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. eCollection 2017.

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.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Chemotherapy, Adjuvant / methods*
  • Disease-Free Survival
  • Humans
  • Middle Aged
  • Prognosis
  • Proteomics / methods*
  • RAC2 GTP-Binding Protein
  • Software
  • Transcriptome / genetics
  • Triple Negative Breast Neoplasms / drug therapy*
  • Triple Negative Breast Neoplasms / metabolism*
  • Triple Negative Breast Neoplasms / mortality
  • Triple Negative Breast Neoplasms / pathology
  • rab GTP-Binding Proteins / metabolism
  • rac GTP-Binding Proteins / metabolism

Substances

  • Rab6 protein
  • rab GTP-Binding Proteins
  • rac GTP-Binding Proteins

Grants and funding

We want to particularly acknowledge the patients in this study for their participation and to the IdiPAZ and I+12 Biobanks for the generous gifts of clinical samples used in this work. The IdiPAZ and I+12 Biobanks are supported by Instituto de Salud Carlos III, Spanish Economy and Competitiveness Ministry (RD09/0076/00073 and RD09/0076/00118 respectively) and Farmaindustria, through the Cooperation Program in Clinical and Translational Research of the Community of Madrid. This work was supported by Instituto de Salud Carlos III, Spanish Economy and Competitiveness Ministry, Spain and co-funded by FEDER program, “Una forma de hacer Europa” (PI12/00444, PI12/01016 and PI15/01310). LT-F is supported by Spanish Economy and Competitiveness Ministry (DI-15-07614). The CRG/UPF Proteomics Unit is part of the “Plataforma de Recursos Biomoleculares y Bioinformáticos (ProteoRed)” supported by grant PT13/0001 of ISCIII and Spanish Ministry of Economy and Competitiveness. We acknowledge support of the Spanish Ministry of Economy and Competitiveness, “Centro de Excelencia Severo Ochoa 2013-2017”, SEV-2012-0208, and from “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2014SGR678). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.