There is an urgent need for novel noninvasive prognostic biomarkers for monitoring the recurrence of breast cancer. The purpose of this study is to identify circulating microRNAs that can predict breast cancer recurrence. We conducted a microRNA profiling experiment in serum samples from 48 breast cancer patients using Exiqon miRCURY microRNA RT-PCR panels. Significantly differentiated miRNAs for recurrence in the discovery profiling were further validated in an independent set of sera from 20 patients with breast cancer recurrences and 22 patients without recurrences. We identified seven miRNAs that were differentially expressed between breast cancer patients with and without recurrences, including four miRNAs upregulated (miR-21-5p, miR-375, miR-205-5p, and miR-194-5p) and three miRNAs downregulated (miR-382-5p, miR-376c-3p, and miR-411-5p) for recurrent patients. Using penalized logistic regression, we built a 7-miRNA signature for breast cancer recurrence, which had an excellent discriminating capacity (concordance index=0.914). This signature was significantly associated with recurrence after adjusting for known prognostic factors, and it was applicable to both hormone-receptor positive (concordance index=0.890) and triple-negative breast cancers (concordance index=0.942). We also found the 7-miRNA signature were reliably measured across different runs of PCR experiments (intra-class correlation coefficient=0.780) and the signature was significantly higher in breast cancer patients with recurrence than healthy controls (p=1.1x10-5). In conclusion, circulating miRNAs are promising biomarkers and the signature may be developed into a minimally invasive multi-marker blood test for continuously monitoring the recurrence of breast cancer. It should be further validated for different subtypes of breast cancers in longitudinal studies.
Keywords: breast neoplasms; prognosis; real-time polymerase chain reaction; serum; microRNAs.