Nongenic cancer-risk SNPs affect oncogenes, tumour-suppressor genes, and immune function

Maud Fagny,Xihong Lin,Marieke Lydia Kuijjer,John Platig,John Quackenbush

doi:10.1038/s41416-019-0614-3

Abstract

BackgroundGenome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. However, how these SNPs affect cancer risk is still largely unknown.MethodsWe used a systems biology approach to analyse the regulatory role of cancer-risk SNPs in thirteen tissues. By using data from the Genotype-Tissue Expression (GTEx) project, we performed an expression quantitative trait locus (eQTL) analysis. We represented both significant cis- and trans-eQTLs as edges in tissue-specific eQTL bipartite networks.ResultsEach tissue-specific eQTL network is organised into communities that group sets of SNPs and functionally related genes. When mapping cancer-risk SNPs to these networks, we find that in each tissue, these SNPs are significantly overrepresented in communities enriched for immune response processes, as well as tissue-specific functions. Moreover, cancer-risk SNPs are more likely to be ‘cores’ of their communities, influencing the expression of many genes within the same biological processes. Finally, cancer-risk SNPs preferentially target oncogenes and tumour-suppressor genes, suggesting that they may alter the expression of these key cancer genes.ConclusionsThis approach provides a new way of understanding genetic effects on cancer risk and provides a biological context for interpreting the results of GWAS cancer studies.

Highlights

Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer
Cancer-risk SNPs are located in noncoding regions We defined a set of cancer-risk SNPs based on the NHGRI-EBI GWAS catalogue; we extracted a set of 872 SNPs from 565 independent linkage disequilibrium (LD) blocks associated with 135 unique traits and disease terms related to cancers, representing 41 cancer types
As observed for other traits and diseases,[32] we found that only 9.7% of cancer-risk SNPs were exonic or splice variant SNPs, 40% were intronic and the rest was annotated as ‘regulatory variant’ or ‘intergenic.’ The lack of a clear known biological function based on SNP location suggests that many of the remaining 91.3% may play a regulatory role

Summary

Introduction

Genome-wide association studies (GWASes) have identified many noncoding germline single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of developing cancer. Cancers often result from somatic mutations in oncogenes and tumour suppressors, which frequently arise due to environmental exposures such as UV light, tobacco, smoke or carcinogenic chemicals.[1,2,3] Hereditary cancers represent between 5 and 10% of all cancers and are characterised by a family history of the disease, a younger than usual age of onset and a higher likelihood of primary cancers in multiple organs They are often associated with germline alterations in oncogenes or tumour-suppressor genes.[4] But beyond these obvious cancer ‘drivers,’ it is widely recognised that other genetic factors play a role in cancer development and progression. Many SNPs identified through GWASes fall into nongenic regions, making it difficult to interpret their biological role in disease development, progression and response to therapy.[5]

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Conclusion