ArticleFrontiers in oncology2025
Comprehensive molecular profiling of urologic tumors presented in a molecular tumor board: insights from a real-world precision oncology cohort.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: Molecular tumor boards (MTBs) have become an integral component of precision oncology, yet data on their real-world impact in urologic cancers are limited. This study aimed to characterize the molecular landscape of urologic malignancies presented to the MTB at the University Medical Center Freiburg and to evaluate the frequency and clinical relevance of genomic alterations across tumor entities. Methods: We retrospectively analyzed 118 patients with histologically confirmed urologic tumors presented at the Freiburg MTB between Januar 2019 and December 2024. Comprehensive molecular profiling was performed using next-generation sequencing (TruSight Oncology 500 or whole exome sequencing). Data were analyzed for mutation frequency, tumor mutational burden (TMB), and co-occurrence patterns, and integrated with clinical data to guide therapy recommendations. Results: Somatic mutations were identified in 90.6% of cases. Frequent alterations included TP53, BRCA2, KMT2D, and ATM, with DNA damage response and chromatin remodeling pathways commonly affected. Prostate cancers showed high rates of BRCA2 and APC co-mutations, indicating potential benefit from combined PARP and Wnt-targeted therapies. In bladder and upper tract urothelial carcinomas (UTUC), KMT2C co-occurred with genes such as SPTA1 and LRP1B, suggesting a hypermutated, immunoresponsive phenotype. Renal tumors frequently harbored alterations in VHL, PBRM1, and SETD2. Rare entities such as penile and testicular tumors displayed distinct mutation patterns, including BRCA1/2 and MMR gene alterations. Conclusions: Comprehensive molecular profiling in a MTB setting reveals distinct and therapeutically relevant mutational patterns across urologic cancers. These data support the integration of MTBs into clinical workflows and highlight the potential of co-mutational signatures to guide personalized treatment strategies.
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