Publication
GC-MS-based endometabolome analysis differentiates prostate cancer from normal prostate cells
| dc.contributor.author | Lima, Ana | |
| dc.contributor.author | Araújo, Ana | |
| dc.contributor.author | Pinto, Joana | |
| dc.contributor.author | Jerónimo, Carmen | |
| dc.contributor.author | Henrique, Rui | |
| dc.contributor.author | Bastos, Maria | |
| dc.contributor.author | Carvalho, Márcia | |
| dc.contributor.author | Guedes de Pinho, Paula | |
| dc.date.accessioned | 2019-10-01T12:29:39Z | |
| dc.date.available | 2019-10-01T12:29:39Z | |
| dc.date.issued | 2018-03 | |
| dc.description.abstract | Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography-mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.3390/metabo8010023 | pt_PT |
| dc.identifier.issn | 2218-1989 | |
| dc.identifier.issn | 2218-1989 | |
| dc.identifier.uri | http://hdl.handle.net/10284/8088 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI | pt_PT |
| dc.relation | FEDER funds POCI/01/0145/FEDER/07728 | pt_PT |
| dc.relation | National funds (FCT/MEC, Fundação para a Ciência e a Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreement PT2020 UID/MULTI/04378/2013 | pt_PT |
| dc.relation | UFP Energy, Environment and Health Research Unit | |
| dc.relation.publisherversion | https://www.mdpi.com/2218-1989/8/1/23 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Prostate cancer | pt_PT |
| dc.subject | Cancer metabolomics | pt_PT |
| dc.subject | Cell lines | pt_PT |
| dc.subject | Metabolomics | pt_PT |
| dc.subject | Endometabolome | pt_PT |
| dc.subject | GC-MS | pt_PT |
| dc.title | GC-MS-based endometabolome analysis differentiates prostate cancer from normal prostate cells | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | UFP Energy, Environment and Health Research Unit | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FMulti%2F04546%2F2013/PT | |
| oaire.citation.issue | 1 | pt_PT |
| oaire.citation.startPage | 23 | pt_PT |
| oaire.citation.title | Metabolites | pt_PT |
| oaire.citation.volume | 8 | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Carvalho | |
| person.givenName | Marcia | |
| person.identifier | 2017111 | |
| person.identifier.ciencia-id | 8B10-171E-E63E | |
| person.identifier.orcid | 0000-0001-9884-4751 | |
| person.identifier.rid | D-5999-2013 | |
| person.identifier.scopus-author-id | 7201413997 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 3837b828-ba57-47f7-a811-cce65e4922c6 | |
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