Oztemur Yasemin, Bekmez Tufan, Aydos Alp, Yulug Isik G, Bozkurt Betul, Dedeoglu Bala Gur
Ankara University, Biotechnology Institute, Ankara, Turkey.
Gazi University, Faculty of Dentistry, Ankara, Turkey.
PLoS One. 2015 May 15;10(5):e0126837. doi: 10.1371/journal.pone.0126837. eCollection 2015.
Breast cancer is one of the most important causes of cancer-related deaths worldwide in women. In addition to gene expression studies, the progressing work in the miRNA area including miRNA microarray studies, brings new aspects to the research on the cancer development and progression. Microarray technology has been widely used to find new biomarkers in research and many transcriptomic microarray studies are available in public databases. In this study, the breast cancer miRNA and mRNA microarray studies were collected according to the availability of their data and clinical information, and combined by a newly developed ranking-based meta-analysis approach to find out candidate miRNA biomarkers (meta-miRNAs) that classify breast cancers according to their grades and explain the relation between miRNAs and mRNAs. This approach provided meta-miRNAs specific to breast cancer grades, pointing out let-7 family members as grade classifiers. The qRT-PCR studies performed with independent breast tumors confirmed the potential biomarker role of let-7 family members (meta-miRNAs). The concordance between the meta-mRNAs and miRNA target genes specific to tumor grade (common genes) supported the idea of mRNAs as miRNA targets. The pathway analysis results showed that most of the let-7 family miRNA targets, and also common genes, were significantly taking part in cancer-related pathways. The qRT-PCR studies, together with bioinformatic analyses, confirmed the results of meta-analysis approach, which is dynamic and allows combining datasets from different platforms.
乳腺癌是全球女性癌症相关死亡的最重要原因之一。除了基因表达研究外，包括miRNA微阵列研究在内的miRNA领域的不断进展的工作，为癌症发展和进展的研究带来了新的方面。微阵列技术已被广泛用于在研究中寻找新的生物标志物，并且许多转录组微阵列研究可在公共数据库中获得。在本研究中，根据乳腺癌miRNA和mRNA微阵列研究的数据和临床信息的可用性进行收集，并通过一种新开发的基于排名的荟萃分析方法进行合并，以找出根据乳腺癌分级对其进行分类并解释miRNA与mRNA之间关系的候选miRNA生物标志物（元miRNA）。这种方法提供了特定于乳腺癌分级的元miRNA，指出let-7家族成员作为分级分类器。对独立乳腺肿瘤进行的qRT-PCR研究证实了let-7家族成员（元miRNA）的潜在生物标志物作用。肿瘤分级特异性的元mRNA与miRNA靶基因（共同基因）之间的一致性支持了mRNA作为miRNA靶标的观点。通路分析结果表明，大多数let-7家族miRNA靶标以及共同基因都显著参与了癌症相关通路。qRT-PCR研究与生物信息学分析一起证实了荟萃分析方法的结果，该方法是动态的，允许合并来自不同平台的数据集。
