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miRNAs with the potential to distinguish follicular thyroid carcinomas from benign follicular thyroid tumors: results of a meta-analysis.

机译:有可能将滤泡性甲状腺癌与良性滤泡性甲状腺肿瘤区分开的miRNA:荟萃分析的结果。

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The detection of somatic mutations in indeterminate or follicular proliferation fine-needle aspiration cytologies (FNACs) is able to clarify only a subgroup of those FNACs. Therefore, further markers to differentiate this problematic FNAC category by the identification of mutation negative thyroid cancers and benign nodules are urgently needed. Our objective was to evaluate previously published miRNA markers and discover novel ones from all publicly available miRNA expression profiling data sets. By literature review and data repository search we gathered 3 data sets describing human miRNA expression profiles of follicular thyroid cancer (FTC) and follicular adenoma (FA) samples. Literature review summarized 27 previously published miRNAs, which were validated in the 3 available data sets. By means of uniform statistical analysis 6 further miRNAs were identified and tested in an independent, previously published microarray data set. Meta-analysis confirmed 7 out of 27 previously published, and 4 out of 6 de novo identified miRNAs. The low confirmation rate of previously published miRNA markers was induced by low numbers of samples in the analyzed studies and high false discovery rates that were higher than 0.2. Finally, miR-637, miR-181c-3p, miR-206, and miR-7-5p were discovered as de novo potential FTC markers and validated in at least one independent, previously published data set. Two out of these new identified miRNAs (miR-7-5p and miR-206) were validated by qPCR in an independent sample set of 32 FTC and 46 FA samples. Especially miR-7-5p was able to differentiate benign and malignant thyroid tumors in several datasets.
机译:不确定或滤泡增生的细针抽吸细胞学(FNAC)中的体细胞突变检测仅能够阐明这些FNAC的一个亚组。因此,迫切需要通过鉴定突变阴性甲状腺癌和良性结节来区分该有问题的FNAC类别的其他标记。我们的目标是评估以前发表的miRNA标记,并从所有可公开获得的miRNA表达谱数据集中发现新颖的标记。通过文献综述和数据存储库搜索,我们收集了3个数据集,描述了滤泡性甲状腺癌(FTC)和滤泡性腺瘤(FA)样品的人miRNA表达谱。文献综述总结了27种先前发表的miRNA,并在3个可用数据集中进行了验证。通过统一的统计分析,在独立的,先前发布的微阵列数据集中鉴定并测试了另外6个miRNA。荟萃分析确认了先前发表的27种miRNA中的7种,以及从头开始鉴定的6种miRNA中的4种。先前发表的miRNA标记物的低确认率是由分析研究中的样本数量少和高于0.2的高错误发现率引起的。最后,发现了miR-637,miR-181c-3p,miR-206和miR-7-5p作为潜在的FTC标记,并在至少一个独立的,先前发布的数据集中进行了验证。通过qPCR在32个FTC和46个FA样品的独立样品集中对这些新鉴定的miRNA中的两个(miR-7-5p和miR-206)进行了验证。特别是miR-7-5p能够在多个数据集中区分甲状腺良性和恶性肿瘤。

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