It has been demonstrated that there are abundant stable microRNAs (miRNAs) in plasma/serum, which can be detected and are potentially disease specific. However, the lack of suitable endogenous controls for serum miRNA detection is the restriction for the widely usage of this kind of biomarkers and for the between-laboratory comparison of the findings. We first systematically screened for endogenous control miRNAs (ECMs) by testing 10 pooling samples (using both Solexa sequencing and TaqMan low density array) and 50 individual samples (using quantitative reverse transcription-PCR) of different cancer traits and healthy controls. Then we assessed serum miRNAs used as potential biomarkers for breast cancer risk prediction based on a two-stage case-control analysis, including 48 breast cancer patients and 48 controls for the discovery stage and 76 breast cancer patients and 76 controls for validation. We identified two candidate ECMs (miRNA-191 and miRNA-484). Normalized by the two ECMs, we found four miRNAs (miR-16, miR-25, miR-222 and miR-324-3p) that were consistently differentially expressed between breast cancer cases and controls. The area under the receiver operating characteristic curve is 0.954 for the four-miRNA signature in the discovery stage (sensitivity = 0.917 and specificity = 0.896) and 0.928 in the validation stage (sensitivity = 0.921 and specificity = 0.934). In conclusion, the four-miRNA signature from serum may serve as a non-invasive prediction biomarker for breast cancer. Furthermore, we proposed the combination of miRNA-484 and miRNA-191 as endogenous control for serum miRNA detection, at least for most common cancers.