Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts
Perron, Umberto (Omniscope España)
Grassi, Elena (University of Torino)
Chatzipli, Aikaterini (Boston Children's Hospital (Boston, Estats Units d'Amèrica))
Viviani, Marco (University of Torino)
Karakoc, Emre (Wellcome Sanger Institute. Wellcome Genome Campus)
Trastulla, Lucia (Open Targets. Wellcome Genome Campus)
Brochier, Lorenzo M. (Nerviano Medical Sciences)
Isella, Claudio (University of Torino)
Zanella, Eugenia R. (Candiolo Cancer Institute FPO IRCCS)
Klett, Hagen (Charles River Germany GmbH)
Molineris, Ivan (Department of Life Sciences and Systems Biology. University of Torino)
Schueler, Julia (Charles River Germany GmbH)
Esteller, M (Institut Germans Trias i Pujol. Institut de Recerca contra la Leucèmia Josep Carreras)
Medico, Enzo (University of Torino)
Conte, Nathalie (European Molecular Biology Laboratory European Bioinformatics Institute)
McDermott, Ultan (AstraZeneca Oncology R&D)
Trusolino, Livio (University of Torino)
Bertotti, Andrea (University of Torino)
Iorio, Francesco (Wellcome Sanger Institute. Wellcome Genome Campus)
Universitat Autònoma de Barcelona

Data:	2024
Resum:	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.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Animals ; Antineoplastic Agents, Immunological ; Biomarkers, Tumor ; Cell Line, Tumor ; Cetuximab ; Colorectal Neoplasms ; ErbB Receptors ; Female ; Humans ; Mice ; Xenograft Model Antitumor Assays
Publicat a:	Nature communications, Vol. 15 Núm. 1 (december 2024) , p. 9139, ISSN 2041-1723

DOI: 10.1038/s41467-024-53163-y
PMID: 39528460

20 p, 2.4 MB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP) > Institut de Recerca contra la Leucèmia Josep Carreras
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