Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomics
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- dc.contributor.author Gámez Pozo, Angeloca
- dc.contributor.author Trilla Fuertes, Lucíaca
- dc.contributor.author Prado Vázquez, Guillermoca
- dc.contributor.author Chiva, Cristinaca
- dc.contributor.author López Vacas, Rocíoca
- dc.contributor.author Nanni, Paoloca
- dc.contributor.author Berges Soria, Juliaca
- dc.contributor.author Grossmann, Jonasca
- dc.contributor.author Díaz Almirón, Marianaca
- dc.contributor.author Ciruelos, Evaca
- dc.contributor.author Sabidó Aguadé, Eduard, 1981-ca
- dc.contributor.author Espinosa Arranz, Enriqueca
- dc.contributor.author Fresno Vara, Juan Ángelca
- dc.date.accessioned 2018-07-06T06:57:26Z
- dc.date.available 2018-07-06T06:57:26Z
- dc.date.issued 2017
- 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.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.doi http://dx.doi.org/10.1371/journal.pone.0178296
- dc.identifier.issn 1932-6203
- dc.identifier.uri http://hdl.handle.net/10230/35042
- dc.language.iso eng
- dc.publisher Public Library of Science (PLoS)ca
- 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.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Breast cancer
- dc.subject.keyword Adjuvant chemotherapy
- dc.subject.keyword Transcriptome analysis
- dc.subject.keyword Proteomics
- dc.title Prediction of adjuvant chemotherapy response in triple negative breast cancer with discovery and targeted proteomicsca
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion