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

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

Research output: Contribution to journalArticlepeer-review

161 Scopus citations

Abstract

The 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.

Original languageEnglish (US)
Article number2301
JournalNature communications
Volume12
Issue number1
DOIs
StatePublished - Dec 1 2021

All Science Journal Classification (ASJC) codes

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

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