Supplementary Methods; Supplementary Figures S1-S5

Background The advent of functional genomic techniques and next generation sequencing has improved the characterization of the non-protein coding regions of the genome. However, the integration of these data into clinical practice is still in its infancy. Fifty percent of cancers mutate TP53 , which promotes tumorigenesis, in part, by inhibiting its ability to bind to non-coding regions of the genome and function as a sequence-specific transcription factor. P53 is a tumour suppressor that inhibits cell survival through regulating transcription of anti-survival genes. However, p53 also regulates transcription of pro-survival genes and the target gene(s) responsible for p53 tumour suppression remains an open topic of research.Methods In this study, we integrate detailed genome-wide maps of p53 responsive elements (p53-RE), p53 occupancy, recently defined candidate cis-Regulatory Elements (cCREs) and whole genome sequencing for cancers to better define the regions of the genome that harbour functional p53 enhancers.Results We determine that p53-REs are more likely to be closer to the consensus binding site, to be evolutionarily conserved and to be occupied by p53 in cellulo , when they reside in regions of the genome that have been noted to have accessible DNA and a regulatory epigenomic mark in at least one human cell even without obvious p53 activation signals (cCRE p53-REs). We offer evidence that it is only in cCRE p53-REs, where multiple signs of differential natural selection between pro-survival and anti-survival target genes can be noted. Using whole genome sequences of 38,377 individuals, we go on to demonstrate that carriers of rare germline mutations in cCRE p53-REs can have similar traits to carriers of rare p53 coding mutations that cause the Li-Fraumeni cancer predisposition syndrome.Conclusions Together, these observations suggest that functional p53 enhancers are enriched in cCREs and that germline mutations in them have the potential to improve current cancer risk management and screening strategies.### Competing Interest StatementThe authors have declared no competing interest.### Funding StatementFunding for GLB for this work was provided by the Ludwig Institute for Cancer Research and University of Birmingham. PZ was funded in part by the Ludwig Institue for Cancer Research. DB was funded by the University of Birmingham. This research was made possible through access to the data and findings generated by the 100,000 Genomes Project. AMF and NP are supported by the National Institute for Health Research, UCLH Biomedical Research Centre and the UCL Experimental Cancer Centre. SDN holds a Jean Shanks Foundation - Pathological Society Clinical PhD Fellowship. PVL was supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001202), the UK Medical Research Council (FC001202), and the Wellcome Trust (FC001202).### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Genomics England 100K genomes projectI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll datasets used in this study are publicly available, with details included in the manuscript and supplementary information. All data produced in the present study are available upon request.

Abstract Insights into oncogenesis derived from cancer susceptibility loci (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, although 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 prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival 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. Significance: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.

Background Height and other anthropometric measures are consistently found to associate with differential cancer risk. However, both genetic and mechanistic insights into these epidemiological associations are notably lacking. Conversely, inherited genetic variants in tumour suppressors and oncogenes increase cancer risk, but little is known about their influence on anthropometric traits. Methods By integrating inherited and somatic cancer genetic data from the Genome-Wide Association Study Catalog, expression Quantitative Trait Loci databases and the Cancer Gene Census, we identify SNPs that associate with different cancer types and differential gene expression in at least one tissue type, and explore the potential pleiotropic associations of these SNPs with anthropometric traits through SNP-wise association in a cohort of 500,000 individuals. Results We identify three regulatory SNPs for three important cancer genes, FANCA, MAP3K1 and TP53 that associate with both anthropometric traits and cancer risk. Of particular interest, we identify a previously unrecognised strong association between the rs78378222[C] SNP in the 3' untranslated region (3'-UTR) of TP53 and both increased risk for developing non-melanomatous skin cancer (OR=1.36 (95% 1.31 to 1.41), adjusted p=7.62E −63 ), brain malignancy (OR=3.12 (2.22 to 4.37), adjusted p=1.43E −12 ) and increased standing height (adjusted p=2.18E −24 , beta=0.073±0.007), lean body mass (adjusted p=8.34E −37 , beta=0.073±0.005) and basal metabolic rate (adjusted p=1.13E −31 , beta=0.076±0.006), thus offering a novel genetic link between these anthropometric traits and cancer risk. Conclusion Our results clearly demonstrate that heritable variants in key cancer genes can associate with both differential cancer risk and anthropometric traits in the general population, thereby lending support for a genetic basis for linking these human phenotypes.