Fang Rui, Zhu Yong, Hu Ling, Khadka Vedbar Singh, Ai Junmei, Zou Hanqing, Ju Dianwen, Jiang Bin, Deng Youping, Hu Xiamin
Bioinformatics Core, Department of Complementary and Integrative Medicine, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States.
Shanghai University of Medicine and Health Sciences, Shanghai, China.
Front Physiol. 2019 Jan 8;9:1879. doi: 10.3389/fphys.2018.01879. eCollection 2018.
Breast cancer is the second leading cause of cancer death among females. We sought to identify microRNA (miRNA) markers in breast cancer, and determine whether miRNA expression is predictive of early stage breast cancer. The paired panel of microRNAs is promising. Global miRNA expression profiling was performed on three pooling samples of plasma from breast cancer, benign lesion and normal, using next generation sequencing technology. Thirteen microRNAs (hsa-miR-21-3p, hsa-miR-192-5p, hsa-miR-221-3p, hsa-miR-451a, hsa-miR-574-5p, hsa-miR-1273g-3p, hsa-miR-152, hsa-miR-22-3p, hsa-miR-222-3p, hsa-miR-30a-5p, hsa-miR-30e-5p, hsa-miR-324-3p, and hsa -miR-382-5p) were subsequently validated using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR) in a cohort of 53 breast cancer, 40 benign lesions and 38 normal cases. The pairwise miRNA ratios were calculated as biomarkers to classify breast cancer. According to the model used to predict breast cancer from benign lesions, a panel of five miRNA pairs had high diagnostic power with an AUC of 0.942. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of this model after 10-fold cross validation were 0.881, 0.775, 0.827, and 0.756, respectively. In addition, the other panels of miRNA pairs distinguishing the breast cancer from normal and non-cancer patients had good performance. Certain MicroRNA pairs were identified and deemed effective in breast cancer screening, especially when distinguishing cancer from benign lesions.
乳腺癌是女性癌症死亡的第二大主要原因。我们试图鉴定乳腺癌中的微小RNA（miRNA）标志物，并确定miRNA表达是否可预测早期乳腺癌。配对的miRNA组合很有前景。使用下一代测序技术对来自乳腺癌、良性病变和正常血浆的三个混合样本进行了全局miRNA表达谱分析。随后，在53例乳腺癌、40例良性病变和38例正常病例的队列中，使用实时定量逆转录-聚合酶链反应（RT-qPCR）对13种微小RNA（hsa-miR-21-3p、hsa-miR-192-5p、hsa-miR-221-3p、hsa-miR-451a、hsa-miR-574-5p、hsa-miR-1273g-3p、hsa-miR-152、hsa-miR-22-3p、hsa-miR-222-3p、hsa-miR-30a-5p、hsa-miR-30e-5p、hsa-miR-324-3p和hsa-miR-382-5p）进行了验证。计算成对的miRNA比率作为对乳腺癌进行分类的生物标志物。根据用于从良性病变预测乳腺癌的模型，一组五个miRNA对具有较高的诊断能力，曲线下面积（AUC）为0.942。该模型在10倍交叉验证后的灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）分别为0.881、0.775、0.827和0.756。此外，区分乳腺癌与正常和非癌症患者的其他miRNA对组合也表现良好。某些miRNA对被鉴定为在乳腺癌筛查中有效，尤其是在区分癌症与良性病变时。
