The prognostic value of NRF2 in breast cancer patients: a systematic review with meta-analysis
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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.
KeywordsNRF2 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.
This article does not contain any studies with human participants performed by any of the authors.
- 16.Light R, Pillemer D (1984) Summing up: the science of reviewing research. Harvard University Press, CambridgeGoogle Scholar
- 17.Light R, Singer J, Willett J (1994) The visual presentation and interpretation of meta-analyses. In: Cooper H, Hedges LV (eds) The handbook of research synthesis. Russell Sage Foundation, New York, pp 439–445Google Scholar
- 19.Duval S, Tweedie R (2000) A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J Am Stat Assoc 95:89–98Google Scholar
- 24.Xiao Y, Hu G, Dong D-D, Tian W, Li T-T, Jiang X-H, Wang L (2016) Prognostic value of NRF2 in breast cancer patients and its role as a tumor suppressor by directly inhibiting HER2 expression. Int J Clin Exp Pathol 9:4292–4306Google Scholar
- 27.Bocci F, Tripathi SC, Mercedes SV, George JT, Casabar J, Wong PK, Hanash S, Levine H, Onuchic JN, Jolly MK (2018) NRF2 activates a partial epithelial-mesenchymal transition and is maximally present in a hybrid epithelial/mesenchymal phenotype. biorxiv 11(6):251–263Google Scholar
- 33.Weigman VJ, Chao H-H, Shabalin AA, He X, Parker JS, Nordgard SH, Grushko T, Huo D, Nwachukwu C, Nobel A (2012) Basal-like Breast cancer DNA copy number losses identify genes involved in genomic instability, response to therapy, and patient survival. Breast Cancer Res Treat 133:865–880CrossRefGoogle Scholar