The germ-line genetic variants identified thus far generally explain only part of the predicted genetic risk for most cancers, including renal cell carcinoma (RCC). A component of the remaining risk may be explained by functionally consequent genetic variants that are individually very rare (or private). The contribution that thi spectrum of genetic variation makes to susceptibility to RCC remains unexplored. Strategies that allow for agnostic, genome-wide assessment of such variants are likely to require very important sample sizes for adequate statistical power. In addition to the large cost, such study approaches may not be practical for rare cancers due to the lack of sufficiently large bio-repositories. Unusual frequencies of "two-hit" mutation events (one mutation in the germ-line, and a second, somatic mutation in the same individual) may be able to map genes involved in RCC cancer susceptibility. Within the exceptional IARC RCC bio-repository, we propose to use this "two-hit mapping" approach in a discovery and replication study design to identify genes involved in genetic susceptibility to RCC acting via Knudson's two hit model.
A component of genetic susceptibility to renal cell carcinoma (RCC) may be explained by functionally consequent genetic variants that have very rare population frequencies (or are even private to that person and their family). As each such variant is very rare, but most people carry a large number within their genome, sample sizes in the order of many thousands may be needed to identify rare variants involved in disease susceptibility. In addition to the large study cost, assembling such sample sizes for a rarer cancer like RCC may prove challenging. Within this application, rather than focusing solely on germ-line events, we propose to use the events that occur in the tumor in combination with the constitutional genetic variants to detect and validate RCC susceptibility genes.