micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information on the biological state of the cell and, hence, of the function of the expressed miRNAs (1). The Peterlab compared the large amount of available gene array data on the steady state system of the NCI60 cell lines to two different data sets containing information on the expression of 583 individual miRNAs. In addition, they have generated custom data sets containing expression information of 54 miRNA families sharing the same seed match. A novel strategy was developed for correlating miRNAs with individual genes based on a summed Pearson Correlation Coefficient (sPCC) that mimics an in silico titration experiment. By focusing on the genes that correlate with the expression of miRNAs without necessarily being direct targets of miRNAs, miRNAs were clustered into different functional groups. This has resulted in the identification of three novel miRNAs that are linked to the epithelial-to-mesenchymal transition (EMT) in addition to the known EMT regulators of the miR-200 miRNA family which was previously identified by the Peterlab as a key regulator of epithelial-to-mesenchymal transition (EMT) (2). An analysis of gene signatures associated with EMT, c-MYC activity, and ribosomal protein gene expression allowed to assign different activities to each of the functional clusters of miRNAs (3). All correlation data are available via a web interface that allows investigators to identify genes whose expression correlates with the expression of single miRNAs or entire miRNA families. miRConnect.org can aid in identifying pathways regulated by miRNAs without requiring specific knowledge of miRNA targets.
More recently the Peterlab has extended this analysis to three primary human cancers (ovarian cancer, glioblastoma multiforme, and kidney renal clear cell carcinoma) available at the Cancer Genome Atlas (TCGA), and has correlated the expression of the clustered miRNAs with 158 oncogenic signatures (miRConnect 2.0) (4). This resulted in the identification of functionally antagonistic groups of miRNAs. One group (the agonists), which contains many of the members of the miR-17 family, correlated with c-Myc induced genes and E2F gene signatures. A group that was directly antagonistic to the agonists in all three primary cancers contains miR-221 and miR-222. Since both miR-17 ~ 92 and miR-221/222 are considered to be oncogenic this points to a functional antagonism of different oncogenic miRNAs. Analysis of patient data revealed that in certain patients agonistic miRNAs predominated, whereas in other patients antagonists predominated. In glioblastoma a high ratio of miR-17 to miR-221/222 was predictive of better overall survival suggesting that high miR-221/222 expression is more adverse for patients than high miR-17 expression. miRConnect 2.0 is useful for identifying activities of miRNAs that are relevant to primary cancers. The new correlation data on miRNAs and mRNAs deregulated in three primary cancers are also available at miRConnect.org.
- Schickel, R., Boyerinas, B., Park, S.-M. and Peter, M.E. (2008) MicroRNAs: keyplayers in the immune system, differentiation, tumorigenesis and cell death. Oncogene, 27, 5959-5974.
- Park, S.-M., Gaur, A.B., Lengyel, E. and Peter, M.E. (2008) The miR-200 family determines the epithelial phenotype of cancer cells by targeting the E-cadherin repressors, ZEB1 and ZEB2. Genes Dev. 22, 894-907 .
Press release by Cold Spring Harbor Press on March 31, 2008: "MicroRNAs, EMT and Cancer Progression".
N&V in Nature Cell Biology, May 2008, "miRNAs - keeping cells in formation".
Literature Report in EMBO Reports, online May 16, 2008: "A new regulatory loop in cancer-cell invasion".
Selected Summary in Gastroenterology: "The miR-200 family: Central player for gain and loss of the epithelial phenotype"
- Hua, Y.J., Duan, S., Murmann, A.E., Larsen, N., Kjems, J., Lund, A.H. and Peter, M.E. (2011) miRConnect: identifying effector genes of miRNAs and miRNA families. PLoS ONE, 6, e26521.
- Hua, Y.J., Larsen, N., Kalyana-Sundaram, S., Kjems, J., Chinnayan, A.M. and Peter, M.E. (2013) miRConnect 2.0: Identification of antagonistic, oncogenic miRNA families in three human cancers. BMC Genomics, 14, 179.
Looking for more information? View the miRConnect Website.