GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients
Autor(a) principal: | |
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Data de Publicação: | 2017 |
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/10284/8089 |
Resumo: | The analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography-mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers. |
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GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patientsVolatile organic compoundsUrineBiomarkersRenal cell carcinomaGas chromatography–mass spectrometryMultivariate statistical analysisThe analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography-mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers.John Wiley & SonsRepositório Institucional da Universidade Fernando PessoaMonteiro, MárciaMoreira, NathaliePinto, JoanaPires-Luís, Ana S.Henrique, RuiJerónimo, CarmenBastos, Maria de LourdesGil, Ana M.Carvalho, MárciaGuedes de Pinho, Paula2019-10-01T12:38:40Z2017-01-01T00:00:00Z2017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10284/8089eng1582-183810.1111/jcmm.131321582-4934info: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:RCAAP2022-09-06T02:07:28Zoai:bdigital.ufp.pt:10284/8089Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:44:59.016117Repositório 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 |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
title |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
spellingShingle |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients Monteiro, Márcia Volatile organic compounds Urine Biomarkers Renal cell carcinoma Gas chromatography–mass spectrometry Multivariate statistical analysis |
title_short |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
title_full |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
title_fullStr |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
title_full_unstemmed |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
title_sort |
GC-MS metabolomics-based approach for the identification of a potential VOC-biomarker panel in the urine of renal cell carcinoma patients |
author |
Monteiro, Márcia |
author_facet |
Monteiro, Márcia Moreira, Nathalie Pinto, Joana Pires-Luís, Ana S. Henrique, Rui Jerónimo, Carmen Bastos, Maria de Lourdes Gil, Ana M. Carvalho, Márcia Guedes de Pinho, Paula |
author_role |
author |
author2 |
Moreira, Nathalie Pinto, Joana Pires-Luís, Ana S. Henrique, Rui Jerónimo, Carmen Bastos, Maria de Lourdes Gil, Ana M. Carvalho, Márcia Guedes de Pinho, Paula |
author2_role |
author 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 |
Monteiro, Márcia Moreira, Nathalie Pinto, Joana Pires-Luís, Ana S. Henrique, Rui Jerónimo, Carmen Bastos, Maria de Lourdes Gil, Ana M. Carvalho, Márcia Guedes de Pinho, Paula |
dc.subject.por.fl_str_mv |
Volatile organic compounds Urine Biomarkers Renal cell carcinoma Gas chromatography–mass spectrometry Multivariate statistical analysis |
topic |
Volatile organic compounds Urine Biomarkers Renal cell carcinoma Gas chromatography–mass spectrometry Multivariate statistical analysis |
description |
The analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography-mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01T00:00:00Z 2017-01-01T00:00:00Z 2019-10-01T12:38:40Z |
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/10284/8089 |
url |
http://hdl.handle.net/10284/8089 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1582-1838 10.1111/jcmm.13132 1582-4934 |
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 |
John Wiley & Sons |
publisher.none.fl_str_mv |
John Wiley & Sons |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799130315861524480 |