Functional analysis of genetic variants associated with risk for breast cancer: 12q24, a candidate risk locus

• Autor(a) principal: Silva, Joceline Janice Correia
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.1/10019
• topic: Cancro da mama; Suscetibilidade; Polimorfismos de nucleóticos únicos; Variantes cis-reguladoras; Expressão alélica diferencial

Common risk alleles identified through Genome-Wide Association Studies (GWAS) explain about 14% of familial breast cancer cases. However, GWAS do not identify causative variants in the risk loci and do not contribute to the understanding of risk mechanisms. All of the risk loci functionally analysed to date are cis-regulatory, i.e. polymorphisms that modify gene expression. Therefore, we hypothesize that cis-regulation is a central mechanism in breast cancer susceptibility. Differential allelic expression (DAE) is the most robust method to identify the effect of cis-regulatory single nucleotide polymorphisms (SNPs). Our group established a whole-genome DAE map for normal breast tissue, which we integrated with the GWAS data, to identify risk loci with greater potential to be cis-regulatory. We identified 111 loci, with one of them in the 12q24 locus, containing an unpublished GWAS SNP, rs7307700, and 15 DAE SNPs. We performed in silico analysis to characterize the regulatory potential of candidate cis-regulatory SNPs (rSNPs) in breast cell lines, and in vitro analysis by electrophoretic mobility shift assay (EMSA) to explore interactions between candidate rSNPs and candidate transcription factors (TFs). Three candidate rSNPs, rs10773145, rs10846834 and rs12302714, overlapped regulatory elements and DNase I hypersensitivity sites, and were associated with the DAE observed for two transcribed SNPs (or DAE SNPs), rs7301263 and rs12581512. The candidate SNPs rs10773145 and rs10846834 were both located within known c-FOS and STAT3 binding sites, but showed small allelic differences in the ChIP-seq data. Since there was no ChIP-seq data for rs12302714, we carried EMSA analysis. Although we detected DNA-protein binding for both alleles of this SNP, no allelic differences were detected. We also analysed candidate SNPs for microRNA binding and the results suggested that a microRNA have preferentially binding to the alleles of candidate rSNP rs12302714. These results indicate that the DAE observed might not be explained by differential binding of TFs at the three candidate rSNPs and might be due to other regulatory mechanisms, that require further exploration, such as splicing and microRNAs.