Publicação
Zebrafish Avatar-test forecasts clinical response to chemotherapy in patients with colorectal cancer
| dc.contributor.author | Costa, Bruna | |
| dc.contributor.author | Estrada, Marta F. | |
| dc.contributor.author | Gomes, António | |
| dc.contributor.author | Fernandez, Laura M. | |
| dc.contributor.author | Azevedo, José M. | |
| dc.contributor.author | Póvoa, Vanda | |
| dc.contributor.author | Fontes, Márcia | |
| dc.contributor.author | Alves, António | |
| dc.contributor.author | Galzerano, António | |
| dc.contributor.author | Castillo-Martin, Mireia | |
| dc.contributor.author | Herrando, Ignacio | |
| dc.contributor.author | Brandão, Shermann | |
| dc.contributor.author | Carneiro, Carla | |
| dc.contributor.author | Nunes, Vítor | |
| dc.contributor.author | Carvalho, Carlos | |
| dc.contributor.author | Parvaiz, Amjad | |
| dc.contributor.author | Marreiros, Ana | |
| dc.contributor.author | Fior, Rita | |
| dc.date.accessioned | 2024-10-03T13:32:59Z | |
| dc.date.available | 2024-10-03T13:32:59Z | |
| dc.date.issued | 2024-06-05 | |
| dc.description.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. | eng |
| dc.description.sponsorship | Ministry of Education and Science | Fundao para a Cincia e a Tecnologia (Portuguese Science and Technology Foundation) FCT-PTDC/MEC-ONC/31627/2017 LISBOA-01-0145-FEDER-022170 FCT/Lisboa2020 Champalimaud Foundation BIAL Award in Clinical Medicine | |
| dc.identifier.doi | 10.1038/s41467-024-49051-0 | |
| dc.identifier.issn | 2041-1723 | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/25991 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Springer Science and Business Media | |
| dc.relation | Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa | |
| dc.relation.ispartof | Nature Communications | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.title | Zebrafish Avatar-test forecasts clinical response to chemotherapy in patients with colorectal cancer | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F50021%2F2020/PT | |
| oaire.citation.issue | 1 | |
| oaire.citation.title | Nature Communications | |
| oaire.citation.volume | 15 | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Marreiros | |
| person.givenName | Ana | |
| person.identifier.ciencia-id | 9A12-9450-7051 | |
| person.identifier.orcid | 0000-0001-9410-4772 | |
| person.identifier.scopus-author-id | 57194785077 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
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