Abstract
Constitutional copy number variants (CNVs) include inherited and de novo deviations from a diploid state at a defined genomic region. These variants contribute significantly to genetic variation and disease in humans, including breast cancer susceptibility. Identification of genetic risk factors for breast cancer in recent years has been dominated by the use of genome-wide technologies, such as single nucleotide polymorphism (SNP)-arrays, with a significant focus on single nucleotide variants. To date, these large datasets have been underutilised for generating genome-wide CNV profiles despite offering a massive resource for assessing the contribution of these structural variants to breast cancer risk. Technical challenges remain in determining the location and distribution of CNVs across the human genome due to the accuracy of computational prediction algorithms and resolution of the array data. Moreover, better methods are required for interpreting the functional effect of newly discovered CNVs. In this review, we explore current and future application of SNP array technology to assess rare and common CNVs in association with breast cancer risk in humans.
Highlights
Over the past decade there have been a large number of studies that have explored the biological impact of constitutional copy number variants (CNVs) in the human genome [1,2]
CNVs have been reported to encompass genes known to be involved in breast cancer susceptibility, including BRCA1 and BRCA2, and may affect other genes involved in breast cancer-related pathways [12]
There is a wealth of array data available from single nucleotide polymorphism (SNP)-based genome-wide association studies that can be utilised for assessing the contribution of CNVs to breast cancer risk
Summary
Over the past decade there have been a large number of studies that have explored the biological impact of constitutional (inherited and de novo) copy number variants (CNVs) in the human genome [1,2]. Gene-Environment Study (COGS) used a custom-designed array to assess almost 200,000 SNPs across the genome in approximately 50,000 breast cancer cases and 50,000 controls [28] Studies of this size are statistically powered to evaluate variants with a minor allele frequency 92% and specificity >87% An exception to these results was the ability of QuantiSNP to accurately call homozygous and heterozygous deletions, with call rates of 68% and 62%, respectively). CNAT, CNVPartition, GADA, Nexus, PennCNV and cnvHap, CNVPartition, PennCNV and PennCNV, Aroma.Affymetrix, APT and CRLMM
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