Hard Work Ahead: Fine Mapping and Functional Follow-up of Susceptibility Alleles in Cancer GWAS

Abstract

Genome-wide association studies (GWAS) in cancer have successfully identified over 450 regions that harbor susceptibility alleles with small effects contributing to the risk of one or more cancers. Less than 10 % of the regions identified thus far are common to more than one cancer, but it is these regions which display pleiotropy that are especially informative and provide new opportunities to gain insights into common mechanisms of carcinogenesis. Since the GWAS age has been notable for scalability, large-scale consortia have successfully combined many studies to identify novel regions associated with risk for cancer. In fact, for common cancers, a substantial fraction of markers for common alleles have been identified, and additional studies of the cumulative “polygenic” effect of large scans further suggest that many additional alleles remain to be characterized. The emerging catalog of common variants, which represents a fraction of the underlying genetic architecture of cancer susceptibility, already constitutes a set for common cancers that could be used in stratification and public health measures. On the other hand, the discovery of many regions is occurring at a rate that exceeds our capacity to understand the underlying biology contributing to each risk allele. Nearly all susceptibility regions harbor one or more variants that point towards changes in the regulation of key genes and pathways and not protein coding changes resulting in “drivers” of somatic alterations. Further investigation of each region depends upon the sequence of fine mapping (e.g., identification of correlated variants) using in silico functional tools to nominate the most promising variants for detailed laboratory follow-up studies. Each region has to be interrogated individually, taking into account the unique features of each genomic locale in order to understand the biological underpinnings of the susceptibility variants. Building a comprehensive catalog of susceptibility alleles, across a spectrum of frequencies and effect sizes, and functional annotation of these should be instrumental in revealing new cancer biology and eventually used in precision prevention.