Identifying mRNA targets of microRNA dysregulated in cancer: with application to clear cell Renal Cell Carcinoma
1 BioMaPS Institute, Rutgers University, Piscataway, NJ 08854, USA
2 Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
3 Broad Institute of MIT and Harvard, 7 Cambridge Center, MA, 02142, USA
4 Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ 08903, USA
5 Department of Pathology, Boston University Medical School, Boston, MA 02118, USA
6 Cambridge Health Alliance, Harvard Medical School, Cambridge MA 02139, USA
7 Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ 08540, USA
8 Departments of Medicine and Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
9 Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ 08854, USA
10 Department of Physics, Rutgers University, Piscataway, NJ 08854, USA
11 Current address: Bioinformatics, Centocor R&D Inc, 145 King of Prussia Road, Radnor, PA 19087, USA
BMC Systems Biology 2010, 4:51 doi:10.1186/1752-0509-4-51Published: 27 April 2010
MicroRNA regulate mRNA levels in a tissue specific way, either by inducing degradation of the transcript or by inhibiting translation or transcription. Putative mRNA targets of microRNA identified from seed sequence matches are available in many databases. However, such matches have a high false positive rate and cannot identify tissue specificity of regulation.
We describe a simple method to identify direct mRNA targets of microRNA dysregulated in cancers from expression level measurements in patient matched tumor/normal samples. The word "direct" is used here in a strict sense to: a) represent mRNA which have an exact seed sequence match to the microRNA in their 3'UTR, b) the seed sequence match is strictly conserved across mouse, human, rat and dog genomes, c) the mRNA and microRNA expression levels can distinguish tumor from normal with high significance and d) the microRNA/mRNA expression levels are strongly and significantly anti-correlated in tumor and/or normal samples. We apply and validate the method using clear cell Renal Cell Carcinoma (ccRCC) and matched normal kidney samples, limiting our analysis to mRNA targets which undergo degradation of the mRNA transcript because of a perfect seed sequence match. Dysregulated microRNA and mRNA are first identified by comparing their expression levels in tumor vs normal samples. Putative dysregulated microRNA/mRNA pairs are identified from these using seed sequence matches, requiring that the seed sequence be conserved in human/dog/rat/mouse genomes. These are further pruned by requiring a strong anti-correlation signature in tumor and/or normal samples. The method revealed many new regulations in ccRCC. For instance, loss of miR-149, miR-200c and mir-141 causes gain of function of oncogenes (KCNMA1, LOX), VEGFA and SEMA6A respectively and increased levels of miR-142-3p, miR-185, mir-34a, miR-224, miR-21 cause loss of function of tumor suppressors LRRC2, PTPN13, SFRP1, ERBB4, and (SLC12A1, TCF21) respectively. We also found strong anti-correlation between VEGFA and the miR-200 family of microRNA: miR-200a*, 200b, 200c and miR-141. Several identified microRNA/mRNA pairs were validated on an independent set of matched ccRCC/normal samples. The regulation of SEMA6A by miR-141 was verified by a transfection assay.
We describe a simple and reliable method to identify direct gene targets of microRNA in any cancer. The constraints we impose (strong dysregulation signature for microRNA and mRNA levels between tumor/normal samples, evolutionary conservation of seed sequence and strong anti-correlation of expression levels) remove spurious matches and identify a subset of robust, tissue specific, functional mRNA targets of dysregulated microRNA.