Yu Xiaokang, Liang Jinsheng, Xu Jiarui, Li Xingsong, Xing Shan, Li Huilan, Liu Wanli, Liu Dongdong, Xu Jianhua, Huang Lizhen, Du Hongli
School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Department of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
J Breast Cancer. 2018 Dec;21(4):363-370. doi: 10.4048/jbc.2018.21.e56. Epub 2018 Dec 10.
Breast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers.
To discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction.
The miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively.
The present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.
乳腺癌是全球女性中最常见的癌症,因此,迫切需要改进其早期检测方法。由于微小RNA(miRNA)越来越被认为是肿瘤发生中的关键调节因子,并且在血浆中具有出色的稳定性,本研究专注于使用miRNA开发一种识别非侵入性生物标志物的方法。
为了发现关键候选物,对来自癌症基因组图谱数据库的409例早期乳腺癌患者和87例健康对照的组织源性miRNA谱进行了差异表达分析。我们从差异表达的miRNA中选择候选物,然后评估由这些候选物形成的每一种可能的分子特征。使用逆转录定量实时聚合酶链反应在来自113例早期乳腺癌患者和47例健康对照的独立血清样本中验证了最佳特征。
根据先前的研究,我们方法中的miRNA候选物被证明与乳腺癌相关,并显示出作为有用生物标志物的潜力。在独立血清样本中进行验证时,最终miRNA特征(miR-21-3p、miR-21-5p和miR-99a-5p)的曲线下面积为0.895。诊断敏感性和特异性分别为97.9%和73.5%。
本研究建立了一种新颖有效的方法来识别早期乳腺癌的生物标志物。并且该方法也适用于其他癌症类型。此外,三种miRNA的组合被确定为乳腺癌早期检测的一种有前景的生物标志物。