Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer

• Published in: Cancers Vol. 13; no. 9; p. 2130
• Main Authors: Zou, Ruiyang, Loke, Sau Yeen, Tan, Veronique Kiak-Mien, Quek, Swee Tian, Jagmohan, Pooja, Tang, Yew Chung, Madhukumar, Preetha, Tan, Benita Kiat-Tee, Yong, Wei Sean, Sim, Yirong, Lim, Sue Zann, Png, Eunice, Lee, Shu Yun Sherylyn, Chan, Mun Yew Patrick, Ho, Teng Swan Juliana, Khoo, Boon Kheng James, Wong, Su Lin Jill, Thng, Choon Hua, Chong, Bee Kiang, Teo, Yik Ying, Too, Heng-Phon, Hartman, Mikael, Tan, Ngiap Chuan, Tan, Ern Yu, Lee, Soo Chin, Zhou, Lihan, Lee, Ann Siew Gek
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 28.04.2021; MDPI
• Subjects: Benign; Biomarkers; Biopsy; Breast cancer; Cancer screening; Estrogens; Lesions; Lymph nodes; Lymphatic system; Mammography; Medical screening; MicroRNAs; miRNA; breast cancer; abnormal mammograms; circulating microRNAs; biomarkers; qRT-PCR
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers13092130

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.