Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression, and drug response.
Zhang P., Kitchen-Smith I., Xiong L., Stracquadanio G., Brown K., Richter PH., Wallace MD., Bond E., Sahgal N., Moore S., Nornes S., De Val S., Surakhy M., Sims D., Wang X., Bell DA., Zeron-Medina J., Jiang Y., Ryan AJ., Selfe JL., Shipley J., Kar S., Pharoah PDP., Loveday C., Jansen R., Grochola LF., Palles C., Protheroe A., Millar V., Ebner DV., Pagadala M., Blagden SP., Maughan TS., Domingo E., Tomlinson I., Turnbull C., Carter H., Bond GL.
Insights into oncogenesis derived from cancer susceptibility loci (single nucleotide polymorphisms, SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, while both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of pro-survival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacological inhibition of the pro-survival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies.