Metabolomic studies of breast cancer in murine models: a review

Detalhes bibliográficos
Autor(a) principal: Araújo, Rita
Data de Publicação: 2020
Outros Autores: Bispo, Daniela, Helguero, Luisa A., Gil, Ana M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/31230
Resumo: Metabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies. Scope of review: This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturallyoccurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study. Major conclusions: Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination. General significance: Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.
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spelling Metabolomic studies of breast cancer in murine models: a reviewBreast cancerMurine modelsMetabolomicsMetabonomicsBiomarkersDiagnosisMetabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies. Scope of review: This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturallyoccurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study. Major conclusions: Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination. General significance: Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.Elsevier2021-04-23T17:04:02Z2020-05-01T00:00:00Z2020-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/31230eng0925-443910.1016/j.bbadis.2020.165713Araújo, RitaBispo, DanielaHelguero, Luisa A.Gil, Ana M.info: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:RCAAP2024-05-06T04:31:40Zoai:ria.ua.pt:10773/31230Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-06T04:31:40Repositório 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 Metabolomic studies of breast cancer in murine models: a review
title Metabolomic studies of breast cancer in murine models: a review
spellingShingle Metabolomic studies of breast cancer in murine models: a review
Araújo, Rita
Breast cancer
Murine models
Metabolomics
Metabonomics
Biomarkers
Diagnosis
title_short Metabolomic studies of breast cancer in murine models: a review
title_full Metabolomic studies of breast cancer in murine models: a review
title_fullStr Metabolomic studies of breast cancer in murine models: a review
title_full_unstemmed Metabolomic studies of breast cancer in murine models: a review
title_sort Metabolomic studies of breast cancer in murine models: a review
author Araújo, Rita
author_facet Araújo, Rita
Bispo, Daniela
Helguero, Luisa A.
Gil, Ana M.
author_role author
author2 Bispo, Daniela
Helguero, Luisa A.
Gil, Ana M.
author2_role author
author
author
dc.contributor.author.fl_str_mv Araújo, Rita
Bispo, Daniela
Helguero, Luisa A.
Gil, Ana M.
dc.subject.por.fl_str_mv Breast cancer
Murine models
Metabolomics
Metabonomics
Biomarkers
Diagnosis
topic Breast cancer
Murine models
Metabolomics
Metabonomics
Biomarkers
Diagnosis
description Metabolomic strategies have been extensively used to search for biomarkers of disease, including cancer, in biological complex mixtures such as cells, tissues and biofluids. In breast cancer research, murine models are of great value and metabolomics has been increasingly applied to characterize tumor or organ tissues, or biofluids, for instance to follow-up metabolism during cancer progression or response to specific therapies. Scope of review: This review briefly introduces the different murine models used in breast cancer research and proceeds to present the metabolomic studies reported so far to describe the deviant metabolic behavior associated to breast cancer, in each type of model: xenografts (cell- or patient-derived), spontaneous (naturallyoccurring or genetically engineered) and carcinogen-induced. The type of sample and strategies followed are identified, as well as the main findings from of study. Major conclusions: Metabolomics has gradually become relevant in characterizing murine models of breast cancer, using either Nuclear Magnetic Resonance (NMR) or Mass Spectromety (MS). Both tissue and biofluids are matrixes of interest in this context, although in some type of models, reports have focused primarily on the former. The aims of tissue studies have comprised the search for mechanistic knowledge of carcinogenesis, metastasis development and response/resistance to therapies. Biofluid metabolomics has mainly aimed at finding non-invasive biomarkers for early breast cancer detection or prognosis determination. General significance: Metabolomics provides exquisite detail on murine tumor and systemic metabolism of breast cancer. This knowledge paves the way for the discovery of new biomarkers, potentially translatable to in vivo non-invasive patient follow-up.
publishDate 2020
dc.date.none.fl_str_mv 2020-05-01T00:00:00Z
2020-05
2021-04-23T17:04:02Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/31230
url http://hdl.handle.net/10773/31230
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0925-4439
10.1016/j.bbadis.2020.165713
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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