Identifying metastatic signatures, including TP53, with a new miRNA-target profiling analysis method
Inhan Lee, Won-Mean Lee, and James W. Proscia - miRcore, Ann Arbor, MI 48105, USA
Kwanbok Lee and Yong Sun Lee - Department of Biochemistry & Molecular Biology, University of Texas, Galveston, TX 77555, USA
We have identified a new microRNA (miRNA) target class, miBridge, in which the 5'- and 3'-end of a miRNA can simultaneously interact with the 3'-UTR and 5'-UTR of a single gene. In addition to confirming the existence of such targets in the recent PAR-CLIP sequencing data, we have developed a method to extract new genetic signatures from genome-wide miRNA-mRNA or miRNA-protein profiling data using miBridge target prediction. Since this method is independent of previous knowledge, we can provide hypothesis-free genetic signatures consisting of miRNA and its targets. As the majority of miRNA functions are still unknown, these signatures can potentially reveal novel and significant relations.
We used our method to identify metastatic signatures among miRNA, mRNA, and protein profiling data from NCI60 cell lines, comparing the expression patterns of nine metastatic cancer cell lines with 50 non-metastatic cancer cell lines. Through our analysis of mRNA and miRNA profiles, a total 4 miRNAs and 3 coding genes were identified as signatures, among them miR-200a and c, well-known metastasis-related miRNAs (low miR-200 can lead to EMT). All identified miRNA-target pairs were validated with luciferase assay. When we analyzed miRNA-protein profiles together, 6 miRNAs and 4 proteins were identified, again including miR-200c, further confirming the validity of our method (no coding genes identified from the miRNA-mRNA analysis were included in the original protein profiles). Interestingly, TP53 was among the 4 proteins, its level being significantly lower in metastatic cell lines though its mRNA level was not. This discrepancy between TP53`s mRNA and protein levels may reflect a miRNA function in metastasis.