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Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics

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dc.contributor.author Gámez Pozo, Angelo
dc.contributor.author Trilla Fuertes, Lucía
dc.contributor.author Prado Vázquez, Guillermo
dc.contributor.author Chiva, Cristina
dc.contributor.author López Vacas, Rocío
dc.contributor.author Nanni, Paolo
dc.contributor.author Berges Soria, Julia
dc.contributor.author Grossmann, Jonas
dc.contributor.author Díaz Almirón, Mariana
dc.contributor.author Ciruelos, Eva
dc.contributor.author Sabidó Aguadé, Eduard, 1981-
dc.contributor.author Espinosa Arranz, Enrique
dc.contributor.author Fresno Vara, Juan Ángel
dc.date.accessioned 2018-07-06T06:57:26Z
dc.date.available 2018-07-06T06:57:26Z
dc.date.issued 2017
dc.identifier.citation Gámez-Pozo A, Trilla-Fuertes L, Prado-Vázquez G, Chiva C, López-Vacas R, Nanni P et al. Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics. PLoS One. 2017 Jun 8;12(6):e0178296. DOI: 10.1371/journal.pone.0178296
dc.identifier.issn 1932-6203
dc.identifier.uri http://hdl.handle.net/10230/35042
dc.description.abstract BACKGROUND: Triple-negative breast cancer (TNBC) accounts for 15-20% of all breast cancers and usually requires the administration of adjuvant chemotherapy after surgery but even with this treatment many patients still suffer from a relapse. The main objective of this study was to identify proteomics-based biomarkers that predict the response to standard adjuvant chemotherapy, so that patients at are not going to benefit from it can be offered therapeutic alternatives. METHODS: We analyzed the proteome of a retrospective series of formalin-fixed, paraffin-embedded TNBC tissue applying high-throughput label-free quantitative proteomics. We identified several protein signatures with predictive value, which were validated with quantitative targeted proteomics in an independent cohort of patients and further evaluated in publicly available transcriptomics data. RESULTS: Using univariate Cox analysis, a panel of 18 proteins was significantly associated with distant metastasis-free survival of patients (p<0.01). A reduced 5-protein profile with prognostic value was identified and its prediction performance was assessed in an independent targeted proteomics experiment and a publicly available transcriptomics dataset. Predictor P5 including peptides from proteins RAC2, RAB6A, BIEA and IPYR was the best performance protein combination in predicting relapse after adjuvant chemotherapy in TNBC patients. CONCLUSIONS: This study identified a protein combination signature that complements histopathological prognostic factors in TNBC treated with adjuvant chemotherapy. The protein signature can be used in paraffin-embedded samples, and after a prospective validation in independent series, it could be used as predictive clinical test in order to recommend participation in clinical trials or a more exhaustive follow-up.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Public Library of Science (PLoS)
dc.relation.ispartof PLoS One. 2017 Jun 8;12(6):e0178296
dc.rights © 2017 Gámez-Pozo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0178296
dc.subject.keyword Breast cancer
dc.subject.keyword Adjuvant chemotherapy
dc.subject.keyword Transcriptome analysis
dc.subject.keyword Proteomics
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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