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dc.contributor.authorEritja Sánchez, Núria
dc.contributor.authorJové Font, Mariona
dc.contributor.authorEldevik Fasmer, Kristine
dc.contributor.authorGatius Calderó, Sònia
dc.contributor.authorPortero Otín, Manuel
dc.contributor.authorTrovik, Jone
dc.contributor.authorKrakstad, Camilla
dc.contributor.authorSol, Joaquim
dc.contributor.authorPamplona Gras, Reinald
dc.contributor.authorHaldorsen, Ingfrid S.
dc.contributor.authorMatias-Guiu, Xavier
dc.date.accessioned2018-01-10T11:26:40Z
dc.date.available2018-01-10T11:26:40Z
dc.date.issued2017
dc.identifier.issn1949-2553
dc.identifier.urihttp://hdl.handle.net/10459.1/62325
dc.description.abstractPurpose: We aimed to study the potential influence of tumour blood flow –obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)- in the metabolomic profiles of endometrial tumours. Methods: Liquid chromatography coupled to mass spectrometry established the metabolomic profile of endometrial cancer lesions exhibiting high (n=12) or low (n=14) tumour blood flow at DCE-MRI. Univariate and multivariate statistics (ortho-PLS-DA, a random forest (RF) classifier and hierarchical clustering) and receiver operating characteristic (ROC) curves were used to establish a panel for potentially discriminating tumours with high versus low blood flow. Results: Tumour blood flow is associated with specific metabolomic signatures. Ortho-PLS-DA and RF classifier resulted in well-defined clusters with an out-of-bag error lower than 8%. We found 28 statistically significant molecules (False Discovery Rate corrected p<0.05). Based on exact mass, retention time and isotopic distribution we identified 9 molecules including resolvin D and specific lysophospholipids associated with blood flow, and hence with a potentially regulatory role relevant in endometrial cancer. Conclusions: Tumour flow parameters at DCE-MRI quantifying vascular tumour characteristics are reflected in corresponding metabolomics signatures and highlight disease mechanisms that may be targetable by novel therapies.ca_ES
dc.description.sponsorshipSupported by grants, PI13/01701 and PI16/00692 from Fondo de Investigaciones Sanitarias del Instituto de Salud Carlos III cofinanciado por Fondo Europeo de Desarrollo Regional (FEDER) (“Una manera de hacer Europa”), Red Temática de investigación en Cáncer RD12/0036/0013 and Red de Oncología (CIBERONC-ONCG33/2017) and the Department of Health from the Generalitat of Catalonia (SLT002/16/00250). Grups consolidats de la Generalitat de Catalunya (2009SGR794 and 2014SGR168), Fundació La Marató de TV3 (2/C2013), Grupos estables AECC, Plataforma de Biobancos ISCIII (PT13/0010/0014) and ENITEC NETWORK. NE holds a postdoctoral fellowship from Generalitat de Catalunya (SLT002/16/00274).ca_ES
dc.language.isoengca_ES
dc.publisherImpact Journalsca_ES
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.18632/oncotarget.22558ca_ES
dc.relation.ispartofOncotarget, 2017, vol. 8, núm. 65, p, 109018-109026ca_ES
dc.rightscc-by (c) Eritja et al., 2017ca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectEndometrial cancerca_ES
dc.subjectDCE-MRIca_ES
dc.subjectBlood flowca_ES
dc.subjectMetabolomic analysisca_ES
dc.titleTumour-microenvironmental blood flow determines a metabolomic signature identifying lysophospholipids and resolvin D as biomarkers in endometrial cancer patientsca_ES
dc.typearticleca_ES
dc.identifier.idgrec026371
dc.type.versionpublishedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.18632/oncotarget.22558


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