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Patient-derived xenografts and organoids model therapy response in prostate cancer

Author

Listed:
  • Sofia Karkampouna

    (University of Bern)

  • Federico La Manna

    (University of Bern
    Leiden University Medical Center)

  • Andrej Benjak

    (University of Bern)

  • Mirjam Kiener

    (University of Bern)

  • Marta De Menna

    (University of Bern
    University of Bern)

  • Eugenio Zoni

    (University of Bern)

  • Joël Grosjean

    (University of Bern)

  • Irena Klima

    (University of Bern)

  • Andrea Garofoli

    (University of Basel)

  • Marco Bolis

    (Università della Svizzera italiana
    Bioinformatics Core Unit
    Mario Negri Institute for Pharmacological Research)

  • Arianna Vallerga

    (Università della Svizzera italiana
    Bioinformatics Core Unit)

  • Jean-Philippe Theurillat

    (Università della Svizzera italiana)

  • Maria R. De Filippo

    (University of Bern
    University of Basel)

  • Vera Genitsch

    (University of Bern)

  • David Keller

    (ETH Zurich)

  • Tijmen H. Booij

    (ETH Zurich)

  • Christian U. Stirnimann

    (ETH Zurich)

  • Kenneth Eng

    (Weill Cornell Medicine)

  • Andrea Sboner

    (Weill Cornell Medicine)

  • Charlotte K. Y. Ng

    (University of Bern)

  • Salvatore Piscuoglio

    (University of Basel
    University of Basel
    Clarunis Universitäres Bauchzentrum Basel)

  • Peter C. Gray

    (The Salk Institute for Biological Studies)

  • Martin Spahn

    (Lindenhofspital
    University Duisburg-Essen)

  • Mark A. Rubin

    (University of Bern
    University of Bern and Inselspital)

  • George N. Thalmann

    (University of Bern
    Bern University Hospital)

  • Marianna Kruithof-de Julio

    (University of Bern
    University of Bern
    University of Bern and Inselspital
    Bern University Hospital)

Abstract

Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe an androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naïve, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harbors BRCA2 and CHD1 somatic mutations, shows an SPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modeled in vivo. Comparison of the treatment-naïve PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds.

Suggested Citation

  • Sofia Karkampouna & Federico La Manna & Andrej Benjak & Mirjam Kiener & Marta De Menna & Eugenio Zoni & Joël Grosjean & Irena Klima & Andrea Garofoli & Marco Bolis & Arianna Vallerga & Jean-Philippe T, 2021. "Patient-derived xenografts and organoids model therapy response in prostate cancer," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21300-6
    DOI: 10.1038/s41467-021-21300-6
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    Cited by:

    1. Martina Minoli & Thomas Cantore & Daniel Hanhart & Mirjam Kiener & Tarcisio Fedrizzi & Federico La Manna & Sofia Karkampouna & Panagiotis Chouvardas & Vera Genitsch & Antonio Rodriguez-Calero & Eva Co, 2023. "Bladder cancer organoids as a functional system to model different disease stages and therapy response," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Marco Bolis & Daniela Bossi & Arianna Vallerga & Valentina Ceserani & Manuela Cavalli & Daniela Impellizzieri & Laura Di Rito & Eugenio Zoni & Simone Mosole & Angela Rita Elia & Andrea Rinaldi & Ricar, 2021. "Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression," Nature Communications, Nature, vol. 12(1), pages 1-15, December.

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