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Molecular correlates of cisplatin-based chemotherapy response in muscle invasive bladder cancer by integrated multi-omics analysis

Author

Listed:
  • Ann Taber

    (Aarhus University Hospital
    Aarhus University)

  • Emil Christensen

    (Aarhus University Hospital
    Aarhus University)

  • Philippe Lamy

    (Aarhus University Hospital)

  • Iver Nordentoft

    (Aarhus University Hospital)

  • Frederik Prip

    (Aarhus University Hospital
    Aarhus University)

  • Sia Viborg Lindskrog

    (Aarhus University Hospital
    Aarhus University)

  • Karin Birkenkamp-Demtröder

    (Aarhus University Hospital
    Aarhus University)

  • Trine Line Hauge Okholm

    (Aarhus University Hospital
    Aarhus University)

  • Michael Knudsen

    (Aarhus University Hospital)

  • Jakob Skou Pedersen

    (Aarhus University Hospital
    Aarhus University)

  • Torben Steiniche

    (Aarhus University Hospital)

  • Mads Agerbæk

    (Aarhus University Hospital)

  • Jørgen Bjerggaard Jensen

    (Aarhus University
    Aarhus University Hospital)

  • Lars Dyrskjøt

    (Aarhus University Hospital
    Aarhus University)

Abstract

Overtreatment with cisplatin-based chemotherapy is a major issue in the management of muscle-invasive bladder cancer (MIBC), and currently none of the reported biomarkers for predicting response have been implemented in the clinic. Here we perform a comprehensive multi-omics analysis (genomics, transcriptomics, epigenomics and proteomics) of 300 MIBC patients treated with chemotherapy (neoadjuvant or first-line) to identify molecular changes associated with treatment response. DNA-based associations with response converge on genomic instability driven by a high number of chromosomal alterations, indels, signature 5 mutations and/or BRCA2 mutations. Expression data identifies the basal/squamous gene expression subtype to be associated with poor response. Immune cell infiltration and high PD-1 protein expression are associated with treatment response. Through integration of genomic and transcriptomic data, we demonstrate patient stratification to groups of low and high likelihood of cisplatin-based response. This could pave the way for future patient selection following validation in prospective clinical trials.

Suggested Citation

  • Ann Taber & Emil Christensen & Philippe Lamy & Iver Nordentoft & Frederik Prip & Sia Viborg Lindskrog & Karin Birkenkamp-Demtröder & Trine Line Hauge Okholm & Michael Knudsen & Jakob Skou Pedersen & T, 2020. "Molecular correlates of cisplatin-based chemotherapy response in muscle invasive bladder cancer by integrated multi-omics analysis," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18640-0
    DOI: 10.1038/s41467-020-18640-0
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    Cited by:

    1. Zikun Ma & Zhiyong Li & Yize Mao & Jingwei Ye & Zefu Liu & Yuzhao Wang & Chen Wei & Jun Cui & Zhuowei Liu & Xiaoyu Liang, 2023. "AhR diminishes the efficacy of chemotherapy via suppressing STING dependent type-I interferon in bladder cancer," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. JungHo Kong & Doyeon Ha & Juhun Lee & Inhae Kim & Minhyuk Park & Sin-Hyeog Im & Kunyoo Shin & Sanguk Kim, 2022. "Network-based machine learning approach to predict immunotherapy response in cancer patients," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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