An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer

Author:

Lindskrog Sia ViborgORCID,Prip Frederik,Lamy PhilippeORCID,Taber AnnORCID,Groeneveld Clarice S.ORCID,Birkenkamp-Demtröder KarinORCID,Jensen Jørgen Bjerggaard,Strandgaard Trine,Nordentoft IverORCID,Christensen EmilORCID,Sokac Mateo,Birkbak Nicolai J.ORCID,Maretty Lasse,Hermann Gregers G.,Petersen Astrid C.,Weyerer Veronika,Grimm Marc-Oliver,Horstmann Marcus,Sjödahl GottfridORCID,Höglund Mattias,Steiniche Torben,Mogensen Karin,de Reyniès Aurélien,Nawroth Roman,Jordan Brian,Lin Xiaoqi,Dragicevic Dejan,Ward Douglas G.,Goel Anshita,Hurst Carolyn D.,Raman Jay D.,Warrick Joshua I.ORCID,Segersten Ulrika,Sikic Danijel,van Kessel Kim E. M.,Maurer Tobias,Meeks Joshua J.,DeGraff David J.,Bryan Richard T.,Knowles Margaret A.,Simic Tatjana,Hartmann Arndt,Zwarthoff Ellen C.,Malmström Per-Uno,Malats NúriaORCID,Real Francisco X.ORCID,Dyrskjøt LarsORCID

Abstract

AbstractThe molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.

Funder

L.D. is supported by the following funding sources: Aarhus University, The Danish Cancer Biobank, The Danish Cancer Society.

Publisher

Springer Science and Business Media LLC

Subject

General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry

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