构建mRNA/miRNA/蛋白质调控网络寻找胰腺导管腺癌分子标志物

Identification of molecular biomarker for pancreatic ductal adenocarcinoma through mRNA/miRNA/protein regulation network

目的整合高通量miRNA/mRNA/蛋白质表达数据,寻找胰腺导管腺癌(pancreatic ductal adenocarcinoma,PDAC)分子标志物(Biomarker)。方法本文提出利用PDAC样本的mRNA、miRNA与蛋白质表达谱数据,通过"转录因子(TF)调控miRNA"与"miRNA靶向调控基因"的关系构建在PDAC发病过程中的核心调控网络,并据此预测定义选候PDAC相关mRNA与miRNA,同时利用差异表达蛋白进一步定义调控网络。结果发现6个miR let-7家族miRNA成员(hsa-let-7i、hsa-let-7d、hsa-let-7b、hsalet-7g、hsa-let-7c、hsa-let-7e)与5个在基因与蛋白层面同时差异表达的基因(ALDH1A1、TGFB1、ANXA2、FN1、THBS1)形成的一个核心调控网络,其网络中涉及的5个基因全都为已知与PDAC发生发展明确相关的分子。利用5个基因对3套大规模的PDAC表达数据进行分型分析,结果发现其分类准确性分别达到了93%(91%～94%)、90%(89%～92%)与88%(87%～89%)。结论通过miRNA/mRNA/蛋白三种数据整合分析得到的5候选标记基因具有良好的分型能力,可作为新的PDAC分型Biomarker。

Objective Using mRNA/miRNA/protein expression profiles to identify the molecular biomarker for pancreatic ductal adenocarcinoma（PDAC）. Method We used miRNA , mRNA and protein ex-pression data of PDAC to construct the molecular regulatory network by the interaction of＆quot;transcription factor （TF） target miRNA＆quot; and＆quot;miRNA target gene＆quot;, and based on this network to infer some candidate genes and miRNAs which were related to the molecular mechanism of PDAC. Result We found a key network related to 6 miR let-7 family members （hsa-let-7i、hsa-let-7d、hsa-let-7b、hsa-let-7g、hsa-let-7c、hsa-let-7e） and 5 differently expressed genes（ALDH1A1、TGFB1、ANXA2、FN1、THBS1）, all genes and miRNA were PDAC related molecular in this key network. Three large-scale expression profile of PDAC was used to test the 5 genes. The results shown that the prediction accuracy were 93%（91%~94%）、90%（89%~92%）、88%（87%~89%） in three expression datasets, respectively. Conclusion Five genes identified by our new methods with multidimensional data minning show a great classified power for PDAC, and should be new biomarkers for PDAC.