Effects of BRCA2 cis-regulation in normal breast and cancer risk amongst BRCA2 mutation carriers

Abstract

Introduction: Cis-acting regulatory single nucleotide polymorphisms (SNPs) at specific loci may modulate penetrance of germline mutations at the same loci by introducing different levels of expression of the wild-type allele. We have previously reported that BRCA2 shows differential allelic expression and we hypothesize that the known variable penetrance of BRCA2 mutations might be associated with this mechanism.

Methods: We combined haplotype analysis and differential allelic expression of BRCA2 in breast tissue to identify expression haplotypes and candidate cis-regulatory variants. These candidate variants underwent selection based on in silico predictions for regulatory potential and disruption of transcription factor binding, and were functionally analyzed in vitro and in vivo in normal and breast cancer cell lines. SNPs tagging the expression haplotypes were correlated with the total expression of several genes in breast tissue measured by Taqman and microarray technologies. The effect of the expression haplotypes on breast cancer risk in BRCA2 mutation carriers was investigated in 2,754 carriers.

Results: We identified common haplotypes associated with differences in the levels of BRCA2 expression in human breast cells. We characterized three cis-regulatory SNPs located at the promoter and two intronic regulatory elements which affect the binding of the transcription factors C/EBPα, HMGA1, D-binding protein (DBP) and ZF5. We showed that the expression haplotypes also correlated with changes in the expression of other genes in normal breast. Furthermore, there was suggestive evidence that the minor allele of SNP rs4942440, which is associated with higher BRCA2 expression, is also associated with a reduced risk of breast cancer (per-allele hazard ratio (HR) = 0.85, 95% confidence interval (CI) = 0.72 to 1.00, P-trend = 0.048).

Conclusions: Our work provides further insights into the role of cis-regulatory variation in the penetrance of disease-causing mutations. We identified small-effect genetic variants associated with allelic expression differences in BRCA2 which could possibly affect the risk in mutation carriers through altering expression levels of the wild-type allele.

Figure 1

Differential allelic expression association with BRCA2 haplotypes in blood and breast. Fold difference between the G and the T allele for samples heterozygous for rs144848. 'Low-Expression Haplotypes' are significantly associated with differential allelic expression and correspond to haplotypes 2 and 5, and 'High-Expression Haplotypes are not associated with differential allelic expression and correspond to haplotypes 3 and 4.

Figure 2

Differential gene expression analysis in normal breast tissue (controls and breast cancer patients) and normal blood samples. Box plots displaying differentially expressed genes in normal breast samples from healthy controls (n = 29), matched normal breast tissue from breast cancer patients (n = 144) and blood samples from healthy individuals (n = 20) analyzed by Illumina HT12 v3 arrays and real-time PCR. (A) Gene expression versus genotype correlations between the genes SPP1, PAX8, MUC16 and IGFBP5 and two SNPs associated with higher expression of BRCA2, rs206081 (haplotype 3) and rs4942448 (haplotype 4), and one SNP associated with lower expression of BRCA2, rs9567578 (haplotype 2); P-values correspond to ANOVA testing. (B) Gene expression versus expression haplotype correlations for the genes MUC16 and SPP1; P-values correspond to a two-sided Student's t-Test. ANOVA, analysis of variance; PCR, polymerase chain reaction; SNP, single nucleotide polymorphism.

Figure 3

In silico and in vitro DNA-protein binding studies. EMSA results, binding sequence motifs for each transcription factor and the DNA sequence around each SNP (alleles in red) are shown. Sequences are shown in the strand direction for which the prediction was found, and red underlines indicate homology between TF motif and allele sequence. DNA motifs were obtained from TRANSFAC and Schmidt et al. (C/EBPα) [12,50]. Arrows indicate specific bands for each EMSA. (A) Both alleles of rs1799943 show weak in vitro binding of C/EBPα. (B) Analysis of rs9567576, using cell extract from two cell lines as indicated, and competition assays indicate stronger binding of HMGA1 to the probe containing the T allele. (C) EMSA analysis of rs4942485 for the A allele (upper panel) and G allele (lower panel). The A allele shows strong binding to DBP, as identified by competition assays. When using the probe containing the G allele, a lower third band appears in the presence of Zn²⁺ in the buffer, identified as binding to ZF5 in competition assays. EMSA, electrophoretic mobility shift assay; DBP, d-binding protein; SNP, single nucleotide polymorphism; TF, transcription factors.

Figure 4

In vivo analysis of transcription factor occupancy at cis-regulatory sites. The data show occupancy fold enrichment compared to chromatin input, and corrected against a negative control. The genotype of the cell lines used for each experiment is shown in the legend. (A) PCR analysis for ChIP of OCT-1 and C/EBPα at the rs1799943 site. (B) PCR analysis for ChIP of HMGA1 at the rs9567576 site. Sequencing chromatograms showing preferential pull-down of T allele in the immunoprecipitate in comparison with input chromatin in a heterozygous cell line. (C) PCR analysis for ChIP of DBP and ZF5 at the rs4942485 site. The data are the average of three replicates ± SD in two different cell lines. ChIP, chromatin immunoprecipitation; DBP, d-binding protein; PCR, polymerase chain reaction; SD, standard deviation.

Figure 5

Complex cis-regulation of BRCA2 gene expression. RefSeq genes mapped to the region surrounding BRCA2, position of regulatory features according to Ensembl, and position of DAE marker SNP rs144848 (black star) and functional SNPs (numbered). Haplotypes associated with low and high expression levels are shown with the corresponding binding of transcription factors. Linkage disequilibrium (r²) for CEU phased genotype data from HapMap (Data release24/phaseII). CEU, Utah residents with Northern and Western European ancestry from the CEPH collection; SNP, single nucleotide polymorphism.