomic and transcriptomic data, potential therapeutic options per transcriptomic subtype and individual patient were proposed. ConclusionsThis study expands our knowledge on the molecular landscape of mUC, and serves as a reference for subtype-oriented and patient-specific research on the etiology of mUC, and for novel drug development. Trial registrationThe mUC cohort studied here is part of the Netherlands nationwide study of the center for personalized cancer treatment consortium (CPCT-02 Biopsy Protocol, NCT01855477), and the Drug Rediscovery Protocol (DRUP Trial, NCT02925234).
- organism: human
- assay: whole-genome sequencing
- assay: bulk RNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- The evolution of genomic, transcriptomic, and single-cell protein markers of metastatic upper tract urothelial carcinoma
K. Ohara, A. F. Rendeiro, … J. M. Mosquera·bioRxiv·Nov 16, 2021
- Mutational signatures in upper tract urothelial carcinoma define etiologically distinct subtypes with prognostic relevance
Xuesong Li, Huan Lü, … Weimin Ci·bioRxiv·Aug 15, 2019
- Integrated molecular and pharmacological characterization of patient-derived xenografts from bladder and ureteral cancers identifies new potential therapies.
H. Lang, C. Beraud, … T. Massfelder·Frontiers in OncologyPeer-reviewed·Aug 11, 2022
- Frequency and Characterization of Rare Histologic Subtypes in Canine Invasive Urothelial Carcinoma
Megan P. Corbett, Mohamed Elbadawy, … Karin Allenspach·bioRxiv·May 13, 2025
- Molecular profiling of driver events and tumor-infiltrating lymphocytes in metastatic uveal melanoma
J. Karlsson, L. M. Nilsson, … J. A. Nilsson·bioRxiv·Aug 21, 2019
- A versatile and upgraded version of the LundTax classification algorithm applied to independent cohorts
Elena Aramendía Cotillas, Carina Bernardo, … Pontus Eriksson·Journal of Molecular DiagnosticsPeer-reviewed·Sep 24, 2024