Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND AND OBJECTIVE: Muscle-invasive bladder cancer (MIBC) is a biologically heterogeneous disease with variable prognosis after radical cystectomy. While conventional clinicopathological parameters offer limited prognostic value, growing evidence highlights the role of the tumor immune microenvironment (TIME)-including immune cell composition and spatial architecture-as robust biomarkers for disease progression and outcomes. METHODS: The study included 251 consecutive patients with MIBC who underwent cystectomy (2004-2014, LMU Munich). Three 1-mm-diameter cores were sampled from the tumor invasive front and center in the cystectomy specimen. Six immune checkpoint proteins (ICPs; IDO, PD-L1, PD-1, LAG-3, TIM-3, and VISTA) were quantified digitally following immunohistochemical (IHC) staining. ICP-positive immune and tumor cells were stratified and densities were hierarchically clustered. Multivariable Cox models were then used to assess the association with overall (OS) and disease-free survival. The minimum tumor sample count needed to detect the maximum ICP expression per patient was estimated via a 1000-fold bootstrap resampling simulation. KEY FINDINGS AND LIMITATIONS: immune cells, while four cores were required for all other markers. ICP-based clustering revealed three TIME subtypes (CID1-3), of which CID3 was associated with markedly worse prognosis (median OS 18.5 vs 100.5 mo; p = 0.0007). This classification outperformed Union for International Cancer Control staging and improved patient stratification in late-stage MIBC. CONCLUSIONS AND CLINICAL IMPLICATIONS: A six-marker, multiregional ICP panel delivers a robust, stage-independent, actionable risk stratification in MIBC. At least four biopsies are advised for routine immune profiling; further longitudinal external validation is warranted.
Source: European Urology Oncology
Authors: Nadia Jurczok, Gabriel Dernbach, Benedikt Ebner, Henning Plage, Mihnea P. Dragomir, Philipp Keyl, Julika Ribbat-Idel, Evelyn Ramberger, Florian Roßner, Alexander Quaas, Guido Sauter, Thorsten Schlomm, Frederick Klauschen, Christian Stief, David Horst, Gerald Bastian Schulz, Marie-Lisa Eich, Simon Schallenberg
Institutions: Charité - Universitätsmedizin Berlin, Berlin Institute for the Foundations of Learning and Data, LMU Klinikum, Ludwig-Maximilians-Universität München, Humboldt-Universität zu Berlin, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Pathologisches Institut, University of Cologne, University Hospital Cologne, University Medical Center Hamburg-Eppendorf
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,790
Awards: G5307159553, G6986424208
OpenAlex ID: W7117588976
