Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression and drug response

Ping Zhang, Isaac Kitchen-Smith, Lingyun Xiong, Giovanni Stracquadanio, Katherine Brown, Philipp Richter, Marsha Wallace, Elisabeth Bond, Natasha Sahgal, Samantha Moore, Svanhild Nornes, Sarah De Val, Mirvat Surakhy, David Sims, Xuting Wang, Douglas A Bell, Jorge Zeron-Medina, Yanyan Jiang, Anderson Ryan, Joanna SelfeJanet Shipley, Siddhartha Kar, Paul Pharoah, Chey Loveday, Rick Jansen, Lukasz F Grochola, Claire Palles, Andrew Protheroe, Val Millar, Daniel Ebner, Meghana Pagadala, Sarah P. Blagden, Tim Maughan, Enric Domingo, Ian P.M. Tomlinson, Clare Turnbull, Hannah Carter, Gareth L Bond

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Insights into oncogenesis derived from cancer susceptibility loci (single nucleotide polymorphisms, SNPs) could 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 p53 mutational status to modify cancer risk, progression and response to therapy. First, we provide supportive evidence for this hypothesis by focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity, and by integrating germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation. We go on to demonstrate that through the integration of germline and somatic genetic data, we can identify a novel entry point for therapeutically manipulating p53 activities. We provide evidence that a cluster of cancer risk SNPs result in increased expression of a pro-survival p53 target gene (KITLG) and attenuation of p53-mediated responses to genotoxic therapies, which can be reversed by pharmacological inhibition of the pro-survival cKIT 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.
Original languageEnglish
JournalCancer Research
Publication statusPublished - 8 Feb 2021


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