Assessing the Role of MicroRNAs in Predicting Breast Cancer Recurrence-A Systematic Review.
Luis Bouz MkabaahMatthew G DaveyJames C LennonGhada BouzNicola MillerMichael J KerinPublished in: International journal of molecular sciences (2023)
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.
Keyphrases
- poor prognosis
- systematic review
- free survival
- end stage renal disease
- meta analyses
- long non coding rna
- ejection fraction
- case control
- newly diagnosed
- chronic kidney disease
- prognostic factors
- prostate cancer
- public health
- randomized controlled trial
- small molecule
- cell proliferation
- deep learning
- long noncoding rna
- machine learning
- current status
- high throughput
- dna methylation
- rectal cancer