Biofluid quantification of TWEAK/Fn14 axis in combination with a selected biomarker panel improves assessment of prostate cancer aggressiveness

dc.contributor.authorRuiz‑Plazas, Xavier
dc.contributor.authorRodríguez‑Gallego, Esther
dc.contributor.authorAlves, Marta
dc.contributor.authorAltuna Coy, Antonio
dc.contributor.authorLozano‑Bartolomé, Javier
dc.contributor.authorPortero Otín, Manuel
dc.contributor.authorGarcía‑Fontgivell, Joan Francesc
dc.contributor.authorMartínez‑González, Salomé
dc.contributor.authorSegarra, José
dc.contributor.authorChacón, Matilde R.
dc.date.accessioned2020-03-09T13:38:08Z
dc.date.available2020-03-09T13:38:08Z
dc.date.issued2019
dc.description.abstractBackground: Conventional clinical biomarkers cannot accurately differentiate indolent from aggressive prostate cancer (PCa). We investigated the usefulness of a biomarker panel measured exclusively in biofluids for assessment of PCa aggressiveness. Methods: We collected biofluid samples (plasma/serum/semen/post-prostatic massage urine) from 98 patients that had undergone radical prostatectomy. Clinical biochemistry was performed and several cytokines/chemokines including soluble(s) TWEAK, sFn14, sCD163, sCXCL5 and sCCL7 were quantified by ELISA in selected biofluids. Also, the expression of KLK2, KLK3, Fn14, CD163, CXCR2 and CCR3 was quantified by real-time PCR in semen cell sediment. Univariate, logistic regression, and receiver operating characteristic (ROC) analyses were used to assess the predictive ability of the selected biomarker panel in conjunction with clinical and metabolic variables for the evaluation of PCa aggressiveness. Results: Total serum levels of prostate-specific antigen (PSA), semen levels of sTWEAK, fasting glycemia and mRNA levels of Fn14, KLK2, CXCR2 and CCR3 in semen cell sediment constituted a panel of markers that was significantly different between patients with less aggressive tumors [International Society of Urological Pathology (ISUP) grade I and II] and those with more aggressive tumors (ISUP grade III, IV and V). ROC curve analysis showed that this panel could be used to correctly classify tumor aggressiveness in 90.9% of patients. Area under the curve (AUC) analysis revealed that this combination was more accurate [AUC = 0.913 95% confidence interval (CI) 0.782-1] than a classical non-invasive selected clinical panel comprising age, tumor clinical stage (T-classification) and total serum PSA (AUC = 0.721 95% CI 0.613-0.830). Conclusions: TWEAK/Fn14 axis in combination with a selected non-invasive biomarker panel, including conventional clinical biochemistry, can improve the predictive power of serum PSA levels and could be used to classify PCa aggressiveness.ca_ES
dc.description.sponsorshipThis study was supported by a project from the Fondo de Investigación Sanitaria, PI17/00877 (M.R.CH and X.R-P.), co-financed by the European Regional Development Fund and by “Ayuda de Investigación Pedro Cifuentes” grant awarded by the “Fundación para la Investigación en Urología” to Dr Xavier Ruiz as well as the Fundació Vallformosa “IV Premi Martí Via”.ca_ES
dc.identifier.doihttps://doi.org/10.1186/s12967-019-2053-6
dc.identifier.idgrec029491
dc.identifier.issn1479-5876
dc.identifier.urihttp://hdl.handle.net/10459.1/68180
dc.language.isoengca_ES
dc.publisherBMC (part of Springer Nature)ca_ES
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.1186/s12967-019-2053-6ca_ES
dc.relation.ispartofJournal of Translational Medicine, 2019, vol. 17, ID 307ca_ES
dc.rightscc-by (c) Ruiz-Plazas et al., 2019ca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectTWEAK/Fn14 axisca_ES
dc.subjectProstate cancerca_ES
dc.subjectBiomarkersca_ES
dc.subjectDiagnosisca_ES
dc.subjectBiofluidsca_ES
dc.titleBiofluid quantification of TWEAK/Fn14 axis in combination with a selected biomarker panel improves assessment of prostate cancer aggressivenessca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_ES
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