TY - JOUR
T1 - Identification of common microRNA-mRNA regulatory biomodules in human epithelial cancer
AU - Yang, Xi Nan
AU - Lee, Younghee
AU - Fan, Hong
AU - Sun, Xiao
AU - Lussier, Yves A.
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (60971099, 60671018 and 60771024), Center for Multilevel Analyses of Genomic and Cellular Networks (1U54CA121852-01A1), and the Cancer Research Foundation. We thank WALTS Adrienne for her contribution to editing. We also thank XIE Jianming for contributive discussion on the biological impact.
PY - 2010/11
Y1 - 2010/11
N2 - 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 biomodules common to distinct cancers of the same tissue. These biomodules also comprise novel microRNA and genes as well as an imputed regulatory network, which may accelerate the work of cancer biologists as large regulatory maps of cancers can be drawn efficiently for hypothesis generation.
AB - 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 biomodules common to distinct cancers of the same tissue. These biomodules also comprise novel microRNA and genes as well as an imputed regulatory network, which may accelerate the work of cancer biologists as large regulatory maps of cancers can be drawn efficiently for hypothesis generation.
KW - biomodule
KW - cancer
KW - gene expression
KW - microRNA expression
KW - molecular diagnosis
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U2 - 10.1007/s11434-010-4051-1
DO - 10.1007/s11434-010-4051-1
M3 - Article
AN - SCOPUS:78349303386
SN - 1001-6538
VL - 55
SP - 3576
EP - 3589
JO - Chinese Science Bulletin
JF - Chinese Science Bulletin
IS - 31
ER -