Single nucleotide polymorphism array analysis of cancer

Abstract

Classifying tumors and identifying therapeutic targets requires a description of the genetic changes underlying cancer. Single nucleotide polymorphism (SNP) arrays provide a high-resolution platform for describing several types of genetic changes simultaneously. With the resolution of these arrays increasing exponentially, they are becoming increasingly powerful tools for describing the genetic events underlying cancer. The ability to map loss of heterozygosity (LOH) and overall copy number variations using SNP arrays is known. Techniques have recently been developed to map LOH at high resolution in the absence of paired normal data. Copy number variations described by SNP array studies are now reaching resolutions enabling the identification of novel oncogenes and tumor suppressor genes. The ability to determine allele-specific copy number changes has only recently been described. Moreover, SNP arrays offer a high-throughput platform for large-scale association studies that are likely to lead to the identification of multiple germline variants that predispose to cancer. SNP arrays are an ideal platform for identifying both somatic and germline genetic variants that lead to cancer. They provide a basis for DNA-based cancer classification and help to define the genes being modulated, improving understanding of cancer genesis and potential therapeutic targets.