Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine

Detalhes bibliográficos
Autor(a) principal: Lima, Ana Rita
Data de Publicação: 2019
Outros Autores: Pinto, Joana, Azevedo, Ana Isabel, Barros-Silva, Daniela, Jerónimo, Carmen, Henrique, Rui, Bastos, Maria de Lourdes, Guedes de Pinho, Paula, Carvalho, Márcia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10284/10029
Resumo: Background: The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods: A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results: Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions: It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.
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spelling Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urineProstateMetabolomicsVolatile organic compoundsEarly detection of cancerBackground: The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods: A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results: Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions: It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.Nature Publishing GroupRepositório Institucional da Universidade Fernando PessoaLima, Ana RitaPinto, JoanaAzevedo, Ana IsabelBarros-Silva, DanielaJerónimo, CarmenHenrique, RuiBastos, Maria de LourdesGuedes de Pinho, PaulaCarvalho, Márcia2021-07-02T13:42:49Z2019-01-01T00:00:00Z2019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10284/10029eng0007-092010.1038/s41416-019-0585-41532-1827info: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:RCAAP2022-09-06T02:09:19Zoai:bdigital.ufp.pt:10284/10029Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:46:48.023006Repositório 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 Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
title Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
spellingShingle Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
Lima, Ana Rita
Prostate
Metabolomics
Volatile organic compounds
Early detection of cancer
title_short Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
title_full Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
title_fullStr Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
title_full_unstemmed Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
title_sort Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
author Lima, Ana Rita
author_facet Lima, Ana Rita
Pinto, Joana
Azevedo, Ana Isabel
Barros-Silva, Daniela
Jerónimo, Carmen
Henrique, Rui
Bastos, Maria de Lourdes
Guedes de Pinho, Paula
Carvalho, Márcia
author_role author
author2 Pinto, Joana
Azevedo, Ana Isabel
Barros-Silva, Daniela
Jerónimo, Carmen
Henrique, Rui
Bastos, Maria de Lourdes
Guedes de Pinho, Paula
Carvalho, Márcia
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório Institucional da Universidade Fernando Pessoa
dc.contributor.author.fl_str_mv Lima, Ana Rita
Pinto, Joana
Azevedo, Ana Isabel
Barros-Silva, Daniela
Jerónimo, Carmen
Henrique, Rui
Bastos, Maria de Lourdes
Guedes de Pinho, Paula
Carvalho, Márcia
dc.subject.por.fl_str_mv Prostate
Metabolomics
Volatile organic compounds
Early detection of cancer
topic Prostate
Metabolomics
Volatile organic compounds
Early detection of cancer
description Background: The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods: A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results: Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions: It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01T00:00:00Z
2019-01-01T00:00:00Z
2021-07-02T13:42:49Z
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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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10284/10029
url http://hdl.handle.net/10284/10029
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0007-0920
10.1038/s41416-019-0585-4
1532-1827
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.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
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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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
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