Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , |
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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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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 |
format |
article |
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 instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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 |
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1799130334697095168 |