Zebrafish Avatar-test forecasts clinical response to chemotherapy in patients with colorectal cancer

Bruna Costa, Marta F. Estrada, António Gomes, Laura M. Fernandez, José M. Azevedo, Vanda Póvoa, Márcia Fontes, António Alves, António Galzerano, Mireia Castillo-Martin, Ignacio Herrando, Shermann Brandão, Carla Carneiro, Vítor Nunes, Carlos Carvalho, Amjad Parvaiz, Ana Marreiros and Rita Fior ()
Additional contact information
Bruna Costa: Champalimaud Foundation
Marta F. Estrada: Champalimaud Foundation
António Gomes: Hospital Prof. Doutor Fernando Fonseca
Laura M. Fernandez: Champalimaud Clinical Centre, Champalimaud Foundation
José M. Azevedo: Champalimaud Clinical Centre, Champalimaud Foundation
Vanda Póvoa: Champalimaud Foundation
Márcia Fontes: Champalimaud Foundation
António Alves: Faculty of Medicine of the University of Lisbon
António Galzerano: Champalimaud Foundation
Mireia Castillo-Martin: Champalimaud Foundation
Ignacio Herrando: Champalimaud Clinical Centre, Champalimaud Foundation
Shermann Brandão: Champalimaud Foundation
Carla Carneiro: Hospital Prof. Doutor Fernando Fonseca
Vítor Nunes: Hospital Prof. Doutor Fernando Fonseca
Carlos Carvalho: Champalimaud Foundation
Amjad Parvaiz: Champalimaud Clinical Centre, Champalimaud Foundation
Ana Marreiros: University of Algarve
Rita Fior: Champalimaud Foundation

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Cancer patients often undergo rounds of trial-and-error to find the most effective treatment because there is no test in the clinical practice for predicting therapy response. Here, we conduct a clinical study to validate the zebrafish patient-derived xenograft model (zAvatar) as a fast predictive platform for personalized treatment in colorectal cancer. zAvatars are generated with patient tumor cells, treated exactly with the same therapy as their corresponding patient and analyzed at single-cell resolution. By individually comparing the clinical responses of 55 patients with their zAvatar-test, we develop a decision tree model integrating tumor stage, zAvatar-apoptosis, and zAvatar-metastatic potential. This model accurately forecasts patient progression with 91% accuracy. Importantly, patients with a sensitive zAvatar-test exhibit longer progression-free survival compared to those with a resistant test. We propose the zAvatar-test as a rapid approach to guide clinical decisions, optimizing treatment options and improving the survival of cancer patients.

Date: 2024
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DOI: 10.1038/s41467-024-49051-0

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