Institut für Informatik, Ludwig-Maximilians-Universität München, Germany.
PLoS One. 2011;6(8):e22519. doi: 10.1371/journal.pone.0022519. Epub 2011 Aug 17.
Several expression datasets of miRNA transfection experiments are available to analyze the regulatory mechanisms downstream of miRNA effects. The miRNA induced regulatory effects can be propagated via transcription factors (TFs). We propose the method MIRTFnet to identify miRNA controlled TFs as active regulators if their downstream target genes are differentially expressed.
METHODOLOGY/PRINCIPAL FINDINGS: MIRTFnet enables the determination of active transcription factors (TFs) and is sensitive enough to exploit the small expression changes induced by the activity of miRNAs. For this purpose, different statistical tests were evaluated and compared. Based on the identified TFs, databases, computational predictions and the literature we construct regulatory models downstream of miRNA actions. Transfecting miRNAs are connected to active regulators via a network of miRNA-TF, miRNA-kinase-TF as well as TF-TF relationships. Based on 43 transfection experiments involving 17 cancer relevant miRNAs we show that MIRTFnet detects active regulators reliably.
CONCLUSIONS/SIGNIFICANCE: The consensus of the individual regulatory models shows that the examined miRNAs induce activity changes in a common core of transcription factors involved in cancer related processes such as proliferation or apoptosis.
有几个 miRNA 转染实验的表达数据集可用于分析 miRNA 效应下游的调控机制。miRNA 诱导的调控效应可以通过转录因子 (TF) 进行传播。如果它们的下游靶基因表达差异，我们提出了方法 MIRTFnet 来识别 miRNA 控制的 TF 作为活性调节剂。
方法/主要发现：MIRTFnet 能够确定活性转录因子 (TF)，并且足够敏感，可以利用 miRNA 活性诱导的微小表达变化。为此，评估并比较了不同的统计检验。基于鉴定的 TF，我们构建了数据库、计算预测和文献下游的调控模型。miRNA 转染通过 miRNA-TF、miRNA-激酶-TF 以及 TF-TF 关系网络连接到活性调节剂。基于涉及 17 种癌症相关 miRNA 的 43 个转染实验，我们表明 MIRTFnet 可以可靠地检测到活性调节剂。
结论/意义：个体调控模型的共识表明，所研究的 miRNA 诱导与增殖或凋亡等癌症相关过程相关的常见核心转录因子的活性变化。
