Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer

Detalhes bibliográficos
Autor(a) principal: Mendes, Rita
Data de Publicação: 2022
Outros Autores: Graça, Gonçalo, Silva, Fernanda, Guerreiro, Ana C L, Gomes-Alves, Patrícia, Serpa, Jacinta, Boghaert, Erwin R, Alves, Paula M, Félix, Ana, Brito, Catarina, Isidro, Inês A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/144474
Resumo: Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.
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spelling Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancerbiomarkerschemoresistancedrug responseex vivo modelsmetabolomicsovarian carcinomatumor microenvironmentSDG 3 - Good Health and Well-beingPredicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.Instituto de Tecnologia Química e Biológica António Xavier (ITQB)NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)iNOVA4Health - pólo NMSRUNMendes, RitaGraça, GonçaloSilva, FernandaGuerreiro, Ana C LGomes-Alves, PatríciaSerpa, JacintaBoghaert, Erwin RAlves, Paula MFélix, AnaBrito, CatarinaIsidro, Inês A.2022-10-04T22:15:25Z2022-09-142022-09-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/144474eng2072-6694PURE: 46752095https://doi.org/10.3390/cancers14184460info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:24:08Zoai:run.unl.pt:10362/144474Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:51:35.388948Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
title Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
spellingShingle Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
Mendes, Rita
biomarkers
chemoresistance
drug response
ex vivo models
metabolomics
ovarian carcinoma
tumor microenvironment
SDG 3 - Good Health and Well-being
title_short Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
title_full Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
title_fullStr Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
title_full_unstemmed Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
title_sort Exploring Metabolic Signatures of Ex Vivo Tumor Tissue Cultures for Prediction of Chemosensitivity in Ovarian Cancer
author Mendes, Rita
author_facet Mendes, Rita
Graça, Gonçalo
Silva, Fernanda
Guerreiro, Ana C L
Gomes-Alves, Patrícia
Serpa, Jacinta
Boghaert, Erwin R
Alves, Paula M
Félix, Ana
Brito, Catarina
Isidro, Inês A.
author_role author
author2 Graça, Gonçalo
Silva, Fernanda
Guerreiro, Ana C L
Gomes-Alves, Patrícia
Serpa, Jacinta
Boghaert, Erwin R
Alves, Paula M
Félix, Ana
Brito, Catarina
Isidro, Inês A.
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Instituto de Tecnologia Química e Biológica António Xavier (ITQB)
NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
iNOVA4Health - pólo NMS
RUN
dc.contributor.author.fl_str_mv Mendes, Rita
Graça, Gonçalo
Silva, Fernanda
Guerreiro, Ana C L
Gomes-Alves, Patrícia
Serpa, Jacinta
Boghaert, Erwin R
Alves, Paula M
Félix, Ana
Brito, Catarina
Isidro, Inês A.
dc.subject.por.fl_str_mv biomarkers
chemoresistance
drug response
ex vivo models
metabolomics
ovarian carcinoma
tumor microenvironment
SDG 3 - Good Health and Well-being
topic biomarkers
chemoresistance
drug response
ex vivo models
metabolomics
ovarian carcinoma
tumor microenvironment
SDG 3 - Good Health and Well-being
description Predicting patient response to treatment and the onset of chemoresistance are still major challenges in oncology. Chemoresistance is deeply influenced by the complex cellular interactions occurring within the tumor microenvironment (TME), including metabolic crosstalk. We have previously shown that ex vivo tumor tissue cultures derived from ovarian carcinoma (OvC) resections retain the TME components for at least four weeks of culture and implemented assays for assessment of drug response. Here, we explored ex vivo patient-derived tumor tissue cultures to uncover metabolic signatures of chemosensitivity and/or resistance. Tissue cultures derived from nine OvC cases were challenged with carboplatin and paclitaxel, the standard-of-care chemotherapeutics, and the metabolic footprints were characterized by LC-MS. Partial least-squares discriminant analysis (PLS-DA) revealed metabolic signatures that discriminated high-responder from low-responder tissue cultures to ex vivo drug exposure. As a proof-of-concept, a set of potential metabolic biomarkers of drug response was identified based on the receiver operating characteristics (ROC) curve, comprising amino acids, fatty acids, pyrimidine, glutathione, and TCA cycle pathways. Overall, this work establishes an analytical and computational platform to explore metabolic features of the TME associated with response to treatment, which can leverage the discovery of biomarkers of drug response and resistance in OvC.
publishDate 2022
dc.date.none.fl_str_mv 2022-10-04T22:15:25Z
2022-09-14
2022-09-14T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/144474
url http://hdl.handle.net/10362/144474
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2072-6694
PURE: 46752095
https://doi.org/10.3390/cancers14184460
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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