XENTURION is a population-level multidimensional resource of xenografts and tumoroids from metastatic colorectal cancer patients

Simonetta M. Leto, Elena Grassi, Marco Avolio, Valentina Vurchio, Francesca Cottino, Martina Ferri, Eugenia R. Zanella, Sofia Borgato, Giorgio Corti, Laura Blasio, Desiana Somale, Marianela Vara-Messler, Francesco Galimi, Francesco Sassi, Barbara Lupo, Irene Catalano, Marika Pinnelli, Marco Viviani, Luca Sperti, Alfredo Mellano, Alessandro Ferrero, Caterina C. Zingaretti, Alberto Puliafito, Luca Primo, Andrea Bertotti () and Livio Trusolino ()
Additional contact information
Simonetta M. Leto: Candiolo Cancer Institute – FPO IRCCS
Elena Grassi: Candiolo Cancer Institute – FPO IRCCS
Marco Avolio: Candiolo Cancer Institute – FPO IRCCS
Valentina Vurchio: Candiolo Cancer Institute – FPO IRCCS
Francesca Cottino: Candiolo Cancer Institute – FPO IRCCS
Martina Ferri: Candiolo Cancer Institute – FPO IRCCS
Eugenia R. Zanella: Candiolo Cancer Institute – FPO IRCCS
Sofia Borgato: Candiolo Cancer Institute – FPO IRCCS
Giorgio Corti: University of Torino
Laura Blasio: Candiolo Cancer Institute – FPO IRCCS
Desiana Somale: Candiolo Cancer Institute – FPO IRCCS
Marianela Vara-Messler: Candiolo Cancer Institute – FPO IRCCS
Francesco Galimi: Candiolo Cancer Institute – FPO IRCCS
Francesco Sassi: Candiolo Cancer Institute – FPO IRCCS
Barbara Lupo: Candiolo Cancer Institute – FPO IRCCS
Irene Catalano: Candiolo Cancer Institute – FPO IRCCS
Marika Pinnelli: Candiolo Cancer Institute – FPO IRCCS
Marco Viviani: Candiolo Cancer Institute – FPO IRCCS
Luca Sperti: Candiolo Cancer Institute – FPO IRCCS
Alfredo Mellano: Candiolo Cancer Institute – FPO IRCCS
Alessandro Ferrero: Mauriziano Umberto I Hospital
Caterina C. Zingaretti: Mauriziano Umberto I Hospital
Alberto Puliafito: Candiolo Cancer Institute – FPO IRCCS
Luca Primo: Candiolo Cancer Institute – FPO IRCCS
Andrea Bertotti: Candiolo Cancer Institute – FPO IRCCS
Livio Trusolino: Candiolo Cancer Institute – FPO IRCCS

Nature Communications, 2024, vol. 15, issue 1, 1-22

Abstract: Abstract The breadth and depth at which cancer models are interrogated contribute to the successful clinical translation of drug discovery efforts. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, where experimental therapies are typically tested. Here we introduce XENTURION, an open-science resource offering a platform of 128 PDX models from patients with metastatic CRC, along with matched PDX-derived tumoroids. Multidimensional omics analyses indicate that tumoroids retain extensive molecular fidelity with parental PDXs. A tumoroid-based trial with the anti-EGFR antibody cetuximab reveals variable sensitivities that are consistent with clinical response biomarkers, mirror tumor growth changes in matched PDXs, and recapitulate EGFR genetic deletion outcomes. Inhibition of adaptive signals upregulated by EGFR blockade increases the magnitude of cetuximab response. These findings illustrate the potential of large living biobanks, providing avenues for molecularly informed preclinical research in oncology.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-51909-2 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51909-2

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-51909-2

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().