Recurrent
breast cancer occurring after the initial treatment is associated with poor outcome. A bimodal relapse pattern after surgery for primary
tumor has been described with peaks of early and late recurrence occurring at about 2 and 5 years, respectively. Although several clinical and pathological features have been used to discriminate between low- and high-risk patients, the identification of molecular
biomarkers with prognostic value remains an unmet need in the current management of
breast cancer. Using microarray-based technology, we have performed a
microRNA expression analysis in 71 primary
breast tumors from patients that either remained disease-free at 5 years post-surgery (group A) or developed early (group B) or late (group C) recurrence. Unsupervised hierarchical clustering of
microRNA expression data segregated
tumors in two groups, mainly corresponding to patients with early recurrence and those with no recurrence. Microarray data analysis and RT-qPCR validation led to the identification of a set of 5
microRNAs (the 5-
miRNA signature) differentially expressed between these two groups: miR-149, miR-10a, miR-20b, miR-30a-3p and miR-342-5p. All five
microRNAs were down-regulated in
tumors from patients with early recurrence. We show here that the 5-miRNA signature defines a high-risk group of patients with shorter relapse-free survival and has predictive value to discriminate non-relapsing versus early-relapsing patients (AUC = 0.993, p-value<0.05). Network analysis based on
miRNA-target interactions curated by public databases suggests that down-regulation of the 5-miRNA signature in the subset of early-relapsing
tumors would result in an overall increased proliferative and angiogenic capacity. In summary, we have identified a set of recurrence-related
microRNAs with potential prognostic value to identify patients who will likely develop
metastasis early after primary breast surgery.