Abstract
Although mammography is the gold standard for breast cancer screening, the high rates of false-positive mammograms remain a concern. Thus, there is an unmet clinical need for a non-invasive and reliable test to differentiate between malignant and benign breast lesions in order to avoid subjecting patients with abnormal mammograms to unnecessary follow-up diagnostic procedures. Serum samples from 116 malignant breast lesions and 64 benign breast lesions were comprehensively profiled for 2,083 microRNAs (miRNAs) using next-generation sequencing. Of the 180 samples profiled, three outliers were removed based on the principal component analysis (PCA), and the remaining samples were divided into training (n = 125) and test (n = 52) sets at a 70:30 ratio for further analysis. In the training set, significantly differentially expressed miRNAs (adjusted p < 0.01) were identified after correcting for multiple testing using a false discovery rate. Subsequently, a predictive classification model using an eight-miRNA signature and a Bayesian logistic regression algorithm was developed. Based on the receiver operating characteristic (ROC) curve analysis in the test set, the model could achieve an area under the curve (AUC) of 0.9542. Together, this study demonstrates the potential use of circulating miRNAs as an adjunct test to stratify breast lesions in patients with abnormal screening mammograms.
Highlights
Mammography is the current gold standard for breast cancer screening; this modality produces false-negatives and has high false-positive rates [1,2,3,4,5]
This present study describes the identification of a circulating eight-miRNA signature which was significantly differentially expressed between malignant breast lesions and benign breast lesions, and could segregate both cases and controls on principal component analysis (PCA)
The present findings demonstrate the use of circulating miRNAs from blood as a promising tool to detect breast cancer with higher area under the curve (AUC) in discriminating malignant cases and benign controls as compared to previous miRNA discovery studies [15,16,17]
Summary
Mammography is the current gold standard for breast cancer screening; this modality produces false-negatives and has high false-positive rates [1,2,3,4,5]. States (U.S.), out of all screening mammograms (n = 702,154), approximately 24.5% (n = 171,829) were found to be abnormal, with 2,599 women diagnosed with ductal carcinoma in situ (DCIS) or invasive breast cancer [1]. As an individual woman may undergo several breast screenings in her lifetime, the cumulative probability of false-positive recalls after 10 years of annual mammogram screening is estimated to be 61% [6]. The national expenditure of false-positive mammograms in the U.S (including various service costs and fees for follow-up diagnostic procedures) is estimated to be US$2.8 billion annually based on the assumption of an 11% false-positive rate among 29.5 million women aged 40 to 59 years [1]
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