The prognostic value of NRF2 in breast cancer patients: a systematic review with meta-analysis

  • Micaela Almeida
  • Mafalda Soares
  • Ana Cristina RamalhinhoEmail author
  • José Fonseca Moutinho
  • Luiza Breitenfeld
  • Luísa Pereira



Nuclear factor E2-related factor 2 (NRF2) is a transcription factor that plays a major role in the regulation of intracellular antioxidant response. The effect of NRF2 overexpression in many malignancies is still unclear and recent meta-analysis correlated NRF2 overexpression with poor prognosis in a variety of human cancers. However, the effect of NRF2 overexpression in breast cancer is still unclear. Thus, the main goal of this work was to clarify the role of NRF2 expression in survival and relapse of breast cancer patients by performing a systematic review according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement, followed by a meta-analysis.


The electronic search was conducted in PubMed, Scopus, SciELO, Web of Science and Embase between November of 2017 and September of 2018. To be included, studies should evaluate NRF2 expression in breast cancer tissue, through immunohistochemistry and/or mRNA and had to report one or more of the following outcomes: overall survival (OS), disease-free survival (DFS), mean survival and median survival.


For the meta-analysis, seven studies were included and NRF2 expression was correlated with OS and DFS. It was observed that compared to patients with low NRF2 expression, patients with NRF2 overexpression had poorer OS with a hazard ratio of 1.82 (95% CI 1.32–2.50; p value < 0.0001), and poorer DFS, with a hazard ratio of 1.79 (95% CI 1.07–3.01; p value = 0.03).


These results suggest that tumours that overexpress NRF2 have a worse clinical outcome. Thus, NRF2 expression could be a marker for the prognostic of breast cancer patients and, in the future, it would be pertinent to focus on improving treatment efficacy for patients with NRF2 overexpression.


NRF2 Breast cancer Systematic review Meta-analysis 



We would like to thank the financial support of our research through the project “Validation of risk assessment model for breast cancer based on genetic polymorphisms of low penetrance to assess breast cancer risk” (Ref. PTDC/DTP-PIC/4743/2014), funded by the Portuguese Foundation for Science and Technology (FCT) through the European Fund for the Regional Development (FEDER) and through the Operational Program of Competitiveness and Internationalization (Ref. POCI-01-0145-FEDER-16620). This project is developed in Health Sciences Research Centre of University of Beira Interior (CICS-UBI) in collaboration with Group of Systematic Reviews of University of Beira Interior (GRUBI), Centre of Mathematics and Applications, University of Beira Interior (CMA-UBI) and with University Hospital Centre of Cova da Beira (CHUCB). We also thank to “Data mining for systematic reviews and Meta-Analyses in Health Sciences” C4—Cloud Computing Competences Centre (Ref. CENTRO-01-0145-FEDER-000019), funded by the Portuguese Foundation for Science and Technology (FCT) through the European Fund for the Regional Development (FEDER). We would also like to knowledge Novartis for giving us access to Embase.


This study was funded by the Portuguese Foundation for Science and Technology (FCT), Ref. PTDC/DTP-PIC/4743/2014, through the European Fund for the Regional Development (FEDER) and through the Operational Program of Competitiveness and Internationalization, Ref. POCI-01-0145-FEDER-16620.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.CICS-UBI—Centro de Investigação em Ciências da SaúdeUniversidade da Beira InteriorCovilhãPortugal
  2. 2.GRUBI, Grupo de Revisões Sistemáticas da Universidade da Beira InteriorCovilhãPortugal
  3. 3.Centro Hospitalar Universitário Cova da Beira, E.P.E. Quinta do AlvitoCovilhãPortugal
  4. 4.CMA-UBI, Centro de Matemática e AplicaçõesUniversidade da Beira InteriorCovilhãPortugal

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