Large-scale single nucleotide polymorphism analysis of candidates for low-penetrance breast cancer genes

BRCA1 and BRCA2 are high-penetrance genes that account for around 25% of families with hereditary breast cancer [1]. Given that no additional high-penetrance susceptibility genes have been found to be involved in breast cancer, it has been proposed that different genetic backgrounds due to the combination of low-penetrance genes (polygenic mechanism) could explain the remaining familial breast cancer risk [2]. Hence there is much interest in the search for low-penetrance gene/variants for breast cancer, which exist with high prevalence in the general population.

Single nucleotide polymorphisms (SNPs) have emerged as genetic markers of choice because of their high density and relatively even distribution in the human genomes [3, 4], and are being using for fine mapping of disease loci and for candidate gene association studies. Approximately 10 million SNPs have been identified across the human genome and new technologies are available today for high-throughput genotyping.

In this study we used the SNPlex^™ (Applied Biosystems, Foster City, CA, USA) high-throughput genotyping platform, which allows the study of up to 48 SNPs simultaneously, to study 984 SNPs of 92 cancer-related genes, in a total of 480 female cases of breast cancer and 480 female controls.

Gene selection was made on the basis of their involvement in different cancer pathways and genes: DNA reparation, cell cycle control, BRCA1-associated binding proteins, and so on. SNP selection was performed using an indirect approach (1 SNP/10 kb) and based on the individual allele frequency (FAM ≤ 10%) in the European population, using public and private SNP databases and bioinformatics tools (dbSNP, HapMap, Sequenom Real SNP, PUPASNPI Ensembl, and Celera, among others).

To date, 415 SNPs from 44 genes have been genotyped in nine SNPlex pools. A case–control analysis was conducted for the 318 remaining SNPs. Preliminary results showed association in 24 SNPs from 12 candidate genes (P < 0.05). We will present the analysis of the remaining 48 genes at the time of the congress.