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

Lindskrog, Sia Viborg ; Prip, Frederik ; Lamy, Philippe ; Taber, Ann ; Groeneveld, Clarice S. ; Birkenkamp-Demtröder, Karin ; Jensen, Jørgen Bjerggaard ; Strandgaard, Trine ; Nordentoft, Iver and Christensen, Emil , et al. (2021) In Nature Communications 12.
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... (More)

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.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Communications
volume
12
article number
2301
publisher
Nature Publishing Group
external identifiers
  • scopus:85104378401
  • pmid:33863885
ISSN
2041-1723
DOI
10.1038/s41467-021-22465-w
language
English
LU publication?
yes
id
9097e5ff-635e-4a49-ba63-c7ee9f1bf16e
date added to LUP
2021-05-04 16:59:46
date last changed
2025-02-10 12:29:46
@article{9097e5ff-635e-4a49-ba63-c7ee9f1bf16e,
  abstract     = {{<p>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.</p>}},
  author       = {{Lindskrog, Sia Viborg and Prip, Frederik and Lamy, Philippe and Taber, Ann and Groeneveld, Clarice S. and Birkenkamp-Demtröder, Karin and Jensen, Jørgen Bjerggaard and Strandgaard, Trine and Nordentoft, Iver and Christensen, Emil and Sokac, Mateo and Birkbak, Nicolai J. and Maretty, Lasse and Hermann, Gregers G. and Petersen, Astrid C. and Weyerer, Veronika and Grimm, Marc Oliver and Horstmann, Marcus and Sjödahl, Gottfrid and Höglund, Mattias and Steiniche, Torben and Mogensen, Karin and de Reyniès, Aurélien and Nawroth, Roman and Jordan, Brian and Lin, Xiaoqi and Dragicevic, Dejan and Ward, Douglas G. and Goel, Anshita and Hurst, Carolyn D. and Raman, Jay D. and Warrick, Joshua I. and Segersten, Ulrika and Sikic, Danijel and van Kessel, Kim E.M. and Maurer, Tobias and Meeks, Joshua J. and DeGraff, David J. and Bryan, Richard T. and Knowles, Margaret A. and Simic, Tatjana and Hartmann, Arndt and Zwarthoff, Ellen C. and Malmström, Per Uno and Malats, Núria and Real, Francisco X. and Dyrskjøt, Lars}},
  issn         = {{2041-1723}},
  language     = {{eng}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Communications}},
  title        = {{An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer}},
  url          = {{http://dx.doi.org/10.1038/s41467-021-22465-w}},
  doi          = {{10.1038/s41467-021-22465-w}},
  volume       = {{12}},
  year         = {{2021}},
}