Assessing the Role of MicroRNAs in Predicting Breast Cancer Recurrence—A Systematic Review

Author:

Bouz Mkabaah Luis1ORCID,Davey Matthew G.1ORCID,Lennon James C.1,Bouz Ghada2ORCID,Miller Nicola1ORCID,Kerin Michael J.1

Affiliation:

1. Discipline of Surgery, Lambe Institute for Translational Research, University of Galway, H91 YR71 Galway, Ireland

2. Faculty of Pharmacy in Hradec Králové, Charles University, 50005 Hradec Králové, Czech Republic

Abstract

Identifying patients likely to develop breast cancer recurrence remains a challenge. Thus, the discovery of biomarkers capable of diagnosing recurrence is of the utmost importance. MiRNAs are small, non-coding RNA molecules which are known to regulate genetic expression and have previously demonstrated relevance as biomarkers in malignancy. To perform a systematic review evaluating the role of miRNAs in predicting breast cancer recurrence. A formal systematic search of PubMed, Scopus, Web of Science, and Cochrane databases was performed. This search was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) checklist. A total of 19 studies involving 2287 patients were included. These studies identified 44 miRNAs which predicted breast cancer recurrence. Results from nine studies assessed miRNAs in tumour tissues (47.4%), eight studies included circulating miRNAs (42.1%), and two studies assessed both tumour and circulating miRNAs (10.5%). Increased expression of 25 miRNAs were identified in patients who developed recurrence, and decreased expression of 14 miRNAs. Interestingly, five miRNAs (miR-17-5p, miR-93-5p, miR-130a-3p, miR-155, and miR-375) had discordant expression levels, with previous studies indicating both increased and reduced expression levels of these biomarkers predicting recurrence. MiRNA expression patterns have the ability to predict breast cancer recurrence. These findings may be used in future translational research studies to identify patients with breast cancer recurrence to improve oncological and survival outcomes for our prospective patients.

Funder

National Breast Cancer Research Institute, Ireland

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

Reference42 articles.

1. Cancer statistics, 2022;Siegel;CA Cancer J. Clin.,2022

2. Disease recurrence and oncological outcome of patients treated surgically with curative intent for estrogen receptor positive, lymph node negative breast cancer;Davey;Surg. Oncol.,2021

3. Recurrent Breast Cancer Treatment Strategies for Maintaining and Prolonging Good Quality of Life;Gerber;Dtsch. Arztebl. Int.,2010

4. Breast cancer recurrence: Factors impacting occurrence and survival;Courtney;Ir. J. Med. Sci.,2022

5. Mattick, J.S. (2009). The Genetic Signatures of Noncoding RNAs. PLoS Genet., 5.

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