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. 2010 Apr 1;70(7):2789-98.
doi: 10.1158/0008-5472.CAN-09-3541. Epub 2010 Mar 23.

Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility

Affiliations

Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility

Milena S Nicoloso et al. Cancer Res. .

Abstract

Single-nucleotide polymorphisms (SNP) associated with polygenetic disorders, such as breast cancer (BC), can create, destroy, or modify microRNA (miRNA) binding sites; however, the extent to which SNPs interfere with miRNA gene regulation and affect cancer susceptibility remains largely unknown. We hypothesize that disruption of miRNA target binding by SNPs is a widespread mechanism relevant to cancer susceptibility. To test this, we analyzed SNPs known to be associated with BC risk, in silico and in vitro, for their ability to modify miRNA binding sites and miRNA gene regulation and referred to these as target SNPs. We identified rs1982073-TGFB1 and rs1799782-XRCC1 as target SNPs, whose alleles could modulate gene expression by differential interaction with miR-187 and miR-138, respectively. Genome-wide bioinformatics analysis predicted approximately 64% of transcribed SNPs as target SNPs that can modify (increase/decrease) the binding energy of putative miRNA::mRNA duplexes by >90%. To assess whether target SNPs are implicated in BC susceptibility, we conducted a case-control population study and observed that germline occurrence of rs799917-BRCA1 and rs334348-TGFR1 significantly varies among populations with different risks of developing BC. Luciferase activity of target SNPs, allelic variants, and protein levels in cancer cell lines with different genotypes showed differential regulation of target genes following overexpression of the two interacting miRNAs (miR-638 and miR-628-5p). Therefore, we propose that transcribed target SNPs alter miRNA gene regulation and, consequently, protein expression, contributing to the likelihood of cancer susceptibility, by a novel mechanism of subtle gene regulation.

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Figures

Fig. 1
Fig. 1. Genome-wide identification of miRNA::target SNPs interactions
Schematic overview of the integrated bioinformatics strategy used for miRNA and SNP interaction analyses. The 8% MFE absolute change corresponds to the 20 and 80 percentile threshold values obtained form the MFE change distributions (Supplemental Fig. S2).
Fig. 2
Fig. 2. BC-associated target SNPs affect miRNA gene regulation
(a) miRanda predictions. # indicates that no specific miRNA::SNP interaction was found with default thresholds (MFE< −16, score >80). (b) Schematic representation of luciferase reporter constructs containing target SNP inside the miRNA binding site and their effect on miRNA interaction. (c) Top, for the selected SNPs the miRNA::mRNA interaction is shown with the active alleles (green) or the NON-active alleles (red) highlighted. Bottom, luciferase activity for pGL3-SNP constructs of BC-associated SNP co-transfected with the predicted interacting miRNA or the scrambled negative control (=1); values represent the average +/− standard deviation of 3 to 5 independent experiments performed in six replicates. (d) WB for TGFB1 (left) and XRCC1 (right) after miR-187 and miR-138 transfection respectively, in cell lines carrying different rs1982073-TGFB1 and rs1799782-XRCC1 variants. Genotypes are reported on the top of the immunoblots; below are reported TGFB1 and XRCC1 expression levels normalized for Vinculin protein levels and compared to the scrambled negative control transfection (=1) per each cell line.
Fig. 3
Fig. 3. Validation of target SNP predictions
(a) Top, for the two SNPs the miRNA::mRNA interaction is shown with the active alleles (green) or the NON-active alleles (red) highlighted. Bottom, luciferase reporter assay for pGL3-SNP allelic pairs co-transfected with the predicted interacting miRNA, rs799917-BRCA1::miR-638 (left panel) and rs334348-TGFBR1::miR-628-5p (right panel). Luciferase activity is expressed relative to scrambled negative control (=1); values represent the average +/− standard deviation of at least 3 independent experiments performed in six replicates. Also shown are miRNA::mRNA interactions according to miRanda predictions, with the active alleles (green) or the NON-active alleles (red) highlighted. (b) WB for BRCA1 (left panels) and TGFBR1 (right panels) after miR-638 and miR-628-5p transfection respectively, in cell lines carrying different rs799917-BRCA1 or rs334348-TGFBR1 variants. Genotypes are reported on the top of the immunoblots; below are reported BRCA1 and TGFBR1 expression levels normalized for Vinculin protein levels and compared to the scrambled negative control transfection (=1) per each cell line. (c) Average of BRCA1 and TGFBR1 protein reduction (left and right panel, respectively) in all cells analyzed after miRNA transfection compared to scrambled native control (=1) per each genotype.

References

    1. Filipowicz W, Bhattacharyya SN, Sonenberg N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat Rev Genet. 2008;9:102–14. - PubMed
    1. Miranda KC, Huynh T, Tay Y, et al. A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell 22. 2006;126:1203–17. - PubMed
    1. Tay Y, Zhang J, Thomson AM, Lim B, Rigoutsos I. MicroRNAs to Nanog, Oct4 and Sox2 coding regions modulate embryonic stem cell differentiation. Nature. 2008;455:1124–8. - PubMed
    1. Spizzo R, Nicoloso MS, Croce CM, Calin GA. SnapShot: MicroRNAs in Cancer. Cell. 2009;137:586e1. - PubMed
    1. Pharoah PD, Dunning AM, Ponder BA, Easton DF. Association studies for finding cancer-susceptibility genetic variants. Nat Rev Cancer. 2004;4:850–60. - PubMed

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