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Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts

Author

Listed:
  • Umberto Perron

    (Human Technopole
    Omniscope España)

  • Elena Grassi

    (Candiolo Cancer Institute FPO IRCCS
    University of Torino)

  • Aikaterini Chatzipli

    (Wellcome Sanger Institute, Wellcome Genome Campus
    Boston Children’s Hospital, Harvard Medical School)

  • Marco Viviani

    (Candiolo Cancer Institute FPO IRCCS
    University of Torino)

  • Emre Karakoc

    (Wellcome Sanger Institute, Wellcome Genome Campus)

  • Lucia Trastulla

    (Human Technopole
    Open Targets, Wellcome Genome Campus)

  • Lorenzo M. Brochier

    (Human Technopole
    Nerviano Medical Sciences)

  • Claudio Isella

    (Candiolo Cancer Institute FPO IRCCS
    University of Torino)

  • Eugenia R. Zanella

    (Candiolo Cancer Institute FPO IRCCS)

  • Hagen Klett

    (Charles River Germany GmbH)

  • Ivan Molineris

    (University of Torino)

  • Julia Schueler

    (Charles River Germany GmbH)

  • Manel Esteller

    (Badalona
    Centro de Investigacion Biomedica en Red Cancer (CIBERONC)
    Institucio Catalana de Recerca i Estudis Avançats (ICREA)
    University of Barcelona (UB))

  • Enzo Medico

    (Candiolo Cancer Institute FPO IRCCS
    University of Torino)

  • Nathalie Conte

    (European Molecular Biology Laboratory European Bioinformatics Institute)

  • Ultan McDermott

    (Wellcome Sanger Institute, Wellcome Genome Campus
    AstraZeneca Oncology R&D)

  • Livio Trusolino

    (Candiolo Cancer Institute FPO IRCCS
    University of Torino)

  • Andrea Bertotti

    (Candiolo Cancer Institute FPO IRCCS
    University of Torino)

  • Francesco Iorio

    (Human Technopole
    Wellcome Sanger Institute, Wellcome Genome Campus)

Abstract

Patient-derived xenografts (PDXs) are tumour fragments engrafted into mice for preclinical studies. PDXs offer clear advantages over simpler in vitro cancer models - such as cancer cell lines (CCLs) and organoids - in terms of structural complexity, heterogeneity, and stromal interactions. Here, we characterise 231 colorectal cancer PDXs at the genomic, transcriptomic, and epigenetic levels, along with their response to cetuximab, an EGFR inhibitor used clinically for metastatic colorectal cancer. After evaluating the PDXs’ quality, stability, and molecular concordance with publicly available patient cohorts, we present results from training, interpreting, and validating the integrative ensemble classifier CeSta. This model takes in input the PDXs’ multi-omic characterisation and predicts their sensitivity to cetuximab treatment, achieving an area under the receiver operating characteristics curve > 0.88. Our study demonstrates that large PDX collections can be leveraged to train accurate, interpretable drug sensitivity models that: (1) better capture patient-derived therapeutic biomarkers compared to models trained on CCL data, (2) can be robustly validated across independent PDX cohorts, and (3) could contribute to the development of future therapeutic biomarkers.

Suggested Citation

  • Umberto Perron & Elena Grassi & Aikaterini Chatzipli & Marco Viviani & Emre Karakoc & Lucia Trastulla & Lorenzo M. Brochier & Claudio Isella & Eugenia R. Zanella & Hagen Klett & Ivan Molineris & Julia, 2024. "Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53163-y
    DOI: 10.1038/s41467-024-53163-y
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