Development and validation of a circulating microRNA panel for the early detection of breast cancer

被引:35
作者
Zou, Ruiyang [1 ]
Loke, Sau Yeen [2 ]
Tang, Yew Chung [1 ]
Too, Heng-Phon [3 ,4 ]
Zhou, Lihan [1 ]
Lee, Ann S. G. [2 ,5 ,6 ]
Hartman, Mikael [7 ,8 ,9 ]
机构
[1] Dept Res & Dev, MiRXES Lab, Singapore, Singapore
[2] Natl Canc Ctr, Humphrey Oei Inst Canc Res, Cellular & Mol Res, Singapore, Singapore
[3] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Biochem, Singapore, Singapore
[4] Natl Univ Singapore, NUS Ctr Canc Res, Yong Loo Lin Sch Med, Singapore, Singapore
[5] Duke NUS Med Sch, SingHlth Duke NUS Oncol Acad Clin Programme, Singapore, Singapore
[6] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Physiol, Singapore, Singapore
[7] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Surg, Singapore, Singapore
[8] Natl Univ Hlth Syst, Singapore, Singapore
[9] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore, Singapore
基金
英国医学研究理事会;
关键词
FALSE DISCOVERY RATE; IDENTIFICATION; BIOMARKERS; SIGNATURE;
D O I
10.1038/s41416-021-01593-6
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BACKGROUND: Mammography is widely used for breast cancer screening but suffers from a high false-positive rate. Here, we perform the largest comprehensive, multi-center study to date involving diverse ethnic groups, for the identification of circulating miRNAs for breast cancer screening. METHODS: This study had a discovery phase (n = 289) and two validation phases (n = 374 and n = 379). Quantitative PCR profiling of 324 miRNAs was performed on serum samples from breast cancer (all stages) and healthy subjects to identify miRNA biomarkers. Two-fold cross-validation was used for building and optimising breast cancer-associated miRNA panels. An optimal panel was validated in cohorts with Caucasian and Asian samples. Diagnostic ability was evaluated using area under the curve (AUC) analysis. RESULTS: The study identified and validated 30 miRNAs dysregulated in breast cancer. An optimised eight-miRNA panel showed consistent performance in all cohorts and was successfully validated with AUC, accuracy, sensitivity, and specificity of 0.915, 82.3%, 72.2% and 91.5%, respectively. The prediction model detected breast cancer in both Caucasian and Asian populations with AUCs ranging from 0.880 to 0.973, including pre-malignant lesions (stage 0; AUC of 0.831) and early-stage (stages I-II) cancers (AUC of 0.916). CONCLUSIONS: Our panel can potentially be used for breast cancer screening, in conjunction with mammography.
引用
收藏
页码:472 / 481
页数:10
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