Kodahl, Annette R4; Lyng, Maria Bibi5; Binder, Harald3; Cold, Søren4; Gravgaard, Karina5; Knoop, Ann S4; Ditzel, Henrik J5
1 Oncology, Department of Clinical Research, Det Sundhedsvidenskabelige Fakultet, SDU2 Ditzel group, Department of Molecular Medicine, Det Sundhedsvidenskabelige Fakultet, SDU3 Johannes Gutenberg-Universität Mainz4 Oncology, Department of Clinical Research, Det Sundhedsvidenskabelige Fakultet, SDU5 Ditzel group, Department of Molecular Medicine, Det Sundhedsvidenskabelige Fakultet, SDU
A case control study
INTRODUCTION: There are currently no highly sensitive and specific minimally invasive biomarkers for detection of early-stage breast cancer. MicroRNAs (miRNAs) are present in the circulation and may be unique biomarkers for early diagnosis of human cancers. The aim of this study was to investigate the differential expression of miRNAs in the serum of breast cancer patients and healthy controls. METHODS: Global miRNA analysis was performed on serum from 48 patients with ER-positive early-stage breast cancer obtained at diagnosis (24 lymph node-positive and 24 lymph node-negative) and 24 age-matched healthy controls using LNA-based quantitative real-time PCR (qRT-PCR). A signature of miRNAs was subsequently validated in an independent set of 111 serum samples from 60 patients with early-stage breast cancer and 51 healthy controls and further tested for reproducibility in 3 independent data sets from the GEO Database. RESULTS: A multivariable signature consisting of 9 miRNAs (miR-15a, miR-18a, miR-107, miR-133a, miR-139-5p, miR-143, miR-145, miR-365, miR-425) was identified that provided considerable discrimination between breast cancer patients and healthy controls. Further, the ability of the 9 miRNA signature to stratify samples from breast cancer patients and healthy controls was confirmed in the validation set (p = 0.012) with a corresponding AUC = 0.665 in the ROC-curve analysis. No association between miRNA expression and tumor grade, tumor size, menopausal- or lymph node status was observed. The signature was also successfully validated in a previously published independent data set of circulating miRNAs in early-stage breast cancer (p = 0.024). CONCLUSIONS: We present herein a 9 miRNA signature capable of discriminating between ER-positive breast cancer and healthy controls. Using a specific algorithm based on the 9 miRNA signature, the risk for future individuals can be predicted. Since microRNAs are highly stable in blood components, this signature might be useful in the development of a blood-based multi-marker test to improve early detection of breast cancer. Such a test could potentially be used as a screening tool to identify individuals who would benefit from further diagnostic assessment.
Molecular Oncology, 2014, Vol 8, Issue 5, p. 874-83