Identification of common microRNA-mRNA regulatory biomodules in human epithelial cancer  

作　　者：YANG XiNan LEE Younghee FAN Hong SUN Xiao LUSSIER Yves A 

机构地区：[1]State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China [2]Center for Biomedical lnformatics and Section of Genetic Medicine, Department of Medicine, the University of Chicago, Chicago, IL 60637, USA [3]Key Laboratory of Developmental Genes & Human Diseases of Ministry of Education, Southeast University, Nanjing 210009, China [4]University of Chicago Cancer Research Center, and the Ludwig Center for Metastasis Research, the University of Chicago, Chicago, IL 60637, USA [5]Institute for Genomies and Systems Biology, and the Computational Institute, Argonne National Laboratories and the University of Chicago, Chicago, IL 60637, USA

出　　处：《Chinese Science Bulletin》2010年第31期3576-3589,共14页

基　　金：supported by the National Natural Science Foundation of China (60971099,60671018 and 60771024);Center for Multilevel Analyses of Genomic and Cellular Networks (1U54CA121852-01A1);the Cancer Research Foundation

摘　　要：The complex regulatory network between microRNAs and gene expression remains an unclear domain of active research.We proposed to address in part this complex regulation with a novel approach for the genome-wide identification of biomodules derived from paired microRNA and mRNA profiles,which could reveal correlations associated with a complex network of dys-regulation in human cancer.Two published expression datasets for 68 samples with 11 distinct types of epithelial cancers and 21 samples of normal tissues were used,containing microRNA expression and gene expression profiles,respectively.As results,the microRNA expression used jointly with mRNA expression can provide better classifiers of epithelial cancers against normal epithelial tissue than either dataset alone(P=1×10-10,F-test).We identified a combination of 6 microRNA-mRNA biomodules that optimally classified epithelial cancers from normal epithelial tissue(total accuracy = 93.3%;95% confidence intervals:86%-97%),using penalized logistic regression(PLR) algorithm and three-fold cross-validation.Three of these biomodules are individually sufficient to cluster epithelial cancers from normal tissue using mutual information distance.The biomodules contain 10 distinct microRNAs and 98 distinct genes,including well known tumor markers such as miR-15a,miR-30e,IRAK1,TGFBR2,DUSP16,CDC25B and PDCD2.In addition,there is a significant enrichment(Fisher's exact test P=3×10-10) between putative microRNA-target gene pairs reported in 5 microRNA target databases and the inversely correlated microRNA-mRNA pairs in the biomodules.Further,microRNAs and genes in the biomodules were found in abstracts mentioning epithelial cancers(Fisher's Exact test,unadjusted P<0.05).Taken together,these results strongly suggest that the discovered microRNA-mRNA biomodules correspond to regulatory mechanisms common to human epithelial cancer samples.In conclusion,we developed and evaluated a novel comprehensive method to systematically identify,on a genome scale,microRNA-mRNA expression bThe complex regulatory network between microRNAs and gene expression remains an unclear domain of active research. We proposed to address in part this complex regulation with a novel approach for the genome-wide identification of biomodules derived from paired microRNA and mRNA profiles, which could reveal correlations associated with a complex network of dys-regulation in human cancer. Two published expression datasets for 68 samples with 11 distinct types of epithelial cancers and 21 samples of normal tissues were used, containing microRNA expression and gene expression profiles, respectively. As results, the microRNA expression used jointly with mRNA expression can provide better classifiers of epithelial cancers against normal epithelial tissue than either dataset alone （P=1×10-10 F-test）. We identified a combination of 6 microRNA-mRNA biomodules that optimally classified epithelial cancers from normal epithelial tissue （total accuracy = 93.3%; 95% confidence intervals： 86%-97%）, using penalized logistic regression （PLR） algorithm and three-fold cross-validation. Three of these biomodules are individually sufficient to cluster epithelial cancers from normal tissue using mutual information distance. The biomodules contain 10 distinct microRNAs and 98 distinct genes, including well known tumor markers such as miR-15a, miR-30, IRAK1, TGFBR2, DUSP16, CDC25B and PDCD2. In addition, there is a significant enrichment （Fisher＇s exact test P=3×10-l0） between putative microRNA-target gene pairs reported in 5 microRNA target databases and the inversely correlated microRNA-mRNA pairs in the biomodules. Further, microRNAs and genes in the biomodules were found in abstracts mentioning epithelial cancers （Fisher＇s Exact test, unadjusted P〈0.05）. Taken together, these results strongly suggest that the discovered microRNA-mRNA biomodules correspond to regulatory mechanisms common to human epithelial cancer samples. In conclusion, we developed and evaluated a novel comprehensive method to systemat

关 键 词：RNA基因 上皮细胞 监管机制 FISHER精确检验 癌症 MICRORNA 人类 识别 

分 类 号：Q813.11[生物学—生物工程] TQ920.1[轻工技术与工程—发酵工程]